Department of Physics, Chemistry and Biology

MASTER’S THESIS

New SPR based assays for plasma protein titer determination.

Johan Kärnhall

Performed at GE Healthcare Bio-Sciences AB

Linköping, February 2011

LITH-IFM-A-EX—11-2388--SE

The Department of Physics, Chemistry and Biology

Linköping University

SE-581 83 Linköping, Sweden

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Department of Physics, Chemistry and Biology

New SPR based assays for plasma protein titer determination.

Johan Kärnhall

Performed at GE Healthcare Bio-Sciences AB

Linköping, February 2011

Supervisors:

Åsa Frostell-Karlsson

Dr. Camilla Estmer Nilsson

Examiner:

Prof. Bo Liedberg

GE Healthcare Bio-Sciences AB

SE-750 15 Uppsala, Sweden

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Abstract Reliable analytical tools are important for time efficient and economical process development,

production and batch release of pharmaceuticals. Therapeutics recovered from human plasma,

called plasma protein products, involve a large pharmaceutical industry of plasma fractionation.

In plasma fractionation of human immunoglobulin G (hIgG) and albumin (HSA) recommended

analysis techniques are regulated by the European Pharmacopoeia and are including total protein

concentration assays and zone electrophoresis for protein composition and purity. These

techniques are robust, but more efficient techniques with higher resolution, specificity and less

hands-on time are available.

Surface plasmon resonance is an optical method to study biomolecular interactions label-free

in real time. This technology was used in this master thesis to set up assays using Biacore systems

for quantification of HSA and hIgG from all steps of chromatographic plasma fractionation as a

tool for process development and in-process control. The analyses have simplified mass balance

calculations to a high extent as they imply specific detection of the proteins compared with using

total protein detection. The assays have a low hands-on time and are very simple to perform and

the use of one master calibration curve during a full week decreases analysis time to a minimum.

Quick, in-process control quantification of one sample is easily obtained within

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Acknowledgement

I would like to thank:

My supervisors Åsa Frostell-Karlsson and Camilla Estmer Nilsson at GE Healthcare

Bio-Sciences for their great support and help throughout the project and for giving me

the opportunity to perform my master thesis project at GE Healthcare.

Members of the Protein Analysis R&D, Applications division for support and for

answering any Biacore-related questions.

Members of the BioProcessing section for their very friendly and supporting manner

during the three weeks of guidance and evaluation of the purification process and the

associated analyses. And for providing me process samples throughout the project.

Klara Pettersson, my opponent for carefully reading through this report and giving me

valuable feedback.

Bo Liedberg, for taking the time to be my examiner for this master‟s thesis project.

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Table of Contents

1 Introduction ............................................................................... 1

1.1. Background ....................................................................................................... 1

1.2. Aim ..................................................................................................................... 2

1.3. General approach ............................................................................................... 2

2 Theory ....................................................................................... 3

2.1. Plasma ................................................................................................................ 3

2.1.1. Plasma fractionation process ......................................................................................... 3

2.1.2. Immunoglobulin G ......................................................................................................... 6

2.1.3. Albumin ............................................................................................................................ 7

2.2. Protein characterization and quantification ...................................................... 8

2.2.1. Protein composition ....................................................................................................... 8

2.2.2. Molecular size distribution ............................................................................................. 8

2.2.3. Protein quantification ..................................................................................................... 8

2.2.4. International reference material .................................................................................... 9

2.2.5. Coefficient of Variation (CV) ...................................................................................... 10

2.3. Surface plasmon resonance biosensor technology .......................................... 11

2.3.1. Biacore system ............................................................................................................... 12

2.3.2. Sensor chip ..................................................................................................................... 13

2.3.3. Immobilization .............................................................................................................. 14

2.3.4. Concentration measurements ...................................................................................... 15

3 Materials and Methods ............................................................ 17

3.1. Materials .......................................................................................................... 17

3.1.1. Chemicals ....................................................................................................................... 17

3.1.2. Reagents .......................................................................................................................... 19

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3.1.3. Materials.......................................................................................................................... 20

3.2. Methods ........................................................................................................... 21

3.2.1. pH scouting .................................................................................................................... 21

3.2.2. Immobilization .............................................................................................................. 21

3.2.3. Regeneration .................................................................................................................. 22

3.2.4. Biacore concentration assay development ................................................................. 23

3.2.5. Activity and cross-reactivity experiment with capture antibodies .......................... 26

3.2.6. Value transfer from international reference material to calibrator ........................ 27

3.2.7. Biuret, total protein concentration assay ................................................................... 31

3.2.8. SDS-PAGE .................................................................................................................... 32

3.2.9. ELISA ............................................................................................................................. 34

4 Results ...................................................................................... 37

4.1. Total IgG concentration assay ........................................................................ 37

4.1.1. Evaluations of reagents for total IgG concentration assay ..................................... 37

4.1.2. Assay development total IgG concentration ............................................................. 37

4.1.3. International reference material calibration for IgG standard ................................ 41

4.1.4. Results total IgG assay on plasma-derived process samples .................................. 42

4.2. IgG subclass distribution assay ....................................................................... 46

4.2.1. Evaluations of reagents for IgG subclass distribution assay .................................. 46

4.2.2. Assay development IgG subclass distribution .......................................................... 52

4.2.3. International reference material calibration IgGSc-standard .................................. 55

4.2.4. Results IgG subclass distribution assay on plasma-derived samples ..................... 57

4.3. Albumin concentration assay .......................................................................... 64

4.3.1. Evaluations of reagents for albumin concentration assay ....................................... 64

4.3.2. Assay development albumin concentration .............................................................. 67

4.3.3. International reference material calibration for albumin standard ........................ 68

4.3.4. Results albumin assay on plasma-derived process samples .................................... 70

4.4. Albumin specificity assay ................................................................................ 74

4.4.1. Evaluations of reagents for albumin specificity assay .............................................. 74

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5 Discussion ................................................................................ 77

5.1. Total IgG concentration assay ........................................................................ 77

5.2. IgG subclass distribution assay ....................................................................... 77

5.3. Albumin concentration assay .......................................................................... 78

5.4. Biacore assays, performance and comparison ................................................ 78

5.4.1. Specificity ....................................................................................................................... 78

5.4.2. Sensitivity ........................................................................................................................ 79

5.4.3. Resolution ...................................................................................................................... 79

5.4.4. Robustness ..................................................................................................................... 80

5.4.5. Hands-on and analysis time ......................................................................................... 80

5.4.6. Consumables cost ......................................................................................................... 82

6 Recommendations ................................................................... 83

7 References ................................................................................ 85

Appendix A Regeneration scouting α-hIgG2........................................ 89

Appendix B Hands-on and analysis time .............................................. 91

Appendix C Protocol total IgG concentration assay ............................ 92

Appendix D Protocol IgG subclass distribution assay ......................... 94

Appendix E Protocol albumin concentration assay ............................. 97

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List of abbreviations CM5 Carboxymethylated Dextran 5 CV Coefficient of Variance EA Ethanolamine EDC 1-ethyl-3-dimethylaminopropyl-carbodiimide EDTA Ethylene diamintetra acetic acid HBS-EP+ 10 mM Hepes pH 7.4, 150 mM NaCl, 0.5 mM EDTA, 0.5 %

surfactant P20 IFC Integrated microfluidic cartridge IgG Immunoglobulin G IgGSc Immunoglobulin G subclass IVIG Intravenous immunoglobulin NHS N-hydroxysuccinimide P20 Surfactant P20 (Tween 20) RI Refractive Index RM Reference Material RU Resonance Unit SDS-PAGE Sodium dodecyl sulphate polyacrylamide gel electrophoresis SPR Surface Plasmon Resonance TM Target Material

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- INTRODUCTION -

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Chapter 1

1Introduction

1.1. Background

Today, plasma protein products recovered from human plasma is a major class of

therapeutics. A large pharmaceutical industry for fractionation of human plasma in the world

with over 70 factories exists [1]. During the development of fractionation processes, during the

execution of the process and for quality control (QC) there are high demands on good and

sensitive analytical tools. Analysis of plasma protein products is highly regulated for safety

reasons and current approved methods are presented in the European Pharmacopoeia by the

European Directorate for the Quality of Medicine and HealthCare [2].

Albumin has been used as a therapeutic for over 50 years and its main usage is for colloid

replacement and maintaining of blood volume at blood loss [3]. Intravenous Immunoglobulin G

has been used for over 25 years and mainly for replacement therapy in primary

immunodeficiency syndromes and for myeloma or chronic lymphatic leukaemia, but new areas of

use are emerging [4].

GE Healthcare Bio-Sciences AB in Uppsala, Sweden has a chromatographic plasma

fractionation process for the protein products coagulation factor VIII, factor IX, human serum

albumin and Immunoglobulin G from human blood plasma. The sensitivity, specificity, analysis-

and hands-on time of the available analysis methods were not satisfactory for the involved parties

who required new and better methods.

GE Healthcare‟s platform Biacore, which employs surface plasmon resonance biosensor

technology and is a highly sensitive label-free analysis tool for biomolecular interactions, was

chosen for the study.

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1.2. Aim

The first aim of this study was to perform a feasibility study to see which of the plasma

protein products that was possible to quantify satisfactory with a Biacore-assay, with focus on

albumin, Immunoglobulin G (IgG) and the relative distribution of Immunoglobulin G subclasses

(IgGSc) 1-4. The second aim was to develop the most viable assay as far as time allowed, in

addition the results and methods were to be compared with current alternative analyses.

1.3. General approach

Several antibody reagents will be tested and conditions optimized for the Biacore-system. The

extreme salt and pH conditions that occur from the purification steps could possibly interfere

with the interactions required for the analysis and these parameters needed investigation. Process

samples will be analysed with the new Biacore assay as it is developed as well as with current

methods as a comparison. The plasma fractionation process will be examined for insight into the

actual experimental situation.

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Chapter 2

2Theory

2.1. Plasma

2.1.1. Plasma fractionation process

Methods used for plasma fractionation has been developed since the 1946 with methods

varying from traditional cold ethanol fractionation with ethanol precipitation and centrifugation

as the major techniques to modern chromatographic processes [3]. The use of a chromatographic

process enables a larger variety of products to be extracted from the plasma other than traditional

albumin processes, it is also less damaging and generally gives a higher yield.

There are two types of human plasma differentiated by the means of collection. The major

type is plasma collected with plasmapheresis or apherisis where blood is filtered or continuously

centrifuged and the blood cells returned to the donor. The second type is plasma recovered

through double centrifugation of whole blood donations. Plasma from plasmapheresis

corresponds to 65 % and recovered plasma to 35 % of the total plasma fractionated in the world

today [1]. Both the plasmapheresis donations (category A plasma) and whole blood donations

(category B plasma) are to be frozen within 6 hours, if frozen within 24 hours of donation

(category C plasma) it can only be used in the production of immunoglobulin G and albumin [5].

The current process of interest is a chromatographic method using several steps of buffer

exchange chromatography, gel filtration chromatography, anion- and cation exchange

chromatography together with ultra- and diafiltration and numerous other steps. Ultrafiltration is

used to increase the concentration while diafiltration also replaces the buffer. An overview of the

process is displayed in Figure 2-1. The process is structured with factor VIII being the first

product to be separated, thereafter factor IX followed by albumin and finally IgG. This leads to

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four segments that can be called: factor VIII-trail, factor IX-trail, albumin-trail and finally IgG-

trail. The crude plasma has to be treated with heparin, which is a highly-sulphated

glycosaminoglycan acting as an anti-coagulant. All the products have to undergo virus

inactivation and sterile filtration in order to be safe to use as a pharmaceutical [1, 5]. Virus

inactivation is typically done by addition of solvent and detergent chemicals, such as tween-80,

TNBP, or triton X-100, or by pasteurisation and finally sterile filtration.

The chromatographic purification requires a variety of different buffers with different pH and

salt levels to elute the wanted proteins. Sodium Chloride (NaCl) levels vary between 0 and 500

mM and pH levels vary from pH 4.0 to pH 9.0. Together, this can yield quite extreme conditions

complicating the quantification methods.

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Figure 2-1: Process overview plasma fractionation by GE Healthcare The four sections are denoted Factor VIII-trail, Factor IX-trail, Albumin-trail and IgG-trail. Blue boxes represent chromatography steps and yellow boxes represent filtration steps. In this study only the Albumin- and IgG-trail were studied, each time starting from plasma following the black arrows. Samples were taken and analysed from the entire process, at least before and after every major chromatography and filtration step. For example the DEAE Sepharose FF step in the Albumin-trail was denoted “Alb DEAE” and the second ultrafiltration in the IgG-trail was denoted “IgG UF2”.

Plasma

Pre-treatment

Sepharose 4 FF

Q Sepharose HP

Chemical addition

Virus inactivation

SP Sepharose HP

Superose 12 pg

Formulation

Ultrafiltration

Sterile filtration

Filling

Lyophilisation

Severe heat treatment

DEAE Sepharose FF

Chemical addition

Virus inactivation

Heparin Sepharose FF

Q Sepharose FF

Ultra-diafiltration

Sterile filtration

Filling

Lyophilisation

Severe heat treatment

Ultrafiltration

Sephadex G-25 C

Euglobulin precipitation

Centrifugation

DEAE Sepharose FF

CM Sepharose FF

Ultrafiltration

Heat treatment

Centrifugation

Sephacryl S-200 HR

Ultra-diafiltration

Formulation

Sterile filtration

Ultrafiltration

Q Sepharose FF

Ultrafiltration

Chemical addition

Virus inactivation

CM Sepharose FF

Ultra-diafiltration

Formulation

Sterile filtration

Filling

Pasteurization

Filling

Factor VIII Albumin

Factor IX

IgG

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2.1.2. Immunoglobulin G

Immunoglobulins, also known as antibodies, are protein molecules part of the immune system

used to specifically identify and bind antigens leading to an immune response. Antibodies usually

bind the antigens tightly, sometimes not even leaving space for water molecules, by interactions

primarily formed by hydrogen bonds and electrostatic interactions. In the bloodstream the most

common class of immunoglobulins are immunoglobulin G class (IgG), which will hereby be

described more thoroughly. In a normal pool of plasma, the total IgG level is on average 8.5

mg/ml [6]. IgG is a globular, water-soluble protein with a molecular weight of approximately

150 000 Dalton (150 kDa). IgG is composed of two light chains consisting of two domains each

and two heavy chains consisting of four domains each, linked together with disulphide bonds, see

Figure 2-2 for a structural overview [7]. All domains possess the characteristic immunoglobulin

fold consisting of two sandwiched antiparallel β-sheets [8].

Immunoglobulins are glycoproteins containing of 82-96 % protein and 4-18 % carbohydrate

attached to the heavy chains [8]. Each IgG has two antigen binding sites located at the N-termini

of the light and heavy chains in the variable domains (Figure 2-2) [7]. The region on an antigen

recognized by the antibody is called the epitope; there can be several epitopes on one antigen

recognized by different antibodies.

Figure 2-2: Structural overview of Immunoglobulin G An illustration of Immunoglobulin G showing the heavy (red) and light (blue) chain and also the Fc and Fab regions [7].

The pharmaceutical product intravenous immunoglobulin (IVIG or IGIV in the US) has

many clinical uses but with potential risks and an inevitable limited supply due to its human

origin. The United States Food and Drug Administration (FDA) currently have six clinical

indications licensed for IVIG, they are: primary immunodeficiency disease, idiopathic

thrombocytopenic purpura, Kawasaki disease, B-cell chronic lymphocyticleukemia, HIV

infection, bone marrow transplantation [4]. In recent studies, it has also been found to work for

autoimmune diseases [9] and Alzheimer‟s Disease [10].

Antigen binding site

Fab

Fab

Fc

hinge region

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2.1.2.1. IgG subclasses

There are four different isotypes, or subclasses, of IgG named IgG1, IgG2, IgG3 and IgG4.

The distribution of these subtypes in the blood varies with individuals, depending mainly on age

and sex. The average distribution is as followed: IgG1 (58,9 %) > IgG2 (21,1 %) > IgG3 (4,3 %)

≈ IgG4 (4,7 %) [7]. These different IgG subclasses, illustrated in Figure 2-3, show differences in

structure where IgG3 is larger (170 kDa) than the others (146 kDa) with the main difference in

the hinge region, with 62 amino acids in IgG3 rather than 12 in the others. IgG3 is also more

susceptible to proteolytic enzymes and has a shorter biological half-time, 7 days compared to 21

days [7].

Figure 2-3: Immunoglobulin G subclasses Illustrations of the four IgG subclasses. The major visible differences are the hinge-region which is uniquely elongated in IgG3 and shorter in IgG4 [7].

2.1.3. Albumin

Albumin is the most abundant protein in the plasma and corresponds to approximately 60 %

of the total protein by mass. On average, in a normal pool of plasma, the albumin level is 34

mg/ml [6]. It is a very stable, highly water-soluble protein with a molecular weight of 66 500

Dalton (66.5 kDa) [11]. Albumin maintains the colloid osmotic pressure which ensures retaining

of water in the circulation. The protein is also a carrier for several hormones, enzymes, fatty-

acids, metal ions and medical products [3]. In the blood, albumin is generally composed with 0.5 -

1.5 moles fatty-acids per mole albumin [11]. The most frequent fatty-acids are: Oleic < 33 %,

Palmitic 25 %, and Linoleic < 20 % [11]. During purification, some of the fatty-acid composition

will be depleted and by special steps it can be completely removed yielding a fatty-acid free

albumin preparation [11].

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2.2. Protein characterization and quantification

2.2.1. Protein composition

The protein composition in a plasma sample is generally determined by sodium dodecyl

sulphate polyacrylamide gel electrophoresis (SDS-PAGE). Proteins are separated on a gel by

electrophoresis, solely based on their molecular weight. By comparing the molecular mobility of

the samples with molecular markers, the protein composition and the purity may be concluded.

Other techniques for determination of protein composition are 2D gel electrophoresis (2DGE)

and capillary zone electrophoresis.

2.2.2. Molecular size distribution

Size exclusion chromatography, also called gel filtration chromatography, is used to determine

the molecular size distribution of the purified protein products. According to the European

Pharmacopoeia, for albumin at least 95 % of the total peak area has to be composed of monomer

or dimer and polymers and aggregates may not represent more than 5 % of the total peak area

[2]. For IgG the peaks of polymers and aggregates should not be more than 10 % of the total

peak area [2].

2.2.3. Protein quantification

Quantification of proteins is generally carried out with an assay based on analysis of a

calibrator of known concentration in several dilutions. In Biacore, there exists an alternative to

using a calibrator called Calibration Free Concentration Analysis (CFCA), more on this in section

2.3.4. The measured signal is used to construct a standard curve where standard points are fitted

with either a linear or non-linear mathematical fitting model. Samples with unknown

concentration with different dilutions is analysed and interpolated on the standard curve to give

the concentration. Preferably, a control sample with known concentration is also analysed and

the concentration interpolated on the standard curve is compared with the true concentration

[12].

Modern surface plasmon resonance based biosensor systems as well as nephelometric or

turbidimetric optical systems and ELISA use an antibody to recognize the targeted antigen in the

sample and these assays are called immunoassays or immunochemical assays. Other techniques

than immunoassays such as biuret-assay, Kjeldahl nitrogen-assay and absorbance spectroscopy

are less sensitive and not specific to a certain protein.

Quantification assays have a high demand on instrument and antibody reagents as well on

calibrators and controls. Immunoassays for human plasma protein measurements are highly

influenced by several factors that are not always met [13]. The nature of the antibody and antigen

is vital, with demand on highly specific antibodies and a homogenous invariable antigen. This is

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not always the case when analysing samples throughout a purification process as the antigen may

change as it becomes purer, for example the removal of fatty-acids bound to albumin (mentioned

in section 2.1.3) which may impact the interaction. Further, changes in salt levels as well as pH

might interfere with the antibody recognition in the immunoassay. Finally, the calibrator used has

to behave identically with the measured analyte in order to yield a comparable signal.

The leading techniques for protein quantification in clinical chemistry today are nephelometry

and turbidimetry [12]. The two methods are both immunochemical fluid phase optical sensors,

where nephelometry measures an increase in side-scattered light while turbidimetry measures a

decrease in light transmission. Calibrators or samples are injected into a reaction tube. Antibodies

against for example human IgG1 are added and antibody-antigen complexes are formed. After a

fixed time, the side-scattered light is recorded. Standard curves are constructed and sample

measures are interpolated and concentrations calculated [7].

There are several assays available for quantitative determination of IgG subclasses. The most

common ones are radial immunodiffusion (RID), nephelometry, turbidimetry and ELISA [7].

RID is performed in ready-to-use agar plates integrated with specific antibodies against the

IgGSc. Standards, controls and samples are added in holes in the agar. As the IgGSc migrates

into the agar and forms complexes with the integrated antibodies precipitation rings will emerge.

The diameter is proportional to the level of that specific IgG subclass. The method requires 48-

60 hours incubation time with a moderate hands-on time and no automation [7].

Nephelometry and turbidimetry are discussed above. The detection limit is in μg/ml range

with a fairly short analysis time and an automated system [7].

Enzyme-linked immunosorbent assay (ELISA) which was the method chosen to compare

with in this study is a well-known and widely used immunochemical method. The IgG subclasses

are captured by a coated anti-human IgG subclass-specific antibody. A secondary enzyme-linked

antibody is added and quantified by a coloured enzyme reaction upon addition of a substrate.

The ELISA method has a very low detection limit but demands a high hands-on time and a long

analysis time [7].

2.2.4. International reference material

In order to ensure the use of good and correct standards for quantification and to reduce the

observed variation of up to 50 – 100 % depending on the calibrator used, international reference

material has been introduced [13]. A variety of international reference materials has been used for

decades and has previously been produced by amongst others the World Health Organisation

(WHO), Community Bureau of References of the Commission of the European Communities

(BCR) and today by the Committee on Plasma Protein Standardisation of the International

Federation of Clinical Chemistry (IFCC) [13].

The latest recognised international reference material for plasma proteins is called ERM®-

DA470k/IFCC and is valid for twelve common plasma proteins: α2-macroglobulin, αl-acid

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glycoprotein (orosomucoid), αl-antitrypsin (αl-protease inhibitor), albumin, complement 3c,

complement 4, haptoglobin, immunoglobulin A, immunoglobulin G, immunoglobulin M,

transferrin and transthyretin (prealbumin) [14]. This type of reference material is called a certified

reference material (CRM) and is provided with a certificate of analysis with certified and traceable

values, accompanied with a value of uncertainty. CRMs are generally short on stock and are not

to be used on a daily basis [15].

Development and use of analytical tools requires large quantities of reference material and

with CRMs this would become quite costly. Instead it is recommended and practical to use other

reference materials or standards that are purchased or produced in-house to act as the calibrator

[15]. This calibrator is to be calibrated against the CRM using determined procedure and protocol

to transfer the value from the reference material to the target material [16-17].

2.2.5. Coefficient of Variation (CV)

The coefficient of variation (CV) is a normalized measure of reliability expressed in

percentage. It has the advantages to be a dimensionless number enabling the user to compare the

CV between different data sets without taking into consideration the mean value. When the mean

value is closer to zero the CV is very sensitive to small changes and are therefore not as useful.

CV is normally presented in percentage and with the number of data in the set as n. CV is

calculated with Equation 2-1 below.

Equation 2-1

Where σ = standard deviation and µ = mean.

100%

CV

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2.3. Surface plasmon resonance biosensor technology

Surface plasmon resonance (SPR) biosensor technology is a powerful tool in label-free

biomolecular interaction analysis used in drug discovery and proteomic research. Today, several

biosensor systems employing SPR technique exists on a growing market, the leader in SPR

biosensors is Biacore from GE Healthcare [18]. Also, other technologies for label-free

biomolecular interaction analysis are available, such as bio-layer interferometry (BLI) used in

ForteBio‟s instruments and quartz crystal microbalance used in Attana‟s and Q-sense‟s

instruments [19].

The application of surface plasmon resonance biosensors on biomolecules was first

demonstrated in 1983 [20]. When a beam of plane-polarized light passes through a prism with a

thin metal film it is totally internally reflected if the angle is above a certain critical angle of

incidence [21]. The reflected light is monitored and the intensity measured.

As the angle of incidence is changed the reflected light will decrease in intensity at a specific

angle showing a dip in reflected light. At this specific angle, surface plasmons in the metal film

are excited by the light inducing surface plasmon resonance (SPR) [21]. When the wave vector of

the incident light matches the wavelength of the surface plasmons, the free electrons in the metal

film resonate, hence the term surface plasmon resonance. The angle with the maximum loss of

intensity is called the SPR angle or resonance angle. This angle is dependent on the optical

properties of the media adjacent to the metal film.

Figure 2-4: Principle of SPR and schematic sensorgram Left: The principle of a SPR biosensor. Right: A schematic sensorgram showing the response upon association of analyte during injection and the dissociation post injection followed by regeneration.

1 0

Regeneration Analyte injection phase

Post-injection

phase

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On one side is the glass prism with an unaltered high refractive index (RI) and on the other

side the measured medium with a low RI [21]. Molecules such as proteins are bound and thereby

increasing the mass, the refractive index is changed leading to a shift in the SPR angle [21]. Figure

2-4 illustrates the principles of SPR described here and also shows a schematic sensorgram. The

shift in angle is translated to resonance units (RU), 1 RU is equivalent to 10-4° corresponding to

about 1 pg/mm2 bound protein and is linear all the way to the upper limit of the dynamic range

[22].

The surface plasmon creates an electromagnetic field, called the evanescent field, which

propagates into the media [22]. Any change in mass, and thereby a change in RI, occurring

within this evanescent field is detected by the sensor [22]. The molecule immobilized on the

surface is called ligand and the molecule injected sample is called the analyte.

Since the response is dependant of the refractive index of the solution in the flow channel,

when a solution with a different RI is injected a bulk response will be visible. When the injection

is completed, the bulk response will disappear. This can for example be visible when using

different buffers and variable concentrations of salts, such as NaCl in the solutions. Extreme

levels of NaCl (very high or low) might also affect interactions in other ways, as many

interactions are governed by electrostatic attractions.

2.3.1. Biacore system

The Biacore system from GE Healthcare can monitor a biomolecular interaction in real-time

and label-free. The system consists of three main units, the SPR optics, the liquid handling

system and the sensor chip [21]. The sensor chip will be discussed in section 2.3.2 and the SPR

optics and the principle of SPR technology was brought up in section 2.3. The instrument used in

this study was Biacore T100 system and in some cases T200, see Figure 2-5. These instruments

are very similar but with a higher sensitivity in the T200. In this system the liquid handling system

consists of an IFC with four flow-cells, sample injection loops, highly accurate pumps and

pneumatic valves [23]. For different applications the flow-cells can be used independently or

serially as in Figure 2-6.

Figure 2-5: Biacore T100 instrument A Biacore T100 instrument that was used during this study.

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Figure 2-6: flow-cells. Illustration of the flow-cells in a Biacore T100 system [24]. The flow-cells are formed when the sensor chip is docked on the IFC (top). The four flow-cells can be used either serially (left) or independently (right).

2.3.2. Sensor chip

The sensor chip (see Figure 2-7) consists of a plastic cassette designed so the sensor chip is

easily moved and positioned automatically onto the integrated microfluidic cartridge (IFC) in the

instrument. The chip itself is composed of a thin glass covered with a 50nm gold film, coated

with a monolayer of hydroxyalkanethiol linkers [23]. There are several different sensor chips

available with different surface chemistry attached to the linkers; they are suitable for different

interactions, applications and immobilization techniques. The most common sensor chip, and the

chip used in this study, is the CM5; which has a carboxymethylated dextran matrix attached [22].

The dextran matrix is used as an anchor for the immobilization of ligands (see section 2.3.3).

There are more advantages by using a dextran matrix; firstly it enables the ligands to be

positioned in a three dimensional space increasing the number of interactions sensed by the

evanescent field and thereby increasing the binding response, secondly it enables the interaction

to proceed under conditions that mimics a fluidic and thirdly it minimises non-specific binding to

the gold surface [24].

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Figure 2-7: Series S sensor chip CM5 The carboxymethylated dextran matrix spans 100 nm into the flow-cell and is attached to the gold surface with a layer of linkers (grey).

2.3.3. Immobilization

There are several available coupling chemistries to immobilize proteins to the sensor chip

surface. To the carboxymethylated dextran matrix on CM5 sensor chip it is possible to do several

different coupling chemistries [25]. Amine coupling, the most used technique and the one used

in this study, will be further described below [26]. Carboxyl groups on the matrix forms covalent

bonds with primary amines on the ligand protein. This reaction does not occur spontaneously

and an activation of carboxyl groups into esters is necessary. This is done with a mixture of 1-

ethyl-3-dimethylaminopropyl-carbodiimide (EDC) and N-hydroxysuccinimide (NHS) as

illustrated in Figure 2-8.

First, EDC reacts with the carboxyl group forming a reactive intermediate. Second, the NHS

reacts and forms a NHS ester which is a good leaving group. Finally, as the protein is injected the

activated ester will spontaneously react with primary amines on the protein forming a covalent

bond. The final step is to inject an ethanolamine (EA) solution that reacts with the remaining of

the activated esters.

Figure 2-8: EDC NHS chemistry The chemical reaction during EDC/NHS immobilization. EDC reacts with the carboxyl group on the dextran matrix. This forms a reactive intermediate which reacts with NHS, leaving an ester. The NHS ester is a good leaving group, reacting with a primary amine on the ligand, forming a covalent bond.

Carboxyl group / Ligand

Dextran

Linker layer

Gold film

Glass

- THEORY -

- 15 -

During the immobilization, in order to attract the ligand to the surface to ensure the reaction

to occur to a satisfactory extent it has to be attracted by electrostatic forces in something called

pre-concentration. By dissolving the ligand in a buffer with a pH below the pI of the protein, this

will result in the protein having a net positive charge and it will be attracted to the slightly

negatively charged dextran matrix.

The optimum pH can be determined by a pH scouting experiment described in section 3.2.1.

The properties that can be modified in order to vary the level of final immobilized ligand to the

desired level are concentration, pH of buffer, flow-rate and contact time.

2.3.4. Concentration measurements

The SPR technology can be used for concentration measurements in a robust, accurate,

precise and specific manner [27]. In several recent studies, SPR biosensors have been used for

quantification, for example quantification of bovine IgG in milk (2010) [28], estriol metabolites in

liquid media (2009) [29] and yessotoxin from marine dinoflagellates (2008) [30]. In general, three

methods for quantification exist. A traditional method using the relative response after injection

[23], a method using the binding rate (RU/s) [31] and the most recent calibration free

concentration analysis (CFCA) using two different flow-rates [32].

- MATERIALS AND METHODS -

- 17 -

Chapter 3

3Materials and Methods

3.1. Materials

3.1.1. Chemicals

Chemical Cat. No. Supplier

Milli-Q filtered H2O Millipore

HBS-EP+ 10X BR-1006-69 GE Healthcare

MgCl2 M2670 Sigma-Aldrich

50 mM NaOH BR-1003-58 GE Healthcare

3M MgCl2 BR-1008-39 (capture kit) GE Healthcare

Glycine pH 2.0 BR-1003-55 GE Healthcare

Amine coupling

Ethanol amine BR-1000-50 GE Healthcare

EDC BR-1000-50 GE Healthcare

NHS BR-1000-50 GE Healthcare

Immobilization pH scouting

Acetate pH 4.0 BR-1003-49 GE Healthcare

Acetate pH 4.5 BR-1003-50 GE Healthcare

Acetate pH 5.0 BR-1003-51 GE Healthcare

Acetate pH 5.5 BR-1003-52 GE Healthcare

- CHAPTER 3 -

- 18 -

Regeneration Scouting

Glycine pH 1.5 Regeneration scouting kit GE Healthcare

Glycine pH 2.0 BR-1005-56 GE Healthcare

Glycine pH 2.5 BR-1005-56 GE Healthcare

Glycine pH 3.0 BR-1005-56 GE Healthcare

SDS 0.5% BR-1005-56 GE Healthcare

NaCl 5M BR-1005-56 GE Healthcare

MgCl2 4M BR-1005-56 GE Healthcare

NaOH 200mM BR-1005-56 GE Healthcare

Ethylene Glycol BR-1005-56 GE Healthcare

SDS-PAGE NuPAGE Novex 4-12% Bis-Tris Gel, 1.9 mm, 12 well NP0322BOX Invitrogen

Precision Plus Protein Dual Color Standard 161-0374 Bio-Rad Laboratories AB

NuPAGE LDS sample buffer 4X NP0007 Invitrogen

β-Mercapthoethanol M6250 Sigma-Aldrich

NuPAGE MOPS SDS Running buffer 20X NP0001 Invitrogen

GelCode Blue Stain Reagent #24592 Thermo Scientific

ELISA

Peliclass human IgG subclass kit M1551 Sanquin

Chromatography media

Ion exchanger media ( GE Healthcare)

Matrix: Highly cross-linked agarose, 6%

Particle size: average 90 μm (45 – 165 μm)

Q Sepharose™ FF Quaternary ammonium strong anion exchanger

Cat. No. 17-0510-05

DEAE Sepharose™ FF Diethylaminoethyl weak anion exchanger

Cat. No. 17-0709-05

CM Sepharose™ FF Carboxymethyl weak cation exchanger

Cat. No. 17-0719-05

Gel filtration media (GE Healthcare)

Sepharose 4 Fast Flow Highly cross-linked 4% agarose

Cat. No. 17-0149-01 Particle size: 45 – 165 µm

Fractionation range: 6 × 104 – 3 × 107 Da

Sephacryl S-200 HR Spherical allyl dextran and N, N’-methylenebisacrylamide

Cat. No. 17-0584-10 Particle size: 50 µm

Fractionation range: 5 × 103 – 2.5 × 105 Da

Sephadex G-25 Cross-linked dextran

Cat. No. 17-0034-01 Particle size: 75 – 510 µm

Fractionation range: 1 × 103 – 5 × 103 Da

- MATERIALS AND METHODS -

- 19 -

3.1.2. Reagents

Name Denotation Supplier / Cat. No.

human IgG hIgG Sigma / I4506

human IgG1 κ (myeloma) hIgG1 Millipore / AG502

human IgG2 κ (myeloma) hIgG2 Millipore / AG504

human IgG3 κ (myeloma) hIgG3 Millipore / AG506

human IgG4 κ (myeloma) hIgG4 Millipore / AG508

Peliclass human IgG subclass standard IgGSc-standard Sanquin / M1551

Peliclass human IgG subclass control IgGSc-control Sanquin / M1551

HSA "Essentially fatty acid free" HSAa Sigma / A-3782

HSA "Fraction V" HSAb Sigma / A-1653

HSA “internally purified” HSAc GE Healthcare / internal

BSA BSA Sigma / P9418

HSA and gamma-globulins Sigma / P8119

International RM - ERM-DA470k/IFCC ERM-DA470k Sigma / ERMDA470KIFCC-1VL Antibodies

Species +

Specificity Denotation Clone Isotype Supplier / Cat. No.

human IgG (Fc) α-hIgG GE Healthcare / BR-1008-39

human IgG1 α-hIgG1poly sheep (poly) The binding site / AU006

human IgG1 (Fc) α-hIgG1a HP6091 mouse IgG2a The binding site / MC003

human IgG1 (Fc) α-hIgG1b HP6069 mouse IgG1 Invitrogen / MH1013

human IgG1 (Fc) α-hIgG1 HP6070 mouse IgG1 Invitrogen / MH1015

human IgG2 (Fab) α-hIgG2 HP6014 mouse IgG1 The binding site / MC005

human IgG3 (Fab2) α-hIgG3 HP6050 mouse IgG1 The binding site / MC006

human IgG4 (pFc) α-hIgG4 HP6025 mouse IgG1 The binding site / MC009

mouse IgG (Fc) α-mIgG Rabbit (poly) GE Healthcare / BR-100838

HSA α-HSApoly Rabbit (poly) GE Healthcare / internal

HSA α-HSAmab mouse IgG1 Abcam / Ab399

BSA α-BSAa 2A3E6 mouse IgG1 Santa Cruz Biotech / sc-32816

BSA α-BSAb 0.N.32 mouse IgG1 Santa Cruz Biotech / sc-70445

BSA α-BSAc BGN/D1 mouse IgG1 Santa Cruz Biotech / sc-80704

- CHAPTER 3 -

- 20 -

3.1.3. Materials

Material Cat. No. Supplier

Microplate 96 well

Microplate cover-foil 96 well

Microplate flat bottom 96 well

Pipette and pipette tips, 10-100ul Eppendorf

Pipette and pipette tips, 20-200ul Eppendorf

Pipette and pipette tips, 100-1000ul Eppendorf

Finnpipette, 5mL Labsystems

Finntips, 5mL 940 20 50 Thermo Scientific

Pipette Multi channel, 30-300ul Eppendorf

Pipette Multi channel automatic, 10-200ul Eppendorf

Pipette Multi channel automatic, 100-1000ul Eppendorf

Series S Sensor chip CM5 BR-1006-68 GE Healthcare

Plastic vials, ø 7mm BR-1002-12 GE Healthcare

Glass vials, ø 16mm BR-1002-09 GE Healthcare

Rubber cap, type 3 (for ø 7mm) BR-1005-02 GE Healthcare

Rubber cap, type 2 (for ø 16mm) BR-1004-11 GE Healthcare

Instrument Software Supplier

Biacore T100 Control software v2.0.3, Evaluation software v2.0.3 GE Healthcare

Biacore T200 Control software v1.0, Evaluation software v1.0 GE Healthcare

Milli-Q Advantage A10 Millipore

Electrophoresis power supply – EPS 301 GE Healthcare

miniVE – Vertical electrophoresis system GE Healthcare

ImageScanner III Labscan 6.0 GE Healthcare

ImmageQuant TL 6.0 GE Healthcare

SPECTRA Max PLUS 384 SoftMax Pro v5.4 Molecular Devices

Microplate-shaker

ÄKTA pilot Unicorn v5.11 GE Healthcare

- MATERIALS AND METHODS -

- 21 -

3.2. Methods

If nothing else is stated, all Biacore-experiments were performed at 25°C with HBS-EP+ as

sample and running buffer. For longer (>12 hours) experiments the sample compartment

temperature was decreased to 10°C from 25°C, but the analysis temperature remained unaltered.

3.2.1. pH scouting

In order to determine the optimal pH for pre-concentrating the ligand to the matrix during

immobilization, as described in section 2.3.3, a pH scouting was performed. The ligand was

diluted to 20 μg/ml in buffers with different pH and injected during 2.5 minutes over an

unmodified sensor chip. After each injection the surface was regenerated with 50 mM NaOH to

ensure no ligand remains non-specifically bound to the surface. The most neutral pH was

injected first followed by more acidic injections. The aim was to obtain a sufficiently high

increase of response but with the most neutral pH possible in order to maintain the native state

of the ligand. The buffers used were 10 mM sodium acetate with pH ranging from 4.0 to 5.5, 10

mM maleate pH 6.0 to 6.5 and 10 mM phosphate pH 7.0. An example of a pH scouting can be

seen in Figure 4-8.

3.2.2. Immobilization

Immobilization of ligands to the sensor chip surface was performed with amine coupling

chemistry, as described in section 2.3.3. Chemicals from amine coupling kit (GE Healthcare)

were utilised. The surface was activated with a 7 minute injection of 1:1 mixture of EDC and

NHS. The ligand injection was optimized for each antibody and specified under each result

section; typically a 7 minute injection of 20 μg/ml antibody diluted in pre-concentration buffer

was used. The surface was deactivated with a 7 minute injection of ethanol amine (EA). An

example of an immobilization sensorgram is displayed in Figure 3-1.

Figure 3-1: Typical immobilization sensorgram

0

10000

20000

30000

0 400 800 1200 1600

Re

spo

nse

(RU

) .

Time (s)

EA Ligand ~10000 RU EDC/NHS

- CHAPTER 3 -

- 22 -

3.2.3. Regeneration

For experiments when the affinity of the interaction is high, and the analyte does not

dissociate by itself it is required to regenerate the surface between cycles. This is generally the

case for concentration analysis with high affinity antibodies and high responses. The principle of

regeneration is that the interactions between the analyte and the ligand are broken at the same

time as the analyte may be partly denatured whilst the ligand maintains its activity. Therefore, for

an easier regeneration the less stable protein should be the analyte.

Different results that might occur during regeneration are illustrated in

Figure 3-2. A and B show optimal and acceptable regeneration when the analyte response and

the baseline remains the same. C and D illustrate incomplete regeneration. The last two show

irreversible changes of the ligand due to the regeneration, E has a loss of ligand activity and in F

the ligand is lost from the surface.

Figure 3-2: Illustration of regeneration results Common regeneration results are illustrated. A and B show good regeneration. C and D illustrate incomplete regeneration. E and F indicate an irreversible change on the ligand due to regeneration.

3.2.3.1. Regeneration scouting

The protocol from the regeneration scouting kit was followed. A freshly immobilized and

previously unused surface was used for each regeneration solution tested. An analyte with a high

concentration was injected and the binding response and baseline was compared to the initial

cycle. The mildest condition for each solution was used first with a successively tougher

Analyte response

Baseline

A Optimal regeneration.

C Incomplete regeneration. Accumulation of analyte and loss of capacity. .

E Loss of ligand activity. Irreversible change.

B Acceptable regeneration.

D Incomplete regeneration. Accumulation of analyte.

F Loss of ligand. Irreversible change.

- MATERIALS AND METHODS -

- 23 -

condition following. For each condition the analyte was injected and regenerated four to five

times.

The conditions are met if the response is recovered to preferably 70 % from the first cycle and

the baseline is similar to the first cycle, a small constant decrease in baseline may be acceptable as

long as the analyte response is repeatable. The condition that gives the best regeneration is

verified by 20 or more cycles with the same condition. Further, the injection time of regeneration

solution might be increased or decreased in order to give a better regeneration.

The tested regeneration solutions were:

10 mM Glycine-HCl, pH 3.0 to 1.5

Ethylene glycol, 50% to 100%

Sodium hydroxide (NaOH), 1 mM to 75 mM

Magnesium chloride (MgCl2), 1 M to 4 M

Sodium chloride (NaCl), 0.5 M to 5 M

Sodium dodecyl sulphate (SDS), 0.02 % to 0.5 %

3.2.4. Biacore concentration assay development

There were three different methods of concentration determination in Biacore to choose

from. First, the traditional method where the relative response of the calibrator was plotted

against the concentration [23]. Second, a method where the binding rate (RU/s) of the calibrator

was plotted against the concentration [31]. Third, a calibration free concentration analysis

(CFCA) where a calibrator was not needed by using different flow-rates [32-33]. With the plasma

and process samples that were analysed, the traditional relative response method was chosen due

to large bulk responses and some non-specific binding during injection of non-purified samples

interfering with the other methods.

The Biacore concentration assays that were developed in this study had a number of

parameters that were optimized and thus leading to the assays presented in section 4.1.2 for total

IgG, section 4.2.2 for IgG subclass distribution and section 4.3.2 for albumin. These parameters

and the criterions to determine them will be discussed here.

Biacore concentration assay parameters:

Ligand antibody

o Choice of antibody

The desired characteristics for an antibody to be used in a concentration assay

was that it binds the analyte specific and with a high affinity when immobilized

on the sensor chip. Antibodies were also necessary to be able to regenerate

under known conditions without losing activity. Preferably commercially

available monoclonal antibodies were chosen.

- CHAPTER 3 -

- 24 -

o Immobilization level: Buffer, injection time, flow-rate, concentration

The aimed immobilization level for concentration assays is generally around

10000 RU. A high immobilization level is necessary in order to have mass-

transport limited interaction as discussed below. To reach a certain level the

pH of the pre-concentration buffer had to be determined by a pH scouting

(section 3.2.1). Also the injection time was evaluated to obtain desired level.

Finally the concentration of the antibody diluted into the pre-concentration

buffer was studied to determine a suitable concentration. Several antibodies

were delivered in sodium-azide preservative and Tris-buffer and had to be

diluted enough to avoid interfering with the immobilization. As these

compounds contain a primary amine they would otherwise be immobilized.

The flow-rate decreased in order to reduce consumption of reagents.

Concentration assay

o Buffer

HBS-EP+ has in several previous studies been shown as an appropriate buffer

for real-time interaction studies and was found to work well also for these

assays.

o Choice of reagent

The reagent used as standard needs to interact with the antibody in an identical

manner as the sample. The reagent should preferably be commercially

available. Users of the assays can utilise their own standards as long as it is

calibrated against the international reference material.

o Concentration range, injection time and flow-rate

Injection time and concentrations were varied to obtain an assay where the

lowest point in the standard curve gave high enough response while

maintaining sufficient sensitivity. At the same time the assays were designed to

be as rapid as possible. The time could readily be shortened as the sensitivity

was not the main focus, since the samples generally had high concentrations.

The highest point in the standard curve was chosen so the interaction would

be mass-transport limited and thus having a linear increase of response during

the injection and avoiding the antibodies to approach steady-state [31, 33].

This lead to linear standard curves without a plateau, consequently giving a

higher resolution and precision. The dilutions of the standard were typically

done by six serial 2- or 2.5-fold dilutions.

Even though the flow-rate might affect the response slightly this parameter

was normally only set to reduce sample consumption.

- MATERIALS AND METHODS -

- 25 -

o Regeneration: Conditions, injection time, flow-rate

If not previously known, the regeneration conditions were found by

regeneration scouting (section 3.2.3.1). The flow-rate was typically set slightly

higher than the flow-rate for the analyte injection. The injection time of

regeneration solution was also kept as short as possible to have a short analysis

time but with a complete regeneration. A so called pre-dip was used to avoid

dilution of the regeneration solution with running buffer during analysis of

many samples.

An example of a sensorgram from the injection of a standard curve is shown in Figure 3-3.

Some of the parameters discussed above are also illustrated in the figure. The relative response

was found by subtracting the baseline response, before injection, from the response after

injection as illustrated. Also seen in the figure is the short sample injection time with almost

completely constant RU/s. The delay between end of injection and regeneration was limited by

IFC washing in the instrument.

Figure 3-3: Example of sensorgrams from injection of standard curve. Illustrating standard curves from six concentrations of standard. In the example the injection and regeneration time are illustrated with arrows.

x x

[standard] (µg/ml)

0

1000

2000

3000

0 20 40 60 80 100 120 140 160

Time (s)

x

x

x

x x

50

20

3.2

8

1.3 0.5

Injection Regeneration

Response (RU)

x

- CHAPTER 3 -

- 26 -

3.2.5. Activity and cross-reactivity experiment with capture antibodies

The set-up for an experiment with a capture antibody was used to ensure the mildest possible

treatment of the antibody by relieving it from the stress of being immobilized by acidic

conditions during covalent coupling. The set-up is also preferred if the regeneration conditions

for the antibody are not yet known.

It is possible to get false negative results if the immobilized ligand binds to the binding

domain of the capture antibody making it unable to bind its antigen. To eliminate false positive

results it is essential to also inject the analyte without the capture antibody to ensure it does not

interact with the ligand alone.

The set-up is illustrated in Figure 3-4 supported with a schematic sensorgram. As the capture

antibody is injected there is an increase in response. If there is another increase in response as the

analyte is injected it is considered a positive interaction. This is followed by regeneration of the

surface and a second capture antibody can be injected.

Figure 3-4: Set-up of method with capture antibody The first antibody (blue) represents the ligand immobilized to the dextran matrix on the sensor chip. The capture antibody (red) is injected giving a response seen in the sensorgram. As the analyte (green) is injected it gives a response in the sensorgram if the interaction is positive.

Inject capture Ab

Inject sample Positive!

Regeneration

Immobilized ligand Capture antibody Analyte

Re

spo

nse

(RU

)

Time (s)

- MATERIALS AND METHODS -

- 27 -

3.2.6. Value transfer from international reference material to calibrator

A protocol developed by the International Federation of Clinical Chemistry and Laboratory

Medicine (IFCC) to transfer plasma protein concentration values from an reference material

(RM), here ERM-DA470k/IFCC [14], to an internal calibrator, called target material (TM), was

followed [16-17]. The procedure will be described here and deviations from the protocol will be

accentuated. The value transfer was performed after the assays were completed. While the

procedure is described here the results for each of the three assays are presented in their

respective result section (4.1.3 for total IgG, 4.2.3 for IgG subclass distribution and 4.3.3 for

albumin).

According to the protocol, the measurements were to be performed three times a day on four

consecutive days, but due to time constraints the measurements were only performed once a day

over three days but with duplicate measurements for both calibration curve and samples. For

each day, new dilutions were made. Both the calibration curve and the sample consisted of six

dilutions each. This yielded in 36 determinations each (6 dilutions * 2 replicates * 3 days = 36) for

the RM and the TM. An additional special dilution of RM was used as control sample giving

another 6 determinations (2 replicates * 3 days = 6).

The RM was reconstituted according to the product sheet:

The vial was thawed in room temperature for one hour.

The vial was tapped gently to ensure all material settled on the bottom.

Removing the screw cap.

The vial together with rubber stopper was weighed in gram with four decimals.

1 mL of water was added, new weight recorded to acquire the water mass.

The concentration after constitution was calculated with Equation 3-1 below.

After one hour, the vial was inverted gently five times during one hour.

Vail stored in room temperature overnight.

Equation 3-1

Where is the certified concentration and the actual concentration after

reconstitution.

Six dilutions of the reconstituted RM served as standards for the calibration curve. The

concentrations were evenly distributed over the measuring range of the assay. To minimize the

sources of errors all volumes dispensed were controlled by weighing and the actual dilutions with

four decimals were calculated. The densities of all liquids were approximated to 1.

water

R

water

RR

m

C

m

mCC

0000.1''

'

RC RC

- CHAPTER 3 -

- 28 -

An example of the dilution scheme for human IgG is presented in Table 3-1 below. In order

to get suitable volumes of RM and dilution buffer in the scheme, a predilution of the RM was

performed. Additionally, to avoid pipetting small volumes, Std.4, Std.5 and Std.6 were prepared

from Std.2, Std.3 and Std.5 respectively.

The relative concentration in percentage was calculated by Equation 3-2 and these

concentrations represent the values on the x-axis in the calibration curve. Another excel-

spreadsheet equivalent to that in Table 3-1 was filled in with actual masses from pipetting where

actual dilutions and relative concentrations were calculated. Hence, these were the values entered

into the method as concentration in percentage.

Equation 3-2

Where is the mass of reference material, the mass of dilution buffer,

predilF is the predilution factor and Std.2 is the relative concentration of Standard 2.

Human IgG - Intended predilution of the Reference Material

Dilution buffer, (g) 0,9500

Reference Material, (g) 0,0500

Predilution factor, FPredil 0,050000 RM reconst. conc. (CR)

Human IgG - Intended dilutions of the Reference Material 9259,82 μg/ml

Std. 1 Std. 2 Std. 3 Std. 4 Std. 5 Std. 6 Control

Dilution buffer, (g) 0,8000 1,2000 1,3000 0,4000 0,7000 0,6000 1,1000

Reference Material, (g) 0,1000 0,1000 0,0750 0,3000 0,3000 0,1000 0,0500

of predil of predil of predil of Std. 2 of Std. 3 of Std. 5 of predil

Total mass, (g) 0,9000 1,3000 1,3750 0,7000 1,0000 0,7000 1,1500

Dilution factor 0,1111 0,0769 0,0545 0,4286 0,3000 0,1429 0,0435

Predilution factor 0,050000 0,050000 0,050000 0,003846 0,002727 0,000818 0,050000

Relative concentration, (%) 0,5556 0,3846 0,2727 0,1648 0,0818 0,0117 0,2174

Concentration, (μg/ml) 51,44 35,61 25,25 15,26 7,58 1,08 20,13

Aimed target conc. (μg/ml) 50,00 35,00 25,00 15,00 7,50 1,00 20,00

Table 3-1: Example of intended dilution scheme of reference material for value transfer Predilutions for Std.4, Std.5 and Std.6 were calculated from the dilution of the standard it was prepared from. All weights were recorded in grams with four decimals and predilution factors with six decimals. Volumes were chosen to give a concentration in μg/ml (calculated from CR and the relative concentration) close to the aimed target concentration, which was based on the concentration range of the assay. This dilution scheme was followed and an equivalent excel-spread sheet was filled in with actual masses where actual dilutions and actual relative concentrations were calculated.

RM DilM

(when Std.4 is prepared

from Std.2)

or

DilR

Rpredil

MM

MFStdconcrel

1002..

DilR

R

MM

MStdStdconcrel

2.4..

- MATERIALS AND METHODS -

- 29 -

The target material was also diluted in six dilutions. As these six dilutions were samples they

were aimed to all fall within the calibration curve generated. A predilution was performed to a

concentration in the upper quarter of the standard curve. The prediluted TM was added in

decreasing volumes to correspondingly increasing volumes of dilution buffer yielding in a

constant total volume, with all weights recorded. An example of dilution scheme of target

material for IgG is shown in Table 3-2. The dilution factor denoted FT2 was calculated by

Equation 3-3 and was used as the x-value in the upcoming plot and calculations. The actual

masses were weighed and entered in an excel-spreadsheet giving the actual values of FT2.

Equation 3-3

Where is the mass of prediluted target material and the mass of dilution buffer.

Human IgG - intended predilution of the Target Material

Dilution buffer, (g) 2,5000

Target Material, (g) 0,0400

Predilution factor, FT1 0,015748

TM estimated conc.

Human IgG - intended dilutions of the Target Material 2000,00 μg/ml

Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Sample 6

Dilution buffer, (g) 0,0000 0,0500 0,1000 0,2000 0,3000 0,3750

Target Material, (g) 0,5000 0,4500 0,4000 0,3000 0,2000 0,1250

Dilution factor, FT2 1,0000 0,9000 0,8000 0,6000 0,4000 0,2500

Predilution factor, FT1 0,015748 0,015748 0,015748 0,015748 0,015748 0,015748

Relative concentration, (%) 1,5748 1,4173 1,2598 0,9449 0,6299 0,3937

Concentration, (μg/ml) 31,50 28,35 25,20 18,90 12,60 7,87

Table 3-2: Example of intended dilution scheme of target material for value transfer The highlighted values are dilution factor FT2. All weights were recorded in grams with four decimals. The actual values from the corresponding excel-spreadsheet will be used as x-values in the upcoming plot and calculations.

When all dilutions were made, the assay was executed with one set of standards, duplicates of

all samples, a duplicate of control sample and finally another set of standards. The outcome was a

standard curve similar to the illustration in Figure 3-5, with relative concentration in percentage

versus response in RU. In the evaluation software, the responses of the samples were

interpolated on the standard curve giving a relative concentration in percentage.

Figure 3-5: Schematic standard curve value transfer The standard curve with relative concentration in percentage on the x-axis and response in RU on the y-axis.

DilT

TT

MM

MF

2

TM DilM

Response, (RU)

Relative concentration, (%)

- CHAPTER 3 -

- 30 -

The average concentration for each sample was transformed with Equation 3-4 to become a

y-value, or relative concentration factor FR, that was comparable with the x-values, FT2. The

control samples were compared to expected relative concentrations to give an indication of assay

performance. This was done by dividing the interpolated relative concentration with the expected

relative concentration; a value of 1.0 equals a control with 100 % compared to expected.

Equation 3-4

Where FR is the relative concentration factor for sample i and FT1 is the predilution factor.

The dilution factor FT2 was then plotted against the measured relative concentration factor FR

for all six samples. This gave a plot similar to Figure 3-6. A linear regression ( ) was

performed and if a zero intercept was within the confidence interval a new regression was

performed with the intercept set to zero ( ). A zero intercept means that there was no

matrix effects in the assay, i.e. the buffer conditions were the same for TM and RM after

dilutions.

Figure 3-6: schematic plot of FT2 versus FR for value transfer Linear regression with intercept set to zero for dilution factors plotted against relative concentration factors. The slope is equal to the ration of target material and reference material concentrations as shown in Equation 3-5.

According to Blirup-Jensen et al [16], derivation not shown here, the slope of the line is equal

to the ratio between the target and reference material concentrations as in Equation 3-5.

Accordingly, the actual target material concentration CT was calculated by the right side of

Equation 3-5.

Equation 3-5

Where CT is the actual target material concentration, CR the reconstituted reference material concentration calculated in Equation 2-1 and β the slope from the linear regression.

1001

)(

T

RF

isampleaverageiF

XY

0

RT

R

T CCC

C

y-value: relative concentration factor, FR

x-value: Dilution factor, FT2

- MATERIALS AND METHODS -

- 31 -

A transfer factor (TF) was calculated with Equation 3-6 for transformation of results done

prior to this reference calibration. Previous results were multiplied with the TF giving the correct

concentrations.

Equation 3-6

Where CT is the actual target material concentration after value transfer and is

the previously known concentration of the target material (if applicable).

This whole procedure was performed on three consecutive days giving three linear regressions

with one slope each, giving three values on the actual target material concentration CT from

which the average target material concentration was calculated. The results for each assay are

presented in section 4.1.3 for total IgG, 4.2.3 for IgG subclass distribution and 4.3.3 for albumin.

3.2.7. Biuret, total protein concentration assay

The total protein concentration was determined with the biuret assay as described in the

European Pharmacopoeia 2.55.3 [2]. The assay involves a reaction in alkali solution between

cupric ions and peptide bonds to form a complex with absorbance at 546 nm. Preparation of the

biuret solution is described below. A protein standard containing both HSA and hIgG was used

(80mg/ml, Sigma). Two different standard curves and protocols were used depending on the

estimated samples concentration; see table x. The standard curves included 5 points in 2 times

serial dilutions. The larger volume of the standards/samples for the low calibration curve was due

to that the absorbance should be between OD 0.1-1 to be optimal in measurement.

Volume Standard

5-80 mg/ml Standard 0.5-6 mg/ml

Standard 10µl 100µl

Sample 10µl 100µl

Biuret solution 200µl 100µl

Table 3-3: Volumes used for two standard curves.

Standards and samples were added in duplicates into a flat bottom 96-well microplate. Biuret

solution was added and the microplate was incubated for 30 minutes on a shaker. The

absorbance was measured in a plate reader at 541 nm and the concentration calculated by

constructing a linear calibration curve.

Preparations of biuret solution:

3.0 g CuSO4x5 H20 + 9.0 g C4H4KNaO6x4 H20 + 5.0 g KI

Add 800 mL milli-Q water, stir until dissolved

Add 100 mL 6.0 M NaOH

Fill up to 1000 mL with milli-Q water

old

T

T

C

CTF

old

TC

- CHAPTER 3 -

- 32 -

3.2.8. SDS-PAGE

In order to calculate the specific IgG or albumin concentration with traditional methods, the

purity in percentage was estimated by SDS-PAGE and then multiplied with the total protein

concentration from biuret.

The samples were diluted with water according to Table 3-4 to get suitable amounts of protein

on the gel. To reduce the proteins prior to loading the samples were mixed with sample loading

buffer (10 µl sample + 10 μl 4X NuPAGE sample buffer with 20% β-mercapthoethanol) and

heated at 70°C for 10 minutes.

Sample concentration (µg/µl) Dilution

1-2 2x

2-9 5x

10-19 10x

20-70 50x

70-90 100x

>100 200x

Table 3-4: Sample dilutions for SDS-PAGE Simplified dilution scheme of samples in order to load an appropriate amount of protein onto the gel to avoid over-load or not having enough protein.

The gel was docked to the electrophoresis system and running buffer (NuPAGE MOPS SDS

running buffer, Invitrogen) was added. 5 μl of molecular weight marker (Precision Plus Protein

Dual Color Standard, Bio-Rad Laboratories AB) was added to the first lane and 10 μl of sample

mixture to all other lanes. The gel was run for 10 minutes with 60 V to gather the protein bands

below the wells followed by 70 minutes with 150 V. The protein bands were stained using

GelCode blue staining kit (Thermo Fisher Scientific) over night while shaking, then destained in

water for another 24 hours.

Dyed gels were scanned on an ImageScanner III using Labscan 6.0 (GE Healthcare) and

analysed in ImageQuant TL 6.0 (GE Healthcare). The peaks on each lane were identified and

cut-offs determined. The known proteins in the samples, such as IgG, albumin and transferrin,

were recognized. An example gel is shown below in Figure 3-7 with the “pixelogram” analysis of

lane 10 in Figure 3-8. From the area under the curves the relative quantity of that specific protein

was calculated in relation to the total curve area in the lane. As seen in Figure 3-8 the relative

quantity of each protein was an estimation and therefore not highly accurate. The relative

quantity was also interpreted as the purity of the proteins in the sample.

- MATERIALS AND METHODS -

- 33 -

Figure 3-7 (left): Scanned picture of a SDS-PAGE gel Lane 1 contains the molecular weight marker and lane 2 to 12 samples from different steps in the plasma fractionation process.

Figure 3-8 (right): Analysis of lane 10 from SDS-PAGE Example showing the analysis of lane 10 from the gel in Figure 3-7. Peak 5 at 70 kDa was believed to corresponds to transferrin, peak 6 and 7 at 62 and 57 kDa to albumin and finally peak 9 and 12 at 50 and 21 kDa to IgG. The relative quantity, thereby also the purity, was calculated to 51 % for albumin and 18 % for IgG in this sample.

As IgG consists of several chains linked with disulphide bonds more than one band will

appear on a reduced gel as illustrated in Figure 3-9. If detected they were added for the full IgG

composition.

Figure 3-9: IgG bands on reduced SDS-PAGE gel Due to complete or incomplete reduction of disulphide bonds in IgG up to five detectable bands occur. The highest relative quantity is that of completely reduced heavy chain at ~55 kDa and light chain at ~22 kDa.

~155

~130

~75

~55

~22

250

150

100

75

50

37

25

20

IgG kDa #1 #2 Mw kDa

Lane: 1 2 3 4 5 6 7 8 9 10 11 12

Lane 10

- CHAPTER 3 -

- 34 -

3.2.9. ELISA

Enzyme-linked immunosorbent assay, or ELISA, was used to analyse the IgG subclass

concentrations in samples to compare with the developed Biacore IgG subclass distribution

assay. Peliclass human IgG subclass kit (Sanquin) was used for the measurements. The kit

contained strips of wells, pre-coated with specific monoclonal anti-human subclass antibodies.

Six strips of eight wells existed for every subclass. For each experiment three strips for each

subclass was used giving 96 wells in total. The calibration curve had five points in duplicates, two

blanks and one control in duplicate leaving space for five samples in duplicates as illustrated in

Figure 3-10. If all six strips were used in one analysis this would leave space for 17 samples.

Figure 3-10: Illustration of human IgG subclass ELISA kit set-up. a) Calibration curve. b) Blanks. c) Control sample. Five samples in duplicates can be analysed at once.

The product protocol for the kit was followed. Due to the different abundances of the

different subclasses different ranges of standards were used. Following a dilution scheme the

calibrator was diluted to eight points, ranging from 10000 times to 1280000 times dilution. The

five most diluted were used for IgG1 and the five least diluted were used for IgG2-4, see Table

3-5.

# Dilution IgG1 IgG2 IgG3 IgG4

ng/ml ng/ml ng/ml ng/ml

1 1:10000 - 368 45 59

2 1:20000 - 184 22 29

3 1:40000 - 92 11 15

4 1:80000 81 46 6 7

5 1:160000 41 23 3 4

6 1:320000 20 - - -

7 1:640000 10 - - -

8 1:1280000 5 - - -

Table 3-5: IgG subclass concentrations in ELISA calibrator Concentrations of IgG1-4 in diluted standards for IgG1-4 in Peliclass human IgG subclass kit according to manufacturer.

a a a a a a a a

a a a a a a a a

a a a a a a a a

a a a a a a a a

a a a a a a a a

b b b b b b b b

c c c c c c c c

α-hIgG1 α-hIgG2 α-hIgG3 α-hIgG4

- MATERIALS AND METHODS -

- 35 -

Samples and control sample were diluted 240000 times for IgG1 strips and 30000 times for

IgG2-4 strips. As the kit was only intended for plasma samples and not purified IgG the purified

process samples were also prediluted 1, 2 and 4 times in order to not exceed the calibration

curve. Also the HRP-conjugated secondary antibody had individual dilutions for each IgG

subclass strip: 1:500, 1:3000, 1:2000 and 1:1000 for IgG1 to IgG4 respectively.

Wells were washed four times with wash buffer.

100 μl of calibrators, control sample and samples were added to their intended wells.

Incubated for 1 hour at 37°C.

Wells were washed four times with wash buffer.

100 μl of specifically diluted HRP-conjugated antibodies were added.

Incubated for 1 hour at 37°C.

Wells were washed four times with wash buffer.

100 μl of ABTS-substrate diluted in substrate buffer were added to all wells.

Incubated for 30 minutes at room temperature.

50 μl stop solution were added to all wells.

Plates were read in a SPECTRA Max PLUS 384 plate reader at 414 nm.

4-parameter standard curves were plotted and fitted. Individual evaluation files were created

for each IgG subclass with one standard curve each. The software calculated concentrations,

taking dilutions into consideration, giving the individual subclass concentrations for the control

sample and process samples.

- RESULTS -

- 37 -

Chapter 4

4Results

4.1. Total IgG concentration assay

4.1.1. Evaluations of reagents for total IgG concentration assay

The conditions used for the immobilization and regeneration of the antibody used was

already optimized and performed according to instructions from the manufacturer. The antibody

α-hIgG was diluted to 20 μg/ml in 10 mM sodium acetate pH 5.0 pre-concentration buffer and

injected for 6 minutes, typically resulting in an immobilization level of 10000 RU. Regeneration

was performed with 3M MgCl2 for 30 seconds according to the product protocol.

4.1.2. Assay development total IgG concentration

Initially the method to use a slope (RU/s) instead of the relative response (RU) as a measure

of the signal was evaluated. Due to bulk effects from high protein concentrations (e.g. when

detecting IgG losses in discarded samples with high albumin level) and variable NaCl levels this

approach was not suitable for the assay. In order to keep the analysis time to a minimum, the

injection time was kept to only 20 seconds. Owing to the great performance of the monoclonal

anti-human IgG antibody it was possible to use a master standard curve for at least one week of

measurements with over 1000 process samples. After samples analysis the result-file was

appended in the evaluation software with a result-file containing the standard curve, it required to

be with the same method and from the same chip, flow-cell and immobilization.

- CHAPTER 4 -

- 38 -

At least one start-up cycle was necessary to condition the surface for the analysis, especially if

a master standard curve from a prior measurement was used. One or two control samples were

evenly distributed during the analysis. For example one with a high concentration and one with a

low concentration on the standard curve.

4.1.2.1. Standard curve

The standard curve was set to start at 50 μg/ml with six 2.5-fold dilutions to approximately

0.5 μg/ml. The lower point was chosen to get a high sensitivity of the assay and the higher point

to avoid the antibodies to be saturated and thereby reducing the resolution on the standard curve

for higher concentrations, as discussed in 3.2.4. The samples were then diluted to fit on the

standard curve and at the same time eliminate pH, buffer and NaCl effects by dilution. The

standard curve for IgG can be seen in Figure 4-6.

4.1.2.2. Sample preparations

Samples were first diluted using a dilution factor based on the estimated concentration,

followed by two two-fold dilutions to increase the number of measurement points and to ensure

the sample concentrations fall within the standard curve. Samples expected to contain IgG were

diluted 200 times, samples close to the final product with estimated concentrations above 10

mg/ml were diluted 1000 times and samples expected not to contain IgG were diluted at a

minimum 10 times to detect losses and to avoid pH, buffer and NaCl effects. The effect of

dilution on samples with a high (500 mM) and low (0 mM) NaCl level is exemplified in Table 4-1

concluding that the critical samples containing IgG with dilutions above 200 times were

completely diminished from NaCl effects.

Dilutions in 150 mM NaCl (HBS-EP+)

Sample 10X 20X 40X 200X 400X 800X

500 mM NaCl 185 167 159 152 151 150

0 mM NaCl 135 142 146 150 150 150

Table 4-1: Calculated NaCl levels in diluted samples Dilutions of samples with high and low NaCl level into HBS-EP+ with 150 mM NaCl. Samples diluted 10 and 20 times have a moderately increased or decreased level from optimal which might give a positive or negative bulk, as described in section 2.3. Although for samples diluted 200 times and more all effects are diminished, these are also the sample with the most critical concentrations.

- RESULTS -

- 39 -

4.1.2.3. Assay procedure

Immobilization of 20 μg/ml α-hIgG for 6 minutes resulted in approximately 10000 RU ligand.

After conditioning start-up cycles the calibrant was injected in increasing concentrations, if a

master standard curve was not employed. Thereafter samples with increasing concentrations

within the three dilutions were injected in duplicates. Also evenly distributed control-samples

were injected. Regeneration was performed with 30 second injection of 3M MgCl2 after each

cycle. When evaluating the results one dilution giving either a too low concentration or a too high

concentration on the standard curve was excluded giving four determinations for each sample

(n=4). For samples without expected IgG, i.e. 10 times diluted samples, if possible the two most

diluted samples were chosen to avoid buffer, pH and NaCl effects. F