CMOS Biosensor for Rapid Detection of Bacteria and Antibiotic Susceptibility by Nasim Nikkhoo A ...

195 Pages·2015·8.88 MB·English

CMOS Biosensor for Rapid Detection of Bacteria and
Antibiotic Susceptibility
by
Nasim Nikkhoo
A thesis submitted in conformity with the requirements
for the degree of Doctor of Philosophy
Graduate Department of Electrical and Computer Engineering
University of Toronto
c Copyright 2015 by Nasim Nikkhoo
�
Abstract
CMOS Biosensor for Rapid Detection of Bacteria and Antibiotic Susceptibility
Nasim Nikkhoo
Doctor of Philosophy
Graduate Department of Electrical and Computer Engineering
University of Toronto
2015
The development of a low-cost, specific and sensitive integrated system for the detection
and identification of bacteria, that can provide results rapidly has been a major research
challenge. This thesis introduces a systematic approach to the selection and design of
appropriate biological components combined with a microelectronics system, that pro-
vides rapid and highly specific detection results at a low sensor cost and using a small
sample volume. The bacterial detection system achieves specific identification through
the use of two types of biological recognition elements: bacteriophages and bacteriocins.
Both systems utilize the rapid e✏ux of potassium ions to the sample as a result of the
infection ofthespecificbacteriain thesamplebythebiological recognition elements. The
potassium e✏ux is a transducing event detectable by a potassium selective field e↵ect
transistor implemented in CMOS, providing conclusive results in less than 10 minutes.
Di↵erent strains of Gram-negative E. coli were tested using bacteriophages, and both
Gram-negative and Gram-positive bacterial species were tested using bacteriocins. Mea-
surement protocols and processing techniques are implemented to cancel the e↵ect of
ion-selective system DC baseline variations and drift. The implemented sensors achieve
the minimum detection limit of 3 107 cfu/ml at 10-minute detection time using the
⇥
PVC-based potassium-sensitive membranes with the sensitivity of 10 6M of potassium.
�
Processing of the raw sample has been simplified to a less-than-5 minute assay that sim-
ply resuspends the raw sample into a constant suspension medium for measurements
using a 100µl sample volume.
ii
A predictive model is presented for the bacterial sensor system that captures the ef-
fects of biological, chemical and environmental parameters on the system output signal.
The bacterial detection system can be repurposed to equivalently determine bacteria sus-
ceptibilitytopore-formingantibiotics. ExperimentalresultsusingpolymyxinBantibiotic
and di↵erent strains of Gram-negative E. coli are presented.
iii
Acknowledgements
The work presented in this thesis could not be completed without guidance, help support
and encouragement of so many people that I had the privilege of getting to know and
interacting with during my years at University of Toronto. I hope to acknowledge them
in a small way.
I would like to thank my supervisor professor Glenn Gulak for his invaluable guidance
and support throughout this journey. His broad vision and encouragement has been a
source of inspiration for me. I would also like to thank my thesis committee members
professor Roman Genov, professor Yu Sun, professor Amr Helmy, professor Wai Tung
Ng and external examiner professor Vamsy Chodavarapu for their valuable insights and
comments that improved this thesis tremendously. I had the privilege of collaborating
with Dr. Karen Maxwell’s group at department of molecular genetics and I feel greatly
indebted to her for her support, kind mentorship and patience. I would like to thank
Diane Bona that helped me with all biological setup and experiments step by step with
kindness and patience. Special thanks to Alan Gulak for his help in designing antibiotic
experiments.
I feel blessed to get to know so many friends throughout my years at University
of Toronto. I learned many valuable lessons from each one of them. I would like to
specially thank Kelly Reimer, Nichole Cumby, Senjuti Saha and Mostafa Fatehi for their
true friendship, enjoyable discussions and encouragements. They generously taught me
how to perform biological assays, spent so much time explaining the science and lent
me their recipes, bu↵ers, hard-made plates and more. I would like to thank Meysam
Zargham and Michal Fulmyk for their true friendship, memorable moments and fun
we had. Their presence made my final Ph.D years more productive and enjoyable. I
would like to thank my fellow BA5000 and BA5158 graduate students, Mario Milicevic,
KevinBanovic, AlirezaNilchi, SadeghJalali, MahdiShabany, SamiraKarimelahi, Dustin
Dunwell, Mike Bichan, Alhassan Khedr, Aynaz Vatankhah, Behzad Dehghani, Zeynep
Lulec, Dawei Song, Rosana Murugesu, Arshya Feyz for their friendship and support.
Special thanks to Sara Scharf for her wonderful comments on the thesis and Jeetendar
Narsinghani for his help and support with lab setup and equipments.
No words are su�cient to express my gratitude and love for my mom and dad who
have always been supportive, loving and have encouraged me to achieve the better and
my sister, Neda, who has been cheering me up. I could never complete this work without
their help.
Iwouldliketothankmyhusband,Ali,whowasalwaysthereformeandsupportedme.
He helped me through the tough times during this work through his love and kindness.
iv
Last but not the least, special thanks to my lovely little son, Elias, who has brought
greatest joy and excitement in my life. He entered this world just in time to defend this
thesis with me.
v
Contents
List of Figures xi
List of Tables xix
List of Acronyms xx
List of Symbols xxii
1 Introduction 1
1.1 Motivation for Bacterial Detection and Antibiotic Testing . . . . . . . . . 1
1.2 Bacterial Detection and Antibiotic Testing Systems and Their Specifications 2
1.3 Challenges and Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Outline of the Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2 Fundamentals of Bacterial Sensing Systems 7
2.1 Introduction to Basic Biological Components . . . . . . . . . . . . . . . . 7
2.1.1 Bacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1.2 Antibiotics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.3 Viruses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2 Current Techniques for Bacterial Detection and Identification . . . . . . 10
2.2.1 Visual Inspection . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2.2 Culturing Techniques . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.2.3 Enzyme-Linked Immunosorbent Assay (ELISA) . . . . . . . . . . 13
2.2.4 Phage Typing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2.5 DNA Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3 Biosensors and Their System Block Diagrams . . . . . . . . . . . . . . . 15
2.3.1 Biological Recognition Element (BRE) . . . . . . . . . . . . . . . 16
2.3.2 Recognition-Event Translator . . . . . . . . . . . . . . . . . . . . 16
2.3.3 Electrical Transducer . . . . . . . . . . . . . . . . . . . . . . . . . 17
vi
2.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3 System Design and Modelling of the Bacteria Biosensor 21
3.1 Biological Recognition Element (BRE) . . . . . . . . . . . . . . . . . . . 22
3.1.1 Bacteriophages (“Phages”) . . . . . . . . . . . . . . . . . . . . . . 22
3.1.2 Bacteriocins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.2 Recognition-Event Translator . . . . . . . . . . . . . . . . . . . . . . . . 25
3.2.1 Sensors Utilizing Bacteriophages . . . . . . . . . . . . . . . . . . . 25
3.2.2 Sensors Utilizing Bacteriocins . . . . . . . . . . . . . . . . . . . . 27
3.3 Ion-Selective Electrode Systems as Electrical Transducers . . . . . . . . . 28
3.3.1 Ion-Selective Electrode Systems (ISE Systems) . . . . . . . . . . . 29
3.3.2 Non-Idealities in ISE Systems . . . . . . . . . . . . . . . . . . . . 31
3.4 Analog Front-End and Processing Unit . . . . . . . . . . . . . . . . . . . 31
3.5 Complete Bacterial Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.6 Modelling the System Behaviour . . . . . . . . . . . . . . . . . . . . . . . 35
3.6.1 Ion-Selective Electrode System Output Voltage versus Potassium
Concentration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.6.2 Maximum Ion-Selective Electrode Output Voltage Signal Varia-
tions with Bacterial Cell Concentration . . . . . . . . . . . . . . . 37
3.6.3 ISE System Output Signal Over Time . . . . . . . . . . . . . . . 39
3.6.4 Biosensor Calibration Curve . . . . . . . . . . . . . . . . . . . . . 42
3.6.5 Extracting System Model Parameters from Measurement Results 43
3.6.6 System Model Predictability . . . . . . . . . . . . . . . . . . . . . 46
3.6.7 System Model Summary . . . . . . . . . . . . . . . . . . . . . . . 48
3.7 Experimental Design and Errors . . . . . . . . . . . . . . . . . . . . . . . 49
3.7.1 Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.7.2 Control Experiments . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.7.3 False Positive and False Negatives . . . . . . . . . . . . . . . . . . 50
3.8 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
4 ISFET and Analog Front-End Design 52
4.1 Introduction to Ion-Selective Field E↵ect Transistors (ISFETs) . . . . . . 53
4.1.1 Ion-Selective Membrane . . . . . . . . . . . . . . . . . . . . . . . 56
4.2 ISFET Design and Characterization and ISFET Readout Circuitry . . . 59
4.2.1 Single-Ended vs. Di↵erential ISFET System . . . . . . . . . . . . 61
4.2.2 ISFET Readout Circuitry . . . . . . . . . . . . . . . . . . . . . . 64
4.2.3 Analog to Digital Conversion . . . . . . . . . . . . . . . . . . . . 67
vii
4.3 Design of the First Test IC . . . . . . . . . . . . . . . . . . . . . . . . . . 68
4.4 Design of the Second IC . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
4.4.1 ISFETsConnectedtoaVoltage-ModeDrain-SourceFollowerRead-
out . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
4.4.2 ISFETs Connected to Current-Mode Fixed Source and Drain . . . 80
4.4.3 Di↵erential ISFET plus Drain-Source Follower Readout . . . . . . 82
4.5 Discussion and Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
5 Detection of E. coli Using Bacteriophages 84
5.1 Sample preparation and Processing . . . . . . . . . . . . . . . . . . . . . 85
5.2 Initial Experiments using Commercial ISE . . . . . . . . . . . . . . . . . 85
5.3 System Model Parameter Extraction and
Predictive Model Estimation . . . . . . . . . . . . . . . . . . . . . . . . . 89
5.3.1 EstimationofISEOutputVoltageSignalversusBacterialCellCon-
centration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
5.3.2 ISE System Output Signal Over Time . . . . . . . . . . . . . . . 91
5.4 Test Chip Experimental Setup and Procedures . . . . . . . . . . . . . . . 95
5.4.1 Chip Implementation and Preparation . . . . . . . . . . . . . . . 95
5.5 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.5.1 Experimental Protocol . . . . . . . . . . . . . . . . . . . . . . . . 96
5.5.2 Group A Experiments using T Phage as the biological recognition
6
element . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.5.3 Group B Experiments using � Phage at 37 C . . . . . . . . . . . 99
�
5.5.4 Group C Experiments using � Phage at 23.7 C . . . . . . . . . . 99
�
5.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
6 Detection of Bacteria Using Bacteriocins 102
6.1 Initial Plating Experiments of the Bacteriocin . . . . . . . . . . . . . . . 103
6.2 Selection of Biological Probes Using a Commercial ISE . . . . . . . . . . 104
6.3 System Model Parameter Extraction and Predictive Model Estimation . 108
6.3.1 Estimation of the ISE Output Voltage Signal versus
Bacterial Cell Concentration . . . . . . . . . . . . . . . . . . . . . 108
6.3.2 Calibration Curve Using Commercial ISE . . . . . . . . . . . . . . 111
6.3.3 ISE system Output Signal Over Time . . . . . . . . . . . . . . . . 112
6.4 CMOS Chip Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
6.5 Experimental Results Using the CMOS Chip . . . . . . . . . . . . . . . . 118
6.5.1 CMOS Biosensor Specifications at 10-Minute Detection Time . . . 122
viii
6.5.2 Comparison to State-of-the-Art . . . . . . . . . . . . . . . . . . . 122
6.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
7 Biosensor Application for Antibiotic Susceptibility Testing 125
7.1 Antibiotic Categories and Resistance . . . . . . . . . . . . . . . . . . . . 125
7.2 Model Antibiotics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
7.3 Experimental Design using Polymyxin B (PMB) Antibiotics . . . . . . . 127
7.4 Measurement Results Using CMOS Chip . . . . . . . . . . . . . . . . . . 131
7.4.1 CMOS Biosensor Specifications at 10-Minute Testing Time . . . . 133
7.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
8 Contributions and Future Work 135
8.1 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
8.2 Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
8.3 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
8.3.1 Biological Recognition Elements . . . . . . . . . . . . . . . . . . . 139
8.3.2 Multiple Detection and Identification on a Single CMOS Chip . . 139
8.3.3 Integration of ADC and Processing Unit . . . . . . . . . . . . . . 139
8.3.4 Membrane Optimization . . . . . . . . . . . . . . . . . . . . . . . 140
8.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
Appendix A Protocols 141
A.1 Bu↵ers and Media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
A.1.1 Lennox Broth (LB) . . . . . . . . . . . . . . . . . . . . . . . . . . 141
A.1.2 SM Bu↵er . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
A.1.3 N-Minimal Medium . . . . . . . . . . . . . . . . . . . . . . . . . . 141
A.1.4 Phosphate Bu↵er Saline . . . . . . . . . . . . . . . . . . . . . . . 142
A.2 Bacteriophage Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . 142
A.2.1 T Phage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
6
A.2.2 � Phage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
A.3 Bacteriocin Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
A.4 Raw Bacteria Sample Preparation . . . . . . . . . . . . . . . . . . . . . . 145
A.5 Bacetria Sample Processing . . . . . . . . . . . . . . . . . . . . . . . . . 146
A.6 Potassium-Sensitive Membrane Preparation, Chip Preparation and Mem-
brane Deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
A.6.1 Reagents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
A.6.2 Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
ix
A.6.3 Suppliers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
Appendix B Bacteria Sensing Using Ion-Induced Voltage Fluctuations 148
B.0.4 Experimental Results Using � Phage . . . . . . . . . . . . . . . . 151
B.0.5 Experimental Results Using Pyocin . . . . . . . . . . . . . . . . . 152
B.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
Bibliography 156
x