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3 l IBRARY
83:0 Michigan State
UnWemmy

 

 

This is to certify that the
dissertation entitled

ELECTRICALLY-ACTIVE POLYANILINE COATED
MAGNETIC NANOPARTICLES: A NOVEL CONCENTRATOR
AND NANOSTRUCTURED TRANSDUCER IN BIOSENSOR
DEVICES

presented by

SUDESHNA PAL

has been accepted towards fulfillment
of the requirements for the

PhD. degree in Biosystems Engineering

 

 

 

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ELECTRICALLY-ACTIVE POLYANILINE COATED MAGNETIC
NANOPARTICLES: A NOVEL CONCENTRATOR AND
NANOSTRUCTURED TRANSDUCER IN BIOSENSOR DEVICES
By

Sudeshna Pal

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Biosystems Engineering

2009

ABSTRACT
ELECTRICALLY-ACTIVE POLYANILINE COATED MAGNETIC
NANOPARTICES: A NOVEL CONCENTRATOR AND NANOSTRUCTURED
TRANSDUCER IN BIOSENSOR DEVICES
By

Sudeshna Pal

Nanomaterial based biosensors are emerging as sensitive, Specific, efficient and
rapid diagnostic tools for the detection of pathogenic microorganisms in biodefense and
diagnostics. This research demonstrates the novel application of a nanostructured
material in the dual function of a magnetic concentrator and a transducer in biosensor
devices. The nanostructured materials are synthesized from aniline monomer made
electrically active by acid doping coating the surface of gamma iron oxide cores. The
synthesized electrically active polyaniline coated magnetic (EAPM) nanoparticles are
adapted in antibody based and DNA based biosensors for the detection of Bacillus
anthracis as a model pathogen. The antibody based detection involves immunomagnetic
concentration of targets using biologically modified EAPM nanoparticles followed by

their direct application to a charge transfer biosensor. Experimental results indicate that
the biosensor is able to detect B. anthracis spores at concentrations as low as 4.2 X 102

spores per ml in 16 min. The DNA based detection mechanism encompasses sandwiched
hybridization of DNA targets onto probe labeled EAPM nanoparticles which is
succeeded by electrochemical detection of the EAPM DNA hybrids on screen printed
carbon electrodes. The sensitivity of the DNA biosensor is assessed to be 0.01ng/ul of

PCR amplified B. anthracis pag A gene fragment in a total detection time of 60 min.

To my parents and my husband, Tuhin

iii

ACKNOWLEDGMENTS

I sincerely thank everyone who contributed to the completion of this research. I
express my deepest gratitude to Dr. Evangelyn Alocilja for being more than an advisor to
me. I am grateful for her guidance, time, encouragement and appreciation for even the
smallest achievements, and her prayers during my graduate program. I am thankful to the
members of my Ph.D. guidance committee: Dr. David Tomanek, Dr. Shantanu
Chakrabartty, Dr. Daniel Guyer and Dr. Frances Downes for their suggestion and
support.

I thank all past and present members of the Biosensors research group (Deng, Edith,
Emma, Finny, Maria, Lisa, Michelle, Michael, Shannon, Srini, Yang, Yilun and Zarini)
for sharing a pleasant work place. A special thank you to Ms. Edith Torres Chavolla for
her guidance in molecular biology and for the help she extended to me. I am also thankful
to Ms. Hanna Miller and all the other undergraduate assistants who have worked with me
over the past few years.

I owe my gratitude to my parents and my sisters for the unconditional love they have
showered upon me throughout the years. Their unceasing support and concern for me will
always be my strength.

Last but not the least; I would like to express my heartfelt gratitude to my husband
for being my friend, philosopher, and guide in our wonderful journey together. Thank

you very much for your love and support!!

Sudeshna Pal

iv

TABLE OF CONTENTS

 

 

 

 

List of Tables ix
List of Figures xii
Chapter 1: INTRODUCTION 1
Chapter 2: LITERATURE REVIEW 4
2.1 Bacillus anthracis and Anthrax ........................................................................... 4
2.1.1 Virulence of Anthrax .............................................................................. 4

2.1.2 Routes of Infection .................................................................................. 6

2.1.3 Anthrax and Biosecurity ......................................................................... 7

2.1.4 Traditional Identification Methods ......................................................... 8

2. 2 Biosensors in Pathogen Detection ..................................................................... 10
2.2.1 Introduction ........................................................................................... 10

2.2.2 Biosensor Transducing Mechanisms .................................................... 12

2.2.2.1 Mechanical biosensors .................................................................... 12

2.2.2.2 Optical biosensors ........................................................................... 17

2.2.2.3 Electrochemical biosensors ............................................................ 21

2.2.2.4 Magnetic biosensors ....................................................................... 25

2.2.3 Biological Sensing Elements ................................................................ 27

2. 3 NanoBiosensors and Nanostructured Transducers ........................................... 30
2.3.1 Nanowire Based Biosensors ................................................................. 30

2.3.1.1 Silicon nanowires ............................................................................ 31

2.3.1.2 Conducting poymer nanowires ....................................................... 32

2.3.2 Nanotube Based Biosensors .................................................................. 34

2.3.2.1 Carbon nanotubes ........................................................................... 34

2.3.2.2 Conducting poymer nanotubes ....................................................... 36

2.3.3 NanOparticle Based Biosensors ............................................................. 37

2.3.3.1 Magnetic nanoparticles ................................................................... 37

2.3.3.2 Gold nanoparticles .......................................................................... 39

2.3.3.3 Semiconductor nanoparticles .......................................................... 42

2.3.3.4 Silica nanoparticles ......................................................................... 44

2.3.4 Nanoporous Material Based Biosensors ............................................... 46

2.3.5 Nanorod and Nanosphere Based Biosensors ........................................ 47

2. 4 Polyaniline — A Conducting Polymer ................................................................ 49
2.4.1 Introduction ........................................................................................... 49

2.4.2 Structural and Electrical Properties ...................................................... 51

2.4.2.1 Oxidation states .............................................................................. 52

2.4.2.2 Electronic conduction ..................................................................... 54

2.4.3 Electrochemistry and Redox Switching ................................................ 58

 

 

2.4.3.1 Cyclic voltammetry ........................................................................ 61

2.4.4 Electrically-Active Magnetic Polyaniline ............................................. 63
2.4.5 Polyaniline in Biosensor Applications .................................................. 67
Chapter 3: RESEARCH HIGHLIGHTS 70
3.1 Research Novelty ............................................................................................... 70
3.2 Research Significance ........................................................................................ 72
3.3 Hypothesis .......................................................................................................... 73
3.4 Research Objectives ........................................................................................... 73
Chapter 4: RESEARCH MATERIALS AND METHODS - - 74
4.] Objective 1 ......................................................................................................... 74
4.1.1 EAPM Nanoparticle Synthesis ............................................................. 74
4.1.2 EAPM Nanoparticle Characterization .................................................. 75
4.1.2.1 Magnetic characterization ............................................................... 75
4.1.2.2 Electrical characterization .............................................................. 75

4.1.2.3 Structural characterization .............................................................. 76
4.1.2.4 Spectral analysis ............................................................................. 76

4.2 Objective 2 ......................................................................................................... 77
4.2.1 Biosensor Design and Data Collection ................................................. 77
4.2.2 EAPM Based Immunosensor Fabrication ............................................. 79
4.2.2.1 Chemicals and reagents .................................................................. 79
4.2.2.2 EAPM antibody modification ......................................................... 79

4.2.2.3 Biosensor capture pad functionalization ......................................... 80
4.2.2.4 Application and absorption pad preparation ................................... 81

4.2.2.5 Sensor assembly .............................................................................. 81
4.2.2.6 Antibody attachment confirmation studies ..................................... 82

4.3 Objective 3 ......................................................................................................... 82
4.3.1 Bacterial Culture and Plating ................................................................ 83
4.3.1.1 B. anthracis sporulation protocol ................................................... 83

4.3.2 Immunomagnetic Concentration Using EAPM NPs ............................ 84
4.3.3 Biosensor Testing .................................................................................. 85
4.3.4 Biosensor Sensitivity Study .................................................................. 85
4.3.5 Biosensor Specificty Analysis .............................................................. 86
4.3.6 Biosensor Testing in Food Matrices ..................................................... 86
4.3.7 Statistical Analysis ................................................................................ 87
4.3.8 Confirmation and EAPM Capture Efficiency Calculations .................. 87

4. 4 Objective 4 ......................................................................................................... 88
4.4.1 Biosensor Design and Data Collection ................................................. 88
4.4.2 Chemicals and Reagents ....................................................................... 89
4.4.3 Selection and Analysis of DNA Primers and Probes ............................ 90
4.4.4 Extraction, Amplification and Characterization of B. anthracis DNA. 90
4.4.4.1 DNA extraction ............................................................................... 90
4.4.4.2 Polymerase chain reaction (PCR) amplification and Optimization. 92
4.4.4.3 PCR product purification ................................................................ 92

Vi

4.4.4.4 PCR product characterization ......................................................... 93

 

4.4.5 EAPM-DNA Probe Labeling Study ...................................................... 93
4.4.5.1 EAPM-DNA modification .............................................................. 93
4.4.5.2 Confirmation and optimization ....................................................... 94

4.4.6 SPCE Surface Modification .................................................................. 95

4.5 Objective 5 ......................................................................................................... 95

4.5.1 Sandwiched Hybridization of DNA Targets on EAPM NPs ................ 95
4.5.1.1 Sandwiched hybridization protocol ................................................ 95
4.5.1.2 Optimization of hybridization conditions and confirmation .......... 96

4.5.2 Electrochemical Detection Using SPCE Biosensor .............................. 97
4.5.2.1 Electrochemical Characterization of EAPM NPS ........................... 97
4.5.2.2 Detection of EAPM-Target-Biotin Hybrids ................................... 97

4.5.3 SPCE Biosensor Sensitivity Study ........................................................ 98

4.5.4 Statistical Analysis ................................................................................ 98

4.5.5 Specificity Analysis .............................................................................. 99

Chapter 5: RESULTS AND DISCUSSION 100
5.1 Objective 1 ....................................................................................................... 100
5.1.1 EAPM Nanoparticle Characterization ................................................ 100

5.2 Objective 2 ....................................................................................................... 112

5.2.1 EAPM Based Immunosensor Fabrication ........................................... 112
5.2.1.1 Confirming EAPM antibody modification ................................... 112
5.2.1.2 Confirming biosensor capture pad functionalization .................... 113

5.2.2 EAPM Based Immunosensor Detection Concept ............................... 116
5.2.2.1 Validation of detection concept .................................................... 118

5.3 Objective 3 ....................................................................................................... 122

5.3.1 Immunosensor Performances Using Different EAPM Types ............. 122

5.3.2 Immunosensor Sensitivity Study ........................................................ 125

5.3.3 Immunosensor Specificity Analysis ................................................... 128

5.3.4 Immunosensor Testing in Food Matrices ........................................... 131

5.3.5 Confirmation and EAPM Capture Efficiency Determination ............. 134

5.4 Objective 4 ....................................................................................................... 138

5.4.] Selection and Analysis of DNA Primers and Probes .......................... 138

5.4.2 Extraction, Amplification and Characterization of B. anthracis DNA138

5.4.3 Confirming EAPM-DNA Probe Modification .................................... 141

5.4.4 EAPM Based Electrochemical DNA Biosensor Detection Concept .. 143

5.5 Objective 5 ....................................................................................................... 145

5.5.1 Sandwiched Hybridization of DNA Targets on EAPM NPS ............. 145
5.5.1.1 Determination of hybridization conditions ................................... 145
5.2.1.2 Confirming sandwiched hybridization on EAPM NPS ................. 147

5.5.2 Electrochemical Detection Using SPCE Biosensor ............................ 149
5.5.2.1 Electrochemical characterization of EAPM NPS .......................... 149
5.5.2.2 Electrochemical detection of EAPM-Target-Biotin DNA hybrid 153

5.5.3 SPCE Biosensor Sensitivity Study ...................................................... 155

5.5.4 Specificity Analysis ............................................................................ 160

vii

Chapter 6: CONCLUSION AND FUTURE RESEARCH - -_ 162

 

 

 

Appendix A: STATISTICAL ANALYSIS RESULTS 165
A. I Anova Analysis of Different EAPM Based Immunosensors ............................. 165
A. 2 Anova Analyszs for Immunosensor Sensitivity ................................................. 168
A3 Anova Analysis for Immunosensor Specificity ................................................. I 70
A4 Anova Analysis for Lettuce Testing .................................................................. 1 71
A5 Anova Analysis for Ground Beef Testing ......................................................... 1 73
A6 Anova Analysis for Whole Milk Testing ........................................................... 175
A. 7 Anova Analysis for SPCE Biosensor Sensitivity .............................................. 1 77
Appendix B: DATA - 179
REFERENCES 183

 

viii

LIST OF TABLES

Table 2-1. Chemical structure and conductivity of typical conducting polymers (Adapted

and modified from Rahman et al., 2008). ....................................................... 50
Table 2-2. Review of electrically-active magnetic polyaniline nanostructures. ............... 66
Table 3-1. Novelty of research as compared to existing literature. .................................. 71
Table 4-1. Dimensions of the EAPM based immunosensor. ............................................ 79
Table 4-2. Sequence information of B. anthracis primer pairs and probes. ..................... 91
Table 5-1. Magnetic parameters measured for the EAPM NPs ...................................... 102
Table 5-2. Conductivity values measured for the EAPM NPS. ...................................... 104

Table 5-3. Capture efficiency (CE) of immno-EAPMS in pure spore suspensions of B.
anthracis.estimated from plate count data .................................................... 136

Table 5-4. Capture efficiency (CE) of immuno-EAPMS in romaine lettuce, whole milk,
and ground beef contaminated with B. anthracis spores estimated from plate

count data ...................................................................................................... 137
Table 5-5. Optimum concentration of PCR components. ............................................... 139
Table 6-1. Specifications of EAPM based biosensors. ................................................... 164

Table A-1. Type 3 tests of fixed effects (Anova analysis of different EAPM based
immunosensors) ........................................................................................... 165

Table A-2. Tests of effect slices (Anova analysis of different EAPM based
immunosensors) ........................................................................................... 165

Table A-3. Estimates (Anova analysis of different EAPM based immunosensors) ....... 166

Table A-4. Least squares means (Anova analysis of different EAPM based
immunosensors) ........................................................................................... 1 66

ix

Table A-5. Differences of least squares means (Anova analysis of different EAPM based

immunosensors) ........................................................................................... l 67

Table A-6. Type 3 tests of fixed effects (Anova analysis for immunosensor sensitivity)

..................................................................................................................... 168
Table A-7. Estimates (Anova analysis for immunosensor sensitivity) ........................... 168
Table A-8. Least squares means (Anova analysis for immunosensor sensitivity) ......... 168
Table A-9. Differences of least squares means (Anova analysis for immunosensor

sensitivity) ................................................................................................... 1 69

Table A-10.

Table A-1 1.

Table A-12.

Table A-13.

Table A-l4.

Table A-15.

Table A—16.

Table A-17.

Table A-18.

Table A-19.

Table A-20.

Table A-21.

Type 3 tests of fixed effects (Anova analysis for immunosensor specificity)

..................................................................................................................... 170
Estimates (Anova analysis for immunosensor specificity) ......................... 170
Type 3 tests of fixed effects (Anova analysis for lettuce testing) .............. 171
Least squares means (Anova analysis for lettuce testing) .......................... 171

Differences of least squares means (Anova analysis for lettuce testing) 172
Type 3 tests of fixed effects (Anova analysis for ground beef testing) ...... 173
Least squares means (Anova analysis for ground beef testing) .................. 173

Differences of least squares means (Anova analysis for ground beef testing)
..................................................................................................................... 174

Type 3 tests of fixed effects (Anova analysis for whole milk testing) ....... 175
Least squares means (Anova analysis for whole milk testing) ................... 175

Differences of least squares means (Anova analysis for whole milk testing)
..................................................................................................................... 176

Type 3 tests of fixed effects (Anova analysis for SPCE biosensor sensitivity)
..................................................................................................................... 177

Table A-22. Estimates (Anova analysis for SPCE biosensor sensitivity) ...................... 177
Table A-23. Least squares means (Anova analysis for SPCE biosensor sensitivity) ..... 177

Table A-24. Differences of least squares means (Anova analysis for SPCE biosensor
sensitivity) ................................................................................................... l 78

xi

LIST OF FIGURES

Figure 2-1. Plasmids and genes associated with Virulence of B. anthracis (adapted from

Mock and F ouet, 2001). ................................................................................ 5
Figure 2-2. Mode of action of B. anthracis toxin proteins ................................................. 6
Figure 2-3. Schematic representation of a biosensor. ....................................................... 10

Figure 2-4. Recent trends in pathogen detection (adapted from Lazcka et al. , 2007). ..... 1 1

Figure 2-5. Schematic of the polyaniline nanowire biosensor for B. cereus detection (Pal
et al., 2008). ................................................................................................... 33

Figure 2-6. TEM images of (A) single-walled carbon nanotubes and (B) multi-walled
carbon nanotubes. .......................................................................................... 35

Figure 2-7. Schematic representation of Au nanoparticle based bio barcode assay (Zhang
et al., 2009) .................................................................................................... 42

Figure 2-8. Structure of polyaniline, x = degree of polymerization, [y + (1 -y)] =1] (Ray et
al., 1989) ........................................................................................................ 53

Figure 2-9. Structure of emeraldine (polyaniline), (a) before protonation and (b)-(d) after
protonation, (b) formation of bipolarons, (0) formation of polarons, and (d)
the separate polarons which result in a polaron lattice (adapted from
Stafstrom et al., 1987) .................................................................................... 56

Figure 2-10. Band structure of conjugated polymers showing polaronic and bipolaronic
states ............................................................................................................... 57

Figure 2-11. CVs of polyaniline films recorded at pH values of (a) 1.0, (b) 2.0, (c) 2.5, (d)
3.0 and (e) 4.0 (Prakash, 2001). ..................................................................... 60

Figure 2-12. Typical cyclic voltammogram (I-E curve) for a redox system .................... 63
Figure 2-13. Synthesis of electrically-active magnetic polyaniline (Li et al., 2007). ....... 64

Figure 2-14. Polymer ligand interactions to iron oxide particle sufaces (L = Ligand)
(Kryszewski and Jeszka, 1998) ...................................................................... 65

xii

Figure 4-1. Schematic representation of polyaniline coating of gamma-iron oxide
nanoparticles .................................................................................................. 75

Figure 4-2. Schematic of (A) EAPM based immunosensor architecture and (B) data
collection system for detection of B. anthracis spores. ................................. 78

Figure 4-3. Modification of EAPM NPS with monoclonal antibodies. ............................ 80

Figure 4-4. Functionalization of biosensor capture pad for attachment of polyclonal
antibodies. ...................................................................................................... 81

Figure 4-5. Screen printed carbon electrode biosensor. .................................................... 89

Figure 4-6.Crosslinking chemistry between the detector DNA probe and magnetic EAPM
NPS ................................................................................................................. 94

Figure 5-1. Experimental M-H curves of the four different EAPM NPS and unmodified
Fe203 NPS at 300K. ..................................................................................... 101

Figure 5-2. Experimental F C-ZFC magnetization curves for 1:0.6 EAPM NPS at 100 Oe

...................................................................................................................... 102
Figure 5-3. Room temperature electrical conductivity of the EAPM NPS ..................... 104
Figure 5-4. TEM and electron diffraction images of y-Fe203 NPS. ............................... 105
Figure 5-5. TEM and electron diffraction images of EAPM NPS (left) 1: 0.1 EAPM;
(right) 1:0.4 EAPM .................................................................................... 106
Figure 5-6. TEM and electron diffraction images of EAPM NPs (left) 1: 0.6 EAPM;
(right) 1:0.8 EAPM .................................................................................... 107
Figure 5-7. Elemental analysis of the 1:0.6 EAPM NPS using energy dispersive
spectroscopy (EDS) in SEM. ..................................................................... 109

Figure 5-8. UV-VIS spectra absorption spectra of pure polyaniline and EAPM NPs.... 111

Figure 5-9. UV spectrum of pure anti-B. anthracis IgG molecules and unreacted IgG
molecules after magnetic separation from EAPM NPS ............................. 113

xiii

Figure 5-10.

Figure 5-11.

Figure 5-12.

Figure 5-13.

Figure 5-14.

Figure 5-15.

Figure 5-16.

Figure 5-17.

Figure 5-18.

Figure 5-19.

Figure 5-20.

Figure 5-21.

Laser scanning confocal microssope images of antibody modified biosensor
capture pad with FITC anti-goat IgG label (left) and capture pad without
FITC anti—goat IgG label (right) (scale bar = 20pm) ................................. 115

Schematic representation of the EAPM based immunosensor for detection of
B. anthracis spores ..................................................................................... 117

Amperometric response of the EAPM based immunosensor in the presence
and absence of the target antigen. .............................................................. 120

Resistance changes in the EAPM immunosensor in the presence and absence
of the target antigen calculated from the measured amperometric response
................................................................................................................... 121

Comparison of biosensor resistance response of the four EAPM NP at three
different spore concentrations (Mean resistance d: SD, n = 3) . ................ 124

EAPM based immunosensor resistance response in pure spore suspensions
of B. anthracis (mean resistance 3: SD, n = 3). Different superscripts over
the bars indicate significantly different resistance response (P < 0.05) 127

Comparison of immunosensor resistance response in pure spore suspensions
of B. anthracis and pure cultures of generic E. coli and S. Enteritidis.
Different superscripts over bars indicate sgnificantly different resistance
response (P < 0.05) .................................................................................... 130

Resistance response of the EAPM based immunosensor in food matrices
contaminated with B. anthracis spores. For each food sample, different
superscripts over bars indicate significantly different resistance response(P
< 0.05). ....................................................................................................... 133

Gel electrophoresis of PCR amplified Bacillus anthracis. (M- Marker, BAl
and BA2- B. anthracis, NC- Negative control) ......................................... 140

Fluorescence signal of pure Ph-PRO probes and unreacted Ph-PRO probes
after magnetic separation from the EAPM NPS ......................................... 142

Schematic representation of the EAPM based electrochemical DNA
biosensor for detecting B. anthracis pag gene ........................................... 144

Normalized fluorescence signal of PCR DNA targets before and after
hybridization at different hybridization temperatures. .............................. 146

xiv

Figure 5-22. Normalized fluorescence signal of PCR DNA targets before and after
hybridization at different hybridization times. .......................................... 147

Figure 5-23. Change in fluorescence of PRO-Bio probes in the presence and absence of
PCR targets during sandwiched hybridization ........................................... 148

Figure 5-24. Cyclic voltammograms of (a) EAPM NPS on SPCE and (b) bare SPCE in
0.1 MHCl at 20 mV/s ................................................................................ 151

Figure 5-25. Cyclic voltammograms of EAPM NPs in 0.1 M HCl at scan rates of 20, 50,
100, 150 and 200 mV/s. Inset- Plots of anodic and cathodic peak current vs.
scan rate. .................................................................................................... 152

Figure 5-26. Electrochemical responses of EAPM captured targets DNA hybrids on
SPCE, of bare SPCE, and of streptavidin modified SPCE in 0.1 M HCl at 20
mV/s ............................................................................................................ 154

Figure 5-27. Cyclic voltammograms of the EAPM based SPCE biosensor in different
concentrations of PCR target DNA in 0.1M HCl at a scan rate of 20 mV/s.
..................................................................................................................... 156

Figure 5-28. Anodic (oxidation) peaks of PCR target concentrations ranging from 1ng/ul
to 0 ng/ul, inset: anodic peak of 10 ng/ul PCR target (obtained from cyclic
voltammograms) .......................................................................................... 1 57

Figure 5-29. CV mediated anodic peak current at different PCR target concentrations
from three experimental trials (mean current i SD, n = 3). ........................ 158

Figure 5-30. Change in fluorescence intensity of non-complementary sequences before
and after sandwiched hybridization on EAPM NPS. ................................... 161

Figure 8-1. SEM images of (A) Iron oxide NPs and (B) EAPM NPS ............................ 179
Figure B-2. Immunosensor responses of different EAPM concentrations in B. cereus. 180
Figure B-3. Immunosensor responses of different B. cereus antibody concentrations .. 181

Figure B-4. Light microscopy images of B. anthracis spores at after two different
incubation periods (Final spore count — 4.2 X 108 spores/ml) ..................... 182

XV

 

CHAPTER 1: INTRODUCTION

In 2001, the anthrax cases associated with the intentional distribution of Bacillus
anthracis spores through the postal system highlighted the danger posed to global citizens
from bioterrorism related attacks. A total of 22 cases of anthrax were identified by the
Centers for Disease Control and Prevention (CDC), of which 11 were confirmed to be
inhalational and the remaining were determined to be cutaneous (CDC, 2001). Before
2001, smaller incidents of bacteriological criminal assault, such as intentional
contamination of salad bars with Salmonella in Oregon in 1984, and Shigella in muffins
and pastries in Texas in 1996 were reported (Chang et al., 2003). A wide range of
infectious disease agents have been currently identified that can be intentionally used to
cause harm. Diseases caused by these potentially weaponized agents include anthrax,
botulism, plague, small pox, tularemia and viral hemorrhagic fevers and have been
categorized as ‘Category A’ agents by the CDC (CDC, 2009).

Bioterrorism related incidents can have huge economic impacts on the society.
Researchers have estimated the economic impact of an anthrax scenario on 100,000
people to be as $ 26.2 billon (Kaufmann et al., 1997). Current human and animal
diagnostic methods for infectious microbial agents are generally based on conventional
microbiological culturing techniques followed by biochemical identification which are
time consuming, requiring 2 to 7 days for confirmation (FDA 2000) and include costly
and laborious sample preparation. Hence, developing rapid detection devices have
become an absolute necessity to strengthen surveillance systems, to provide early
identification in timely manner in cases of exposures thus reducing the possibility of

developing symptoms, and also to prevent further transmission of the agents.

Biosensors are promising, inexpensive, and efficient alternatives for early
identification of such infectious pathogens. Biosensor technology is rapidly evolving in
the field of pathogen detection with a wide range of detection platforms being explored
recently. The emergence of nanotechnology has further allowed the integration of
different nanomaterials into these biodetection systems for developing field-ready, low
cost, sensitive, and specific devices for pathogen detection.

Different nanostructured materials such as silicon nanowires, carbon nanotubes, gold
and magnetic nanoparticles have been employed as transducer materials in biosensor
applications. Recently, conductive magnetic nanostructures consisting Of a magnetic core
and an electrically active conducting polymer shell have been developed. The conducting
polymer, polyaniline, is the most exploited in such magnetic nanostructures. These
electrically active polyaniline coated magnetic (EAPM) nanostructures have magnetic
properties in addition to the electrical properties, electrochemical activity, mechanical
strength, and chemical flexibility of the polymer material. Current literature shows that
such novel EAPM nanostructures have not been explored in biosensor detection systems
till date.

This dissertation describes the development of EAPM nanostructure based detection
systems that can utilize the magnetic, electrical, and electrochemical properties of the
EAPM nanoparticles for magnetic concentration and biosensor transduction in one
system for rapid and specific identification of infectious pathogens. Two different
detection approaches have been demonstrated to show the versatility of these novel
EAPM nanoparticles in detecting Bacillus anthracis as the model target pathogen. In the

first approach, an EAPM based immunosensor was developed that coupled

 

immunomagnetic separation with direct electrical detection of the EAPM nanoparticles in
a membrane based charge transfer biosensor. In the second approach, an EAPM based
DNA biosensor was developed that involved magnetic concentration of DNA targets
combined with direct electrochemical detection of EAPM nanoparticles on a screen
printed biosensor.

Chapter 2 of this dissertation provides an overview on biosensors and
nanotechnology with respect to detection of pathogenic microorganisms and also covers
background information on polyaniline and magnetic polyaniline nanostructures. Chapter
3 highlights the novelty and significance of the research conducted and summarizes the
research hypothesis and objectives. Chapter 4 walks through the materials and methods
involved in synthesizing and characterizing the EAPM nanostructures (Section 4.1), in
developing the EAPM based immunosensor and EAPM based DNA biosensor (Sections
4.2 and 4.4), and in implementing the biosensors for detection (Sections 4.3 and 4.5).
Chapter 5 presents the results obtained from the objectives set for this research. The first
part of this chapter (Section 5.1) discusses the different characterization studies
performed on the synthesized EAPM nanostructures. The second part (Sections 5.2 and
5.3) discusses fabrication and performance of the EAPM based immunosensor in pure
samples and complex matrices. The final part (Sections 5.4 and 5.5) describes the
fabrication and performance of the EAPM based DNA sensor in PCR amplified DNA
targets. This is followed by the concluding remarks and future work in Chapter 6. Finally,

the appendices give statistical analysis results and data from certain experimental studies.

CHAPTER 2: LITERATURE REVIEW

2.1 BA CILL US ANT HRA CIS AND ANTHRAX

Bacillus anthracis is a gram-positive, non-motile, aerobic, facultative anaerobic,
spore-forming, rod-shaped bacterium and is the etiological agent of anthrax. Anthrax is
primarily a zoonotic disease but all mammals, particularly humans, may develop this
disease. The spore forms of Bacillus anthracis are highly resistant to environmental
conditions such as heat, ultraviolet and ionizing radiation, pressure and chemical agents.
They are able to survive for long periods of time in contaminated soils and this account
for the ecological cycle of the microorganism. However, it is not clear whether the
complete life cycle from germination to sporulation occurs outside the host (Mock and
Fouet, 2001). The vegetative cells of the bacterium are square ended and capsulated
having a size range of 3 to 5 um while the spores are elliptical with a size range of 1 to 2
pm.
2.1.1 Virulence of Anthrax

The primary Virulence factors of B. anthracis are toxin production and capsule
formation. Virulent strains of the microorganism carry two large plasmids pXOl and
pX02 which encode these virulence factors. The plasmid pXOl carriesthe structural
genes for the anthrax toxin proteins pagA (protective antigen), lef (lethal factor), and cya
(edema factor); two trans-acting regulatory genes atxA and pagR; a gene encoding type I
topoisomerase, topA; and a three gene operon, gerX, which affects germination. Plasmid
pX02 carries three genes which encode capsule synthesis, capB, capC, and capA; a gene

associated with capsule degradation, dep; and a trans-acting regulatory gene acpA

 

(Okinaka et al., 1999). Figure 2-1 shows a schematic representation of the B. anthracis

plasmids and their associated virulence.

 

bicarbonate

 

 

 

pXOl

 
     

4,,
/ temperature k/

V~ I dep capA capC capB
lef pagR pagA gerX atx “

® 69

Figure 2-1 Plasmids and genes associated with virulence of B. anthracis (adapted
from Mock and Fouet, 2001).

 

 

 

 

 

 

 

 

 

B. anthracis toxins are composed of three proteins (Figure 2-2): protective antigen
(PA), lethal factor (LF) and edema factor (EF). The mature PA protein, an 83 kDa
protein, is made up of 735 amino acids (Petosa et al., 1997). The mature LP (90 kDa) is a
protein that contains 776 amino acids (Pannifer et al., 2001). The mature EF protein (89
kDa) is an inactive enzyme that has 767 amino acids (Leppla, 1982). None of the above

proteins are toxic separately. Toxicity is associated with the formation of binary

exotoxins. The association of PA and LF results in the formation of lethal toxin (LTx),
which provokes lethal shock in animals, while the association of PA and EF forms the

edema toxin (ETx), which produces edema in the skin (Collier and Young, 2003).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Lethal factor Protective antigen Edema factor
Lethal Toxin (LTx) Edema Toxin (ETx)
Lethal shock Edema

 

 

 

 

 

 

Figure 2-2. Mode of action of B. anthracis toxin proteins.

The Bacillus anthracis capsule is a polymer of y-D-glutamic acid. The molecular
weight of the polyglutamic chains is in between 20 and 55 kDa in vitro and estimated to
be 215 kDa in Vivo. The capsule enables the bacteria to evade the host’s immune-system
and provoke septicemia thus resulting in pathogenicity. However, the capsule by itself is
a monotonous linear polymer which is weakly immunogenic and does not favor immune
response (Mock and Fouet, 2001).

2.1.2 MS of Infection

Anthrax is initiated by the entry of the spores into the host body through skin lesions,
insect bite, ingestion of contaminated meat or inhalation of airborne spores. Depending
on the route of infection, there are three clinical forms of anthrax: cutaneous,
gastrointestinal and inhalational (pulmonary). The cutaneous form accounts for 90% of

all human cases (Spencer, 2003) and occurs when the spores enter the host body through

a skin lesion and appears at first as a small pimple developing into a painless back eschar
within few days. Antibiotic treatment is highly effective in cases of cutaneous anthrax
which has a mortality rate of about 20% in untreated cases (CDC, 2001). The
gastrointestinal form of anthrax is extremely rare but potentially fatal. It frequently
occurs after the ingestion of undercooked meat from infected animals and is characterized
by fever, nausea, vomiting, abdominal pain and bloody diarrhea (Mock and Mignot,
2003). Gastrointestinal anthrax has been reported to cause fatalities in 25-60% of cases
(CDC, 2001). The inhalational form of anthrax is considered the most dangerous among
the three having a mortality rate nearing 100% (CDC, 2001). The inhaled spores reach
the alveolus where they are phagocytosed by macrophages and transported to the
mediastinal lymph nodes, where spore germination can occur up to 60 days. The disease
progresses rapidly following germination resulting in the production of exotoxins that
cause edema, necrosis, and hemorrhage (Mock and Fouet, 2001). Diagnosis is difficult in
both gastrointestinal and inhalational forms resulting in the disease to become treatment
resistant and rapidly fatal.

2.1.3 Anthrax and Biosecurity

The use of microorganisms as biological weapons has long been reported in history. One
of the first major attacks that have been reported occurred in the 14th century with
Yersenia pestis during the siege of Kaffa (Inglesby et al., 2000). The most recent was the
deliberate release of B. anthracis spores through the postal system in the United States in
October 2001, shortly after the September 2001 terrorist attack in New York and
Washington resulting in 22 cases of anthrax and 5 deaths (Jemigan et al., 2001). An

optimal biological weapon should be highly lethal, easily produced in large quantities,

environmentally stable and have the capability to be readily dispersed into aerosol (i.e. 1
to lOum particle size) (Peruski and Peruski, 2003). When reviewed for these
characteristics, B. anthracis is the most likely to be used as a biological weapon since it
has the ability to form spores which can be easily aerosolized, inhalational anthrax has a
high mortality rate nearing 100%, and the spore forms of the bacteria are very stable
surviving harsh environmental conditions. It has been estimated that the release of 50 kg
of dried anthrax spores for two hours can lead to a complete breakdown in medical
resources and civilian infrastructure in a city of 500,000 inhabitants (Spencer, 2003). The
Centers for Disease Control and Prevention (CDC) has categorized B. anthracis as a
category A agent or a high priority agent. Category A agents include agents that can be
easily transmitted from person to person, cause high mortality with potential for major
public health impact, may cause public panic and social disruption, and require special
action for public health preparedness (CDC website).
2.1.4 Traditional Identification Methods

Detection and specific identification of B. anthracis require complex techniques and
laborious methods because of the genetic similarities among various Bacillus species as
well as their existence in both spore forms and vegetative state. B. anthracis is identified
using standard biochemical techniques such as its sensitivity to penicillin, non-motility,
non B-hemolytic behavior on sheep or horse blood agar plates and its susceptibility to
lysis by gamma phage. It has been reported that identification of B. anthracis by initial
blood culturing requires 6-24h for growth, which is followed by morphological and
biochemical identification that requires additional 12-24h and finally definitive

identification that requires an additional 1-2 days (Inglesby, 2000). B. anthracis is also

shown to selectively grow on polymyxin-lysozyme EDTA-thallous acetate (PLET) agar
which requires 1-2 days for grth followed. by further confirmation (Erickson and

Kornacki, 2003).

2.2 BIOSENSORS IN PATHOGEN DETECTION
2.2.1 Introduction

A biosensor can be defined as an analytical device that integrates a biological
sensing element with an electrical transducer to quantify a biological event (for e.g. an
antigen-antibody reaction) into an electrical output. The basic concept of operation of a
biosensor has been illustrated in Figure 2-3. The biological sensing elements include
enzymes, antibodies, DNA, aptamers, molecularly imprinted polymers, microorganisms
and whole cells. Depending on the transducing mechanism used, biosensors can be of
many types such as: electrochemical, electrical, optical, mechanical and magnetic
biosensors. The different transducing mechanisms and biological sensing elements are

discussed in detail in later part of this section.

ANALYTE BIORECEPTOR TRANSDUCER SIGNAL PROCESSING

' “G Antibodies Electrochemical

Nucleic Acids Electrical

0 «<1 Ottaal :> l:> MESS...

Enzymes Mechanical

. «C Whole Cells Magnetic

 

 

 

 

 

 

 

 

 

 

Figure 2-3. Schematic representation of a biosensor.

Biosensor technology is emerging as a promising field for rapid detection of
pathogens. Currently, the two most popular methods for detection of pathogens are:
microbial culturing followed by biochemical identification, and polymerase chain
reaction (PCR) assay. The main disadvantages of the conventional microbial culturing
techniques are the time consuming process and the multistep assay procedures for food

samples requiring pre-enrichment steps. The PCR technology, although highly sensitive,

10

has some disadvantages, such as requirement of expensive equipments, skilled personal
to perform assays, DNA extraction stages which increase the detection time, and prior
information of target DNA sequences. On the other hand, biosensors show high
sensitivity and specificity to targets and can be used as simple one-shot measurement
tools or as multi-measurement devices. Moreover, biosensors can be designed to be
operated on a real-time basis thus eliminating the need of expensive lab—based testing
(Terry et al., 2005). The miniaturization ability of biosensors and their compatibility with
data processing technologies allow them to be integrated into small portable devices. This
versatility in biosensors has prompted worldwide research and commercial exploitation
of the technology. Recent trends indicate (Figure 2-4) that biosensors is the fastest

growing technology for rapid detection of pathogens (Lazcka et al., 2007).

 

 

120 .
1 5 Forecast
1 I
a 100* 5 / PCR
m .
E 1 E
3 .
-2 801
8 i . / Culture Methods
'5 604 . Biosensors
E . \
2 / \l
8 40‘
a l -
20‘ / - ————» ELISA
f . ' VA/ _'_“"" Gel Electrophoresis
0+}??? _I ff, I ' I ' i I f . I
1985 1990 1995 2000 2005 2010

Figure 2-4. Recent trends in pathogen detection (adapted from Lazcka et al., 2007).

11

2.2.2 Biosergor Transducing Mechanisms
2. 2. 2.1 Mechanical Biosensors

2.2.2.1.] Quartz Crystal Microbalance (OCM) Biosensors

Quartz crystal resonators form the basis of QCM sensors. The term “QCM” is used
collectively for bulk acoustic wave (BAW), quartz crystal resonance sensors (QCRS) and
thickness shear mode (TSM) acoustic sensors (Cooper and Singleton, 2007). QCM
sensors comprise Of a thin quartz disc with electrodes plated on it. When an oscillating
electric field is applied across the disc, an acoustic wave with a certain resonant
frequency is induced. The disc can be coated with a sensing layer of biomolecules based
on the analyte to be detected. The interaction of the analyte with the biomolecules on the
disc surface causes a change in mass and a concurrent change in resonance frequency that
can be directly correlated to the biomolecular interactions(O'Sullivan and Guilbault,
1999). The relation between mass and the resonant frequency is given by the Sauerbrey

equation:

—2.3x106F2Am
AF: 0
A (2.1)

 

where, AF is the change in frequency (Hertz), F 0 is the resonant frequency of the crystal

(MHz), A m is the deposited mass (grams) and A is the coated area (cmz). The quartz

crystals are inexpensive, easily available and robust thus making them suitable for
chemical sensors and biosensors. In addition, QCM based sensors provide great
flexibility, wide dynamic range of frequency measurements and label free detection

(O'Sullivan and Guilbault, 1999).

12

A wide range of non-labeled QCM biosensors have been reported in the literature for
the detection of pathogenic bacteria and viruses. QCM sensors based on lectin
recognition systems for bacterial identification have been studied by Shen et al. and
Safina et al. (Shen et al., 2007;Safina et al., 2008). Shen et al have used a combination of

mannose self-assembled monolayer (SAM) and lectin concanavalin A for the detection of
E. coli W1485 in a linear range of 7.5 X 102 to 7.5 x 107 cells/m1. Safina et al. utilized
lectin reporters to develop a flow injection QCM biosensor for detection of
Campylobacterjejuni and Helicobacter pylori. The authors were able to detect 103 to 105

cells/ml in 30 min. A SAM based QCM immunosensor was developed for the detection
of E. coli 0157: H7 by Su et al. (Su and Li, 2004a). The immunosensor was able to
detect the target bacteria in the range of 103 to 105 CFU/ml in 30-50 min. Detection of B.
subtilis spores as a surrogate to B. anthracis was achieved by Lee et al. utilizing a QCM
immunosensor to a detection limit of 450 spores/ml (Lee et al., 2005). Furthermore, virus
(dengue virus and hepatitis B virus) detection with QCM immune and nucleic acid based
sensors have been reported by Wu et al. and Yao et al. (Yao et al. , 2008;Wu et al., 2005)
QCM biosensors for the detection of DNA sequences have also been developed

using nanoparticle labels as amplifiers. Mao et al. reported the use of streptavidin
conjugated Fe3O4 nanoparticles for the detection of E. coli 0157: H7 eaeA gene. The
nanoparticles acted as ‘mass enhancers’ and amplified the change in frequency. The
biosensor could attain a sensitivity of 1012 M synthetic oligonucleotides and 2.67 X 102

CFU/ml E. coli 0157: H7 cells (Mao et al., 2006). Similarly, Au nanoparticles were

employed by Wang et al. for real time bacterial DNA detection in a circulating flow

13

QCM biosensor. The authors reported a sensitivity of 2.0 X 103 CFU/ml for E. coli 0157:

H7 eaeA gene (Wang et al., 2008).
Although QCM biosensors are being used widely for pathogen detection, they have
limited potential for scalability since the mass detection capability scales with the QCM
sensor surface.

2. 2. 2. 1.2 Surface Acoustic Wave (SA W) Biosensors

SAW sensors are the second class of acoustic wave sensors that have found
applications in biosensor devices. SAW sensors consist of two metal interdigital
transducers (IDT) etched from a thin metal film deposited on a piezo-electric substrate.
The sensing mechanism is based on the changes in SAW velocity or attenuation when
mass is sorbed on the sensor surface. Since the acoustic energy is strongly confined to the
surface, SAW devices are very sensitive to changes in the surface such as mass loading,
viscosity, and conductivity changes (Galipeau et al., 1997). It has been suggested that
SAW based biosensors have greater sensitivities than QCMS because of their higher mass
sensitivities (~ 200 times > QCM) (Galipeau et al., 1997).

SAW biosensors have been successfully applied for the detection of bacteria and
viruses. E. coli detection using SAW biosensors have been reported by multiple authors
in the literature (Berkenpas et al., 2006;Deobagkar et al., 2005;Moll et al., 2007;Moll et

al., 2008). The biosensors have used antibodies as the biological sensing element with
sensitivities ranging from 106 cells/ml to 0.4 cells/pl. Branch and Brozik have developed
a 36° YX cut LiTaO3 based SAW device for the detection of the Bacillus anthracis

simulant Bacillus thuringiensis spores in aqueous conditions (Branch and Brozik, 2004).

The authors have investigated two waveguide materials polyimide and polystyrene for

14

creating the Love wave sensors. Detection of Bacillus thuringiensis spores at
concentrations below the lethal dose of anthrax spores was possible using both
waveguide materials. The sensor had a detection limit of a few hundred cells per ml and a

response time of < 100 s. Jin et al. developed a SAW biosensor for detecting the gene of
Staphylococcal Enterotoxin B utilizing ST-cut quartz and SiOz guiding layer. The

biosensor had a sensitivity of 10 ng/ml and a linear range of 35-200 ng/ml (Jin et al.,

2003). Recently, SAW biosensors were used for detecting viral bioagents by Bisoffi et al.
(Bisoffi et al., 2008). A lithium-tantalate based SAW transducer with SiOz waveguide

sensor platform was used for Coxsackie virus B4 and Sin Nomber Virus detection.

SAW resonators are suitable for use in simple electronic setups because of their low
insertion losses and sharp resonance frequencies. As a result, insertion of such devices
into oscillator circuits is beneficial as such circuits are commonly used in point-of—care
diagnostics. Furthermore, the SAW based biosensors can be prepared from cheap
components thus making them suitable for integration into inexpensive sensor arrays
(Lange et al., 2008).

2. 2. 2. 1.3 Microcantilever Based Biosensors

Microcantilever based biosensors are derived from microfabricated cantilevers used
in atomic force microscopy (AFM) and are based on the bending induced in the
cantilever when a biomolecular interaction takes place on one of its surface which is
translated into nanomechanical motion and is commonly coupled to an optical or
piezoelectric readout system (Carrascosa et al., 2006). The cantilevers can be operated in
the static deflection mode where analyte binding causes cantilever bending or in the

dynamic resonant mode where analyte binding causes change in resonant frequency

15

(Waggoner and Craighead, 2007). Microcantilever sensors are promising for biosensor
applications since they can perform local, high resolution, and label-free molecular
recognition measurements (Carrascosa et al. , 2006).

Davila et al. have demonstrated microcantilever based biosensors in the detection of
B. anthracis Sterne strain in air and water (Davila et al., 2007). The detection scheme
involved measurement of the decrease in resonant frequency driven by thermally induced
oscillations as a result of the mass of spores measured by a laser Doppler vibrometer. The
authors reported a minimum detection of 2 spores (740 fg) and 50 spores (139 pg) in air
and water, respectively, using 20 um long, 9 pm wide, and 200 nm thick cantilevers.
Muthasaran and coworkers have utilized piezoelectric-excited millimeter-sized cantilever
sensors for the detection of B. anthracis Sterne spores and E. coli 0157: H7 cells. The
sensors consisted of a piezoelectric and a glass layer and were able to detect B. anthracis
spores at 300 spores/ml and E. coli 0157: H7 cells in ground beef at 50 to 100 cells/ml.
Extremely sensitive microcantilever based biosensors capable of detecting a single
pathogen have also been reported in literature(Campbell and Mutharasan, 2006). Illic et
al. were able to detect a single E. coli 0157: H7 cell using low stress silicon-nitride
cantilever beams in air (Ilic et al., 2001). The mass of a single E. coli 0157: H7 cell was
found by the authors to be 665 fg. Similarly, Johnson et al. reported the use of microscale
silicon cantilever resonators for vaccinia virus detection in air (Johnson et al. , 2006). The
authors measured the mass of a single vaccinia virus particle to be 12.4 21:13 fg and 7.9 i:

4.6 fg using two different sized cantilever beams.

16

2. 2.2.2 Optical Biosensors

2. 2. 2. 2.1 Surface Plasmon Resonance (SPR) Biosensors

SPR is an Optical technique for monitoring biomolecular interactions that occur in
the close vicinity of a transducer surface. SPR based biosensing can be subdivided into
three categories depending on the mode of SPR detection: angular SPR biosensing,
spectral SPR biosensing, and local SPR biosensing. Angular SPR biosensing is the most
common form of SPR biosensing and involves attenuated total reflection approach using
Kretschmann geometry (Erickson et al., 2008). Spectral SPR biosensing is conducted at a
fixed incident angle and utilizes the wavelength dependence of the dielectric constant of
the metal film to interrogate the surface plasmon coupling conditions. Local SPR (LSPR)
biosensing or nanoparticle based SPR involve coupling of surface immobilized metallic
nanoparticles or nanostructures into a plasmon mode which results in a decrease in the
transmitted power at a specific resonant wavelength dependant on environmental
dielectric conditions (Erickson et al. , 2008).
SPR biosensors provide several advantages over conventional transduction techniques,
such as, capability of label-free detection, ability to produce continuous real-time
responses, regeneration of the active sensor surface, feasibility for miniaturization,
sensitive detection of small molecules, and multiplexing ability ((Shankaran et al., 2007).
Particularly, multiplex detection, or detection of different targets on the same platform, is
an important characteristic in these biosensors since it adapts to screening of unknown
samples.

SPR based immunosensors have been developed for the detection of E. coli 0157:

H7 by Irudayaraj and coworkers. The authors have demonstrated a sensitivity Of 103

17

CFU/ml for the pathogen using a SAM based SPR biosensor and the commercially
available Spreeta SPR biosensor (Waswa et al., 2007;Subrarnanian et al., 2006).
Detection of Salmonella Typhimurium in chicken carcasses was achieved using an

antibody based SPR biosensor by Lan et al. (Lan et al., 2008). The SPR biosensor had a

lowest detection limit Of l X 106 CFU/ml. Highly sensitive detection of Salmonella

Enteritidis was attained by Waswa et al. using the commercial BiacoreTM SPR biosensor

(Waswa et al., 2006). The limit of detection (LOD) of the biosensor as reported by the
authors was 23 CFU/ml for Salmonella. Chen et al. have demonstrated an
immunomagnetic separation based SPR detection method for the foodbome pathogen

Staphylococcus aureus (Chen et al., 2007). The detection system involved an initial
immunomagnetic bead based separation step of 30 min and had a sensitivity of 106
CF U/ml in a total assay time of 2 h. A SAM based SPR immunosensor was developed by
Jyoung et al. for the detection of Vibrio cholerae 01 with a detection range of 105 to 109

cells/m1 (.1 young et al. , 2006). Detection of viruses using SPR based biosensors have been
reported by Chung et al. and Vaisocherova et al. (Chung et al. , 2005;Vaisocherova et al. ,
2007). Vaisocherova and coworkers developed a SPR biosensor for detecting antibodies
against Epstein-Barr Virus. The antibody detection was performed using an
immunoreaction between the antibody and a synthetic peptide for the Virus. The sensor
had a sensitivity of 0.2 ng/ml (~ lpM). Furthermore, multiplex detection of four
foodbome bacterial pathogens (E. coli 0157: H7, Salmonella Typhimurium, Listeria
monocytogenes & Campylobacter jejuni) was demonstrated by Taylor et al. using an

eight-channel SPR biosensor (Taylor et al., 2006). The LOD for each Of the four species

Of bacteria was in the range of 3.4 X 103 and 1.2 X 105 CFU/ml.

18

Several detailed review articles are available in literature that focus on different
SPR based detection techniques and their applications (Shankaran et al., 2007;Homola,
2008;Hoa et al. , 2007).

2. 2. 2. 2.2 Fluorescence Based Biosensors

Fluorescence is the radiative deexcitation of a molecule following the absorption of a
photon. Generally, the emitted photon is of lower energy than the absorbed photon, and
the fluorescence emission peak of a species is at longer wavelength than the absorption
peak, the wavelength separation being referred as Stoke’s shift. Fluorescence based
detection systems have gained popularity in biosensors due to their high sensitivity and
are mostly based on the detection of the fluorescent signal generated by fluorophores
used to label the biomolecules.

Fluorescence detection techniques can be performed in the high-throughput mode in
combination with platforms such as microarrays. Microarrays offer the advantage of
using a two-dimensional layout of recognition elements for simultaneous detection and
quantification. Taitt et al. have demonstrated a fluorescence based microarray
immunosensor for the simultaneous detection of nine targets comprising of B. anthracis
Sterne, B. globigii, Francisella tularensis, Yersenia pestis, S. Typhimurim,
Staphylococcal enterotoxin B, ricin, cholera toxin and M82 coliphage (Taitt et al., 2002).
Li et al. have developed DNA-based fluorescence nanobarcodes to integrate with DNA-
microarrays for the simultaneous detection of four targets (B. anthracis, Francisella
tularensis, Ebola virus and SARS coronavirus) (Li et al., 2005). The feasibility study
involved confocal microscopy, dot blotting and flow cytometry which resulted in

attomolar sensitivity.

19

Fluorescence resonance energy transfer (FRET) based detection involves non-
radiative energy transfer between a donor fluorophore and an acceptor fluorophore when
they are in close proximity (Epstein et al., 2002). A fiber optic portable biosensor
utilizing the principle of FRET was developed by K0 and Grant for rapid detection of S.

Typhimurium in ground pork samples (K0 and Grant, 2006). The biosensor had a
sensitivity of 105 CFU/ml in a response time of 5 min. Kim et al. reported a molecular

beacon DNA microarray system for fast detection of E. coli 0157: H7 based on FRET
(Kim et al., 2007a). In this system, unlike conventional fluorophore-quencher beacon
design, two fluorescence molecules allowed active visualization of both hybridized and

unhybridized states of the beacon. The target gene detection limit for the system was

lng/ul.

Fluorescence based tapered fiber optic biosensors have also been employed in
pathogen detection. A fluorescence based fiber optic biosensor for detecting E. coli

0157: H7 in ground beef samples was developed by Geng et al. (Geng et al., 2006). The
authors reported sensitivity of 103 CFU/ml in pure cultures and of 1 CFU/ml in

artificially contaminated ground beef samples after 4 h enrichment using a sandwich

immunoassay. Nanduri et al. developed an automated fiber optic based immunosensor
called RAPTORTM for the detection of Lysteria monocytogenes in food samples. The
LOD of the system was 5 X 105 CFU/ml in food samples and 1 x 103 CFU/ml in PBS

(Nanduri et al., 2006).
Inspite of the enhanced sensitivity, all fluorescence based biosensors suffer from

disadvantages attributed mainly to the characteristics of the fluorescent probe such as

20

stability and efficiency of labeling. The expensive fluorescent labels are also a drawback
of this technology.
2. 2.2.3 Electrochemical Biosensors

Electrochemical biosensors are based on the detection of electrochemical signal
generated by consumption or production of electrons from biological interactions
occurring at the sensor surface. Advantages such as low cost, high sensitivity,
miniaturization ability, low power requirements, and simple instrumentation make the
electrochemical biosensors well suited for clinical and environmental analysis.
Electrochemical biosensors are generally classified as amperometric, potentiometric,
conductometric and impedimetric.

2. 2. 2. 3. I Amperometric Biosenm

Amperometric biosensors are based on the measurement of current changes resulting
from oxidation or reduction of an electroactive species in a biochemical reaction. The
current is typically measured at a fixed potential (amperometry) or during controlled
variations of the potential (voltammetry).
Theegala et al. reported an oxygen-electrode based amperometric biosensor for the
qualitative detection of E. coli 0157: H7 in water (Theegala et al., 2008). The biosensor
detected changes in oxygen concentration due to decrease in enzymatic activity upon
binding of bacterial cells. The biosensor could detect as low as 50 cells/ml in 20 minutes.
A renewable amperometric immunosensor for the detection of S. Typhi was reported by

Singh et al. (Singh et al., 2005). The detection technique involved a sandwich ELISA
system with a LOD of 105 cells/ml in 90 minutes. Amperometric detection of antibodies

against Bacillus anthracis protective antigen was also achieved by Aguilar et al. (Aguilar

21

and Sirisena, 2007). The antibodies were captured and detected using microcavities with
a LOD of 10 fg in a 200 nL sample. A disposable amperometric immunosensor based on
screen printed electrode (SPE) coated with agarose/nano-Au membrane and horseradish
peroxidase labeled antibody for specific detection of the foodbome pathogen Vibrio

parahaemolyticus was developed by Zhao et al. (Zhao et al., 2007). The immunosensor
showed a sensitivity of 7 X 104 CFU/ml for the pathogen and its accuracy was in good

agreement (97.5%) with ELISA results.

Lermo et al. described a genomagnetic assay for the electrochemical detection of
Salmonella spp. based on in situ DNA amplification and magnetic primers (Lermo et al.,
2007). Detection was achieved by sandwich hybridization of the target on magnetic beads
which were then separated by a magneto electrode based on graphite—epoxy composite
followed by electrochemical detection using an enzyme marker anti-digoxigenin
horseradish peroxidase. The authors achieved a sensitivity of 2.8 frnol with PCR
amplicons. Multianalyte detection using electrochemical genosensors have also been
studied by Farabullini et al. and Elsholz et al. (Elsholz et al., 2006;Farabullini et al.,
2007). F arabullini et al. achieved nanomolar detection limits for the pathogenic bacteria,
Salmonella sp., E. coli 01572H7, L. monocytogenes and S. aureus using differential pulse
voltammetry to detect u-napthol signal in less than 1 h.

2. 2. 2. 3. 2 Potentiometric Biosen_s_0_rs

Potentiometric devices are based on the measurement of accumulation of charge

potential at the working electrode of an electrochemical cell in comparison to the

reference electrode with zero or negligible current flow between the electrodes. The

22

measured potential is related to the concentration of the analyte through the Nersnt

equation:

E = 150 i (RT/nF)1nQ (2.2)

where, E is the cell potential at zero current, E0 is the standard potential, R is the

universal gas constant, T is the absolute temperature, F is the Faraday constant, n is the
total number of charges of ion, Q is the ratio of ion concentration at the anode to that at
the cathode (Diamond, 1998;Eggins, 2002).

Among electrochemical transducing methods, potentiometric methods are the least
exploited in pathogen detection due to their high detection limits and poor selectivity, the
main advantage of these devices being wide detectable concentration range and
continuous measurement capability (Palchetti and Mascini, 2008). Another approach
involves ion selective field effect transistors (ISFETs) that employ semiconductor field-
effect to detect biorecognition events. However, the application of these devices in
biosensors has been limited by production problems related to immobilization,
fabrication and packaging, poor detection limits and device stability (Lazcka et al. , 2007).
An advancement that has evolved from the ISFET is the light addressable potentiometric
sensor (LAPS) which combines potentiometry with optical detection (Hafeman et al.,
1988;Lazcka et al., 2007). Ercole et al. reported an antibody based LAPS biosensor for
determination of E. coli in food (Ercole et al., 2003). The biosensor detected variations in
pH due to ammonia production by urease-E. coli antibody conjugates in commercial
lettuce, Sliced carrot, and rucola samples. The sensor was able to reach a sensitivity of 10

cells per ml in an assay time of 1.5 h.

23

2. 2. 2. 3. 3 Conductometric Biosensors

Conductometric biosensors utilize the electrical conductivity of a sample to
determine the components and their concentration (Rahman et al., 2008). Muhammad
Tahir and Alocilja (Muhammad-Tahir and Alocilja, 2003a;Muhammad-Tahir et al.,
2005) have developed a conductometric biosensor for the detection of pathogenic
bacteria and viruses. The biosensor was fabricated using conducting polyaniline as an
electronic label in a sandwich immunoassay scheme and the authors demonstrated that

polyaniline improved the sensitivity of the biosensor by forming a conductive molecular

bridge between silver electrodes. The authors reported a sensitivity of 8.3 X 101 CFU/ml
for Salmonella, 7.9 x 101 CFU/ml for E. coli 01572H7, 7.5 x 101 CFU/ml for E. coli and

103 CCID/ml for BVDV virus in a detection time of 10 min with the conductometric

biosensor. A conductometric immunosensor based on magnetic nanoparticles has been
recently developed for the detection of E. coli by Hnaiein et al. (Hnaiein et al., 2008).
The immunosensor was composed of streptavidin modified magnetic nanoparticle layer
immobilized on a conductometric transducer consisting of interdigitated gold electrodes.
Conductivity measurements allowed detection of 0.5 CFU/ml of E. coli without the need
for amplification.

2. 2. 2. 3. 4 Impedimetric Biosensors

Impedance spectroscopy involves applying small amplitude perturbing sinusoidal
voltage signal to an electrochemical cell and measuring the resulting current response.
The complex impedance, sum of real and imaginary impedance components, can be
calculated as a function of the excitation frequency of the applied potential by varying it

over a range of frequencies (Katz and Willner, 2003). Impedimetric detection techniques

24

provide advantages of high sensitivity, linearized current-potential characteristics,
measurement over wide time or frequency range and label free sensing (Rahman et al.,
2008;Lazcka et al. , 2007)

Radke and Alocilja had developed a microimpedance biosensor for the detection of E.
coli (Radke and Alocilja, 2005). The sensor detected changes in impedance caused by the
presence of bacteria immobilized on interdigitated gold electrode arrays fabricated from

silicon. The biosensor was able to discriminate between different cellular concentrations
of the bacteria (105 to 107 CFU/ml) in 5 min. Nandakumar et al. have demonstrated the

detection of S. Typhimurium using electrochemical impedance spectroscopy based on
Bayesian decision theory (Nandakumar et al., 2008). The technique detected the
pathogen in 6 min at a lowest concentration of 500 CFU/ml. An impedance biosensor
based on interdigitated array microelectrode coupled with magnetic nanoparticle-
antibody conjugates was developed for rapid and specific detection of E. coli 01 57:H7 in
ground beef samples by Varshney et al. (Varshney and Li, 2007). Magnitude of
impedance and phase angle was measured in a frequency range of 10 Hz to 1 MHz in the

presence of 0.1 M mannitol solution. The lowest detection limit of the biosensor for E.
coli OlS7:H7 was 7.4 X 104 CFU/ml in pure cultures and 8.0 X 105 CFU/ml in ground

beef samples, the total detection time being 35 min.
2. 2. 2.4 Magnetic Biosensors

Devices based on the detection of magnetic labels are emerging as a promising new
approach in the field of biosensing. Magnetic labels have gained popularity in biosensing
because they are physically and chemically stable, are relatively inexpensive, and can be

easily made biocompatible. Several approaches have been developed in the past few

25

years for both direct and indirect detection of magnetic labels. Direct detection includes
approaches for measuring magnetic parameters such as magnetic permeability, magnetic
remanence, magnetoresistance, and Hall Effect. The indirect detection methods are based
on micro-cantilever based force amplified sensors and magnetic relaxation switches
(Tamanaha et al., 2008). However, the applications of these magnetic devices for
detection of actual targets such as pathogenic microorganisms remain limited and require
further research.

Edelstein et al. had developed a multi-analyte BARC (Bead Array Counter)
biosensor using giant magnetoresistive (GMR) sensors to detect and identify biological
warfare agents (Edelstein et al., 2000). The prototype designed by the authors consisted
of a microfabricated chip with GMR sensor arrays, an electronic chip-carrier board, a
fluidics cell and an electromagnet. DNA probes were patterned onto the GMR sensor
chips and hybridized with complementary PCR products. Micron sized magnetic beads
were then bound to the DNA sample by streptavidin biotin interactions and the unbound
beads were removed by applying a magnetic field. The bound magnetic beads were then
detected by the GMR sensors. The authors were able to demonstrate the detection of B.
anthracis lethal factor and C. botulinum neurotoxin A using the BARC biosensor. -

A mass-sensitive magnetoelastic immunosensor for the detection of E. coli 0157:H7
was reported by Ruan et al. (Ruan et al., 2003). The detection was based on the
immobilization of alkaline phosphatase labeled antibodies on the surface of a
micrometer-scale magnetoelastic cantilever and amplification of the mass change

associated with antigen-antibody binding reaction by biocatalytic precipitation of bromo-

26

4-chloro-3 -indolyl phosphate. The minimum detectable level of the immunosensor was 6
X 102 cells/ml.

A high efficiency Hall effect micro-biosensor platform has recently been developed
for the detection of magnetically labeled biomolecules by Sandhu et al. (Sandhu et al.,
2007). In this system, the integration of Hall-effect structures with micro-current lines
allowed manipulation of the magnetic beads position via field gradients. The authors
studied the hybridization of fully-complementary DNA strands of 20-25 bases using
Dynabeads as magnetic labels with this platform. Although, the sensitivity of the sensor
was not reported, the authors were able to demonstrate a quantitative relationship
between the number of magnetic labels and the output signal.

2.2.3 Biological Sensing Elements

The main classes of biological sensing elements that are currently used in biosensors
for pathogen detection are: (i) enzymes, (ii) antibodies, (iii) nucleic acids, (iv) aptamers
and (v) molecularly imprinted polymers.

Enzymes are large complex macromolecules consisting mainly of protein, and
containing a prosthetic group, that often include one or more metal atoms. Enzymes act
as biocatalysts in biochemical reactions. Enzymes are mostly used for labeling other
biomolecules such as antibodies and DNA in pathogen biosensing similar to assays such
as ELISA (Lazcka et al., 2007).

Antibodies are molecules consisting of polypeptide chains and can be classified as
polyclonal, monoclonal and recombinant antibodies. Antibodies have been extensively
applied in biosensors for the following advantages: they are very selective for a particular

antigen, they are ultra-sensitive, and can bind very strongly with the corresponding

27

antigen. Antibodies can also be easily labeled with different molecules such as enzymes,
radioisotopes, fluorescent probes, chemiluminescent probes or metal tags (Eggins, 2002).
Most antibody based biosensors (immunosensors) are based on a competitive or
sandwich assay when applied to detection of low and high molecular weight molecules,
respectively (Marquette and Blum, 2006).
Nucleic acid (DNA & RNA) hybridization is a thermodynamically favored process which
is triggered by highly specific interactions between the base-pairs where each nucleotide
base strongly binds to its complementary base through multiple hydrogen bonds. This
property makes nucleic acids an excellent choice for use as bio-recognition elements in
biosensors. The nucleic acid based biosensors reported in literature can be classified
based on optical, mass sensitive or electrochemical detection platforms (Diamond, 1998).
Of these, DNA-based electrochemical sensors which rely on the conversion of DNA
base-pair recognition event into useful electrical signal have been exploited the most.
Such DNA based electrochemical devices have the advantages of high sensitivity,
selectivity, low-cost, miniaturization ability and minimal power requirements (Wang,
2002). Numerous approaches for electrochemical detection of DNA have been
developed which include direct electrochemistry of DNA, electrochemistry at polymer-
modified electrodes, electrochemistry of DNA-specific redox reporters, electrochemical
amplification with nanoparticles and devices based on DNA-mediated charge transport
chemistry (Drummond et al., 2003).

Aptamers are synthetic folded DNA or RNA oligonucleotide sequences specifically
generated complementary to diverse target molecules. Aptamers offer multiple

advantages as bio-recognition elements in biosensors in comparison to natural receptors

28

such as antibodies and enzymes. These include: high selectivity for targets (similar to
monoclonal antibodies), smaller size, high reproducibility with minimum batch to batch
variations, cost-effectiveness, chemical stability, greater flexibility for biosensor design
and synthesizing ability for any given target (Song et al., 2008;Mairal et al., 2008).
Molecular imprinting is a template-induced process for the formation of specific
recognition sites in a polymeric material, where the template directs the positioning and
orientation of the material’s structural components by a self-assembling mechanism.
Molecularly imprinted polymers (MIPS) have several advantages over natural
biomolecules such as antibodies and receptors. These include their unique stability in
harsh environmental conditions, high affinity and selectivity similar to that of natural
receptors, and their simplicity of preparation and ease of adaptation to practical
applications (Ye and Haupt, 2004;Piletsky et al., 2006). MIPS have been generated for a
broad range of molecules from small molecules such as drugs to large proteins and cells,
the best results being obtained for molecular weights in the range of 200-1200 Da

(Piletsky et al., 2006).

29

2.3 NANOBIOSENSORS & NAN OSTRUCTURED TRANSDUCERS

Nanotechnology is defined as the creation of functional materials, devices and
systems through the control of matter at the l-100 nm scale (Wang, 2005). Recent
advances in nanotechnology have led to the development of a variety of nanomaterials,
e.g., nanowires, nanotubes, nanoparticles, nanospheres and nanorods. Due to their
extremely small size, these nanomaterials exhibit unique properties such as physical
strength, chemical reactivity, electrical conductivity, magnetism and optical
characteristics. Such characteristics of the nanomaterials offer enormous prospects in
designing novel methods of signal transduction and in integrating them into biosensing
devices. Nanomaterials and nanoelectrodes are an important component of
nanobiosensors. This section describes different nanostructured transducer materials and
their current applications in biosensors with special emphasis on the detection of
pathogenic microorganisms.
2.3.1 Nanowire Based Biosensors

Recently, nanowires have been explored as biosensor transducers for the following
reasons: Firstly, the high aspect ratios of the nanowires make them extremely sensitive to
biological interactions. Secondly, the electronically switchable properties of
semiconducting nanowires allow direct and label-free electrical detection. Thirdly, the
size-tunability of the nanowires to sub-100 nm allows high density device fabrication
(Wang et al., 2007a). Semiconducting nanowires including silicon nanowires, and
conducting polymer nanowires, as well as metallic nanowires are the most studied ones in
biosensor architectures. Laser-assisted metal-catalyzed growth (LCG), Vapor-liquid-solid

growth (VLS), Vapor-solid-solid growth (VSS), chemical-solution based growth and

30

template-assisted growth are some techniques employed in the synthesis of nanowires
(Spanier, 2006).
2.3.1.] Silicon Nanowires

Semiconductor nanowire based detectors that show a change in conductivity with
respect to variations in electric potential are referred to as field-effect transistors (F ET).
FETs have been widely used as transducers in detection devices because of the high
surface to volume ratio and high sensitivity of the carrier mobility to variations in electric
field at the semiconductor nanowire surfaces. Silicon (Si) nanowire based FETs are
particularly attractive for electrical based sensing because of their superior electrical
performance characteristics, high reproducibility and controllability during growth, and
their high-performance switching characteristics that affect sensitivity (Cui et al.,
2003;Eggins, 2002;Patolsky et al., 2006).

In a recent study, Mishra and coworkers have developed a nanowire field effect
transistor (nano-FET) for detecting the enterotoxins released by the food borne pathogen
Staphylococcus aureus (S. aureus Enterotoxin B, SEB) (Mishra et al., 2008). The nano-
F ETs were fabricated using 50 nm doped polysilicon nanowires that were attached to
small gold terminals separated by a gap of 150 nm using c beam lithography with
controlled reactive ion etching using chlorine plasma. The authors reported a very low
sensitivity of 10 1M of pure SEB using electrochemical impedance spectroscopy.
Detection of single influenza A viruses was achieved by Patolsky et al. with antibody
modified Si nanowire arrays (Patolsky et al., 2006). The detection was based on the

change of conductance of the nanowire device from a baseline value upon binding of the

31

virus particle followed by simultaneous return of the nanowire conductance to the
baseline value upon unbinding of the viruses

Si nanowires have also been applied for the detection of DNA sequences. A two-
terminal Si nanowire based electronic device for ultrasensitive DNA detection have been
described by Hahm et al. (Hahm and Lieber, 2004). The device was modified by the
authors with peptide nucleic acid (PNA) receptors that could distinguish between the wild
type and and AF508 mutation site in the cystic fibrosis trans membrane receptor gene.
The time dependant conductance change due to PNA-DNA hybridization demonstrated
that the device could selectively detect DNA concentrations as low as 10 M. The
detection limit of the device as suggested by the authors were better than other real-time
measurement systems such as nanoparticle enhanced surface plasmon resonance (SPR)
sensors and quartz crystal microbalance. More recently, arrays of highly ordered n-type
silicon nanowires were fabricated using complementary metal-oxide semiconductor
(CMOS) technology by Gao et al. (Gao et al., 2007). The Si nanowire arrays enabled real
time linear detection of DNA hybridization to its complementary target over a large
dynamic range of 25 fM to 5 pM with a detection limit of 10 tm.
2.3. 1.2 Conducting Polymer Nanowires

Conducting polymer (CP) nanowires or ‘organic’ nanowires are another class of
nanowires that are used as transducer materials in biosensors. Simple synthetic
procedures, controllable electrical properties, flexible chemical structures, compatability
with biomolecules and efficient charge transfer in biochemical reactions are some of the
properties which make CP nanowires attractive candidates for biosensing. Polyaniline

and polypyrrole are the two most studied CPS in biosensor applications.

32

Pal et al. have described a polyaniline nanowire based direct-charge transfer
biosensor for the detection of Bacillus species (Figure 2-5) (Pal et al., 2008). The
biosensor used two sets of antibodies (secondary and capture antibodies) for detection of
the food borne pathogen, Bacillus cereus. The detection principle involved an
immunoreaction coupled with direct electron charge flow by polyaniline nanowires
across silver electrodes. The biosensor could attain sensitivity as low as 10l CFU/ml in 6
min through a reagentless process. The biosensor showed little or no cross-reactivity with
other non-target bacteria and was also able to detect the presence of the target in a mixed

culture of five different microorganisms.

Application Conjugate
pad Pad Capture

Pad Electrode

   
 
  
 
 
 

’ Absorption
.. . i a " Pad
.m- at, .. ..
. as .l-

 

» .1... . , Platform

.3... at: a»

   
      

 

Figure 2-5. Schematic of the polyaniline nanowire biosensor for Bacillus cereus

detection (Pal et al., 2008).

Fan et al. have reported a nanogapped microelectrode-based biosensor array for
detection of microRNAs (miRNAs) utilizing polyaniline nanowires (Fan et al., 2007).
PNA capture probes were immobilized in nanogaps of the microelectrodes and
hybridized with their complementary miRNA. Conductance of the enzymatically
catalyzed polyaniline nanowires, deposited on hybridized target miRNA, corresponded to
the hybridized target concentration. The detection limit of the biosensor as reported by

the authors was 5.0fM. Ramanathan et al. demonstrated DNA detection using avidin

33

functionalized polypyrrole nanowires that were electrodeposited in nanometer sized
channels on the surface of silicon wafers and the resistance change of the avidin modified
polypyrrole nanowires were used as indicator of the binding event of biotin-DNA
(Ramanathan et al., 2005). Resistance change for biotin-DNA concentration as low as 1
nM could be detected with an increasing resistance for increasing concentration till 100
nM.
2.3.2 Nanotube Based Biosensors
2.3.2.1 Carbon Nanotubes

In recent years, carbon nanotubes (CNT) have found broad applications in biosensors
for detecting biomolecules and biological agents. This can be attributed to a number of
factors such as unique electrical and electrochemical properties, high mechanical
strength, and high aspect ratio for adsorption and immobilization of biomolecules on
CNTs. CNTs can be functionalized in different configurations as covalent/non-covalent,
defect, sidewall and endohedral, thus, making them compatible for different applications
and can also be grown as single-walled nanotubes (SWNT) and multi-walled nanotubes
(MWNT) (Figure 2-6) with diameters ranging from 0.4 to 3 nm for SWNT, and from 2 to
100 nm for MWNT respectively (Erickson et al., 2008;Kim et al., 2007b;Vaseashta and
mova—Malinovska, 2005). CNTs have two distinct advantages over Si nanowires in their
higher electron mobilities and their diameters in sub nanometer range and were first used

in FET based devices for chemical sensing by Kong et al. (Kong et al. , 2000).

34

 

Figure 2-6. TEM images of (A) single-walled carbon nanotubes and (B) multi-walled

carbon nanotubes.

A SWNT based FET device was developed by Villamizar et al. for the detection of
the foodbome pathogen Salmonella Infantis (V illarnizar et al., 2008). The device used
anti-Salmonella antibodies adsorbed onto the CNTs as the biological sensing element and
was able to detect 100 CFU/ml of the pathogen in 1h. The device was selective and
showed no cross-reactivity with antigens such as S. pyogenes and S. sonnei. So et al.
reported an aptamer (So et al., 2008) based SWNT FET array as a screening tool for E.
coli DHa5 using the most probable number method. The sensor applied RNA based E.
coli aptamers as the molecular recognition element and was able to complete the
detection process in 20 min. Zhou et al. had utilized the high polarizability and dielectric
mobility of SWNTs to capture, concentrate, and detect low numbers of bacteria in small
sample volumes using microelectrode arrays (Zhou et al., 2006). AC impedance spectra
measurements yielded a detection threshold of 104 bacteria/ml with this technique.
SWNT based FET devices functionalized with PNA were also used to detect an RNA
sequence of the Hepatitis C virus at concentrations as low as fractional pM range by

Dastagir et al. (Dastagir et al., 2007). Dong et al. have shown a label-free detection

35

method for DNA sequences using resistors prepared from double-walled carbon nanotube
networks (Dong et al., 2008). The device was able to detect DNA concentrations in the
range of 50 and 500 nM and has potential for handheld applications.

CNTs have also been extensively applied in the electrochemical detection of
biomolecules. CNT based electrochemical biosensors usually employ electrodes modified
with CNTS, or hybrid materials, such as CNT-conducting polymer composites, CNT-
metal nanoparticles, and other CNT based composites as their detection platforms. Direct
electron transfer promoted by the nanotubes between enzymes and the CNT modified
electrodes has enabled the widespread application of CNTs in enzyme based
electrochemical biosensors (Zhu et' al., 2007). CNT based electrochemical
immunosensors and genosensors have also been reported in the literature (Yun et al.,
2007;Chang et al., 2008).

2. 3. 2.2 Conducting Polymer Nanotubes

Conducting polymer nanotubes are the new class of one-dimensional nanostructures
that have found applications as biosensor transducers. Unlike CNT based sensors,
conducting polymer nanotube based sensors have the potential of achieving high
sensitivity without involving complicated reaction steps, purification or end open
processing (Chang et al., 2007b).

A polyaniline nanotube array based electrochemical biosensor reported by Chang et al.
enabled ultrasensitive detection of nucleic acids (Chang et al., 2007b). The authors
demonstrated a sensitivity of 1.0 M target DNA for the biosensor and selectivity of one-
nucleotide mismatch at concentrations as low as 137.59 N. Label-free DNA detection

using polypyrrole nanotubes has been shown by K0 et al. with a biosensor sensitivity of

36

1.0 nM target DNA (K0 and Jang, 2008). An aptamer conjugated amine-functionalized
polypyrrole nanotube based FET device has been developed by Yoon et al. (Yoon et al.,
2008) for the detection of the protein, human-a-thrombin. The device could detect 166
nM thrombin in blood serum samples.
2.3.3 Nanoparticle Based Biosm

Nanoparticles have unique physical, chemical, Optical, and electronic properties that
have made them appropriate for numerous applications in electrochemical sensors and
biosensors. Immobilization and labeling of different biomolecules such as enzymes,
antibodies, and DNA; acting as electrochemical catalysts and electron transfer agents;
and performing the function of reactants and magnetic concentrators are the basic
functions performed by these nanoparticles in sensing systems (Luo et al., 2006).
Discussed below are current developments in biosensors based on magnetic
nanoparticles, metal nanoparticles including gold and silver, and semiconductor
nanocrystalline particles (quantum dots).
2.3.3.1 Magnetic Nanoparticles

Magnetic nanoparticles (mostly superparamagnetic) have the ability to quickly
agglomerate and resuspend in response to changes in external magnetic field. These
unique properties of magnetic nanoparticles have led to their exploitation in various
separation processes and detection devices such as biosensors. Magnetic separation
techniques are widely used in bioengineering and biomedical applications such as
magnetic resonance imaging, gene delivery, drug delivery, diagnostics, immunoassays
and biosensors (Xu and Sun, 2007;Ludwig et al., 2006;Lee et al., 2006). In biosensor

detection, magnetic separation techniques can provide a number of advantages, such as,

37

elimination of nonspecific adsorption of interfering biomolecules by modifying surface
chemistries, elimination of sample pretreatment by centrifugation or chromatography thus
reducing analysis time, and exclusion of centrifugation steps thus reducing stress-induced
damages to biomolecules.

Varshney et al. have developed an impedance biosensor based on interdigitated array
microelectrode coupled with magnetic nanoparticle antibody conjugates for detection of

E. coli 0157: H7 in ground beef samples (Varshney and Li, 2007). The biosensor

provided rapid and specific detection of the pathogen with a sensitivity of 7.4 X 104

CFU/ml in pure cultures and 8.0 X 105 CFU/ml in ground beef samples in a detection

time of 35 min.

Magnetic nanoparticles have also been employed for concentrating and
electrochemical sensing of DNA targets in the literature. Zhu et al. have developed a
method for detecting DNA hybridization using magnetic nanoparticle modified pyrolitic

graphite electrode and the common electrochemical redox couple
K3[Fe(CN)6]/K4[Fe(CN)6] (Zhu et al., 2006b). Magnetoswitchable controlled DNA

hybridization was performed on DNA probe modified electrodes with subsequent
electrochemical detection of the redox indicator. The detection limit for the sensor was 2
nM target DNA. In a separate study, DNA hybridization at magnetic nanoparticles
coupled with electrochemical stripping detection of zinc sulfide nanoparticle tags on
glassy carbon electrode was used by Zhu et al. (Zhu et al., 2004).The authors were able
to attain sensitivity as high as 0.2 pmol /L with the described methods.

Lately, several sensing devices have been developed that perform the detection

process by measuring the magnetic properties of the magnetic nanoparticle tags. Kaittanis

38

et al. have reported a magnetic nanosensor for detecting Mycobacterium avium sp.
paratuberculosis (MAP) in blood and milk samples using magnetic relaxation switches
(MRS) (Kaittanis et al., 2007).The detection mechanism involved switching of
superpararnagnetic iron oxide nanoparticles between a dispersed and clustered state upon
target interaction and measurement of the resultant change in spin-spin relaxation time of
the protons in water solution. The authors were able to quantify MAP from 15.5 to 775
CFUs in milk samples using these magnetic nanosensors. A magnetic microarray was
developed by Wang et al. utilizing magnetic tunnel junction (MTJ) detectors which was
aimed at detecting single molecules of DNA on individual magnetic nanoparticle tags
(Wang et al., 2005). Wang and coworkers have also recently prototyped magneto-nano
chips using 8 X 8 array of 64 giant magnetoresistance (GMR) spin valve (SV) sensors
(Wang and Li, 2008). The authors were also able to successfully detect Human
Papillomavirus (HPV) DNA sequences using these GMR DNA chips at concentration
levels of 10 pM. A magnetic permeability meter (MPM-100) was developed by
Abrahamsson et al for DNA detection (Abrahamsson et al., 2004). The limit of detection
of the MPM sensor was 12 ug/ml in buffered solutions.
2. 3.3.2 Gold Nanoparticles

In the last few years, intensive research has been carried out in the field of gold (Au)
nanoparticle based biosensing devices. Au nanoparticles have a unique physical property
of localized surface plasmon resonance i.e. the change in color that arises in the
nanoparticles during aggregation (red-to-purple) or redispersion of aggregates (purple-to-
red) from interparticle plasmon coupling. The above principle has been applied in Au

nanoparticle based colorimetric biosensors for detection of different targets including

39

nucleic acids, proteins, saccharides, metal ions, small molecules and cells. A detailed
review on colorimetric biosensing assays has been provided by Zhao et al. (Zhao et al.,
2008).The ability of Au nanoparticles to provide a suitable microenvironment for the
immobilization of biomolecules retaining their bioactivity is a major advantage in
biosensor fabrication. In addition, Au nanoparticles facilitate direct electron transfer
between immobilized biomolecules and electrode surfaces without the use of electron
transfer mediators, thus making them appropriate for electrochemical biosensing
(Pingarron et al., 2008).

Panda et al. have developed an optical detection method for the rapid quantification
of bacterial cells using fluorescent Au nanoparticle-polymer composites (Panda et al.,
2008). The method is based on the loss of fluorescence intensity of positively charged Au
nanoparticle-polythiophene composites in the presence of bacterial cells. The detection
limit of the system was 1000 bacterial cells for both Gram-positive and Gram-negative
bacteria. A highly sensitive electrochemical immunosensor for the detection of S typhi
has been reported by Dungchai et al. using copper enhanced gold nanoparticles
(Dungchai et al., 2008). The presence of bacteria was detected by measuring the
concentration of released copper ions from copper deposited on the colloidal Au nanotags
using a copper enhancer solution by anodic stripping voltammetry. The authors reported
a detection limit of 98.9 CFU/ml using the electrochemical immunosensor. Wang et al.
have described a Quartz Crystal Microbalance (QCM) biosensor based on Au
nanoparticles for the real-time detection of E. coli 0157: H7 DNA in a circulating flow

system (Wang et al. , 2007c). The sensor was able to detect the target DNA corresponding

40

to 2.0 X 103 CFU/ml of E. coli 0157: H7 cells based on mass change and concomitant

frequency shifts of the QCM.

Au nanoparticle based biobarcode assays allow highly sensitive detection of DNA
sequences and are emerging as promising alternatives to polymerase chain reaction
(PCR) for DNA detection. Au nanoparticles heavily functionalized with oligonucleotide
probes are the building blocks of biobarcode assays. Hill et al. have reported a
biobarcode assay for the detection of B. subtilis genomic DNA (Hill et al., 2007). The
biobarcodes were detected by scanometric methods. The assay demonstrated a sensitivity
of 2.5 fM for double stranded genomic DNA. A fluorescent bio barcode assay for the
detection of the foodbome pathogen Salmonella Enteritidis has been reported by Zhang et
al. (Zhang et al., 2009a). Au nanoparticles were first coated with target specific DNA
probes and fluorescent labeled DNA barcodes. The DNA target was then sandwiched
between the Au nanoparticles and magnetic nanoparticle coated with second DNA probes
and separated by applying a magnetic field. The barcode DNA was released from the Au
nanoparticles and quantified by fluorescence measurements. The authors reported a

sensitivity of 1 ng/ml with the assay.

41

Magnetic nanoparticles

    

with 2 "‘1 probe
t” %
, W
—> ——->
Target DNA Barcode DNA

with 1 3‘ probe

 

——> ——+
Probe Barcode DNA
Separation

release

   

Figure 2-7. Schematic representation of Au nanoparticle based bio barcode assay
(Zhang et al., 2009a).

2.3.3.3 Semiconductor Nanoparticles (Quantum Dots)

Quantum dots (QDS) are luminescent nanocrystalline semiconductor particles that
are roughly spherical in nature with particle diameters ranging from 1 to 12 nm. QDS
have higher fluorescence quantum yields, better photoluminescence stability, and less
toxicity than organic fluorophores along with their size tunable fluorescent properties.
QDs are also resistant to photobleaching, denaturation of biomolecules and to variations
in pH and temperature. Multi color QD nanocrystals have the potential for multiplexed
and high-throughput analysis. These properties have made QDS suitable for application in
optical detection systems (Costa-Femandez, 2006;Sapsford et al., 2006;Pileni, 2001). QB

based optical biosensors can be roughly divided into luminescence-based and absorption-

42

based sensors depending on the changes of emission and absorption intensity (Comparelli
etal,2007)

Recently, Liu et al. have used multi-layers of quantum dots for rapid magnetic bead
based detection of E. coli 0157: H7 eae target DNA (Liu et al., 2008). The target DNA
was first captured on magnetic beads by probe hybridization and the signal was amplified
by using multi-layers of QDs. Fluorescence intensity measurements yielded a sensitivity
of 250 zM within 40-60 min using this method. Su et al. reported an antibody based
rapid, sensitive, and specific detection method for E. coli 0157: H7 using cadmium
selenide- zinc sulfide (CdSe-ZnS) QDS (Su and Li, 2004b). Magnetic beads coated with
anti- E. coli 0157: H7 antibodies were used to capture the target bacteria and were

labeled with QDs by streptavidin-biotin conjugation. Fluorescence intensity

measurements were proportional to E. coli 0157: H7 concentrations in the range of 103

to 107 CFU/ml with the total detection time being less than 2h. The detection system was

also selective against E. coli K12 and S. Typhimurium. Goldman et al. have utilized
CdSe—ZnS QDs conjugated with antibodies to perform multiplex fluoroimmunoassays for
the detection of cholera toxin, ricin, shiga-like toxin 1 and Staphylococcal enterotoxin B
(Goldman et al. , 2004).

QDs have also found suitable applications in fluorescence resonance energy transfer
(FRET) biosensors. The FRET technique relies on distance-dependant transfer of energy
from a donor fluorophore to an acceptor fluorophore. The narrow emission spectra and
the broad absorption spectra of QDS combined with their donor-acceptor separation
distance of 1-10 nm result in improved performance of QDS in FRET assays over organic

fluorophores. Zhang et al. reported an ultrasensitive DNA nanosensor based on FRET

43

using single QDs (Zhang et al., 2005a). The system used QDs conjugated with DNA
probes to capture DNA targets bound to dye-labelled reporter strands which formed a
donor-acceptor ensemble. The QDS acted as a target concentrator and signal amplifier in
the nanoscale domain. The nanosensor was capable of generating a strong FRET signal
when bound to 50 copies of DNA or less. Recently, a FRET biosensor based on Au
nanoparticles and QDS was developed by Stringer et al. for the detection of Porcine
Reproductive and Respiratory Syndrome Virus (PRRSV) (Stringer et al., 2008). The
biosensor consisted of two architectures; a PRRSV- specific capture antibody labeled
with a fluorescent dye bound to a QD labeled protein and a PRRSV- specific capture
antibody labeled with a fluorescent dye bound to a Au nanoparticle labeled protein. The
detection limit of the sensor was 3 particles /ul.

The metal components of the semiconductor nanoparticles in the QDS (CdS, PbS,
and ZnS) have intrinsic redox properties susceptible to sensitive electrochemical stripping
analysis thus making them suited for electrochemical biosensors. QD based
electrochemical biosensors have been reported in literature for detection of different
protein molecules and DNA but have not been applied in the detection of pathogenic
microorganisms (Thurer et al., 2007;Hansen et al., 2006). Pumera et al. have developed a
protocol for the detection of DNA hybridization based on magnetically triggered
electrochemical detection of Au67 QD tracers (Pumera et al., 2005). The authors reported
a detection limit of 12nM target DNA with this system.

2. 3.3.4 Silica Nanoparticles
Literature reveals that silica (Si) nanoparticles have been successfully used as

nanotransducers in electrochemical and fluorescence based biosensors and bioassays.

44

Zhao et al. have reported a rapid bioassay for the detection of a single bacterial cell of E.
coli 0157: H7 using fluorescent-bioconjugated silica nanoparticles (Zhao et al., 2004).
The authors were able to detect a single E. coli 0157: H7 bacterium within 20 min in
spiked ground beef samples with this bioassay. Multicolored FRET Si nanoparticles were
used by Wang et al. for multiplex monitoring of bacterial pathogens (Wang et al.,
2007b). Each dye doped Si nanoparticle encapsulated about 10,000 dye molecules in a 60
nm silica sphere which provided an extremely strong fluorescent signal for bioanalysis.
The authors reported simultaneous detection of E. coli, S. Typhimurium and S. aureus
with this assay in 30 min.

Ping et al. have developed a PCR based detection system for the detection of a
SARS Coronavirus gene using Si coated superpararnagnetic nanoparticles and Si coated
fluorescent nanoparticles (Gong et al., 2008). PCR amplified targets were concentrated
using Si coated magnetic nanoparticles and then hybridized with the Si coated fluorescent

nanoparticles in a sandwiched hybridization format. The limit of detection of the assay

was 2.0 X 103 copies in a total detection time of less than 6h. A sensitive electrogenerated
chemiluminescence (ECL) detection of DNA hybridization based on Ru(bpy)32+ doped Si

nanoparticles was developed by Chang et al. (Chang et al., 2006). The Ru(bpy)32+ doped

Si nanoparticles labeled DNA probes were first hybridized with DNA targets
immobilized on the surface of polypyrrole modified platinum electrodes. The

hybridization events were then detected by ECL signals. Using the ECL signals, the
authors were able to detect the target DNA at levels as low as 1.0 X 10'13 mol/l with

selectivity of a three base mismatch sequence and a non-complementary sequence.

45

2.3.4 Nanoporous Material Based Biosensors

Novel nanoporous materials such as porous silicon, porous carbon, and porous
alumina have recently found effective applications as biosensor transducers. Nanoporous
silicon, characterized by its high surface to volume ratio and photoluminescence
properties, has been employed in more than one biosensor transduction mechanisms.
Mathew and Alocilja developed a pathogen biosensor for the detection of E. coli
exploiting the optical properties of nanoporous silicon (Mathew and Alocilja, 2005). The
reaction of B-galactosidase enzyme from E. coli with a dioxetane-polymyxinB mixture

functionalized on porous silicon chips generated light at 530 nm. Light emission
measurements from the porous silicon biosensor demonstrated a sensitivity of 101-102

CFU/ml for the pathogen. Electrochemical detection of targets using nanoporous silicon
platforms has been reported by Zhang et al. (Zhang and Alocilja, 2008). The authors
fabricated nanoporous silicon with P-type silicon wafers by electrochemical etching and
applied them in the detection of DNA targets for the foodbome pathogen Salmonella
Enteritidis. The sensitivity of the biosensor based on the electrical properties of DNA,
redox indicators, and cyclic voltammetry was 1 ng/ml. The extremely high surface area
of nanoporous silicon films have also been used for sensitive detection of the
bacteriophage virus MSZ by Rossi et al. (Rossi et al., 2007). Porous silicon films were

used to selectively capture dye-labeled M82 viruses from solution and a sensitivity of 2 X
107 plaque-forming units per ml (PFU/ml) were reported by the authors by measuring

fluorescence from the exposed porous silicon film.
Bothara et al. (Bothara et al., 2008) have developed an electrical immunoassay based

on nanoporous alumina membranes for the sensitive detection of proteins. The detection

46

principle involves the formation of electrical double layer and the perturbations caused by
proteins trapped in a nanoporous alumina membrane over a microelectrode array
platform. Label-free electrical detection of protein biomarkers for cardiovascular
diseases, C-reactive protein and (CRP) and myeloperoxidase (MPO) were achieved
through this assay. The lower detection limits for CRP and MP0 were 200 pg/ml and 500
pg/ml respectively.

Porous conductive carbon has been shown to be a good matrix for biosensor
construction. The high conductivity of carbon is suitable for electrochemical transduction
and in combination with its porosity makes it ideal for adsorption Of biomolecules.
Nanoporous carbon has been successfully used for the construction of acetylcholine
esterase biosensor by Sotiropoulou and Chaniotakis (Sotiropoulou et al. , 2005).

2.3.5 Nanorod and Nanosghere Based Biosensors

Gold nanorods have been successfully employed in optical biosensors. Marinakos et
al. have developed a label-free chip-based localized surface plasmon resonance (LSPR)
biosensor using gold nanorods (Marinakos et al., 2007). The biosensor monitored
streptavidin binding to biotin by studying the LSPR peak shifts at the gold nanorod
surface. The biosensor sensitivity was 94 pM in phosphate buffered saline and 19 nM in
serum. Multiplex detection of three different IgG molecules was also achieved on gold
nanorods of different aspect ratios fabricated by a seed-mediated growth by Yu and
Irudayaraj (Yu and Irudayaraj, 2007). A gold/silicon hetero nanorod biosensor was
developed by Fu et al. for detection of the foodbome pathogen Salmonella Typhmurium

(Fu et al., 2008). The hetero nanorods were functionalized with anti-Salmonella

47

antibodies and detection was accomplished through fluorescence signaling mediated by
multiple Alexa488 dye molecules bound on the nanorods.

Different nanospheres viz. silica, nickel oxide (NiO), cadmium sulfide (CdS), and
magnetic gold are being currently utilized as bioSensor transducers in literature. NiO
hollow nanospheres have been used for glucose biosensing by Li et al. (Li et al. , 2008). A
novel nitrite biosensor based on direct electron transfer of hemoglobin (Hb) immobilized
on CdS hollow nanosphere modified glassy carbon electrode has been reported by Dai et
al. (Dai et al., 2008). Thionine doped magnetic gold nanospheres synthesized by reverse
micelle method have enabled ultrasensitive electrochemical immunosensing of
carcinoembroyonic antigen protein by Tang et al. (Tang et al., 2008). The use of
fluorescent silica nanospheres as luminescent signal amplifiers in detecting the breast
cancer marker HER2/neu in a simple glass slide based assay has been reported by Rossi

et al. (Rossi et al. , 2006).

48

2.4 POLYANILINE — A CONDUCTING POLYMER
2.4.] Introduction

Polymers containing loosely held electrons in their backbones are referred to as
conjugated polymers or conducting polymers and have attracted considerable interest for
the past two decades. Research on conducting polymers intensified after the rediscovery
of polyacetylene in 1977 by McDiarmid and Heeger. They were able to enhance the
electrical conductivity of polyacetylene by many orders of magnitude by simple doping
with oxidizing and reducing agents (Gerard et al., 2002). The presences of u—electron
backbones in the conducting polymers result in their unusual electronic properties, such
as high electrical conductivity, low ionization potential, and high electron affinity. They
are also known as ‘intrinsically conducting polymers’ due to the presence of partially
filled molecular orbitals which allow free movement of electrons throughout the polymer
lattice and overlapping molecular orbitals which allow the formation of delocalized
molecular wave functions. These types of polymers have also attracted interest for their
nonlinear Optical properties, since the electrons in these delocalized systems are easily
polarized by an external electric field. These polymers have been considered to be as
“molecular wires” for nanotechnology (German and Grubbs, 1991). As a result of such
unusual properties, conducting polymers have a number of practical applications, such as
in electronic displays, telecommunication, electrochemical storing systems, and
molecular electronics and sensors (Hohnholz et al., 2005;Kaneto et al.,
2007;Ramanavicius et al., 2006). Table 2-1 shows the chemical structures and

conductivity of some common conducting polymers.

49

Table 2-1. Chemical structure and conductivity of typical conducting polymers

(adapted and modified from Rahman et al., 2008).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Conducting Polymer Structure Conductivity (S/cm)
Polyacetylene N ~ 1000
n
Polyparaphenylene ‘83} 100 ~ 500
n

|
Polyparaphenylene ~3
vinylene

n
Polyazulene ~0 .l
O n
,-

l‘

Polyaniline --©—N 1~ 100
x n
Polypyrrole N 40 ~ 100
Polythiophene I :3: ‘ 10 ~ 100
n
Polycarbazole O N O 10 ~ 100
.1. n

NH2

Polydiaminonapthalene 10 '3
NH2

 

50

 

2.4.2 Structure and Electrical Progerties

Among all conducting polymers, polyaniline is intensely investigated particularly
due to its excellent stability in different solutions, good electronic properties, and strong
biomolecular interactions (Feast et al., 1996;Ryder et al., 1997). Polyaniline is
synthesized from its monomer form, aniline. There are two basic methods of polyaniline
synthesis: chemical synthesis and electrochemical synthesis. The chemical synthesis
involves step-growth polymerization of an aqueous solution of the monomer in the
presence of an oxidizing agent and a protonating acid. In the aqueous acidic media,
aniline cation radicals are the first product of the oxidation. The aniline cation radicals
then recombine into benzidine and N-phenyl-p—phenylenediamine, or, participate in the
growth of polyaniline chains in the perrrigraniline form. The oxidative polymerization
reaction continues according to equations 2-3 and 2-4 until all the pemigraniline is

converted into emeraldine by equations 2-5 and 2-6 (Stej skal and Gilbert, 2002).

.NH; ‘__—-_, .NH2+ H++ e
(2-3)

R‘NHz + .NHZ ‘__——:_—;
+. +. +
RHNNH2 + 2H + 26
(2-4)

51

820:} 26 3:; 2804' (2-5)

tear-t +e -——»
Ml

(2-6)

The electrochemical synthesis of polyaniline is carried out in a typical
electrochemical bath by adopting a standard three-electrode configuration. The standard
three-electrode system usually comprises of a working electrode, a counter electrode and
the reference electrode. The electrochemical polymerization generally employs a constant
current or galvanostatic, constant potential or potentiostatic or potential scanning/cycling
methods (Ahuja et al., 2007). The commonly used working electrodes are chromium,
nickel, gold, platinum, palladium and glass coated with tin oxide or indium tin oxide.

2. 4. 2.1 Oxidation States

The conducting polymer, polyaniline, exists in a variety of forms differing in

electrical conductivity and color. The general chemical structure of polyaniline has been

H

O 1* C I

N

shown in Figure 6, where, indicate the reduced repeat units, and
-~-©=~O

indicate the oxidized repeat units of the polymer.

52

H H
N N =

N
Reduced unit Oxidixed unit 14y

— ‘

 

 

 

K
Figure 2-8. Structure of polyaniline, x = degree of polymerization, [y + (l-y)] = 1.

(Ray et al., 1989)

There are three distinct oxidation states of the polymer, namely, “leucoemeraldine”,
“emeraldine” and “pemigraniline”. The fully reduced form of polyaniline is
“leucoemeraldine” (l-y = 0, y =1), while “pemigraniline” (l-y = 1, y = 0) is the fully
oxidized form of polyaniline and “emeraldine” (y = l-y = 0.5) is the 50% oxidized form
of polyaniline (Ray et al. , 1989). Each oxidation state of the polymer can exist in its base
form or its protonated form (salt) by treatment of the base with acid.

Interconversion between the different forms of polyaniline occurs during the
oxidative polymerization of aniline which imparts electrical conductivity and color to the
different forms. The most important and stable form of polyaniline is protonated
emeraldine which is green in color and electrically conductive. It is produced directly by
the oxidative polymerization of aniline. When stronger oxidizing conditions are
employed, it converts to protonated pemigraniline which is blue and is expected to be
conducting. Further treatment with alkali results in pemigraniline base which is violet
and non-conducting. The acid-base transition occurs at pH 0-1. Emeraldine can also be

reduced to the colorless, non-conducting, leucoemeraldine form (Stej skal et al., 1996).

53

2. 4. 2.2 Electronic Conduction

It is well known that the electrical conduction properties of elemental
semiconductors, such as Si, can be rigorously controlled by addition of small quantities
of foreign atoms into the semiconductor lattice. The semiconductors can be made n type
or p type depending on the nature of the dopant atoms, i.e. whether it has an excess or
deficit of electrons. The electrical conduction in conjugated or conducting polymers can
also be explained by a similar terminology. However, the doping mechanism in
conducting polymers is considerably different from the conventional semiconductors.
Firstly, the doping levels are significant in conjugated polymers (as large as 10 mole
percent) and secondly, there is charge transfer between the incorporated dopant atom and
the polymer chain, hence the later is partially oxidized or reduced (Lyons, 1994). The
partial oxidation of the polymer chain is termed as p-doping while partial reduction is
termed as n-doping.

Electrical conductivity results (0) from the existence of charge carriers and the
ability of those carriers to move. It is expressed as,

c = nep (2-7)

where, n is the number of charge carriers per unit volume, e is the electronic charge and u
is the carrier mobililty. Hence, doped conjugated polymers or conducting polymers are
good conductors for two reasons; firstly, doping introduces charge carriers into the 112-
electron system of the polymer and since every monomer is a potential redox site, they
can be heavily doped, and secondly, the 712- bonding leads to 7t- electron delocalization

along the polymer chains thereby leading to charge carrier mobility which is extended

54

into three dimensional transport by interchain electron transfer interactions (Heeger and
Smith, 1991).

The half-oxidized form of polyaniline (i.e. emeraldine) is the most studied and the
most stable form of polyaniline. The emeraldine base form of polyaniline has been found
to be different from other polymers in several aspects. First, it is not charge conjugation
symmetric in contrast to polymers such as polyacetylene and polythiophene. Second,
both the carbon rings and the nitrogen atoms in polyaniline are within the conjugation
path forming a generalized “A-B” polymer. Third, the C6 benzenoid rings of polyaniline
can rotate or flip thus significantly altering the electronic structure (Pouget et al. , 1991).

It has been shown that the emeraldine base form of polyaniline can be reversibly
varied from an insulator (o < 10'10 ohm'lcm'l) to a conductor (0 ~ 10 Ohm’lcm'l) through

protonation (Epstein et al., 1987). The doping of emeraldine base with a non-oxidizing
protonic acid such as HCl involves a new concept. Unlike the doping of all other
conducting polymers, the number of electrons in the polymer backbone remains
unchanged (Macdiarmid et al. , 1987). Unlike other doped conducting polymers which are
polycarbonitun ions or polycarbanions, the emeraldine salt polymer is based on a
“nitrogenonium” ion polymer in which the positive charge resides chiefly on the nitrogen
(Macdiarmid et al. , 1987).

The conductivity of polyaniline is believed to be due to the analogous protonation of
emeraldine base which leads to the formation of a polysemiquinone radical cation
(polaron) and gives rise to a polaron conduction band by coulombic repulsion leading to a

metallic state (Macdiarmid et al., 1987).

55

i“ N/
l j,
H Protonation
(b) 1' <2x>ll+ T
N i
ii i“ l
H H ' x
(c) Internal Redox Reaction
H H
| I
N ”/31.
ll 1 l
H H X
Polaron Separation
(d) Ill H
|
‘1‘!- ”A"!
\i i J
H H 2X

Figure 2-9. Structure of emeraldine (polyaniline), (a) before protonation and (b) -

(d) after protonation, (b) formation of bipolarons, (c) formation of polarons, and (d)

the separate polarons which result in a polaron lattice (adapted from Stafstrom et

al., 1987).

56

A model based on two-step transition from isolated, doubly charged spinless,
bipolarons to a polaronic metal has been suggested by Stafstrom et al (Stafstrom et al.,
1987). The first step relates to instability of a bipolaron on a polyemeraldine chain which
results in the formation of two polarons, and the second step involves the separation of
the polarons to yield a polaron lattice (Stafstrom et al., 1987). Figure 2-9 shows the
changes in the structure of polyaniline as suggested in the above model.

Figure 2-10 shows the band structure of a conjugated polymer as a function of
doping level which illustrates the polaronic and bipolaronic states in the band gap. A
neutral polymer acts as an insulator and has a full valence band and an empty conduction
band which is separated by a band gap. Removal of an electron by doping results in the
generation of a polaron level at the midgap. Further oxidation results in the removal of a

second electron to generate a bipolaron.

CONDUCTION BAND

 

 

 

 

 

 

 

 

 

 

 

 

 

I

E9 A
VALENCE BAND
|
I

Neutral polymer Polaron Bipolaron
Via 1e- oxidation Via 2e-oxidation

 

 

 

     

‘— Doped polymer _’

Figure 2-10. Band structure of conjugated polymers showing polaronic and

bipolaronic states.

57

2.4.3 Electrochemistgy and Redox Switching

The electrochemical preparation of polyaniline has typically been carried out in
aqueous electrolytes galavanostatically, potentiostatically or through cycling of the
potential of the substrate anode. Several electrolytes have been successfully used for the
synthesis of polyaniline such as hydrochloric acid, perchloric acid, sulfuric acid, nitric
acid, trifluoroacetic acid and fluoroboric acid (Delvaux et al., 2000;Duic et al.,
1994;Duic et al., 1995;Pan et al., 2006;Wei and Ivaska, 2006)with the polymer being
deposited on diverse substrates such as platinum, gold, indium tin oxide, carbon and
stainless steel (Bereket et al., 2005;Mazur et al., 2002;Tang et al., 1996;Wei et al.,
2008;Zhang et al., 2009b). Investigation of the electrochemical properties (redox
switching) of polyaniline is considered to be the key factor in understanding the physical
and chemical properties of polyaniline.

The redox switching process of polyaniline has been studied for many years using
various kinds of voltammetry. The concomitant processes that occur during the redox
switching of polyaniline are as follows: (a) cyclic voltammetry reveals that two peaks are
associated with the switching of polyaniline from the fully reduced leucoemeraldine state
to the conducting emeraldine state and from the emeraldine state to the fully oxidized
pemigraniline state; (b) the conducting emeraldine state of polyaniline exits in a potential
window instead of a fixed potential; (c) the redox switching property of polyaniline
depends mainly on the pH of the medium and in neutral or alkaline medium, the polymer
loses its electrochemical activity; ((1) the redox behaviour of polyaniline is fundamentally

asymmetric; and (e) the oxidation transition occurs at a lower rate than that of the

58

reduction transition (Gospodinova et al., 1996;Grzeszczuk and Szostak, 2003;Hong and
Park, 2005).

The redox transition of polyaniline usually occurs in the potential range of -200 to
400mV (saturated calomel electrode) and is accompanied by proton ejection or injection.
There is a proton ejection during the oxidation of a fully relaxed polymer from the
leucoemeraldine form to emeraldine form and from it to fully oxidized form, while the
reduction of the polymer is accompanied by protOn injection which is incomplete because
of the slow proton equilibration process (Ybarra et al., 2000;Lyons, 1994). The redox
switching in polyaniline is also accompanied by a small increase in volume of the
polymer. Several factors such as water and ion exchange with the electrolyte, coulombic
repulsion between charged sites in the polymer backbone, anion-polymer interactions,
and a structural change of the polymer backbone govern the swelling of the polymer
during the switching process (Lizarraga et al., 2004).

The effect of pH on the electrochemical activity of polyaniline has been studied by
authors (Prakash, 2002). Cyclic voltammograms (CVS) of polyaniline films on a Pt
working electrode and Ag/AgCl reference electrode were recorded in HCl solutions in the
pH range of 1-4 by the author (Figure 2-11). At pH 1.0, three reversible anodic peaks and
their corresponding reduction peaks, were observed. As the pH was increased, a shift in
one redox peak toward lower potential values which merged into a single broad peak at
pH 4.0 occurred This peak was associated with the involvement of protons in the redox
reaction which made the peak pH dependant, whereas, the other peaks only involved

transfer of electrons (Prakash, 2002).

59

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60

2. 4.3.1 Cyclic Voltammetry
Cyclic voltammetry is a form of linear sweep voltammetry in electrochemistry where

the potential applied to the working electrode of a three electrode electrochemical cell is

ramped linearly versus time between an initial potential (E 1) and a final potential (E2).

When the potential reaches E 2, it is ramped back to the initial potential of E]. This
ramping of the potential is known as the scan rate and is usually expressed in V/s or

mV/s. For a reversible redox system, the resulting current (I) measured while scanning
the potential is represented with respect to the potential (E) in a typical cyclic
voltammogram. Figure 2-12 shows a typical I-E curve (cyclic voltammogram) for a
redox system. The voltammogram is characterized by a peak potential Ep, a potential
corresponding to the point where the measured current reaches its maximum value Ip. In

Figure 2-12, [pa and 1pc indicate the anodic and cathodic peak currents and End and Epc
indicate the anodic and cathodic peak potentials, respectively. Two parameters that are of

interest in the I -E curves are the ratio of the peak currents [pa/1pc, and the separation
peak potentials, Epa —Epc.

For a reversible system, the peak current, IP, is given by the equation

1/2
F3 .
1p = 0.4463[fi] n3/2AD3/2C0V1/2 (2-8)

where, F = Faraday’s constant (Q mol'l), R = universal gas constant (J mol'lK'l), T =

temperature (K), n = no. Of electrons exchanged in the reaction, A = area of the electrode

surface (cmz), D0 = diffusion coefficient of the electroactive species (cmz/s), C5:

61

concentration of the electroactive species (mol/cm3), and v = scan rate (V/s) (Bard and
Faulkner, 2001).

Similarly, the peak potential, Ep, for a reversible system is given by the equation

RT
Ep =E,,2—1.109E (2-9)

For systems with stable product (reversible reactions), the following two conditions

should be satisfied: the anodic peak current should be equal to the cathodic peak current,
i.e., [pa/1pc = 1 and the separation of the anodic and cathodic peak potentials should obey

the following equation:

IAEPI = lEpa—Epc = 0.059/n (2-10)

 

For totally irreversible redox systems, Ep is a function of scan rate, shifting (for
reduction) in a negative direction by an amount of about 0.03V ten fold increase in v
whereas in quasi-reversible systems, 1,, is not proportional to v (Bard and Faulkner,

2001).

62

I (A;

Cathode

 

so?)

Anode

 

Figure 2-12. Typical cyclic voltammogram (I-E curve) for a redox system.

Cyclic voltarnmtery is a very powerful tool for electrochemical studies of new
systems and provides useful information on complicated electrode reactions. The current
research will investigate the diagnostic strength of cyclic voltammetry in evaluating the
concentration of an electrically active species from peak current heights.

2.4.4 ElectricgflLv-Active Magnetic Polyaniline

Magnetic polymer nanostructures are a new class of materials where magnetic
nanoparticles are embedded in polymer matrices. Such nanostructures have attracted
considerable interest in recent years due to their immense potential for applications in
electromagnetic devices, drug targeting, cell separation, enzyme immunoassays and
electromagnetic interface shielding (Asmatulu et al., 2005;Boissiere et al., 2006;El-
Tantawy et al., 2004). Multi component systems containing conducting polymers and

nanoparticles of metal oxides have the advantages of non-corrosiveness, light weight,

63

mechanical strength and dielectric tunability along with novel magnetic and optical
properties (Poddar et al., 2004b). Polyaniline is the most studied conducting polymer in
such multi component systems due to its unique properties such as controllable electrical
and chemical properties, excellent environmental stability and simple and low cost
synthesis (Ray et al., 1989).

The general approach for the synthesis of such magnetic polyaniline nanocomposites
or nanoparticles is polymerization of the monomer aniline around a magnetic core or

template nanoparticle as represented in Figure 2-13.

Oxidizing agent

 

””2 Acid

 

Template Aniline Magnetic polyaniline

Figure 2-13. Synthesis of electrically-active magnetic polyaniline (Li et al., 2007b).

Till date, the most common magnetic nanomaterials that are used in the synthesis of
magnetic polymer composites are iron oxides and ferrofluids. A review of the magnetic
properties of iron oxides has been provided by Kryszewski et al (Kryszewski and Jeszka,
1998). Some of the most important properties as mentioned by them are: (a) electrostatic
exchange dominates for Fe ions at adjacent sites, (b) the specific saturation magnetization
of iron oxide nanoparticles decrease with increase in specific surface of the nanoparticle
and is also influenced by the particle morphology, (0) surface hydroxyl groups by
adsorption of water make iron oxide nanoparticles amphoteric so that they can react both

with acids and bases, and (d) the acidity and reactivity of differently coordinated iron

64

changes. According to Kryszewski et al. the incorporation of iron oxide nanoparticles
into polymer matrices involves specific interactions with ligands which replace the

surface hydroxyl groups as represented in Figure 2-14.

L L L
| / \ /
777- 0 777— 770777—077 770777077-
| \ Fe / I |
Fe Fe Fe
Mononuclear Mononuclear Binuclear

Figure 2-14. Polymer ligand interactions to iron oxide particle surfaces (L = ligand)
(Kryszewski and Jeszka, 1998).

Under ideal circumstances, nanoparticles can exhibit novel magnetic properties when
they exist as isolated particles. A critical obstacle in maintaining a nanoscale magnetic
material is its tendency to agglomerate (Kryszewski and Jeszka, 1998). For practical
applications, a collection or aggregate of nanoparticles or nanopowders are more
prevalent. The dispersion of the nanoparticles in the polymer matrix is also a critical issue
and needs extensive research. The competition between polymer-polymer and polymer-
particle needs to be balanced in order to achieve good dispersion and avoid clustering of
particles in the polymer composites (Alam et al., 2007).

Recent literatures suggest that different kinds of magnetic nanoparticles are being
used as a core or template for the synthesis of electrically active magnetic polyaniline
nanostructures. Table 2-2 shows a brief review of electrically active magnetic polyaniline
nanostructures available in the literature. The size range of the synthesized nanostructures

varies from 30 nm to 5 pm and their magnetization values are in between 0.76 and 181

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66

2.4.5 Polyaniline in Biosensor Apglications

Conducting polymers such as polyaniline have gained. popularity in biosensor
applications due to the following reasons:

0 Flexible chemical structure that allows modulation of the required electronic and

mechanical properties of the polymer.

0 Suitable immobilization matrix for biomolecules providing suitable environment

for the immobilization.

0 Associated with efficient transfer of electric charge produced by biochemical

reaction to electronic circuits.

0 Can be deposited onto electrode surfaces which provide them with the versatility

of being used in diverse biosensor platforms.

0 Control over parameters such as polymer layer thickness, electrical properties and

bio-reagent loading.

Langer et al. have developed an enzyme based biosensor for detection of the amino
alcohol, choline, using nanostructured polyaniline layers of controlled porosity and
micrometer or nanometer thickness (Langer et al., 2004). The enzyme choline oxidase
was immobilized in the nanoporous polyaniline layers which were useful in trapping the
enzymes due to coulombic interactions between the positively charged polyaniline and
negatively charged polar groups in the enzyme molecules. The authors were able to
enhance the electrical response of the biosensor by continuous charging and discharging
of the polyaniline molecules in presence of the enzyme. The sensitivity of the sensor as

reported by the authors was 5 pA mmol/L in the amperometric mode and 10 mV mmol/L

67

in the potentiometric mode, with the detection limit being 20 mmol/L for choline in the
potentiometric mode.

An antibody based polyaniline biosensor was developed by Muhammad-Tahir et al.
for detection of the bovine viral diarrhea virus using indium tin oxide (ITO) as the
platform (Tahir et al., 2007). The ITO glass was spin coated with self-doped polyaniline
which served as a matrix for immobilization of antibodies specific to the Virus. The
antibody modified electrodes were then treated with 1 ml of the viral culture for 30 min.
The detection process involved measurement of the amperometric response of the
antibody modified polyaniline spin coated ITO electrodes before and after treatment with
, the viral culture in a three electrode electrochemical cell.

Malhotra and coworkers have reported polyaniline based nucleic acid sensors for
detection of E. coli and Mycobacterium tuberculosis genomic DNA. Avidin modified
polyaniline was electrochemically deposited on a Pt disk electrode and immobilized with
biotin labeled E. coli probes (Prabhakar et al., 2008;Arora et al., 2007). Direct detection
of E. coli was performed using differential pulse voltammetric technique in the presence
of methylene blue as DNA hybridization indicator. The authors were able to detect 0.01
ng/uL of E. coli genomic DNA and 11 E. coli cells/mL within 605 to 14 min. Detection
of M. tuberculosis genomic DNA was achieved by the same authors using polyaniline

modified gold electrodes and PNA as the bio-recognition element. The authors reported a
detection limit of 0.125 X 10'18M in a 5 min sonicated M. tuberculosis genomic DNA

within 1 min of hybridization time.
Polyaniline has been used in numerous biosensing applications, viz, amperometric,

potentiometric, conductometric, optical, calorimetric and piezoelectric biosensors.

68

Different biomolecules ranging from enzymes, microorganisms, and antibodies to nucleic
acids have been employed in the polyaniline based biosensors. Detailed information on
the different polyaniline and conducting polymer based biosensors can be found in
review articles by Wei et al., Malhotra et al., and Gerard et al. (Wei and Ivaska,

2006;Malhotra et al., 2006;Gerard et al., 2002).

69

CHAPTER 3: RESEARCH HIGHLIGHTS

3.1 RESEARCH NOVELTY

The innovativeness of this research lies in exploring the prospect of a novel
nanostructured material (electrically active magnetic polyaniline, EAPM, nanoparticles)
in the dual function of a magnetic concentrator as well as a biosensor transducer. The
dual potential of this novel nanomaterial was exploited in the development of a nano-
biosensor for food safety and biodefense. The versatility of the nanomaterial was
demonstrated in both antibody based and DNA based biosensor detection systems. The
nanobiosensor described in this study is novel in terms of design and application. Current
literature shows a considerable amount of research on polyaniline and magnetic
polyaniline synthesis. A sizeable number of applications can be found in the use of
polyaniline transducers in biosensors as well. Extensive literature is also available in
magnetic concentration procedures using different micro- and nano- magnetic particles.
However, till date no literature has been reported that employ EAPM nanoparticles in an
integrated design of biosensor transduction and magnetic concentration in one system.
Table 3-1 demonstrates the novelty of this research in contrast to existing literature. The
shaded regions indicate the absence of any current literature in these areas and the

contribution of this research to the knowledge base at this point of time.

70

Table 3-1. Novelty of research as compared to existing literature

 

 

 

 

 

 

 

 

 

 

Parameters Current Comments
literature

Polyaniline synthesis (Li et al. , One dimensional nanostructures,

2007a) vanadic acid oxidant, size-10/50 nm
Polyaniline based antibody (Sai et al. , Piezoelectric immunosensor, IgG
biosensor 2006) detection
Polyaniline based DNA (Chang et al. , Alumina electrode, electrochemical
biosensor 2007a) detection of synthetic Oligos
Electrically active magnetic (Li et al. , Polyaniline-hydroxyl iron, diameter:
polyaniline (EAPM) synthesis 2007b) 0.5-5 pm
EAPM based antibody
biosensor
EAPM based DNA biosensor
EAPM nanoparticles as redox
indicators in DNA detection
Magnetic particles as cell (Yang and Li, Impedance detection of Salmonella,
concentrator in biosensor 2006) Dynabeads®, diameter-2.8 pm
Magnetic particles as DNA (Yeung and Electrochemical detection of E. coli,
concentrator in biosensor

Hsing, 2006)

commercial beads, diameter-3 um

 

EAPM as cell concentrator

 

 

EAPM as DNA concentrator

 

 

 

71

 

3.2 ESEARCH SIGNIFICANCE

Electrically active polyaniline coated magnetic (EAPM) nanoparticles couple the
flexibility of the conducting polymer, in terms of its chemical, electrical and mechanical
properties, with the magnetic properties of the core material, iron oxide. EAPM
nanoparticles when adopted in biosensors are expected to provide several advantages in
detection. The nanoscale dimensions of the EAPMS will impart an increased surface to
volume ratio for biological events to occur. Appropriate biological surface modification
of the EAPMs can bring them in close proximity to targets for achieving fast assay
kinetics, e.g., rapid antigen-antibody interactions. In addition, magnetic manipulation Of
the EAPMs can minimize matrix interference due to improved separation thus avoiding
pre-enrichment and pre-treatment procedures commonly practiced in food and
environmental samples. Hence, magnetic manipulation will be advantageous in reducing
sample processing time and background signal in detection devices. Furthermore, the
electrical, electrochemical, and magnetic properties of the EAPMs will present multiple
options in designing biosensor platforms. The compatibility of the polymer surfaces in
EAPMS with biomodification procedures will add to the versatility of these biosensor
platforms. .

As described above, EAPM nanoparticles hold great promise in future biosensing
applications. The current research developed an antibody based and a DNA based EAPM
biosensor with high sensitivity and specificity and rapid detection time. Two different

biosensor platforms involving different transducing mechanisms were examined.

72

3.3

HYPOTHESIS

This research was based on the following hypothesis:

3.4

Electrically-active polyaniline coated magnetic (EAPM) nanoparticles can be
synthesized and modified with different biological detecting elements such as
antibodies and DNA.

The magnetic properties of the EAPM nanoparticles will concentrate biological
targets such as whole cells and DNA.

The electrical properties of the EAPM nanoparticles can be exploited in different
biosensor transducing mechanisms to report a biodetection event.

The dual function of the EAPM nanoparticles can be demonstrated using B.

anthracis as the model pathogen

RESEARCH OBJECTIVES

The specific Obj ectives of this research are as follows:

Objective 1: Synthesis and characterization of EAPM nanoparticles.

Objective 2: Design and fabrication of an EAPM based immunosensor for detection of B.

anthracis spores.

Objective 3: Evaluation of sensitivity and specificity of the EAPM based immunosensor

and determination of EAPM immunomagnetic capture efficiency

Objective 4: Fabrication of an EAPM based electrochemical DNA biosensor for detection

of B. anthracis.

Objective 5: DNA hybridization on EAPM NPS and sensitivity and specificity evaluation

of the EAPM based electrochemical DNA biosensor.

73

CHAPTER 4: RESEARCH MATERIALS & METHODS

4.1 OBJECTIVE]
Synthesis and characterization of electrically active polyaniline coated magnetic
(EAPM) nanoparticles (NPS)

This objective was aimed at synthesizing the EAPM NPS following a chemical
synthesis procedure and performing magnetic, electrical, and structural characterization
studies of the NPs for assessing their suitability and applicability prior to developing the
biosensors.

4.1.1 EAPM Nanogarticle Synthesis

The EAPM NPS were synthesized from aniline monomer made electrically active by

acid doping and gamma iron (III) oxide (y-Fe203) NPS (Sharma et al., 2005). The 7-

FezO3 NPS were obtained from a commercial source (Sigma-Aldrich, MO). These NPS

were dispersed in a mixture of 50 ml 1M HCl, 10 ml de-ionized water and 0.4m] of
aniline by sonication for 1h at 0°C to disintegrate the agglomerated nanoparticles. This
was followed by a slow drop-wise addition of the oxidant, ammonium persulfate, at a rate

of 0.1 ml/min with continuous stirring of the above solution mixture which resulted in
coating of polyaniline on the smaller y-Fe203 NPS. The above reaction was continued for

an additional 4 h in an ice bath and the final product was filtered followed by subsequent

washings with 1M HCl, methanol and diethyl ether. The product obtained was dried for
48 h at room temperature. Four different weight ratios of y-FezO3: aniline monomer

(1:0.1, 1:0.4, 1:06, and 1:0.8) was maintained in the synthesis procedure (from literature)

with increasing concentrations of the monomer.

74

 

 

NH2
+ HCI >
(NH4)25203

Aniline

Figure 4-1. Schematic representation of polyaniline coating of gamma-iron oxide

nanoparticles.

4.1.2 EAPM Nanoparticle Characterization

4. I . 2.1 Magnetic Characterization

A superconducting quantum interference device (Quantum Design MPMS SQUID)
was used for magnetic characterization and room temperature hysteresis measurements of
the synthesized EAPM NPs. The M-H hysteresis loop measurements for the four
different EAPM samples (1:0.1, 1:0.4, 1:0.6, and 120.8) were performed at a constant
temperature of 300K with the magnetic field cycling between + 20 kOe and -20kOe. The

saturation magnetization (Ms) values of the EAPM NPS were determined in emu/gm and
were compared with that of bare y-Fe203 NPS. The coercivity (Hg) and retentivity (MR)
of the NPs were also determined from the hysteresis loop measurements in order to study
the presence of super paramagnetic behavior in these samples. Zero field cooled-field

cooled (ZFC-FC) measurements were performed for the 120.6 EAPM NPS for a

temperature range of 5K to 300K at an applied magnetic field of 100 Oe in order to
determine the blocking temperatures of the EAPM NPS.

4. 1.2.2 Electrical Characterization
The electrical conductivity of the four different EAPM samples (1:0.1, 1:0.4, 120.6,

and 120.8) was evaluated in the solid form. Approximately, 0.25 gm of each sample was

75

compressed into pellets of 1.5 to 2 mm thickness using a hydraulic press (Fisher
Scientific, NJ) and applying a pressure of about 10,000 psi. Room temperature electrical
conductivity of the compressed pellets was then measured using a Four Point Probe
(Lucas/Signaton Corporation, Pro4, CA).
4.1.2.3 Structural Characterization

The structural morphology of the four types of EAPM NPS were analyzed using both
transmission electron microscope (TEM, Japan Electron Optics Laboratories, JEOL
100CX II) and scanning electron microscope (SEM, JEOL 6400V). The crystalline nature
of the EAPM NPs was studied by selected area electron diffraction using the 200kV
JEOL 2200 field emission TEM. In order to confirm the presence of the polymer,
elemental analysis of the EAPM NPs was performed by X-ray energy dispersive
spectroscopy using the JEOL 6400 SEM at an accelerating voltage of 20 kV and a
working distance of 15 mm.
4.1.2.4 Spectral Analysis

The UV-visible spectra of the four different EAPM samples were obtained using a
UV-VIS-NIR Scanning spectrophotometer (UV-3101PC, Shimadzu, Kyoto, Japan). The
EAPM NPs were at first dispersed in de-ionized water at a concentration of 1 mg/ml by
sonication for 10 min. 1 ml of the nanoparticle suspension was transferred into a quartz
cuvet (10 mm path length) and the absorbance was measured by the scanning the sample

for a wavelength range of 300 to 1000 nm using a step size of 1 nm.

76

4.2 OBJECTIVE 2
Design and fabrication of an EAPM NP based immunosensor for the detection of B.
anthracis spores.

This objective was aimed at designing and constructing an antibody based biosensor
detection system using EAPM NPS as magnetic concentrator and biosensor transducer for
the rapid detection of B. anthracis (Sterne) spores as a model pathogen.

4.2.1 Biosensor Design and Data Collection

The biosensor was comprised of three distinct membrane pads: sample application
pad, capture pad, and absorption pad. The dimensions of the overall as well as different
biosensor zones are presented in Table 4-1. The membrane pads were arranged on a
polystyrene adhesive backing with silver electrodes fabricated 0.5 mm apart on the
capture membrane. The application and the absorption pads were made of cellulose
membranes with a flow rate 180 ml/min and the capture pad was made of nitrocellulose
membrane with a flow rate of flow rate 135 sec/4cm according to the manufacturer’s
specification (Millipore, Bedford, MA). For data collection, the fabricated biosensor unit
was attached to an etched copper printed circuit board (PCB) and connected to a portable
multimeter [BK Precision, Model 390A, range: 4009 - 40MQ, resolution: 0.1!) - 10k (2,
accuracy: i (0.5 to 1.5% rdg + 4 digits), sampling rate: 2 measurements per second] with
RS-232 interface to a computer. The biosensor architecture and the data collection system

are shown in Figure 4-2 along with a picture of the setup.

77

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78

Table 4-1. Dimensions of the EAPM based immunosensor.

 

 

Biosensor Zone Dimension (mm)
Application 20 X 5
Capture 23 X 5
Absorption 17 X 5
Overall 60 X 5

 

4.2.2 EAPM Based Immunosensor Fabrication
4. 2. 2.1 Chemicals and Reagents

Tris-HCl buffer, glutaraldehyde, polysorbate 20 (Tween 20), peptone water, and
sodium phosphate (dibasic and monobasic) were purchased from Sigma-Aldrich (St.
Louis, MO). Mouse monoclonal anti-anthrax IgG (clone 2C3) and polyclonal goat anti-
anthrax combo IgG molecules were obtained from Chemicon International (Millipore,
CA) whereas anti—goat IgG-FITC (whole molecule) was obtained from Sigma- Aldrich
(St. Louis, MO). Nitrocellulose and cellulose acetate membrane pads for the biosensor
were purchased from Millipore (Bedford, MA). Conductive micro tip pen used for
dispensing silver electrodes were procured from Chemtronics (Kennesaw, GA). De-
ionized water from Millipore Direct-Q system was used for preparing all reagents.
4. 2. 2.2 EAPM Antibody Modification

The synthesized EAPM NPs were conjugated with mouse monoclonal anti-B.
anthracis IgG molecules by direct physical adsorption of the antibodies onto the NPs
(Figure 4-3). The EAPM NPS (100 mg/ml) were dispersed in 100 mM phosphate buffer
(pH-7.4) by sonication for 10 to 20 min and mixed with anti- B. anthracis IgG
(150ug/ml) antibodies. The reaction mixture was incubated for 1 h at 25°C in a rotational

hybridization oven (Amerex Instruments Inc., CA). After incubation, the IgG labeled

79

NPs (immuno-EAPMS) were magnetically separated to remove the supernatant using a
magnetic separator (Spherotech, IL). The resulting immuno-EAPMs were washed three
times with a blocking buffer consisting of 100 mM Tris-HCl buffer (pH-7.6) and 0.1%
(w/v) casein. Finally, the immuno-EAPMS were suspended in 100 mM phosphate buffer

(ph-7.4) and stored at 4°C.

Y
+ YYY Adsorption» ®

Magnetic EAPM NPs Monoclonal Antibodies Antibody Labeled EAPM NPs

 

Figure 4-3. Modification of EAPM NPs with monoclonal antibodies.

4. 2. 2.3 Biosensor Capture Pad F unctionalization

Figure 4-4 illustrates the functionalization of the biosensor capture pad for
polyclonal antibody attachment. The nitrocellulose biosensor capture membrane pads
were first cleaned with de-ionized water followed by 10% methanol (v/v) for 45 min and
dried at room temperature. The cleaned membranes were treated with 0.5 %
glutaraldehyde solution (v/v) for 1 h and dried at room temperature. After drying, the
glutaraldehyde activated capture membranes were coated with polyclonal goat anti-B.
anthracis IgG (SOOug/ml) using a reagent dispensing module (Matrix 1600, Kinematic
Automation Inc., CA) and incubated for 1 h at 37°C. Finally, the membrane surface was
washed with blocking buffer consisting of 100 mM Tris-HCl (pH-7.6) and 0.1% (v/v)

Tween 20 and incubated for 45 min at 37°C to inactivate the residual aldehyde groups.

80

The antibody modified membranes were dried at room temperature and stored at 4°C

before use.

O=CH(CH2)3CH=O

 

Lia—n-u—HEEJ + OBCHNH2)3CH"O'—___> '

Capture Pad Glutar aldehyde Functionalized Capture Pad
Crosslinker

    

Blocking <——

<——— YNH2¥NH2

Antibody Attachment Polyclonal Antibodies

 

Figure 4-4. Functionalization of biosensor capture pad for attachment of polyclonal _

antibodies.

4. 2.2.4 Application and Absorption Pad Preparation

The application and the absorption cellulose membrane pads of the biosensor were
washed with de-ionized water to remove dirt and surface residues. The membranes were

then air-dried and stored in a clean container before being assembled into the biosensor.
4.2.2.5 Sensor Assembly

The application, capture and the absorption pads after preparation were assembled
according to the arrangement as shown in Figure 4-2 (A) with the membrane pads
overlapping one another. After assembly, the biosensors were cut into 5 mm strips using
a programmable shear module (Matrix 2360, Kinematics Automation Inc. CA, USA).
Silver electrodes were fabricated on the capture membrane surface at 0.5 mm distances
apart using silver conductive ink (Chemtronics, GA) and the biosensor strips were

connected to the data acquisition systems as described as shown in Figure 4-2 (B).

81

4.2.2.6 Antibody Attachment Confirmation Studies

The antibody modification of the EAPM NPs was confirmed and investigated by
measuring the absorption of IgG molecules using a UV-VIS-NIR Scanning
Spectrophotometer (UV-3101PC, Shimadzu, Kyoto, Japan). The UV spectrum of pure
anti- B. anthracis IgG (150ug/ml) molecules and that of the unreacted IgG molecules
present in the supernatant after magnetic separation of the immuno-EAPMs was studied
by scanning the samples for a wavelength range of 200 nm to 400 nm using a resolution
of 1.0 nm. The attachment of polyclonal anti- B. anthracis IgG molecules on the
biosensor capture pad was confirmed by a Laser Scanning Confocal Microscope
(Olympus Fluoview 1000). The antibody modified biosensor capture pad was labeled
with secondary anti-goat IgG-FITC molecules using a working dilution of 1:320.
Fluorescence was observed by excitation with 488-nm line of argon-ion laser and

detection of emission using a 505 nm long pass filter.

4.3 OBJECTIVE 3
Evaluation of sensitivity and specificity of the EAPM NP based immunosensor and
determination of EAPM immunomagnetic capture efficiency.

This objective was aimed at determining the sensitivity of the fabricated EAPM
based immunosensor in pure suspensions of B. anthracis spores and artificially
contaminated food matrices, determining the immunosensor specificity in non-target
bacterial cultures, and in determining the capture efficiency of EAPM NPs in

immunomagnetic concentration procedures.

82

4.3.1 Bacterial Culture and Plating

Characterized strains of Bacillus anthracis (Sterne) and Bacillus cereus were
obtained from the Michigan Department of Community Health (Lansing, M1) for
performing sensitivity studies with the immunosensor. Generic E. coli and Salmonella
enterica Serovar Enteritidis (S-64) strains from the collection of the Biosensors
Laboratory were used for specificity experiments. The Bacillus strains and generic E. coli
were grown in trypticase soy broth (TSB, Difco) while lactose broth (Difco) was used for
growing Salmonella Enteritidis. The cultures were grown in an incubator (Fisher
Scientific, IA) at 37°C for 24 h and were enumerated by spiral plating in the appropriate
. plating media followed by colony counting after 24 and 48h. Both the plating and colony
counting were performed using automated equipments (Microbiology International, MD,
USA).

4.3.1.] B. anthracis Sporulation Protocol

Sporulation of B. anthracis (Sterne) cells was promoted following a previously
published protocol (Pezard et al., 1991). B. anthracis vegetative cells from a 24 h
enrichment culture were streaked on Nutrient Yeast Broth (NYB) agar slopes and
incubated at 30°C for seven days. Sporulation was monitored by Schaeffer-Fulton
staining and light microscopy. Once the sporulation was greater than 90%, the spores
were harvested by suspending them in 5 ml sterile de-ionized water and incubating at
65°C in waterbath for 30 min to kill the remaining vegetative cells. The spores were
collected by centrifugation at 12000 rpm for 3 min, and re-suspended in 5ml of sterile de-
ionized water. Finally, the total spore count was estimated using a disposable

hemocytometer (C-Chip DHC-NOl, Fisher Scientific, Pittsburg, PA) and the viable

83

spores were enumerated by microbial plating in trypticase soy agar (TSA II) with 5%
sheep blood plates (BD Biosciences, MD) and counting the colonies after 16 and 36h.
The spore suspension was stored at 4°C for fixture use.
4.3.2 lmmunomaggetic Concentration using EAPM NPs

Following the antibody modification procedure, the antibody coated EAPM NPs

(immuno-EAPMS) were added to different concentrations of B. anthracis spore
suspensions (10l to 107 spores/ml) in order to have a final immuno-EAPM concentration

of 20 mg/ml. The amount of EAPM NPs to be used in the immunomagnetic
concentration procedure was determined from prior studies with B. cereus as target
pathogen. The mixture was incubated with gentle shaking in a hybridization oven
(Boekel Scientific, PA) for 10 min at room temperature. The immuno-EAPM-spore
complexes formed were magnetically separated from the unbound spores, to remove the
supernatant and washed twice with sterile de-ionized water before re-suspending in 10 ml
sterile de-ionized water.
4.3.3 Biosensor Testing

One hundred microliters of the immuno-EAPM-spore complexes obtained after
immunomagnetic concentration was applied carefully to the application pad of the
biosensor. The flow time of the sample from the application pad to the capture pad was
approximately 1 min. Recording of the resistance signal across the biosensor electrodes
was started from 2 min and carried for a total time of 6 min as determined from prior
studies (Pal et al., 2007). Resistance measurements were also made before applying the
sample to the biosensor to ensure that the biosensor strips were not conductive before

sample application. Three trials were performed for each set of experiments. All

84

biosensor testing were performed inside a Class II Biosafety Cabinet (Model 1284,
ThermoElectron Corporation, OH).
4.3.4 Biosensor Sensitivity Stud!

Pure spore suspension of B. anthracis was used to assess the sensitivity of the EAPM

biosensor. The B. anthracis spores stock solution was serially diluted to spore
concentrations ranging from 100 to 107 spores/ml. The performance of the four different
EAPM samples (1:0.1, 120.4, 110.6 and 1:08) was evaluated in the detection of B.
anthracis spores prior to choosing the best nanoparticle type for the sensitivity analysis.
Three different spore concentrations (101, 104 anle7 per ml) were used in this
comparison study. The biosensor sensitivity was then determined using the EAPM NPs
that showed the best biosensor performance in the above study in spore concentrations
ranging from 100 to 107 per ml. All biosensors were baselined against a negative control

solution containing EAPM nanoparticles in sterile water (concentration-20 mg/ml).
4.3.5 Biosensor Specificity Analysis
Pure cultures of generic E. coli and S. Enteritidis were used for determining the

specificity of the EAPM biosensor. Twenty four hour enrichment cultures of generic E.
coli and S. Enteritidis were serially diluted to cell concentrations ranging from 101 to 105

CFU/ml using sterile 0.1 % (w/v) peptone water. The immuno-EAPMS were added to
appropriate cell concentrations of the desired bacteria to obtain a final immuno-EAPM
concentration of 20mg/ml. The immunomagnetic concentration and biosensor detection
procedure was similar to that as described in Sections 4.3.2 and 4.3.3. The resistance
signal generated was compared statistically with positive and negative control samples of

B. anthracis spores to evaluate the biosensor specificity.

85

4.3.6 Biosensor Testing in Food Matrices

The efficiency of the EAPM biosensor was tested in three different food matrices.
Romaine lettuce, lean ground beef, and ultra-pasteurized whole milk, was purchased from
a local grocery store. For the lettuce and beef samples, 25-g samples were weighed,
mixed with 225 m1 of 0.1% (w/v) peptone water in a Whirl-Pak plastic bag, and
stomached in a stomacher (Microbiology International, MD) for 1 minute. The whole
milk sample was used as purchasedl Nine milliliters of the three kinds of liquid samples
were thoroughly mixed with 1 ml of appropriate concentrations of B. anthracis spore

stock solution. Finally, a series of 10 ml samples inoculated with B. anthracis spores at
concentrations ranging from 101 to 107 spores/ml were obtained.

Following the food sample preparation, immuno-EAPMs (20 mg/ml) were mixed
with different concentrations of the B. anthracis spore inoculated food matrices.
Immunomagnetic concentration of B. anthracis spores from the food matrices and
biosensor testing was performed according to the procedure described in Section 4.3.2
and 4.3.3. EAPM NPs suspended in the liquid samples (20 mg/ml) obtained from the
three different food matrices without inoculated B. anthracis spores was used as a
negative control.

4.3.7 Statistical Analysis

Statistical analysis of the biosensor data was performed using the SAS software
(SAS, Cary, NC). The means and standard deviations of the biosensor resistance signals
for. all samples were calculated on the basis of data from three replicates and the
differences between the means were compared using analysis of variance (ANOVA) to a

significance of 95% ((1 =0.05). Factorial ANOVA analysis (Two-way ANOVA with

86

slicing of interactions) was performed to determine the interactive effects of EAPM NP
type and spore concentration as well as the double interaction of both factors on the
biosensor resistance responses in the EAPM comparison study. For sensitivity study, the
two-way interaction of spore concentration and time was analyzed. For specificity
analysis, interactive effects of different pathogen types, cell concentrations as well as
combined effect of both factors were studied using two-way ANOVA. Single factor
analysis of variance was performed on the food sample data.
4.3.8 Confirmation and EAPM Capture Efficiency Calculations

The immunomagnetic capture of B. anthracis spores using EAPM nanoparticles
from pure spore suspension and different food matrices was confirmed by microbial
plating in TSA II blood agar plates. One hundred microliters of the immuno-EAPM-spore
complexes obtained after immunomagnetic concentration was used for plating. Triplets
of each sample were plated. The viable spore count was enumerated after 16 to 36h. The

capture efficiency (CE) of the EAPM nanoparticles was calculated using the equation:

Cb
CE(%)= Zn 100

where, C, is total concentration of viable spores in the sample (CPU/ml), and Cb is the

concentration of viable spores bound to the EAPM nanoparticles (CFU/ml).

87

4.4 OBJECTIVE 4
Fabrication of an EAPM based electrochemical DNA biosensor for detection of B.
anthracis.

This objective was aimed at developing an electrochemical DNA biosensor system
using EAPM NPs for target DNA concentration as well as biosensor transduction for the
detection of Bacillus anthracis protective antigen (pagA) gene.

4.4.1 Biosensor Desigg and Data Collection

A screen printed three electrode sensor (Gwent Group, UK) was used in the
electrochemical detection of DNA targets. The sensor chip had an overall dimension of
22 X 12 mm with a circular working electrode of 4 mm diameter and a partially circular
(270°) common reference and counter electrode of 1.5 mm width. Screen printed carbon
acted as the working electrode while screen printed silver/silver chloride (Ag/AgCl) acted
as the common reference and counter electrode on a polyester backing. The screen
printed carbon and silver ink had a resistance of 50 Ohms at 12 microns, and 320 mOhms
at 25 microns, respectively, according to the manufacturer’s specifications. Figure 4-5
shows the architecture of the screen printed carbon electrode (SPCE) biosensor. For data
collection, the SPCE biosensor units were connected to a Potentiostat/ Galvanostat

(Model 263A, Princeton Applied Research, OakRidge, TN).

88

   

—> Polyester Backing

 

Reference & Counter Electrode
(Common)

‘———> Working Electrode

 

Figure 4-5. Screen printed carbon electrode biosensor.

4.4.2 Chemicals and Reagents

Sodium chloride (NaCl), sodium phosphate (monobasic and dibasic), sodium acetate,
phosphate buffered saline tablets (0.01M), formamide, ethylene diamine tetra acetic acid
(EDTA), isopropanol, ethanol, sodium dodecyl sulfate (SDS), proteinase K, hydrochloric
acid (HCl), Trizma base, ethidium bromide, gel loading solution and Streptavidin from

Streptomyces avidim'i were purchased from Sigma Aldrich (St Loius, MS). AccuPrimeTM

Taq DNA Polymerase system, UltrapureTM DNAse RNAse free water and UltrapureTM

agarose were purchased from Invitrogen Corporation (Carlsbad, CA). QIAquick PCR
purification kit was procured from Qiagen Inc. Valencia, CA. EDC (1-ethyl-3-[3-
dimethylaminopropyl] carbodiimide hydrochloride) was obtained from Pierce (Rockford,

IL).

89

4.4.3 Selection and Analysi_s of DNA Primers and Probes

The primers pairs for PCR, and the capture and detector probes for the biosensor,
were designed and selected from the protective antigen (pag A) gene, while the non-
complementary sequence was selected from the capsular (cap A) gene of Bacillus
anthracis (Song et al., 2005). Detailed information on the sequences of the probes and
the primer pairs has been shown in Table 4-2. The specificity of the primer and the probe
sequences were analyzed using the Basic Local Alignment Search Tool (BLAST).
4.4.4 Extraction, Amplification and Characterization of B. anthracis DNA
4. 4. 4.] DNA Extraction

Genomic DNA was extracted from a 24 h enrichment culture of B. anthracis using a
modified protocol for mammalian DNA extraction (Laird et al., 1991). One ml of the
overnight culture was transferred into a 1.5 ml microcentrifuge tube and centrifuged for
10 min at 13000 rpm to precipitate the DNA. The supernatant was discarded and the
remaining pellet was re-suspended in 500 pl of lysis buffer (IOOmM Tris HCl, 5mM
EDTA, 0.2% SDS, 200 mM NaCl) and Sul of proteinase K solution. The tube was placed
in a waterbath for 75 min at 55°C and then introduced in ice. Five hundred microliters of
isopropanol was added to the tube and mixed, followed by freezing the tube for 30 min at
- 80°C. The precipitated DNA was recovered by centrifugation for 15 min at 13000 rpm
followed by addition of 500 pl of pre-cooled ethanol solution and centrifugation at 13000
rpm for 15 min. Finally, the supernatant was discarded and the pellet was dried to and

resuspended in 100 u] of DNAse and RNAse free water.

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The concentration of the extracted double stranded target DNA was determined by
measuring the absorbance of the sample at 260 nm using a spectrophotometer (Bio-Rad
SmartSpec 3000).
4. 4. 4.2 Polymerase Chain Reaction (PCR) Amplification and Optimization

Polymerase chain reaction of the extracted target DNA was performed using a DNA
thermocycler (Eppendorf, Westbury, NY). The SOul PCR reaction mixture consisted of

template DNA, forward and reverse primers, PCR buffer [1X], 2’-deoxynucleoside 5’-

triphospate (dNTP) mix [0.2 mM], magnesium chloride (MgClz) [1.5 mM], and In] of

AccuPrimeTM Taq DNA Polymerase. The PCR amplification reaction was optimized
with respect to the amount of DNA template, the concentration of forward and reverse
primers, the melting temperature (Tm) and the reaction time in order to obtain the best

amplification of targets. All PCR reactions were performed inside a PCR Workstation
(Fisher Scientific, IA).
4. 4. 4.3 PCR Product Purification

The amplified PCR product was purified using the QIAquick PCR purification kit.
Five volumes of the buffer PB was mixed with 1 volume of the PCR product. The sample
was then applied to a QIAquick column that was placed in a 2 ml collection tube for
binding DNA. The column was centrifuged for 60 s and the flow-through was discarded.
For washing, 750 pl of the buffer PE was added to the QIAquick column, centrifuged for
60 sec, and the flow-through was discarded. The QIAquick column was then placed back
in the collection tube and centrifuged for 60 sec. Finally, to elute the DNA, the QIAquick
column was placed in a clean 1.5 ml microcentrifuge tube, 50 pl of DNAse RNase free

water was added to the column and it was centrifuged for 60 sec.

92

4. 4. 4.4 PCR Product Characterization

The results from PCR amplification and purification were confirmed by performing
gel electrophoresis in ethidium bromide stained 2.5 % agarose gels using a mini gel
electrophoresis system (EmbiTec, San Diego, CA) at 50 Volts for 30 min. The amplified
PCR bands were then observed in a Gel Documentation system (Fotodyne Incorporated,

Hartland, WI). The concentration of the purified PCR DNA was determined using the
NanoDropTMIOOO spectrophotometer (ThermoScientific, Wilmington, DE). Two

microliters of the DNA sample was placed in the sample holder of the spectrophotometer
and the UV-VIS absorbance was measured at 260 nm.
4.4.5 EAPM-DNA Probe Labeling Study
4. 4. 5.1 EAPM-DNA Modification

The EAPM NPs (1:0.6) were labeled with the single stranded phosphorylated
detector DNA probes (Ph-PRO) through the formation of phosphoramidate bonds
between the amino groups present in the polyaniline of EAPM NPs and the phosphate
group of the oligonucleotide based on a procedure previously described by (Zhu et al.,
2006a). The EAPM NPs were first suspended in 100 pl of the Ph-PRO probe solution
[22.5 uM] containing 10 mM sodium acetate buffer (pH 5.2) and 0.1 M l-ethyl-3-[3-
dimethylaminopropyl] carbodiimide hydrochloride (EDC). The mixture was incubated
with shaking in a rotational hybridization oven at room temperature for 4 h (Amerex
Instruments Inc., CA). Finally, the Ph-PRO DNA probe attached EAPM NPs (PRO-
EAPMs) were separated by a magnetic separator and washed repeatedly with acetate
buffer and DNAse RNAse free water to remove the unbound probes. Figure 4-6 shows

the cross-linking chemistry between the NPs and the detector probe.

93

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3'M—o/ \HN/. «—

EAPM Linked DNA Probe Magnetic EAPM Nps
(Phosphoramidate Bond)

Figure 4-6. Crosslinking chemistry between the detector DNA probe and magnetic
EAPM NPs.

4. 4. 5.2 Confirmation and Optimization

The attachment of the Ph-PRO detector probes to the EAPM NPs were confirmed by
fluorescence measurements performed in a Microplate Fluorometer Reader (V ictor3,

Perkin Elmer, MA) and UV-VIS absorbance measurements performed in a NanoDrop
1000 Spectrophotometer. For the fluorescence confirmatory experiment, the Ph-PRO
probes were labeled with 6-carboxy flouorescein (6-FAMTM) at 3’ end. Fluorescence of
the pure 6-FAMTM labeled Ph-PRO probe solution and that of the unreacted probes
remaining in the supernatant after magnetic separation of the PRO-EAPMS was observed
by excitation at 495 nm and detection of emission at 520 nm. The UV-VIS absorbance at
260 nm of the pure probe and the supernatant solution was also measured. The optimum

concentration of the EAPM NPs for labeling with the Ph-PRO probes was determined

94

from the fluorescence and absorbance measurements by keeping the Ph-PRO probe
concentration fixed at 22.5 uM and varying the NP concentrations as 0.1, 1, 10 and 20
myml
4.4.6 SPCE Surface Modification

The SPCE surface was modified with streptavidin for biosensor measurements. Forty
microliters of streptavidin solution (1mg/ml) prepared in 0.1M phosphate buffer (pH-7.0)
was added onto the working electrode surface and incubated for 2 h at room temperature.
The electrodes were then dried for an additional 30 min and were ready for use in

biosensor experiments. As a result, the working electrode surface was coated with

approximately 0.8 pig/mm2 of streptavidin.

4.5 OBJECTIVE 5
DNA hybridization on EAPM NPs and sensitivity and specificity evaluation of the
EAPM based electrochemical DNA biosensor.

This objective was focused on hybridizing the amplified B. anthracis target gene
fragment to the PRO-EAPMs for integration onto screen printed carbon electrodes for
determining the sensitivity and specificity of the EAPM based electrochemical DNA
biosensor.

4.5.1 Sandwiched Hybridization of DNA Targm EAPM NPs
4. 5. 1.1 Sandwiched Hybridization Protocol

The PCR amplified DNA targets were hybridized dually with the detector probe

labeled EAPM NPs (PRO-EAPMS) and the biotinylated capture probes (PRO-Bio) based

on a hybridization protocol adapted and modified from Song et al. (Song et al., 2006).

95

Before hybridization, the pmified PCR product was denatured by heating at 95° for 10
min in the thermocycler and cooling in icebath for 5 min, followed by a second cycle of
heating at 95° for 5 min and cooling for 5 min to separate the double stranded DNA
fragments into single strands. One hundred microliters of the denatured PCR product was
then diluted with 35 ul of hybridization buffer composed of 2M NaCl and 0.2M
phosphate buffer (pH-7.4) and added to appropriate concentrations of the PRO-EAPMs
and the PRO-Bio probes. The hybridization reaction was carried out in a hybridization
oven. The EAPM-Target-Biotin DNA hybrids were then washed twice with his ethylene
diamine tetracetic acid (TE) buffer (1X, pH-7.4) for 1 min by magnetic separation of the
EAPM NPs to remove the unbound target DNA. This was followed by washing the
EAPM NPs with 20% forrnarnide in 0.01M phosphate buffered saline (PBS) at 50° for 1
min by magnetic separation to remove the nonspecifically bound DNA targets. Finally,
the EAPM-Target—Biotin DNA hybrids were resuspended in 40ul of DNAse RNAse free
water.
4.5.1.2 Optimization of Hybridization Conditions and Confirmation

Optimization and confirmation of the hybridization conditions was performed in two
steps. The first step involved hybridization of the target DNA with the PRO-EAPMS
which was confirmed through fluorescence assays using the Microplate Fluorometer
Reader. Fluorescence labeled PCR amplified target DNA was obtained using 5’ 6-FAM
labeled reverse primers in the PCR reaction. The hybridization time and temperature for
the target DNA with the PRO-EAPMS was determined by observing the supernatant
fluorescence after hybridization of the 6-FAM labeled PCR product with PRO-EAPMs

and magnetic separation by excitation at 495 nm and measurement of emission at 520

96

nm. Three different hybridization temperatures (25°C, 45°C and 55°C) and three different
hybridization times (30 min, lb and 2h) were trialed.

The second step involved confirmation of the sandwiched hybridization of the PRO-
Bio probes with the target DNA using the Optimized conditions obtained from the above
study through fluorescence assays. Five prime 6-FAM labeled PRO-Bio probes were
used in this study. Three different concentrations of 6-FAM labeled PRO-Bio probes
(1 uM, 5 uM and lOuM) were used to confirm the dual hybridization event by measuring
the fluorescence of the pure probe solution and that of the supernatant after magnetic
separation.
4.5.2 Electrochemical Detection Using SPCE Biosensor
4. 5. 2.1 Electrochemical Characterization of EAPM NPs

Prior to detection of the target bound EAPM NPs on the SPCE biosensor, the
detection of straight EAPM NPs on the SPCE sensor surface was performed using cyclic
voltammetry. One hundred microliters of EAPM NP solution (concentration -100 ug/ml)
in 0.1M HCl was applied to the SPCE sensor and allowed to equilibrate for 10 min.
Cyclic voltammetry was performed using a Potentiostat/Galvanostat with two vertex
potentials in the ramp mode. A potential window between -0.4V and +1.0V was used.
The scan rate was varied in between 20 and 200 mV/s.
4. 5. 2.2 Detection of EAPM- T arget-Biotin DNA Hybrids

The EAPM-Target-Biotin DNA hybrids obtained after sandwiched hybridization
were carefully added to the streptavidin modified working electrode surface of the SPCE
biosensor. The DNA hybrids were allowed to react with the avidin coated sensor surface

for 15 min at room temperature. The electrodes were then rinsed with DNAse RNAse

97

free water for three consecutive times to remove any unbound EAPM NPs from the
surface and left to air dry for 15 min. One hundred microliters of 0.1M HCl solution was
added to the SPCE surface and the electrodes were allowed to equilibrate for 5 min.
Cyclic voltammetry was performed in the ramp mode with a potential window between -
0.4 V and +0.1V at a scan rate of 20 mV/s. Three trials were performed for each set of
experiments.

4.5.3 SPCE Biosensor Sensitivity Study

For the sensitivity study, the purified PCR products were serially diluted to
concentrations ranging from 10'1 ng/ul to 10'5 ng/ul using DNAse RNAse free water.

Each PCR concentration was then dually hybridized with the PRO-EAPM and the PRO-
Bio probes according to the procedure described in Section 4.5.1.1. The sensitivity of the
biosensor was determined by performing electrochemical detection of the hybrids
obtained from the serially diluted PCR products following the procedure described in
Section 4.5.2.2. A negative control consisting of EAPM NPs (concentration: lmg/ml)
suspended in DNAse RNAse free water was tested for comparison. Base line curves for
bare SPCE biosensor and streptavidin modified SPCE biosensor in 0.1M HCl was
obtained for each experiment.
4.5.4 Statistical Analysis

For each experiment, the cyclic voltammetry (CV) data was obtained as a current vs.
potential (I vs. E) curve of 1020 pair of points, half of which corresponded to the
oxidation reaction of the cycle, and the other half corresponded to the reduction reaction.
The oxidation (anodic) and reduction (cathodic) peak potentials were first determined for

EAPM NPs from the electrochemical characterization of the EAPM NPs. The oxidation

98

(anodic) and reduction (cathodic) peak currents were then determined at the
corresponding peak potentials for each experimental run. For sensitivity analysis, only
the anodic peak current was chosen for convenience. The means and standard deviations
of the anodic peak current for all target concentrations were determined on the basis of
data from three replicates and the differences between the means were compared using
single factor analysis of variance (ANOVA) to a significance of 95% ((1 =0.05) using the
SAS software.
4.5.5 Specificity Analysis

Specificity experiments for the SPCE biosensor were conducted using synthetic non-
complementary (NC) DNA sequences. Dual hybridization of the NC sequences with
PRO-EAPM and PRO-Bio probes were performed following the procedures described in
Sections 4.5.1.1. Different concentrations of the NC sequences (luM, SuM, and lOuM)
prepared by diluting the stock in DNAse RNAse free water. Nonspecific hybridization of
the NC sequences with the PRO-EAPMs was monitored by fluorescence assays using a
microplate fluorometer reader with 5’ FAM labeled NC sequences. Fluorescent intensity
measurements at 520 nm were compared between pure 5’ FAM labeled NC sequences

and the supernatant remaining after the dual hybridization event.

99

CHAPTER 5: RESULTS AND DISCUSSION

5.1 QiJECTIVE 1
Synthesis and characterization of electrically active polyaniline coated magnetic
(EAPM) nanoparticles (NPs)

5.1.1 EAPM Nanoparticle Characterizatiop

The change in mass magnetization (M) in the presence of a sweeping magnetic field

(H) for the four different EAPM NPs (1:01, 1:04, 1:06, and 1:08) as well as the
unmodified y-FezO3‘NPs is shown by the M—H hysteresis measurements performed at

300K in Figure 5-1. The key magnetic parameters are extracted from the hysteresis

measurements and have been tabulated in Table 5-1. The saturation magnetization (M3)
for the unmodified y-FezO3 NPs is found to be 64.4 emu/ g, whereas for the four different

EAPM NPs, the Mg values range from 61.1 to 33.5 emu/g. All five systems show a
tendency to saturate at an applied field of 20 kOe. The gradual decrease in the Ms value
with increase in the polymer (polyaniline) content is expected due to the surface
interactions between polyaniline, which is diarnagnetic in nature, and the iron oxide NPs

(Alam et al., 2007). As observed in Table 5-1, the coercivity (Hg) for all four EAPM NPs
are the same as the unmodified F e203 NPs i.e. 200 Oe, thus indicating that the anisotropy
energy of the magnetic NPs is not affected by the presence of polyaniline (Poddar et al.,
2004a). The remanent magnetization (MR) values for the NPs vary between 15.3 and 9.18
emu/ g. The high He and finite MR values in the EAPM NPs indicate that hysteresis is not

completely absent in the NPs, thus suggesting that the NPs are still in the ferromagnetic

phase (Sorensen, 2001).

100

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Table 5-1. Magnetic parameters measured for the EAPM NPs.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

. . Remanent Saturation
EAPM. Coercmty Magnetization Magnetization
Composrtlon (300K) (300K) (300K)
(y-Fe203:Amllne) HC (Oe) MR (em u/g) Ms (em u/g)
1:0 200 14.4 64.4
1:0.1 200 15.3 61.1
120.4 200 9.57 40.3
120.6 200 9.48 37.7
1:08 200 9.18 33.5
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Figure 5-2. Experimental FC-ZFC magnetization curves for 1:0.6 EAPM NPs at 100
Oe.

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Figure 5-2 shows the comparison of field cooled (FC) and zero field cooled (ZFC)
curves for the 1: 0.6 EAPM NPs in the temperature range of 5 to 100K at an applied field
of 100 Oe. The characteristic sharp change in magnetization associated with the well
established ferromagnetic to superparamagnetic transition in single domain particles is
absent in the FC-ZF C curves (Sorensen, 2001). The FC-ZFC results thus indicate that the
nanoparticles within the polymer matrix are predominantly in the ferromagnetic regime at

room temperature and are consistent with the experimental M-H data.

Conductivity results for the unmodified y-Fe203 and the synthesized EAPM NPs are
shown in Figure 5-3 and Table 5-2. Pure iron oxide NPs have electrical conductivity as
low as 10'5 S/cm thus exhibiting an insulating behavior. The synthesized EAPM NPs
have conductivities in the range of 10'2 to 100 S/cm. As observed in Figure 5-3, the
conductivity of the EAPM NP pellets show an exponential increase in the electrical

conductivity with decreasing Fe203 content from 90 wt. % to 55 wt. % in the 1:01 to
1:0.8 EAPM samples. The conductivity of the 1: 0.4 (71 wt. %) EAPM (7.68 x 10" S/cm)
is an order of magnitude higher than that of the 1:0.1(90 wt. %) NP (9.2 X 10'2 S/cm) and

similarly, the 120.6 (55 wt. %) and 1:0.8 (62 wt. %) NPs (1.1 x 10°, 2.43 x 10° S/cm)

show conductivities an order of magnitude higher than the 1:04 (71 wt. %) NP. The
conductivity of the EAPM NPs decrease with increasing iron oxide content due to the
insulating property of the oxides which partially block the conductive path in the polymer

matrix (Zhang and Wan, 2003 ;Zhang et al., 2005b).

103

 

 

 

 

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Figure 5-3. Room temperature electrical conductivity of the EAPM NPs.

Table 5-2. Conductivity values measured for the EAPM NPs.

 

 

 

 

 

 

 

EAP M C0mP9Sffi°n Fe203 Content Pellet Thickness Conductivity at
('y-Fe203:Anlllne) (Wt. %) (Hm) 300K
(s /cm)
1:0 100 1488 0.00005
1:01 90 1683 0.092
104 71 1476 0.768
120.6 62 1983 1.129
1:08 55 1938 2.436

 

 

 

 

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Transmission electron microscope (TEM) images were used to study the structural
morphology and size distribution of the unmodified y-Fe203 and the synthesized EAPM
NPs. The TEM image of the bare y-Fe203 NPs in Figure 5-4 shows that the NPs have
spherical shape and are less than 50 nm in size with an approximate size distribution of
10 to 40 nm which is consistent with the manufacturer’s specifications. Selected area
electron diffraction images (Figure 5-4, inset) indicate that the 'y-Fe203 NPs are
crystalline in nature. The TEM image of the 1:01 EAPM NPs (Figure 5-5, left) shows
that the particles are spherical in shape similar to that of the y-Fe203 NPs. The average
size distribution of the 1:01 EAPMS are smaller than 50 nm thus indicating that the NPs
have very minute quantities of polymer coating on them. Crystalline nature of the 1:01

EAPMs are confirmed through the electron diffraction rings (Figure 5-5, inset).

 

Figure 5-4. TEM and electron diffraction image of y-Fe203 NPs.

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Figure 5-6. TEM and electron diffraction images of EAPM NPs: (left) 1:0.6 EAPM; (right) 1:0.8 EAPM.

The 1:0.4 EAPM (Figure 5-5, right) aggregates show spherical morphology with an
average size distribution of 100 to 200 nm and are crystalline (Figure 5-5, right inset).
The 1:0.6 EAPMs (Figure 5-6, left) have an approximate size distribution of 50 to 100
nm and exhibit a chain like morphology similar to observations made by Sharma et al.
(Sharma et al., 2005). The electron diffraction image (Figure 5-6, left inset) of the 1:06
EAPMs also reveal the crystalline nature of the samples. The 1:0.8 EAPMs (Figure 5-6,
right) show the presence of excess polymer as compared to the 1:04 and 1:06 EAPMs
and the aggregates are greater than 200 nm in size. The electron diffraction patterns of the
1:08 EAPMs (Figure 5-6, right inset) also indicate that they are mostly amorphous in
nature. The TEM observations of the synthesized EAPM NPs are quite consistent with
the measured magnetic and electrical parameters of the NPs.

The 1:0.6 EAPM was consequently chosen over the 1:01, 1:04 and 1:08 EAPMs
for performing structural characterization studies as the NPs show good saturation
magnetization as well as high electrical conductivity values thus suggesting a uniform

distribution of the polymer and the magnetic core in the sample. The presence of both
polyaniline and y-Fe203 in the 120.6 EAPM NPs as well as its conductive nature was

therefore confirmed by energy-dispersive X-ray microanalysis (EDS) of the EAPM

samples using a scanning electron microscope and through UV—VIS spectral analysis.

108

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Figure 5-7 shows the EDS elemental analysis data of the 1:0.6 EAPMs. All the
elements barring hydrogen present in polyaniline i.e. carbon (C), nitrogen (N), and

chlorine (Cl) could be detected in the 1:06 EAPM sample. The absence of hydrogen in
the EDS data was due to instrumental limitations of the EDS detector in the SEM
microscope which could only detect elements having atomic numbers higher than 5. The
dopant Cl atoms in the EDS data also suggest that polyaniline is present in its conductive

form in the EAPM NPs. High percentages of Iron (Fe) and oxygen (O) atoms are also
detected in the 1:06 EAPM NPs thus confirming presence of y-FezO3.

Figure 5-8 shows the result of UV-vis spectral analysis of pure polyaniline and the
120.6 EAPM NPs dispersed in water. As observed in the figure, the characteristics peaks

of pure polyaniline appear at 356 nm, 433 nm and 862 nm. The peak at 356 nm can be

attributed to 7t-7t* transition of the benzenoid ring, while the peaks at 433 nm and 862 nm

*
are associated with polaron- 7t and a-polaron band transitions of polyaniline, respectively

(Stafstrom et al., 1987;Lv et al., 2005;Dallas et al., 2006). For the EAPM NPs,

characteristic absorption peaks are observed at 441 nm and 864 nm that can be related to

the polaron- 7d and n—polaron band transitions of polyaniline. For the EAPM NPs, the
polaron- 7t. peak shows an 8 nm shift and the n-polaron peak shows a 2 nm shift from that
of pure polyaniline. These red shifts observed in the spectrum can be explained by
interactions between the Fe203 nanoparticles and the polymer backbone. However, the 7:-
1t“ transition peak of the polymer is not properly distinguished in the absorbance

spectrum of the EAPM NPs. The absorbance data fiirther confirms that the polymer is

present in the doped (conductive) state in the EAPM NPs (Ohira et al. , 1987).

110

 

Absorbance

 

 

 

300 400 500 600 700 800 900
Wavelength (nm)
[— Polyaniline —— 120.6 EAPMI

Figure 5-8. UV-VIS absorption spectra of pure polyaniline and EAPM NPs.

111

5.2 @JECTIVE ;
Design and fabrication of an EAPM NP based immunosensor for detection of B.
anthracis spores.
5.2.1 EAPM Based Immunosensor Fabrication
5. 2. 1.1 Confirming EAPM Antibody Modification

The labeling of the EAPM NPs with antibodies was confirmed by
spectrophotometric studies. Figure 5-9 shows the UV spectrum of pure anti-B. anthracis
IgG (lSOug/ml) molecules and that of the unreacted IgG molecules in the supernatant
after magnetic separation of the immuno-EAPMS measured by a UV-VIS-NIR scanning
spectrophotometer. As evident in the figure, pure IgG solution shows a characteristic
peak of protein molecules at 280 nm. However, the supernatant from the immuno-
EAPMs shows no characteristic peak at 280 nm, thus implying that the anti-B. anthracis
IgG molecules are adsorbed onto the EAPM NPs and no unreacted IgG molecules remain
in the supernatant. Physical adsorption was used for bio-modification of the EAPM NPs
with IgG molecules because the conjugation procedure is simple and allows IgG
molecules to retain their activity and conformation. Physical adsorption is affected by
several factors, such as van der Waals interaction, electrostatic interaction, hydrophobic
effect and hydrogen bonding (Zhou et al., 2004). Literature suggests that IgG adsorption
occurs preferentially through Fc fragment of the molecule (Buijs et al., 1996). Hence, it
can be suggested that electrostatic interactions between negatively charged Fc fragments
of IgG molecules and positively charged polymer surfaces of EAPM NPs play a

significant role in the physical adsorption process.

112

 

Absorbance

 

 

 

l l

250 300 350 400
Wavelength (nm)

—Anti- B. anthracis IgG (150uglml) — Unreacted IgG (supernatant)

 

 

 

 

Figure 5-9. UV spectrum of pure anti-B. anthracis IgG molecules and unreacted IgG

molecules after magnetic separation from EAPM NPs.

5.2.1.2 Confirming Biosensor Capture Pad F unctionalization

The successful immobilization of polyclonal goat anti-B. anthracis IgG (500ug/m1)
on the biosensor capture pad was confirmed by fluorescent images obtained from the
Laser Scanning Confocal Microscope. The anti-B. anthracis IgG immobilized biosensor
capture pads were modified with secondary antibodies (FITC-anti-goat IgG) using a
working dilution of 1:320. Figure 5-10 (left) shows the fluorescent image of the capture
pad labeled with the secondary FITC anti-goat IgG and Figure 5-10 (right) shows the

image of the capture pad without the FITC label (control), observed by excitation with

113

488-nm line of argon ion laser, and the detection of emission using a 505 nm long pass
filter. The bright green fluorescence emission in Figure 5-10 (left) confirms the
immobilization of anti-B. anthracis IgG on the capture pad which is detected by the F ITC
label of the secondary anti-goat IgG molecules. In contrast, the control image (Figure 5-
10, right) shows no significant fluorescence emission because of the absence of the
secondary FITC labeled antibody in the control. The appearance of a few fluorescent dots
in the control image can be explained by the tendency of the nitrocellulose membrane to

fluoresce when exposed to the argon ion laser.

114

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115

5.2.2 EAPM Based Immunosensor Detection Concept

Figure 5-11 is a schematic representation of the immunomagnetic separation
technique and the detection procedure of the EAPM based immunosensor. The detection
principle involves a sandwich immunoassay, with a capture antibody (polyclonal anti- B.
anthracis IgG) immobilized on the biosensor capture pad and a detector antibody
(monoclonal anti- B. anthracis IgG) conjugated with the synthesized EAPM NPs. The
detector antibody conjugated EAPM NPs are first added to the target antigen
contaminated samples (FigureS-l 1, step 1) to capture the antigen by applying a magnetic
field (step 2). The immunomagnetically captured target antigens are then washed to
remove unbound antigens and other materials (step 3) and applied to the sample
application pad of the biosensor (step 4). The antigen-antibody-EAPM complex flows to
the capture pad, where the antigen is anchored by the capture antibodies present on the
sensor capture pad and a sandwich structure is formed (step 5). The electrically active
EAPM NPs bound to the antigens in the sandwich aid in direct electron transfer across
the silver electrodes thus acting as a voltage controlled “ON” switch and generating an
electrical signal which is recorded (step 6) (Muhammad-Tahir and Alocilja, 2003b;Pal et
al., 2007). In the absence of antigens, the sandwich complex is not generated and as a
result of which the electron transfer by the EAPM NPs between the electrodes is not

facilitated.

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The biosensor detection concept is based on the difference between the electric
signal in the absence of the target and the signal in the presence of the target. The
electrical signal generated across the electrodes on the biosensor surface can be measured

in terms of current (I) or in terms of resistance (R) when a fixed potential (V) is applied
across the electrodes. Thus, from Ohm’s law (I = %)’ it can be theoretically suggested

that at a fixed applied potential, the current response of the biosensor should increase in
the presence of an antigen, while the resistance response of the biosensor should decrease
in the presence of the antigen.
5. 2. 2. 1 Validation of Detection Concept

The theory of detection of the EAPM based immunosensor was first validated by
studying the amperometric response of the sensors in presence and absence of the target
using a potentiostat. A potentistat was initially used for the validation of detection
concept because of its higher precision over the hand-held multimeter that was

subsequently used in later biosensor experiments. The biosensors were tested for an
antigen concentration of 106 spores per ml and a control solution which had no antigens,

using 100 pl of the antigen-antibody-EAPM complex obtained after immunomagnetic
concentration. The current responses of the sensors were recorded over a total time of 20
minutes (1200 seconds) at a constant potential of 0.05 V chosen arbitrarily as the input
signal. As observed in figure 5-12, the biosensor current response at high antigen
concentration increases rapidly to a maximum value of 0.46uA before saturating. On the
contrary, the control amperometric signal only attains a value of 0.128 uA before
saturation. This increase in the amperometric response of the biosensor at high antigen

concentration in comparison to the control suggests the formation of a sandwich structure

118

(Figure 5-11, step 5) on the capture pad where electrically active EAPM NPs act as an
‘ON’ switch and increase the electron flow across the electrodes. The finding is in
agreement with the proposed theory of detection of the biosensor discussed earlier. For
the control solution, the formation of a sandwich ‘bridge’ is hindered due to the absence
of antigens as a result of which the electron transfer process across the electrodes is not
facilitated and a decrease in the amperometric response is observed. The experimental
results demonstrate the novel concept of employing EAPM NPs as a transducer for
electric signal generation in biosensors in contrast to straight polyaniline that has been
used for signal amplification in biosensors by Kim et a1 and Sergeyeva et al. (Kim et al.,
2000;Sergeeva et al. , 1996).

As evident in Figure 5-12, initial' fluctuations are observed in the biosensor
amperometric responses for approximately 100 sec as a result of which the control signal
is not significantly differentiable from the sample. Resultantly, a data acquisition time
starting from 2 min after sample application was considered to be applicable for
subsequent studies. A total data acquisition time limited to 6 min was acceptable for
distinction between the blank or control signal and a sample containing the antigens from

prior studies (Pal et al. , 2007).

119

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—— 10"6 spores/ml —— Control

 

 

Figure 5-12. Amperometric response of the EAPM based immunosensor in the

presence and absence of the target antigen.

Figure 5-13 shows the plot of resistance versus time for the EAPM immunosensors
calculated from the measured amperometric response. The resistance values were
calculated for 6 min at 2 min intervals as discussed earlier. As seen in Figure 5-13, the
resistance values for the control solution varies between 2.5 MOhm and 18.5 MOhms,
whereas, in the presence of antigens, the resistance values varies between 300 and 1000
kOhms. This decrease in resistance in the presence of antigens once again corroborates
the fact that the EAPM NPs result in enhanced electron transfer across the immunosensor

electrodes.

120

Resistance (kOhm)

100000

 

10000“

10*

 

 

 

100

150

Y T

200 250 300 350 400
Time (sec)

 

 

—-— 10"6 spores/ml + Control

 

 

Figure 5-13. Resistance changes of the EAPM immunosensor in the presence and

absence of the target antigen calculated from the measured amperometric response.

The NP concentration to be used in the EAPM based immunosensor was determined

based on optimization experiments previously performed in a B. cereus biosensor (data in
Appendix B). B. cereus was chosen as the model pathogen for its genetic similarities with
B. anthracis. The antibody concentration for EAPM modifications was fixed at 150
ug/ml from prior studies and preliminary experiments with B. cereus (Pal et al., 2007).
The optimum NP concentration for the best biosensor response as determined from
preliminary experiments was 20 mg/ml and was used in subsequent immunosensor

studies for B. anthracis detection. For immunomagnetic concentration, the antibody

121

coated EAPM NPs were allowed to react with the antigens and a 10 min incubation time
was found to be adequate for attachment of the antigens to the antibodies. The antibody
modified EAPM NPs were only used for single measurements in both the magnetic
concentration and biosensor detection steps and the reusability of these NPs for both

procedures need to be determined.

5.3 @JECTIVE 3
Evaluation of sensitivity and specificity of the EAPM NP based immunosensor and
determination of EAPM immunomagnetic capture efficiency.

All biosensor experiments were performed in pure spore suspensions of B. anthracis.
A spore stock solution was created using a previously published protocol that has been
elaborated in Chapter 3 of this dissertation. Sporulation was monitored by light
microscopy and the spore image results have been presented in Appendix B (Figure B-3).
The spore count of the stock solution as estimated by counting using a hemacytometer
(cell counting chamber) was 420 spores per ml. For all sensitivity, specificity and food
matrix studies, the spore dilutions were created from the above stock solution.
5.3.1 Immunosensor Performances Using Different EAPM hm

The biosensor performances of the four different EAPM NPs (1:01, 1:04, 1:06, and

1:08) were assessed in pure spore suspensions of B. anthracis. Biosensor tests were
carried out for three different spore concentrations (101, 104 and 107 per ml) for each NP

type. Multi-factor analysis of variance (Two-way ANOVA) to a significance of 95% was
used to compare the interactive effects of the different spore concentrations as well as the

different EAPM types on the biosensor resistance signals (results in Appendix A). Figure

122

5-14 shows a comparison of the mean resistance signals generated with the four different
types of magnetic NPs. The effect of the different EAPM NPs and the different spore

concentrations on the biosensor resistance responses is found to be statistically significant

(P < 0.0001) from the Type 3 Tests of Fixed Effects table (Table A-l).
As evident in Figure 5-14, at high spore concentration (107 per ml), all four EAPM

NP types show significant statistical differences (P < 0.05) in resistance values from the
control thus implying detection. However, the effect of the different EAPM types on the
resistance signal is not statistically significant at this concentration (P = 0.7351). This

could be explained by the very high antigen concentration that was capable of generating
a strong biosensor signal. At 104 spores per ml, only the 120.4 and 1:06 EAPM NPs show
resistance values statistically different from the control (P < 0.0001) whereas at the
lowest spore concentration (101 per ml), none of the EAPM NPs show significant
differences from the control thus implying no detection at this concentration (P > 0.05).
These results suggest that the effect of different EAPM types is more pronounced at 104

spores per ml.

Figure 5-14 also shows that the 1:0.1 EAPM NPs can only detect the spores at the
highest concentration level (107 per ml) and hence was not considered further for
subsequent experiments. Similarly, the 1:08 EAPM NPs have no statistically significant
effect on the biosensor resistance signals (P = 0.8227). This can be due to the greater
agglomeration and larger size observed in the 110.8 NPs (in Figure5-6) which have an
impeding effect on the flow of the EAPM NPs as well as the EAPM-antibody-spore
complexes through the capture pad thus resulting in a high background signal which

makes the control signal indistinguishable from that of the different spore concentrations.

123

The 120.6 EAPM NPs were consequently chosen for biosensor sensitivity and
specificity studies. The high electrical conductivity and competent magnetic properties of
the NPs confirmed by DC SQUID and four point probe measurements as well as the low
variability in the resistance responses of the biosensor (Figure 5-14) at high antigen
concentrations with these NPs suggests that the 1:06 EAPMS offers the best trade off

between desired NP characteristics and biosensor signal generation.

 

           

   

 

 

500
400 —
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100 — %
/
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Control 10"1 10M 10"?
No. of spores per ml

 

{—l120.1l1:0.4 I1:0.6 mos.

 

Figure 5-14. Comparison of biosensor resistance response of the four EAPM NPs at

three different spore concentrations (Mean resistance :I: SD, n = 3).

124

5.3.2 Immunosensor Sensitivity Study

The sensitivity study for the EAPM based B. anthracis immunosensor was
performed for spore concentrations ranging from 100 to 107 spores per ml. Figure 5-15

shows the average biosensor resistance measured from three trials using the 1:06 EAPM
NPs. Multi factor analysis of variance (Two-way ANOVA with time as repeated
measures) to a significance of 95% (P < 0.05) was used to study the effect of cell
concentrations and time on the biosensor resistance responses and to compare the
differences in the resistance readings between the control and the different spore
concentrations (results in Appendix A). The type 3 Tests of Fixed Effects table (Table A-
6) indicates that only spore concentration and not time has a significant effect on the
biosensor resistance signal (P- value for concentration: < 0.000], P- value for time:
0.9983). The average resistance recorded for the different spore concentrations show
significant statistical differences from the control solutions (P < 0.0001). The clarity in
signal can be attributed to the magnetic concentration procedures in this assay which
provide advantages such as low interference from other biological materials,
concentration of target pathogens into smaller volumes, and reduced background signal
(Kriz et al., 1998).

In figure 5-15, a gradual increase in the mean resistance signal is observed as the
spore concentration decreases from 107 to 100 spores/ml with an exception to the signal
at 103 spores/ml. This can be explained by the fact that a higher concentration of

pathogen will have a higher concentration of EAPM NPs bound to them resulting in an
increased electron transfer between the electrodes and a concomitant decrease in the

resistance signal. However, the resistance values recorded for the different spore

125

 

concentrations are not statistically different from one another. This disparities observed in
the biosensor signal can be explained by a number of factors such as imperfections in
biosensor fabrication, non-uniformity in EAPM samples, probabilistic interactions
between the antigens and antibodies, antibody orientations on the capture pad surface and
stability of the sandwich complex formed on the capture pad.

The lowest B. anthracis spore concentration which produces a resistance signal
statistically (P < 0.05) lower than the control is considered to be the analytical sensitivity

or the detection limit of the biosensor. Since the biosensor signal at the threshold
concentration of 4.2 x 102 spores per ml (estimated from spore count) is statistically
significant from the control, the sensitivity of the biosensor was determined to be 4.2 x
102 spores/ml. This is an excellent sensitivity in terms of rapid identification since the ID

50 (median infectious dose) for B. anthracis has been reported to be in between 8000 and
10,000 spores and most biosensors developed for the detection of B. anthracis spores
have sensitivities greater than 103 spores/ml (Cieslak and Eitzen, 1999;Krebs et al.,
2006;Liu et al., 2007).

At this stage of research, the biosensor can only be considered as qualitative device
as the resistance signal at different spore concentrations are not statistically differentiable.
Futhermore, the higher data variability observed in the control as well as at very low
spore concentrations (viz. 101 and 102 spores/ml) could not be explained at this stage and
would require further investigations. However, the biosensor signal demonstrates the
success of the immunomagnetic capture process by the EAPM NPs, which is further
confirmed by microbial plating results and capture efficiency calculations discussed in

Section 5.3.5 of this chapter.

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5.3.3 Immunosensor Specificity Analysis

Figure 5-16 shows the specificity analysis of the EAPM nanoparticle based

immunosensor. A comparison of the biosensor resistance responses in pure cultures of E.

coli with cell concentrations ranging from 1.7 X 101 to 1.7 X 105 CFU/ml, in pure cultures
of S. Enteritidis with cell concentrations ranging from 1.6 X 101 to 1.6 X 105 CFU/ml, and
pure spore suspensions of B. anthracis with spore concentrations ranging from 4.2 X 10l

to 4.2 x 105 spores/ml, is presented in this figure. Multi factor analysis of variance (Two-

way ANOVA) to a significance of 95% (P < 0.05) was used to study the effect of
different cell concentrations and the effect of the two pathogen types on the biosensor
resistance responses and to compare the differences in the resistance readings between
the control and the different cell concentrations (results in Appendix A). The type 3 Tests
of Fixed Effects table (Table A-lO) indicates that neither the pathogen type nor the cell
concentration had a significant effect on the biosensor resistance signal (P- value for
concentration: 0.6084, P- value for pathogen type: 0.1537).

As observed in Figure 5-16, the biosensor average resistance values for different
concentrations of the non-target bacteria (i.e. E. coli and S. Enteritidis) are similar to the
values observed for the control with no statistically significant differences. The P-values
range from 0.1171 to 0.8398 for E. coli, and from 0.5210 to 0.9905 for S. Enteritidis. The
results indicate that the effects of non-specific interactions are insignificant for the range
of cell concentrations tested on the biosensor. In comparison, for pure B. anthracis spore

suspensions, the biosensor average resistance responses show significant differences
between the control and spore concentrations ranging from 102 to 105 spore/m1 (P—value

< 0.0001) which is expected since the antibodies used in the biosensor are specific for B.

128

anthracis. However, at a low B. anthracis spore concentration of 101 spores/ml, the

biosensor resistance response is similar to that of the control which implies no detection

at this concentration (P-value: 0.5440).

 

129

 

///////////

////////
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//////////////////

 

 

500

400 —

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130

 

10"2 1043 10"4 10"5
Cell [Spore Concentration

10"1

Control

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Figure 5-16. Comparison of immunosensor resistance response in pure spore suspensions of B. anthracis and pure cultures of

generic E. coli and S. Enteritidis. For each pathogen, different superscripts over bars indicate significantly different resistance

response (P < 0.05).

5.3.4 Immunosensor Testing in Food Matrices

Figure 5-17 shows the average resistance readings measured with the EAPM NP
based immunosensor in lettuce, whole milk, and ground beef samples inoculated with B.
anthracis spores. The average resistance signals obtained from three replicates are plotted
for the control that consisted of uninoculated food samples containing EAPM NPs at a

concentration of 20 mg/ml and the food samples contaminated with spore concentrations
ranging from 4.2 x 101 to 4.2 X 107 spores/ml. As observed, the resistance values

recorded for the different spore concentrations are much lower than the values for the
control solution that has no spores in it. The average resistances for the control are in the
range of 288.2 :l: 68 k!) and 353.8 :1: 51 k0, whereas the average resistances for the
different spore concentrations in the three food samples vary from 75.1 :1: 14 to 132.6 :L-
19 k!) for the detectable spore concentrations. The reduced resistance values further
support the formation of a sandwich structure on the capture pad that was hypothesized
earlier where the conductive EAPM NPs help in electron transfer causing a drop in the
resistance signal across the silver electrodes (Kim et al., 2000;Pal et al., 2007).

Single factor analysis of variance tests (One-way ANOVA) to a significance of 95%
(P < 0.05) were conducted to compare the differences in the resistance values between
the control and the different spore concentrations to determine the biosensor sensitivity in

food matrices. For the lettuce and ground beef samples, the biosensor sensitivity is 4.2 x

102 spores/ml as estimated from spore stock concentration with statistically significant
differences from the control (P-value for lettuce at 102 spores/ml < 0.0001; P-value for
ground beef at 102 spores/ml < 0.0001). For whole milk samples, the biosensor can reach

a sensitivity of 4.2 X 103 spores/ml where statistically significant differences can be

131

observed from the control (P-value at 103 spores/ml was < 0.0001). The reduced

biosensor sensitivity in whole milk samples can be explained by interferences due to
proteins molecules viz. antibodies and fat molecules that influence binding kinetics of the
spores with the EAPM NPs during the immunomagnetic capture process.

As observed in the figure, at a particular spore concentration, the resistance signals
for the different food matrices are not statistically differentiable from one another in most
cases although the values are lower than the control. Similarly, the differences in the
resistance signal in between different spore concentration of each food sample is also not
statistically significant. These results are consistent with the sensitivity data of the
biosensor in pure spore suspensions thus emphasizing the fact that at this stage the
biosensor can only be considered as a qualitative device for a yes/no diagnosis of B.
anthracis spores. However, the biosensor shows high sensitivity and fast detection time
in comparison to the very few rapid detection systems for B. anthracis in food matrices
that have been reported in the literature (Cheun et al., 2001;Tims and Lim, 2004). The
biosensor results also indicate that the EAPM NPs are successful in concentrating the B.
anthracis spores from the different food matrices. This is further confirmed by microbial
plating of the spore-antibody-EAPM complexes, the results of which are discussed in

Section 5.3.5 of this chapter.

132

 

 

 

 

 

 

 

 

 

 

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133

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o '
g (1115:) eouejsau g o

10"1 10"2 10"3 10% 105 1046 10"?
Spore Concentration

Control

:3 Whole milk |

S Ground beef

 

 

I I Romaine lettuce

Figure 5-17. Resistance response of the EAPM based immunosensor in food matrices contaminated with B. anthracis spores.

For each food sample, different superscripts over bars indicate significantly different resistance response (P < 0.05).

 

5.3.5 Confirmation and EAPM Capture Efficiengy Determination

The immunomagnetic target capture process (step 1 in Figure 5-11) using the EAPM
NPs performed before the biosensor detection was confirmed by microbial plating of the
immuno-EAPM-spore complexes. The capture efficiency (CE) of the EAPM NPs was
calculated using the equation described in Section 4.3.8 of Chapter 4. I

Table 5-3 shows the plate count data and the CE calculations of the immuno-EAPMs
in pure spore suspensions of B. anthracis. As observed in Table 5-3, the EAPM NPs has

very high CE values ranging in between 95.8% and 76.0% for viable B. anthracis spore

concentrations of 4.73 X107 CFU/ml to 4.73 X101 CFU/ml. The highest CE value of

95.8% is observed at a viable spore concentration of 4.73 X102 CFU/ml. The immuno-
EAPMs also demonstrate efficient capture from B. anthracis spores concentrations as low
as 101/ml with a CB value of 91.6%. The CE values are determined only after an

immuno-reaction time of 10 min between the EAPM NPs and the different spore
concentrations before applying the complexes to the biosensor. From the CE results, it
can be concluded that the immuno-EAPMS are very efficient in rapid capturing of B.
anthracis spores from pure spore suspensions. The high capture efficiency of the EAPM
NPs can be attributed to their small sizes that make them ideal for achieving efficient
diffusion and rapid binding kinetics in solutions (Soukka et al., 2001;Varshney et al.,
2005)

Table 5-4 shows the plate count data and the CE calculations of the immuno-EAPMS
in the three different food matrices (romaine lettuce, whole milk, and ground beef)
contaminated with B. anthracis spores. As evident in Table 5-4, the capture effect of the

immuno-EAPMs in the lettuce and ground beef samples are quite similar to the capture

134

effect observed in the pure spore suspensions. In both food samples, the CE values are
highest at a viable spore concentration of 1.52 X 102 CFU/ml with a CB value of 97% for
lettuce and that of 72% for ground beef. Similarly, the EAPM NPs can achieve an
immunomagnetic capture at viable spore concentration as low as 1.52 X lOlCFU/ml from

both lettuce and ground beef samples. However, the CE values for both food samples are
lower than the CE values of the pure spore suspensions. For lettuce, the CE values of the
immuno-EAPMS range in between 14.6 and 96.7 %, while, for beef samples, the CE
values range between 9 and 72.3 %. This decrease can be explained by the interference
from food matrices in the antigen-antibody binding kinetics. For whole milk samples, the

immunomagnetic capture of the viable B. anthracis spores can only go as low as 1.52 X
102 CFU/ml and the capture effects are the same for all viable spore concentrations with

CE values in the range of 6% and 11%. The presence of gangliosides (a class of
glycolipids) in milk fat globule membranes of whole milk samples can lead to
competitive binding of B. anthracis spores with the gangliosides and the immuno-
EAPMs and is thought to be a possible reason for the low CE values observed in the
whole milk samples. The use of gangliosides as nonspecific receptors of pathogens and
toxins is well reported in literature (Desai et al., 2008; Mason et al., 2006).

The CE results demonstrated that the immuno-EAPMs were successful in rapidly
concentrating B. anthracis spores from pure spore suspensions and food matrices with
very high capture efficiencies at low spore concentrations. Since the CE values of the
EAPM NPs were calculated based on an EAPM concentration of 20 mg/ml and antibody

concentration of 150 ug/ml, it is expected that higher capture efficiencies can be attained

135

with the EAPM NPs by increasing both EAPM and antibody concentrations in the

capture process.

Table 5-3. Capture Efficiency (CE) of immuno-EAPMs in pure spore suspensions of

B. anthracis estimated from plate count data.

 

 

 

 

 

 

 

 

 

 

 

 

 

Total Viable Spore Viable Spores Bound
Dilution Count 3 SD to EAPM NPs 3: SD Cantu“
Factor (11:3) (11:3) Eggzizgy
Ct (CFU/ml) Cb (CFU/ml)
101 4.73 x1074 9.07 4.07 x 107 i 9.07 86.0
102 4.73 x10“ 3.59 x 106 :l: 4.93 76.0
103 4.73 x10” 3.97 x 105 i 3.05 83.9
104 4.73 x10“ 4.07 x 104 :l: 9.29 86.0
105 4.73 x10” 4.33 x 103 i 2.51 91.6
106 4.73 x10” 4.53 x 102 :t 7.09 95.8
107 4.73 x10" 4.33 X101i1.52 91.6
108 4.73 x10‘" 0 0
Control 0 O 0

 

 

 

* Estimated spore concentrations
SD = Standard Deviation, n = no. of replicates

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137

5.4 OBJECTIVE 4
Fabrication of an EAPM based electrochemical DNA biosensor for detection of B.
anthracis.
5.4.1 Selection and Analysis of DNA Primers and Probes
B. anthracis Sterne strain, a strain with attenuated virulence, was used as the

model organism in this study. Virulent strains of B. anthracis have two virulent plasmids:
pXOl (184 kb), which encodes toxins and pX02 (95 kb), which encodes the capsule
(Reif et al., 1994). The B. anthracis Sterne strain lacks the pX02 plasmid encoding the
poly-y-D glutamic capsule which is a major determinant of virulence in anthrax. For this
reason, the PCR primers and the DNA probes were selected from a fragment of the pag A
gene, which is present in the plasmid pXOl. The specificity of the selected probes and
primers were checked using the BLAST analysis tool. BLAST results indicated that both
the probe and primer pairs had a high degree of specificity (AB value: 8e-19, Max ident:
100% for the detector probe; AE value: 3e-7, Max ident: 100% for the capture probe; AE
value: 0.43, Max ident: 100% for the primer pairs) for the B. anthracis Sterne strain
plasmid pXOl pag A gene. The only Bacillus species with which the sequences showed
high similarity was B. cereus (B. cereus strain 69241 plasmid pBCXOl, Max ident:
100%).
5.4.2 Extraction, Amplification and Characterization of B. anthracis DNA

Genomic DNA was extracted from overnight cultures of B. anthracis grown in TSB
broth using a procedure for mammalian DNA extraction. The concentration of the double
stranded DNA (dsDNA) after the extraction process was determined to be 326.6 ug/ml

by measuring the absorbance at 260 nm in a spectrophotometer following which the

138

DNA was diluted according to the requirements of PCR reaction. The PCR amplification

reaction was optimized with respect to the concentration of the reactants, the melting
temperature (Tm) and the amplification time in order to obtain the best amplification of

targets in the shortest possible time. Table 5-5 shows the optimized concentrations of the
reactants used in the PCR reaction.

Table 5-5. Optimum concentration of PCR components.

 

 

 

 

 

 

 

 

:$;'§.:::::;':;:::.:
Buffer 1X

dNTP mix 0.2mM

MgClZ 1.5mM
Accuprime Taq DNA Polymerase 1 ul

Forward Primer 100 nM
Reverse Primer 100 nM

DNA Template 100 ng

 

 

 

 

The PCR amplification reaction was optimized and run under the following
conditions: 95°C for 2 min; 35 cycles of 95°C for 30 s, 55°C for 303, 72°C for 605; and
72°C for 5 min in the DNA thermal cycler. The PCR products obtained were first purified
using the QIAquick kit and then characterized by gel electrophoresis and

spectrophotometric measurements.

139

BA1

 

Figure 5-18. Gel Electrophoresis of PCR amplified Bacillus anthracis. (M- Marker,
BA1 and BA2 — B. anthracis, NC— Negative Control)

Figure 5-18 shows the result of the PCR reaction after purification on 2.5 % agarose
gel. The appearance of distinct bands in lanes BA1 and BA2 just above the 100 bp band
of the marker confirms the length of the PCR product (120 bp). The appearance of bands
in lanes BA] and BA2 and no bands in lane NC also confirms the successful optimization
of the PCR reaction conditions along with the PCR purification process. The dsDNA
concentration in the purified PCR products (BA1 and BA2 pooled together), when tested
in the NanoDrop Spectrophotometer, ranged in between of 7.0 and 12.0 ng/ul with

Azm/zgo ratios in between 1.63 and 2.38, thus indicating the high quality of the PCR

product.

140

5.4.3 Confirming EAPM -DNA Probe Modification
The biomodification of the EAPM NPs with DNA probes (Ph-PRO) was confirmed

by fluorescence and spectrophotometric studies. Figure 5-19 shows the fluorescence
intensity measurements of the pure 6—FAM labeled Ph-PRO probe solution [22.5uM] and
that of the unreacted probes remaining in the supernatant after magnetic separation of the
PRO-EAPMS (probe labeled EAPMs) by excitation at 495 nm and detection of emission
at 520 nm for four different EAPM NP concentrations (0.1, 1, 10 and 20 mg/ml). As
evident in the figure, the 6-FAM labelled Ph-PRO probes (pure probe) show the highest
fluorescence signal since there are no EAPM NPs present in the solution. In comparison,
the supernatant obtained from magnetic separation of the PRO-EAPMS after the labeling
study using different EAPM NP concentrations show significantly lower fluorescence
signal than that of the pure probe thus indicating the attachment of the probes to the NPs.
A linear decrease in the fluorescence signal is also observed as the NP concentration
increases from 0.1 to 20 mg/ml which is expected since an increased EAPM NP
concentration would result in a greater number of attachment sites (terminal amine
groups of polyaniline) for the phosphorylated probes. The single-stranded DNA (ss-
DNA) concentration measurements of the pure probes and the supematants using the
NanoDrop spectrophotometer further confirmed the attachment of the probes to the
EAPM NPs. As observed in figure 5-19, the ss-DNA concentration for the pure probe is
385.2 ng/ul, whereas for the supematants from PRO-EAPMS, the ss-DNA concentration
decreases and is in the range of 310.2 and 0 ng/ul. From the fluorescence and the
absorbance results, an EAPM concentration of 1 mg/ml was chosen for subsequent

hybridization studies, since at this concentration, the EAPM NPs were saturated with

141

adequate concentrations of the DNA probes required for hybridization with the target

 

  
  
 

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EAPM Concentration (mg/ml)

Figure 5-19. Fluorescence signal of pure Ph-PRO probes and unreacted Ph-PRO
probes after magnetic separation from the EAPM NPs.

142

5.4.4 EAPM Based Electrochemical DNA Biosensor Detection Concept

Figure 5-20 is a schematic representation of the detection mechanism of the EAPM
based electrochemical DNA biosensor. The detection principle involves an
electrochemical sandwich assay engaging a detector DNA probe and a. capture DNA
probe. The detector probe is labeled with EAPM NPs whereas the capture probe is
labeled with biotin. Both the EAPM labeled detector probe and biotinylated capture
probe are first added to the target sequence, where the target undergoes sandwiched
hybridization with both probes. The EAPM-target-biotin DNA hybrids thus formed are
separated from other noncomplementary sequences and unreacted DNA by magnetic
separation of the EAPM NPs. The EAPM-target-biotin DNA hybrids are then added
directly to the surface of streptavidin modified screen printed electrodes for anchoring the
hybrids on the electrode surface by streptavidin-biotin interactions. After a short
incubation period, the electrode surface is washed to remove the excess EAPM NPs and
the unbound DNA hybrids. The target DNA is finally detected on the SPCE biosensor

surface by the redox activity of the EAPM NPs using cyclic voltammetry.

143

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5.5 OBJECTIVE 5
DNA hybridization on EAPM NPs and sensitivity and specificity evaluation of the
EAPM based electrochemical DNA biosensor.

5.5.1 Sandwiched Hybridization of DNA Targets on EAPM NPs

5. 5. 1. 1 Determination of Hybridization Conditions
The EAPM labeled detector probes (PRO-EAPMS) were hybridized with the target
DNA obtained from the PCR product. The optimum temperature required for the

hybridization reaction was determined by fluorescence assays using 6—FAM labeled PCR
products (Xexcitauon: 495 nm, Remission: 520 nm). To determine the optimum temperature,
the hybridization reaction was performed for 1 hour at three different temperatures: at 25

°C (room temperature), at 45 °C (25 °C below the melting temperature, Tm, of the Ph-
PRO probe) and at 55°C (15 °C below the Tm of the probe). Figure 5-21 shows the

normalized fluorescence intensity of the DNA targets obtained from PCR reaction before
and after hybridization with the PRO-EAPMs at the three different temperatures. At each
temperature, the fluorescence signal of the PCR target is normalized against the PCR
negative control to eliminate the effect of any background fluorescence.

It is evident from figure 5-21 that the highest decrease in fluorescence signal for the
PCR target DNA is observed at 45 °C with the reduction in normalized fluorescence

being 11448 :l: 106.4 counts/0.1 s. This is expected since a hybridization temperature 25
°C below the Tm (Tm of Ph-PRO probe is 704°C) allows the maximum rate of

hybridization (Mehlen et al., 2004). For the hybridization studies at 25 °C and 55 °C, the

reduction in normalized fluorescence are only 5030 2!: 117.5 and 448 i 110.9 counts/0.1 s,

145

respectively. Therefore, the hybridization temperature was kept at 45 °C for subsequent

 

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Figure 5-21. Normalized fluorescence signal of PCR DNA targets before and after

hybridization at different hybridization temperatures.

In order to ensure a fast hybridization reaction between the target DNA and the Ph-
PRO probe labeled EAPM NPs (PRO-EAPMS), the hybridization time was optimized by
fluorescence assays using 6-FAM labeled PCR products. The DNA hybridization
reaction was performed for 30 min, 1 h and 2 h at 45 °C. Figure 5-22 shows the
normalized fluorescence intensity (background subtracted) of the PCR targets before and

after hybridization with the PRO-EAPMS at three different times. As observed in the

146

figure, the decrease in the fluorescence signals of the PCR targets after the hybridization
event are almost the same for the three hybridization times trialed. The reduction in the
normalized fluorescence values for hybridization times of 30 min, 1 h, and 2 h are 10862
:1: 107.6, 10380 i 64.5, and 10226 :t 300.8 counts/0.15, respectively. Thus, the

hybridization time was limited to 30 min in the succeeding studies.

 

  

 

 

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Figure 5-22. Normalized fluorescence signal of PCR DNA targets before and after
hybridization at different hybridization times.

5.5.1.2 Confirming Sandwiched Hybridization on EAPM NPs
The sandwiched hybridization of the PCR targets with the EAPM labeled detector

probe (PRO-EAPMS) and the biotinylated capture probe (PRO-Bio) was confirmed by

147

fluorescent assays using 6-FAM labeled PRO-Bio probes (kexdtation: 495 nm, Langston:
520 nm). The hybridization temperature and time was fixed at 45°C and 30 min,
respectively, to ensure maximum hybridization of the targets with the detector probes.
Three different concentrations of the PRO-Bio probes (luM, SuM, and IOuM) were
trialed in the sandwich hybridization event. Figure 5-23 shows a comparison of the
change in fluorescence signal of the PRO-Bio probes in the presence and absence of the

PCR targets during the sandwiched hybridization.

 

 

 

 

 

 

 

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of PCR targets during sandwiched hybridization.

148

As evident in Figure 5-23, the fluorescence signal of the PRO- Bio probes reduces by
an order of magnitude in the presence of the PCR targets during the dual hybridization
process for all three probe concentrations. This signal reduction confirms the successful
sandwiched hybridization of the biotinylated capture probes with the PCR targets. In the
absence of the PCR targets, a small decrease in fluorescence is observed at all capture
probe concentrations. This can be attributed to mild bleaching of the fluorescent labels
during the stringent hybridization and washing procedures. From the above results a
PRO-Bio probe concentration of SuM was fixed for the successive detection experiments
and the resulting EAPM-target-biotin DNA hybrids from the sandwiched hybridization
were used directly for electrochemical detection.

5.5.2 Electrochemical Detection Using SPCE Biosensor
5. 5. 2.1 Electrochemical Characterization of EAPM NPs

Electrochemical characterization of the synthesized EAPM NPs was performed on
the screen printed carbon electrodes (SPCEs) using cyclic voltammetry (CV) before
proceeding to the detection of EAPM captured DNA hybrids. Figure 5-24 shows the
cyclic voltammogram of EAPM NPs in 0.1 M HCl scanned from -O.4 V to 1.0 V at a
scan rate of 20 mV/s. Two stable redox peaks are observed in the voltammogram that can
be related to the presence of the polymer, polyaniline, in the EAPM samples. The anodic
peaks at 0.12 V and 0.59 V correspond to the switching of the leucoemeraldine base to
emeraldine salt and emeraldine to pemigraniline salt respectively (Arora et al.,
2007;Gospodinova et al., 1996). The corresponding cathodic peaks for the reduction

process are observed at 0.53 V and -0.07 V, respectively.

149

Figure 5-25 shows the effect of scan rate on the rate of electron transfer to the SPCE
electrodes by the EAPM NPs. The two characteristic redox peaks of the EAPM NPs are
visible at all scan rates. With an increase in the scan rate, the anodic peak potential of the
EAPM NPs is shifted to a more positive value and the cathodic peak potential is shifted
to a negative direction. Figure 5-25 (inset) shows a plot of the dependence of the anodic
peak current and the cathodic peak current versus the scan rate. As observed in the figure,
the peak currents exhibits a linear relationship with increasing scan rate thus suggesting

surface controlled behavior and diffusion controlled system (Bard and Faulkner, 2001).

However, the ratio of the peak currents at different scan rates [pa/1pc 76 1 which indicates

a quasi-reversible chemistry of the EAPM NPs and the SPCE electrode process (Bard and

Faulkner, 2001;Ram et al., 1999).

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5. 5. 2.2 Detection of EAPM- T arget-Biotin DNA Hybrids

Following the sandwiched hybridization of the PCR DNA targets with the EAPM-
PRO probes and the PRO-Bio probes, the EAPM-target—biotin DNA hybrids were
directly detected electrochemically on the SPCE electrodes. Figure 5-26 shows the
electrochemical response of the EAPM captured target DNA hybrids from undiluted PCR
products (concentration-7.3ng/ul) on the SPCE electrode. The electrochemical responses
of the bare SPCEs and streptavidin modified SPCEs were compared as control. As
observed in the figure, the cyclic voltammogram of the EAPM captured targets shows the
two characteristic redox peaks of the EAPM NPs that were absent in the control. The
anodic peak potentials are located at 0.12 V and 0.59 V, whereas the cathodic peak
potentials are located at 0.53 V and -0.09 V, similar to the CV response obtained with
just EAPM NPs in 0.1M HCl. The CV response demonstrates the fact that the EAPM
NPs maintained their native electrochemical behavior after the probe labeling and
sandwiched target hybridization procedures. The appearance of the EAPM redox peaks in
the CV response of the PCR targets also confirms the successful capture of the EAPM-
target DNA-biotin hybrids and detection of the EAPM NPs on the streptavidin modified

SPCE electrodes.

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5.5.3 SPCE Biosensor Sensitivity Study

The sensitivity of the EAPM based SPCE biosensor was estimated in different
concentrations of the PCR target DNA obtained by serially diluting the PCR product.
Figure 5-27 shows the electrochemical response (cyclic voltammograms) of the biosensor
in PCR target concentrations ranging from10 ng/ul to 1 pg/ul and the control. The control
consists of just EAPM NPs with no PCR target (shown as O ng/ul in the figure). As
observed in the CV response, the two characteristic redox peaks of the EAPM NPs are
present in different concentrations of the PCR target. A gradual decrease in the intensity
of the redox peaks is also noted with a decrease in the target concentration. This is
expected since a lower concentration of the target would result in lower concentration of
the EAPM-target DNA-biotin hybrids bound on the streptavidin coated electrode. The
presence of the EAPM redox peaks at lower target concentrations also shows that the
EAPM NPs are capable of generating redox signals at very low concentrations.

Although both redox peaks of EAPM NPs are evident at lower target
concentrations, the anodic peak current (oxidation peak) at an anodic peak potential of
0.59V was chosen for further analysis due to the minimal shift observed in the peak
current in repeated observations at this peak potential. Figure 5-28 shows a plot of the
anodic (oxidation) current in the potential range of 0.3 V to 0.7V obtained from the cyclic

voltammograms of the different PCR target concentrations and the control.

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ugly] to 0 ng/ul. Inset- anodic peak of 10 ng/ul PCR target (obtained from cyclic

voltammograms).

As evident in Figure 5-28 (Inset), the anodic peak current at 0.59 V is maximum
(62uA) for the highest PCR target concentration (10ng/ul) and decreases from 62uA to 2
uA as the PCR target concentration decreases from 10 to 0.01 ng/ul. The anodic peak
currents for the control and for a target concentration of 0.001 ng/ul are 0.84 and 0.29
uA, respectively. The higher current values of the control than 0.001 ng/ul of the target
indicate that there is no detection at this concentration and the peak current signal is
generated by the nonspecifically adsorbed EAPM NPs on the electrode surface for both

C3868.

157

 

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DNA Concentration (ng/ul)

Figure 5-29. CV mediated anodic peak current at different PCR target

concentrations from three experimental trials (mean current :1: SD, n = 3).

Figure 5-29 shows the mean anodic peak current of different concentrations of PCR
targets obtained from three experimental trials of the EAPM based SPCE biosensor. It is
evident from the above figure that the mean anodic peak current for the SPCE biosensor
increases with increasing target concentration. A linear increase in the anodic current is
observed for target concentrations between 0.01 and 1 ng/ul which is followed by an
exponential increase in the anodic current at the highest target concentration of 10 ng//ul.
It is also noted that the lowest PCR target concentration for which the mean anodic peak

current can be differentiated from that of the control is 0.01 ng/ul. Based on these results

158

from the cyclic voltammetry experiments, the lowest detection limit of the EAPM based
SPCE biosensor is determined to be 0.01 ng/ul of PCR DNA.

To confirm the sensitivity results obtained from CV response, the anodic peak
current signal of the biosensor for the different PCR concentrations were statistically
analyzed by one-way AN OVA using the SAS software (results in Appendix A). From the
tests of fixed effects table (Table A-21), it is evident that the PCR DNA concentrations
have significant effect (P < 0.0001) on the anodic peak current signal. The table of
estimates (Table A-22) further shows that the peak current values for DNA
concentrations ranging from 10 ng/ul to 0.01 ng/ul are significantly different from that of
control, whereas, the peak current at 0.001 ng/ul of DNA is not significantly different
from the control (P = 0.6943). Thus, the statistical analysis results affirm the SPCE
biosensor sensitivity to be 0.01 ng/ul of PCR DNA. Furthermore, the differences of least
squares means table (Table A-24) shows that the anodic peak current signal is
significantly different for different DNA concentrations (P S 0.05) thus indicating that
the SPCE biosensor is quantitative for the range of DNA concentrations tested.

Results of the SPCE DNA biosensor conclude that EAPM nanoparticles can be
successfully used as a redox indicator in biosensor detection systems. This is a unique
approach for DNA detection that has not been investigated in current literature and its
potential needs to be explored in future studies. Other studies have reported DNA
detection on polyaniline modified electrodes using redox indicators such as methylene

blue and duanorubicin (Arora et al., 2007;Chang et al., 2007a).

159

5.5.4 Specificity Analysis

The specificity of the detector probe labeled EAPM NPs (Pro-EAPMS) was
evaluated by fluorescence assays using 6-FAM labeled noncomplementary sequence
(NC). The NC sequence was designed from the cap A gene of Bacillus anthracis.
Theoretical alignment of the NC sequence with the detector probe sequence using the
BLAST analysis tool indicated no significant similarity between the sequences.

Figure 5-30 shows fluorescence results before and after hybridization of the Pro-
EAPMs with the 6-FAM labeled NC sequences at three different concentrations (luM,
SuM and 10 uM). As evident in the figure, a small decrease in the fluorescence signal is
observed for the 6-FAM labeled NC sequences at the three concentrations tested after
hybridization with the Pro-EAPMS. This can be attributed to the occurrence of small
amounts of cross reactions between the detector probe and the NC sequence as both
sequences were designed from the same microorganism. Although theoretical results
(BLAST analysis) indicated highly dissimilar sequences but such ideal conditions are
hard to achieve in real samples. However, the reduction in fluorescence signal for the NC
sequences were not significant as none of the concentrations showed a decrease in
fluorescence intensity by an order of magnitude. Therefore, specificity studies with
different noncomplementary sequences designed from different microorganisms are

required in future for further specificity analysis.

160

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Figure 5-30. Change in fluorescence intensity of non-complementary sequences
before and after sandwiched hybridization on EAPM NPs.

161

CHAPTER 6: CONCLUSION AND FUTURE RESEARCH

In this dissertation the potential of electrically active polyaniline coated magnetic
nanoparticles (EAPM) as a novel nanostructured transducer and as a magnetic
concentrator was explored for biosensor applications. The five major objectives of this
research describe synthesis and characterization studies of the EAPM nanoparticles,
fabrication and implementation of an EAPM nanoparticle based immunosensor, and
fabrication and implementation of an EAPM based DNA biosensor.

The EAPM nanoparticles were synthesized by a chemical polymerization method
using y-Fe203 nanoparticles and the monomer aniline. DC Squid magnetism and Four

point probe conductivity studies showed that the synthesized nanoparticles were in the
ferromagnetic regime and had room temperature electrical conductivity as high as 2.4
S/cm. TEM analysis indicated that the nanoparticle size was related to polymer
concentration and SEM EDS analysis as well as UV-VIS spectral analysis further
confirmed the presence of the polymer in the EAPM nanoparticles in the doped or
conductive state.

An integrated antibody based biosensor (immunosensor) using EAPM nanoparticles
as an immunomagnetic concentrator and transducer was designed and fabricated. The
fabricated biosensor was implemented in the detection of B. anthracis Sterne spores. The
detection process was fast and included a magnetic concentration time of 10 min and
signal detection time of 6 min. A comparison study showed that the 120.6 EAPM
nanoparticles performed better in the detection system and hence was chosen for

successive experiments. The EAPM based immunosensor had a lower detection limit of

4.2 X 102 B. anthracis spores/ml in pure spore suspensions that was well below the

162

reported ID 50 for B. anthracis. The immunosensor sensitivity was also evaluated in food
matrices and was found to be 4.2 x 102/4.2 X 103 spores/m1. Specificity analysis indicated

no cross reactivity in the sensor signal with non-target pathogens such as E. coli and S.
Enteritidis. Capture efficiency (CE) experiments using EAPM nanoparticles confirmed

successful immunomagnetic concentration of the target pathogens with the highest CE

value of 97% in concentrations as low as 101 spores/ml.

A DNA biosensor was developed based on sandwiched hybridization of DNA targets
on probe labeled EAPM nanoparticles and electrochemical detection of the hybridization
process through the redox signal of EAPM nanoparticles. The EAPM based DNA
biosensor was fabricated and implemented in the detection of B. anthracis pag A gene.
Fluorescence assays confirmed the sandwiched hybridization of PCR amplified DNA
targets with EAPM labeled detector probes and biotinylated capture probes. The EAPM
DNA biosensor was able to detect B. anthracis DNA with a lower detection limit of 0.01
ng/ul of PCR amplified targets. The electrochemical detection process was completed in
60 min.

In summary, this research shows the feasibility of using EAPM nanoparticles for
magnetic concentration and biosensor transduction in more than one detection system.
Table 6-1 compiles the specifications of the two different EAPM nanoparticle based

biosensors that were developed.

163

 

 

Table 6-1. Specifications of EAPM based biosensors.

 

 

 

 

 

 

 

 

 

 

Parameters Immunosensor DNA sensor
Detection mechanism Charge transfer resistance Redox activity
Target B. anthracis spores B. anthracis pag A gene
Lower detection limit 4.2 X 102 spores/ml 0.01 ng/ul PCR DNA
Range Of Detection 102 to 107 spores/ml 10 - 0.01 ng/ul
Detection time 16 min 60 min
Specificity Specific Specific

 

Future research should be directed toward a number of different activities: (1)
synthesizing uniform EAPM nanostructures with excellent electrical and magnetic
properties and minimum nanoparticle aggregation; (2) advancing the EAPM based
immunosensor toward quantitative evaluation of samples; (3) implementing the DNA
based biosensor in detection of genomic DNA for field based applications; (4) exploring
different techniques for electrochemical detection of EAPM nanostructures; (5)
advancing EAPM nanostructures as an efficient magnetic concentrator; (6) developing
EAPM nanostructure based biosensors for different targets , and (6) developing low-cost

EAPM based magnetic detection devices.

164

APPENDIX A: STATISTICAL ANALYSIS RESULTS

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

A.l ANOVA ANALYSIS OF DIFFERENT EAPM BASED IMMUNOSENSORS
The Mixed Procedure
Table A-1. Type 3 Tests of Fixed Effects
Num Den
Effect DF DF F Value Pr > F
Concentration 3 128 3 1 .73 <.0001
Sample 3 128 22.89 <.0001
Sample*Concentration 9 128 5.47 <.0001
Table A-2. Tests of Effect Slices
Num Den
Effect Conc. Sample DF DF F Value Pr > F
Sample*Concentration 10"1 3 128 14.29 <.0001
Sample*Concentration 10"4 3 128 8.88 <.0001
Sample*Concentration 1007 3 128 0.43 0.7351
Sample*Concentration Control 3 128 15.71 <.0001
Sample*Concentration l : 0.1 3 128 17.14 <.0001
Sample*Concentration l : 0.4 3 128 5.81 0.0009
Sample*Concentration 1 :0.6 3 128 24.89 <.0001
Sarnple*Concentration 1 :0.8 3 128 0.3 0.8227

 

 

 

 

 

 

 

 

165

 

Table A-3. Estimates

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Label Estimate Stgndard DF t Value Pr > |t|
rror
10"1 vs. Control for sample 0.1 38.8 35.7967 128 1.08 0.2804
10"4 vs. Control for sample 0.1 -27.9444 35.7967 128 -0.78 0.4365
10"7 vs. Control for sample 0.1 -198.67 35.7967 128 -5.55 <.0001
10"] vs. Control for sample 0.4 -31.4889 35.7967 128 -0.88 0.3807
10"4 vs. Control for sample 0.4 -81.5222 35.7967 128 -2.28 0.0244
10"7 vs. Control for sample 0.4 -139.53 35.7967 128 -3.9 0.0002
10"1 vs. Control for sample 0.6 -105.82 35.7967 128 -2.96 0.0037
10"4 vs. Control for sample 0.6 -244.7 35.7967 128 -6.84 <.0001
10"7 vs. Control for sample 0.6 -270.57 35.7967 128 -7.56 <.0001
1001 vs. Control for sample 0.8 -21.8556 35.7967 128 -0.61 0.5426
10"4 vs. Control for sample 0.8 -26.0778 35.7967 128 -0.73 0.4676
1007 vs. Control for sample 0.8 -31.9667 35.7967 128 -0.89 0.3735
Table A-4. Least Squares Means
Effect Conc. Sample Estimate Stgndard DF t Pr >|t|
rror Value
Sample*Conc. 10"1 0.1 308.4 25.3121 128 12.18 <.0001
Sample*Conc. 10"4 0.1 241.66 25.3121 128 9.55 <.0001
Sample*Conc. 10"7 0.1 70.9333 25.3121 128 2.8 0.0059
Sample*Conc. Control 0.1 269.6 25.3121 128 10.65 <.0001
Sample*Conc. 10"1 0.4 210.46 25.3121 128 8.31 <.0001
Sample*Conc. 10"4 0.4 160.42 25.3121 128 6.34 <.0001
Sample*Conc. 10"7 0.4 102.41 25.3121 128 4.05 <.0001
Sample*Conc. Control 0.4 241.94 25.3121 128 9.56 <.0001
Sample*Conc. 10"] 0.6 233.6 25.3121 128 9.23 <.0001
Sample*Conc. 10"4 0.6 94.7222 25.3121 128 3.74 0.0003
Sample*Conc. 1007 0.6 68.8556 25.3121 128 2.72 0.0074
Sample*Conc. Control 0.6 339.42 25.3121 128 13.41 <.0001
Sample*Conc. 10"1 0.8 78.7 25.3121 128 3.11 0.0023
Sample*Conc. 10"4 0.8 74.4778 25.3121 128 2.94 0.0039
Sample*Conc. 10"7 0.8 68.5889 25.3121 128 2.71 0.0077
Sample*Conc. Control 0.8 100.56 25.3121 128 3.97 0.0001

 

 

 

 

 

 

 

 

166

 

 

 

 

 

Table A-5. Differences of Least Squares Means

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Effect Sample Cone. __Conc. Estimate 3;de DF Value Pr > M
Sample*Conc. 0.1 10"] 10"4 66.7444 35.7967 128 1.86 0.0645
Sample*Conc. 0.1 10"] 10"7 237.47 35.7967 128 6.63 <.0001
Sample*Conc. 0.1 10"] Control 38.8 35.7967 128 1.08 0.2804
Sample*Conc. 0.1 10"4 10"7 170.72 35.7967 128 4.77 <.0001
Sample*Conc. 0.1 10"4 Control —27.9444 35 .7967 128 -0.78 0.4365
Sample*Conc. 0.1 10"7 Control -198.67 35.7967 128 -5.55 <.0001
Sample*Conc. 0.4 10"] 10"4 50.0333 35.7967 128 1.4 0.1646
Sample*Conc. 0.4 10"] 10"7 108.04 35.7967 128 3.02 0.0031
Sample*Conc. 0.4 10"] Control -31 .4889 35 .7967 128 -0.88 0.3807
Sample*Conc. 0.4 10"4 10"7 58.01 11 35.7967 128 1.62 0.1076
Sample*Conc. 0.4 10"4 Control -81.5222 35 .7967 128 -2.28 0.0244
Sample*Conc. 0.4 10"7 Control -] 39.53 35.7967 128 -3.9 0.0002
Sample*Conc. 0.6 10"] 10"4 138.88 35.7967 128 3.88 0.0002
Sample*Conc. 0.6 10"] 10"7 164.74 35.7967 128 4.6 <.0001
Sample*Conc. 0.6 10"] Control -105.82 35.7967 128 -2.96 0.0037
Sample*Conc. 0.6 10"4 10"7 25.8667 35.7967 128 0.72 0.4712
Sample*Conc. 0.6 10"4 Control -244.7 35.7967 128 -6.84 <.0001
Sample*Conc. 0.6 10"7 Control -270.57 35.7967 128 -7.56 <.0001
Sample*Conc. 0.8 10"] 10"4 4.2222 35.7967 128 0.12 0.9063
Sample*Conc. 0.8 10"] 10"7 10.1111 35.7967 128 0.28 0.778
Sample*Conc. 0.8 10"] Control -2] .8556 35.7967 128 -0.6] 0.5426
Sample*Conc. 0.8 10"4 10"7 5.8889 35.7967 128 0.16 0.8696
Sample*Conc. 0.8 10"4 Control -26.0778 35.7967 128 -0.73 0.4676
Sample*Conc. 0.8 10"7 Control -31.9667 35.7967 128 -0.89 0.3735

 

167

 

 

 

A.2

AN OVA ANALYSIS FOR IMMUNOSENSOR SENSITIVITY

The Mixed Procedure

Table A-6. Type 3 Tests of Fixed Effects

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Effec‘ NDan 13)? Veiiue Pr > F
Concentration 8 54 10.32 <.0001
Time 2 54 0.34 0.7122
Concentration*Time 16 54 0.25 0.9983
Table A-7. Estimates
Label Estimate Error DF Vatlue Pr > |t|
10"] vs. Control -23.8222 39.0112 54 -0.6] 0.544
10"2 vs. Control ~139.83 39.0112 54 ~3.58 0.0007
10"3 vs. Control -186.43 39.0112 54 -4.78 <.0001
10"4 vs. Control -162.7 39.0112 54 -4.17 0.0001
10"5 vs. Control -174.7 39.0112 54 -4.48 <.0001
10"6 vs. Control -191.94 39.0112 54 -4.92 <.0001
10"7 vs. Control -]88.57 39.0112 54 -4.83 <.0001
Table A-8. Least Squares Means
Effect Cone. Estimate $3:de DF Vatlue Pr > |t|
Cone. 10"1 233.6 27.585] 54 8.47 <.0001
Cone. 10"2 117.59 27.5851 54 4.26 <.0001
Conc. 10"3 70.9889 27.5851 54 2.57 0.0128
Conc. 10"4 94.7222 27.5851 54 3.43 0.0012
Conc. 10"S 82.7222 27.5851 54 3 0.0041
Cone. 10"6 65.4778 27.5851 54 2.37 0.0212
Conc. 10"7 68.8556 27.5851 54 2.5 0.0156
Cone. Control 257.42 27.5851 54 9.33 <.0001

 

 

 

 

 

 

 

168

 

Table A-9. Differences of Least Squares Means

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Effect Conc. _Conc. Estimate Standard DF t Pr > |t|
Error Value

Conc. 10"] 10"2 116.01 39.0112 54 2.97 0.0044
Conc. 10"] 10"3 162.61 39.0112 54 4.17 0.0001
Conc. 10"] 10"4 138.88 39.0112 54 3.56 0.0008
Conc. 10"] 10"5 150.88 39.0112 54 3.87 0.0003
Cone. 10"] 10"6 168.12 39.0112 54 4.31 <.0001
Conc. 10"] 10"7 164.74 39.01 12 54 4.22 <.0001
Conc. 10"] Control -23.8222 39.0112 54 -0.61 0.544

Cone. 10"2 10"3 46.6 39.0112 54 1.19 0.2375
Conc. 10"2 10"4 22.8667 39.0112 54 0.59 0.5602
Conc. 10"2 10"5 34.8667 39.0112 54 0.89 0.3754
Conc. 10"2 10"6 52.1111 39.0112 54 1.34 0.1872
Cone. 10"2 10"7 48.7333 39.0112 54 1.25 0.217

Conc. 10"2 Control -139.83 39.0112 54 -3.58 0.0007
Conc. 10"3 10"4 -23.7333 39.0112 54 -0.61 0.5455
Conc. 10"3 10"5 -11.7333 39.0112 54 -0.3 0.7647
Cone. 10"3 10"6 5.5111 39.0112 54 0.14 0.8882
Conc. 10"3 10"7 2.1333 39.0112 54 0.05 0.9566
Conc. 10"3 Control -186.43 39.01 12 54 -4.78 <.0001
Conc. 10"4 10"5 12 39.0112 54 0.3] 0.7596
Conc. 10"4 10"6 29.2444 39.0112 54 0.75 0.4567
Conc. 10"4 10"7 25.8667 39.0112 54 0.66 0.5101
Cone. 10"4 Control -162.7 39.0112 54 -4. 1 7 0.0001
Conc. 10"5 10"6 17.2444 39.01 12 54 0.44 0.6602
Conc. 10"5 10"7 13.8667 39.0112 54 0.36 0.7236
Conc. 10"5 Control -1 74.7 39.01 12 54 -4.48 <.0001
Cone. 10"6 10"7 -3.3778 39.0112 54 -0.09 0.9313
Conc. 10"6 Control -191.94 39.0112 54 -4.92 <.0001
Conc. 10"7 Control -188.57 39.0112 54 -4.83 <.0001

 

 

 

 

 

 

 

 

169

 

A.3 AN OVA ANALYSIS FOR IMMUNOSENSOR SPECIFICITY

The Mixed Procedure

Table A-10. Type 3 Tests of Fixed Effects

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Effect N151? 11))? Vine Pr > F

Pathogen ] 96 2.07 0.1537

Concentration 96 0.72 0.6084

Pathogen*Concentration 96 0.83 0.5284

Table A-ll. Estimates
Label Estimate Standard DF t Pr > |t|
Error Value

10"] vs. Control for E. coli -50.8222 34.6163 96 -1.47 0.1453
10"2 vs. Control for E. coli 7.0167 34.6163 96 0.2 0.8398
10"3 vs. Control for E. coli -38.4889 34.6163 96 -1.11 0.269
10"4 vs. Control for E. coli -54.7333 34.6163 96 -1.58 0.1171
10"5 vs. Control for E. coli -50.7111 34.6163 96 -1.46 0.1462
10"] vs. Control for S. Enteritidis -9.4778 34.6163 96 -0.27 0.7848
10"2 vs. Control for S. Enteritidis -0.4111 34.6163 96 -0.01 0.9905
10"3 vs. Control for S. Enteritidis -l6.4333 34.6163 96 -0.47 0.6361
10"4 vs. Control for S. Enteritidis 0.9667 34.6163 96 0.03 0.9778
10"5 vs. Control for S. Enteritidis 22.3 34.6163 96 0.64 0.521

 

 

 

 

 

 

170

 

AA

The Mixed Procedure

ANOVA ANALYSIS FOR LETTUCE TESTING

Table A-12. Type 3 Tests of Fixed Effects

 

 

 

Num Den
Effect DF DF F Value Pr > F
Concentration 7 64 25.37 <.0001

 

 

 

 

 

 

Table A-l3. Least Squares Means

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Effect Estimate Standard DF t Pr > |t|
Error Value
Concentration 10"] 290.86 16.1587 64 18 <.0001
Concentration 10"2 123.69 16.1587 64 7.65 <.0001
Concentration 10"3 99.7889 16.1587 64 6.18 <.0001
Concentration 10"4 132.66 16.1587 64 ' 8.21 <.0001
Concentration 10"5 150.48 16.1587 64 9.31 <.0001
Concentration 10"6 99. 1 16.1587 64 6.13 <.0001
Concentration 10"7 102.37 16.1587 64 6.34 <.0001
Concentration Control 288.23 16.1587 64 17.84 <.0001

 

171

 

Table A-14. Differences of Least Squares Means

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Effect Conc. _Conc. Estimate Stgndard DF t Value Pr > |t|
rror

Conc. 10"] 10"2 167.17 22.8518 64 7.32 <.0001
C0110. 10"] 10"3 191.07 22.8518 64 8.36 <.0001
COHC- 10"] 10"4 158.2 22.8518 64 6.92 <.0001
COHC- 10"] 10"5 140.38 22.8518 64 6.14 <.0001
COHC- 10"] 10"6 191.76 22.8518 64 8.39 <.0001
CODC- 10"1 10"7 188.49 22.8518 64 8.25 <.0001
COHC- 10"] Control 2.6222 22.8518 64 0.1 1 0.909

COHC- 10"2 10"3 23.9 22.8518 64 1.05 0.2996
CODC- 10"2 10"4 -8.9667 22.8518 64 -0.39 0.6961
C0110. 10"2 10"5 -26.7889 22.8518 64 -1.17 0.2454
COHC- 10"2 10"6 24.5889 22.8518 64 1.08 0.286

Conc. 10"2 10"7 21.3222 22.8518 64 0.93 0.3543
CODC- 10"2 Control -l64.54 22.8518 64 -7.2 <.0001
COHC- 10"3 10"4 -32.8667 22.8518 64 -1.44 0.1552
C0110. 10"3 10"5 -50.6889 22.8518 64 -2.22 0.0301
COHC- 10"3 10"6 0.6889 22.8518 64 0.03 0.976

C0110. 10"3 10"7 -2.5778 22.8518 64 -0.11 0.9105
COHC- 10"3 Control -188.44 22.8518 64 -8.25 <.0001
COHC- 10"4 10"5 -17.8222 22.8518 64 -0.78 0.4383
COIN- 10"4 10"6 33.5556 22.8518 64 1.47 0.1469
COHC- 10"4 10"7 30.2889 22.8518 64 1.33 0.1897
Conc. 10"4 Control -155.58 22.8518 64 -6.81 <.0001
COHC- 10"5 10"6 51.3778 22.8518 64 2.25 0.028

COHC- 10"5 10"7 48.1111 22.8518 64 2.11 0.0392
Cone. 10"5 Control -137.76 22.8518 64 -6.03 <.0001
COHC- 10"6 10"7 -3.2667 22.8518 64 -0. 14 0.8868
COHC- 10"6 Control -189.13 22.8518 64 -8.28 <.0001
Conc. 10"7 Control —185.87 22.8518 64 -8.13 <.0001

 

172

 

A.5 ANOVA ANALYSIS FOR GROUND BEEF TESTING

The Mixed Procedure

Table A-15. Type 3 Tests of Fixed Effects

 

 

 

Num Den
Effect DF DF F Value Pr > F
Concentration 7 64 37.93 <.0001

 

 

 

 

 

 

Table A-16. Least Squares Means

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Effect Conc. Estimate Standard DF t Value Pr > |t|
Enor
Concentration 10"] 262.02 16.0192 64 16.36 <.0001
Concentration 10"2 1 13.8 16.0192 64 7.1 <.0001
Concentration 10"3 80.2556 16.0192 64 5.0] <.0001
Concentration 10"4 75.1889 16.0192 64 4.69 <.0001
Concentration 10"5 1 14.28 16.0192 64 7.13 <.0001
Concentration 10"6 98.0889 16.0192 64 6.12 <.0001
Concentration 10"7 64.9889 16.0192 64 4.06 0.0001
Concentration Control 331.83 16.0192 64 20.71 <.0001

 

173

 

Table A-l7. Differences of Least Squares Means

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Effect Conc. _Conc. Estimate Stgndard DF t Value Pr > |t|
rror

Cone. 10"] 10"2 148.22 22.6545 64 6.54 <.0001
COHC- 10"] 10"3 181.77 22.6545 64 8.02 <.0001
CODC- 10"] 10"4 186.83 22.6545 64 8.25 <.0001
COHC- 10"1 10"5 147.74 22.6545 64 6.52 <.0001
COHC- 10"] 10"6 163.93 22.6545 64 7.24 <.0001
Cone. 10A1 10A7 197.03 22.6545 64 8.7 <.0001
CODC- 10"] Control -69.81 11 22.6545 64 -3.08 0.3030
CODC- 10"2 10"3 33 .5444 22.6545 64 1.48 0.1436
COHC- 10"2 10"4 38.6111 22.6545 64 1.7 0.0932
COHC- 10"2 10"5 -0.4778 22.6545 64 -0.02 0.9832
CODC- 10"2 10"6 15.7] 1 1 22.6545 64 0.69 0.4905
CODC- 10"2 10"7 48.8111 22.6545 64 2.15 0.035

C0110. 10"2 Control -218.03 22.6545 64 -9.62 <.0001
COHC- 10"3 10"4 5.0667 22.6545 64 0.22 0.8237
COHC- 10"3 10"5 -34.0222 22.6545 64 -1.5 0.1381
CODC- 10"3 10"6 -17.8333 22.6545 64 -0.79 0.4341
COHC- 10"3 10"7 15.2667 22.6545 64 0.67 0.5028
COHC- 10"3 Control -251.58 22.6545 64 -1 1.1 <.0001
COHC- 10"4 10"5 -39.0889 22.6545 64 -1.73 0.0893
COHC- 10"4 10"6 -22.9 22.6545 64 -1.01 0.3159
COHC- 10"4 10"7 10.2 22.6545 64 0.45 0.6541
COHC- 10"4 Control -256.64 22.6545 64 -1 1.33 <.0001
CODC- 10"5 10"6 16.1889 22.6545 64 0.71 0.4775
C0110 10"5 10"7 49.2889 22.6545 64 2.18 0.0333
COHC- 10"5 Control -2 1 7 .56 22.6545 64 -9.6 <.0001
CODC- 10"6 10"7 33.] 22.6545 64 1.46 0.1489
CODC- 10"6 Control -233.74 22.6545 64 -10.32 <.0001
COHC- 10"7 Control -266.84 22.6545 64 -] 1.78 <.0001

 

 

 

 

 

 

 

 

174

 

A.6 ANOVA ANALYSIS FOR WHOLE MILK TESTING

The Mixed Procedure

Table A-18. Type 3 Tests of Fixed Effects

 

Num Den
DF DF

Concentration 7 64 32.15 <.0001

Effect F Value Pr > F

 

 

 

 

 

 

 

 

Table A-l9. Least Squares Means

 

Effect Conc. Estimate Standard DF tValue Pr > It]
Enor

 

Concentration 10"] 267.94 18.9017 64 14.18 <.0001

 

Concentration 10"2 274.57 18.9017 64 14.53 <.0001

 

Concentration 10"3 1 16.21 18.9017 64 6.15 <.0001

 

Concentration 10"4 103.44 18.9017 64 5 .47 <.0001

 

Concentration 10"5 116.61 18.9017 64 6.17 <.0001

 

Concentration 10"6 84.6889 18.9017 64 4.48 <.0001

 

Concentration 10"7 76.4 1 8.901 7 64 4.04 0.0001

 

 

 

 

 

 

 

 

Concentration Control 353.88 18.9017 64 18.72 <.0001

 

 

175

Table A-20. Differences of Least Squares Means

 

Standard

Y

1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Effect Conc. _Conc. Estimate Error DF tValue ‘ Pr>tl
Cone. 1041 1042 -6.6222 26.731 64 -025 ' 0.8051
Conc- 1041 1043 151.73 26.731 64 5.68 <.0001 -
Cone. 1041 1044 164.5 26.731 64 6.15 <.0001 ‘
Cone. 1041 1045 151.33 26.73] 64 5.66 <.0001
Cone. 1041 1046 183.26 26.73] 64 6.86 <.0001
Conc- 1041 1047 191.54 26.731 64 7.17 <.0001
Cone. 1041 Control -85.9333 26.731 64 -321 0.2020
Conc- 1042 1043 158.36 26.731 64 5.92 <.0001
Cone. 1042 1044 171.12 26.73] 64 6.4 <.0001
Cone. 1042 1045 157.96 26.731 64 5.91 <.0001
Cone. 1042 1046 189.88 26.731 64 7.1 <.0001
Cone. 1042 1047 198.17 26.731 64 7.41 <.0001
Cone. 1042 Control -7931 1 1 26.731 64 -297 0.4002
Cone. 1043 1044 12.7667 26.731 64 0.48 0.6346
Cone. 1043 1045 .04 26.731 64 -001 0.9881
Cone. 1043 10"6 31.5222 26.731 64 1.18 0.2427
Cone. 1043 1047 39.811] 26.731 64 1.49 0.1413
Cone. 1043 Control -237.67 26.73] 64 -8.89 <.0001
Cone. 1044 1045 -13.1667 26.731 64 -049 0.624
Cone. 1044 1046 18.7556 26.731 64 0.7 0.4854
Conc- 1044 1047 27.0444 26.731 64 1.01 0.3155
Cone. 1044 Control -25043 26.73] 64 -937 <.0001
Cone. 1045 1046 31.9222 26.731 64 1.19 0.2368
Cone. 1045 1047 40.21 1 1 26.731 64 1.5 0.1374
Cone. 1045 Control -23727 26.731 64 -8.88 <.0001
Cone. 1046 1047 8.2889 26.731 64 0.31 0.7575
Cone. 1046 Control -269.19 26.731 64 -1007 <.0001
Cone. 1047 Control -277.48 26.73] 64 -10.38 <.0001

 

 

 

 

 

 

 

 

176

 

 

A.7

The Mixed Procedure

Table A-21. Type 3 Tests of Fixed Effects

 

 

 

 

 

 

 

 

 

ANOVA ANALYSIS FOR SPCE BIOSENSOR SENSITIVITY

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Effec‘ NDan 11):}:1 Veilue P‘ > F
DNA Cone. 5 12 72.19 <.0001
Table A-22. Estimates
Label Estimate Standard DF t Value Pr > |t|
Error
0.00] vs. Control -0.8033 1.9949 12 -0.4 0.6943
0.01 vs. Control 14.3433 1.5827 12 9.06 <.0001
0.1 vs. Control 19.9767 2.2137 12 9.02 <.0001
1 vs. Control 37.3767 2.7075 12 13.8 <.0001
10 vs. Control 330.21 143.02 12 2.31 0.0396
Table A-23. Least Squares Means
Effect DNA Conc. Estimate Standard DF t Pr > |t|
Error Value
DNA Conc. 0.001 4.72 1.2258 12 3.85 0.0023
DNA Conc. 0.01 19.8667 0.1667 12 119.2 <.0001
DNA Conc. 0.1 25.5 1.5567 12 16.38 <.0001
DNA Conc. 1 42.9 2.203 12 19.47 <.0001
DNA Conc. 10 335.73 143.01 12 2.35 0.0369
DNA Conc. Control 5.5233 1.5739 12 3.51 0.0043

 

177

 

Table A-24. Differences of Least Squares Means

 

DNA

DNA

Standard

t

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Effect Conc. _Conc. Estimate Error DF Value Pr > m
DNA Conc. 0.001 0.01 -15.1467 1.237 ] 12 -12.24 <.0001
DNA Conc. 0.001 0.1 -20.78 1.9814 12 -10.49 <.0001
DNA Conc. 0.001 1 -38.18 2.5211 12 -15.14 <.0001
DNA Cone. 0.001 10 -331.01 143.02 12 -2.31 0.0392
DNA Cone. 0.001 Control -0.8033 1.9949 12 -0.4 0.6943
DNA Conc. 0.01 0.1 —5.6333 1.5656 12 -3.6 0.0037
DNA Cone. 0.01 1 -23.0333 2.2093 12 -10.43 <.0001
DNA Conc. 0.01 10 -315.87 143.01 12 -2.21 0.0474
DNA Conc. 0.0] Control 14.3433 1.5827 12 9.06 <.0001
DNA Cone. 0.1 1 -17.4 2.6975 12 -6.45 <.0001
DNA Conc. 0.1 10 -310.23 143.02 12 -2.17 0.0509
DNA Cone. 0.1 Control 19.9767 2.2137 12 9.02 <.0001
DNA Conc. 1 10 -292.83 143.03 12 -2.05 0.0432
DNA Conc. 1 Control 37.3767 2.7075 12 13.8 <.0001
DNA Cone. 10 Control 330.21 143.02 12 2.31 0.0396

 

 

 

 

 

 

 

 

178

 

APPENDIX B: DATA

Figure B-l. SEM images of (A) Iron oxide NPs and (B) EAPM NPs

179

 

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g 150
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Cell Concentration (CFUImI)
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8 50 -
t:
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fl
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Cell Concentration (CFUImI)
200

 

100 mglml

150 -

Resistance (kOhm)
01 8
O O

 

 

 

Control 10" 7 10" 4 10" 1
Cell Concentration (CFUImI)

Figure B-2. Immunosensor responses of different EAPM concentrations in B. cereus

180

 

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.15: 150 —
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Figure B-3. Immunosensor responses of different B. cereus antibody concentrations.

181

 

B. anthracis spores monitored after 10 day incubation period

Figure B-4. Light microscopy images of B. anthracis spores after two different

incubation periods. (Final Spore Count — 4.2 X 108 spores/ml)

182

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