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CHAPTER 1

PERSPECTIVE AND LACUNAE

The inimitable properties of biosensors such as high target specificity and high sensitivity,

imparted by biological recognition systems, has led to their wider acceptability and

commercialization threatening the existing sensors market. Biosensor industry is a global

industry having potential application in varied fields, such as medical diagnostics [1],

fermentation [2], pharmaceutical, drug [3], food and beverage industry [4-6]. Additional areas

of biosensor application that still lie dormant include agricultural, environment, mining

industry and veterinary investigation. Global market research report by Global Industry

Analysts, Inc. indicates that presently United States is globally dominating the biosensor

market followed by Europe while Asia-Pacific is expected to emerge as the fastest growing

market for biosensors by 2017, with the worldwide Biosensors market expected to reach 12

billion US$ by the year 2015. Currently, about 90% of the universal biosensors market is

seized by glucose biosensor.

Increasing health-related concerns or diabetic population is the major driving force

behind growth of glucose biosensors in clinical diagnostic sector. However, low thermal

stability and large response time are two of the major factors behind the untapped market of

glucose biosensors other than health sector. Low thermal stability of enzymes leads to fast

decline in activity of enzyme and hence poor biosensor efficiency, resulting in overall cost

escalation leading to a reduced commercial viability. Large response time of currently

available membrane or hydrogel based glucose biosensor [7, 8] compromises the product

quality and reproducibility. Thus the above mentioned two factors - the large response time

and instability of biomolecule, are the key reasons limiting the application of current day

biosensor in industries such as food, beverage and fermentation where continuous monitoring

of glucose is of paramount importance in order to ensure the quality of product. The fusion of

current day biosensor technology with nanotechnology is acting as a market propeller in this

area. Nano sized structures of gold [9], nickel [10], platinum [11], silica [12], carbon [13] etc.

have revolutionized the biosensor research by reducing the response time to 2-10 seconds and

sensitivities ranging from 5μA mM−1

cm−2

to as high as 112μA mM−1

cm−2

[14]. However,

increasing sensitivities generally results in reduced linear range and the reported high

sensitivity biosensors suffer from low operational stability (short shelf life). Hence it is

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imperative to devise alternative nanomaterials and strategies targeting both thermal and

operational stability and sensitivity at the same time.

1.1 Need for Industrial Glucose Biosensor

The constant on-line estimation of different saccharides in industries like food, beverage and

fermentation is of paramount importance for ensuring the quality of products. Glucose is used

as the main carbon and energy source for the microbial growth and also acts as growth

limiting substrate in industrial fermentations. Generally, glucose concentration ranges from 0

g/L to 15 g/L (0 mM - 20 mM) in different fermentation processes. Variations in glucose

levels from the desired concentrations, affect the yield, quality and reproducibility of the

product, hence continuous monitoring of glucose concentration becomes crucial. Until

recently, sugar monitoring was limited to external sampling techniques such as

dinitrosalicylic acid (DNS) method. The external sampling techniques suffered from two

major drawbacks – one increased susceptibility to contamination, as the microorganisms were

not removed and often the sampling stream was recirculated into the fermenter and secondly,

depletion of the medium volume due to numerous sampling at regular intervals. These

conventional methods were overshadowed by on-line rapid screening using analytical

chromatographic techniques like HPLC (High Pressure Liquid Chromatography) and GC

(Gas Chromatography). However, these are sophisticated, expensive instruments and require

sample pre-preparation and trained manpower for operating the instrument. In order to

circumvent the identified drawbacks of the conventional and analytical techniques, biosensors

were proposed as convenient in situ sensing tools requiring no trained manpower and are cost

effective as well.

1.2 What is a Biosensor?

Biosensor can be considered as a sensor or a sensing device employing biological or

biologically-derived sensing element for sensing the analyte(s) of interest. These biological

elements or bioreceptors (enzyme, antibody, nucleic acid, microorganism or cell) are

integrated with or within a transducer to convert chemical or physical signal (arising from

interaction of analyte with biological element) into electrical signal that is amplified and

displayed as discrete or continuous digital signal. Schematic representation of a biosensor is

shown in Figure 1.1

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Biosensors are classified according to the transducer used and the type of biomolecule. Four

major classes of biosensors, depending on the transducer type are electrochemical

(amperometric, potentiometric and Conductometric/Impedimetric); optical; mass-sensitive

(piezoelectric) and thermal (calorimetric) biosensors. The preference of the transducer is

invariably dependent on the biological element involved for the progression of biological

reaction and the accompanied physical/chemical changes. Enzymatic reactions are generally

monitored through electrochemical or thermal transducers, where as the mass-sensitive

devices usually detect affinity based reactions (DNA hybridization or antigen-antibody

reactions). Biosensors are also described in terms of biological sensing element - enzymatic

biosensor (enzyme), immunobiosensor (antibody or antigen), DNA biosensor (DNA) and

microbial sensor (microbial cells or organelles).

1.3 Desirable Characteristics of a Biosensor

Biosensor performance and efficiency is evaluated in terms of well defined technical and

functional characteristics according to guidelines laid down by IUPAC. These desirable

characteristics for any medical or industrial biosensor are:

Figure 1.1: Schematic representation of a biosensor.

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1.3.1 Selectivity

Selectivity of a biosensor can be defined as the specificity of the sensing electrode towards

single analyte or to avoid false results caused by interfering species. Two major factors which

determines the selectivity of the sensing electrode includes the type of biomolecule and

transducer. Enzymes and antibodies are generally specific for single analyte and have been

widely used for development of biosensors, while biomolecules such as microorganisms, are

known to be highly non-specific and are comparatively less exploited. Biosensor response

could either be enhanced or reduced in the presence of interfering species. Enhanced

interference is recorded when the interfering species shares structural and chemical similarity

with the substrate and are recognized by biocatalyst. On the contrary, if the interfering species

shows inhibitive effects towards the immobilized biocatalyst a drastic reduction in response of

the sensing electrode is observed.

1.3.2 Sensitivity

Sensitivity of the sensing electrode can be defined by the slope of the calibration curve or the

rate of change of response function with analyte concentration [15]. It is further quantified as

the ability of sensing electrode to reliably measure less than 1% fluctuation in concentration.

For accurate results sensitivity is always calculated over the linear portion of calibration

curve.

1.3.3 Detection Limit

Detection limit of the biosensor is the lowest value of the analyte concentration that can be

measured accurately by sensing electrode with an acceptable signal to noise (S/N) ratio. Low

signal to noise ratio puts a limit on the lower detection limit though a high sensitivity can be

achieved.

1.3.4 Response Time

Response time is one of the vital parameters for taking any biosensor from lab to industrial

level. It can be categorized into two types: Steady state response time which can be defined as

the time required for response signal to reach 95% of the steady state value [16] whereas the

transient response time is the time required for the derivative of the response signal to reach

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its maximum value after the addition of the substrate. Desirably, the response time of

biosensor should be as low as possible.

Following factors influence the response time of a biosensor:

Thickness and permeability of the membrane used for biocatalyst immobilization.

Agitation rate of the analyzing mixture.

Concentration of the substrate.

Temperature of the sample.

Amount of immobilized biocatalyst or its activity.

Geometry of the electrode surface.

Material of the electrode.

Multi-enzyme systems where serial enzyme reactions results in large response time.

1.3.5 Recovery Time

Recovery time is defined as the minimum time required between two successive

measurements. The baseline potential can be achieved with sufficient washing of the electrode

after every measurement by removing the accumulated unreacted substrate and formed

product from the membrane.

Factors influencing recovery time of the biosensor:

High concentration of substrate.

Thickness and permeability of the membrane on which biocatalyst is immobilized.

Nature of the biocatalyst.

1.3.6 Ruggedness

Ruggedness is defined as the ability of the biosensor to withstand any minor physical or

electrical variation i.e., no calibrations drift.

1.3.7 Reproducibility

The reliability of the biosensor is highly dependent on reproducibility or repeatability of the

results. It is defined as the ability of an instrument to give the same output for equal inputs

applied over some period of time. Signal baseline drift and/or sensitivity drift is the primary

limit on reproducibility.

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1.3.8 Storage and Operational Stability

Commercial worth of a biosensor is dictated by its stability in addition to other factors like

high sensitivity or selectivity. The stability of biosensor is evaluated in terms of operational

stability and storage stability.

The operational stability of biosensor is governed by:

Method of biocatalyst immobilization.

Operational conditions of the biosensor like pH, temperature, presence of organic

solvents, etc. of the analyzing mixture.

Binding force between biomolecule and electrode surface.

Whereas the storage stability depends on the factors like

Temperature of storage.

Composition of buffer used for storage.

pH of the buffer.

State of storage (wet or dry).

1.3.9 Lifetime of a Biosensor

According to IUPAC [17], lifetime of biosensor (tL) can be defined as the storage or

operational time necessary for the sensitivity, within the linear concentration range, to

decrease by a factor of 10% (tL10) or in certain cases 50% (tL50). Lifetime of any biosensor is

highly dependent on its frequency of usage. Higher frequency of usage results in lowering the

lifetime of biosensor. In general reduction in the slope of calibration curve of an enzymatic

biosensor varies between 60 to 120 days. However, according to IUPAC [17], electrode can

be used till the accuracy of the measured signal and linearity of the system is maintained, but

it is highly recommended to perform daily calibration of the system. The increased usage,

results in loss of activity of enzyme and hence reduced lifetime.

1.4 Lacunae in Current State-of-Art

Above discussed lacunae in current state-of-art can be grouped into two major categories: one

being large response time, low sensitivity and narrow linear range of the existing biosensors;

while the other is low thermal and operational stability resulting in short shelf-life of the

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biosensor (see Figure 1.2). All these aspects need to be addressed together to achieve efficient

biosensor performance.

The large response time response time of the membrane based biosensors can be explained in

terms of the diffusion controlled steps - 1) analyte movement from bulk to enzyme active site

and 2) electron (via mediator or mediatorless) transfer from enzyme active site(redox centre)

to the electrode surface (see Figure 1.3). When a solid body (here a biosensor) is immersed in

a stirred bioreactor (fluid in motion) a boundary layer is formed around the stationary body

where the velocity of fluid is negligible. A fast convective transfer of analyte in the bulk

region ensures homogeneity of the fluid. The transfer of analyte (to be monitored) from bulk

to the electrode is governed by diffusion controlled process in the region of boundary layer

surrounding the membrane of the electrode where fluid velocity is negligible (see DL1 in

Figure 1.3). The physical/chemical change due to analyte interaction with biomolecule is

recorded through diffusion of one of the substrate/(by)product or mediator assisted electron

transfer from enzyme redox center to the electrode surface (see DL2 in Figure 1.3). Both these

diffusion limited processes DL1 and DL2 are responsible for the large response time since

diffusion is a slow process. To reduce the response time thickness of the membrane can be

reduced thereby reducing the thickness of boundary layer and hence the response time.

However, efforts in this direction led to the reduction in response time that was not

substantial. To overcome this problem, we have exploited nanotechnology. As seen in Figure

1.3, the usage of nanoparticles (NPs) reduces the size of the boundary layer or liquid film to

Figure 1.2 Lacunae of existing biosensors responsible for their dormancy

in fermentation and other industries

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nanolengthscale (smaller DL1) and since NPs would be either covalently or electrostatically

immobilized onto electrode surface DL2 would be negligible. Diffusion over such small

lengthscales

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targeted goals, nanomaterials of different morphologies exhibiting unique physical and

chemical properties have been exploited. Thesis is structured as, Perspectives and Lacunae

(chapter 1), Review of Literature (chapter 2), Characterization Techniques (chapter 3)

followed by work done presented in the subsequent chapters as controlled synthesis

nanostructures of specific morphologies (chapter 4) and applications of the same for enzyme

immobilization and biosensor fabrication (chapter 5-7). Chapter 8 describes a unified

approach of nanobiotechnology detailing a novel process to synthesize thermostable enzyme

nanoparticles. Design of study is presented in Figure 1.4.

Chapter 1 presents perspective of the proposed work and identified lacunae of the existing

biosensors. This is followed by Review of Literature on glucose biosensors in Chapter 2

discussing the historical perspectives of glucose sensing devices as first-, second- and third-

generation biosensors and their limitations. A detailed survey of technological advancements

in the field describing characteristics like sensitivity, lower detection limit, response time,

linear dynamic range, stability and the material used for immobilization of enzyme has been

presented. In addition to this, we have tried to comprehend the vast gap between limited

numbers of technology transfers in comparison to large numbers of published papers. The

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extensive analysis yielded stability of immobilized enzymes as the crucial lacunae behind the

slow pace of commercialization.

Performance characteristics of fabricated biosensor are controlled by achieving an

understanding and control over the distinctive properties of the materials used. To accomplish

the same physical and chemical characterization of materials used in addition to response

characteristics of biosensor after each modification step becomes pertinent. Current biosensor

technology exploits nanostructures and their varied optical, electronic, magnetic and other

properties for enhancing performance and efficiency. Morphological characterization of these

nanostructures is of paramount importance since their properties vary drastically with their

size and shape. Microscopic techniques like Transmission electron microscopy (TEM),

scanning electron microscopy (SEM) and optical microscopy (OM) are exploited for

morphological analysis. Moreover, chemical and electrochemical characterization of the

nanostructures and biosensors, in the present work, is done through spectroscopic techniques

(UV-Visible spectroscopy, energy dispersive X-ray spectroscopy, electrochemical impedance

spectroscopy), zeta potential analysis and cyclic voltammetry. Chapter 3 gives a brief

description of these characterization techniques.

Chapter 4 describes optimization of synthesis protocols to achieve monodispersed

nanostructures. The pioneering method of Turkevich et. al.[18] for synthesis of gold

nanoparticles using chloroauric acid as precursor and trisodium citrate as reducing agent has

been exploited for exploring effect of various parameters on morphology and size of

nanoparticles synthesis. Effect of parameters like concentration of precursor, reducing agent,

reducing agent/precursor ratio and rate of addition of reducing agent has been studied. Based

on the above studies and analysis thereof, we have proposed probable mechanism for

controlled synthesis of charged gold nanochains and/or monodispersed spherical

nanoparticles.

The major concern of conventional methods is usage of toxic chemicals. Although most of

these conventional methods are simple in implementation, however, high cost and hazardous

environmental impact due to usage of organic solvents necessitates the need for alternative

eco-friendly route. Spherical and anisotropic gold and silver nanostructures are synthesized

via conventional and eco-friendly routes using trisodium citrate and amino acids respectively

as reducing agents [19]. Furthermore, we have explored the effect of choice of amino acids,

pH of the solution on synthesis of varied shape nanostructures. Finally, probable mechanism

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controlling the morphology of nanostructures following eco-friendly route has also been

proposed.

In addition to optimization of controlled synthesis of gold and silver nanostructures we have

also synthesized magnetite nanoparticles following the method of co-precipitation by Zhu et.

al. [20]. The reason being magnetite nanoparticles are being extensively explored in

applications like drug delivery, biological imaging etc and their high biocompatibility. We

have included magnetite nanoparticles in our study to compare the biocompatibility and

response characteristics of biosensor using these with that of synthesized gold nanoparticles.

Biosensing efficiency of these synthesized nanostructures has been evaluated in the next four

chapters, i.e., Chapter 5-8. The efficiency of a biosensor, i.e., the sensitivity, stability and

response time, is very much subjected to the kind of support material used and the method of

immobilization. The most suitable support material and immobilization method vary

depending on the enzyme and particular application. Key parameters for selection of suitable

material and method are binding capacity of the material, stability, retention of enzyme

activity and minimizing leakage of enzyme after immobilization on the material.

Recent advances in material development have led to better understanding and design of

proper material surface to immobilize the enzyme. Advances in mesoporous and

nanomaterials have brought opportunities for materials scientist to improve the enzyme

loading capacities in order to develop an efficient enzyme based sensor [21-23]. Most of the

reported literature on immobilization method or matrix is compared with free enzyme

response only. However, a comparative study and analysis of different methods, matrices,

design and loading capacity of enzyme is rarely reported in a set of experiment or at a

laboratory to enable suitable choice of methods and materials for biosensor fabrication.

In chapter 5, we have presented a comparative study of immobilization techniques and

materials for fabrication of glucose biosensor. Conventional matrices (calcium alginate beads,

polyacrylamide gel) and membranes (NC and PVDF) have been compared with current-day

nano- sized materials (gold and magnetite nanoparticles) for optimum enzyme

immobilization. In addition to this, immobilization methods – electrostatic, covalent, physical

adsorption and entrapment based methods have also been evaluated for their effect on

immobilization efficiency (leakage of enzyme, retention of activity and thermal stability)

Comparative analysis demonstrates covalently bound enzyme onto nanomaterials to be the

most suitable method and matrix for enzyme immobilization. The characteristic compatible

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curvature and nanoelectrode behavior of nanomaterials were further exploited for enhancing

biosensing capabilities of glucose biosensor. The present comparative analysis may serve as a

set of design criteria to help engineers fabricate an efficient biosensor.

As discussed above, nanomaterials were found to be more suitable matrices for enzyme

immobilization and biosensor fabrication yielding improved biosensor characteristics as

compared to conventional matrices. In Chapter 6, efforts have been directed towards further

enhancement of biosensing capabilities. This has been achieved through modulation of the

electron transfer properties of gold nanoparticles by inducing coupling amongst the particles.

Gold nanoparticles attached in the form of a chain are synthesized using different amino acid,

as a reducing and capping agent (as discussed in chapter 4). Usage of the above amino acid

facilitates the coupling among the particles (the chain like arrangement of particles). The

glucose biosensor developed by immobilization of glucose oxidase enzyme onto amino

functionalized chain like coupled gold nanoparticles showed much more enhanced sensitivity

and excellent operational stability in comparison to biosensors fabricated using spherical gold

nanoparticles. The probable mechanism responsible for enhancement in biosensor

characteristics has also been proposed [19].

In chapter 6, we have presented a benign strategy to synthesize gold nanochains by self-

assembly of individual gold nanoparticles. However, controlling the chain length was once

again major challenge. Template based synthesis is one of the most popular approach for

synthesis of controlled length scales of metallic nanostructures [24, 25]. Removal of the

template in order to obtain pure metallic structures is the major limitation of this approach.

Hence it is pertinent to explore more eco-friendly route for synthesis of 1D

micro/nanostructures. In Chapter 7 we have exploited unique microbial cell architectures as

biotemplates for desired size and morphology. This chapter is dedicated to bio-inspired gold

microwires (AuMWs) synthesis, their evaluation as potential microelectrodes for electron

transfer between enzyme and electrode surface, in amperometric biosensing applications. To

the finest of our knowledge, these bio-inspired gold microwires for the development of

amperometric glucose biosensors have not been explored so far. Three different fungal

species, having different nutritional characteristics, have been used to understand whether

gold microwires synthesis is solely adsorption based or nutritional driven or both. Our work is

aimed at understanding the mechanism of synthesis of these functional microstructures of

gold and exploring their potential use for efficient biosensor fabrication.

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In all the previous chapters, we have exploited nanotechnology for biotechnological

application, i.e., biosensor fabrication by immobilization of enzyme on nanostructures. In

Chapter 8, we have done hybridization of the two fields and in true sense an example of

nanobiotechnology is presented in the form of nanoparticles of enzyme itself. Major driving

force behind present work being improving shelf life of enzyme based electrodes due to the

major challenge posed by fragile nature of enzymes. Long shelf life of biosensor in particular

and any product in general, is of paramount importance for commercialization. Hence, it is

imperative to develop methods to enhance the stability of enzymes. Synthesis of

nanoparticles of enzymes has been able to achieve the desired aim. We report a novel process

to synthesize nanoparticles of enzymes in general and results for two enzymes Glucose

oxidase (GOx) and Horse radish peroxidase (HRP) are presented. Optimized synthesis of the

enzyme nanoparticles has been achieved by controlling the major governing factors such as,

concentrations of desolvating and crosslinking agent and suitable choice of functionalizing

agent. The synthesized enzyme nanoparticles exhibit improved thermal stability and

biocatalytic activity over a wide range of temperature relative to free enzyme in solution or

immobilized over conventional or nanoparticles based matrices.