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Surface energetics of adsorbent-biomass interactionsduring expanded bed chromatography. Implications
for process performance
by
Rami Reddy Vennapusa
A thesis submitted in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy
in Biochemical Engineering
Approved, Thesis committee
Prof. Dr. Marcelo Fernández-Lahore
Prof. Dr . Jürgen Fritz
Prof. Dr. Briger Anspach
Date of Defense: September 3, 2008
School of Engineering and Science
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II
ORIGINALITY STATEMENT
‘I hereby declare that this submission is my own work and to the best of knowledge itcontains no materials previously published or written by another researcher, or substantial proportions of material which have been accepted for the award of any other degree or diploma at Jacobs University or any other educational institutions, except where dueacknowledgement is made in the thesis. I also declare that the intellectual content of thisthesis is the product of my own work, except to the extent that assistance from my thesissupervisor in the project’s design and conception or in style, presentation and linguisticexpression is acknowledged.’
Signature …………………………….
Date ……………………..
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III
Abstract
Common limitations encountered during the direct recovery of bioproducts from an
unclarified feedstock are related to the presence of biomass in such processing systems.
Biomass related effects can be described as biomass-to-support interaction and cell-to-cell
aggregation. In the current thesis work biomass related effects were studied in an important
integrated primary unit operation mode viz Expanded bed adsorption (EBA), which was
proved to suffer from the detrimental effects by the presence of biomass.
Current work involves the investigation and understanding of the biomass interaction and
aggregation onto various EBA process surfaces at local or molecular level. In doing so
Streamline materialsTM of various chemistries were taken as process surface and intactyeast cell, yeast homogenates, and disrupted bacterial paste were employed as model
colloids to understand their deposition and subsequent aggregation.
Deposition and aggregation was studied with surface energetics according to XDLVO
theory. These predictions based on the application of XDLVO theory were confirmed by
independent experimental methods, like biomass deposition experiments and laser
diffraction spectroscopy.
Biomass components and beaded adsorbents were characterized by contact angle
determinations with three diagnostic liquids and zeta potential measurements.
Subsequently, free energy of interactionvs. distance profiles between interacting surfaces
was calculated in aqueous media provided by its operating mobile phase. The effect of
various chromatographic conditions based on the mode of operation was explored in
relation to yeast interaction and aggregation.
Calculations indicated that the interaction and aggregation is mainly due to the existence of
a reversible secondary energy minimum. The extent and depth of pocket varied based on
the operating process conditions for different interacting pairs.
Understanding biomass-related effects will overcome or at least mitigate the process
limitations. Exploring the effect of various types of additives for their ability to inhibit
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IV
either biomass deposition, cell aggregation, or a combination of both effects, a non ionic
polymer PVP 360 was found to alleviate biomass deposition on weak anion exchangers.
The predictions made by the XDLVO theory were well correlated with the physicochemical
parameter α, in relation to ion exchangers where only interaction is happening. On the other
hand a discrete modifications of XDLVO energies was observed with the lump parameter α
for hydrophobic and pseudo affinity process surfaces where interaction and aggregation is
taking place. Establishing a correlation defined a safe operational windows for EBA
process when U≤ |50| kT and α ≤ 0.15.
Fundamental knowledge which could predict feedstock behaviour during primary unit
operations of downstream processing would alleviate the current bottleneck during
processing of bioproducts.
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VI
Not only the academic support important to conclude a thesis but also the emotional
support especially when you are so far away from home. I would like thank Marcelo and
his family members for being to my host family and supporting emotionally during my stay
away from my home.
My most profound thanks, my most heartfelt appreciation; my deepest gratitude goes to my
family without whom none of this could have been accomplished. To my mum and dad,
thanks for your unwavering confidence in me, for your love and sacrifice and for the moral
energy. Thanks you so much for all the prayers and taking interest in my progress. Actually
I have no words to thanks my dad and mom for their enumerous moral support. Thanks to
my brothers Vasu and Kesav and their families for their love and encouragement. Deepest
appreciation to my brother Kesav a doctor by profession, who took care of my sanity during
course of my PhD. I also would like thank all my family members my grandfather, to my
memory of grandmother and my siblings for constant caring and great moral support.
Friends are every thing once you cross the sea; I have many friends back from India and
here to thank who have directly and indirectly helped during the work. Thank you
everyone.
Finally the most important one Lord God almighty. With out his blessings nothing would
have been possible today. I am infinitely grateful to my God for being my courage and
refuge. Since there are no words to thank God for taking care of me all though my current
life as heartfelt appreciation the current work is dedicated in his name.
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VII
Dedication
To Lord Sri Venkateswara SwamyTTD, Tirumala
India.
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VIII
Table of contents
ABSTRACT …………………………………………………………………. III
ACKNOWLEDGEMENTS ………………………………………………… V
1 GENERAL INTRODUCTION …………………………………………… 11
1.1 Introduction to Biotechnology ………………………………………….. 11
1.2 Downstream Processing ………………………………………………… 12
1.2.1 Process integration ………………………………………………... 13
1.2.2 Expanded bed adsorption ………………………………………… 14
1.2.3 Operating principle ………………………………………………. 15
1.3 Problem statement and Research objective ……………………………. 17
1.4 Goal of the work …………………………………………………………. 21
1.5 References ……………………………………………………………….. 23
2.0 RESULTS / ORGANIZATION OF THESIS ………………………….. 27
2.1 Assessing adsorbent-biomass interactions during expanded bed adsorption
Onto ion exchangers utilizing surface energetics ……………………… 28
2.1.1 Abstract ……………………………………………………………. 28
2.1.2 Introduction ……………………………………………………….. 29
2.1.3 Theory ……………………………………………………………… 31
2.1.4 Materials and Methods …………………………………………… 35
2.1.5 Results and discussions …………………………………………… 38
2.1.6 Conclusion …………………………………………………………. 572.1.7 Acknowledgements ………………………………………………... 58
2.1.8 Nomenclature ……………………………………………………… 59
2.19 References …………………………………………………………… 61
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IX
2.2 Colloid deposition experiments as a diagnostic tool for biomass attachment onto
bioproduct adsorbent surfaces ………………………………………….. 65
2.2.1 Abstract ……………………………………………………………… 65
2.2.2 Introduction …………………………………………………………. 66
2.2.3 Materials and Methods …………………………………………….. 69
2.2.4 Results and Discussions …………………………………………..... 72
2.2.5 Conclusion …………………………………………………………... 84
2.2.6 Acknowledgements ………………………………………………..... 85
2.2.7 Nomenclature ……………………………………………………….. 85
2.2.8 References …………………………………………………………… 87
2.3 Surface energetics to assess biomass attachment onto hydrophobic interaction
adsorbents in expanded beds ……………………………………………… 90
2.3.1 Abstract ………………………………………………………………. 90
2.3.2 Introduction …………………………………………………….......... 91
2.3.3 Materials and Methods ……………………………………………… 93
2.3.4 Results and Discussions ……………………………………………… 97
2.3.5 Conclusions …………………………………………………………… 112
2.3.6 Acknowledgements …………………………………………………… 123
2.3.7 Nomenclature …………………………………………………………. 124
2.3.8 References …………………………………………………………….. 125
2.4 Surface energetics to assess biomass attachment onto immobilized metal affinity
adsorbents in expanded beds ……………………………………………… 128
2.4.1 Abstract ……………………………………………………………..... 128
2.4.2 Introduction ………………………………………………………….. 129
2.4.3 Materials and Methods ……………………………………………… 131
2.4.4 Results and Discussions ……………………………………………... 135
2.4.5 Conclusions …………………………………………………………... 151
2.4.6 Acknowledgements …………………………………………………… 151
2.4.7 Nomenclature ………………………………………………………… 1522.4.8 References …………………………………………………………….. 153
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X
2.5 Surface energetics to assess biomass deposition onto fluidized chromatographic
supports …………………………………………………………………...... 156
2.5.1 Abstract ………………………………………………………………. 156
2.5.2 Introduction ………………………………………………………….. 157
2.5.3 Materials and Methods ……………………………………………… 159
2.5.4 Results and Discussions ……………………………………………… 163
2.5.5 Conclusions …………………………………………………………… 174
2.5.6 Acknowledgements …………………………………………………… 175
2.5.7 Nomenclature …………………………………………………………. 175
2.5.8 References …………………………………………………………….. 177
2.6 The effect of chemical additives on biomass deposition onto beaded
chromatographic supports ………………………………………………... 179
2.6.1 Abstract ………………………………………………………………. 179
2.6.2 Introduction ………………………………………………………….. 180
2.6.3 Materials and Methods ………………………………………………. 183
2.6.4 Results and Discussions ………………………………………………. 187
2.5.5 Conclusions …………………………………………………………… 2022.6.6 Acknowledgements …………………………………………………… 202
2.6.7 References …………………………………………………………… 203
3.0 GENERAL CONCLUSIONS AND REMARKS ………………………….. 207
4.0 Appendix …………………………………………………………………….. 214
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Introduction
11
1 General Introduction
1.1 Introduction to Biotechnology
Biotechnology is known to exist as such since the late 17th century. This “traditional”
biotechnology was mostly concerned with processing of food e.g. wine, beer, cheese and
other diary products. In the late 19th century a new wave in the biotechnology industry
started when complex organic molecules like antibiotics and enzymes were produced for
the first time by biosynthesis (Enfors and Häggström 2005). With the knowledge gained on
microbial physiology, biochemistry and genetics it was possible to think about genetic
manipulations of the cells during the 70’s and the so called “genetic engineering” was born.
The advances in genetic engineering led to a new era in biotechnology with products like
insulin, erythropoietin, and interferon. These biopharmaceutical products have a high
market value. In the current century, the biopharmaceutical industry in one the fastest
growing sectors in the global economy (Pavlou and Reichert 2004). Proteins constitute an
important class of biopharmaceutical products, but also have food and biotechnology
applications (Headon and Walsh 1994). Advances in the recombinant DNA and cell culture
technology have permitted the large scale production of virtually any protein by
fermentation routes at increased titers (Walsh 2006), thereby shifting the bottleneck in
biopharmaceutical process development to the purification of such bioproducts (Smith2005; Thiel 2004).
Also microbial bioprocess can be divided in main two parts: a) the fermentation step, as the
(bio) synthesizing step, and b) downstream processing, for the primary recovery and
purification of the desired product (Ref. Figure 2). Since considerable efforts were made on
the genetic manipulation of cells and on the improvement of fermentation strategies, a
considerable increase in production level was already accomplished. However, optimizeddownstream processes have to be designed for the subsequent recovery of these products so
as to match “upstream” performance.
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Introduction
12
1.2 Downstream processing
The most cost intensive component of biotech-processing is DOWNSTREAM
PROCESSING (DSP), which accounts for ≥ 50-85% of the total processing cost. Increasing
competition in biotech markets, and the development of new (niche) markets, which are possible due to the utilization of recombinant DNA technology and modern cell culture
techniques in the industry have triggered the development of novel and efficient (bio)
separation technologies (Gupta and Mattiasson 1994).
Biotechnological process fluids are generally of complex nature and contain solid
(biological) particles of various sizes, as well as solutes of various molecular masses and
chemistries (Anspach et al. 1999; Thömmes 1997). The required purity of the products inthe biotechnological industry ranges from partially purified concentrates e.g. food enzymes
to highly purified preparations e.g. purity demand≥ 99.99% in the case of therapeutic
proteins used for intravenous dosage. A direct consequence of the latter is that purification
processes comprise a relatively large number of unit operations whose complexity depends
on the final product purity required (Wheelright 1991). It is common place to observe
downstream processes having a total number of processing steps between seven and
fourteen (Bonnerjea et al. 1986; Fish and Lilly 1984; Wheelright 1991). Each additional
step or unit operation will affect the overall process economy by increasing operational cost
and process time. Additional steps will also produce a certain degree of product loss and
thus, the overall yield after a certain processing “train” will substantially decrease. For
example, assuming single step yields in the range 70-95%,≈ 60% of the product will be
lost after six processing steps (Maitra and Verma 2003) (Ref. Figure 1). Therefore, the
process economics, yield and time are interrelated and an optimum balance between them
has to be found in order to design a successful downstream process.
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Introduction
13
Figure 1: Series of steps and their yields in Downstream Processing.
1.2.1 Process Integration
Integration is the creation of link between previously separate unit operations or combining
individual steps in to one unit operation, by which product losses and process economics
can be minimized.
Process integration has been actively researched in the field of biochemical engineering
over the last decade and these efforts continue today. The reason is that “integration” could
be one of the keys for the rational, cost-effective and productive design of (bio) separation
processes. From the preceding paragraphs it is understood that increasing the processing
steps would lead to a suboptimal process.
Draeger and Chase in the year 1994 (Chase 1994) presented a novel integrated concept
based on fluidized adsorbent beads for the direct sequestration of bioproducts. Expanded
bed adsorption (EBA) was introduced as an advantageous unit operation; details are given
in following sections (McCormick 1993).
100 9585.5
72.6
61.7
46.341.6
0
20
40
60
80
100
P r o d u
c t S L
S
D I S R U P
C L A R
I F / C O N
C
C H R O
M # 1
C H R O
M # 2
G F
Individual ste
Global process
Yield (%)
Processing steps
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Introduction
15
1.2.3 Operating principle
Standard chromatographic columns (“packed beds”) are characterized by adsorbent beads
which are physically confined within the bed. On the other hand, EBA systems allow the
introduction of a crude feedstock e.g. containing biological particulates, without the danger of clogging. This is due to the fact that the particulate matter and cell or cell debris can flow
within the inter-particular space created upon the solid-liquid fluidization. EBA columns
are fed from the bottom while a movable adapter is held away from the adsorbent bead
population, thus letting the same to “expand”. As buffer is pumped from below, these beads
become not only fluidized but also classified according to their size and density. This
fluidization and classification occurs when their sedimentation velocity equals to the
upward liquid velocity (Figure 3b). To accentuate this effect commercial adsorbent beadshave been modified to include inert quartz or metal alloy cores, and beads have a defined
size/density range (StreamlineTM GE Healthcare, Uppsala, Sweden; FastLineTM Upfront,
Copenhagen, Denmark). Adsorbent beads used in EBA have a size range within 50 to 400
mm. When stable fluidization / classification occurs (“expansion”) the local mobility of the
matrix particles is reduced (Figure 4). Therefore, EBA systems mimic packed bed
chromatography in the sense of creating a number of equilibrium stages (“plates”)
alongside the column length (Hubbuch et al. 2005). EBA mode of operation is shown in
Figure 3.
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Introduction
16
a) Sedimentedbed b) Equilibration
ClassifiedFluidization
c) SampleApplication
d) Elution
+
Bio-product cell
a) Sedimentedbed b) Equilibration
ClassifiedFluidization
c) SampleApplication
d) Elutiona) Sedimented
bed b) EquilibrationClassified
Fluidization
c) SampleApplication
d) Elution
++
Bio-product cell
Figure 3: The unclarified feedstock when applied to the EBA column. The particulates and the cell debrisare supposed to move freely around the adsorbent beads and eventually leave through the top of the column.The compound of interest interacts with the beadsvia specific ligands and becomes adsorbed. Afterwards, thematrix is allowed to settle and the plunger is moved down flow. Elution can be performed either in the packed bed mode or alternatively in the expanded bed mode at decreased superficial velocity (Lihme et al. 1999).
Particle size gradient Particle density gradient
+ +
Plug flow
Particle size gradient Particle density gradient
+ +
Plug flow
Particle density gradient
+ +
Plug flow
Figure 4: The phenomenon of proper fluidization and classification during the expanded bed adsorption.
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Introduction
19
cells
Bio-product Bead
cells
Bio-product Bead
BeadBead
cells
Bio-product Bead
cells
Bio-product Bead
BeadBead
cells
Bio-product Bead
cells
Bio-product Bead
BeadBead
Figure 5: Interacting expanded system causing impaired hydrodynamics and decreasingsorption performance.
Bio-product Bead
cells
Local level (distance 1.5 )
Bio-product Bead
cells
Local level (distance 1.5 )
BeadBead
cells
Local level (distance 1.5 )
Figure 6: Illustration signifying biomass interaction to adsorbent (at a local level).
The biomass deposition phenomena is hampering the industrial utilization of EBA since its
introduction in 1994 (Curbelo et al. 2003). Some advancement was made in the 90’s to
alleviate such limitation with partial success. Several methods were developed to analyze
the extent of biomass–adsorbent interactions. The methods include finite bath adsorption,
pulse response and residence distribution analysis (Hubbuch et al. 2005). All these
techniques can only provide an overall indication of the state of fouling. Few recent studies
attempted to understand this phenomenon more in detail (Lin et al. 2006). The
aforementioned diagnostic methods address the degree of interaction of biomass to a
Interaction
Aggregation
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Introduction
20
limited range of material types, particularly anion-exchangers. For example, zeta potential
was introduced as a significant parameter for process design, due to the obvious ionic
interaction prevailing in ion-exchange systems. However, this approach cannot explain the
interaction and aggregation of biomass onto hydrophobic and pseudo-affinity beads as
electrostatic interactions play a minor role in such cases. This is due to processing
conditions under which high-conductivity buffers are employed (Gallardo-Moreno et al.
2002; Klotz et al. 1985). Exploring further in this direction Peter Brixius during his doctoral
work in Jülich and Novo Nordisk A/S (Brixius 2003) addressed the existence of some other
forces like Van der Waals and hydrophobic forces involved in the adhesion of biomass
apart from the electrostatic forces. However, Brixius’ work mainly dealt with charge-
mediated attraction forces onto anion exchangers. Some insight on physicochemical
parameters affecting the adhesion of biomass on ion exchanger adsorbents was provided
(Vergnault et al. 2004). A few authors also tried to understand fouling on chromatographic
beads utilizing confocal laser microscopy (Siu et al. 2006). Also manufacturers have tried
to alleviate biomass interaction by introducing novel type of equipment for EBA by
designing novel bead structures (Viloria-Cols et al. 2004). Among the various methods
tried to overcome the interaction of biomass to process surfaces thermal pretreatment of
biomass before loading on the column was reported in literature (Ng et al. 2007).
Despite all these efforts, a comprehensive picture of the interfacial forces acting between
cells and beads was unavailable until now. Particularly, previous work has focused on cell-
to-bead interaction but the role of cell-to-cell aggregation was neglected since this
phenomenon can not be captured by existing methods, like the biomass-impulse test earlier
developed by Feuser (Feuser et al. 1999). Today, we have realized the importance of
aggregation under certain processing conditions (Fernandez-Lahore et al. 2000). Fouling is
a common phenomena in the integrated process where there direct contact between crudefeedstock and reactive solids e.g., membrane operations, magnetic separations, direct
capture techniques (Bierau et al. 2001; Theodossiou et al. 2001; Ventura et al. 2008)
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Introduction
21
1.4 Goal of the work
Complementing all the above research findings by different authors on the biomass
adhesion, current work further progressed with the objective to have more quantitative
fundamental understanding at local level between biomass and adsorbent bead, which are
commonly utilized in EBA technology. It was targeted to determine the basic underlying
phenomenon of the interfacial forces (Lifshitz-van der Waals, hydrophobic attractive or
hydrophilic repulsive and electrostatic) at micrometer scale between a biological particle
and process surface or between two biological particles (Figure 6). Understandings the
phenomena at molecular level will allow developing an improved process performance of
EBA making the process more robust and less complex in the process scenario with all its
added advantages. Additionally the fundamental understanding could help to propose a
universal tool for process/material design when direct sequestration is in focus.
For having this comprehensive picture, surface thermodynamics was utilized. XDLVO
theory was used to determine the interactions and aggregation onto the process surface.
XDLVO calculations were performedvia experimental determination of contact angles and
zeta potentials values for the interacting surfaces or particles. Experimental XDLVO
quantitative information was validated independently with the biomass deposition
experiments (Tari et al. 2008) and laser diffraction experiments.
Under the frame of current research work the following aspects were studied
1) Interaction of three different biomass types intact yeast, yeast homogenates and
E.coli homogenates with the Streamline ion exchangers. Aggregation of only intact
yeast was studied with this type.
2) Interaction and aggregation of Saccharomycess cervisiae with the Streamline
hydrophobic and chelating (pseudo affinity) supports.3) Influence of chemical additives on the interaction and aggregation of
Saccharomycess cervisiae with different Streamline materials.
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Introduction
22
Surface energetics or physicochemical properties of the above-mentioned supports and bio-
foulants are studied in detail at various process conditions in order to have a clear picture in
the problem-creating scenario while downstream processing.
The biomass adhesion on the different substrata has been studied by many authors
(Absolom et al. 1983; Bos et al. 1999) by applying classical DLVO (CDLVO) and
extended DLVO (XDLVO) theory, which was proven to be more advantageous and can be
applied to biological particles (Bos et al. 1999). The detailed theoretical part of XDLVO is
described in chapter I within this thesis.
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References
23
1.5 References
Absolom DR, Lamberti FV, Policova Z, Zingg W, Van Oss CJ, Neumann AW. 1983.
Surface thermodynamics of bacterial adhesion. Appl Environ Microbiol 46(1):90-7.
Ameskamp N, Priesner C, Lehmann J, Lütkemeyer D. 1999. Pilot scale recovery of monoclonal antibodies by expanded bed ion exchange adsorption. Bioseparation
8(1):169-188.
Anspach FB, Curbelo D, Hartmann R, Garke G, Deckwer WD. 1999. Expanded-bed
chromatography in primary protein purification. J Chromatogr A 865(1-2):129-144.
Bierau H, Hinton RJ, Lyddiatt A. 2001. Direct process integration of cell disruption and
fluidised bed adsorption in the recovery of labile microbial enzymes. Bioseparation
10(1-3):73-85.Bonnerjea J, Oh S, Hoare M, Dunnill P. 1986. Protein Purification: The Right Step at the
Right Time. Nat Biotech 4(11):954-958.
Bos R, Van der Mei HC, Busscher HJ. 1999. Physico-chemistry of initial microbial
adhesive interactions--its mechanisms and methods for study. FEMS Microbiol Rev
23(2):179-230.
Brixius PJ. 2003. On the influence of feedstock properties and composition on process
development of expanded bed adsorption. Dusseldorf, Germany: Heinrich Heine
University.
Chase HA. 1994. Purification of proteins by adsorption chromatography in expanded beds.
Trends Biotechnol 12(8):296-303.
Curbelo DR, Garke G, Guilarte RC, Anspach FB, Deckwer WD. 2003. Cost Comparison of
Protein Capture from Cultivation Broths by Expanded and Packed Bed Adsorption.
Eng Life Sci 3(10):406-415.
Enfors S, Häggström L. 2005. Bioprocess Technology - Fundamentals and Applications A
textbook for introduction of the theory and practice of biotechnical processes. 1-350
p.
Erickson JC, Finch JD, Greene DC. 1994. Direct capture of recombinant proteins from
animal cell culture media using a fluidized bed adsorber. In: Griffiths B, Spier RE,
BertholdW, editors. Animal cell technology:Products for today, prospects for
tomorrow. Oxford: Butterworth-Heinemann:557-560.
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Fernandez-Lahore HM, Geilenkirchen S, Boldt K, Nagel A, Kula MR, Thommes J. 2000.
The influence of cell adsorbent interactions on protein adsorption in expanded beds.
J Chromatogr A 873(2):195-208.
Feuser J, Walter J, Kula MR, Thommes J. 1999. Cell/adsorbent interactions in expanded bed adsorption of proteins. Bioseparation 8(1-5):99-109.
Fish NM, Lilly MD. 1984. The Interactions Between Fermentation and Protein Recovery.
Nat Biotech 2(7):623-627.
Gallardo-Moreno AM, Gonzalez-Martin ML, Perez-Giraldo C, Garduno E, Bruque JM,
Gomez-Garcia AC. 2002. Thermodynamic Analysis of Growth Temperature
Dependence in the Adhesion of Candida parapsilosis to Polystyrene. Appl Environ
Microbiol 68(5):2610-2613.
GEHealthCare. 2001-04. Cost comparison: expanded bed adsorption (EBA)vs
conventional recovery in the industrial scale processing of proteins. Application
note STREAMLINE expanded bed adsorption. p 1150-21 AA.
GEHealthCare. 2002-11. A comparison of STREAMLINE expanded bed adsorption with
the combined techniques of filtration and conventional fixed bed chromatography
for the capture of an Fc-fusion protein from CHO cell culture. Application note
STREAMLINE expanded bed adsorption. p 1144-87 AB.
Gupta MN, Mattiasson B. 1994. Novel technologies in downstream processing. Chem Ind
17:673-675.
Headon DR, Walsh G. 1994. The industrial production of enzymes. Biotechnol Adv
12(4):635-646.
Hubbuch J, Thommes J, Kula MR. 2005. Biochemical engineering aspects of expanded bed
adsorption. Adv Biochem Eng Biotechnol 92:101-23.
Klotz SA, Drutz DJ, Zajic JE. 1985. Factors Governing Adherence of Candida Species to
Plastic Surfaces. Infect Immun 50(1):97-191.Lihme A, Zafirakos E, Hansen M, Olander M. 1999. Simplified and more robust EBA
processes by elution in expanded bed mode. Bioseparation 8(1):93-97.
Lin DQ, Fernandez-Lahore HM, Kula MR, Thommes J. 2001. Minimising
biomass/adsorbent interactions in expanded bed adsorption processes: a
methodological design approach. Bioseparation 10(1-3):7-19.
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Lin DQ, Zhong LN, Yao SJ. 2006. Zeta potential as a diagnostic tool to evaluate the
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Biotechnol Bioeng 95(1):185-91.
Maitra SS, Verma AK. 2003. End of Small Volume High Value Myth in Biotechnology,Process Design for a Mega-plant Producing gamma Interferon for Mega Profit. IE
(I) Journal CH 84.
McCormick DK. 1993. Expanded Bed Adsorption. Nat Biotech 11(9):1059-1059.
Ng MYT, Tan WS, Abdullah N, Ling TC, Tey BT. 2007. Direct purification of
recombinant hepatitis B core antigen from two different pre-conditioned unclarified
Escherichia coli feedstocks via expanded bed adsorption chromatography. J
Chromatogr A 1172(1):47-56.
Pavlou AK, Reichert JM. 2004. Recombinant protein therapeutics-success rates, market
trends and values to 2010. Nat Biotech 22(12):1513-1519.
Poulin F, Jacquemart R, DeCrescenzo G, Jolicoeur M, Legros R. 2008. A Study of the
Interaction of HEK-293 Cells with Streamline Chelating Adsorbent in Expanded
Bed Operation. Biotechnol Prog 24(1):279-282.
Siu SC, Boushaba R, Topoyassakul V, Graham A, Choudhury S, Moss G, Titchener-
Hooker NJ. 2006. Visualising fouling of a chromatographic matrix using confocal
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Smith C. 2005. Striving for purity: advances in protein purification. Nat Meth 2(1):71-77.
Smith MP, Bulmer MA, Hjorth R, Titchener-Hooker NJ. 2002. Hydrophobic interaction
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Tari C, Vennapusa RR, Cabrera RB, Fernandez-Lahore M. 2008. Colloid deposition
experiments as a diagnostic tool for biomass attachment onto bioproduct adsorbent
surfaces. J Chem Technol Biotechnol 83:183-191.Theodossiou I, Sondergaard M, Thomas OR. 2001. Design of expanded bed supports for
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3):31-44.
Thiel KA. 2004. Biomanufacturing, from bust to boom...to bubble? Nat Biotech
22(11):1365-1372.
Thömmes J. 1997. Fluidized bed adsorption as a primary recovery step in protein
purification. Adv Biochem Eng/Biotechnol 58:185-230.
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Ventura AM, Fernandez Lahore HM, Smolko EE, Grasselli M. 2008. High-speed protein
purification by adsorptive cation-exchange hollow-fiber cartridges. J Membr Sci
321(2):350-355.
Vergnault H, Mercier-Bonin M, Willemot RM. 2004. Physicochemical parameters involvedin the interaction of Saccharomyces cerevisiae cells with ion-exchange adsorbents
in expanded bed chromatography. Biotechnol Prog 20(5):1534-42.
Viloria-Cols ME, Hatti-Kaul R, Mattiasson B. 2004. Agarose-coated anion exchanger
prevents cell-adsorbent interactions. J Chromatogr A 1043(2):195-200.
Walsh G. 2006. Biopharmaceutical benchmarks 2006. Nat Biotech 24(7):769-776.
Walter J, Feuser J. Novel approach and technology in expanded bed adsorption techniques
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2.0 Organization of dissertation
The dissertation is organized in the form of the manuscripts originated during the course of
my PhD work
Assessing adsorbent-biomass interactions during expanded bed adsorption onto ionexchangers utilizing surface energeticsR.R. Vennapusa, S.M. Hunegnaw, R.B. Cabrera, M. Fernandez-Lahore, published inJournal of Chromatography A. 2008, 1181, (1-2), 9-20.
Colloid deposition experiments as a diagnostic tool for biomass attachment onto bioproductadsorbent surfacesC.Tari† , R.R. Vennapusa†, R.B. Cabrera, M. Fernandez-Lahore, published in Journal of
Chemical Technology & Biotechnology, 2008, 83, 183-191.
Surface energetics to assess biomass attachment onto hydrophobic interaction adsorbents inexpanded bedsR.R. Vennapusa, C. Tari, R. B. Cabrera, M. Fernandez-Lahore. Biochemical EngineeringJournal (accepted).
Surface energetics to assess biomass attachment onto immobilized metal affinity adsorbentsin expanded bedsR.R. Vennapusa, M. Aasim, R.B. Cabrera, M. Fernandez-Lahore. Biotechnology and
Bioprocess Engineering (Submitted).
Surface energetics to assess microbial adhesion onto fluidized chromatography adsorbentsR.R. Vennapusa, S. Binner, R.B. Cabrera, M. Fernandez-Lahore. Engineering in LifeSciences (accepted)
The effect of chemical additives on biomass deposition onto beaded chromatographicsupportsR.R. Vennapusa, M. Fernandez-Lahore. Journal of Biotechnology (Submitted).
† : Equal authorship
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2.1 Assessing adsorbent-biomass interactions during expandedbed adsorption onto ion-exchangers utilizing surface energetics
Rami Reddy Vennapusa, Sara M. Hunegnaw, Rosa B. Cabrera, and Marcelo Fernández-LahoreDownstream Processing Laboratory, Jacobs University, Campus Ring 1, D-28759, Bremen,
Germany.
2.1.1 Abstract
Biomass adhesion onto an adsorbent matrix or “interaction” as well as biological particle
co-adhesion or “aggregation” can severely affect the overall performance of many direct-
contact methods for downstream processing of bioproducts. Studies to quantitativelydescribe this biomass-adsorbent interaction were developed utilizing surface energetics. An
indirect thermodynamic approachvia contact angle and zeta potential measurements was
utilized. Intact yeast cells, yeast homogenates, and disrupted bacterial paste were employed
as model system. Various surfaces that are relevant to biochemical and environmental
applications were characterized. The extended Derjaguin, Landau, Verwey, Overbeek
(XDLVO) theory was found to appropriately predict biomass adhesion behaviour. It was
observed that cell attachment onto anion exchange supports is promoted by strong andclose interaction within a secondary energy minimum followed by moderate multilayer cell
aggregation. On the other hand, cell interaction with cation exchange materials can take
place within a reversible secondary energy minimum and at longer separation distance. The
influence particle charge and size, as well as the influence of the nature of the material
under study were summarized in the form of energy vs. distance profiles. These
investigations lead to many process-related conclusions: a) Process buffer conductivity
windows can be recommended for anion-exchange chromatography (AEX) vs. cation-
exchange chromatography (CEX) systems, b) Increased hydrodynamic shear is required to
prevent biomass attachment onto AEX as compared to CEX, and c) Aggregation
phenomena is a function of contact time and biomass concentration. Understanding
biomass-adsorbent interaction at the particle (local) level is opening the pave for optimized
operation of Expanded Bed Adsorption methods at the process (macro) scale. A universal
methodological approach is presented to guide both process and material design.
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2.1.2 Introduction
The current key component of biotech manufacturing is product downstream processing.
Recovery and purification processes comprise a relatively large number of unit operations,
which complexity depends on the final product purity required and which typically accountfor ≥ 50-85% of the total bioprocessing cost. The required purity of the products in the life
science industry ranges from partially purified biocatalysts to highly purified therapeutic
agents. In any case, bioprocess fluids are generally of complex nature and contain
suspended solids like biological particles of various sizes, as well as solutes of various
molecular masses and chemical structures. Moreover, the need for additional unit
operations during downstreaming will cause a degree of product loss and will substantially
decrease overall process yield. For example, assuming single step yields in the range 70-95%, ~ 60% of the product will be lost after six processing steps.
Expanded Bed Adsorption (EBA) has been proposed as an “integrative” downstream
processing technology allowing the direct capture of targeted species from an unclarified
feedstock e.g. a cell containing fermentation broth. This unit operation has the potential to
combine solids removal, product concentration, and partial purification in a single
processing step. The application of EBA implies, however, that intact cell particles or celldebris present in the feedstock will interact –in a minor or larger extent- with fluidized
adsorbent beads. It is already known that interaction between biomass and the adsorbent
phase may lead to the development of poor system hydrodynamics and therefore, impaired
sorption performance under real process conditions (Anspach et al. 1999; Hubbuch et al.
2005). Detrimental processing conditions can also be expected in any other downstream
operation where direct contacting between a crude feedstock and a reactive solid phase is
supposed to occur (Bierau et al. 2001; Theodossiou et al. 2001). Moreover, biomass
interaction would result in increased buffer consumption in order to remove and wash away
sticky biological particles (GEHealthCare 2001; Northelfer and Walter 2002). These
phenomena i.e. decreased sorption performance and buffer consumption is detrimental to
cost-efficient processing utilizing direct sequestration unit operations.
Earlier studies on biomass-adsorbent interactions were restricted to simple diagnostic tests
to determine the extent of cell –or cell debris- attachment to the desired chromatographic
supports (Feuser et al. 1999). The development of residence time distribution methods as
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applied to turbid feedstock, and their subsequent application to evaluate system
hydrodynamics under real process conditions, has established a clear picture of the
deleterious potential of biomass-adsorbent interactions (Fernandez-Lahore et al. 1999).
Further studies pointed out that interactions between (positively charged) anion exchangersand (negatively charged) biological particles resulted the most problematic system to deal
with (Fernandez-Lahore et al. 2000; Lin et al. 2001). Due to the obvious electrostatic nature
of such interaction, a single property of these interacting bodies i.e. the zeta potential has
been recently proposed for a better understanding and prediction of biomass-adsorbent
interactions (Lin et al. 2003; Lin et al. 2006). Other investigations on microbial adhesion to
solid surfaces have lead to similar conclusions in the sense that electrostatic interaction
between microbial cells and process surfaces is an important factor affecting such
phenomena (Mills et al. 1994; Vergnault et al. 2007). These conclusions, however, were
based on proving biomass adhesion on a single material type in solutions of different ionic
strength. Furthermore, these studies were restricted to ion-exchangers, to yeast cells having
a certain degree of hydrophobic character, and to an experimental evaluation based on the
microbial-adhesion-to-solvents test. On the other hand, some studies have found a better
correlation between surface energy, calculated by the three liquid contact angle method,
and microbial adhesion on different solid supports at constant solution chemistry (Li and
Logan 2004).
Taken into consideration the complexity of interfacial phenomena at the (sub) micrometer
scale, a more comprehensive approach would consider interaction forces other than those
purely electrostatic in nature and would employ principles of colloid chemistry to explain
biomass-adsorbent attachment at the local (particle) level (Van Oss 1994). It is known that
biological particles like microbial cells can be considered “soft” colloidal particles and thus
their adhesion to substrata should be studied as a physicochemical phenomenon. It isevident that, besides hydrodynamic effects, biomass adhesion to process supports has the
potential to be strongly influenced by long-range (electrodynamic Lifshitz – van der Waals,
electrostatic) and short-range (acid-base) interfacial interactions. Within theclassical
DLVO (Derjaguin, Landau, Verwey, Overbeek) theory, Lifshitz-Van der Waals (LW) and
electrostatic interactions (EL) are considered while in theextended approach (XDLVO) the
so called acid-base (AB) component is also accounted for. Application of these principles
to process science would lead to the development of appropriate tools for better bioprocess
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design and prediction and would guide the development of improved materials for
downstream processing. The later is especially true when direct sequestration methods are
in focus.
Accurate understanding and prediction of interfacial forces during biomass adhesion onto
process supports require the utilisation of quantitative models which, in turn, require
experimental measurements to be performed. EL interactions arise from the existence of
overlapping double layers of counter-ions near charged surfaces in aqueous media and are
accessible by determination of the zeta potential. On the other hand, LW interactions are
caused by the specific alignment and coupling of molecular dipoles. Additionally, the
extended approach has been adopted to explain cell-surface interactions in the presence of
other forces like hydrophobic (Van Oss 1995), hydration (Strevett and Chen 2003), and
electrostatic (Camesano and Logan 2000). LW and AB forces are experimentally accessible
via contact angle measurement with three diagnostic liquids.
The aim of this paper was to contribute to a more in-depth understanding of biomass-
adsorbent adhesion and to propose a universal tool for process / material design. In doing
so, the physicochemical properties of biomass-derived material, taken as colloidal particles,
vs. the physicochemical properties of the adsorbent beads, taken as a process surface, were
determined indirectlyvia contact angle and zeta potential measurements. Subsequently,
total interfacial interaction energy values were calculated as a function of surface distance
in aqueous media e.g. process buffer. Calculated interaction energy values were correlated
to process performance.
2.1.3 Theory
2.1.3.1 Total interaction energy
The total interaction energy between a colloidal particle and a solid surface can be
expressed in terms of the classical DLVO theory as:
ELmwc
LW mwc
DLVOmwc U U U += (1)
where UDLVO is the total interaction energy in aqueous media, ULW is the LW interaction
term, and UEL
is the EL interaction term. The subscript m is utilised for thechromatographic matrix (adsorbent bead), w refers to the watery environment, and c to the
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colloidal (cell) particle. This classical DLVO approach can be extended to include a third
short-range (≤ 5 nm) Lewis AB term so as to include “hydrophobic attractive” and
“hydrophilic repulsive” forces into account (Van Oss 1994).
ABmwc
ELmwc
LW mwc
XDLVOmwc U U U U ++= (2)
where UDLVO is the total interaction energy and UAB is the AB interaction term.
2.1.3.2 Lifshitz-van der Waals acid-base approach
Surface energy parameters (tensions) can be calculated from contact angle measurements
on the colloidal particles and adsorbent surface utilising the LW-AB approach. These
parameters (or components) can be determined by performing contact angle measurementsutilising three probe liquids (i.e. two high-energy polar liquids and one high-energy non-
polar liquid) with known surface tension parameters and employing the extended Young’s
equation:
( ) ( +−−+ ++=+ l sl s LW l
LW s
TOT l γ γ γ γ γ γ γ θ 2cos1 (3)
where θ is the contact angle,γLW is the LW surface tension parameter,γ+ is the electron-
acceptor parameter, andγ- is the electron-donor parameter. The subscript s and l is utilised
for solid and liquid respectively. The polar AB component is given by:
−+= γ γ γ 2 AB (4)
and the total surface tension of a pure substance can be represented by the sum of the polar
AB and the non-polar LW surface tension parameters. The later represents a single
electrodynamic property of a certain material.
2.1.3.3 Free energy of interaction
The mentioned surface energy parameters can be employed to evaluate the free energy of
interaction between two defined surfaces (ΔGLW - ΔGAB) e.g. the cell particles and the
adsorbent bead (interaction) or between two cells (aggregation).ΔG represents here the
interaction energy per unit area between two (assumed)infinite planar surfaces bearing the
properties of the adsorbent bead and the cell or two cells, respectively. Moreover, contacts
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between any of these two surfaces are evaluated at the so-called minimum cut-off distance
(h0) i.e. the distance between the outer electron shells of adjoining non-covalently
interacting molecules. The value for h0 is commonly assumed to be 0.158 nm. However, the
mentioned LW and AB interaction energy components follow a unique decay profile withsurface separation distance. Dimensions of the preceding equations are Joule. Nevertheless,
for interaction energies the kT scale is preferred since 1 kT represents the Brownian motion
energy of a microbial particle.
The ULW energy-distance profile can be expressed according to the existing geometric
constraints in order to obtain the actual interaction energy as:
( ) ⎥⎦
⎤⎢⎣
⎡
⎟⎟
⎠ ⎞
⎜⎜
⎝ ⎛
++
++−=
cc
cc LW mwc Rh
h Rh
Rh
R AhU
2ln
26(Sphere-Plate) (5a)
( )( )mc
mc LW cwc R Rh
R R AhU
+−=
6(Sphere-Sphere) (5b)
where R c and R m are the radius of the interacting bodies i.e. ~ 5μm for yeast and∼200 μm
for the adsorbent bead. A is the Hamaker constant that can be obtained fromΔGLW, as
calculated from contact angle measurements, according to
LW Gh A Δ−= 2012π (6a)
( ( LW w
LW c
LW m
LW w
LW mwcG γ γ γ γ −−=Δ 2 (6b)
The UAB energy-distance profile can be expressed according to the existing geometric
constraints in order to obtain the actual interaction energy as:
⎥⎦
⎤⎢⎣
⎡ −Δ=λ
λ π hh
G RhU ABc
ABmwc
0exp2)( (Plate-Sphere) (7a)
⎥⎦
⎤⎢⎣
⎡ −Δ=λ
λ π hh
G RhU ABc
ABcwc
0exp)( (Sphere-Sphere) (7b)
where λ is a characteristic decay length for AB interactions in water (λ ~ 0.6 nm) and
where:
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( ( ( +−−++++−−−−+ +−−++−+=Δ cmcmwcmwwcmw ABmwcG γ γ γ γ γ γ γ γ γ γ γ γ 222 (8)
In order to account for UEL
energy-distance profile the following expression can beemployed assuming either plate-sphere or sphere-sphere geometry, respectively:
( ) ( )( ) ( ){ }⎥
⎦
⎤⎢⎣
⎡ −−+−−−+
++= h
hh
RhU cm
cmcmcr
ELmwc κ
κ κ
ζ ζ ζ ζ
ζ ζ ε ε π 2exp1lnexp1exp1ln2)( 22
220 (9a)
( )( )
( )( )
( ){ }⎥⎦
⎤⎢⎣
⎡ −−+−−−+
+++= h
hh
R R R R
hU cm
cm
mc
cmmcr ELcwc κ
κ κ
ζ ζ ζ ζ ζ ζ ε ε π 2exp1ln
exp1exp1ln2)( 22
220 (9b)
where ε0εr is the dielectric permittivity of the suspending fluid,ζm is the zeta potential of
the adsorbent bead, andζc is the zeta potential of the cell particle. Zeta potential values are
measured by electrophoretic mobility experiments.κ is the inverse Debye screening length
and can be calculated on the basis of the relationship below:
T k
z ne
r
ii
0
22
ε ε κ ∑= (10)
where e is the electron charge, ni is the number concentration of ioni in solution, zi is the
valence of ioni, k is the Boltzman constant, and T is the absolute temperature.
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2.1.4 Materials and Methods
2.1.4.1 Materials
Chromatographic matrices and columns were purchased from GE Healthcare (Munich,
Germany). Solvents utilised for contact angle measurements (1-bromonaphtalene and
formamide) were obtained from Fluka (Buchs, Switzerland) with 99% and 99.5% purity,
respectively. Water was Milli-Q quality. All other chemicals were of analytical grade.
The goniometric system (OCA 20) was obtained from DataPhysics Instruments GmbH
(Filderstadt, Germany). Zeta potential was measured with a Zetasizer Nano ZS from
Malvern Instruments (Worcestershire, United Kingdom).
2.1.4.2 Biomass
Yeast cells (Saccharomyces cerevisiae ) were cultivated, harvested at late exponential
phase, and washed three times with dilute buffer solutions (Ganeva et al. 2004). Fresh E.
coli DH5α biomass was produced according to standard methods (Sambrook and Russell
2006). Cell disruption was performed by bead milling, as previously described (Fernandez-
Lahore et al. 1999).
2.1.4.3 Surface preparation for contact angle measurements
Preparation of the intact yeast cells for contact angle measurements was performed
essentially according to Henriques et al. (Henriques et al. 2002). Fresh (washed) cells were
suspended to 10% (w/v) in 50 mM citrate phosphate buffer (pH 3, 5, 7 or 9). Suspended
cells were further allowed to equilibrate in the respective buffer for 30 minutes and the
suspension was poured onto an agar plate containing 10% glycerol and 2% agar-agar. The
plate was allowed to dry for 24-36 hours at room temperature on a properly levelled surface
and free from dust.
Agarose-based adsorbent beads harbouring various ligand chemistries were thoroughly
equilibrated in 50 mM sodium acetate (pH 4) or 20 mM phosphate buffer (pH 7). Once
equilibrated, matrix beads were frozen in liquid nitrogen and crushed mechanically.
Crushing efficiency was assessed by microscopic examination and particle size
determination. Crushed matrix was made 40% (w/v) in buffer and allowed to remain in
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contact with the liquid phase for additional 30 minutes with gentle mixing. Fine bead
fragments were poured onto a glycerol-containing agar plate and allowed to dry, as
described before.
Immobilized biomass or adsorbent fragments (< 10μm diameter) on squares pieces of the
agar-supported surface were utilised for measuring the contact angles.
2.1.4.4 Contact angle measurements
For the contact angle estimation, the sessile drop technique was utilized (Sharma and Rao
2002). Data acquisition and analysis was performed utilising SCA20 commercial software
(DataPhysics Instruments GmbH, Filderstadt, Germany). Measurements were performed at
room temperature, using three different diagnostic liquids: water, formamide and 1-
bromonaphtalene. Assays were performed in triplicate and at least 20 contact angles per
samples were measured. Contact angles were measured for biomass samples as a function
of pH in the range from 3.0 to 7.0. Measurements for adsorbent materials were performed
at pH 4.0 and pH 7.0 in diluted buffer solutions. The solution chemistry employed reflected
common process conditions.
2.1.4.5 Zeta potential determinations
Particle zeta potential was determined for the cell particles and for the chromatographic
supports under study. Biomass-derived particles were suspended to 1% (w/v) in 20 mM
phosphate or citrate-phosphate buffers. Fragmented Sepharose beads were utilized instead
of Streamline beads due to their lower density and to avoid sedimentation during
measurements. Particles were contacted with buffer until equilibrium was reached and
further diluted to appropriate particle count (~200) before measuring the zeta potential. Zeta
potentials were calculated from the electrophoretic mobility data as per theSmoluchowski’s equation (Ottewill and Shaw 1972). All the measurements were done in
triplicate.
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2.1.4.6 Biomass-pulse experiments
Experiments were performed on an ÄKTA Explorer system (GE-Healthcare, Munich,
Germany) utilising a modified XK-10 chromatographic column filled with the sample
adsorbent (2.0 ml) and irrigated from the bottom with the mobile phase. The solid phasewas fluidised at a fluid velocity of 7.5-8.3⋅10-4 m⋅s-1 in order to promote the formation of a
stable expanded bed. A biomass pulse (~ 2 ml of 0.03% w/v biomass suspension) were
loaded into the system through a three way injection port. Cell concentration in the pulse
before and after passage through the expanded bed was detected on-line by measuring the
optical density at 600 nm. Results were expressed as Cell Transmition Index (CTI) (Feuser
et al. 1999).
2.1.4.7 Partition experiments
Solid-liquid partitioning experiments were performed with adsorbent beads and biomass in
glass flasks (4 cm height, 1.5 cm diameter), which were closed with plastic caps.
Chromatographic beads (0.5 ml) were contacted with a cell suspension (2.0 ml of 0.03%
w/v) under gentle orbital stirring. Samples were taken after 15 min and 3 h to evaluate the
fast and slow phases of cell deposition (Fernandez-Lahore et al. 2000). The optical density
of the samples was evaluated by absorbance at 600 nm. The fraction of non-bound cells or biomass particles to each material type was defined as the Cell Partition Index (CPI).
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2.1.5 Results and Discussions
2.1.5.1 Contact angle measurements
The diagnostic liquids water, formamide, and 1-bromonaphtalene were employed to
measure contact angles on lawns of hydrated biomass or crushed agarose beads utilising the
sessile drop technique. The surface free energy componentsγLW and γAB, as well as, the
electron-donating and electron-accepting parameters for these liquids can be found in the
literature (Bos et al. 1999). Biomass and adsorbent fragments were equilibrated in 20 mM
phosphate buffer pH 7, which provides a chemical environment similar to that found under
ion-exchange sorption processing in industrial practice. In this work, biomass or crushed
adsorbent lawns were prepared on agar layers (Henriques et al. 2002). This method permits
contact angle measurements under the assumption that only bound water is present on thesample surface and proved to be suitable to handle a variety of materials by forming an
even and homogeneous surface.
Table 1: Contact angle measurements for agarose-based beaded supports. Determinationswere performed on lawns of crushed agrose-based adsorbents in in 20mM Phosphate buffer, pH 7.
Support type Contact angle ( θ)
Water Formamide 1-Bromonaphtalene
Sepharose 4B 9.5 ± 2 10 ± 1 44 ± 1
Q Sepharose XL 12 ± 1 14 ± 2 52 ± 1
DEAE Sepharose 9.6 ± 3 13 ± 2 41 ± 1
SP Sepharose 6.7 ± 3 13 ± 1 39 ± 1
Table 1 shows the contact angle values for the anion-exchanger DEAE-Sepharose, the
cation exchanger SP-Sepharose, and the agarose base material 4B-Sepharose. An additional
composite ion-exchanger, Q-Sepharose-XL was also included. Sepharose materials were
utilised for obtaining small particles suitable for contact angle measurements since
Streamline materials have a difficult-to-brake quartz core but similar chemical structure. In
the later case, particle diameter was lower than 10μm to assure no interference with
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measurement of contact angles. Contact angle values with polar liquids were similar for all
the chromatographic supports under consideration. Low values were observed for water (7-
12°) and formamide (10-14°), which reflects the general very hydrophilic nature of the
beads under study. However, 1-bromonaphtalene contact angles were able to discriminate between Agarose- based beads (Sepharose series) and the Agarose-Dextran composite (XL
material). The contact angle value with the apolar solvent for the later was 20% higher,
which might indicate an increased hydrophilic character for XL-Sepharose in comparison
with standard materials. This is in agreement with the known higher hydrophilic character
of Dextran T-70 in comparison with polymeric Agarose as judged by the free energy of
interaction of these molecules in water:ΔGsws was reported as -9.2 mJ·m-2 for agarose and
+17.6 mJ·m-2 for Dextran (Van Oss 1994). Moreover, comparison between 1-
bromonaphtalene contact angle values for functionalised vs. non-functionalised Sepharose
materials showed decreased values for the first group i.e. 44° (base material) vs. 39°- 41°
(SP and DEAE materials, respectively). This might reflect an increased hydrophobic
character of the functionalised adsorbent due to the influence of ligand immobilisation
chemistry. Contact angles were determined with the various adsorbents and all the three
liquids at pH 4 but no major changes were observed (data not shown).
Table 2: Contact angle measurements for biological materials. Determinations were performed in 20mM Phosphate buffer at pH 7.
Biomass type Contact angle ( θ )Water Formamide 1-Bromonaphtalene
Intact yeast cells 15 ± 2 14 ± 1 54 ± 1
Yeast homogenate 18 ± 1 22 ± 2 53 ± 1
Bacterial homogenate 28 ± 4 30 ± 2 54 ± 3
Table 2 shows the contact angle values obtained for biomass types which are relevant to
process situations: intact yeast cells, disrupted yeast cells, and disrupted bacterial cells.
Saccharomyces cerevisiae and Escherichia coli were employed as model biomass systems.
Cell disruption was accomplished by bead milling which generated yeast cell fragments
with a size ~ 2-3 μm and bacterial fragments with a size ~ 1μm. As opposed to theobserved trend when analysing the adsorbent materials, contact angle values for the apolar
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In which the AB component equals
+−= sv sv AB sv γ γ γ 2
The electron-donating (−
svγ ) and the electron-aceptor (+
svγ ) free energy components give anindication on the biomass or material ability to exert acid-base interactions on an scale
taking water as an arbitrary reference. Since 1-bromonaphtalene is apolar ( ABlvγ = 0), this
liquid can be utilised to calculate the LW component of the biomass/material:
( )2
21cos⎪⎭
⎪⎬⎫
⎪⎩
⎪⎨⎧ += θ γ
γ lv LW sv
On the other hand, since water and formamide are polar, these liquids can be employed in
combination to calculate the electron-donating and electron-accepting parameters of the
sample surface from:
( ) −++− +=−+ lv svlv sv LW lv
LW svlv γ γ γ γ γ γ θ γ 2221cos
According to van Oss (Van Oss 1997) the hydrophilic/ hydrophobic character of a certain
material can be defined in terms of the variation of the free energy of interaction betweentwo moieties of that material immersed in water. This is given after:
( ) ( )+−−+−+−+ −−+−−−=Δ w sw sww s s LW w
LW s
TOT swsG γ γ γ γ γ γ γ γ γ γ 42
2
Calculation of ΔGsws yielded positive values for all the adsorbents i.e. > +25 mJ·m-2, which
demonstrates their hydrophilic nature. However, further inspection of Table 3 showed that
a lower γLW
value was obtained for the XL material and therefore the more polar character of this composite in comparison with the Agarose beads can be confirmed. Moreover, an
increased value for the electron-acceptor parameter characterises the composite adsorbent.
On the basis of the contact angle values obtained with polar liquids and the calculation of
the corresponding surface free energy parameters, the tested adsorbents can be considered
to have a polar character according to the following series:
Q-XL > Beaded agarose > DEAE = SP
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Calculation of ΔGsws also yielded positive values for all the biomass types under
consideration (Table 4). Concerning microorganisms it is generally accepted thatΔG > 0
characterises hydrophilic cell surfaces and therefore, the tendency of these biological
particles to aggregate in aqueous environments is very limited. This is particularly true for cells suspended in dilute buffer solutions, which are common during adsorption onto ion-
exchangers.
Table 3: Surface energy parameters for agarose and beaded chromatographic supportscalculated from contact angle measurements at pH 7.
Support typeSurface energy parameters [mJ m -2]
γLW
γ+
γ-
γAB
γTOT
ΔG sws
Agarosea 40.9 0.1 23.8 2.9 43.9 -9.2Dextran T-70a 41.8 1.0 47.2 13.7 55.5 +17.6Sepharose 4B 32.8 2.9 53.6 24.9 57.7 +28.1
Q Sepharose XL 28.9 3.9 53.2 28.8 57.8 +26.6DEAE Sepharose 34.1 2.3 54.5 22.3 56.7 +30.7
SP Sepharose 35.0 2.0 55.7 21.1 56.4 +31.9
(a) Taken from van Oss (Van Oss 1994).
Table 4: Surface energy parameters for several common biomass types at pH 7 ascalculated from contact angle measurements.
Biomass typeSurface energy parameters (mJ m -2)
γLW γ+ γ - γAB γTOT ΔG sws
Intact yeast cells 27.9 4.4 51.5 30.1 58.3 +24.3Yeast homogenate 28.4 3.3 53.2 26.4 55.2 +28.1
Bacterial homogenate 27.9 2.7 49.2 23.1 51.3 +26.0
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2.1.5.3 Interfacial free energy of adhesion: interaction and aggregation
Biomass adhesion to process supports can be considered as a complex phenomenon
including at least two distinct phases: a) The interaction phase characterised by rapidkinetics, where a biological particle approaches the adsorbent bead, and b) The aggregation
phase characterised by cell to cell clumping. The later phase shows lower kinetics and it is
affected by the process contact time and the biomass concentration in the feedstock
(Fernandez-Lahore et al. 1999).
Table 5 depicts the values for interfacial free energy of interaction between several ion-
exchangers and model biomass particles, at closest distance of approximation.ΔGLW values
for agarose-based chromatographic supports were very similar, irrespective of the ligand
chemistry. This may indicate the strong influence of the base material e.g. cross-linked
agarose on the calculated LW energy component. As expected LW energy values were
negative, indicating an attractive interaction. The composite material Q-XL showed a 30%
decreasedΔGLW value (-0.9 mJ·m-2), which again indicates the different structural nature of
the later. On the basis of experimentalΔGLW values it was possible to calculate an average
Hamaker constant for agarose-based materials equal to 4⋅10-21 J or 0.34 k T. This is in
agreement with commonly assumed values for microbial systems (~ 0.49k T). Variations in
ΔGLW values within a range± 50% were observed when comparing beaded agarose
supports with other biomass-interacting materials, like polystyrene, ceramic, or glass.
Repulsive forces were found to play a role during biomass interaction phenomena. This
forces, based on electron donor / electron acceptor or Lewis acid-base, can be seen as
responsible for abnormalities found in the DLVO theoretical interpretation of interfacial
interactions in aqueous media. Table 5 shows an average value for the studiedchromatographic supports in the range +26 to +30 mJ·m-2. These values for the AB
component are 20 times higher than those found for the attractive LW component. AB
forces are known to surpass other DLVO forces by as much as two decimal orders of
magnitude and therefore are extremely important in understanding biomass-support
interactions. The decay with distance of the AB interaction energy is assumed to describe
the distance dependence of the boundary layer ordering. Moreover, ΔGAB values were
shown to change when other systems were examined. For example, the E. coli / PES system
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showed a low value (+2.5 mJ·m-2) and the yeast / Q-Hyper Z or the mammalian cell / glass
showed moderate values (~ +20 mJ·m-2). From these data it becomes clear that acid-base
forces exerted in dilute buffer solutions have the potential to strongly influence biomass
interactions during normal processing conditions. Moreover,ΔGAB
forces are the dominantcomponent of the calculated total interfacial free energy of interaction (ΔGTOT as per Table
5) in several process systems of biochemical and environmental importance.
Table 5: Interfacial free energy of interaction between biomass and process materials.Calculations were performed assuming interactions under process buffer conditions at pH7.
Biomass type Support ΔG (mJ·m -2)ΔG LW ΔG AB ΔG TOT
Intact yeast cells Agarose beads -1.3 +27.6 +26.3XL-Q -0.9 +26.3 +25.5DEAE -1.4 +28.7 +27.4SP -1.5 +29.7 +28.0
Yeast homog. Agarose beads -1.4 +29.7 +28.3XL-Q -0.9 +28.3 +27.3DEAE -1.5 +30.9 +29.3SP -1.6 +31.9 +30.2
Bacterial homog. Agarose beads -1.3 +28.6 +27.3
XL-Q -0.9 +27.3 +26.5DEAE -1.4 +29.7 +28.3SP -1.5 +30.7 +29.0
E. coli a PES -2.0 +2.5 +0.5
S. cerveviseae b Q-Hyper Z -0.7 +18.4 +17.7
Mammaliancellsc
Glass -2.5 +20.9 +17.3
aTaken from (Gallardo-Moreno et al. 2002) , btaken from (Vergnault et al. 2004),ctakenfrom (Li and Logan 2004; Van Oss 1994).
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increased. These values keep constant by decreasing the pH down to 4 in diluted buffer
solution.
Table 7: Zeta potential values for beaded adsorbents.
Zeta potential (mV)
pH (-) 4 7
Cond. (mS/cm) ≤ 9 ~15 ≤ 9 ~15
Support type
Sepharose 4B -3.2a nd -2.0a ndQ Sepharose XL b
+27a
/ +18c
nd + 15a
/ +14c
+8d
DEAE Sepharosee +15a / +24c /+13d nd +8.7a / +21c /
+11d +6d
SP Sepharosee -14a / -29c nd -24a / -30c nd
Zeta potentials values for silica particles (Si-m) were reported as -36.5 mV by Li and Logan(Li and Logan 2004).nd: not determineda Own determinations b Experiments were performed in sodium acetate buffer at pH (1mS/cm) andsodium/potassium phosphate buffer at pH 7 (4 mS/cm).c Published values after Lin et al.(Lin et al. 2006)as performed in 50 mM sodium phosphate buffer pH 7.2 or values after Lin et al (Lin et al. 2003) in 10 mM KNO3 pH 7.2.d Zeta potential measurements according to Lin et al (Lin et al. 2006)in 50 mM phosphate buffer and sodium chloride as added salt.e Experiments were performed in 20 mM sodium/potassium phosphate buffer at pH 4 and pH 7.
Cell or cell debris particles are also known to bear surface charge. Table 8 depicts zeta
potential values for several model biomass types like intact yeast cells, yeast homogenate particles, and bacterial debris. It can be observed that intact yeast cells have negative zeta
potential values raging from∼-30 mV to∼-10 mV in salt solution from 1.0 to 100 mM,
respectively, at neutral pH. At lower pH (∼4) zeta potential values ranged from∼-18 mV
to ∼-2 mV. Biological particles originated by cell disruption have had a tendency to be
less negative (yeast debris∼-12 mV) or more negative (bacterial debris∼-30 mV) than
intact yeast and bacterial cells, respectively. This fact reflects both the influence of
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feedstock treatment and the biological nature of the feedstock (Brixius 2003; Lin et al.
2007).
Values reported here for zeta potential of biomass and process materials were obtained by ameta-analysis of the current literature and confirmed by own measurements. Special
emphasis was placed on conditions that are significant in industrial practice, like feedstock
loading (buffer conductivity≤ 2-9 mS·cm-1) and product elution (buffer conductivity≥ 15
mS·cm-1). Extremes of pH (4 and 7) were considered to evaluate to potential effect of pH
change on electrostatic interactions.
Table 8: Zeta potential values for biological particles.Zeta potential (mV)
pH (-) 4 7
Cond. (mS/cm) ~2-4 ~15 ~2-4 ~15
Biomass type
Intact yeast cells -7a / -7 b / -9c -2c -15a / -9 b / -21c -16c / -7d
Yeast homogenate -4a / -3d nd -12a / -14d -5d E. coli homogenate+ -10a / -5d nd -30a / -35d -22d
nd: Not determined. (+) Published values for intact E.coli cells are -17 at pH 4 and -27 at pH 7 in 50 mM phosphate buffer (Lin et al. 2006). Mammalian cells were reported to havezeta potential values~ -25 mV (Van Oss 1994).a Own measurements in 20mM sodium/potassium phosphate buffer. b Data from Lin et al.(Lin et al. 2006)c According to Kang et al. (Kang and Choi 2005)d Taken from Lin et al.(Lin et al. 2007)
2.1.5.5 Adhesion and interaction phenomena: free energy vs. distance profiles
Integration of the various existing interfacial forces between an adsorbent bead and a
biological particle (interaction) or between two biological particles (aggregation) can be
performed by calculating Energy (U) vs. distance (H) profiles. Figure 1 depicts such
interfacial energy curve for the adhesion of an intact yeast cell onto a DEAE Streamline™
bead. From this figure, it can be realised how different interfacial forces can contribute to
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cell-bead interaction. While LW and EL forces are attractive in this case, AB forces are
repulsive. The total energy profile obtained after application of the DLVO theory would
predict an infinite (primary) energy pocket where a cell would be irreversibly trapped in
close contact with the adsorbent bead. However, previous experimental findings haveshown that intact cell yeasts can be detached from adsorbent beads by applying an
increased shear stress to the system. Calculations based on the XDLVO theory better
explain this phenomenon by showing a secondary energy minimum having a finite
magnitude.
Figure 1: Interfacial free energy components as a function of distance for a DEAEfunctionalized adsorbent particle and an intact yeast cell in aqueous media: (— ) LW: (— )EL: (— ) AB. Total interaction energy profiles are shown according to the DLVO theory(— ) and the (— ) XDLVO theory.
In order to better elucidate the appropriateness of the XDLVO theory to predict microbial
adhesion within the frame of biochemical engineering systems, calculation were run with
several cell / support pairs. Figure 2 depicts the total energy vs. distance profiles for
selected agarose and non-agarose based materials and several biomass types. Adsorbent
beads suitable for expanded bed operation showed, in agreement with previous reports,
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strong interaction with intact cells. It is now clear that this interaction occurs at a distance
of 4-5 nm and within (secondary) energy wells between -200 kT for DEAE (taken as a
reference) and -400 kT for Q-Hyper-Z, a ceramic composite material. These findings can
explain why the utilisation of dynamic flow distribution and the introduction of denser particles can alleviate biomass adhesion to fluidised adsorbent: the increased shear /
hydrodynamic stress provide enough energy to detach cell particles from the (finite)
secondary minimum.
Other system behaved differently. The PES / bacteria pair, which is know as a strong
interacting system (Absolom et al. 1983), showed an infinite primary minimum. This is due
to the hydrophobic nature of the solid substrate and the low contribution of repulsive AB
forces. On the other hand, the mammalian / glass pair showed a moderate secondary energywell (-60 kT) occurring at 15-20 nm distance. This is also in agreement with hydrodynamic
limitations found during the purification of monoclonal antibodies onto porous glass cation
exchangers in the fluidised mode (Thommes et al. 1995).
Figure 2: Total interaction free energy profiles for several process systems according to theextended approach: (— ) DEAE/yeast cells, (— ) PES/bacterial cells, (— ) Q ceramic/yeastcells, and (— ) glass particles/mammalian cells.
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Interaction energy as a function of biomass type in the feedstock can be observed in Figure
3. Calculation performed for intact yeast cells, yeast homogenate, and bacterial homogenate
suggest that a much strong interaction would occur between the intact cell and the DEAE
Streamline adsorbent bead than with any of the two homogenates. This is in fullyagreement with experimental evidence reported earlier by Fernandez Lahore et al
(Fernandez-Lahore et al. 2000; Fernandez-Lahore et al. 1999). Additionally, from this
figure the effect of particle size on the overall energy vs. distance profile can be
understood. Lin et al. (Lin et al. 2003) have realised the importance of biological particle
size, besides the obvious electrostatic effects between two opposite charged spheres, during
biomass interactions in EBA. Both factors, in addition to the contribution of LW, AB, and
BR forces are nicely summarised in a single U vs. H curve.
Figure 3: Total energy vs. distance profiles for an anion-exchange (DEAE)chromatographic support and various types of biomass-derived particles. (— ) intact yeastcells; (— ) yeast homogenate; (— ) bacterial homogenate.
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Process operational parameters and process materials are of prime importance to biomass
adhesion effects. Figure 4 depict the energy vs. distance profiles for agarose based supports
in contact with intact yeast cells. Interaction of yeast cells with these adsorbent beads, as
judged by the depth of the energy pocket, can be ordered as follows:
Q XL(-370 kT) > DEAE (-200 kT) >> BASE (-12 kT)≈ SP (-10 kT)
The depth of the energy pocket correlates with the proximity of such interaction between
cells and adsorbent beads, as follows:
Q XL (4 nm) > DEAE (5 nm) > BASE (10 nm) > SP (20 nm )
The strongest and closest interactions predicted by the XDLVO theory in the mentioned
scale, therefore, fully correlates with previous work on biomass interaction and
hydrodynamics in expanded beds. In the same line of thought (Fernandez-Lahore et al.
2001), it has been reported that ionic strength operation windows could help in alleviating
hydrodynamic and sorption performance constraint during EBA operation with anion-
exchangers. Figure 5 shows energy vs. distance calculations for various buffer conditions
i.e. low vs. high pH and low vs. high conductivity within the range expected to occur
during real operations. Moreover, with ion-exchange operations it was found that an
increased conductivity reduced the depth of the energy pocket from -200 kT to – 40 kT.
Charge-masking effects and double layer compression mainly dominate this effect. The
influence of the pH, within the range 4 to 7, was only marginal for yeast / anion-exchanger
interacting pair. Calculations performed with experimental data gathered from CEX
materials and intact yeast cells revealed an opposite behaviour. The later showed the
development of a secondary energy well at low to very-low salt concentration in therunning buffer (data not shown). This situation could lead to unexpected biomass
interactions with materials known as “non-interacting” (SP) and with mobile phase
compositions that are not suspected to promote impaired hydrodynamic conditions.
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Figure 4 : The influence of the functional ligand on the total interfacial energy when anintact yeast cell and an agarose-based bead are the interacting bodies. (— ) DEAE, (— ) Q-XL,(— ) SP, (— ) BASE.
Figure 5: Energy vs. distance curves showing the influence of the buffer pH andconductivity on the interaction between an anion-exchange bead and an intact yeastcell.(— ) low conductivity pH 7,(— ) high conductivity pH 7, (— ) low conductivity pH 4,(•••) high conductivity pH 4. Low conductivity: 2 ms cm-1, High conductivity: 14mS cm-1.
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2.1.5.6 Aggregation phenomena: the cell to cell interface
As mentioned before, biomass adhesion kinetics recognises two main phases as revealed by
partitioning experiments (Fernandez-Lahore et al. 2000). The second, slow, biomass
concentration dependent phase was linked to cell-to-cell aggregation (homo-coagulation).Therefore, it is also important to study the interfacial free energy between two cell particles
to have a clear picture of biomass adhesion onto surfaces during bioprocessing.
Mathematical expressions derived for sphere-sphere contact were utilised. Figure 6 depicts
cell aggregation at pH 4 and 7. The figure also presents calculated profiles for low and high
salt concentrations at these two pH values. It can be observed that at low salt concentrations
-and with little influence of the pH value- the secondary energy pocket is almost inexistent.
At high salt concentration, however, the depth of the energy trap increases moderately (∼5-10 kT) due to the compression of the double layer at increased ion concentration in the
solution. Consequently, for particles repelling each other by charge-mediated effect the
probability of aggregation is higher than in diluted buffer. This situation is analogous to the
interaction between a (negatively charged) cation-exchanger bead and a (negatively
charged) cell particle, as mentioned before. Interaction effects of this kind, however, are
expected to have more impact on the retention of intact cells than on the adhesion of cell
debris since the size of the particles involved is higher in the first case. Moreover,aggregation might be worsened by the presence of bivalent ions since they were reported to
depress the monopolar electron-donor parameter of the surface tension. This would result in
depressing their mutual repulsion (Van Oss et al. 1987). According to these studies, the
calculated Hamaker constant was 1.4.10-21 for biomass aggregation.
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Figure 6 : Interfacial energy between two yeast cells as function of solution chemistry.(— ) 2 mS cm-1 pH 7, (•••) 14 mS cm-1 pH 7,(— ) 2 mS cm-1 pH 4,(— ) 14 mS cm-1 pH 4.
2.1.5.7 The energy pocket as predictor of process performance
A correlation between the magnitude and sign of the secondary energy pocket and standard
indexes employed to evaluate biomass adhesion onto fluidised adsorbent was established.
These indexes, as obtained by cell pulse experiments or partition experiments are known to
correlate with the quality of bed fluidization and sorption performance in EBA. This
correlation is depicted in Figure 7. Three main groups of data points can be observed:
a) A first group (U values > -20k T) showed almost complete cell transmition (CTI≥ 90%).
Process conditions represented by these points are not expected to create hydrodynamic
disturbances and thus, maximised sorption performance will be reached. This group is
represented by the cation exchangers in dilute buffer solutions, and the anion exchangers at
moderate-high salt containing buffers. The agarose-base material is also included here.
b) A second group (-20k T < U < -200 k T) showed a linear correlation with the celltransmition index, from 40% to 90%. Process conditions represented by this group require
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process optimisation for appropriate sorption performance. Interventionsvia operational
window optimisation or solution chemistry design are mandatory. In the worst cases,
material engineering could restore process performance. This group is mainly composed by
several anion exchangers operating in diluted buffer at pH 4 – 7 and by the cationexchangers in moderate-high salt containing buffers. This group also contain adsorbent
materials other than ion-exchangers (data not shown).
c) A third group was obtained at strongly negative energy pocket (≤ -300 kT) where cell
transmission was extremely reduced e.g. < 30%. The later situation is most commonly
associated with a complete bed collapse upon feedstock application. This group is
represented by strongly adhesive systems, especially when AEX brush-type composite
materials are employed in diluted buffer solutions or when DEAE supports are subjected tolong contact times.
The effect of hydrodynamic forces on the detachment of biological particles on
chromatographic supports and other process materials can be explained on the basis of the
finite value obtained for the calculated minimum of energy. A finite (secondary) minimum
is present at 4-5 nm distance between the interacting bodies, even in those cases where
strong biomass attachment is known to occur and to cause impaired sorption performance.Under such circumstances, detachment of adhering cells will be promoted upon applying
enough energy to overcome the energy pocket. Since interaction energies are proportional
to the particle radius, the effect of the mentioned energy secondary minimum is expected to
be more significant for larger particles. This is in agreement with the strong biomass
adhesion observed for intact yeast cells (4μm diameter) onto fluidised beads as compared
to cell debris (< 1μm diameter).
The surface energetics approach presented in this work can be useful in guiding process
developments. Calculations can be performed easily utilising a personal computer and
commercial software. This assists in finding conditions for reduced interaction and
aggregation with a minimum of experimental effort. Moreover, our approach can help in
the development of novel (less interacting) materials for direct capture applications. In a
recent publication, Kang and Choi (Kang and Choi 2005) have demonstrated the effect of
surface modification as a controlling factor in microbial adhesion. These authors, in
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agreement with this work, have also explained the interaction between microbial cells and
solid substrates on the basis of the XDLVO theory.
The surface energetic approach has a universal nature as predictor of process performancesince it is not restricted to the type of material, the nature / size of the biomass particles, and
the environmental conditions prevailing within the running phase. As such, it is not
restricted to process situations that are dominated by coulomb-type interactions. For
example, Gallardo-Moreno etal. (Gallardo-Moreno et al. 2002) have found a good
correlation between thermodynamic prediction and adhesion behaviour of Candida
parapsilosis to polystyrene.
It is worth to mention at this point that interactions other than the ones described here may
influence interaction between biological and/or polymeric particles. For example, steric
interaction may arise between a polymer-coated surface, which is the case for some
microbial and adsorbent surfaces. A crude feedstock may also contain variable amounts of
bridging cations or macromolecular polymers (Dainiak et al. 2002; Mattiasson et al. 1996).
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Figure 7: Correlation graph between the depth of the secondary energy pocket and the cellor partition transmission index (CTI). (• ) DEAE, (▲) Q- XL, (▼) Q- Hyper D, (■) SP,
(× ) Base.
2.1.6 Conclusions
A universal approach was developed to understand biomass adhesion to process supports,
with special reference to downstream processing systems where the direct sequestration of
targeted species is intended from the crude feedstock. Besides the influence of coulomb-
type interactions, this approach takes into account other forces so as to present a more
comprehensive visualisation of the underlying thermodynamic phenomena of adhesion.
This is conveniently performed by utilisation of energy-distance profiles. In this way, the
distance and strength of interaction can be explored for support-biomass interaction, as well
as, for cell-cell aggregation.
The LW interaction, which is predominantly attractive in microbial systems, was not
influenced by the ionic strength but both the range and magnitude of the EL interactions
decrease with increasing ionic strength due to shielding of surface charges. AB interactions
were found to be a function of the nature of the process solid phase onto which cell
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adhesion took place. As a consequence, depending on the liquid phase ionic strength and
the nature of the process material, a (finite) secondary minimum may exist allowing the
reversible capture of biological particles.
At the distance at which the energy pocket occurs, a correlation exists between the depth of
such energy minima and the degree of biomass entrapment as described by the “Cell
transmition index” and the “Cell partition index”. This correlation is valid for both cation
and anion exchangers under a variety of common operational conditions, which are relevant
to industrial practice. According to the XDLVO methodological approach interactions are
predicted to be alleviated by working within operational windows at moderate conductivity
values for AEX i.e. when employing diluted buffer for sample application. On the contrary,
high conductivity values might hamper CEX operations i.e. under elution conditions were
high salt concentration are commonly utilised. The evaluation of the complete range of
interfacial forces, as proposed here, represents a first step to global modelling. This would
further establish a link between shear / hydrodynamic effects and cell adhesion onto
process surfaces.
Calculations required are simple to produce and are based on two experimental
measurements that are contact angle measurements and zeta potential determinations. This
approach is useful for process design where reduced optimisation time would be required.
But particularly the method provides an excellent tool for novel material design. This in not
only restricted to the development of improved expanded bed adsorbents. Reactive solid
phases utilised in other direct-capture unit operations like finite bath systems, separations
based on magnetic particles, macroporous systems, and big-beads packed beds can be
tailored with assistance of the surface energetics approach.
2.1.7 Acknowledgements
This work was partially funded by the BID 1201/OC AR 649 PICT 08352 and the start-up
grant from Jacobs University [IUB] (2130-90050). The authors would like thank Dr. H. C.
van der Mei for valuable discussions.
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2.1.8 Nomenclature
A Hamker constant [J] / [kT]
CPI Cell partition index [-]
CTI Cell transmission index [-]
BR Born repulsion
DEAE Diethylaminoethyl-
EBA Expanded Bed Adsorption
∆ G Total interfacial free energy [mJ⋅m-2]
ho Distance at a closet approach [m]
H Distance [m]
IC Intact cells
IEX Ion exchange Chromatography
PES Plastic
R Radius [m]
Si-m Silica
SP Sulphopropyl-
T Temperature [K]
U Total interaction energy [kT]
Greek letters
γ Surface tension [mJ⋅m-2]
γ+ Electron-acceptor component of surface tension (Lewis acid) [mJ⋅m-2]
γ- Electron-donor component of surface tension (Lewis base) [mJ⋅m-2]
λ Characteristic decay length [m]
ε0 Permittivity of vacuum [J⋅m-1⋅V-2]
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εr Relative permittivity or dielectric constant for water [-]
κ Inverse of Debye length [m-1]
k Boltzmann constant [J⋅K -1]
ζ Zeta potential [V]
Superscripts
AB Acid-Base
DLVO Derjaguin, Landau, Verwey and Overbeek Theory
EL Electrostatic
LW Lifshitz-Van der Waals
TOT Total
XDLVO Extended DLVO Theory
Subscripts
c Cell particle
m Chromatographic matrix
l Liquid
s Solid
v Vapour
w Aqueous buffer
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2.1.9 References
Absolom DR, Lamberti FV, Policova Z, Zingg W, Van Oss CJ, Neumann AW. 1983.
Surface thermodynamics of bacterial adhesion. Appl Environ Microbiol 46(1):90-7.
Anspach FB, Curbelo D, Hartmann R, Garke G, Deckwer WD. 1999. Expanded-bedchromatography in primary protein purification. J Chromatogr A 865(1-2):129-44.
Bierau H, Hinton RJ, Lyddiatt A. 2001. Direct process integration of cell disruption and
fluidised bed adsorption in the recovery of labile microbial enzymes. Bioseparation
10(1-3):73-85.
Bos R, Van der Mei HC, Busscher HJ. 1999. Physico-chemistry of initial microbial
adhesive interactions--its mechanisms and methods for study. FEMS Microbiol Rev
23(2):179-230.Brixius PJ. 2003. On the influence of feedstock properties and composition on process
development of expanded bed adsorption. PhD thesis.
Camesano TA, Logan BE. 2000. Probing electrostatic interactions using atomic force
microscopy. Environ Sci Technol 34(16):3354-3362.
Dainiak MB, Galaev IY, Mattiasson B. 2002. Polyelectrolyte-coated ion exchangers for
cell-resistant expanded bed adsorption. Biotechnol Prog 18(4):815-20.
Fernandez-Lahore HM, Geilenkirchen S, Boldt K, Nagel A, Kula MR, Thommes J. 2000.
The influence of cell adsorbent interactions on protein adsorption in expanded beds.
J Chromatogr A 873(2):195-208.
Fernandez-Lahore HM, Kleef R, Kula M, Thommes J. 1999. The influence of complex
biological feedstock on the fluidization and bed stability in expanded bed
adsorption. Biotechnol Bioeng 64(4):484-96.
Fernandez-Lahore HM, Lin DQ, Hubbuch JJ, Kula MR, Thommes J. 2001. The Use of Ion-
Selective Electrodes for Evaluating Residence Time Distributions in Expanded Bed
Adsorption Systems. Biotechnol. Prog. 17(6):1128-1136.
Feuser J, Walter J, Kula MR, Thommes J. 1999. Cell/adsorbent interactions in expanded
bed adsorption of proteins. Bioseparation 8(1-5):99-109.
Gallardo-Moreno AM, Gonzalez-Martin ML, Perez-Giraldo C, Garduno E, Bruque JM,
Gomez-Garcia AC. 2002. Thermodynamic analysis of growth temperature
dependence in the adhesion of Candida parapsilosis to polystyrene. Appl Environ
Microbiol 68(5):2610-3.
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Ganeva V, Galutzov B, Teissie J. 2004. Flow process for electroextraction of intracellular
enzymes from the fission yeast, Schizosaccharomyces pombe. Biotechnol Lett
26(11):933-7.
GEHealthCare. 2001. Cost comparison: expanded bed adsorption (EBA) vs conventionalrecovery in the industrial scale processing of proteins. Application note
STREAMLINE expanded bed adsorption 18-1150-21 AA:1.
Henriques M, Gasparetto K, Azeredo J, Oliveira R. 2002. Experimental methodology to
quantify Candida albicans cell surface hydrophobicity. Biotechnol Lett 24:1111–
1115.
Hubbuch J, Thommes J, Kula MR. 2005. Biochemical engineering aspects of expanded bed
adsorption. Adv Biochem Eng Biotechnol 92:101-23.
Kang S, Choi H. 2005. Effect of surface hydrophobicity on the adhesion of S. cerevisiae
onto modified surfaces by poly(styrene-ran-sulfonic acid) random copolymers.
Colloids Surf B Biointerfaces 10(46(2)):70-7.
Li B, Logan BE. 2004. Bacterial adhesion to glass and metal-oxide surfaces. Colloids Surf
B Biointerfaces 36(2):81-90.
Lin DQ, Brixius PJ, Hubbuch JJ, Thommes J, Kula MR. 2003. Biomass/adsorbent
electrostatic interactions in expanded bed adsorption: a zeta potential study.
Biotechnol Bioeng 83(2):149-57.
Lin DQ, Dong JN, Yao SJ. 2007. Target Control of Cell Disruption To Minimize the
Biomass Electrostatic Adhesion during Anion-Exchange Expanded Bed Adsorption.
Biotechnol Prog 23(1):162-7.
Lin DQ, Fernandez-Lahore HM, Kula MR, Thommes J. 2001. Minimising
biomass/adsorbent interactions in expanded bed adsorption processes: a
methodological design approach. Bioseparation 10(1-3):7-19.
Lin DQ, Zhong LN, Yao SJ. 2006. Zeta potential as a diagnostic tool to evaluate the biomass electrostatic adhesion during ion-exchange expanded bed application.
Biotechnol Bioeng 95(1):185-91.
Mattiasson B, Galaev I, Garg N. 1996. Polymer-shielded dye-affinity chromatography. J
Mol Recognit 9(5-6):509-14.
Mills AL, Herman JS, Hornberger GM, Dejesus TH. 1994. Effect of Solution Ionic
Strength and Iron Coatings on Mineral Grains on the Sorption of Bacterial Cells to
Quartz Sand. Appl Environ Microbiol 60(9):3300-3306.
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Northelfer F, Walter JK. 2002. A comparsion of STREAMLINE expanded bed adsorption
with the combined techniques of filtration and conventional fixed bed
chromatography for the capture of an Fc-fusion protein from CHO cell culture.
Application note streamline expanded bed adsorption 18(1144-87 AB):1.Ottewill RH, Shaw JN. 1972. Electrophoretic studies on polystyrene lattices. J Electroanal
Chem 37:133-142.
Sambrook J, Russell DW. 2006. The condensed protocols from Molecular cloning: a
laboratory manual. Cold Spring Harbor, N.Y: Cold Spring Harbor Laboratory Press.
v, 800 p. p.
Sharma PK, Rao KH. 2002. Analysis of different approaches for evaluation of surface
energy of microbial cells by contact angle goniometry. Adv Colloid Interface Sci
98(3):341-463.
Strevett KA, Chen G. 2003. Microbial surface thermodynamics and applications. Res
Microbiol 154(5):329-35.
Theodossiou I, Sondergaard M, Thomas ORT. 2001. Design of expanded bed supports for
the recovery of plasmid DNA by anion exchange adsorption. Bioseparation 10(1-
3):31-44.
Thommes J, Weiher M, Karau A, Kula M-R. 1995. Hydrodynamics and Performance in
Fluidized Bed Adsorption. Biotechnol Bioeng 48(4):367-374.
Van der Mei HC, Bos R, Busscher HJ. 1998. A reference guide to microbial cell surface
hydrophobicity based on contact angles. Colloids Surf B Biointerfaces 11(4):213-
221.
Van Oss CJ. 1994. Interfacial forces in aqueous media. New York: M. Dekker. viii,440p. p.
Van Oss CJ. 1995. Hydrophobicity of biosurfaces - origin, quantitative determination and
interaction energies. Colloids Surf B Biointerfaces 5:91-110.
Van Oss CJ. 1997. Hydrophobicity and hydrophilicity of biosurfactants. Curr Opin ColloidInterface Sci 2:503-512.
Van Oss CJ, Chaudhury MK, Good RJ. 1987. Monopolar surfaces. Adv Colloid Interface
Sci 28(1):35-64.
Van Oss CJ, Good RJ. 1988. Orientation of the water molecules of hydration of human
serum albumin. J Protein Chem 7(2):179-83.
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2.2 Colloid deposition experiments as a diagnostic tool forbiomass attachment onto bioproduct adsorbent surfaces
Canan Tari1† , Rami Reddy Vennapusa2† , Rosa B. Cabrera2, and Marcelo Fernández-Lahore2.
1Department of Food Engineering, Izmir Institute of Technology, Urla, Izmir 35430,Turkey.2Downstream Processing Laboratory, Jacobs University, Campus Ring 1, D-28759,Bremen, Germany.† These authors contributed equally to the work.
2.2.1 Abstract
BACKGROUND: Detrimental processing conditions can be expected in any downstream
operation where direct contacting between a crude feedstock and a reactive solid phase is
supposed to occur. In this paper we have investigated the factors influencing intact yeast
cells deposition onto anion- and cation- exchangers currently utilised for expanded bed
adsorption of biotechnological products. The aim of this study was two-fold: a) To confirm
previous findings relating biomass deposition with surface energetics according to the
XDLVO theory; and b) To provide a simple experimental tool to evaluate biomassdeposition onto process surfaces.
RESULTS: Biomass deposition experiments were performed on automated workstation
utilizing a packed-bed format. Two commercial ion-exchangers intended for the direct
capture of bioproducts in the presence of suspended biological particles were employed.
Intact yeast cells in the late exponential phase of growth were selected as model bio-
colloids. Cell deposition was systematically evaluated as a function of fluid phase
conductivity and quantitatively expressed as a biomass deposition parameter (α).
CONCLUSION:α ≤ 0.15 was established as criteria to reflect negligible biomass adhesion
to the process support(s). Biomass deposition experiments further confirmed predictions
made on the basis of free interfacial energy calculationsas per the extended DLVO
approach.
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2.2.2 Introduction
Detrimental processing conditions can be expected in any downstream operation where
direct contacting between a crude feedstock and a reactive solid phase is supposed to occur.
This type of unit operations has the potential to combine solids removal, productconcentration, and partial purification in a single processing step. However, it is already
known that suspended biological particles will interact with adsorbent materials. In the
particular case of Expanded Bed Adsorption (EBA) interaction phenomena may lead to the
development of poor system hydrodynamics and therefore, impaired sorption performance
under real process conditions (Hubbuch et al. 2005). Biomass deposition would also result
in increased buffer consumption (Northelfer and Walter 2002).
The principles of colloid chemistry can be applied to explain biomass-adsorbent attachment
at the local (particle) level (Van Oss 1994). Biomass adhesion to process supports has the
potential to be strongly influenced by long-range electrodynamic Lifshitz – van der Waals
(LW) and electrostatic (EL) and short-range acid-base (AB) interfacial interactions. EL
interactions arise from the existence of overlapping double layers of counter-ions near
charged surfaces in aqueous media and are accessible by determination of the zeta
potential. LW and AB forces are experimentally accessiblevia contact angle measurement
with three diagnostic liquids.
Earlier studies on biomass-adsorbent interactions pointed out that interactions between
(positively charged) anion exchangers and (negatively charged) biological particles resulted
the most problematic system to deal with. Due to the obvious electrostatic nature of such
interaction, a single property of these interacting bodies i.e. the zeta potential has been
recently proposed for a better understanding and prediction of biomass-adsorbent
interactions (Lin et al. 2003; Lin et al. 2006). It is now understood that Coulomb-typeinteraction are predominant when the basic nature of the process material and the
characteristics of the microbial species / strains is kept similar. Moreover, charge effects are
only predominant in deposition systems where strongly charged materials are under
consideration. Therefore, a single measure like the particle zeta-potential cannot be
considered a universal approach to process / material design. Some studies have found a
better correlation between surface energy, calculated by the three liquid contact angle
method, and microbial adhesion on different solid supports at constant solution chemistry
(Li and Logan 2004).
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The mechanistic understanding of the transport and deposition of microbial cell onto
natural and process surfaces has significant interest in various environmental and
bioprocess situations. A better description of the factors controlling the transport of
biological particles is important for the appropriate design of direct contact downstreamoperations, as well as, for the development of novel adsorbent materials. Traditionally,
microbial deposition has been studied employing packed-beds. A population of biological
particles is introduced into such systems and the suspended cell or cell-debris effluent is
monitored as a function of process time. This type of experiments can provide useful and
quantitative information when assessing factors like cell size and shape, microorganisms
strain, growth phase, bead size, surface coatings, fluid velocity, and ionic strength on cell
deposition onto process media (Tufenkji 2007).
Mathematical models of microbial transport in porous media most commonly utilises the
advection-dispersion equation as derived by mass balance principles (Brown and Jaffe
2001; Rijnaarts et al. 1996). A common approach to evaluate biomass deposition in
laboratory packed-bed experiments employs the “clean-bed” filtration model or colloid
filtration theory (CFT). This model is valid for steady-state systems which are initially free
of biomass particles and where axial dispersion can be neglected ( Pe ≥ 20) (Unice and
Logan 2000). Within the CFT, mass transport phenomena are accounted by the “single-
collector contact efficiency” (η0) while the physicochemical phenomena related to biomass
attachment are reflected by the “attachment efficiency parameter” (α) (Redman et al. 2004).
At larger biomass loads,α values are controlled not only by cell-support interactions but
also by the amount of previously attached biomass particles. This implies that attached
biomass particles onto the process surface can effectively reduce deposition by a so called
collector “blocking” effect (Rijnaarts et al. 1996). On the other hand, increased biomass
attachment can result from cell-to-cell aggregation a phenomena known as system
“ripening” (Nascimento et al. 2006).
In this paper we have investigated the factors influencing intact yeast cells deposition onto
anion- and cation- exchangers currently utilised for expanded bed adsorption of
biotechnological products. These two systems represent examples of “interacting” vs. “non-
interacting” situations, which are relevant in industrial practice. The aim of this study was
two-fold: a) To confirm previous findings relating biomass deposition with surface
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Utilising experimental data from breakthrough of cells from packed beds the attachment
efficiency parameter (α) can be calculated asα = k d / k d,fav(Redman et al. 2004).
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2.2.4 Results and Discussion
2.2.4.1 Physicochemical properties of the cell particles / beaded adsorbents
The electrokinetic potential of the interacting particles e.g. the yeast cells vs. the beaded
adsorbents were studied as a function of fluid phase conductivity. Figure 1 depicts zeta
potential values for intact yeast cells, cation-exchange beads, and anion-exchange beads in
phosphate buffers of varying conductivities. The zeta-potential has been reported as a main
parameter affecting yeast cell deposition onto beaded adsorbents, particularly onto anion-
exchangers (Lin et al. 2006). Intact yeast cells, harvested at the late exponential phase of
growth, showed zeta-potential values≈ -25 mV at very low buffer concentration (0.7
mS.cm-1). At standard ion-exchange mobile phase composition e.g.∼20 mM phosphate pH
7.6, zeta-potential values were -18 mV. Lower zeta-potential values were observed with
increasing conductivity i.e. -6 mV at 34 mS⋅cm-1. A similar trend was observed when
studying the effect of mobile phase conductivity on the electrokinetic behaviour of the
cation-exchanger beads. SP Sepharose fragments were utilised for such studies in order to
avoid errors derived from the settling of the intact adsorbent particles. Lower zeta-potential
values obtained were -36 mV (0.7 mS⋅cm-1) while maximum values were -14 mV (34
mS⋅cm-1).
A second factor recognized to influence biomass deposition onto process surfaces is cell or
cell-debris size and shape (Hubbuch et al. 2006). In this study, both factors are kept
constant since only intact yeast cells (8μm diameter) of spherical shape were utilised as
model biomass.
Besides electrostatic forces (EL), electrodynamic Lifshitz – Van der Waals forces (LW) are
known to mediate biomass interactions. The LW interaction, which is predominantlyattractive in microbial systems, is not influenced by the ionic strength (Bos et al. 1999) but
both the range and magnitude of the EL interactions decrease with increasing ionic strength
due to shielding of surface charges. LW forces between intact yeast cells and agarose-based
material can be described by a Hamaker constant (A). The value for A, in this particular
system, was previously calculated as 0.34k T from contact angle measurements; details will
be published elsewhere. Obtained Hamaker constant value are in agreement with assumed
values for various microbial systems (Bos et al. 1999).
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The so-called acid-base (AB) forces are also included in the XDLVO approach (Van Oss
1994). AB interactions were found to be a function of the nature of the process solid phase
onto which cell adhesion took place. For agarose-based supports and yeast cells an average
ΔGAB value was calculated as +30 mJ⋅m-2, indicating the repulsive nature of the AB
component (Vennapusa et al. 2006). This value is valid at closest distance of approximation
between the interacting bodies (1.57Å).
Figure 1: Zeta potentials of intact yeast cells and adsorbent beads as a function of fluid phase conductivity at pH 7.6.▲ , intact yeast cells;■, SP beads; ●, DEAE beads.
2.2.4.2 Biomass deposition experiments
Deposition experiments were performed in an automated chromatographic system for
increase throughput and convenience of use. Figure 2 depicts the schematic illustration of
the chromatographic set up. In packed-bed systems, physical straining of bio-colloids is
considered to be significant on the basis of geometrical consideration when d p/dc > 0.05
(Rijnaarts et al. 1996). In the system under study in this work d p/dc ≈ 0.04 and thus physical
straining can be neglected. Although straining has been observed when d p/dc values were as
low as 0.002 (Tufenkji et al. 2004) experiments performed with the cation-exchange
material supported the previous assumption . No physical entrapment of the bio-colloids
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(a)
(b)
Figure 3: Typical experimental data as obtained from packed-bed experiments utilizingchromatographic beads as colloid collectors. Intact yeast cells were employed as a model.(a) Favorable deposition onto DEAE functionalized beads, (b) Unfavorable deposition ontoSP functionalized support. The arrows indicate (A) Cell pulse injection and (B) Columnregeneration with 0.5 mol L-1 NaOH.
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Employing the above described methodology, systematic studies were performed to
evaluate yeast cell deposition onto anion- and cation-exchangers. Figure 4a shows the
family of deposition curves obtained by variation of fluid phase conductivity when DEAE-
Streamline™ beads were utilised as collectors. These adsorbent beads are weak anionexchangers and thus they are positively charged. Results are presented as normalised
concentration (C/C0) vs. pore volumes. In order to calculate C/C0 absorbance data was
employed since cell concentration was linearly related to such measurement within the
concentration range involved in this study. The length of the biomass pulse, equivalent to∼
10 PV, was sufficient to produce a semi-complete breakthrough of suspended biological
particles i.e. the effluent cell concentration never reached C0. It can be observed that total
cell deposition took place at very-low to low conductivity values e.g. almost no cells were
detected when conductivity was≤ 2.0 mS⋅cm-1. An increased conductivity of the mobile
phase has allowed for a progressive increased in the number of cells leaving the system.
These results can be explained considering a predominant role of EL forces in a system
characterised by collectors and colloids harbouring opposite charges. Since other forces
were kept constant, as well as the colloid size, the only mechanism expected to govern
deposition is related to Coulomb-type effects. This is in agreement with previous studies
focusing on zeta-potential as a diagnostic parameter for biomass / support interactions (Lin
et al. 2006).
Similar experiments were performed utilising SP- Streamline™(negatively charged) beads.
The biomass breakthrough curves are presented in Figure 4b. As it can be observed from
this Figure, lower conductivity values in the fluid phase have resulted in negligible
deposition of cells onto the cation-exchange collectors. However, increased conductivity (≥
14 mS⋅cm-1) has promoted biomass deposition onto the cation-exchanger. This finding
might have an impact on bioprocess design since this material has been considered as “non-interacting” with particulate feedstock (Feuser et al. 1999). However, deposition of intact
yeast cells onto SP- Streamline™beads can be inferred from XDLVO calculations as
shown below. Practical consequences related to this behaviour during EBA capture of
bioproducts could arise during product elution i.e. since high conductivity buffers are
commonly employed, aggregative fluidization may develop resulting in a diluted product
fraction.
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Figure 4: Normalized cell-effluent concentrations plotted against pore volumes pumpedthrough the packed bed at different fluid phase conductivity values (pH 7.6). (a) DEAEyeast cells. (b) SP / yeast cells. × 0.66 mS cm-1; 2.00 mScm-1; 8.4 mScm-1 (5.5 mScm-1 in fig. b); 14.00 mS cm-1; 36 mS cm-1.
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2.2.4.3 Parameter calculation
Bio-colloid depositions experiments, as shown in Figure 4, depict cell breakthrough
behaviour compatible with collector blocking or cell release from the packed-bed system.
This is demonstrated by the fact that in most experiments the normalised cell concentration(C/C0) did not raise a steady-state value after the initial dispersive curve region. Therefore,
the initial clean bed C/C0 for each experiment was taken for parameter calculations. This
allowed the application of the colloid filtration theory which is valid under clean bed
conditions (Redman et al. 2004).
Table 1 present calculated values for both k d (s-1) and α (-) as a function of fluid phase
conductivity. k d,fav data corresponds to the experimental run performed with the DEAE-Streamline™beads as collectors under lowest conductivity (0.6 mS⋅cm-1).
Table 1: Calculated parameters from packed-bed experiments where chromatographicsupports were employed as cell collectors. Calculation were performed according to(Redman et al. 2004).
DEAE Streamline TM - Intact yeast
SP StreamlineTM
– Intact yeast
Conductivity( mS cm-1 ) C/C o k d α
0.66 0.003 0.246 1.002.0 0.006 0.211 0.8588.4 0.075 0.107 0.43514.0 0.244 0.058 0.23638.6 0.254 0.056 0.229
Conductivity( mS cm-1 ) C/C o k d α
0.66 0.654 0.017 0.0712.0 0.568 0.023 0.0955.5 0.519 0.027 0.11014.0 0.445 0.033 0.136
38.6 0.333 0.045 0.184
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Evidence is suggesting that simple models for calculatingα based on deposition in the
secondary energy minimum can result in accurate prediction of biomass attachment to
porous media (Tufenkji 2007). For the DEAE-Streamline™ / yeast system, α values
decreased from∼1 at very low conductivity to 0.23 at∼39 mS⋅cm-1
. On the other hand, for the SP-Streamline™/ yeast system,α values increased from 0.07 (∼0.6 mS⋅cm-1) to 0.18 (∼
39 mS⋅cm-1). As a referenceα = 1, has the meaning of complete cell deposition onto the
packed collectors. Figure 5 summarizes these results in a graphic form. Minimumα values
were obtained for the anion-exchanger system, which are nearly equivalent toα values
obtained for SP-Streamline™beads at 39 mS⋅cm-1. These results indicate that biomass
deposition experiments are an appropriate design tool to evaluate biomass deposition onto
process surfaces. On the basis of the preceding experimental evidence,α is proposed as adiagnostic parameter that provides information on biomass attachment onto process
surfaces. Applying the proposed methodology, changes inα can be effectively utilised to
monitor biomass-support interactions even in such cases where such interaction was
overlooked in the past (Feuser et al. 1999).
Figure 5: Changes in the attachment efficiency parameter (α) as a function of fluid phaseconductivity. Deposition of intact yeast cell was studied for () DEAE and ( ) SPchromatographic materials.
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2.2.4.4 Bio-colloid deposition in the secondary minimum
Figure 6 depicts total interfacial energy profiles as a function of the distance between two
interacting bodies (U vs. H) in aqueous media i.e. diluted buffer solutions. Calculations
were performed considering the role of LW, AB, and EL forces, as previously reported(Bos et al. 1999) by utilising data from contact angle measurement and zeta potential
determinations (Vennapusa et al. 2006). Therefore, the presented profiles are in accordance
to the extended DLVO approach. Since the radius of the chromatographic beads is much
higher than the radius of the intact yeast cell, total free energy was computed assuming a
plane-to-sphere geometry.
Figure 6a represents XDLVO energy profiles for the system where a DEAE-Streamline™
bead interacts with an intact yeast cell. It can be observed that a secondary energyminimum exists at a distance of ≈ 5nm, where deposition of the cell particle can occur. This
is essentially a reversible interaction that can be overcome by sufficient energy input for
example, in the form of shear or hydrodynamic stress. The magnitude (depth) of the energy
pocket, however, increases upon modification (reduction) of the liquid phase conductivity.
As a consequence, stronger deposition of cell particles is expected when working with
diluted buffers than when working with buffers / salt solutions with higher conductivities.
This situation is reflected by the biomass deposition experiments as presented in Figure 4a.Therefore, this kind of experiments can confirm the trends predicted by XDLVO
calculations. Both U vs. H calculations and deposition experiments are in full agreement
with the known biomass-interaction behaviour for DEAE-Streamline™(Fernandez-Lahore
et al. 2000; Fernandez-Lahore et al. 1999; Lin et al. 2001). Moreover, biomass deposition
experiments can offer a simple way to access interfacial phenomena in aqueous media.
These phenomena have relevance from the bioprocess point of view and have important
consequences for appropriate process optimisation and material design.
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Figure 6: Calculated XDLVO total interaction energy as a function of separation distance.a) DEAE / yeast cells b) SP / yeast cells. A family of curves representing variations in theconductivity value of the fluid phase is shown (— ) 2 mS cm-1; (— ) 4 mS cm-1; (— ) 9.55mS cm-1; (— )15.1 mS cm-1; (— ) 34 mS cm-1).
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Figure 7: Correlation graph between the attachment efficiency parameter (α) and the totalinteraction energy according to the XDLVO approach.
Besides biomass deposition, as expressed by the deposition parameter (α), the cell breakthrough profiles observed in Figure 4 might indicated that a blocking phenomenon is
also occurring in the systems under study. Blocking refers to the fact that cells which are
already attached to the solid support can interfere with the attachment of further cells being
contacted with the adsorbent beads. This phenomenon, usually accounted by the so called
excluded area parameter (β) has important environmental implications (Bolster et al. 2001).
During direct capture of bioproducts, due to the presence of much higher concentration of
biomass (∼8 % wet weight) in contact with the beaded adsorbents, blocking can besupposed to play a less significant role. Therefore, modeling approaches have been kept
simple enough so as to provide a single parameter (α), which reflects biomass attachment
as an important event having practical consequences for the performance of a direct
capturing unit operation.
Biomass multilayer formation would also occur at long contact time and / or high biomass
concentration, which is not the case for the biomass deposition experiment as described
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here. This phenomenon could be more important in cases where cell-to-cell aggregation or
“ripening” is favored, like during hydrophobic interaction chromatography. Understanding
of cell-to-cell aggregation would require independent experimental methods to be evaluated
(Ramachandran and Fogler 1998).
2.2.5 Conclusions
Biomass deposition experiments were performed in an automated workstation utilizing a
packed-bed format and intact yeast cells in the late exponential phase of growth as biomass
model.
Under carefully controlled experimental conditions, removal of biomass particles onto
chromatographic collectors was assumed to be dependent on a) mass transfer i.e. the
transfer of a biological particle from the bulk liquid phase to the adsorbent bead and b) the
capture of a biological particle onto an adsorbent bead by interfacial forces. Straining was
neglected since the size of the biomass-derived particles is much smaller than the process
beads. Detachment was also supposed to be insignificant under laminar flow conditions.
The description of “aggregation” (cell-to-cell), which implies multilayer adhesion, was
omitted since this phenomenon takes place at high biomass concentrations and long contact
times.
Cell deposition was systematically evaluated as a function of fluid phase conductivity and
quantitatively expressed as a biomass deposition parameter (α). Deposition onto
commercial anion-exchanger beads was observed to increase with decreasing conductivity
values in the mobile phase. The opposite behavior was observed when cation-exchange
beads were utilized as collectors in the packed-bed system. In both cases, experimental
deposition studies confirmed predictions based on the free energy of interaction accordingto the XDLVO theory. Coulomb-type interactions were dominating since EL forces are
affected by the ionic strength of the aqueous media surrounding the interaction bodies.
Other forces, which are relevant to the evaluation of biomass deposition, were kept
constant. The evaluation of LW and AB forces is mandatory when comparing microbial
strains and / or process materials apart from the model system employed in this work.
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d p Diameter of yeast cells [m]
EBA Expanded bed adsorption
EL Electrostatic interaction
H Separation distance [m]
k d Deposition rate coefficient [s-1]
k d fav Deposition rate coefficient for favorable deposition [s-1]
L Length of column [m]
PV Pore volume [ml]
P e Peclet number [-]
Re Reynolds number [-]
SP Sulphopropyl-
U Superficial fluid velocity [ms-1]
U Total interaction energy [kT]
XDLVO Extended DLVO
Greek letters
ε Porosity [-]
α Attachment efficiency parameter [-]
ο η Single collector contact efficiency [-]
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2.2.8 Referances
Bolster CH, Mills AL, Hornberger GM, Herman JS. 2001. Effect of surface coatings, grain
size, and ionic strength on the maximum attainable coverage of bacteria on sand
surfaces. J Contam Hydrol 50(3-4):287-305.Bos R, Van der Mei HC, Busscher HJ. 1999. Physico-chemistry of initial microbial
adhesive interactions--its mechanisms and methods for study. FEMS Microbiol Rev
23(2):179-230.
Brown DG, Jaffe PR. 2001. Effects of Nonionic Surfactants on Bacterial Transport through
Porous Media. Environ Sci Technol 35(19):3877-3883.
Fernandez-Lahore HM, Geilenkirchen S, Boldt K, Nagel A, Kula MR, Thommes J. 2000.
The influence of cell adsorbent interactions on protein adsorption in expanded beds.J Chromatogr A 873(2):195-208.
Fernandez-Lahore HM, Kleef R, Kula M, Thommes J. 1999. The influence of complex
biological feedstock on the fluidization and bed stability in expanded bed
adsorption. Biotechnol Bioeng 64(4):484-96.
Feuser J, Walter J, Kula MR, Thommes J. 1999. Cell/adsorbent interactions in expanded
bed adsorption of proteins. Bioseparation 8(1-5):99-109.
Ganeva V, Galutzov B, Teissie J. 2004. Flow process for electroextraction of intracellular
enzymes from the fission yeast, Schizosaccharomyces pombe. Biotechnol Lett
26(11):933-7.
Hubbuch JJ, Brixius PJ, Lin DQ, Mollerup I, Kula MR. 2006. The influence of
homogenisation conditions on biomass-adsorbent interactions during ion-exchange
expanded bed adsorption. Biotechnol Bioeng 94(3):543-53.
Hubbuch JJ, Thommes J, Kula MR. 2005. Biochemical engineering aspects of expanded
bed adsorption. Adv Biochem Eng Biotechnol 92:101-23.
Li B, Logan BE. 2004. Bacterial adhesion to glass and metal-oxide surfaces. Colloids Surf
B Biointerfaces 36(2):81-90.
Lin DQ, Brixius PJ, Hubbuch JJ, Thommes J, Kula MR. 2003. Biomass/adsorbent
electrostatic interactions in expanded bed adsorption: a zeta potential study.
Biotechnol Bioeng 83(2):149-57.
Lin DQ, Fernandez-Lahore HM, Kula MR, Thommes J. 2001. Minimising
biomass/adsorbent interactions in expanded bed adsorption processes: a
methodological design approach. Bioseparation 10(1-3):7-19.
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Lin DQ, Zhong LN, Yao SJ. 2006. Zeta potential as a diagnostic tool to evaluate the
biomass electrostatic adhesion during ion-exchange expanded bed application.
Biotechnol Bioeng 95(1):185-91.
Nascimento AG, Totola MR, Souza CS, Borges MT, Borges AC. 2006. Temporal and
spatial dynamics of blocking and ripening effects on bacterial transport through a
porous system: A possible explanation for CFT deviation. Colloids Surf B
Biointerfaces 53(2):241-244.
Northelfer F, Walter JK. 2002. A comparison of STREAMLINE expanded bed adsorption
with the combined techniques of filtration and conventional fixed bed
chromatography for the capture of an Fc-fusion protein from CHO cell culture.
Application note STREAMLINE expanded bed adsorption 18 1144-87 AB.
Ottewill RH, Shaw JN. 1972. Electrophoretic studies on polystyrene lattices. J Electroanal
Chem 37:133-142.
Ramachandran V, Fogler HS. 1998. Multilayer Deposition of Stable Colloidal Particles
during Flow within Cylindrical Pores. Langmuir 14(16):4435-4444.
Redman JA, Walker SL, Elimelech M. 2004. Bacterial Adhesion and Transport in Porous
Media: Role of the Secondary Energy Minimum. Environ Sci Technol 38(6):1777-
1785.
Rijnaarts HHM, Norde W, Bouwer EJ, Lyklema J, Zehnder AJB. 1996. BacterialDeposition in Porous Media Related to the Clean Bed Collision Efficiency and to
Substratum Blocking by Attached Cells. Environ Sci Technol 30(10):2869-2876.
Tufenkji N. 2007. Modeling microbial transport in porous media: Traditional approaches
and recent developments. Adv Water Resour 30(6-7):1455-1469.
Tufenkji N, Elimelech M. 2004. Correlation Equation for Predicting Single-Collector
Efficiency in Physicochemical Filtration in Saturated Porous Media. Environ Sci
Technol 38(2):529-536.Tufenkji N, Miller GF, Ryan JN, Harvey RW, Elimelech M. 2004. Transport of
Cryptosporidium Oocysts in Porous Media: Role of Straining and Physicochemical
Filtration. Environ Sci Technol 38(22):5932-5938.
Unice KM, Logan BE. 2000. Insignificant role of hydrodynamic dispersion on bacterial
transport. J Environ Engin 126(6):491-500.
Van Oss CJ. 1994. Interfacial forces in aqueous media. New York: M. Dekker. viii,440 p.
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Vennapusa RR, Cabrera R, Ganeva V, Fernandez-Lahore HM. 2006. Direct capture from
electro-permeabilized yeast cells on expanded beds: a biomass-adsorbent interaction
study via surface energetics. Book of abstracts, 6th European Symposium on
Biochemical Engineering Science.
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2.3 Surface energetics to assess biomass attachment ontohydrophobic interaction adsorbents in expanded beds
Rami Reddy Vennapusa1, Canan Tari2, Rosa Cabrera1, and Marcelo Fernandez-Lahore1*
1Downstream Processing Laboratory, Jacobs University gGmbH, Campus Ring 1, D-28759, Bremen, Germany.2Department of Food Engineering, Izmir Institute of
Technology, Urla, Izmir 35430, Turkey.
2.3.1 Abstract
Cell-to-support interaction and cell-to-cell aggregation phenomena have been studied in a
model system composed of intact yeast cells and Phenyl-Streamline adsorbents. Biomass
components and beaded adsorbents were characterized by contact angle determinationswith three diagnostic liquids and zeta potential measurements. Subsequently, free energy of
interaction vs. distance profiles between interacting surfaces was calculated in the aqueous
media provided by operating mobile phases. The effect of pH and ammonium sulphate
concentration within the normal operating ranges was evaluated. Calculation indicated that
moderate interaction between cell particles and adsorbent beads can develop in the presence
of salt. Cell-to-cell aggregation was suspected to occur at high salt concentration and
neutral pH. Predictions based on the application of the XDLVO approach were confirmed by independent experimental methods like biomass deposition experiments and laser
diffraction spectroscopy. Understanding biomass attachment onto hydrophobic supports
can help in alleviating process limitations normally encountered during expanded bed
adsorption of bioproducts.
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2.3.2 Introduction
Expanded Bed Adsorption (EBA) has been proposed as anintegrative downstream
processing technology allowing the direct capture of targeted species from an unclarified
feedstock e.g. a cell containing fermentation broth. This unit operation has the potential to
combine solids removal, product concentration, and partial purification in a single
processing step. The application of EBA implies, however, that intact cell particles or cell
debris present in the feedstock will interact –in a minor or larger extent- with fluidized
adsorbent beads. It is already known that interaction between biomass and the adsorbent
phase may lead to the development of poor system hydrodynamics and therefore, impaired
sorption performance under real process conditions. Moreover, biomass interaction would
result in increased buffer consumption in order to remove and wash away sticky biological
particles. Biomass components can also mask binding sites thus reducing their availability
to the targeted species. These phenomena i.e. decreased sorption performance and buffer
consumption is detrimental to cost-efficient processing utilizing expanded bed adsorption
(Fernandez-Lahore et al. 1999; Lin et al. 2001).
Previous studies on biomass-adsorbent interactions were restricted to simple diagnostic
tests to determine the extent of cell –or cell debris- attachment to the desiredchromatographic supports (Feuser et al. 1999). More recently, a single property of the
suspended biological particle i.e. the zeta potential has been proposed for a better
understanding and prediction of biomass-adsorbent interactions during expanded bed
adsorption. Since then a number of studies has been developed to illustrate the usefulness
of this approach when adsorption is performed onto anion-exchangers (Lin et al. 2003; Lin
et al. 2006). Such systems are obviously dominated by Coulomb-type interactions and
therefore, non-electrostatic interactions are anticipated to play a minor role (Vergnault et al.2007).
Experimental evidence gathered by many authors has addressed the importance of non-
electrostatic forces for biomass adhesion to process surfaces in the broader context
provided by a group of systems of technical and environmental relevance. For example,
hydrophobic interaction as measured by partition tests has been proposed as a generalized
assay to measure adhesion-potential of bacteria to low-energy surfaces (Stenstrom 1989).Complementarily, differences in the hydrophobic surface characteristics of bacterial strains
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were revealed by hydrophobic interaction chromatography (Smyth et al. 1978). Recently,
acid-base interactions have been employed to understand yeast deposition onto chemically
modified substrates (Kang and Choi 2005). However, very little is known on biomass
attachment onto chromatographic materials like hydrophobic interaction media (HIC) under
real downstream process conditions. The mentioned chromatographic mode represents a
widely utilized industrial operation (Mahn and Asenjo 2005), which is amenable for direct
sequestration of bioproducts. Since sorption performance limitations were already observed
due to biomass interference during HIC-based EBA, a better understanding and control of
such phenomena is needed (Smith et al. 2002).
A more comprehensive approach to understand biomass deposition onto chromatographic
supports has been proposed by utilizing principles of colloid theory to explain biomass-
adsorbent attachment at the local (particle) level (Vennapusa et al. 2008). This approach is
based on extended DLVO calculations performedvia experimentally determination of
contact angles and z-potential values for the interacting surfaces or particles. The
comprehensive method takes into account several types of possible interaction forces i.e.
Lifshitz-Van der Waals (LW) and acid-base (AB) and, therefore, it is not limited to those
purely electrostatic in nature (EL). Biomass adhesion behavior onto chromatographic beads
predicted on the basis of XDLVO calculations was validated by independent biomassdeposition experiments (Tari et al. 2008).
The aim of this paper was to contribute to a deeper understanding of biomass-adsorbent
interactions to further open the pave for optimized EBA processing in industry. Studies
targeted biomass adhesion to hydrophobic interaction materials which have not been
extensively studied so far. The physicochemical properties of biomass-derived material,
taken as colloidal particles, vs. the physicochemical properties of the adsorbent beads,taken as a process surface, were determined indirectlyvia contact angle and zeta potential
measurements. Subsequently, total interfacial interaction energy values were calculated as a
function of surface distance in aqueous media e.g. process buffer. Cell-to-support
interactions and cell-to-cell aggregation phenomena were independently confirmed by
colloid deposition experiments and laser diffraction spectroscopy, respectively.
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2.3.3 Materials and Methods
2.3.3.1 Materials
Chromatographic matrices (Phenyl Sepharose FF, high substitution; Phenyl Streamline) andcolumns (Tricorn 5/50) were purchased from GE Health Care (Munich, Germany).α-
bromonaphtalene and formamide were obtained from Fluka (Buchs, Switzerland). Water
was Milli-Q quality. All other chemicals were analytical grade.
2.3.3.2 Generation of biomass
Yeast cells (Saccharomyces cerevisiae ) wild strain was utilized. Five ml of 24 h culture
were inoculated in 500 ml of 3.5 % (w/v) YES medium (yeast extract with supplements of yeast extract, 5 g l-1; glucose, 30 g l-1; 225 mg l-1 adenine, histidine, leucine, uracail and
lysine hydrochloride) and grown at 30oC. Cells are harvested at late exponential phase by
centrifugation, and washed three times with 10mM phosphate buffer solutions, as
previously described (Ganeva et al. 2004). Cells were employed immediately after
preparation for further experimental measurements or routines.
2.3.3.3 Contact angle measurements
Preparation of intact yeast cells for contact angle measurements was performed as
described (Henriques et al. 2002). To evaluate the effect of pH, washed cells were
suspended to 10% (w/v) in 20mM phosphate buffer, pH 7or 50mM sodium acetate buffer,
pH 4 and to evaluate the effect of salt concentration, biomass was suspended in 20mM
phosphate buffer (pH 7) and 50mM sodium acetate buffer (pH 4) containing added
ammonium sulphate (0.2, 0.4, 0.8, 1.2, 1.6 and 2.0M). Cells were equilibrated in the
appropriate buffer condition and the suspension subsequently poured onto agar platescontaining 10% glycerol and 2% agar-agar. The plate was allowed to dry for 24-36 hours at
room temperature on a properly leveled surface free from dust. Salt crystallization was
avoided. Agar plates without cell spreads were utilized as control.
Contact angles were measuredas per the sessile drop method (Sharma and Rao 2002)
utilizing a commercial goniometric system (OCA 20, Data Physics instruments GmbH,
Filderstadt, Germany). The three diagnostic liquidsα-bromonaphtalene, formamide, and
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water were employed (Bos et al. 1999). All the measurements were performed in triplicate
and at least 20 contact angles per samples were measured.
Contact angle determination on buffer-equilibrated chromatographic beads was performed
utilizing the same physicochemical conditions and experimental procedures described for
cell particles. Previous to pouring onto the agar plates, matrix beads were frozen in liquid
nitrogen and crushed mechanically. Crushing efficiency was assessed by microscopic
examination and particle size determination so as to assure particle fragment diameters≤ 10
μm. Phenyl Sepharose (high-sub) was utilized. Square pieces of the agar supported
chromatographic bead fragments were utilized for measuring contact angles.
2.3.3.4 Zeta potential determination
Zeta-potential measurements were performed with a ZetaSizer Nano-ZS (Malvern
instruments, Worcestershire, United Kingdom), as previously described (Vennapusa et al.
2008). Zeta-potential values were gathered employing biomass pretreated as described
before (under 2.3.3.3) and utilizing the same buffers utilized for contact angle
determination.
Zeta-potential values for crushed and equilibrated chromatographic beads were calculated
from the electrophoretic mobility data according the Smoluchowski’s equation (Ottewill
and Shaw 1972). Data was gathered under identical buffer compositions as shown for
biomass related determinations.
2.3.3.5 Particle size determination and cell aggregation behavior
Particle size determinations and cell aggregation studies were performed by laser diffraction employing a MasterSizer 2000, hydro 2000 G (Malvern instruments,
Worcestershire, United Kingdom), according to manufacturer instructions. Cell aggregation
was studied as a function of pH and ammonium sulphate concentration utilizing the buffers
systems already described. For each condition, kinetic studies were performed within a time
interval of 60 minutes (Voloshin et al. 2005). Measurements were performed utilizing cell
suspensions having an optical density≈ 0.1 for better reproducibility.
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Visual inspection of aggregate formation was performed with a confocal laser scanning
microscope, equipped with argon and helium/neon mixed gas laser with excitation
wavelengths of 488 or 543 nm (LSM 510, Carl Zeiss, Oberkochen, Germany). Washed
yeast cells in 20 mM phosphate buffer (pH 7) or buffered 1.6 M ammonium sulphate
solution were mounted on glass slides and observed. Scans at a resolution of 1024 x 1024
pixels were taken in the line-averaging mode. Micrographs were stored in LSM format
(Carl Zeiss LSM Image Browser).
2.3.3.6 Bio-colloid deposition experiments
Biomass deposition experiments were performed automatically employing an ÄKTA
Explorer 100 system (GE Health Care, Munich, Germany) as previously described (Tari etal. 2008). These experiments were run by introducing a population of yeast cells particles is
introduced into a system composed of collector (adsorbent) beads; the suspended biomass
effluent is monitored as a function of process time. This type of experiments can provide
useful and quantitative information when assessing factors like cell size and shape,
microorganisms strain, growth phase, bead size, surface coatings, fluid velocity, and ionic
strength on cell deposition onto process media (Tari et al. 2008). A common approach to
evaluate biomass deposition in laboratory packed-bed experiments employs the “clean-bed”
filtration model (CBFM). In this case, mass transport phenomena are accounted by the
“single-collector contact efficiency” (η0) while the physicochemical phenomena related to
biomass attachment are reflected by the “attachment efficiency parameter” (α).
Streamline Phenyl materials (high-sub) were packed in commercial chromatographic
columns (5 mm internal diameter, 50mm length). The quality of the packing was evaluated
by residence time distribution analysis employing 1% acetone as tracer (Bak and Thomas
2007). Biomass deposition studies were done by injecting a 4 ml biomass pulse (OD @ 600
nm ≈ 0.8 AU). Experiments were performed utilizing 20 mM phosphate buffer pH 7 or 50
mM acetate buffer pH 4. Buffers contained various amounts of ammonium sulphate as
added salt (0.0, 0.4, 0.8, 1.2, 1.6, 2.0 M). The operational flow rate was 76.4 cm.h-1.
Particle breakthrough curves were obtained by monitoring the effluent suspensions at 600
nm. On the basis of such data, the biomass deposition parameter (α) was calculated
(Redman et al. 2004). Biomass deposition experiments were performed in triplicate and
showed to be reproducible within ± 20%.
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2.3.3.7 Energy-distance profile calculations
The total interaction energy between a colloidal particle and a solid surface can be
expressed in terms of the extended DLVO theory as:
ABmwc
ELmwc
LW mwc
XDLVOmwc U U U U ++= (1)
where UXDLVO is the total interaction energy in aqueous media, ULW is the LW interaction
term, and UEL is the EL interaction term. The subscriptm is utilized for the
chromatographic matrix (adsorbent bead), w refers to the watery environment, and c to the
colloidal (cell) particle. A third short-range (≤ 5 nm) Lewis AB term is included to account
for “hydrophobic attractive” and “hydrophilic repulsive” interactions (Van Oss 2003).
Material surface energy parameters (tensions) can be calculated from contact angle
measurements utilizing three diagnostic liquids, according to (Van Oss 1994). In turn, this
data can be employed to evaluate the free energy of interaction between two defined
surfaces (ΔGLW and ΔGAB). ΔG represents here the interaction energy per unit area
between two (assumed)infinite planar surfaces bearing the properties of the adsorbent bead
and the cell (interaction) or two cells (aggregation), respectively. Interaction between anyof these two surfaces are evaluated at a closest distance of approximation (h0 ≈ 0.158 nm)
(Bos et al. 1999). When integrated into mathematical expressions accounting the geometric
constraints existing between two interacting bodies,ΔG values can be utilized to calculate
the corresponding energy-distance profile (U vs. H). Details of this procedure were
published (Bos et al. 1999; Vennapusa et al. 2008).ΔGLW are also related to the Hamaker
constant, as follows:
LW Gh A Δ−= 2012π (2)
UEL energy-distance profile can be calculated, assuming either plate-sphere or sphere-
sphere geometry, upon experimental determination of particle zeta potential values. Zeta
potential values are measured by electrophoretic mobility experiments (Vennapusa et al.
2008). Calculations were performed employing a commercial software package (GraphPad
Prism, GraphPad Software Inc., San Diego, CA, USA).
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2.3.4 Results and discussions
2.3.4.1 Contact angle measurements and surface energy components
The diagnostic liquids water, formamide, andα-bromonaphtalene were employed tomeasure contact angles onto homogeneous lawns of the materials under study i.e. intact
yeast cells or crushed Phenyl-Sepharose beads. The sessile drop technique was employed.
The utilization of the agar plate method assured that contact angle values were obtained for
the mentioned materials in the hydrated state. Diagnostic liquids were chosen to have a
higher surface tension than the sample materials so as to allow for stable drop formation
and accurate contact angle determination. Both materials were carefully equilibrated with
either 20 mM phosphate buffer (pH 7) or 50 mM acetate buffer (pH 4), which are bufferscommonly encountered as mobile phases during hydrophobic interaction chromatography
(HIC). Since conditions for binding proteins and macromolecules onto this particular
chromatographic media are usually found at increased concentrations of ammonium
sulphate i.e. within the range 0.2 - 2.0 M, this salt was included during sample preparation.
Therefore, contact angles with three different liquids were performed as a function of pH
and salt concentration so as to evaluate material(s) properties within the normal HIC
operational range.
Table 1 summarizes the contact angle values obtained after measurements performed onto
homogeneous layers of intact yeast cells at pH 7 and pH 4. The agar plate technique
utilized allowed the measurement of contact angles under the assumption that only bound
water is present in the sample materials. Irrespective of pH (phosphate buffer pH 7 vs.
acetate buffer pH 4) and salt concentration (the ammonium sulphate concentration
increased from 0 to 2 M in the corresponding buffer solution), data gathered for contact
angles measured with both water and formamide overall showed low and nearly constant
values. Average values for water were≈ 10 and for formamide≈ 12. This indicates the very
hydrophilic nature of the samples. On the contrary, contact angles values gathered withα-
bromonaphtalene decreased from≈ 54 to ≈ 30 and from≈ 46 to ≈ 30 at pH 7 and pH 4,
respectively, upon addition of salt. A more progressive decrease in the contact angle values
was observed -as a function of salt concentration- at pH 7 than at pH 4. In the later case,
values for contact angles at varying salt concentrations tended to keep a constant level (≈
30) a condition which differentiates from the contact angle measured in plain buffer
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solution (≈ 46). This indicates that a non-polar liquid can be employed to discriminate
between biomass types or conditions in relation to surface hydrophobic character (Butkus
and Grasso 1998).
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Table 2 shows contact angle values obtained by performing measurements onto layered
fragments (< 10µm) of the hydrophobic interaction media, Phenyl-Sepharose. This method
was utilized since for soft gel particles other approaches e.g. the capillary raise method are
difficult to implement. Moreover, measurements onto layered materials showed good
reproducibility i.e within ±10% in triplicate measurements (Table 2). As described with
biomass, a range of conditions was explored. At pH 7 contact angle values were≈ 6-7 for
water and ≈ 8-11 for formamide, irrespective of salt concentration. On the other hand, a
step change in the contact angle withα-bromonaphtalene from≈ 48 (no salt) to≈ 30 (0.2 –
2.0 M ammonium sulphate) was noticed. At pH 4 recorded contact angle values were≈ 7-8
with water and≈ 9-10 with formamide but observed values withα-bromonaphtalene were
progressively reduced from≈ 36 (no salt) to≈ 22 (2.0 M ammonium sulphate). As a whole,these results stressed the known hydrophilic nature of the chromatographic beads, which
are composed by an agarose backbone. Contact angles values observed with the apolar
liquid also indicate an increased hydrophobic character in the presence of ammonium
sulphate.
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R e s u l t s
1 0 1
T a b l e 2 : C o n t a c t a n g l e v a l u e s
f o r P h e n y l - S e p h a r o s e p a r t i c l e s
i n 2 0 m
M p h o s p h a t e
b u f f e r p H
7 , 5 0 m
M a c e t a t e
b u f f e r p H
4 a s a
f u n c t i o n o f
s a l t c o n c e n t r a t i o n .
( N H 4 ) 2 S O 4
( M )
W
a t e r ( ◦ )
F o r m a m
i d e
( ◦ )
α - B r o m o n a p h t e l e n e
( ◦ )
p H 7
p H 4
p H 7
p H 4
p H 7
p H 4
0 . 0
6 . 0 ± 1 . 0
7 . 0 ± 1 . 0
1 0 . 0
± 1 . 0
9 . 0 ± 1 . 0
4 8 . 0 ± 4 . 8
3 6 . 0 ± 3 . 5
0 . 2
6 . 0 ± 1 . 0
7 . 3 ± 0 . 5
8 . 0 ± 1 . 0
1 0 . 0 ± 1 . 0
2 8 . 0 ± 1 . 0
2 8 . 5 ± 0 . 5
0 . 4
6 . 0 ± 1 . 0
8 . 0 ± 1 . 0
8 . 0 ± 1 . 0
1 0 . 0 ± 1 . 0
2 3 . 7 ± 2 . 5
2 5 . 0 ± 2 . 2
0 . 8
7 . 0 ± 1 . 0
7 . 4 ± 0 . 5
1 1 . 0
± 1 . 0
9 . 0 ± 1 . 0
3 0 . 7 ± 3 . 1
2 3 . 0 ± 1 . 0
1 . 2
7 . 0 ± 1 . 0
7 . 0 ± 1 . 0
1 0 . 0
± 1 . 0
1 0 . 0 ± 1 . 0
2 4 . 0 ± 2 . 5
2 1 . 0 ± 1 . 0
1 . 6
6 . 0 ± 1 . 0
7 . 7 ± 0 . 5
8 . 0 ± 1 . 0
9 . 0 ± 1 . 0
3 0 . 3 ± 3 . 0
2 2 . 3
± 1 . 0
2 . 0
7 . 0 ± 1 . 0
8 . 0 ± 1 . 0
1 1 . 0
± 1 . 0
1 0 . 0 ± 1 . 0
3 2 . 0 ± 3 . 5
2 3 . 6 ± 1 . 9
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Global analysis of contact angle data suggests a decrease in the contact angle values, as a
function of ammonium sulphate concentration, measured withα-bromonaphtalene for cells
and chromatographic beads. Contact angle values obtained for Phenyl-Sepharose with
water and formamide were nearly constant irrespective of salt concentration. On the other hand, contact angles determined with the later two diagnostic liquids showed a trend to
decrease when yeast cells were tested in the presence of salt
Experimental contact angle determinations were utilized to calculate surface energy
parameters for both biomass and chromatographic media according to the acid-base
approach (Bos et al. 1999). Calculated parameters reflect the contribution of the various
energy components i.e. Lifshitz-van-der-Waals and Acid-base (electron-acceptor, electron-
donor) to the total surface energy of a defined material. Table 3 depicts the surface energycomponents (γ) calculated for layered intact yeast cells as a function of pH (7 and 4) and
ammonium sulphate concentration (0 – 2.0 M). As a general trend it was observed thatγLW
increased (e.g. from 28 mJ⋅m-2 to 38 mJ⋅m-2 at pH 7 and from 32 mJ⋅m-2 to 39 mJ⋅m-2 at pH
4) whileγAB decreased (e.g. from 30 mJ⋅m-2 to 18 mJ⋅m-2 at pH 7 and from 25 mJ⋅m-2 to 18
mJ⋅m-2 at pH 4) as salt concentration was increased. Table 4 shows surface energy
components for crushed chromatographic media as a function of pH and salt concentration,
as before. At pH 7,γLW increased from 31 mJ⋅m-2 (no salt) to 39 mJ⋅m-2 (0.4 - 2.0 M
ammonium sulphate) whileγAB decreased from 28 mJ⋅m-2 (no salt) to 17 mJ⋅m-2 (2.0 M
ammonium sulphate). At pH 4 a similar trend was noticed:γLW increased from 36 mJ⋅m-2
(no salt) to 41 mJ⋅m-2 (1.2 - 2.0 M ammonium sulphate) whileγAB decreased from 21 mJ⋅m-
2 (no salt) to 15 mJ⋅m-2 (2.0 M ammonium sulphate). As observed from Table 3 and 4, the
parameter Δ Giwi took always values +23-27 mJ⋅m-2 reflecting the hydrophilic nature of the
yeast cells and the chromatographic beads. For comparison, the Δ Giwi of hydrophilic
repulsion for Dextran T-150 is +41.2 mJ⋅m-2 (Van Oss 2003). Concerning the materials
acid-base character, particularly noticeable was a decrease of the values of the electron-
acceptor parameter i.e. up to 60% when comparingγ- in the absence and presence of salt,
respectively (Table 3 and Table 4).γ- values obtainedvia contact angle measurements more
often pertain only to the global or averaged surface properties of the materials under study.
Therefore, the agarose backbone onto which Phenyl ligands are immobilized is expected to
have a major contribution to the overall material properties. On the other hand, differences
in surface energy components might arise due to macromolecular changes within the cell
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envelop which can occur as a function of pH and salt concentration. The observed AB
repulsion in aqueous media often explains the formation of stable suspensions of biological
particles or stable dispersions of proteins and polysaccharides (Wu et al. 1999).
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R e s u l t s
1 0 4
T a b l e 3 :
S u r f a c e e n e r g y p a r a m e t e r s o f
i n t a c t y e a s t c e l l s
i n 2 0 m M
p h o s p h a t e b u f f e r p H
7 , 5 0 m
M a c e t a t e
b u f f e r p H
4 a s a
f u n c t i o n o f
a m m o n i u m s u l p h a t e c o n c e n t r a t i o n .
( N H 4 ) 2 S O
4
( M )
γ L W
( m J ⋅ m - 2 )
γ +
( m J ⋅ m - 2 )
γ -
( m J ⋅ m -
2 )
γ A B
( m J ⋅ m - 2 )
γ t o t
( m J ⋅ m - 2 )
Δ G
i w i
( m J ⋅ m - 2 )
p H 7
p H 4
p H 7
p H 4
p H 7
p H 4
p H 7
p H 4
p H 7
p H 4
p H 7
p H 4
0 . 0
2 8 . 0
3 1 . 7
4 . 4
2 . 9
5 1 . 5
5 4 . 1
3 0 . 1
2 4 . 9
5 8 . 3
5 6 . 6
+ 2 3 . 5
+ 2 7 . 2
0 . 2
3 3 . 0
3 7 . 8
2 . 7
1 . 5
5 3 . 2
5 4 . 3
2 4 . 1
1 8 . 0
5 6 . 9
5 5 . 8
+ 2 6 . 0
+ 2 6 . 7
0 . 4
3 5 . 6
3 8 . 6
2 . 0
1 . 4
5 4 . 0
5 4 . 1
2 0 . 7
1 7 . 5
5 6 . 5
5 6 . 0
+ 2 6 . 8
+ 2 6 . 0
0 . 8
3 7 . 4
3 8 . 6
1 . 6
1 . 5
5 4 . 7
5 4 . 0
1 8 . 6
1 7 . 9
5 6 . 0
5 6 . 5
+ 2 7 . 2
+ 2 5 . 7
1 . 2
3 7 . 9
3 8 . 6
1 . 5
1 . 5
5 4 . 8
5 4 . 2
1 8 . 2
1 8 . 0
5 6 . 0
5 6 . 5
+ 2 7 . 0
+ 2 5 . 9
1 . 6
3 8 . 0
3 8 . 6
1 . 5
1 . 5
5 4 . 8
5 4 . 3
1 8 . 0
1 8 . 0
5 6 . 0
5 6 . 6
+ 2 7 . 1
+ 2 6 . 0
2 . 0
3 8 . 5
3 8 . 6
1 . 5
1 . 5
5 4 . 3
5 4 . 4
1 8 . 0
1 8 . 0
5 6 . 6
5 6 . 6
+ 2 6 . 0
+ 2 6 . 0
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R e s u l t s
1 0 5
T a b l e 4 :
S u r f a c e e n e r g y p a r a m e t e r s o f P
h e n y l - S e p h a r o s e p a r t i c l e s
i n 2 0 m
M p h o s p h a t e
b u f f e r p H 7 , 5 0 m
M a c e t a t e
b u f f e r p H 4 a s a
f u n c t i o n o f
a m m o n i u m s u l p h a t e c o n c e n t r a t i o n .
( N H
4 ) 2 S O
4
( M )
γ L W
( m J ⋅ m - 2 )
γ +
( m J ⋅ m - 2 )
γ -
( m J ⋅ m - 2 )
γ A B
( m J ⋅ m - 2 )
γ t o t
( m J ⋅ m - 2 )
Δ G i w i
( m J ⋅ m
- 2 )
p H 7
p H 4
p H 7
p H 4
p H 7
p H 4
p H 7
p H 4
p H 7
p H 4
p H 7
p H 4
0
3 0 . 8
3 6 . 3
3 . 5
2 . 0
5 4 . 4
5 4 . 4
2 7 . 5
2 0 . 8
5 8 . 4
5 7 . 1
+ 2 6 . 5
+ 2 6 . 5
0 . 2
3 9 . 3
3 9 . 1
1 . 4
1 . 3
5 4 . 9
5 5 . 0
1 7 . 3
1 7 . 1
5 6 . 7
5 6 . 3
+ 2 6 . 3
+ 2 6 . 7
0 . 4
3 9 . 3
4 0 . 3
1 . 4
1 . 1
5 4 . 9
5 4 . 8
1 7 . 3
1 6 . 0
5 6 . 7
5 6 . 3
+ 2 6 . 3
+ 2 6 . 0
0 . 8
3 9 . 3
4 0 . 9
1 . 3
1 . 0
5 5 . 4
5 4 . 9
1 6 . 7
1 5 . 3
5 6 . 0
5 6 . 2
+ 2 7 . 3
+ 2 5 . 9
1 . 2
3 9 . 3
4 1 . 1
1 . 3
1 . 0
5 5 . 1
5 4 . 6
1 6 . 9
1 5 . 3
5 6 . 3
5 6 . 4
+ 2 6 . 8
+ 2 5 . 4
1 . 6
3 9 . 3
4 1 . 1
1 . 4
1 . 0
5 4 . 9
5 4 . 8
1 7 . 3
1 5 . 0
5 6 . 7
5 6 . 2
+ 2 6 . 3
+ 2 5 . 7
2 . 0
3 9 . 3
4 1 . 1
1 . 3
1 . 0
5 5 . 4
5 5 . 0
1 6 . 7
1 4 . 8
5 6 . 0
5 6 . 0
+ 2 7 . 3
+ 2 6 . 2
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The Hamaker constant ( A) for the interaction pair Phenyl-Sepharose / yeast cells was
calculated fromΔGLW according to Equation (2). When calculated for dilute buffer solution
i.e. phosphate buffer pH 7 and acetate buffer pH 4, a value of 0.42k T was obtained. The
calculated value for A in buffers containing ammonium sulphate was 1.1k T. Therefore, an
influence of salt concentration but not of pH was observed oninteraction Hamaker constant
values; interaction refers to support-cell phenomena (Butkus and Grasso 1998).
Utilizing the data provided before i.e.ΔGLW, ΔGAB, and zeta potential values, interaction
energy (U) vs. distance (H) profiles were calculated according to the XDLVO approach.
Figure 1(a/b) shows the calculated secondary energy pockets occurring at≈ 5 nm upon
interaction of a yeast cell and the adsorbent surface. Calculations assumed sphere-to-plate
geometry. This is justified since the adsorbent particles are bigger than the yeast particles
by the factor of ~40. The depth of such energy pockets shifted from low to moderate values
≈ -20-50 k T in dilute buffer solutions down to values≈ -120 k T at high salt concentrations.
A more gradual modification of the involved interaction energies took place at pH 7 than at
pH 4. This is agreements with previous findings utilizing bacterial cells (Stenstrom 1989).
Stronger interaction energies between cells and fluidized beads in the presence of
ammonium sulphate might explain observed biomass interference during direct HIC / EBAcapturing of bioproducts from a crude feedstock (Fernandez-Lahore et al. 2000).
Application of the extended DLVO approach is justified since due to the very polar nature
of the buffer solutions where cell-adsorbent interactions take place, these interactions are
known to be strongly influenced by polar Lewis acid-base (AB) or electron-acceptor /
electron-donor forces. Contributions by electric double layer (EL) forces and particularly
contributions by apolar Lifshitz-van der Waals (LW) forces are also expected to occur.Important to the particular system considered here EL and AB forces decay exponentially
with distance but as opposed to EL, the rate of decay of AB forces with distance is
independent on low to moderate variations in the ionic strength. On the other hand, LW
interactions decay gradually and proportional to the separation distance between two
bodies. As observed from Table 5, LW interactions were promoted upon salt addition. On
the other hand, the pronounced asymmetry of the polar properties of hydrophilic materials
like agarose-based chromatographic supports or biological particles promotes a strong ABrepulsion i.e. hydrophilic repulsion. Taken as a whole, calculations performed in relation to
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109
interaction phenomena i.e. cell-to support interactions have shown hydrophilic AB
repulsion, increased LW attraction, and marginal contribution of EL forces under standard
operational conditions.
The extended DLVO approach has served to explain the behavior of many other colloidal
systems. Brandt and Childress have demonstrated that short-range interactions between
synthetic membranes and bio-colloids can be better explained by taking into consideration
the role of AB forces (Brant and Childress 2002). Van Oss and coworkers have studied the
stability of a thixotropic suspension of 2μm hectorite particles and concluded that Lewis
acid-base interactions play a key role in the coagulation dynamics of such system (Grasso
et al. 2002).
2.3.4.3 Biomass deposition experiments
Biomass deposition experiments were performed to evaluate yeast cells attachment to
hydrophobic interaction supports. This allowed an independent experimental verification of
the predictions made on the basis of energy vs. distance calculations (Figure 1 a/b).
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Figure 1: Energy vs. distance profiles for interaction between intact yeast cells andhydrophobic interaction beads, at varying ammonium sulphate concentration. A) 20 mM phosphate buffer pH 7 b) 50 mM acetate buffer pH 4.
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Figure 2 (a/b) depict the cell effluent profiles measured as a function of the chemical
environment provided by the mobile phase. Ammonium sulphate concentration was
systematically varied to observe its influence on cell attachment onto Phenyl-Streamline
beads. Cell deposition was evaluated a pH 7 and 4. Biomass deposition experiments
showed a profound effect of salt concentration on cell effluent profiles e.g. higher cell
deposition with increased ammonium sulphate concentrations. From Figure 2 (a/b) it can
also be noticed that and increased tendency exists for particles to be retained at pH 7 (a)
that at pH 4 (b) when cell deposition was evaluated as a function of increasing ammonium
sulphate concentration (0 – 2 M).
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Figure 2: Biomass deposition experiments as a function of salt concentration. a) Phosphate buffer pH 7 b) Acetate buffer pH 4.
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R e s u l t s
1 1 4
T a b l e 6 : C a l c u l a t e d
l u m p e d
b i o m a s s - a
t t a c h m e n t p a r a m e t e r
f r o m b i o m
a s s d e p o s i t i o n e x p e r i m e n t s f o r
P h e n y l - S t r e a m l i n e T M p a r t i c l e s v s .
i n t a c t
y e a s t c e l l s i n 2 0 m
M p h o s p h a t e
b u f f e r p H
7 , 5 0 m
M a c e t a t e
b u f f e r p H
4 a s a
f u n c t i o n o f a m m o n i u m s u l p h a t e c o n c e n t r a t i o n .
( N
H 4 ) 2 S O 4
( M )
C / C
o ( - )
α ( - )
p H 7
p H 4
p H
7
p H 4
0 . 0
0 . 6 7 7
0 . 8 2 9
0 . 0 6 5
0 . 0 3 1
0 . 4
0 . 5 6 1
0 . 6 4 7
0 . 0 9 7
0 . 0 7 3
0 . 8
0 . 4 9 3
0 . 5 5 1
0 . 1 1 8
0 . 1 0 0
1 . 2
0 . 2 3 4
0 . 3 9 7
0 . 2 4 3
0 . 1 5 5
1 . 6
0 . 1 2 9
0 . 3 2 1
0 . 3 4 3
0 . 1 9 0
2 . 0
0 . 0 7 1
0 . 2 7 9
0 . 4 4 3
0 . 2 1 4
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Figure 3 shows the correlation between the attachment efficiency parameter and the depth
of the secondary free energy of interaction between a cell particle and a chromatographic
bead. Points corresponding to hydrophobic interaction systems are presented within the
frame of previous results gathered with ion-exchangers. It can be observed that conditions
were no salt is present, and irrespective of pH and buffer chemical composition, are
characterized by low deposition parameter values (≤ 0.15) which correlate with limited
energy pockets (≤ |25-50| kT). However, by adding ammonium sulphate to the flowing
phase an increase inα values was noticed. The magnitude of this increment depended on
pH. For buffers at neutral pH the parameter α changed from≈0.1 (0.4 M salt) to≈0.45 (2.0
M salt). On the other hand, at pH 4 moderate changes inα were observed e.g. from≈0.07
(0.4 M salt) to≈0.21 (2.0 M salt). Therefore, cell deposition in the presence of ammonium
sulphate generally resulted inα ≥ 0.15. The later criterion has been set as threshold for
problem-free operation during direct capture of bioproducts from a crude feedstock (Tari et
al. 2008). From a process performance point of view this could indicate hydrodynamic and
sorption performance limitations from example, during expanded bed adsorption of
bioproducts (Fernandez-Lahore et al. 2000). Sorption performance utilizing HIC / EBA
systems has previously been reported (Smith et al. 2002). Until now, however, it has been
difficult to correlate such behavior with simple cell transmission indexes (Feuser et al.
1999). Biomass-impulse experiments, however, have shown to correlate with ion-
exchanger sorption performance were electrostatic-driven cell-to-matrix interactions effects
are predominant.
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Figure 3: Correlation between depth of free energy of interaction pocket and lumpedattachment coefficient for several systems.
Analysis of the correlation between the depth of the interaction energy pockets and the
attachment efficiency values for hydrophobic interaction materials in the presence of
ammonium sulphate reveled differences with ion-exchange adsorbents. For HIC systems, a
modification inα values correlated with discrete modifications in energy pocket values
(Figure 3). Moreover, extreme values of both attachment efficiency and energy valleys
were not observed. These results, as a whole, might indicate that total deposition of biomass
particles is mediated not only by cell-to-matrix interaction but also by cell-to-cell
aggregation phenomena (ripening). Deposition experiments also seem to indicate that
ripening is occurring in a larger extent at pH 7 than at pH 4. Summarizing, for hydrophobic
interaction systems modifications within a secondary interaction energy pocket occurred
only from -70k T to -120 k T but α values increased up to 0.45 when ammonium sulphate
increased from 0 to 2 M (Figure 3).
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Experiments performed to evaluate the influence of the age of the culture on cell
attachment -as observed by biomass deposition experiments- showed increasedα values
when aged cells were employed. For example, in phosphate buffer pH 7 containing 1.0 M
ammonium sulphateα increased from 0.20 to 0.36 when fresh cells were compared to anaged culture (data not shown). At pH 4 a similar trend was observed withα increasing for
0.14 to 0.26 when considering late exponential phase vs. one day aged culture.
2.3.4.4 Cell-to-cell aggregation
Cell-to-cell aggregation might represent and important mechanism promoting overall cell
attachment during biomass deposition experiments. Therefore, increased values for the
lumped α parameter might indicate not only stronger cell-to-supportinteraction butenhanced cell-to-cell aggregation . Consequently, results from biomass deposition
experiments will reveal conditions prevailing during real process performance where both
interaction and aggregation phenomena can coexist.
Contact angle and zeta potential determinations, as reported in this work and elsewhere
(Lin et al. 2006) have been utilized to calculate energy vs. distance profiles between two
intact yeast cells. Sphere-to-sphere geometry was assumed. These XDLVO calculations
have indicated that:
a) At closest distance of approximationΔGLW took values between -1.5 mJ⋅m-2 (20
mM phosphate buffer pH 7) and -3.8 mJ⋅m-2 (50 mM acetate buffer pH 4) under the
chemical environment provided by the buffering solutions employed. By adding
increasing amounts of ammonium sulphate i.e. up to 2 MΔGLW values decreased to
-9.5 mJ⋅m-2, irrespective of system pH. Therefore, attraction between cell particles
due to LW forces is similar at both pH values but increased with salt concentration
(Table 7). Hamaker constant values were 0.6k T (diluted buffer solution) and 2.0k T
(added salt≥ 0.4 M) for yeast-to-yeast aggregation.
b) Under similar conditions,ΔGAB showed more repulsion when calculating interfacial
energy values at pH 4 (from +31.0 mJ⋅m-2 and up to +35.6 mJ⋅m-2 under buffer and
added salt conditions, respectively) than when calculating interfacial energy values
at pH 7 (from +25.0 mJ⋅m-2 and up to +36.0 mJ⋅m-2 under buffer and added salt
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conditions, respectively). Therefore, the model biomass utilized in this work might
have a tendency to be more stable e.g. less aggregation under acidic pH conditions
due to enhanced repulsion by AB forces (Table 7).
c) Coulomb-type interactions are repulsive in nature, but of marginal importance when
salt concentration is higher than 0.1 M ammonium sulphate e.g. EL are irrelevant
under normal processing conditions.
d) Calculations performed to evaluate energy vs. distance profiles for interaction
between two cells in aqueous media have shown secondary energy pockets taking
values within the range -3k T and -11 k T under diluted buffer conditions and≈ -30
k T in the presence of 2.0 M ammonium sulphate (data not shown).
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R e s u l t s
1 1 9
T a b l e 7 :
I n t e r f a c i a l f r e e e n e r g y o f a g g r e g a t i o n o f
i n t a c t y e a s t c e l l s i n 2 0 m
M p h o s p h a t e
b u f f e r p H 7 , 5 0
m M
a c e t a t e b u f f e r p H
4 a s a
f u n c t i o n
o f a m m o n i u m s u l p h a t e c o n c e n t r a t i o n .
( N H
4 ) 2 S O 4
( M )
Δ G
L W
( m
J ⋅ m - 2 )
Δ G
A B
( m J ⋅ m - 2 )
Δ G
T o t
( m J ⋅ m - 2 )
p H 7
p H 4
p H 7
p H 4
p H 7
p H 4
0 . 0
- 1 . 5
- 3 . 8
+ 2 5 . 0
+ 3 1 . 0
+ 2 3 . 5
+ 2 7 . 2
0 . 2
- 4 . 5
- 8 . 8
+ 3 0 . 5
+ 3 5 . 5
+ 2 6 . 0
+ 2 6 . 7
0 . 4
- 6 . 7
- 9 . 5
+ 3 3 . 5
+ 3 5 . 6
+ 2 6 . 8
+ 2 6 . 0
0 . 8
- 8 . 4
- 9 . 5
+ 3 5 . 5
+ 3 5 . 2
+ 2 7 . 1
+ 2 5 . 7
1 . 2
- 8 . 8
- 9 . 5
+ 3 5 . 9
+ 3 5 . 4
+ 2 7 . 0
+ 2 5 . 9
1 . 6
- 8 . 9
- 9 . 5
+ 3 6 . 0
+ 3 5 . 5
+ 2 7 . 1
+ 2 6 . 0
2 . 0
- 9 . 5
- 9 . 5
+ 3 5 . 6
+ 3 5 . 6
+ 2 6 . 0
+ 2 6 . 0
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In order to elucidate cell aggregation behavior as a function of pH and salt concentration
laser diffraction spectroscopic measurements were employed (Voloshin et al. 2005). The
implementation of an independent method to specifically evaluate cell-to-cell aggregation
can help in understanding (lumped) deposition coefficient values. For example, highα
values in the absence of aggregation by light scattering can be attributed to strong cell-to-
support attachment. On the contrary, highα values and strong aggregation can indicate a
combined effect during biomass deposition. Figure 4 depicts particle size for isolated yeast
cells and formed aggregates, if any. Determinations were performed in 20 mM phosphate
buffer pH 7 and in 50 mM acetate buffer pH 4, so as to reproduce the conditions found
during biomass deposition experiments. Under these conditions, results indicated that cells
were suspended without any association and existed as≈ 8 μm particles (Figure 4a). This is
in perfect agreement with the known size of intact yeast cells. Similar experiments
performed in the presence of 1.6 M ammonium sulphate showed a faster cell-to-cell
aggregation at pH 7 that at pH 4 at short contact times (10 min) (Figure 4b). Furthermore,
longer contact times (45 min) promoted the formation of larger aggregates at pH 7 (≈ 400
μm) than at pH 4 (≈ 250 μm) (Figure 4c). Laser diffraction experiments performed in the
presence of salt were also able to show the shrinkage of individual yeast cell to≈ 5 μm
(data not shown). Cell clumping in the presence of salt was confirmed by confocal
microscopy (Figure 4d). Table 8 summarizes quantitative information obtained after laser
diffraction spectroscopic evaluation of the samples. Results are expressed as percentiles.
The d(0.1), d(0.5), and d(0.9) values shown in Table 8 are indicating that 10 %, 50% and 90% of
the particles measured were less than or the equal to the size stated in each case. Sample
replicates (n=5) have indicated that the shear exerted by the instrument during the
measurement process was not promoting aggregate disruption (Table 8).
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Figure 4: Laser diffraction experiments performed with intact yeast cells as a function of salt concentration, pH of the suspending buffer, and contact time. a) control yeast cells in plain buffer at pH 7 and 4; (b) Yeast cells after 10 minutes in contact with buffer containing1.6 M (NH4)2SO4; (c) yeast cells after 45minutes in contact with buffer containing 1.6 M(NH4)2SO4; d) Visual aggregation of yeast cells suspended in 1.6 M of salt.
Table 8: Laser diffraction experimental data gathered for intact yeast cells as a function saltconcentration, pH of the suspending buffer, and contact time.
Time(min)
pH (*) (NH 4)2SO 4
(M) d (0.1) (µm)
d (0.5) (µm)
d (0.9) (µm)
7 - 4.3 ± 1 5.6 ± 1 7.6 ± 110/45
4 - 4.6 ± 1 6.2 ± 1 8.7 ± 0.5
7 1.6 4.7 ± 0.5 160.5 ± 10 231.5 ± 20104 1.6 3.5 ± 0.5 5.3 ± 1 117.5 ± 5
7 1.6 5.2 ± 1 284.7 ± 15 409.0 ± 2545
4 1.6 4.3 ± 0.5 18.4 ± 4 275.3 ± 15
(*) pH 7: 20 mM phosphate buffer; pH 4: 50 mM acetate buffer
a)
c)
b)
d)
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2.3.5 Conclusions
A comprehensive approach to understand biomass deposition / adhesion onto process
supports, with special emphasis on hydrophobic interaction surfaces have included
interaction forces other than those purely electrostatic in nature and have utilized principlesof colloid theory to explain biomass-adsorbent attachment at the local (particle) level.
Within the classical DLVO theory approach, Lifshitz-Van der Waals (LW) and
electrostatic interactions (EL) were considered. Other forces like acid-base (AB)
interactions were included in theextended approach (XDLVO) so as to explain biomass
interaction and aggregation phenomena.
Interaction between biomass particles and chromatographic beads was understood bycalculating interfacial free energy (U) vs. distance (H) profiles. These calculations were
based on the experimental determination of contact angles with three diagnostic liquids and
the additional information gathered from zeta potential determinations. Hydrophobic
interaction chromatography is operated in a context characterized by an increased salt
concentration (high ionic strength and conductivity) in the mobile phase, as well as, by
uncharged beaded adsorbents. Therefore, it was expected that information provided by
contact angle determination would be more relevant to understand cell-to-support
interactions than the information providedvia zeta potential determinations.
Qualitative and quantitative evaluation of cell deposition experiments have revealed several
underlying phenomena like cell-to-support sticking, prevention of cell depositions by
already deposited biomass particles (blocking), and cell-to-cell aggregation (ripening).
Analysis of the correlation between the depth of the interaction energy pockets and the
deposition coefficient values for hydrophobic interaction materials in the presence of
ammonium sulphate reveled differences with ion-exchange adsorbents. For HIC systems,
modifications inα values were followed by discrete modifications in energy pocket depths.
Moreover, extreme values of both deposition coefficients and energy valleys were not
observed. These results, as a whole, might indicate that total deposition of biomass particles
is mediated not only by cell-to-material interaction but mainly by cell-to-cell aggregation
phenomena (ripening).
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Cell-to-cell aggregation has represented and important mechanism promoting overall cell
adhesion during biomass deposition experiments. These results would indicate that similar
phenomena would impact on real process performance. Cell aggregation behavior, as a
function of pH and salt concentration, was confirmed by laser diffraction spectroscopic
measurements. Besides direct attachment of cells to the beaded support, cell aggregation
has contributed to elevatedα-parameter values, particularly at pH 7, during biomass
deposition experiments.
Summarising, it was demonstrated that both cell-to-adsorbent (interaction) and cell-to-cell
(aggregation) phenomena are responsible to biomass deposition onto hydrophobic
interaction chromatographic materials. Interaction and aggregation was inferred from
XDLVO calculations on the basis of contact angle and zeta potential measurements.
Moreover, experimental confirmation was obtained by independent methods like biomass
deposition experiments and laser diffraction spectrometry.
Further work is being performed in our laboratory in order to extent the observations
reported in this paper to other adsorbent chemistries, biomass types of various
characteristics, and broader operational windows. For example, cell debris shows stronger
interactions with hydrophobic adsorbents than intact cells, because of the hydrophobicinner membrane. Additionally, the information provided by the XDLVO approach is being
utilised to alleviate process limitations.
2.3.6 Acknowledgements
CT was financially supported by TUBITAK, the Turkish Scientific and Technical Research
Council, Ankara Turkey. RRVP gratefully acknowledges a doctoral fellowship from
Jacobs University. The authors would like thank Professor Udo Fritsching and Ms. LydiaAchelis, Department of Process Technology, University of Bremen, for helpful assistance
during laser diffraction measurements.
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2.3.7 Nomenclature
AB Acid-Base
DLVO Classical DLVO theory (Derjaguin, Landau, Verwey and Overbeek)
HIC Hydrophobic interaction chromatography
EBA Expanded Bed Adsorption
EL Electrostatic
LW Lifshitz-Van der Waals
A Hamaker constant [k T]
IC Intact yeast cell particles
LW γ Apolar or Lifshitz-van der Waals component of surface tension [mJ⋅m-2]
ABγ Polar or acid–base component of surface tension [mJ⋅m-2]
−γ Electron-donor component of surface tension (Lewis base) [mJ⋅m-2]
+γ Electron-acceptor component of surface tension (Lewis acid) [mJ⋅m-2]
ε Dielectric constant of the medium [-]R Radius of the particle [m]
ζ Zeta potential [mV]
κ Inverse of Debye length [m]
H Distance between surfaces, measured from outer edge [m]
XDLVO Extended DLVO theory, according to Van Oss
ΔG Interfacial free energy @ 1.57 Å approach [mJ⋅m-2]
U Interfacial energy of interaction [k T]
k Boltzmann constant [J⋅K -1]
T Absolute temperature [K]
h0 Closest distance of approximation [1.57 Å]
α Lumped biomass attachment coefficient [-]
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2.3.7 References
Bak H, Thomas ORT. 2007. Evaluation of commercial chromatographic adsorbents for the
direct capture of polyclonal rabbit antibodies from clarified antiserum. J
Chromatogr B 848(1):116-130.Bos R, Van der Mei HC, Busscher HJ. 1999. Physico-chemistry of initial microbial
adhesive interactions--its mechanisms and methods for study. FEMS Microbiol Rev
23(2):179-230.
Brant JA, Childress AE. 2002. Assessing short-range membrane-colloid interactions using
surface energetics. J Membr Sci 203:257-273.
Butkus MA, Grasso D. 1998. Impact of Aqueous Electrolytes on Interfacial Energy. J
Colloid Interface Sci 200(1):172-181.Fernandez-Lahore HM, Geilenkirchen S, Boldt K, Nagel A, Kula MR, Thommes J. 2000.
The influence of cell adsorbent interactions on protein adsorption in expanded beds.
J Chromatogr A 873(2):195-208.
Fernandez-Lahore HM, Kleef R, Kula M, Thommes J. 1999. The influence of complex
biological feedstock on the fluidization and bed stability in expanded bed
adsorption. Biotechnol Bioeng 64(4):484-96.
Feuser J, Walter J, Kula MR, Thommes J. 1999. Cell/adsorbent interactions in expanded
bed adsorption of proteins. Bioseparation 8(1-5):99-109.
Ganeva V, Galutzov B, Teissie J. 2004. Flow process for electroextraction of intracellular
enzymes from the fission yeast, Schizosaccharomyces pombe. Biotechnol Lett
26(11):933-7.
Grasso D, Subramaniam K, Butkus M, Strevett K, Bergendahl J. 2002. A review of non-
DLVO interactions in environmental colloidal systems. Rev Environ Sci Biotechnol
1(1):17-38.
Henriques M, Gasparetto K, Azeredo J, Oliveira R. 2002. Experimental methodology to
quantify Candida albicans cell surface Hydrophobicity. Biotechnol Lett 24:1111–
1115.
Kang S, Choi H. 2005. Effect of surface hydrophobicity on the adhesion of S. cerevisiae
onto modified surfaces by poly(styrene-ran-sulfonic acid) random copolymers.
Colloids Surf B Biointerfaces 10(46 (2)):70-7.
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Lin DQ, Brixius PJ, Hubbuch JJ, Thommes J, Kula MR. 2003. Biomass/adsorbent
electrostatic interactions in expanded bed adsorption: a zeta potential study.
Biotechnol Bioeng 83(2):149-57.
Lin DQ, Fernandez-Lahore HM, Kula MR, Thommes J. 2001. Minimising
biomass/adsorbent interactions in expanded bed adsorption processes: a
methodological design approach. Bioseparation 10(1-3):7-19.
Lin DQ, Zhong LN, Yao SJ. 2006. Zeta potential as a diagnostic tool to evaluate the
biomass electrostatic adhesion during ion-exchange expanded bed application.
Biotechnol Bioeng 95(1):185-91.
Mahn A, Asenjo JA. 2005. Prediction of protein retention in hydrophobic interaction
chromatography. Biotechnol Adv 23(5):359-368.
Ottewill RH, Shaw JN. 1972. Electrophoretic studies on polystyrene lattices. J Electroanal
Chem 37:133-142.
Redman JA, Walker SL, Elimelech M. 2004. Bacterial Adhesion and Transport in Porous
Media: Role of the Secondary Energy Minimum. Environ Sci Technol 38(6):1777-
1785.
Sharma PK, Rao KH. 2002. Analysis of different approaches for evaluation of surface
energy of microbial cells by contact angle goniometry. Adv Colloid Interface Sci
98(3):341-463.Smith MP, Bulmer MA, Hjorth R, Titchener-Hooker NJ. 2002. Hydrophobic interaction
ligand selection and scale-up of an expanded bed separation of an intracellular
enzyme from Saccharomyces cerevisiae. J Chromatogr A 968(1-2):121-128.
Smyth CJ, Jonsson P, Olsson E, Soderlind O, Rosengren J, Hjerten S, Wadstrom T. 1978.
Differences in Hydrophobic Surface Characteristics of Porcine Enteropathogenic
Escherichia-Coli with or without K88 Antigen as Revealed by Hydrophobic
Interaction Chromatography. Infect Immun 22(2):462-472.Stenstrom TA. 1989. Bacterial hydrophobicity, an overall parameter for the measurement
of adhesion potential to soil particles. Appl Environ Microbiol 55(1):142-147.
Tari C, Vennapusa RR, Cabrera RB, Fernandez-Lahore M. 2008. Colloid deposition
experiments as a diagnostic tool for biomass attachment onto bioproduct adsorbent
surfaces. J Chem Technol Biotechnol 83:183-191.
Van Oss CJ. 1994. Interfacial forces in aqueous media. New York: Marcel Dekker.
viii,440p. p.
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Van Oss CJ. 2003. Long-range and short-range mechanisms of hydrophobic attraction and
hydrophilic repulsion in specific and aspecific interactions. J Mol Recognit
16(4):177-190.
Vennapusa RR, Hunegnaw SM, Cabrera RB, Fernandez-Lahore M. 2008. Assessing
adsorbent-biomass interactions during expanded bed adsorption onto ion exchangers
utilizing surface energetics. J Chromatogr A 1181(1-2):9-20.
Vergnault H, Willemot RM, Mercier-Bonin M. 2007. Non-electrostatic interactions
between cultured Saccharomyces cerevisiae yeast cells and adsorbent beads in
expanded bed adsorption: Influence of cell wall properties. Process Biochem
42(2):244-251.
Voloshin S, Shleeva M, Syroeshkin A, Kaprelyants A. 2005. The Role of Intercellular
Contacts in the Initiation of Growth and in the Development of a Transiently
Nonculturable State by Cultures of Rhodococcus rhodochrous Grown in Poor
Media. Microbiology 74:420-427.
Wu W, Giese RF, Van Oss CJ. 1999. Stability versus flocculation of particle suspensions in
water-correlation with the extended DLVO approach for aqueous systems,
compared with classical DLVO theory. Colloids Surf B Biointerfaces 14:47-55.
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2.4 Surface energetics to assess biomass attachment ontoimmobilized metal affinity adsorbents in expanded beds
Rami Reddy Vennapusa, Muhammad Aasim, Rosa Cabrera, and Marcelo Fernandez-Lahore*
Downstream Processing Laboratory, School of Engineering and Science, Jacobs UniversityBremen gGmbH, Campus Ring 1, D-28759, Bremen, Germany.
2.4.1 Abstract
Cell-to-support interaction and cell-to-cell aggregation phenomena have been studied in a
model system composed of intact yeast cells and Chelating-StreamlineTM
adsorbents.Biomass components and beaded adsorbents were mainly characterized by contact angle
determinations with three diagnostic liquids. Complementarily, zeta potential
measurements were performed. These experimental values were employed to calculate free
energy of interaction vs. distance profiles in aqueous media. The effect of immobilized
metal-ion type and buffer pH on the interaction energy was evaluated. Calculations
indicated that moderate interaction between cell particles and adsorbent beads can develop
due to the presence of Cu2+
ions onto the solid phase. The strength of interaction increasedwith buffer pH, within the range 6.0 to 8.3 e.g. secondary energy pockets increased from
|15| to |60| k T. Cell-to-cell secondary energy minimum was≥ |14| k T showing low-to-
moderate tendency to aggregate, particularly at pH≥ 8. Extended DLVO predictions were
generally confirmed by biomass deposition experiments. However, an exception was found
when working with immobilized Cu2+ at pH 8 since yeast cells were able to sequestrate
such immobilized ions. Therefore, lower-than-expected values for the depositions
coefficient (α) were observed. Understanding biomass attachment onto Chelating supportscan help to better design and operate expanded bed adsorption of bioproducts.
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secreted fromS. cerevisiae were also processed employing this technique (Noronha et al.
1999). Generally, recoveries over 80% of the product were achieved in successful cases,
but at least two major weak features must be further improved: low dynamic capacity and
efficiency of Clean In Place (CIP) procedures for eliminating contaminants. The later are
directly linked to biomass interference with the sorption process. The combination of
IMAC and EBA techniques has potential to provide a unique approach to simplifying the
whole downstream process, reduce the number of steps and start-up investment, and thus
make the purification more economical.
Experimental evidence has addressed the importance of non-electrostatic forces for biomass
adhesion to process surfaces in the broader context provided by a group of systems of
technical and environmental relevance. In this regard, a more comprehensive approach tounderstand biomass deposition onto chromatographic supports has been proposed by
utilizing principles of colloid theory to explain biomass-adsorbent attachment at the local
(particle) level (Vennapusa et al. 2008). This approach is based on extended DLVO
calculations performedvia experimentally determined contact angles and z-potentials for
the interacting bodies. This comprehensive method takes into account several types of
possible interaction forces. Lifshitz-Van der Waals (LW) and acid-base (AB) forces are
considered and, therefore, the approach is not limited to those purely electrostatic in nature(EL). Moreover, biomass attachment behavior onto chromatographic beads predicted on the
basis of XDLVO calculations was validated by independent biomass deposition
experiments (Tari et al. 2008).
The aim of this paper was to contribute to a deeper understanding of biomass-adsorbent
interactions. This would further open the pave for optimized EBA processing in industry. In
this work, studies have targeted biomass adhesion to Chelating materials that have not been
extensively studied so far. The physicochemical properties of biomass-derived material (bio
colloid particles) vs. the physicochemical properties of the adsorbent beads (the process
surface) were determined indirectlyvia contact angle and zeta potential measurements.
Subsequently, Gibbs free (interfacial) energy of interaction was calculated as a function of
surface distance in aqueous media e.g. process buffer. Calculations were experimentally
confirmed by independent biomass deposition experiments.
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2.4.3 Materials and Methods
2.4.3.1 Materials
Chromatographic matrices and columns were purchased from GE Health Care (Munich,Germany). α-bromonaphtalene and formamide were obtained from Fluka (Buchs,
Switzerland). Water was Milli-Q quality. All other chemicals were analytical grade.
2.4.3.2 Generation of biomass
Yeast cells (Saccharomyces cerevisiae ) were cultivated in shake-flasks, harvested at late
exponential phase by centrifugation, and washed three times with 10mM phosphate buffer
solutions, as previously described (Ganeva et al. 2004). Cells were employed immediatelyafter preparation for further experimental procedures.
2.4.3.3 Contact angle measurements
Preparation of intact yeast cells for contact angle measurements was performed as
described (Henriques et al. 2002). Washed cells were suspended to 10% (w/v) in IMAC
buffer [20mM phosphate buffer, pH 7.6 / 250 mM sodium chloride / 1 mM imidazol]. Cells
were further equilibrated in the buffer solution and the suspension subsequently poured
onto agar plates containing 10% glycerol and 2% agar-agar. The plate was allowed to dry
for 24-36 hours at room temperature on a properly leveled surface free from dust. Salt
crystallization was avoided. Agar plates without cell spreads were utilized as control.
Contact angles were measuredas per the sessile drop method utilizing a commercial
goniometric system (OCA 20, Data Physics instruments GmbH, Filderstadt, Germany). The
three diagnostic liquidsα-bromonaphtalene, formamide, and water were employed (Bos et
al. 1999). All the measurements were performed in triplicate and at least 20 contact angles per samples were measured.
Contact angle determination on buffer-equilibrated chromatographic beads was performed
utilizing the same physicochemical conditions and experimental procedures described for
cell particles. Chelating Sepharose was utilized (GE Healthcare, Munich, Germany).
Previous to pouring onto the agar plates, matrix beads were frozen in liquid nitrogen and
crushed mechanically. Crushing efficiency was assessed by microscopic examination and particle size determination so as to assure particle fragment diameters≤ 10 μm. Square
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pieces of the agar-supported chromatographic bead fragments were utilized for measuring
contact angles.
2.4.3.4 Zeta potential determination
Zeta-potential measurements were performed with a ZetaSizer Nano-ZS (Malvern
instruments, Worcestershire, United Kingdom), as previously described (Vennapusa et al.
2008). Zeta-potential values were gathered employing biomass pretreated under the
conditions described before.
Zeta-potential values for crushed and pre-equilibrated chromatographic beads were
calculated from the electrophoretic mobility data according the Smoluchowski’s equation
(Ottewill and Shaw 1972). Data was gathered under identical buffer compositions as shownfor biomass related determinations.
2.4.3.5 Cell aggregation behavior
Visual inspection of aggregate formation was performed with a confocal laser scanning
microscope, equipped with argon and helium/neon mixed gas laser with excitation
wavelengths of 488 or 543 nm (LSM 510, Carl Zeiss, Oberkochen, Germany). Washed
yeast cells in control buffer [20 mM phosphate buffer, pH 7.6] or IMAC buffer [20mM phosphate buffer, pH 7.6 / 250 mM sodium chloride / 1 mM imidazol] were mounted on
glass slides and visually inspected. Scans at a resolution of 1024 x 1024 pixels were taken
in the line-averaging mode. Micrographs were stored in LSM format for further analysis
(Carl Zeiss LSM Image Browser).
2.4.3.6 Bio-colloid deposition experiments
Biomass deposition experiments were performed automatically employing an ÄKTA
Explorer 100 system (GE Health Care, Munich, Germany) as previously described (Tari et
al. 2008). Streamline Chelating was packed in commercial chromatographic columns (5
mm internal diameter, 50 mm length). The quality of the packing was evaluated by
residence time distribution analysis employing 1% acetone as tracer (Bak and Thomas
2007). Chelating particles were loaded with metal ions utilizing standard procedures
(Clemmitt and Chase 2000). Biomass deposition studies were done by injecting a 4 ml
biomass pulse (OD≈ 0.8 AU). Experiments were performed utilizing IMAC buffer at pH
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6.0, 7.6, and 8.3. The operational flow rate was 76.4 cm.h-1. Particle breakthrough curves
were obtained by monitoring the effluent suspensions at 600 nm. On the basis of such data,
the biomass deposition parameter (α) was calculated (Redman et al. 2004).
2.4.3.6 Energy-distance profile calculations
The total interaction energy between a colloidal particle and a solid surface can be
expressed in terms of the extended DLVO theory as:
ABmwc
ELmwc
LW mwc
XDLVOmwc U U U U ++= (1)
where UXDLVO is the total interaction energy in aqueous media, ULW is the LW interaction
term, and UEL
is the EL interaction term. The subscriptm is utilized for thechromatographic matrix (adsorbent bead), w refers to the watery environment, and c to the
colloidal (cell) particle. A third short-range (≤ 5 nm) Lewis AB term is included to account
for “hydrophobic attractive” and “hydrophilic repulsive” interactions (Van Oss 2003).
Material surface energy parameters (tensions) can be calculated from contact angle
measurements utilizing three diagnostic liquids (Van Oss 1994). In turn, this data can be
employed to evaluate the free energy of interaction between two defined surfaces (ΔGLW
and ΔGAB). ΔG represents here the interaction energy per unit area between two (assumed)
infinite planar surfaces bearing the properties of the adsorbent bead and the cell
(interaction) or two cells (aggregation), respectively. Interaction between any of these two
surfaces are evaluated at a closest distance of approximation [h0 ≈ 0.158 nm] (Bos et al.
1999). When integrated into mathematical expressions accounting the geometric constraints
existing between two interacting bodies,ΔG values can be utilized to calculate the
corresponding energy-distance profile (U vs. H). Details of this procedure were published
elsewhere (Bos et al. 1999; Vennapusa et al. 2008).ΔGLW is also related to the interaction Hamaker constant, as follows:
LW Gh A Δ−= 2012π (2)
UEL energy-distance curves can be calculated, assuming either plate-sphere or sphere-
sphere geometry, upon experimental determination of particle zeta potential values. Zeta
potential values are measured by electrophoretic mobility experiments. Calculations were
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performed employing a commercial software package (GraphPad Prism, GraphPad
Software Inc., San Diego, CA, USA).
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Table 1: Contact angles obtained on crushed Chelating Sepharose with and withoutimmobilized metal ions. For IDA-Cu2+, determinations were performed a various pHvalues. Measurements were performed in 20 mM phosphate buffer, pH 7.6, containingsodium chloride.
Metal ion pH Contact angle ( θ) [°]
Water Formamideα -
Bromonaphtalene
No metal 7.6 7.0 ± 0.6 9.8 ± 0.8 53.0 ± 1.0
Zn2+ 7.6 8.0 ± 2.0 12.8 ± 2.0 57.0 ± 2.1
Ni2+ 7.6 8.0 ± 1.7 11.4 ± 2.0 54.0 ± 3.4
Co2+ 7.6 10.0 ± 2.0 12.6 ± 3.1 54.0 ± 2.0
Cu2+ 6.0 7.5 ± 0.5 9.5 ± 1.3 57.0 ± 5.5
Cu2+ 7.6 10.2 ± 2.4 12.1 ± 0.9 45.0 ± 3.0
Cu2+ 8.3 11.1 ± 0.4 11.0 ± 1.5 40.0 ± 2.2
Experimental contact angle determinations were utilized to calculate surface energy
parameters for the chromatographic media according to the acid-base approach (Bos et al.
1999). Table 2 depicts the surface energy components (γ) calculated as a function
immobilized metal-ion type.γLW values were≈ 28 mJ⋅m-2 for the free Chelating matrix and
the Ni2+ or Co2+ loaded beads. A decreased value for such parameter, however, was
observed with Zn2+ (26.5 mJ⋅m-2). On the other hand,γLW values increased for Cu2+ (32.3
mJ⋅m-2
).
An interesting behavior was observed in relation with acid-base character of the metal-
immobilized materials. Values taken by the electron-acceptor parameter (γ+) and the total
acid-base parameter (γAB) allowed differentiating between beads harboring different metal-
ions as follows :
Zn2+ > Ni2+ ≈ [IDA]≈ Co2+ >>Cu2+
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γ+ took values between 3.0 and 5.0 mJ⋅m-2 while for most Sepharose adsorbent values≈ 1-2
mJ⋅m-2 are typical (Vennapusa et al. 2008). Similar observations were made by
(Bayramoglu et al. 2006) when comparing L-histidine affinity membranes with or without
immobilised copper (II) ions. These variations in the acid-base character of the (metal ion)loaded chromatographic matrices are expected since IMAC adsorption is based on the
interaction between an immobilised transition-metal ion (electron pair acceptors) and
electron-donor groups e.g. on protein surfaces. For proteins, the apparent affinity for a
metal chelate depends strongly on the metal ion involved in coordination. In the case of the
iminodiacetic acid (IDA) chelator, the affinities of many retained proteins and their
respective retention times are in the following order: Cu2+ > Ni2+ > Zn2+ ≈ Co2+ (Gaberc-
Porekar and Menart 2001).
Table 2: Surface energy parameters calculated for Chelating Sepharose loaded with variousmetal ions, calculated according to the contact angle values reported in Table 1.
Metal ion pH Surface energy parameters [mJ·m -2]
γLW γ+ γ- γAB γTOT ΔG sws
No metal 7.6 28.5 4.4 53.8 30.7 59.2 +25.2Zn2+ 7.6 26.5 5.0 54.1 32.8 59.3 +25.0
Ni2+ 7.6 28.0 4.5 53.9 31.0 59.0 +25.3
Co2+ 7.6 28.0 4.4 53.5 30.7 58.7 +25.2
Cu2+ 6.0 26.5 5.3 53.3 33.5 59.9 +24.0
Cu2+ 7.6 32.3 3.0 53.7 25.0 57.4 +26.3
Cu2+ 8.3 34.6 2.4 53.3 22.5 57.1 +25.6
2.4.4.3 The effect of mobile-phase pH
Adsorption of a protein to the IMAC support is performed at a pH at which imidazole
nitrogen’s in histidyl residues are in the nonprotonated form, normally in neutral or slightly
basic medium (Chaga 2001; Ueda et al. 2003).
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Contact angle determinations were also performed as a function of pH, employing
immobilized copper ions. Table 1 also summarizes the contact angle values obtained in
IMAC buffer at pH 6.0, 7.6, and 8.3. Some tendencies were observed when pH raised: a)
water contact angles increased from 7.5 to 11.0, and b) formamide contact angles increased
from 9.5 to 11.1, but c)α-bromonaphtalene contact angles decreased from 57 to 40.
Table 2 depicts the surface energy components (γ) calculated for the IMAC adsorbent at
various pH values. As a general trend it was observed thatγLW increased with pH (e.g. from
26.5 mJ⋅m-2 at pH 6.0 to 34.6 mJ⋅m-2 at pH 8.3) whileγAB decreased (e.g. from 33.5 mJ⋅m-2
at pH 6.0 to 22.5 mJ⋅m-2 at pH 8.3). Clearly noticeable was the influence of pH on theγ+
since this parameter decreased from 5.3 mJ⋅m-2
at pH 6.0 to 2.4 mJ⋅m-2
at pH 8.3.
As observed from Table 2, the parameter Δ Giwi took always values +24-26 mJ⋅m-2,
irrespective of the type of transition metal ion immobilized or the buffer pH, reflecting the
highly hydrophilic nature of the chromatographic beads.
2.4.4.4 Characterization of the yeast particles
Contact angle determinations were performed on intact yeast cell lawns within the
physicochemical environment provided by the IMAC buffer. Contact angle values werecollected for three distinct pHs: 6.0, 7.6, and 8.3. Water and formamide contact angle
values were observed to increase with pH e.g. from 7.6 to 12.2 and from 10.4 to 18,
respectively. On the contraryα-bromonaphtalene contact angles dropped from 50 to 44.
Overall, this indicates an increased hydrophobic character for the yeast particles at higher
pH values [Refer to Table 3 (a)].
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Zeta potential measurements performed in IMAC buffer at various pHs were≈ |8| mV (data
not shown). Zeta potential values close to zero are expected due to the moderate-high
concentrations of salt which are present in such buffers e.g. from 0.25 to 1.0 M in sodium
chloride.
2.4.4.5 Biomass interaction phenomena
Interaction between biomass particles and chromatographic beads can be understood by
calculating interfacial free energy (U) vs. distance (H) profiles. These calculations are
based on the experimental determination of contact angles with three diagnostic liquids and
the additional information gathered from zeta potential determinations.
Table 4 depicts the interfacial free energy of interaction between a biomass particles and a
Chelating bead, in aqueous media at pH 7.6, at closest distance of approximation (1.57 Å).
For the unloaded particle,ΔGLW and ΔGAB values were -1.1 mJ⋅m-2 and +28 mJ⋅m-2,
respectively. Upon loading the matrix with different transition metal ions, variations in the
preceding values were observed for Zn2+ (ΔGLW = -0.8 mJ⋅m-2 / ΔGAB = 27.4 mJ⋅m-2) and
for Cu2+ (ΔGLW = -1.7 mJ⋅m-2 / ΔGAB = 29.6 mJ⋅m-2) but not for Ni2+ and Co2+.
Interaction between Cu (II) loaded beads and yeast cells was further investigated as a
function of buffer pH (Table 4). It was noticed thatΔGLW decreased from -0.76 mJ⋅m-2 at
pH 6.0 to -2.6 mJ⋅m-2 at pH 8.3. AB values also followed a similar tendency e.g.ΔGAB
increased from 26.6 mJ⋅m-2 at pH 6.0 to 32.6 mJ⋅m-2 at pH 8.3. This data is indicating that
the pH values of the buffer where interaction is occurring are correlated with modification
in interaction energies.
The interaction Hamaker constant ( A) for the pair Chelating-Sepharose / yeast cells wascalculated from ΔGLW according to Equation (2). When calculated for IMAC buffer
solution (pH 7.6) an average value of 0.35 kT was obtained. A was lower for Zn2+ but
higher for Cu2+ i.e. 0.17 kT and 0.40 kT, respectively.
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Table 4: The interfacial Gibbs energy of interaction between intact yeast cells andChelating Sepharose, at closest distance of approximation. Interaction occurs in 20 mM phosphate buffer containing sodium chloride as added salt.
Loaded metal ion Buffer pH ΔG [mJ·m -2]
ΔG LW ΔG AB
No metal 7.6 -1.1 27.9
Zn2+ 7.6 -0.8 27.4
Ni2+ 7.6 -1.0 27.8
Co2+ 7.6 -1.0 27.7
Cu2+ 6.0 -0.76 26.6
Cu2+ 7.6 -1.7 29.6
Cu2+ 8.3 -2.6 32.6
Utilizing the data provided before i.e.ΔGLW, ΔGAB, and zeta potential values, interaction
energy (U) vs. distance (H) profiles were calculated according to the XDLVO approach.
Due to the relatively high conductivity of the mobile phase utilized in Chelating systems (≈
30 mS/cm), zeta-potential values for both yeast particles and chromatographic beads were
very low (< 8-10 mV).
Figure 1(a) and Figure 1(b) shows the calculated secondary energy pockets occurring at≈ 7
nm upon interaction of a yeast cell and the adsorbent surface. Calculations assumed sphere-
to-plate geometry. The depth of such energy pocket for the unloaded matrix showed a
moderate value≈ -20 k T at pH 7.6. Metal ion loaded systems showed a similar energy
profile. However, the presence of immobilized Cu2+ resulted in an increased pocket depth≈ -40 k T. In the later case, modification of pH has lead to a reduced (≈ -15 k T at pH 6.0) or
increased (≈ -60 k T at pH 8.3) energy pocket. Therefore, more cell deposition would be
expected when working with immobilized cupper ions at higher pH values.
Data indicated that cell-to-support interactions can be strongly influenced by polar Lewis
acid-base (AB) or electron-acceptor / electron-donor forces which are included in the
XDLVO approach. This has served to explain the behavior of many other colloidal
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systems. Brandt and Childress have demonstrated that short-range interactions between
synthetic membranes and bio-colloids can be better explained by taking into consideration
the role of AB forces (Brant and Childress 2002; Brant and Childress 2004). Van Oss and
coworkers have studied the stability of a thixotropic suspension of 2μ
m hectorite particles
and concluded that Lewis acid-base interactions play a key role in the coagulation
dynamics of such system (Grasso et al. 2002). Van Oss also has reviewed the importance of
AB forces for the stability of many colloidal systems (Van Oss 1993; Van Oss 2003).
Figure1 (a): Free energy of interaction vs. distance profiles between intact yeast andChelating Sepharose loaded with different metal-ion types. Calculations were performed
assuming that interaction occurs in a buffer with a typical composition for immobilizedmetal affinity chromatography, at pH 7.6 / (— ) No metal, (— ) Zn2+, (--- ) Ni2+, (— ) Co2+, (— ) Cu2+
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Figure 1(b): Free energy of interaction vs. distance profiles between intact yeast andChelating Sepharose loaded with Cu (II) ions. Calculations were performed assuming thatinteraction occurs in a buffer with a typical composition for immobilized metal affinity
chromatography, at various pH values. (—
) pH 6, (—
) pH 7.6, (—
) pH 8.3.
2.4.4.6 Biomass aggregation phenomena
Contact angle and zeta potential determinations, as reported in this work have been utilized
to calculate energy vs. distance profiles between two intact yeast cells. The data gathered
on zeta potential showed that charge effects are of marginal importance for the Chelating
system. Sphere-to-sphere geometry was assumed. Table V depicts the interfacial interaction
free energy between two biological particles, in aqueous media as function of pH at theclosest distance of approximation (1.57 Å). The tendency of ΔGLW and ΔGAB interaction
energy of aggregation is similar to that of the interaction of yeast with IDA-Cu2+ as
function of pH (Table IV). Upon modification of buffer pH from 6.0 to 8.3, theΔGLW
interaction energy decreased from -2.6 mJ⋅m-2 to -4.6 mJ⋅m-2 while ΔGAB changed from
+28.4 mJ⋅m-2 to 33.8 mJ⋅m-2, respectively. Interaction free energies as function of distance
were calculated according to the XDLVO model (Figure 2) . Calculations, in aqueous
media, have indicated that secondary energy pockets can develop at H≈ 5-7 nm. The depth
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of such pockets indicated that attraction between cell particles is higher when the pH of the
buffer increased i.e. U≈ |14| at pH 8.3 and ≤ |8| at lower pH values. This trend was
confirmed by microscopic observations. Figure 3 depicts freely suspended cells in 20 mM
phosphate buffer in comparison with clumped cell in IMAC buffer. Cell aggregation wasverified by independent laser diffraction experiments (Data not shown).
Table 5: The interfacial Gibbs energy of aggregation between intact yeast cells, at closestdistance of approximation. Interaction occurs in 20 mM phosphate buffer containingsodium chloride as added salt.
Buffer pH ΔG LW [mJ·m -2] ΔG AB [mJ·m -2]
6.0 -2.6 28.4
7.6 -2.8 28.7
8.3 -4.6 33.8
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Figure 2: Free energy of interaction vs. distance profiles between intact yeast cells.Calculations were performed assuming that interaction occurs in a buffer with a typicalcomposition for immobilized metal affinity chromatography, at various pH values. (— ) pH6, (— ) pH 7.6, (— ) pH 8.3.
Figure 3 : Microscopic observation of yeast cell aggregation employing a confocal system:a) Cells in 20 mM phosphate buffer at pH 7.6, and b) Cells in sodium chloride containing buffer at the same pH.
a) b)
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2.4.4.7 Biomass deposition experiments
Figure 4(a) depicts the cell effluent profiles measured as a function of the chemical
environment provided by the mobile phase. The transition metal ion immobilized on the
IDA moiety was varied to observe the influence of ion type on cell attachment. ChelatingStreamline beads were utilized. Biomass deposition experiments confirmed that an
increased deposition of yeast cell occur when Cu2+ is the fixed metal ion, at pH 7.6.
Figure 4 (a): Cell effluent profiles obtained after biomass deposition experiments. Intactyeast cells were utilized as model bio-colloids. Runs were performed in phosphate-based buffer solutions, at pH 7.6. Chelating Sepharose was utilized as collector particles.
Iminodiacetic beads were loaded with several metal ions: () No metal, ( ) Zn2+
, ( ) Ni2+
,( ) Co2+, ( ) Cu+2.
This fact is reflected by the “attachment efficiency” parameter (α). This is a lumped
number which depends on experimental conditions; the method has been adapted to a
chromatographic workstation that can operate in automatic mode.α values for the unloaded
material and the Zn2+, Ni2+, and Co2+ loaded support fall within the range 0.056-0.078.
Upon Cu2+ immobilization,α increased to 0.172 i.e. more yeast particles were trapped
within the collector bed (Table 4).
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Figure 4(b): Cell effluent profiles obtained after biomass deposition experiments. Intactyeast cells were utilized as model bio-colloids. Runs were performed in phosphate-based buffer solutions, at several pH values. Chelating Sepharose, loaded with Cu (II) ions, wasutilized as collector particles. () pH 6, ( ) pH 7.6, ( ) pH 8.3.
Cell-to-cell aggregation might represent and important mechanism promoting overall cell
attachment during biomass deposition experiments. Therefore, increased values for the
lumped α parameter might indicate not only stronger cell-to-supportinteraction but
enhanced cell-to-cellaggregation . For the Chelating system, cell aggregation effects are
predicted to be low-to-moderate according to XDLVO calculations. To evaluate whether
cell aggregation or attrition–in the absence of cell-to-matrix interaction- is influencing cell breakthrough profiles, biomass deposition experiments were run with plain material as
collectors but utilizing mobile phase compositions known to increase cell aggregation
(Ljungh and Wadström 1982). Experimental runs showed thatα values were fairly constant
(α ≈ 0.05) irrespective of the presence of ammonium sulphate, a salt that induces cell-to-
cell aggregation (Figure 5).
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Figure 5: Cell effluent profiles obtained after biomass deposition experiments. Intact yeastcells were utilized as model bio-colloids. Runs were performed in phosphate-based buffer solutions, at pH 7.6. Unloaded Chelating Sepharose beads were utilized as collectors. () 20mM phosphate buffer, ( ) Buffer containing added ammonium sulphate (0.8 M), () Buffer containing added ammonium sulphate (1.6 M).
As a whole, biomass deposition experiments have indicated that Cu (II) would promote
more cell deposition than other metal ions. Cell aggregation can occur in buffers containing
moderate-to-high concentration of added salts. However, in the absence of cell-to-support
interaction further deposition due to cell aggregation is not possible. Summarizing, IMAC
systems where biomass deposition could play a role seem to be limited to a) immobilized
Cu (II), b) at pH within the range 7.0 to 7.6, and c) with salt containing buffers.
2.4.4.8 Chelating systems in the context of EBA adsorbents
Figure 6 shows the correlation between the attachment efficiency parameter (α) and the
secondary-pocket-depth (free energy of interaction between a cell particle and a
chromatographic bead). Points corresponding to ion-exchangers and hydrophobic
interaction systems are presented as a reference (Tari et al. 2008). It can be observed that
Chelating materials are generally characterized by low deposition parameter values (α ≤
0.15) which correlate with limited energy pockets (≤ |20| k T). However, the effect of
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2.4.5 Conclusions
A comprehensive approach to understand biomass deposition onto Chelating
chromatogrpahic supports has utilized principles of colloid theory to explain biomass-
adsorbent attachment at the local (particle) level. Acid-base (AB) interactions wereincluded in the extended approach (XDLVO) so as to explain biomass interaction and
aggregation phenomena. Besides, Lifshitz-Van der Waals (LW) (EL) were considered.
Electrostatic interactions played a minor role due to the high conductivity of the process
buffer involved.
Interaction between biomass particles and chromatographic beads was studied by
calculating interfacial free energy (U) vs. distance (H) profiles. These calculations were based on the experimental determination of contact angles with three diagnostic liquids and
the additional information gathered from zeta potential determinations.
Qualitative and quantitative data from cell deposition experiments has revealed a
predominant role of cell-to-support interaction. Cell-to-cell aggregation showed a less
impact on total biomass deposition in Chelating systems. Analysis of the correlation
between the depth of the interaction energy pockets and the deposition coefficient values
for Chelating materials in the presence of sodium chloride at neutral pH reveled differences
with ion-exchange and hydrophobic interaction adsorbents. The strength of biomass
interaction was enhanced by having copper (II) ions immobilized onto the solid phase.
Summarising, it was demonstrated that cell-to-adsorbent (interaction) and –to a lesser
extent- cell-to-cell (aggregation) phenomena are responsible to biomass deposition onto
Chelating chromatographic materials. Interaction and aggregation was inferred from
XDLVO calculations on the basis of contact angle and zeta potential measurements.Moreover, experimental confirmation was obtained by independent methods like biomass
deposition experiments and confocal microscopy.
2.4.6 Acknowledgements
RRVP gratefully acknowledges a doctoral fellowship from Jacobs University. The authors
would thank Dr. Carl Bolster for his valuable discussions during the work.
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2.4.7 Nomenclature
AB Acid-Base
DLVO Classical DLVO theory (Derjaguin, Landau, Verwey and Overbeek)
CHE Chelating [Iminodiacetic Group - IDA]
EBA Expanded Bed Adsorption
EL Electrostatic
LW Lifshitz-Van der Waals
A Hamaker constant [k T]
IC Intact yeast cell particles
IMAC Immobilized metal affinity chromatography LW γ Apolar or Lifshitz-Van der Waals component of surface tension [mJ⋅m-2]
ABγ Polar or acid–base component of surface tension [mJ⋅m-2]
−γ Electron-donor component of surface tension (Lewis base) [mJ⋅m-2]
+γ Electron-acceptor component of surface tension (Lewis acid) [mJ⋅m-2]
Ε Dielectric constant of the medium [-]
R Radius of the particle [m]
Ζ Zeta potential [mV]
κ Inverse of Debye length [m]
H Distance between surfaces, measured from outer edge [m]
XDLVO Extended DLVO theory, according to Van Oss
ΔG Interfacial free energy @ 1.57 Å approach [mJ⋅m-2]
U Interfacial energy of interaction [k T]
K Boltzmann constant [J⋅K -1]
T Absolute temperature [K]
h0 Closest distance of approximation [1.57 Å]
α Lumped biomass deposition coefficient [-]
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2.4.8 References
Bak H, Thomas ORT. 2007. Evaluation of commercial chromatographic adsorbents for the
direct capture of polyclonal rabbit antibodies from clarified antiserum. J
Chromatogr B 848(1):116-130.Bayramoglu G, Celik G, Arica MY. 2006. Immunoglobulin G adsorption behavior of l-
histidine ligand attached and Lewis metal ions chelated affinity membranes.
Colloids Surf A Physicochem Eng Asp 287(1-3):75-85.
Bos R, Van der Mei HC, Busscher HJ. 1999. Physico-chemistry of initial microbial
adhesive interactions--its mechanisms and methods for study. FEMS Microbiol Rev
23(2):179-230.
Brant JA, Childress AE. 2002. Assessing short-range membrane-colloid interactions usingsurface energetics. J Membr Sci 203:257-273.
Brant JA, Childress AE. 2004. Colloidal adhesion to hydrophilic membrane surfaces. J
Membr Sci 241(2):235-248.
Butkus MA, Grasso D. 1998. Impact of Aqueous Electrolytes on Interfacial Energy. J
Colloid Interface Sci 200(1):172-181.
Chaga GS. 2001. Twenty-five years of immobilized metal ion affinity chromatography:
past, present and future. J Biochem Biophys Methods 49(1-3):313-334.
Clemmitt RH, Chase HA. 2000. Immobilised metal affinity chromatography of [beta]-
galactosidase from unclarified Escherichia coli homogenates using expanded bed
adsorption. J Chromatogr A 874(1):27-43.
Fernandez-Lahore HM, Geilenkirchen S, Boldt K, Nagel A, Kula MR, Thommes J. 2000.
The influence of cell adsorbent interactions on protein adsorption in expanded beds.
J Chromatogr A 873(2):195-208.
Gaberc-Porekar V, Menart V. 2001. Perspectives of immobilized-metal affinity
chromatography. J Biochem Biophys Methods 49(1-3):335-360.
Gallardo-Moreno AM, Gonzalez-Martin ML, Perez-Giraldo C, Garduno E, Bruque JM,
Gomez-Garcia AC. 2002. Thermodynamic Analysis of Growth Temperature
Dependence in the Adhesion of Candida parapsilosis to Polystyrene. Appl Environ
Microbiol 68(5):2610-2613.
Ganeva V, Galutzov B, Teissie J. 2004. Flow process for electroextraction of intracellular
enzymes from the fission yeast, Schizosaccharomyces pombe. Biotechnol Lett
26(11):933-7.
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Grasso D, Subramaniam K, Butkus M, Strevett K, Bergendahl J. 2002. A review of non-
DLVO interactions in environmental colloidal systems. Rev Environ Sci Biotechnol
1(1):17-38.
Henriques M, Gasparetto K, Azeredo J, Oliveira R. 2002. Experimental methodology to
quantify Candida albicans cell surface Hydrophobicity. Biotechnol Lett 24:1111–
1115.
Klotz SA, Drutz DJ, Zajic JE. 1985. Factors Governing Adherence of Candida Species to
Plastic Surfaces. Infect Immun 50(1):97-191.
Ljungh Å, Wadström T. 1982. Salt aggregation test for measuring cell surface
hydrophobicity of urinaryEscherichia coli. Eur J Clin Microbiol 1(6):388-393.
Noronha S, Kaufman J, Shiloach J. 1999. Use of Streamline chelating for capture and
purification of poly-His-tagged recombinant proteins. Bioseparation 8(1):145-151.
Ottewill RH, Shaw JN. 1972. Electrophoretic studies on polystyrene lattices. J Electroanal
Chem 37:133-142.
Poulin F, Jacquemart R, De Crescenzo G, Jolicoeur M, Legros R. 2008. A Study of the
Interaction of HEK-293 Cells with Streamline Chelating Adsorbent in Expanded
Bed Operation. Biotechnol Prog 24(1):279-282.
Redman JA, Walker SL, Elimelech M. 2004. Bacterial Adhesion and Transport in Porous
Media: Role of the Secondary Energy Minimum. Environ Sci Technol 38(6):1777-1785.
Tari C, Vennapusa RR, Cabrera RB, Fernandez-Lahore M. 2008. Colloid deposition
experiments as a diagnostic tool for biomass attachment onto bioproduct adsorbent
surfaces. J Chem Technol Biotechnol 83:183-191.
Ting. Y-P, Sun G. 2000. Use of polyvinyl alcohol as a cell immobilization matrix for
copper biosorption by yeast cells. J Chem Technol Biotechnol 75(7):541-546.
Ueda EKM, Gout PW, Morganti L. 2003. Current and prospective applications of metalion-protein binding. J Chromatogr A 988(1):1-23.
Van Oss CJ. 1993. Acid-base interfacial interactions in aqueous media. Colloids Surf A
Physicochem Eng Asp 78:1-49.
Van Oss CJ. 1994. Interfacial forces in aqueous media. New York: M. Dekker. viii,440p. p.
Van Oss CJ. 2003. Long-range and short-range mechanisms of hydrophobic attraction and
hydrophilic repulsion in specific and aspecific interactions. J Mol Recognit
16(4):177-190.
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Vennapusa RR, Hunegnaw SM, Cabrera RB, Fernandez-Lahore M. 2008. Assessing
adsorbent-biomass interactions during expanded bed adsorption onto ion exchangers
utilizing surface energetics. J Chromatogr A 1181(1-2):9-20.
Willoughby NA, Kirschner T, Smith MP, Hjorth R, Titchener-Hooker NJ. 1999.
Immobilised metal ion affinity chromatography purification of alcohol
dehydrogenase from baker's yeast using an expanded bed adsorption system. J
Chromatogr A 840(2):195-204.
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2.5 Surface energetics to assess microbial adhesion ontofluidized chromatography adsorbents
Rami Reddy Vennapusa, Sabine Binner, Rosa Cabrera, and Marcelo Fernandez-Lahore*
Downstream Processing Laboratory, Jacobs University Bremen gGmbH, Campus Ring 1,D-28759, Bremen, Germany.
2.5.1 Abstract
Cell-to-support interaction and cell-to-cell aggregation phenomena have been studied in a
model system composed of intact yeast cells and agarose-based chromatography adsorbent
surfaces. Biomass components and beaded adsorbents were characterized by contact angledeterminations with three diagnostic liquids and, complementarily, by zeta potential
measurements. Such experimental characterization of the interacting surfaces has allowed
the calculation of interfacial free energy of interaction in aqueous media vs. distance
profiles. The extent of biomass adhesion was inferred from calculations performed
assuming standard chromatographic conditions, but different adsorption modes. Several
stationary support / mobile phase systems were considered i.e. ion-exchange, hydrophobic
interaction, and pseudo-affinity. Calculated interaction energy minima revealed marginalattraction between cells and cation-exchangers or agarose-matrix beads (U≤ |10-20|k T) but
strong attraction with anion-exchangers (U≥ |200-1000| k T). Other systems including
hydrophobic interaction and chelating beads showed intermediate energy minima values (U
≈ |40-100| k T) for interaction with biological particles. However, calculations also showed
that working conditions in the presence of salt can promote cell aggregation besides cell-to-
support interaction. Predictions based on the application of the XDLVO approach were
confirmed by independent experimental methods like biomass deposition experiments andlaser diffraction spectroscopy. Understanding biomass attachment onto chromatographic
supports can help in alleviating process limitations normally encountered during direct
(primary) sequestration of bioproducts.
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2.5.2 Introduction
Expanded Bed Adsorption (EBA) has been proposed as anintegrative downstream
processing technology allowing the direct capture of targeted species from an unclarified
feedstock e.g. a cell containing fermentation broth. This unit operation has the potential tocombine solids removal, product concentration, and partial purification in a single
processing step. The application of EBA implies, however, that intact cell particles or cell
debris present in the feedstock will interact –in a minor or larger extent- with fluidized
adsorbent beads. It is already known that interaction between biomass and the adsorbent
phase may lead to the development of poor system hydrodynamics and therefore, impaired
sorption performance under real process conditions. Moreover, biomass interaction would
result in increased buffer consumption in order to remove and wash away sticky biological particles. Biomass components can also mask binding sites thus reducing their availability
to the targeted species. These phenomena i.e. decreased sorption performance and buffer
consumption is detrimental to cost-efficient processing utilizing expanded bed adsorption
and other direct sequestration unit operations(Fernandez-Lahore et al. 1999).
The deposition of microbial cells or biomass debris is related to the physico-chemical
characteristics of the cell-surface components. These surfaces are in most cases of anionic
nature due to the existence of negatively charged chemical groups like phosphate,
carboxylate, and sulphate moieties. However, the cell envelop can also exert hydrophobic
interaction due to the presence of S-layer proteins, amphipathic polymers, and lipids.
Therefore, microbial deposition onto (process) surfaces will be driven by the polymeric
components of the rigid outer boundary and eventually, by the presence of cell-surface
appendages (if present). On the other hand, biomass deposition will be governed by the
nature (material structure) and functionality (ligand type) of the surface e.g. the structure of
the chromatographic support.
Previous studies on biomass-adsorbent interactions were restricted to simple diagnostic
tests to determine the extent of cell –or cell debris- attachment to the desired
chromatographic supports (Feuser et al. 1999). The measurement of the zeta potential has
been proposed for a better understanding and prediction of biomass-adsorbent interactions
during ion-exchange expanded bed adsorption (Lin et al. 2006). Such systems are obviously
dominated by Coulomb-type interactions and therefore, non-electrostatic interactions areanticipated to play a minor role (Vergnault et al. 2007). Recent studies have highlighted
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2.5.3 Materials and Methods
2.5.3.1 Materials
Chromatographic matrices and columns were purchased from GE Health Care (Munich,Germany). α-bromonaphtalene and formamide were obtained from Fluka (Buchs,
Switzerland). Water was ultra pure quality. All other chemicals were analytical grade.
2.5.3.2 Generation of biomass
Yeast cells (Saccharomyces cerevisiae FY 86, wild type, haploid) were cultivated in shake-
flasks, harvested at late exponential phase by centrifugation, and washed three times with
10 mM phosphate buffer solutions, as previously described (Ganeva et al. 2004). Cells wereemployed immediately after preparation.
2.5.3.3 Contact angle measurements
Preparation of intact yeast cells for contact angle measurements was performed as
described (Henriques et al. 2002). Washed cells were suspended to 10% (w/v) in 20mM
phosphate buffer, pH 7 (ion-exchange buffer / Buffer A /σ = 4 mS·cm-1), Buffer A
containing 1.2 M ammonium sulphate (hydrophobic interaction buffer / Buffer B /σ = 145mS·cm-1), and 20 mM phosphate buffer adjusted to pH 7.6 with 250 mM sodium chloride
(Chelating buffer / Buffer C /σ = 30 mS·cm-1). Cells were subsequently poured onto agar
plates containing 10% glycerol and 2% agar-agar. The plate was allowed to dry for 24-36
hours at room temperature on a properly leveled surface free from dust. Salt crystallization
was avoided. Agar plates without cell spreads were utilized as control.
Contact angles were measuredas per the sessile drop method (Sharma and Rao 2002)
utilizing a commercial goniometric system (OCA 20, Data Physics instruments GmbH,
Filderstadt, Germany). The three diagnostic liquidsα-bromonaphtalene, formamide, and
water were employed. All the measurements were performed in triplicate and at least 20
contact angles per samples were measured.
Contact angle determination on buffer-equilibrated chromatographic beads was performed
utilizing the same physicochemical conditions and experimental procedures described for
cell particles. Previous to pouring onto the agar plates, matrix beads were frozen in liquidnitrogen and crushed mechanically. Crushing efficiency was assessed by microscopic
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studies were done by injecting a 4 ml biomass pulse (OD≈ 0.8 AU). Experiments were
performed utilizing the above described buffer solutions. The operational flow rate was
76.4 cm·h-1. Particle breakthrough curves were obtained by monitoring the effluent
suspensions at 600 nm. On the basis of such data, a lumped deposition parameter (α) wascalculated according to Redman et al. (Redman et al. 2004).
2.5.3.7 Energy-distance profile calculations
The total interaction energy between a colloidal particle and a solid surface can be
expressed in terms of the extended DLVO theory as:
ABmwc
ELmwc
LW mwc
XDLVOmwc U U U U ++= (1)
where UXDLVO is the total interaction energy in aqueous media, ULW is the LW interaction
term, and UEL is the EL interaction term. The subscriptm is utilized for the
chromatographic matrix (adsorbent bead), w refers to the watery environment, and c to the
colloidal (cell) particle. A third short-range (≤ 5 nm) Lewis AB term is included to account
for “hydrophobic attractive” and “hydrophilic repulsive” interactions (Van Oss 2003).
Material surface energy parameters (tensions) can be calculated from contact angle
measurements utilizing three diagnostic liquids, according to Van Oss (Van Oss 1994). In
turn, this data can be employed to evaluate the free energy of interaction between two
defined surfaces (ΔGLW and ΔGAB). ΔG represents here the interaction energy per unit area
between two (assumed)infinite planar surfaces bearing the properties of the adsorbent bead
and the cell (interaction) or two cells (aggregation), respectively. Interaction between any
of these two surfaces are evaluated at a closest distance of approximation (h0 ≈ 0.158 nm)
(Bos et al. 1999). When integrated into mathematical expressions accounting the geometric
constraints existing between two interacting bodies,ΔG values can be utilized to calculatethe corresponding energy-distance profile (U vs. H). Details of this procedure were
published (Bos et al. 1999; Vennapusa et al. 2008).ΔGmwc and ΔGcwc was calculated
according to Vennapusa et al (Vennapusa et al. 2008).ΔGLW are also related to the
Hamaker constant, as follows:
LW Gh A Δ−= 2012π (2)
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UEL energy-distance profile can be calculated, assuming either plate-sphere or sphere-
sphere geometry, upon experimental determination of particle zeta potential values. Zeta
potential values are measured by electrophoretic mobility experiments (Vennapusa et al.
2008). Calculations were performed employing a commercial software package (GraphPad
Prism, GraphPad Software Inc., San Diego, CA, USA).
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2.5.4 Results and discussions
2.5.4.1 Contact angle measurements and surface energy components
The diagnostic liquids water, formamide, andα-bromonaphtalene were employed to
measure contact angles onto homogeneous lawns of the materials under study i.e. intact
yeast cells or crushed Sepharose beads. The sessile drop technique was employed. The
utilization of the agar plate method assured that contact angle values were obtained for the
mentioned materials in the hydrated state. Diagnostic liquids were chosen to have a higher
surface tension than the sample materials so as to allow for stable drop formation and
accurate contact angle determination. Materials were carefully equilibrated with buffers
commonly utilized in practice.
Contact angle determinations with three different liquids were performed so as to consider
conditions prevailing in ion-exchange, hydrophobic interaction, or pseudo-affinity
chromatography. Table 1 shows contact angle values obtained by performing
measurements onto layered fragments (< 10µm) of the various chromatographic supports,
including Q-XL, DEAE, SP, Chelating-Cu2+, Phenyl, and agarose-base matrix beads.
At neutral pH, adsorbent contact angle values were≈ 7-10 for water and≈ 10-13 for formamide, when considering the base-matrix, chelating matrix, the anion-exchanger
DEAE-Sepharose, and the cation-exchanger SP-Sepharose. On the other hand, for the
mentioned adsorbents the contact angle values withα-bromonaphtalene were≈ 39-45.
Overall, these values indicate the very hydrophilic nature of such materials. For the
composite support XL-Q Sepharose an increase in the contact angle value for α-
bromonaphtalene was noticed, which might indicate an even increased hydrophilic
character due to the presence of superficial Dextran chains. As expected due to the presenceof hydrophobic ligands, the Phenyl-Sepharose material showed decreased contact angle
values with α-bromonaphtalene. These data indicate that similarities and differences
between different supports can be actually observed on the basis of contact angle
determinations. Published work have shown that the addition of salt can actually influence
the contact angle values -and correspondingly the surface free energy components-
obtained for some types of mineral particles (Karagüzel et al. 2005).
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Table 2: Contact angle measurements for yeast cells. Determinations were performedunder conditions normally encountered in ion-exchange, hydrophobic interaction, andchelating systems.
Experimental contact angle determinations were utilized to calculate surface energy
parameters for chromatographic media and biomass particles according to the acid-base
approach (Bos et al. 1999). Table 3 depicts the surface energy components (γ) calculated
for various chromatographic supports under typical buffer conditions ion-exchange buffer /
20mM phosphate buffer pH 7.0 (Buffer A ), Hydrophobic interaction buffer (Buffer A
containing 1.2 M ammonium sulphate and Chelating buffer (20 mM phosphate buffer
adjusted to pH 7.6 with 250 mM sodium chloride and 1mM imidazole. These supports can be distinguished on the basis of their characteristicγLW and γ+ (electron acceptor
component of the AB surface tension) parameters. According to such parameters, the
chromatographic supports can be ordered as follows:
γLW → [Phenyl] > [Chelating] ≈ [Agarose-matrix] ≈ [DEAE≈ SP] > [Q-XL]
γ+ → [Q-XL] >> [Agarose-matrix] ≈ [Chelating] > [DEAE≈ SP] > [Phenyl]
As a whole these results indicate that each of the materials studied possess characteristic
surface energetic properties that are experimentally accessiblevia contact angle
measurements with three diagnostic liquids. For example, Phenyl supports presented high
γLW values (∼39 mJ·m-2) but low γ+ values (1.3 mJ·m-2) in comparison with the agarose-
backbone bead. On the contrary, the composite material Q-XL showed the inverse tendency
i.e. highγ+ values (3.9 mJ·m-2) but lowγLW values (∼29 mJ·m-2).
Yeast cell suspension Contact angle ( θ) (Degrees)
Water Formamideα -
Bromonaphtalene
IEX-type buffer 15.0 ± 2.2 14.0± 1.0 54.0± 1.8
HIC-type buffer 10.0 ± 0.5 12.0± 1.1 33.0± 2.4
Chelating-type buffer 11.7 ± 2.4 13.7± 1.7 49.3± 1.0
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Table 3: Surface energy parameters for beaded chromatographic supports calculated fromcontact angle measurements under standard buffer compositions.
Support type Surface energy parameters [mJ·m -2]
γLW γ+ γ - γAB γTOT ΔG sws
Q-XL 28.9 3.9 53.2 28.8 57.8 +26.6
DEAE 34.1 2.3 54.5 22.3 56.7 +30.7
SP 35.0 2.0 55.7 21.1 56.4 +31.9
Chelating- CU 2+ 32.3 3.0 53.7 25.0 57.4 +26.3
Phenyl 39.3 1.3 55.1 16.9 56.3 +26.8
Agarose bead 32.8 2.9 53.6 24.9 57.7 +28.1
Modification in the surface characteristics of intact yeast particles were also noticed upon
observation of the values taken by theγLW and γ+ parameters (Table 4), according to the
chemical environment provided by the proposed mobile phases:
γLW → [HIC Buffer ] >> [Chelating Buffer ] > [IEX Buffer ]
γ+ → [IEX Buffer ] > [Chelating Buffer ] >> [HIC Buffer ]
These results are indicative of an increased hydrophobic character for cells in the presence
of high concentrations of ammonium sulphate (HIC Buffer) and indicative of an increased
Lewis-acid character for cells in dilute phosphate buffer (IEX Buffer).
Summarizing, surface energy parameters are able to characterize the various
chromatographic systems under consideration. As observed from Table 3 and 4, the
parameter Δ Gsws took always values +24-31 mJ·m-2 reflecting the hydrophilic nature of the
yeast cells and the chromatographic beads. For comparison, the Δ Gsws of hydrophilic
repulsion for Dextran T-150 is +41.2 mJ·m-2 (Van Oss 2003).
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Table 4: Surface energy parameters for yeast cells calculated from contact anglemeasurements, under conditions provided by typical chromatographic mobile phases.
Yeast cellsuspension
Surface energy parameters [mJ·m -2]
γLW γ+ γ - γAB γTOT ΔG sws
IEX-type buffer 27.9 4.4 51.5 30.1 58.3 +24.3HIC-type buffer 37.9 1.5 54.8 18.2 56.0 +27.0Chelating-type
buffer30.3 3.5 53.4 27.3 57.6 +25.9
2.5.4.2 Interfacial free energy of interaction and energy-distance profilesInteraction between biomass particles and chromatographic beads can be understood by
calculating interfacial free energy (U) vs. distance (H) profiles. These calculations are
based on the experimental determination of contact angles with three diagnostic liquids and
the additional information gathered from zeta potential determinations. Table 5 depicts the
interfacial free energy of interaction between a biomass particle and chromatographic
adsorbent surfaces in aqueous media at closest distance of approximation (1.57 Å).
Furthermore, this table also gives information on zeta-potential values for the mentionedadsorbents.
Hydrophobic interaction and immobilized-metal affinity chromatography are operated in a
context characterized by an increased salt concentration (high ionic strength and
conductivity) in the mobile phase, as well as, by uncharged beaded adsorbents. Therefore, it
is expected that the information provided by contact angle determination will be more
relevant to understand cell-to-support interactions than the information providedvia z- potential determinations. This situation is radically different from the case of the ion-
exchangers where, due to the low conductivity of the mobile phases and the charged nature
of the adsorbents, zeta-potential has been established as a parameter describing biomass
deposition onto process supports (Lin et al. 2006).
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The Hamaker constant ( A) for the interaction chromatographic systems under study were
calculated fromΔGLW according to Equation (2). A values, according to the adsorption
mode, can be ordered as follows:
HIC (1.1k T) > IMAC (0.40k T) > IEX (0.34k T)
Table 5: Interfacial free energy of interaction between intact yeast cells and agarose beadedsupports, at closest distance of approximation. Calculations were performed assuminginteraction under typical bioprocess conditions. Zeta-potential values for thechromatographic beads are provided.
Figure 1: Total free energy of interaction as function of distance between intact yeast cellsand several chromatographic supports, under conditions provided by commonly utilizing
mobile phases. (— ) Q XL, (— ) DEAE, (— ) Phenyl, (— ) IMAC-Cu+2
, (— ) Base, (— )SP.
Support ΔG [mJ·m -2] Zeta potential [mV ]
ΔGLW
ΔGAB
Q-XL -0.9 +26.3 +20.0DEAE -1.4 +28.7 +15.0
SP -1.5 +29.7 -30.0Chelating- CU 2+ -1.7 +29.6 -8.0
Phenyl -4.8 +36.5 -0.1Agarose bead -1.3 +27.6 -2.0
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Figure 1 depicts interaction energy (U) vs. distance (H) profiles calculated according to the
XDLVO approach, utilizing the data provided before (Table 5). Calculated secondary
energy minima occurring at≈ 5-10 nm upon interaction of a yeast cell and the adsorbent
surface were observed. Calculations assumed sphere-to-plate geometry. The depth of such
energy minima shifted from low to moderate values≈ -5-20 k T in dilute buffer solutions for
the agarose-base material or the cation-exchanger down to intermediate values≈ -40-120
k T at high salt concentrations for Chelating and Phenyl supports. Anion exchangers
showed, in 20 mM phosphate buffer, energy pockets in the range -200-400 kT. These
values increased to > |1000| kT in 10 mM phosphate buffer. The information provided by
analyzing U vs. H profiles is in full agreement with previous experimental data concerning
biomass interaction onto expanded bed adsorbents (Fernandez-Lahore et al. 1999).
Application of the extended DLVO approach is justified since due to the very polar nature
of the buffer solutions where cell-adsorbent interactions take place; these interactions are
known to be strongly influenced by polar Lewis acid-base (AB) or electron-acceptor /
electron-donor forces. Contributions by electric double layer (EL) forces and particularly
contributions by apolar Lifshitz-van der Waals (LW) forces are also expected to occur.
The extended DLVO approach has served to explain the behavior of many other colloidalsystems. Brandt and Childress have demonstrated that short-range interactions between
synthetic membranes and bio-colloids can be better explained by taking into consideration
the role of AB forces(Brant and Childress 2002). Van Oss and coworkers have studied the
stability of a thixotropic suspension of 2μm hectorite particles and concluded that Lewis
acid-base interactions play a key role in the coagulation dynamics of such system (Grasso
et al. 2002).
2.5.4.3 Interfacial free energy of aggregation and energy-distance profiles
Contact angle and zeta potential determinations, as reported in this work have been utilized
to calculate energy vs. distance profiles between two intact yeast cells. Table 6 shows
ΔGLW, ΔGAB, and zeta-potential determinations for yeast cells in various buffers. Sphere-to-
sphere geometry was assumed. These XDLVO calculations can be observed in Figure 2 and
they have indicated that cell-to-cell aggregation might have the chance to occur under the
conditions provided by the hydrophobic interaction buffer e.g. at high conductivity values.In the later case, a secondary energy minima (∼-30 k T) can be anticipated at a distance of 5
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nm. Cell clumping in the presence of salt was confirmed by confocal microscopy and laser
diffraction studies (Data not shown).
On the other hand, moderate energy minima were observed for aggregation of cells
suspended in chelating buffer (∼-8 k T @ 5 nm). However, moderate cell clumping could
exist in buffers containing 250 mM sodium chloride i.e. IMAC buffer.
The secondary interfacial free energy well between to yeast cell was of a very limited depth
in the case of dilute phosphate buffer (∼-4 k T @ 5 nm). These low attractive forces would
be easily disrupted by the hydrodynamic stress normally encountered in most processing
schemes. Therefore, cell-to-cell aggregation would rarely take place when biological
particles are suspended in dilute buffer solution due to higher propensity of the cellcomplex to be disrupted by shear drag.
The mentioned aggregation behavior of yeast particles suspended in buffers of various
chemical compositions is also reflected by the values of the corresponding Hamaker
constants, as follows:
HIC (2.0k T) > IMAC (0.65k T) > IEX (0.34k T)and therefore, LW forces can be considered of importance regarding aggregation
phenomena, particularly for cells suspended in high conductivity buffers.
Table 6: Interfacial free energy of aggregation between yeast cells at closest distance of approximation. Calculations were performed assuming standard chromatographicconditions. Zeta potential values are provided.
Yeast cells ΔG [mJ·m-2
] Zeta potentials [mV ] ΔG LW ΔG AB
IEX-type buffer -1.5 +25.1 -18.0
HIC-type buffer -8.8 +35.9 -0.1
Chelating-type
buffer-2.8 +28.7 -8.0
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Figure 2: Interfacial free energy as function of distance between two yeast cells under mobile phases having typical chemical compositions for ion-exchange, hydrophobicinteraction, and immobilised-metal ion affinity chromatography. (— ) IEX buffer, (— )Chelating-Cu2+, (— ) HIC.
2.5.4.4 Biomass deposition experiments
Biomass deposition experiments were performed to evaluate overall yeast cells deposition
onto ion-exchange, hydrophobic interaction, and pseudo-affinity chromatographic supports.
This allowed an independent experimental verification of the predictions made on the basis
of energy vs. distance calculations. Interaction phenomena taken place in each of these
chromatographic systems are verified utilizing mobile phase standard compositions i.e. IEX
buffer, IMAC buffer and HIC buffer.
Figure 3 depict the cell effluent profiles measured for the various chromatographic systems
i.e. diverse combinations of solid and mobile phases. Biomass deposition experiments
showed a characteristic cell effluent profile for each of the systems under study. Particle
retention was extremely high for Q-XL and DEAE materials, moderate for Phenyl and
Chelating supports, and very low for the cation-exchanger and the base matrix. Biomass
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deposition behavior was reflected by an “attachment efficiency” number (α), a lump
parameter describing such phenomena. Qualitative and quantitative evaluation of cell
deposition experiments revealed several underlying phenomena like cell-to-support
attachment (interaction), prevention of cell depositions by already deposited biomass particles (blocking), and cell-to-cell ripening (aggregation). Cell-to-cell aggregation might
represent and important mechanism promoting overall cell attachment during biomass
deposition experiments. Therefore, increased values for the lumpedα parameter might
indicate not only stronger cell-to-supportinteraction but enhanced cell-to-cellaggregation .
Consequently, results from biomass deposition experiments will reveal conditions
prevailing during real process performance where both interaction and aggregation
phenomena can coexist.
Figure 3: Biomass deposition experiments with intact yeast cells onto several processsurfaces. Mobile phases of standard chemical compositions were employed. () QXL, ( )DEAE, ( ) Phenyl,( ) IMAC Cu+2, ( ) Base, ( ) SP.
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Figure 4 shows the correlation between the attachment efficiency parameter and the depth
of the secondary free energy of interaction between a cell particle and a chromatographic
bead. Points corresponding to the various chromatographic systems can be observed. Three
main groups can be clearly distinguished:
a) Group I characterized byα ≤ 0.15 and U≤ |10-20| k T. This group contains systems
were both cell-to-support interaction and cell-to-cell aggregation is negligible and
therefore, overall biomass deposition phenomena can be neglected[CEX].Underlying interaction mechanisms within Group I are repulsive EL and AB forces
with moderate attractive LW forces. Cell-to-cell forces are predominantly repulsive
mainly due to AB and EL components.
b) Group II characterized by 0.2≤ α ≤ 0.4 and U ≈ |50-100| k T. This group is
composed by systems were mixed phenomena occur i.e. there is a degree of
biomass deposition onto the solid phase but additional cell entrapment can exists
due to aggregation [Phenyl and Chelating]. Underlying interaction mechanisms
within Group II attractive LW forces, moderately repulsive AB forces, and a
negligible EL component. Cell-to-cell forces are predominantly attractive mainly
due to LW forces.
c) Group III characterized byα > 0.90 and U > |200-1000| k T. This group represents
systems with strong cell-to-support interaction, mainly mediated by electrostatic
attraction (EL) between the interacting bodies. AB and LW forces play a minor role
in this case.
For expanded bed adsorption (EBA) which is the more studied system concerning biomassdeposition evidence exits in the open literature regarding problem-free operation was
consistently reported for CEX (Group I). On the contrary, biomass interference with
appropriate sorption performance was noticed for AEX (Group III). Information regarding
Group II chromatographic systems is scarce. However, recent reports also indicate that such
process combinations are suffering from biomass compatibility limitation (Poulin et al.
2008; Smith et al. 2002).
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Figure 4: Correlation between the depth of energy pocket and lump factor alpha for several process systems.( ) Cation exchangers, ( ) Base matrix, ( ) Chelating Cu2+, ( ) Phenyl,[( ) DEAE, ( ) Q-XL in 10mM PO4 buffer].
2.5.5 Conclusions
A comprehensive approach to understand biomass attachment onto chromatography
adsorbent surfaces with special emphasis on commonly utilized chromatographic systems
have included several interaction forces, according to the XDLVO approach. These
calculations were based on the experimental determination of contact angles with three
diagnostic liquids and the additional information gathered from zeta-potentialdeterminations.
Qualitative and quantitative evaluation of cell adhesion experiments have revealed several
underlying phenomena like cell-to-support sticking, prevention of cell depositions by
already deposited biomass particles (blocking), and cell-to-cell aggregation (ripening). A
correlation between the depth of the interaction energy pockets and the deposition
coefficient values was established and three distinct groups defined.
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ABγ Polar or acid–base component of surface tension [mJ⋅m-2]−γ Electron-donor component of surface tension (Lewis base) [mJ⋅m-2]
+γ Electron-acceptor component of surface tension (Lewis acid) [mJ⋅m-2]
ζ Zeta potential [mV]
h0 Closest distance of approximation [1.57 Å]
α Lumped biomass attachment coefficient [-]
ΔG Interfacial free energy @ 1.57 Å approach [mJ⋅m-2]
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2.5.8 Referances
Bos R, Van der Mei HC, Busscher HJ. 1999. Physico-chemistry of initial microbial
adhesive interactions--its mechanisms and methods for study. FEMS Microbiol Rev
23(2):179-230.Brant JA, Childress AE. 2002. Assessing short-range membrane-colloid interactions using
surface energetics. J Membr Sci 203:257-273.
Butkus MA, Grasso D. 1998. Impact of Aqueous Electrolytes on Interfacial Energy. J
Colloid Interface Sci 200(1):172-181.
Fernandez-Lahore HM, Kleef R, Kula M, Thommes J. 1999. The influence of complex
biological feedstock on the fluidization and bed stability in expanded bed
adsorption. Biotechnol Bioeng 64(4):484-96.Feuser J, Walter J, Kula MR, Thommes J. 1999. Cell/adsorbent interactions in expanded
bed adsorption of proteins. Bioseparation 8(1-5):99-109.
Ganeva V, Galutzov B, Teissie J. 2004. Flow process for electroextraction of intracellular
enzymes from the fission yeast, Schizosaccharomyces pombe. Biotechnol Lett
26(11):933-7.
Grasso D, Subramaniam K, Butkus M, Strevett K, Bergendahl J. 2002. A review of non-
DLVO interactions in environmental colloidal systems. Rev Environ Sci Biotechnol
1(1):17-38.
Henriques M, Gasparetto K, Azeredo J, Oliveira R. 2002. Experimental methodology to
quantify Candida albicans cell surface Hydrophobicity. Biotechnol Lett 24:1111–
1115.
Karagüzel C, Can MF, Sönmez E, Celik MS. 2005. Effect of electrolyte on surface free
energy components of feldspar minerals using thin-layer wicking method. J. Colloid
Interface Sci. 285(1):192-200.
Lin DQ, Zhong LN, Yao SJ. 2006. Zeta potential as a diagnostic tool to evaluate the
biomass electrostatic adhesion during ion-exchange expanded bed application.
Biotechnol Bioeng 95(1):185-91.
Ottewill RH, Shaw JN. 1972. Electrophoretic studies on polystyrene lattices. J Electroanal
Chem 37:133-142.
Poulin F, Jacquemart R, DeCrescenzo G, Jolicoeur M, Legros R. 2008. A Study of the
Interaction of HEK-293 Cells with Streamline Chelating Adsorbent in Expanded
Bed Operation. Biotechnol Prog 24(1):279-282.
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Redman JA, Walker SL, Elimelech M. 2004. Bacterial Adhesion and Transport in Porous
Media: Role of the Secondary Energy Minimum. Environ Sci Technol 38(6):1777-
1785.
Sharma PK, Rao KH. 2002. Analysis of different approaches for evaluation of surface
energy of microbial cells by contact angle goniometry. Adv Colloid Interface Sci
98(3):341-463.
Smith MP, Bulmer MA, Hjorth R, Titchener-Hooker NJ. 2002. Hydrophobic interaction
ligand selection and scale-up of an expanded bed separation of an intracellular
enzyme from Saccharomyces cerevisiae. J Chromatogr A 968(1-2):121-128.
Tari C, Vennapusa RR, Cabrera RB, Fernandez-Lahore M. 2008. Colloid deposition
experiments as a diagnostic tool for biomass attachment onto bioproduct adsorbent
surfaces. J Chem Technol Biotechnol 83:183-191.
Van Oss CJ. 1994. Interfacial forces in aqueous media. New York: M. Dekker. viii, 440p.
p.
Van Oss CJ. 2003. Long-range and short-range mechanisms of hydrophobic attraction and
hydrophilic repulsion in specific and aspecific interactions. J Mol Recognit
16(4):177-190.
Vennapusa RR, Hunegnaw SM, Cabrera RB, Fernandez-Lahore M. 2008. Assessing
adsorbent-biomass interactions during expanded bed adsorption onto ion exchangersutilizing surface energetics. J Chromatogr A 1181(1-2):9-20.
Vergnault H, Willemot R-M, Mercier-Bonin M. 2007. Non-electrostatic interactions
between cultured Saccharomyces cerevisiae yeast cells and adsorbent beads in
expanded bed adsorption: Influence of cell wall properties. Process Biochem
42(2):244-251.
Voloshin S, Shleeva M, Syroeshkin A, Kaprelyants A. 2005. The Role of Intercellular
Contacts in the Initiation of Growth and in the Development of a Transiently Nonculturable State by Cultures of Rhodococcus rhodochrous Grown in Poor
Media. Microbiology 74:420-427.
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2.6 The effect of chemical additives on biomass deposition ontobeaded chromatographic supports
Rami Reddy Vennapusa and Marcelo Fernandez-Lahore* Downstream Processing Laboratory, School of Engineering and Science, Jacobs University
Bremen gGmbH, Campus Ring 1, D-28759, Bremen, Germany.
2.6.1 Abstract
Common limitations encountered during the direct recovery of bioproducts from an
unclarified feedstock are related to the presence of biomass in such processing systems.
Biomass-related effects can be described as biomass-to-support deposition and cell-to-cell
aggregation. In this work, a number of chemical additives were screened for their ability toinhibit either biomass deposition, cell aggregation, or a combination of both effects. Several
interacting pairs were screened. These were composed of i. a commercial chromatographic
matrix harbouring a variety of ligand types and ii. intact yeast cells -as a model biomass
type. Studies were performed on the basis of partitioning tests and colloid deposition
experiments. Results indicated that the incorporation of the synthetic polymer PVP 360 into
the mobile phase has alleviated biomass deposition onto weak-anion exchanger beads by a
factor of ≈3. This behaviour correlated well with calculations performed according to theXDLVO approach: the secondary (interaction) free energy pockets decreased from -230k T
to -100 k T in the absence and in the presence of PVP 360, respectively. Experiments
performed in parallel demonstrated that total binding capacity for the model protein (BSA)
decreased minimally, from 33.6 to 32.4 mg/ml. Other combinations of additives and
adsorbents were tested. However, no solution chemistry was able to inhibit biomass
deposition onto strong (composite) ion exchangers. Moreover, yeast cells deposition was
only marginally decreased when hydrophobic interaction and pseudo-affinity supports wereexplored. The utilization of non-toxic polymers could help to avoid detrimental biomass
deposition during expanded bed adsorption of bioproducts and other direct contact
sequestration methods.
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2.6.2 Introduction
Current bottleneck in the downstream processing of biological products can be alleviated
by application of direct sequestration methods. For example, the utilization of expanded
bed adsorption (EBA) may play an important role during product primary capture. This process strategy permits simultaneous solids separation and product concentration and
(partial) purification. Therefore, an integrative technology presents a clear benefit as it
reduces the number of process steps and contributes considerably to cost reduction, by
saving on process times and capital demands (Anspach et al. 1999).
To deliver appropriate sorption performance expanded bed systems have to allow for the
formation of a stable or perfectly classified fluidized bed, even in the presence of a turbidfeedstock. However, this is often not the case. It was early reported (Fernandez-Lahore et
al. 1999; Feuser et al. 1999) that interactions between the biomass components and the
fluidized chromatographic adsorbents may disturb the otherwise stable expansion of the
bed, by changing its hydrodynamic characteristics. Moreover, biomass deposition can
reduce the life expectancy of the (costly) matrix due to adsorbent fouling and due to the
harsh regeneration conditions subsequently required to release the bound cellular material
(Dainiak et al. 2002; Feuser et al. 1999). Deteriorated process performance in expanded bed
systems generates an increased processing time and capital investment (Curbelo et al.
2003). Therefore, the biofouling of chromatographic supports is a significant technical
challenge which has to be better understood to overcome the many limitations that have
been addressed in the last years.
The deposition of microbial cells or biomass debris is related to the physico-chemical
characteristics of the cell-surface components. These surfaces are in most cases of anionicnature due to the existence of negatively charged chemical groups like phosphate,
carboxylate, and sulphate moieties. However, the cell envelop can also exert hydrophobic
interaction due to the presence of S-layer proteins, amphipathic polymers, and lipids.
Therefore, microbial deposition onto (process) surfaces will be driven by the polymeric
components of the rigid outer boundary and eventually, by the presence of cell-surface
appendages (if present). On the other hand, biomass deposition will be governed by the
nature (material structure) and functionality (ligand type) of the surface e.g. the structure of
the chromatographic support.
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A semi-quantitative analysis of biomass interactions with several biomass-adsorbent pairs
was performed by Feuser et al (Feuser et al. 1999). Since then, several studies were devoted
to determine the importance and extent of biomass effects on the sorption performance of
fluidized beads (Fernandez-Lahore et al. 1999; Fernandez-Lahore et al. 2001). In order to
overcome such limitations a methodological design approach has been proposed to
determine appropriate operational windows so as to reduce biomass adsorbent interactions
to a minimum (Lin et al. 2001). Our group has recently made an attempt to understand – at
the local level - the deposition of biomass particles onto several process surfaces. This
novel approach might offer a more universal approach and valuable information to guide
process and material design (Vennapusa et al. 2008).
The shielding of chromatographic support surfaces with polymeric layers proved to inhibit
non-specific interactions and therefore to be a helpful strategy to optimize separation
methods, like high performance chromatography or capillary electrophoresis (Desilets et al.
1991; Petro and Berek 1993; Santarelli et al. 1988; Schomburg 1991). A similar strategy
was attempted during expanded bed adsorption by covering fluidised beads with
polyelectrolyte or agarose to reduce biomass interference (Dainiak et al. 2002; Viloria-Cols
et al. 2004). Other methods implemented to reduce non-specific interaction of biological
particles included a thermal treatment of the crude feedstock before contacting with thesolid phase (Ng et al. 2007). However, biomass deposition or cell aggregation is still
observed in many adsorbent-biomass systems e.g. with anion-exchangers, hydrophobic
interaction beads and (some) pseudo-affinity supports (Fernandez-Lahore et al. 2000;
Poulin et al. 2008; Silvino Dos Santos et al. 2002; Smith et al. 2002). There is room enough
for investigations concerning the potential effects of solution chemistry changes on biomass
deposition in bioprocessing systems.
The mechanistic understanding of transport and deposition of microbial cell onto process
surfaces has significant interest in various bioprocess situations. Traditionally, microbial
deposition has been studied employing packed-beds of collector particles. A population of
biological particles is introduced into such systems and the suspended biomass effluent is
monitored as a function of process time. This type of experiments can provide useful and
quantitative information when assessing factors like cell size and shape, microorganisms
strain, growth phase, bead size, surface coatings, fluid velocity, and ionic strength on celldeposition onto process media (Tari et al. 2008). A common approach to evaluate biomass
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deposition in laboratory packed-bed experiments employs the “clean-bed” filtration model
(CBFM). In this case, mass transport phenomena are accounted by the “single-collector
contact efficiency” (η0) while the physicochemical phenomena related to biomass
attachment are reflected by the “attachment efficiency parameter” (α).
This work has gathered information on the effect of several chemical additives, which were
incorporated into chromatographic mobile phases, on biomass deposition onto
chromatographic adsorbents. Additives belong to the group of synthetic polymers, non-
ionic surfactants, neutral detergents, and salts. Yeast cells were utilized as model biomass
particles. Various combinations of commercial adsorbents and additives were screened for
cell depositionvia partition and biomass deposition experiments. Theextended Derjaguin-
Landau-Verwey-Overbeek (XDLVO) theory was employed to explain the observed cell
deposition behaviour.
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2.6.3 Materials and Methods
2.6.3.1 Materials
Chromatography adsorbents and columns were purchased from GE Healthcare, Munich,
Germany. Solvents utilised for contact angle measurements:α-bromonaphtalene (99%
purity) and formamide (99.5% purity), were obtained from Fluka, Buchs, Switzerland.
Water was ultrapure quality. Polyethylene glycol (PEG 3350), polyvinyl alcohol (10 kDa;
Product number 8136), polyvinyl pyrrolidone (PVP 10 and PVP 360),
Polyoxyethylenlaurylether (Brij 35 and Brij 58) were obtained from Sigma-Aldrich Chemie
GmbH, Steinheim, Germnay. Tween 20, Pluronic F68, Nonidet P40, Tween 20 and Triton
X100 were from AppliChem GmbH, Darmstadt, Germany. Sodium polyphosphate (NaPP)
and sodium fluoride (NaF) were obtained from Riedel-de Haën, Seelze, Germany. All other chemicals were of analytical grade.
2.6.3.2 Generation of biomass
Saccharomyces cerevisiae wild strain FY 86, haploid, was obtained from Dr. V. Ganeva
(Sofia University, Bulgaria). The strain was maintained on agar plates made from yeast
extract 10 g/l, soy peptone 20 g/l and agar 20 g/l with D-glucose 20 g/l as additional carbon
source. Yeast cells were grown on YPD medium [1% (w/v) yeast extract, 2% (w/v) peptone, 2% (w/v) glucose] utilising 300 ml cotton-plugged-conical flasks on a rotary
shaker at 30°C. The culture volume was 100 ml and the shaker speed 150 rpm. Growth was
monitored turbidimetrically at 600 nm. After reaching exponential phase (OD600 = 1.9),
cells were collected by centrifugation at 2000 g , washed twice with 10 mM phosphate buffer
(pH 7.6) and re-suspended to give 7.5 × 108 cells·ml−1 (24 mg cell dry wt per ml) (Ganeva
et al. 2004).
2.6.3.3 Physiochemical characterization of particles
2.6.3.4 Contact angle measurements
Contact angles were measuredas per the sessile drop method utilizing a commercial
goniometric system (OCA 20, Data Physics instruments GmbH, Filderstadt, Germany).
Three diagnostic liquids e.g.α-bromonaphtalene, formamide, and water were employed
(Bos et al. 1999). Details of the experimental procedure, as applied for biomass and crushed
chromatographic beads, were published elsewhere (Vennapusa et al. 2008).
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2.6.3.5 Zeta potential determinations
Particle zeta-potential values were measured with a Zetasizer Nano ZS from Malvern
Instruments (Worcestershire, United Kingdom). Fragmented Sepharose particles were
utilized instead of Streamline beads due to their lower density and to avoid sedimentationduring measurements. Before performing the measurement, particles were contacted with
20 mM sodium phosphate buffer at pH 7.6 for 2 h and further diluted to appropriate particle
count (~200 particles total count). Zeta potential measurements were also performed on
particles which were contacted with 1% solution of PVP 360 and then extensively washed
with phosphate buffer. Zeta potentials were calculated from the electrophoretic mobility
data according to the Smoluchowski’s equation (Ottewill and Shaw 1972). All the
measurements were performed in triplicate.
2.6.3.6 Deposition of yeast cells (Partition experiments)
Deposition of yeast cells onto chromatographic beads was studied by partition experiments.
These experiments were performed in glass flasks (4 cm height, 1.5 cm diameter) with
plastic caps. Vacuum dewatered chromatographic beads (0.5 g) were contacted with a cell
suspension (2.0 ml; 0.03% dry weight) under gentle orbital stirring. The optical density of
the cell suspension remaining in the supernatant was evaluated by absorbance at 600 nm.
Cell number was calculated according to the following expression:
x x y 1155.03363.0 2 += Equation 1
where y is the concentration of yeast of cells (% w/v wet basis) and x is the OD@600 nm.
Cell suspensions having an optical density higher than 1.0 were diluted before photometry.
Samples were taken after 3 h to evaluate total cell deposition (Fernandez-Lahore et al.
2000). Results were expressed as a Cell Partition Index (CPI) which was calculated
according to:
i
f
C
C CPI = Equation 2
whereC f is the final concentration of cells (t = 3h) andC i is the initial concentration of the
yeast cells (t = 0) in the supernatant.
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where μ is the viscosity of the polymer solution [Pa·s] and C is the concentration of PVP
360 [wt. %].
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2.6.4 Results and Discussions
2.6.4.1 The potential of additives to influence cell attachment
Certain chemical components may have the ability to modify the interactions between
microbial cells and chromatographic beads –in aqueous media- by promoting changes in
the free interfacial forces / free energy between bodies:
a) Ionic compounds can alter microbial deposition and transport through surface
charge modification (Brown and Jaffe 2001). Polyphosphates are highly negative
charged chemicals which were shown to decrease microbial adhesion to soils and
synthetic membranes. These compounds find applications as microbial dispersants
and to stabilise suspensions of mineral particles. Sodium polyphosphate [NaPP / n =17] compounds can reduce the zeta-potential of microbial particles (Papo et al.
2002; Sharma et al. 1985).
b) Polyvinylpyrrolidone [PVP] is a non-ionic polymer which has been shown to adsorb
onto oxide-surfaces through an acid-base interaction i.e. surface hydroxyl groups,
acting as Bronsted acids, can interact with PVP segments which are considered
Lewis base in aqueous media (Pattanaik and Bhaumik 2000). PVP was also shown
to interact with dye-affinity chromatography supports (Galaev et al. 1994). PVP 360
was utilized in this study.
c) Some studies have demonstrated that Polyethylene glycol [PEG] is preferentially
excluded from macromolecular surfaces. This might elicit an energetically
favourable sharing of the co-solvent hydration shells surrounding the biological
particle and the chromatography media, thus increasing the partition coefficients
(Gagnon et al. 1996). PEG 3350 was utilized in this study.
d) Poly (vinyl alcohol) [PVA] is a polymer having anionic character. This compound
has been reported to bind to controlled-porosity glass beads and to reduce the zeta
potential of such particles (Wisniewska et al. 2007). PVA adsorption would increase
with pH due to the presence of non-hydrolysed acetate groups i.e. the polymer gain
negative charge [89% hydrolysis in this work]. PVA adsorption depends on
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electrostatic forces, hydrogen bonding, and conformational state. PVA having a
MW of 10 kDa was utilized in this work.
e) Adsorbed polymer / surfactants on the solid surface can modify both physical
surface properties and the interaction between interacting bodies. Therefore, other
non-ionic surfactants have been included: Polyoxyethylene cetyl ether [Brij 58],
Polyoxyethylene sorbitan monolaureate [Tween 20], Polyoxyethylene-
polyoxypropylene block copolymer [Pluronic F68], and Ethylphenolpoly(ethylene
glycolether)n [Nonidet P40].
2.6.4.2 Screening additives with partitioning tests2.6.4.3 The effect of additives on cell deposition
A preliminary exploration (screening) on the potential effect(s) of a number of different
additives on yeast cell deposition onto commercial chromatographic beads was performed
utilizing simple partition tests (Fernandez-Lahore et al. 2000; Lin et al. 2001). Partitioning
tests were carefully optimized to accommodate a variety of yeast-adsorbent interaction
pairs. Under such experimental conditions, yeast cell deposition onto non-functionalized
agarose beads was less than 10% as judged by the cell partition index (CPI≥ 0.90).
Standard experiments were performed in 20 mM phosphate buffer (≈ 4.0 mS/cm) and
therefore a certain degree of deposition onto cation-exchanger materials (CPI≥ 0.7 for SP-
Streamline) was observed due to electrical double layer compression effects (Tari et al.
2008). Contact time was fixed to 3 h so as to evaluate the combined effects of the fast and
the slow phases of cell deposition (Fernandez-Lahore et al. 2000).
Anion-exchangers are known to strongly interact with microbial cells, mainly due tocharge-mediated (electrostatic) effects (Lin et al. 2006). Indeed, partition tests run with the
weak anion exchanger DEAE-Streamline and the strong (composite) anion exchanger Q-
Streamline XL showed high cell deposition i.e. a CPI equal to 0.28 and 0.14, respectively.
Subsequent incorporation of non-ionic polymers / surfactants to the liquid phase has
reduced cell deposition in an extent which depends on the additive and the solid phase
under consideration. Table 1 depict the result of screening tests performed for various
adsorbents and additives. When DEAE beads were employed as the solid phase, the basalcondition for cell deposition (i.e. CPI = 0.28 in buffer) was improved: CPI increased to 0.54
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in the presence of Tween 20, to 0.43 with added Pluronic F68, to 0.60 with Brij 58, and
0.34 with PEG. Particularly effective in inhibiting cell deposition onto DEAE beads was
PVP 360; in this case the CPI raised to 0.81. However, the same additive failed to avoid
cell attachment onto the Q-XL material. This could be explained by the presence of
external Dextran chains in the structure of the composite adsorbent. On the contrary,
polymeric sodium phosphate (NaPP), an ionic agent, showed almost no effect in preventing
cell deposition onto DEAE beads but inhibited such phenomena onto Q-XL beads. It could
be hypothesized that NaPP may interact primarily with yeast particles, rendering them more
negative when DEAE beads are present. Thus, cell-to-adsorbent interactions remain the
same. However, the presence of Q-XL beads may trigger the interaction of the (positively)
strongly charged Dextran chains with the (negatively) charged polyphosphate. This would
shield adsorbent charges thus reducing interaction with suspended cells. The distinct
behaviour of the two anion-exchangers rules out a predominant role for the increased
conductivity of the liquid phase in the presence of NaPP (≈ 9.1 mS/cm).
Further studies performed with the DEAE / yeast system in the presence of PVP 360
showed that CPI is fairly proportional to the concentration of the additive in the liquid
phase. A PVP concentration of 1% (w/v) resulted in maximum inhibition of cell deposition.
Kinetic studies also revealed that PVP 360 seems to interfere with cell depositionmechanisms at early stages i.e. the polymer might inhibit cell-to-support interaction (data
not shown). This phenomenon is discussed in more detail in the sections below.
Partition experiments were also performed with hydrophobic interaction supports (Phenyl-
Streamline) in 20 mM phosphate buffer (pH 7.6) containing 0.75 M ammonium sulphate.
The CPI for the control situation i.e. buffer without additive(s) was 0.75 which correlates
well with previous reported values (Fernandez-Lahore et al. 2000). Addition of non-ionic polymer / surfactants failed to improve the baseline situation e.g. CPI fell within the range
0.69-0.83. Therefore, only a marginal effect –if any- was observed for HIC systems. The
presence of high concentrations of ammonium sulphate is HIC systems might interfere with
the potential action of the additives utilised in this work.
Chelating Streamline was utilized to evaluate cell deposition as well. Zn (II) ions were
immobilized within the IDA groups present in the matrix. Partition experiments were
performed in 20 mM phosphate buffer (pH 7.6) containing 250 mM sodium chloride and 1
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mM imidazol. Baseline CPI was 0.90 which is similar to values previously reported in the
literature for IMAC (Fernandez-Lahore et al. 2000). For Chelating systems the addition of
non-ionic polymers / surfactants has had a slightly deleterious effect since CPI values
tended to be lower (0.69 – 0.87). This can be explained considering the effect of
considerable amounts of sodium chloride in the liquid phase and / or a possible bridging
effect exerted by the polymers.
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R e s u l t s
1 9 1
T a b l e 1 : C e l l d e p o s i t i o n s o f
i n t a c t y e a s t c e l l s o n t o
S t r e a m l i n e b e a d s a s o b s e r v e d
b y p a r t i t i o n e x p e r i m e n t s .
A d d i t i v e s w e r e p r e s e n t a t a
f i n a l
c o n c e n t r a t i o n o f
1 % ( w / v ) . E x p e r i m e n
t s w e r e r u n
i n b u f f e r s h a v i n g a
t y p i c a l c o m p o s i t i o n ,
d e p e n d i n g o n
t h e c h r o m a t o g r a p h i c m o
d e i n v o l v e d
( s e e t e x t ) . C o n t a c t t i m e w a s
3 h . C o n t r o l C
P I ( a g a r o s e m a t r i x ) w a s
≥ 0 . 9 0 . T h e C h e l a t i n g m a t e r i a l w a s
l o a d e d w
i t h Z n ( I I ) i o n s . C P I v a l u e s
w e r e w i
t h i n ± 1 0 %
.
n . d : n o t d e t e r m i n e d
B e a d
t y p e
A d d i t i v e t y p e
↓
N o n e
T w e e n
2 0
P l u r o n i c F 6 8
P E G 3 3 5 0
P V P 3 6 0
P V A
B r i j 5 8
N A P P
Q - X L
0 . 1 4
n . d .
n . d .
n . d .
0 . 3 4
n . d .
0 . 4 0
0 . 8 7
D E A E
0 . 2 8
0 . 5 4
0 . 4 3
0 . 3 4
0 . 8 1
0 . 3 5
0 . 6 0
0 . 3 0
P h e n y l
0 . 7 5
0 . 7 0
0 . 8 0
0 . 7 9
0 . 6 9
n . d .
0 . 8 3
n . d .
C h e l a t i n g
0 . 9 0
0 . 9 4
0 . 9 1
n . d .
0 . 7 4
0 . 6 9
0 . 8 7 *
n . d .
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2.6.4.4 The effect of additives on protein binding
A useful additive has to inhibit cell deposition onto a defined type of chromatographic
support without interfering with protein (bioproduct) binding. This situation would lead to a
decreased biomass attachment without compromising adsorbent capacity for the targetedspecies. Therefore, partitioning studies were also performed to assess protein sequestration
from a cell suspension with and without a selected number of promising additives.
Partition studies were performed with DEAE-Streamline. In buffer, this material showed a
high affinity number (0.85); the introduction of cells into the system translated in a≤ 5%
reduction in the affinity (binding) for the model protein. It should be recall that this support
type has also a strong tendency to capture cells (Table 1). The addition of chemicals to thesolution phase, showed no dramatic effect on the (equilibrium) capacity of the adsorbent
(Table 2). Among the additives tested, PVP 360 showed a maximum protection against cell
deposition (CPI 0.81 vs. 0.28) while protein binding remained unaltered (Affinity number
0.80 vs. 0.83). Therefore, PVP was clearly acting without interfering with the charge-
mediated attraction between BSA and the adsorbent beads.
Partition studies were performed also with Q-Streamline XL. This material suffers from an
extremely high deposition of cells, probably due to the presence of densely charged
Dextran chains within its composite structure. As sodium polyphosphate was found to be
effective in inhibiting cell interactions with Q-XL, protein-binding capacities were checked
with buffers containing this chemical. Unfortunately, NaPP was found to interfere with
BSA binding as reflected by affinity numbers falling from 0.92 (cells, no chemical) to 0.13
(cells plus additives). It follows that NaPP most probably interacts with the adsorbent by
masking positively charged sites, therefore inhibiting both cell and protein uptake.
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2.6.4.5 Biomass deposition experiments
Data gathered employing a range of adsorbents and chemical additives showed the
beneficial effect of PVP 360 on preventing cell deposition onto the weak anion-exchanger.
In order to confirm such data under dynamic conditions, biomass (yeast cells) depositionexperiments were run. DEAE-Streamline beads were utilized as collectors. Figure 1 depicts
the cell effluent profiles recorded as a function of PVP 360 concentration, within the range
0.01 to 1.0 %. Cell deposition behavior was characterized by a decreased interaction with
the adsorbent in the presence of increased concentrations of the additive in the flowing
phase. The observed lower deposition of cells was reflected by the “attachment efficiency”
parameter (α); α values are shown in Table 3. The baseline condition i.e. no additive
translated into aα value equal to 0.683 which has decreased by a factor of ≈ 8 due to the presence of the additive. Theα value obtained after running cell deposition experiments in
the presence of 50 mM sodium chloride, a condition known to improve system
hydrodynamics with DEAE adsorbents, was 0.213. Combination of 1% PVP 360 and 50
mM sodium chloride resulted in an minimum value for the attachment coefficient (α =
0.052). However, the incorporation of charge-screening ions into the chromatographic
mobile phase may also lead to a decreased capacity for the targeted proteins.
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Figure 1 : Biomass deposition experiments onto DEAE-beads. Intact yeast cells wereutilised as model biomass. Solution chemistry was provided by a 20 mM phosphate buffer
pH 7.6, which contained PVP 360 at various concentrations: () Control (no additive), ( )0.01% , ( ) 0.05%, ( ) 0.1%, ( ) 0.5 %, ( ) 1 % PVP 360.
Previous work has demonstrated that, as far as a threshold value for the attachment
coefficient e.g.α ≤ 0.15 is not reached, the level of biomass deposition remains low enough
so as to allow for proper bed fluidization and product capture. Therefore, the addition of
PVP within the range 0.2 to 0.5 % would be sufficient to prevent biomass interference with
EBA operation. On the basis of the gathered experimental evidence, anion-exchangerswould operate –in the presence of moderate amounts of PVP 360- similarly to cation-
exchangers. The later are materials which operate without major limitations with a variety
of feedstock compositions (Tari et al. 2008).
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R e s u l t s
1 9 6
T a b l e 3 :
L u m p e d a t t a c h m e n t p a r a m e
t e r ( α ) c a l c u l a t e d
f r o m y e a s t
c e l l d e p o s i t i o n o n t o
D E A E b e a d s . R u n s w e r e p e r f o r m e d
i n 2 0 m
M
p h o s p h a t e b u f f e r a t p H 7 . 6 . P V P 3 6 0 w a s e m p l o y e d a s a n a d d i t i v e .
A d s o r b e n t t y p e
P V P 3 6 0 d
( % )
O t h e r a d d i t i v e
C / C
0
( - )
α ( - )
N a k e d
b e a d s a
0
N o n e
0 . 0 1 7
0 . 6 8 3
0
S a l t b
0 . 2 8 0
0 . 2 1 3
N a k e d
b e a d s a
0 . 0 1
N o n e
0 . 1 3 4
0 . 3 3 7
0 . 0 5
N o n e
0 . 2 5 6
0 . 2 2 8
0 . 1
N o n e
0 . 3 8 2
0 . 1 6 1
0 . 5
N o n e
0 . 5 2 8
0 . 1 0 7
1
N o n e
0 . 6 1 4
0 . 0 8 2
1
S a l t b
0 . 7 3 1
0 . 0 5 2
C
o a t e d b e a d s c
0
N o n e
0 . 5 1 4
0 . 1 1 2
a
D E A E - S t r e a m
l i n e b e a d s w e r e u t i l i z e
d .
b S o d i u m c h l o r i d e a t a
f i n a l c o n c e n t r a t i o n o f 5 0 m
M w
a s e m p l o y e d .
c B
y t r e a t m e n t w
i t h P V P 3 6 0 a n d e x t e n s i v e w a s h i n g w
i t h b u f f e r s o l u t i o n .
d P V
P 3 6 0 a d d e d
t o t h e f l o w i n g p h a s e a t a
f i x e d c o n c e n t r a t i o n .
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R e s u l t s
1 9 7
T a b l e 4 : T
h e e f f e c t o f
P V P 3 6 0 c o n c e n t r a t i o n o n m o b i l e p h a s e v i s c o s i t y , o n c e l l d i f f u s i o n c o e f f i c i e n t , o n
t h e h y d r o d y n a m i c d r a g e x e r t e d o n
y e a s t p a r t i c l e s , a n d o n
t h e a d s o r b e n t b e a d s e t t l i n g v e l o c i t y .
C o n c e n t r a t i o n
P V P
( % w
/ v )
V i s c o s i t y a
( m P a · s )
D i f f u s i o n c o e f f i c i e n t b
( m 2 · s - 1 )
H y d r o d y n a m
i c d r a g c
( N )
S e t t l i n g v e l o c i t y d
( m · s - 1 )
0 . 0 1
0 . 8 9
6 . 0 x
1 0 - 1 4
9 . 5 x 1 0
- 1 1
4 . 9 x
1 0 - 3
0 . 0 5
0 . 9 2
5 . 8 x
1 0 - 1 4
9 . 8 x 1 0
- 1 1
4 . 7 x
1 0 - 3
0 . 1
0 . 9 7
5 . 6 x
1 0 - 1 4
1 . 0 x 1 0
- 1 0
4 . 5 x
1 0 - 3
0 . 5
1 . 3 7
3 . 9 x
1 0 - 1 4
1 . 4 x 1 0
- 1 0
3 . 2 x
1 0 - 3
1
2 . 1 3
2 . 5 x
1 0 - 1 4
2 . 2 x 1 0
- 1 0
2 . 0 x
1 0 - 3
a L i q u i d p h a s e .
C a l c u l a t e d a c c o r d i n g t o
( Y e h e t a l .
1 9 9 8 )
b F o r y e a s t c e l l s .
C a l c u l a t e d a c c o r d i n g
t o ( B r o w n
2 0 0 7 )
c F o r y e a s t c e l l s .
C a l c u l a t e d a c c o r d i n g
t o ( J o h n s o n e t a l .
2 0 0 7 )
d F o r a d s o r b e n t b e a d s .
C a l c u l a t e d a c c o r d i n g
t o ( B r o w n
2 0 0 7 )
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A potential drawback on the utilisation of PVP 360 in fluidised bed systems is the increase
of viscosity due to the presence of such polymer in solution. In turn, viscosity can affect
process characteristics (Table 4). For example, mass transfer properties of cells can be
altered via a reduced diffusion coefficient. Moreover, cell transport might be affected due
to increased hydrodynamic drag exerted on them. Bed hydrodynamics can be also
compromised by a reduced adsorbent particle settling velocity, which may promoted bead
elutriation. Therefore, it is advisable to keep the concentration of this additive to a
minimum compatible with its function as “cell-deposition-preventing” agent.
To get a better insight on the mode of action of PVP 360 as an additive preventing cell
deposition, DEAE beads were contacted with the additive (4 CV) and subsequently washed
with phosphate buffer (20 CV). Interestingly, cell deposition experiments performed onthese beads –but in the absence of any additive in the solution chemistry- also demonstrated
much less cell deposition than with untreated beads (α = 0.112) see table 3. It can be
concluded that PVP 360 might have been retained on the adsorbent surface by a
combination of physicochemical forces. This is in agreement with previous work with
hydrophilic polymers (Dainiak et al. 2002; Viloria-Cols et al. 2004). However, protein
binding sites remain available within the adsorbent structure. Due to its hydrodynamic
radius of gyration (~ 19 nm) (Armstrong et al. 2004) is unlikely that PVP 360 would havecomplete access to the pores existing in the chromatographic support (pore radius = 29 nm)
(Jungbauer 2005). Moreover, these experiments have demonstrated a beneficial effect of
the additive on cell deposition by decoupling cell attachment from viscosity-related effects
in the presence of PVP.
Other experimental findings employing biomass deposition experiments have generally
confirmed results obtained with partition tests (data not shown). These findings can be
summarised as follows: a) Biomass deposition experiments serve to confirm that other
additives like Tween 20 or Brij 58 were ineffective in inhibiting cell interaction with DEAE
beads; b) The utilization of such chemical additives failed to inhibit cell attachment to
Chelating materials; c) Introduction of PVP 360 and Brij 58 in hydrophobic interaction
systems was limited due to a lack of solubility in ammonium sulphate containing mobile
phases; d) PVP 360 was unable to prevent cell deposition onto Q-XL in agreement with
partition experiments.
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2.6.4.6 Interfacial free energy of interaction between bodies
The extended DLVO theory can be applied to understand the interaction of two bodies in
aqueous media, on the basis of colloid chemistry principles. In this case, the XDLVO
approach was employed to calculate energy vs. distance profiles between naked or PVP-
covered interaction particles e.g. yeast cells and adsorbent beads. Performing such
calculations require the input of experimentally determined parameters like contact angle
values with three diagnostic liquids and zeta potentials. Details on the mentioned approach
have been published elsewhere (Vennapusa et al. 2008).
Contact angle on hydrated PVP 360 layers were taken from published work (Faibish et al.
2002) and employed to calculate surface energy parameters. Calculations resulted in thefollowing values:
γLW 35.8 mJ·m-2, γ+ 2.2 mJ·m-2, γ- 34.2 mJ·m-2, and γAB 17.3 mJ·m-2
These values were assumed to be the ones corresponding to either yeast cells or adsorbent
beads when PVP 360 is present on their surface. Utilizing this information, the free
(interfacial) energy of interaction was calculated –at the closest distance of approximation
i.e. 1.57 Å and in aqueous media- for four different cases (Table 5):
a) A naked adsorbent DEAE-bead interacting with a naked yeast cell
b) A polymer coated bead interacting with a naked cell
c) A PVP coated bead interacting with a polymer coated cell
d) Two polymer coated yeast cells
Additionally, zeta potential determinations were performed for polymer coated DEAE
beads and intact yeast cells in 20 mM phosphate buffer (pH 7.6). These measurements haveshown that particle zeta potential values can be reduced in the presence of the additive
(Table 5). Similar observations have been made for silica-based particles (Goncharuk et al.
2001).
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Table 5 : The interfacial free energy of interaction between bodies in aqueous media, atclosest distance of approximation: a) intact yeast cells and DEAE-beads, and b) aggregation between two yeast cell particles. Calculations were performed assuming interaction andaggregation with and without chemical additive at pH 7.6 in 20 mM phosphate buffers.
System ΔGLW [mJ·m-2]ΔGAB [mJ·m-2] Zeta potential[mV]
Naked beada - Cell - 1.4 + 28.7 +15 / -18
Coated bead b - Cell - 1.6 + 20.0 + 5 / -18
Coated bead – Coated Cell
- 3.4 + 12.0 + 5 / -15
Two covered cells - 7.0 + 11.4 -15 / -15
a DEAE Streamline b PVP 360 treated adsorbent
The interaction systems mentioned above can be better understood by interfacial free
energy (U) as a function of distance (H) profiles. Figure 2 depict such energy / force curves
where it can be observed that:
a) Interaction between naked DEAE beads and intact yeast cells is characterized by a
strong interaction, as reported previously. Charge effects i.e. Coulomb-type
attraction is dominating. A secondary energy pocket would exist at 5nm; pocket
depth is -230 k T. This is in agreement with biomass deposition experiments
presented before (Figure 1 and Table 3;α = 0.683).
b) Interaction between a polymer coated adsorbent bead and a naked cell resulted in a
secondary energy pocket of a moderate depth (-100k T). The reduction in
interaction energy / forces can be explained on the basis of modifications observed
in the zeta potential values, particularly for the coated adsorbent bead. This is in
agreement with cell deposition experiment utilizing pre-treated DEAE beads as
collectors (Table 3;α = 0.112).
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c) The assumption of having PVP 360 molecules covering the cell surface would result
in a situation characterized by increased LW attraction, decreased AB repulsion,
and almost unaffected EL attraction (Figure 2; U≈ -160 k T). This behaviour
couldn’t be verified by biomass deposition experiments. Although a slight decreasein the zeta potential value for cells in the presence of PVP was noticed, evidence
more likely supports the idea that this additive preferentially interacts with the
adsorbent beads.
d) The presence of PVP 360 does not severely compromise colloidal stability of cell
particles in suspension and therefore no aggregation is expected to occur (Figure 2;
U ≈ - 20 k T).
Figure 2 : Energy (U) vs. distance (H) profiles calculated for the interaction between aDEAE-bead and a yeast cell, in 20 mM phosphate buffer at pH 7.6. Calculations were performed assuming 4 hypothetical cases (refer to text), as follows: (— ) DEAE/Cell, (— )[DEAE] pvp/[Cell] pvp, (— ) [DEAE] pvp/[Cell], (— ) [Cell] pvp/ [Cell] pvp.
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2.6.5 Conclusions
Several chemical additives were evaluated for their capacity to reduce cell deposition onto
a variety of chromatographic adsorbents.
A simple albeit effective method to reduce biomass deposition onto DEAE adsorbent beads
is presented. Addition of PVP 360, a pharmaceutical grade polymer, seems to preferentially
interact with the adsorbent under process-like conditions. Covered adsorbent beads retain
capacity for proteins but substantially reduce the interaction with suspended cells.
The preceding hypothesis is supported by biomass deposition experiments and XDLVO
calculations.
The utilization of safe additives may find practical application to improve the sorption
performance of direct contact methods in the downstream processing of bioproducts.
2.6.6 Acknowledgements
RRVP great fully acknowledges the doctoral fellowship from Jacobs university.
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References
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Bos R, Van der Mei HC, Busscher HJ. 1999. Physico-chemistry of initial microbial
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Curbelo DR, Garke G, Guilarte RC, Anspach FB, Deckwer WD. 2003. Cost Comparison of
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Interaction of HEK-293 Cells with Streamline Chelating Adsorbent in Expanded
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General Conclusions and Remarks
207
3.0 General conclusions and remarks
Expanded bed adsorption (EBA) is an interesting integrated bioprocess technology unit
operation where solid liquid separation, partial purification and concentration can be
simultaneously achieved. This integrated unit operation loses its significance due tointeraction or aggregation of biological particles onto the process surfaces during direct
sequestration of bioproducts. Many authors have repeatedly addressed this interference of
biomass during primary unit operations of downstream processing such as EBA.
Undoubtedly, biomass effects are detrimental to appropriate sorption performance in EBA.
Information on the underlying mechanisms which govern biomass deposition onto
chromatographic beads, under real process conditions, is still scarce.
To address the significant challenge of biomass interference on EBA performance, the
current thesis work puts emphasis on having a fundamental understanding of the feedstock
behavior during primary-sequestration unit operations in downstream processing. Principles
of colloid chemistry were applied to understand the fouling behavior of the
chromatographic supports. The physicochemical properties of yeast cells (model type of
biomass) and chromatographic supports (several types) were evaluated by contact angles
and zeta potentials measurements. From these experimental determinations, deposition ontothe process surface was predicted using the XDLVO theory. Calculations were confirmed
by independent experiments like biomass deposition in granular beads and laser diffraction
spectroscopy. The XDLVO theory and biomass deposition experiments were able to
explain the attachment behavior of cells as a function of varying solution chemistry, size of
the biological particle, and functionalisation type of the process surface. In this regard, the
approach developed in this work can be anticipated as a universal approach for
understanding the biomass adhesion onto process surfaces. Furthermore, the tools presented
here are useful in guiding process and material design and development.
This piece of work has arrived to remarkable conclusions on the behavior of particulate
feedstock component deposition onto different chromatographic supports of varied
chemistries, ranging from ion-exchangers and hydrophobic interaction supports to metal-
ion chelating surfaces. Besides the utilization of intact yeast cells, other systems like yeast
cell debris and E.coli homogenate were explored with special focus on the ion exchanger
type of chromatographic beads.
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General Conclusions and Remarks
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The following partial conclusions can be mentioned:
1) Ion exchanges surfaces to biomass
The extent of interaction of yeast cells (biomass) with anion- and cation- exchangers
can be explained on the basis of the calculated secondary energy minima e.g. reversible
adhesion can be predicted (Figure 1). The degree of interaction varied with the solution
chemistry e.g. upon changes in buffer pH and conductivity. A positive correlation was
found between energy minima and cell deposition, as evaluated by the so called cell
transmission index (CTI). Coulomb-type interactions, which are related to the measured
zeta potential of the interacting bodies, were confirmed to be dominant. The XDLVO
approach also gave us a clear idea about influence of biomass particle size on the extent of
fouling. The total forces acting during biomass adhesion are greatly altered with the size of
the cell or cell fragments. Secondary interfacial energy minima values were experimentally
validated via biocolloid deposition experiments (BDE). BDE is simple, straightforward and
automatable diagnostic tool, which was developed during the current work. This technique
allowed the calculation of a lumped parameter [α, attachment deposition coefficient]
reflecting biomass interaction and aggregation phenomena.
However, cell-to-cell aggregation is less likely to happen under the conditions
prevailing in an ion-exchange process. This can be explained due to dominant electrostatic
repulsion between (negatively charged) cells in low-conductivity mobile phases. The
conclusion drawn with regard to deposition of biomass onto ion-exchangers from the
fundamental understanding gathered during the current work is in full agreement with the
known EBA operational constraints.
2) Hydrophobic interaction surfaces to biomass
As hydrophobic interactions are expected to occur under high salt concentrations, a
marginal contribution of charge-mediated effects is anticipated under such chromatographic
mode of operation. The consideration of the XDLVO theory was very well justified in the
scenario of hydrophobic interaction chromatography (HIC). In the later case, the
interaction of biomass with the chromatographic beads could be explained due to Lifshitz-
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General Conclusions and Remarks
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Van der Waals (LW) and acid-base (AB) interaction forces. Biomass deposition onto HIC
supports is correlated to the development of a (reversible) energy secondary minimum,
which can be observed to arise from LW and AB forces. Calculations indicated that
moderate interactions between yeast cells and adsorbent beads can develop, especially in
presence of higher salt concentrations at pH 7.
It was also found that cell-to-cell aggregation is taking place in the context of
hydrophobic interaction conditions i.e. at high salt concentrations. Because of the high salt
concentration, the repulsive electrostatic forces are reduced allowing yeast cells to interact
with each other. Again, LW and AB forces were relevant to aggregation phenomena. Buffer
pH and conductivity were found to influence cell-to-bead interaction and cell-to-cell
aggregation. In both cases, predictions based on the XDLVO approach were validated by
biomass deposition experiments, laser diffraction spectroscopy, and confocal microscopy.
3) Chelating beads to biomass
Immobilized ion-metal affinity (“Chelating beads”) chromatography (IMAC) is run at
moderate salt concentrations (viz 250-750 mM sodium chloride). The interaction of
biomass with IMAC-Cu2+ was observed to be related to the development of a (reversible)secondary energy minimum. An influence of buffer pH and conductivity was observed
within normal operational windows. From XDLVO calculations it can be concluded that
favorable interaction of yeast cells with Chelating beads takes place at pH≥ 8. However,
biomass deposition experiments failed to confirm such prediction i.e. a decrease in
deposition coefficient at pH 8 was observed. This anomalous behavior can be explained
considering that Cu2+ can be actually sequestrated from the Chelating beads by yeast cells,
a fact usually exploited for biosorption of metal ions from wastewaters.
Cell-to-cell aggregation behavior also observed at IMAC process buffer conditions. The
aggregation phenomena especially with IMAC Cu2+ system were also discussed. The
extent of cell- cell aggregation was found to be less at IMAC buffer conditions when you
compare with that of the hydrophobic interaction buffer conditions.
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Figure 2 : General correlation betweenα and U.
Force vs. distance profiles were calculated for a large combination of model biomass and
adsorbent bead types. The energy minima values (absolute value / U) obtained for each of
the analyzed cases were correlated with the corresponding deposition coefficient values
(Figure 2). A positive correlation was obtained. It was concluded that total interactionenergy U≤ -25 to -50 kT and biomass deposition parameter α ≤ 0.15 would be a safe region
for EBA operation e.g. biomass interference can be neglected. Deviation in the correlation
was found in such cases where moderate or high cell-to-cell aggregation occurs, for
example in hydrophobic interaction systems.
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5) Remarks
1) The work highlighted the use of yeast as model biomass onto various process surfaces.
The tools developed for understanding of yeast interaction and aggregation onto the process
surfaces can be extended to any different model biomass or any kind of process surface.
From the preceding results and discussions, it allowed us to draw conclusion that
mechanistic tools developed here can be universally applied.
2) Local level understanding of biomass interaction can lead to development and design of
an optimized primary unit operation (like EBA). For example, the amount of hydrodynamic
force required to prevent the interaction or modification of the process surfaces with
polymeric brushes (length of brushes) to prevent interaction.
3) The data provided from this work can act as first step for global modeling of EBA.
4) The knowledge obtained from the physicochemical properties of biomass and absorbent
surfaces would allow easy access to process predictions without any trial and error
experiments in laboratory. Hence the developed approach here can be used to design EBA
process where reduced time and effort is required.
A fundamental knowledge about the roles of key variables affecting interactions
/aggregation described herein is of great importance, because their correct manipulation can
help to prevent or at least mitigate fouling.
6) Recommendations for further work
1) The current thesis work explored interaction of yeast as a model organism onto various
adsorbent surfaces. There is still room to understand the behavior of several other feed-
stocks like yeast and bacterial debris, mammalian cells and plant cells which are commonly
utilized in biotechnology industry as a host system for biopharmaceuticals production. It is
very important to understand the compatibility of various kind of biomass onto process
surfaces, which could allow drawing some general conclusion from where a global model
for EBA process design can be proposed.
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2) The biomass deposition transport phenomenon has to be better modeled where the three
parameters - collision efficiency (cell to process attachment), blocking (amount of process
surface blocked) and ripening (cell-to-cell aggregation), can be quantitatively obtained.
Further quantitative straining models have to be implemented to completely rule out the
role of physical attrition during these biomass deposition experiments.
3) XDVLO predictions made in the current work can be further directly verified
experimentally with force/ distance curves utilizing atomic force microscopy. This would
further broaden understanding and signifies the importance of the various forces to be taken
into consideration.
4) Age of biomass culture and its influence on interaction and aggregation especially with
the hydrophobic materials can be tested. Preliminary studies with the different age of the
culture showed the differences in the deposition phenomenon especially with hydrophobic
material type.
5) HIC/ EBA process limitations are not described in the literature (with any type of
biomass) which is actually prone to have deleterious effects by biomass interference
(observations from current research work). Hence there is room to explore more in thisdirection and define the solution/ operational windows for HIC materials in context of
EBA.
6) PVP 360 additive which was found to inhibit the interaction of yeast with DEAE beads
in this work can be further tested for its compatibility under real EBA operations.
7) Hydrodynamic shear and its impact on the secondary minimum can be explored in detail.
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4.0 AppendixBiomass deposition experiments, which were performed during the current thesis work, are
geared towards in-depth understanding of the fate and transport of biomass through the
packed bed chromatographic adsorbents. These understandings could be helpful in
preventing the attachment or predicting the transport behavior of biomass during bioprocess
scenario where direct sequestration of bioproducts expected in presence of biological
particles like expanded bed adsorption.
The physicochemical parameter α can be obtained from such experiments relates to the
attachment efficiency of colloidal particles (yeast) onto the collector surfaces (process
surface). Obtaining such quantitative information is possible through the application of colloid filtration theory. The physicochemical parameter determined from these
experiments can at times lead to false quantative information which may be due to the
physical filtration means. This indicates the cell effluent profiles go down due to the
attrition effects which have been shown previously in many studies (Tufenkji et al. 2004).
Among many models developed to predict the potential for straining, Bradford (Bradford et
al. 2004) and Sakthivadivel (Sakthivadivel 1966; Sakthivadivel 1969) developed a modelto predict the potential of straining based on the system geometry. According to this
straining could have a significant influence when the ratio of the particle diameter to the
median grain diameter (d p/dc) is greater than 0.05. In the current study d p/dc ≈ 0.04, which
means that, physical filtration effects can be neglected. However there are some studies
showing that straining observed when d p/dc values were as low as 0.002 (Tufenkji et al.
2004). To prove that in the current thesis work straining can be neglected, biomass
deposition experiments were performed with colloids (yeast) utilized in the study with thenon-interacting adsorbent beads (Streamline SP). These experiments were performed in
dilute buffers conditions.
Figure 1 depicts the biomass deposition experiments performed with the yeast and
Streamline SP. At very low ionic strength of the buffer, the electrostatic double layer
repulsion between the particles and beads packed in the column is substantial such that
particle deposition (physicochemical phenomenon) can be neglected. Thus, in this type of
experiment, any particle removal in the packed bed is attributed to the influence of a
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physical mechanism such as straining. Hence it is expected that cell effluent concentrations
should be similar to the concentrations of cells before in contact with the collector. The
experimental evidence from the figure 1 suggest that there is a complete breakthrough of
the curve ( C/Co ≈ 1 ) indicating that straining does not play a role in the removal of
particles in porous media. This also could be reflected in theα ≤ 0.018 the minimum alpha
which represents absence of any type of interactions.
Figure 1: Biomass deposition experiments between intact yeast to cat-ion exchangers
(Streamline SP) at very dilute buffer conditions (0.66 mS.cm-1, pH 7.6).
From this experimental observation now it can be clearly stated that differences in the
physicochemical parameter α reported in this thesis work are mainly due to influence of physicochemical forces.
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