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DNA Hybridization on Walls of Electrokinetically
Controlled Microfluidic Channels
by
Lu Chen
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy
Department of Chemistry University of Toronto
© Copyright by Lu Chen 2010
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DNA Hybridization on Walls of Electrokinetically Controlled
Microfluidic Channels
Lu Chen
Doctor of Philosophy
Department of Chemistry University of Toronto
2010
Abstract
The use of microfluidic tools to develop two novel approaches to surface-based
oligonucleotide hybridization assays has been explored. In one of these approaches,
immobilized oligonucleotide probes on a glass surface of a microfluidic channel were able to
quantitatively hybridize with oligonucleotide targets that were electrokinetically injected into
the channel. Quantitative oligonucleotide analysis was achieved in seconds, with nM
detection limits and a dynamic range of 3 orders of magnitude. Hybridization was detected by
the use of fluorescently labeled target. The fluorescence intensity profile evolved as a
gradient that could be related to concentration, and was a function of many factors including
hybridization reaction rate, convective delivery speed, target concentration and target
diffusion coefficient. It was possible to acquire kinetic information from the static
fluorescence intensity profile to distinguish target concentration, and the length and base-pair
mismatches of target sequences. Numerical simulations were conducted for the system, and
fit well with the experimental data.
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In a second approach, a solid-phase nucleic acid assay was developed using
immobilized Quantum Dot (QD) bioprobes. Hybridization was used to immobilize QDs that
had been coated with oligonucleotides having two different sequences. The hybridization of
one oligonucleotide sequence conjugated to a QD (a linker sequence) with a complementary
sequence that was covalently attached to a glass substrate of a microfluidic channel was
shown to be an immobilization strategy that offered flexibility in assay design, with intrinsic
potential for quantitative replacement of the sensing chemistry by control of stringency. A
second oligonucleotide sequence conjugated to the immobilized QDs provided for the
selective detection of target nucleic acids. The microfluidic environment offered the ability to
manipulate flow conditions for control of stringency and increasing the speed of analytical
signal by introduction of convective delivery of target sequences to the immobilized QDs.
This work introduces a stable and adaptable immobilization strategy that facilitates solid-
phase QD-bioprobe assays in microfluidic platforms.
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Acknowledgments
I would like to thank my supervisor, Prof. Ulrich J. Krull, for giving me the
opportunity to pursue my study with him and the insightful guidance he has given me
throughout my graduate studies. I am especially grateful for his unwavering support and
encouragement from the beginning and especially in the end. Also, I want to thank Prof.
Aaron Wheeler and Prof Julie Audet for being in my advisory committee and giving helpful
comments over the years.
I also want to thank Prof. Claudiu Gradinaru and Mr. Amir Mazouchi at the Chemical
and Physical Science (CPS), University of Toronto at Mississauga, for collecting FCS data
for diffusion coefficient estimation. I would also like to thank Prof. David R. McMillen at the
CPS, University of Toronto at Mississauga, for giving me fluorescence microscope use time.
I would like to give special thanks to Dr. Henry Lee and Mr. Yimin Zhou at Emerging
Communications Technology Institute (ECTI), University of Toronto, for giving me clean
room training. My thanks also go to Dr. Sergei Musikhin for providing expertise in laser
alignment.
I would also like to thank my colleagues, Taufik Al-Sarraj, W. Russ Algar, Andrew
Chan, Yevgenia Kratvsova, Dr. Larry Liu, Melissa Massey, Omair Noor, Eleonora
Petryayeva, Anthony J. Tavares, and Lim Ying for the discussion about research and their
friendship. I would like to give special thanks to colleagues who I have worked closely;
specifically Dr. Yali Gao for her help with numerical simulations, W. Russ Algar and
Anthony J. Tavares for their help with work associated with QDs. I am grateful for the extra
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help and great ideas provided by former summer students: Didi Cheung, Omair Noor and
Solongo Wilson. I must thank the administrative staff, Carmen Bryson and Anna Liza
Villavelez, for offering great help when I need it the most.
I would like to thank my parents for their unconditional love and support over the
years. Lastly, I wish to thank my wife, Iris Zhou, and my Son, Ian Chen, for their invaluable
support. I shall forever be in debted to them.
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Overview of Author Contributions
Throughout the projects presented here, I was aided by various members of the
Chemical Sensors Group and other colleagues. Here I outline the contributions that each
person has made towards the work presented herein.
Chapter 4.2 outlines the simulations of surface hybridization kinetics and
electrokinetic transport using a finite element method. I was fortunate to work with Dr. Yali
Gao on this project. The geometry of the channel used for simulation was based on the
microfluidic chips I used in experiments described in Chapter 4.1. I defined the parameters
used for simulations, either from experimental results or literature values. Dr. Gao entered the
parameters and boundary conditions into the COMSOL software. Together we simulated the
processes using the software. I performed all the subsequent computational analyses, and
evaluated the fit of the models with the experimental results.
Chapter 4.3 outlines a regenerable solid-phase nucleic acid assay in an
electrokinetically driven microfluidic platform using immobilized QD-bioprobes. This work
was performed with W. Russ Algar and Anthony J. Tavares, graduate students in CSG group.
Together, Algar and I performed the QD surface modification and preparation of
oligonucleotide-QD conjugates. Tavares collected the spectral overlap and quantum yield
data, which served as background data for characterization of the materials. All other work
was performed by me.
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Table of Contents Acknowledgments.......................................................................................................................... iv
Overview of Author Contributions ................................................................................................ vi
Table of Contents.......................................................................................................................... vii
Symbols and Abbreviations ........................................................................................................... xi
List of Tables ............................................................................................................................... xvi
List of Figures ............................................................................................................................. xvii
List of Equations ......................................................................................................................... xxii
1 Introduction ................................................................................................................................ 1
1.1 Properties of nucleic acids .................................................................................................. 1
1.1.1 Energetic considerations of nucleic acid hybridization .......................................... 1
1.1.2 Denaturation of nucleic acid hybrids ...................................................................... 2
1.1.3 Effect of pH and ionic strength on stability of DNA hybridization........................ 3
1.1.4 Determination of DNA sequences .......................................................................... 4
1.1.5 Nucleic acid probes................................................................................................. 5
1.1.6 Nucleic acid hybridization assay techniques .......................................................... 6
1.1.7 Transducers for DNA detection .............................................................................. 8
1.2 Microfluidics for nucleic acid hybridization assay........................................................... 10
1.2.1 Introduction of microfluidics ................................................................................ 10
1.2.1.1 Electrophoresis ....................................................................................... 11
1.2.1.2 Electroosmotic flow (EOF) .................................................................... 12
1.2.1.3 Controlling of EOF and DNA transport ................................................. 14
1.2.2 Microfluidic system for DNA analysis ................................................................. 15
1.2.3 Electrokinetically driven microfluidic system...................................................... 17
1.2.3.1 Advantages of electrokinetically driven microfluidic system ................ 17
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1.2.3.2 Joule heating........................................................................................... 18
1.2.4 Microfluidic device fabrication............................................................................. 20
1.2.5 PDMS, plasma treatment and its aging effects ..................................................... 21
1.2.6 Kinetic model of nucleic acid surface hybridization and its relation to convective flow..................................................................................................... 22
1.2.6.1 Factors affecting surface hybridization kinetics and equilibrium .......... 22
1.2.6.2 Kinetic models of nucleic acid surface hybridization ............................ 24
1.2.6.3 Models coupled with convective flow.................................................... 27
1.3 Using Quantum Dots as donors in FRET for nucleic acid hybridization assay................ 28
1.3.1 Introduction........................................................................................................... 28
1.3.2 Quantum dots ........................................................................................................ 29
1.3.3 Surface modification of quantum dots for bioanalytical applications .................. 33
1.3.4 Quantum dots for FRET-based bioanalytical applications ................................... 36
1.3.5 Solid-phase assays using immobilized quantum dots as donors in FRET, and potential for use in microfluidic systems ....................................................... 38
2 Purpose of this thesis................................................................................................................ 40
3 Experimental ............................................................................................................................ 43
3.1 Materials ........................................................................................................................... 43
3.2 Instrumentation ................................................................................................................. 45
3.3 Procedures......................................................................................................................... 48
3.3.1 Preparation of glass substrates .............................................................................. 48
3.3.2 Functionalization of glass substrates with GOPS ................................................. 48
3.3.3 Surface immobilization of probe oligonucleotides ............................................... 49
3.3.4 Details of microfabrication and chip assembly process........................................ 51
3.3.5 EOF mobility measurements................................................................................. 56
3.3.6 DNA hybridization detection protocols ................................................................ 57
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3.3.7 Quantum dot surface modification and preparation of QDs conjugated with two different oligonucleotide sequences............................................................... 58
3.3.8 QD characterization, determining quantum yields and Förster distance .............. 61
3.3.9 Immobilization of QDs in channels ...................................................................... 63
3.3.10 Regeneration of immobilized QDs in channels .................................................... 64
4 Results and discussion.............................................................................................................. 65
4.1 Quantitative DNA hybridization assay in an electrokinetically controlled microfluidic chip............................................................................................................... 65
4.1.1 Introduction........................................................................................................... 65
4.1.2 Chip design ........................................................................................................... 67
4.1.3 Buffer solution selection ....................................................................................... 69
4.1.4 Electrokinetically controlled sample loading, delivery and washing ................... 73
4.1.5 Quantitative DNA hybridization in electrokinetically driven microfluidic chip........................................................................................................................ 77
4.1.6 Quantitative DNA analysis using DNA hybridization.......................................... 80
4.1.7 Hybridization signal profiles for distinguishing different target sequences ......... 83
4.1.8 Summary ............................................................................................................... 86
4.2 Simulations of surface hybridization kinetics and electrokinetic transport ...................... 87
4.2.1 Introduction........................................................................................................... 87
4.2.2 Mathematical model and numerical method......................................................... 88
4.2.3 Simulation results for quantitative extraction of DNA samples by surface hybridization in an electrokinetically driven microfluidic channel ...................... 94
4.2.4 Axial fluorescence intensity profile from hybridization for determination of target concentration .......................................................................................... 95
4.2.5 Comparison between simulation and experimental results................................. 100
4.2.6 Summary ............................................................................................................. 101
4.3 Use of QDs within microfluidic channels for solid-phase nucleic acid hybridization assay.......................................................................................................... 102
4.3.1 Introduction......................................................................................................... 102
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4.3.2 Characterization of QDs and oligonucleotide-QD conjugates............................ 104
4.3.3 Confirmation of hybridization of oligonucleotide-QD conjugates in bulk solution................................................................................................................ 106
4.3.4 Immobilization and stability of QDs in microfluidic channels........................... 109
4.3.5 Nucleic acid hybridization assay using immobilized QDs ................................. 112
4.3.6 Removing and re-coating modified QDs within channels.................................. 116
4.3.7 Summary ............................................................................................................. 120
5 Future directions..................................................................................................................... 122
References................................................................................................................................... 124
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Symbols and Abbreviations A Adenine or acceptor
Across Cross sectional area
µe Electrophoretic mobility
µeo Electroosmotic mobility
Abs. Absorption
C Cytosine or concentration
COC Cycloolefin copolymer
D Donor or detection or diffusion coefficient
Da Damköhler number
DHLA Dihydrolipoic acid
DIPEA "N,N-diisopropylethylamine "
E Intensity of the electrical field or energy tranfer efficiency
E. coli Escherichia coli
EB Ethidium bromide
Em. Emission
EOF Electroosmotic flow
F Fluorescence intensity
FC Fully complementary
FCS Fluorescence correlation spectroscopy
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FISH Fluorescence in situ hybridization
FRET Fluorescence Resonance Energy Transfer
G Guanine
GOPS 3-glycidoxypropyltrimethoxysilane
h Characteristic length
H Concentration of DNA target-probe hybrids
IPA Isopropyl alcohol
J Spectral overlap integral
Keq Equilibrium constant
knr Rate of non-radiative decay
koff Dissociation rate constant
kon Association rate constant
kr Rate of radiative decay
L Linker
l Channel length
LIF Laser-induced fluorescence
LOD Limit-of-detection
MAA Mercaptoacetic acid
MPA Mercaptopropionic acid
MSA Mercaptosuccinic acid
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n Refractive index
NA Numerical aperture
NC Non-complementary
P Concentration of probe
P0 Initial probe density
PC Polycarbonate
PCR Polymerase Chain Reaction
PDMS Polydimethylsiloxane
Pe Peclet number
PE Polyethylene
PEG Polyethylene glycol
PETG Polyethylenetetraphthalate glycol
PL Photoluminescence
PMMA Polymethyl methacrylate
PMT Photomultiplier tube
PP Polypropylene
PS Polystyrene
PVC Polyvinylchloride
PVP Polyvinylpyrrolidone
QCM Quartz crystal microbalance
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QD Quantum dot
r Radius or donor-acceptor distance
R0 Förster distance
RNA Ribonucleic acid
RT-PCR Real-time PCR
SAW Surface acoustic wave
SHOM Sequencing by hybridization to oligonucleotide microchip
SMA Spinal Muscular Atrophy
SMN Survival motor neuron
SMN1 A sequence of survival motor neuron 1 gene
SNP Single Nucleotide Polymorphism
SPR Surface plasmon resonance
T Thymine or target
TBMP 1 × TB + 30 mM MgSO4 + 0.1 % (w/v) PVP
TCEP Tris(2-carboxyethyl)phosphine
Tm Melting temperature
TOP Trioctyl phosphine
TOPO Trioctyl phosphine oxide
Tris Tris(hydroxymethyl)aminomethane
u Sample flow velocity
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UidA A sequence for diagnostic of E. coli.
ve Electrophoretic velocity
veo Electroosmotic velocity
vnet Net velocity
W Length of surface that is coated with immobilized probes
x Distance
X Distance between the inlet and the initial point on the surface that is
coated with immobilized probes
xeq Equilibrium fraction
z Electrical charges on a species
ε Molar absorptivity
η Viscosity
κ2 Orientation factor
λ Wavelength of light or bulk conductivity
μTAS Micro total analysis systems
τ Time
Φ Quantum yield
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List of Tables Table 3.1 Oligonucleotide Sequencesa used in the work of quantitative hybridization assay 44
Table 3.2 Voltage Program for sample loading and subsequent hybridizationa .....................58
Table 3.3 Oligonucleotide Sequencesa used for the experiments with QDs ...........................60
Table 4.1 Comparison of a static solid phase assay using modified QDs and the solid phase
assay done within microfluidic channels. ..............................................................................116
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List of Figures Figure 1.1 Schematic picture of the electrical double layer which is composed of a compact
layer and a diffuse layer. (adopted from ref. [54])...................................................................13
Figure 1.2 (A) Electronic energy states of a semiconductor in the transition from discrete
molecules to nanosized crystals and bulk crystals. Blue denotes ground state electron
occupation. (B) Structure of a colloidal quantum dot. (C) Absorption (upper) and
fluorescence (lower) spectra of CdSe semiconductor. (Adopted and modified from ref. [103])
..................................................................................................................................................31
Figure 1.3 Modification with thioalkyl acid ligand to make QD soluble in aqueous solution:
a) mercaptoacetic acid (MAA); b) mercaptosuccinic acid (MSA); and c) dihydrolipoic acid
(DHLA). The ionization state of the ligand is determined by the pH of the solution. In this
diagram, only the acidic hydrogen atoms are shown. (adopted from ref. [107]).....................35
Figure 3.1 Schematic representation of the epi-fluorescence microscope setup. ....................47
Figure 3.2 Glass surface functionalization reaction. The silanol groups on the glass can react
with GOPS molecules. After the reaction, the surface was modified with GOPS which has an
epoxy group for further linkage to biomolecules.....................................................................49
Figure 3.3 Oligonucleotides surface immobilization reaction. Immobilization solution was
deposited onto the GOPS modified substrate and reacted with the epoxy group. Through a
ring opening reaction, the amine end group on the oligonucleotides formed a covalent bond
with the GOPS and immobilized on the substrate surface.......................................................51
Figure 3.4 (a) Overview of the structure of the microfluidic chip: the assembly of PDMS
cover with microfluidic channel structure and substrate with immobilized probe sites. (b) H
shaped microfluidic channel structure for DNA hybridization: four reservoirs were labeled
with numbers that were used to identify points of applied electrical potential in Table 3.2. ..52
Figure 3.5 The process for making a negative PDMS cast. (a) transparent photomask with
microchannel structure was printed in local printing shop. (b) Su-8 5 negative photoresist was
spin-coated on a glass slide. (c) UV exposure when photomask was in close contact with the
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Su-8 layer to create desired microchannel pattern. (d) creation of positive master with
crosslinked Su-8 photoresist. (e) liquid PDMS mixture casted onto the positive master and
cured. (f) cured negative PDMS cast after it was peeled from the positive master. ................54
Figure 4.1 A schematic of the H shaped chip which has one 30-mm-long center channel and
two 16-mm-long sidearms connecting four ports. All the channels are 250 µm wide and 9 µm
high. The chip layout is not to scale. .......................................................................................69
Figure 4.2 Comparison of different buffer solutions in terms of the conductivity and the
ability to support DNA hybridization (as determined by fluorescence intensity). Normalized
hybridization signal intensity acquired using standard microarray hybridization experiments
and normalized conductivity of the buffer solutions are compared. The results of 0.5 × SSC +
100 mM phosphate hybridization buffer was used as the standard for normalization. The error
bars represent the standard deviations of five replicates. ........................................................72
Figure 4.3 Typical current monitoring results of several cycles of buffer displacement. The
EOF mobility can be derived from the slopes indicated in the graph......................................75
Figure 4.4 Sample loading, and sample delivery and washing stages for the electrokinetically
driven microfluidic chip...........................................................................................................76
Figure 4.5 Electrokinetically controlled quantitative DNA hybridization in microfluidic
channel (1 µM targets are moving from left side to right side). Six fluorescence signal
intensity line scans were acquired at different times from the target loading, which were at
150, 180, 210, 240, 300 and 600 seconds respectively. No targets can be observed
downstream of region with immobilized probes (even after 600 s). .......................................79
Figure 4.6 Integrated fluorescence signal as a function of DNA target concentration (both in
log scale). The error bars represent the standard deviations of three replicates. .....................81
Figure 4.7 Normalized integrated fluorescence intensity as a function of the fractional
composition of complementary targets; oligonucleotide mixtures contained Cy5 labelled 19-
mer complementary target (SMN1-T19) and non-labelled 20-mer non-complementary strands
(NC) with total concentration of 1 μM. The error bars represent the standard deviations of
three replicates. ........................................................................................................................82
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Figure 4.8 Nomalized hybridization signal profile for targets with different length (19, 34 and
49 base pair target sequences)..................................................................................................84
Figure 4.9 Hybridization signal profile of fully complementary targets (SMN1-T19) and 3
base-pair mismatch sequences (SMN1-3BPM). The error bars represent the standard
deviations of at least two replicates. ........................................................................................86
Figure 4.10 Schematic geometry (2-D) of the microfluidic channel for DNA hybridization
used in the model (not to scale). DNA sample entered the microfluidic channel from the left
inlet and travelled through the channel with a plug-like profile. Probes were immobilized on
one channel wall in the centre of the construct. l and h are the length and the height of the
channel. X represents the distance between the inlet and the initial point on the surface where
immobilized probe molecules were present. W is the length of surface that is coated with
immobilized probes. In the simulation, the geometric parameters were: l = 1.7 mm, h = 9 µm,
X = 0.1 mm, and W = 1.0 mm. .................................................................................................92
Figure 4.11 Transient concentration distribution in cross-section showing the channel height
at position 1.5 mm, which is at the end of the portion of the channel surface that was coated
with immobilized probes..........................................................................................................96
Figure 4.12 The hybridization signal intensity profile along the channel at washing time of 45
s after delivering a 60 s plug of 100 nM oligonucleotide target. .............................................98
Figure 4.13 Hybridization signal intensity profiles of different concentrations of
oligonucleotide targets using a 30 s injection followed by 20 s of washing with buffer. Seven
profiles represented targets of 1, 10, 100, 200, 300, 500 nM and 1 µM concentration,
respectively. ...........................................................................................................................100
Figure 4.14 Comparison of hybridization signal intensity profile between experimental and
simulation results for the condition of 60 s injection of 100 nM oligonucleotide target in the
microfluidic channel. The error bars represent the standard deviations of three replicates. .102
Figure 4.15 The normalized absorption (Abs.) and emission (Em.) spectra of green emitting
QDs and Cy3 and the spectral overlap (shaded area) for the FRET pair...............................106
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Figure 4.16 Two different oligonucleotide sequences conjugated with each QD hybridize
with respective complementary targets in bulk solution. (a) QD conjugated with two different
oligonucleotides (LT and DP) and hybridization with complementary target sequences. The
hybridization was detected by FRET-sensitized Cy3 emission. (b) PL of DNA conjugated
QDs that hybridized with a stoichiometrically equivalent quantity of Cy3-LP2 in TB buffer:
(i) 0.1 µM QD―(1 × LT2, 1 × DP2), (ii) 0.1 µM QD―(2 × LT2, 2 × DP2), (iii) 0.1 µM
QD―(1 × LT2, 1 × DP2) hybridized with 0.1 µM Cy3-LP2, and (iv) 0.1 µM QD―(2 × LT2,
2 × DP2) hybridized with 0.2 µM Cy3-LP2. (c) PL of DNA conjugated QDs hybridized with
a stoichiometrically equivalent quantity of DT2 in TB buffer: (i) 0.1 µM QD―(1 × LT2, 1 ×
DP2), (ii) 0.1 µM QD―(2 × LT2, 2 × DP2), (iii) 0.1 µM QD―(1 × LT2, 1 × DP2)
hybridized with 0.1 µM DT2, and (iv) 0.1 µM QD―(2 × LT2, 2 × DP2) hybridized with 0.2
µM DT2. All PL spectra were background subtracted and normalized. ...............................108
Figure 4.17 Microfluidic chip showing pads of QDs. The inset picture depicts immobilization
of QDs in the channel by hybridization with complementary probes on the surface, while
leaving other oligonucleotides available for binding with a target sequence in solution. .....110
Figure 4.18 Images based on QD fluorescence intensities (all images were background
subtracted): (a) after QDs were injected into the channel. (b) after buffer washing at 125
V/cm. (c) after buffer washing at 250 V/cm. (d) after buffer washing at 375 V/cm. (e) after
buffer washing at 500 V/cm. (f) after buffer washing at 625 V/cm. (g) after buffer washing at
750 V/cm. (h) after re-injection of QDs, followed by buffer washing at 125 V/cm (as for (a)).
All steps were 10 minutes in duration....................................................................................113
Figure 4.19 Immobilization of modified QDs and detection of Cy3 labelled targets using
FRET-sensitized Cy3 emission. (a) Fluorescence image of immobilized QDs using
fluorescence emission from QDs (background subtracted). (b) FRET-sensitized Cy3 emission
using Cy3 channel (FRET background). (c) FRET-sensitized Cy3 emission after the addition
of 100 nM Cy3-NC. (d) FRET-sensitized Cy3 emission after the addition of 100 nM DT1. (e)
100 nM non-complementary and fully complementary sequences FRET-sensitized Cy3
emission signal profile along the channel (FRET signal profiles of (c) and (d) with
background subtracted). .........................................................................................................115
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Figure 4.20 Fluorescence images of cycles of QD immobilization, and demonstration of
nucleic acid assay. (a) image of immobilized QDs conjugates based on fluorescence emission
from the QDs (background subtracted). (b) subsequent image collected after washing using
TBMP buffer with 40% v/v formamide. (c) image after a second injection of QD conjugates
using the fluorescence emission from the QDs (background subtracted). (d) image using the
Cy3 emission channel (FRET background). (e) FRET sensitized Cy3 emission image after
injection of 100 nM DT1 (fully complementary target FRET signal)...................................118
Figure 4.21 Idealized solution melting curves for three different DNA hybrids with melting
temperature of (i) 40 ˚C, (ii) 45 ˚C and (iii) 60 ˚C ................................................................119
Figure 4.22 The reproducibility of the immobilization of QD-oligonucleotide conjugates over
several cycles. (a) using QD―(2 × LT1, 2 × DP1). (b) using QD―(2 × LT2, 2 × DP2). ....120
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List of Equations (1.1) Relationship between diffusion coefficient and time........................................................7
(1.2) Electrophoretic volocity expression ................................................................................11
(1.3) Factors determine electrophoretic mobility.....................................................................11
(1.4) Electroosmotic volocity expression ................................................................................14
(1.5) Net volocity expression...................................................................................................14
(1.6) DNA movement net velocity...........................................................................................15
(1.7) Langmuir isotherm for surface hybridization..................................................................26
(1.8) Damköhler number expression........................................................................................27
(1.9) Quantum yield described by radiative and non-radiative processes ...............................32
(1.10) FRET energy efficiency ................................................................................................36
(3.1) Electoomotic velocity......................................................................................................56
(3.2) Förster distance ......................................................................................62
(3.3) Quantum yield determined by relative method ...............................................................62
(3.4) Modified Quantum yield expression ...............................................................................62
(3.5) Spectral overlap ......................................................................................................62
(4.1) Surface hybridization reation ..........................................................................................90
(4.2) Mass balance on surface with hybridization reaction .....................................................90
(4.3) Modified mass balance on surface ..................................................................................90
(4.4) Covective delivery equation............................................................................................91
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1 Introduction
1.1 Properties of nucleic acids
1.1.1 Energetic considerations of nucleic acid hybridization
The stability of the DNA double helix is very important for the fidelity of the DNA
replication. The proofreading ability of the enzymes involved in the DNA replication process
adds another layer of protection for the highly conservative process of DNA replication.
There are numerous forces that contribute to the stability of the double-stranded nucleic acid
structure. Among them, the most significant force for the stabilization of the double helix is
the hydrogen bonds between complementary Watson-Crick base pairs. Considering the DNA
hybridization process in aqueous solution, there is no significant gain or loss for number of
hydrogen bonds. However, DNA hybridization is a favorable process with an enthalpy
change of -9.8 kcal/mol per base pair. This is due to the fact that the hydrogen bonds formed
between complementary base pairs have a six-membered resonance stabilized ring structure
and inductively stabilized internal dipoles of DNA nucleotides [1]. London dispersion forces
and van der Waals forces are also important to the stability of the secondary structure of a
DNA double helix. The interactions of the π electrons of the aromatic purines and
pyrimidines, which is commonly referred to as “stacking interactions”, provide an average
stabilization energy of -8.1 kcal/mol per base pair dimer. An entropic gain is also realized
during the DNA hybridization process, which is the largest contributor to the overall negative
free energy change for the DNA hybridization process. This change in entropy is acquired
from the release of the loosely bound water molecules back to aqueous solution upon DNA
hybridization. The average number of water molecules associated with each base pair is
between 18 and 28. Upon DNA hybridization, an average of five tightly bound and many
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more loosely bound water molecules, associated with the single-stranded DNA, are released
back into the bulk solution per base pair formation. There are also forces which are
unfavorable to DNA hybridization. The most significant of these is electrostatic repulsion
between the polyanionic phosphate backbones. The phosphate backbones of DNA are usually
negatively charged in solution when in biological conditions. Such electrostatic repulsion can
be reduced by the screening effect of ions in solution. So, the stability of the DNA double
helix depends on the ionic strength of the solution.
1.1.2 Denaturation of nucleic acid hybrids
The DNA double helix can also be destabilized by factors which can affect the
attractive and repulsive forces, including sequence composition, solution composition, ionic
strength, pH and temperature. The process of double-stranded DNA separating into two
single-stranded DNA is called DNA denaturation or DNA melting. If DNA denaturation is
due to temperature change, there is a temperature at which 50% of the population of double-
stranded DNA hybrids is separated into single-stranded DNA. This temperature is called
melting temperature, Tm. Melting temperature is a function of DNA length, sequence
composition, presence of mismatches and environment. Each extra base pair in a short
oligonucleotide (up to 14 base pair) will increase melting temperature of DNA by 2-4
degrees, depending on whether the interactions are A-T or G-C pairs [2]. This is because
breaking G-C pairs requires more energy since there are more hydrogen bonds between G-C
pair than for A-T pair. DNA melting temperature can be quantitatively predicted based on
interactions of nucleotides and knowledge of environmental conditions [3]. Single-stranded
DNA with mismatches has a lower thermodynamic stability in comparison to a fully
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complementary sequence since there are less hydrogen bonds and stacking interactions to
break. Under appropriate conditions of temperature, such thermodynamic stability
differences can be used to discriminate a fully complementary sequence from a sequence
with a single mismatch, which is referred as single nucleotide polymorphism (SNP).
Chaotropic agents such as formamide and urea can promote denaturation of double-stranded
DNA since they can form inductively and resonance stabilized hydrogen bond structures
similar to that formed between complementary DNA base pairs. It is known that the
denaturing agent formamide lowers DNA melting temperatures linearly by 0.6 ˚C per volume
fraction percentage of formamide in the buffer with formamide volume fraction up to 40%
[4].
1.1.3 Effect of pH and ionic strength on stability of DNA hybridization
The electrostatic repulsion between the two negatively charged phosphate backbones
in DNA duplex can reduce the stability of the DNA double helix and even separate the DNA
into two single-stranded DNA. Ions in the solution can reduce this electrostatic repulsion
force by reducing the effective charges on the phosphate backbone through charge screening.
The higher the ionic strength of the solution, the smaller the electrostatic repulsion force
between two phosphate backbones. The stability of the DNA duplex (indicated by Tm)
increases with solution ionic strength. A linear relationship is observed between the
logarithm of salt concentration and Tm for salt concentration below 1 M.
The various ionizable states of the nucleobases can influence the structure of double-
stranded DNA. The degree of protonation of nucleobase influences hydrogen bond
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formation, which is crucial for the stability of a DNA duplex. Ionization of nucleobases tends
to be constant in the pH range between 5 and 9, and DNA duplexes are stable at pH 5-9.
When solution pH is out of this range, the DNA duplex can become destabilized due to the
disruption of some inter-strand hydrogen bonding.
1.1.4 Determination of DNA sequences
Food and water contamination by pathogenic microorganisms continues to pose a
major threat with examples that include the tragedy in Walkerton, Ontario caused by drinking
water contamination with Escherichia coli (E. coli) bacteria, and the extensive recall of foods
by Maple Leaf Foods because of Listeria bacterial contamination [5, 6]. Both incidents
suggest the need for rapid and accurate detection and identification methods for pathogens.
Genetic testing is a potential universal method which one can perform for all organisms. The
invention of the polymerase chain reaction (PCR) technique makes it possible to acquire
enough DNA for testing from one or several copies of a piece of DNA or RNA [7-9]. PCR is
widely used for the detection of pathogens in foods. Real-time PCR (RT-PCR) has been
established as the choice for simultaneous amplification and quantitative determination of
nucleic acid targets.
Genetic testing has distinctive advantages over culturing methods for the detection of
pathogenic bacteria and offers the advantages of sensitive, specific, accurate and rapid
detection of target nucleic acids in a sample. Aside from pathogen detection, genetic tests can
also aid in the identification of whether an individual has a genetic disorder or is a carrier of a
genetic disorder, and can provide insight about predisposition to certain diseases. For both
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pathogens and genetic screening, the testing methods need to be rapid, simple, reliable,
sensitive and specific. Ideally, the methods will also allow for real time monitoring at a low
cost. This combination of attributes represents the holy grail of the genetic testing.
1.1.5 Nucleic acid probes
Nucleic acid probes are usually single-stranded sequences which can hybridize with a
single-stranded target sequence that is unique to certain species [10]. Targets for such probes
are many. Numerous research projects have focused on identification of unique sequences in
one or a few gene regions for species identification, which is now called DNA barcoding
[11]. The effort of establishing a universal DNA barcode library containing details about all
organisms is underway.
The nucleic acid probes have lengths ranging from 10 to 10,000 nucleotide bases. The
most common probe length is between 10 and 30 bases [10, 12]. A nucleic acid probe with a
certain minimum length is required in terms of statistical uniqueness to identify species using
hybridization. On the basis of probability, this length is determined to be 17 nucleotide bases
for identification of a unique sequence in the human genome, while 12 nucleotide bases are
required for E. coli. The use of the shorter nucleic acid probes offers advantages in terms of
speed and selectivity. Long nucleic acid probes require longer reaction times to equilibrate
with analyte because of reduced diffusion rates of a target and slower hybridization. For
example, nucleic acid probes with length of several hundred bases usually require
hybridization time of many hours, while short probes (10-15mer) could equilibrate in tens of
minutes [13]. Increased probe length provides for increased probability of forming a stable
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hybrid with a mismatched sequence, reducing the potential for selectivity. This is due to the
fact that the nucleic acid duplex stability increases with its length, and a mismatch
contributes less to the total energy as the hybrid becomes longer.
1.1.6 Nucleic acid hybridization assay techniques
Nucleic acid hybridization assays are based on the ability of single-stranded nucleic
acids to selectively hybridize with complementary strands. Although the basic underlying
principle of operation is the same, there are many formats in which the hybridization can
operate. Different formats include operation in the solid phase or liquid phase, use of labelled
and unlabelled reagents, application of separation steps and direct or indirect methods of
detection.
Microarray technology uses thousands of ordered DNA spots in an array format for
nucleic acid analysis. Each spot contains one particular probe sequence that is selective for
identification of a particular target. Hybridization is typically transduced by use of
fluorescence markers, and spatial registration allows identification of the specific target.
Microarray technology enables large-scale and parallel analysis of targets simultaneously
[14-16].
DNA microarrays usually require a long incubation time of several hours or even
days. The DNA microarray is typically expected to reach equilibrium before signal
acquisition takes place. This approach does not offer real-time signal acquisition and the
kinetic information which can be used for quantitative analysis is lost. Only recently has the
possibility of real-time DNA microarrays been explored [17]. However, new detection
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chemistries and analysis algorithms still need to be developed to make real-time microarrays
a viable solution for DNA analysis.
DNA microarrays are not well suited for small scale fast point-of-care applications
because of their complicated protocols and instrumentation, and diffusion limited reaction
kinetics [18]. The common DNA microarray technologies are slow since they are based on
passive DNA hybridization which relies solely on the diffusion of the target oligonucleotides
to the probes on a solid surface. Such passive DNA hybridization processes may take many
hours to complete based on typical diffusion coefficients of target oligonucleotides. For a
target oligonucleotide transported only by diffusion, the relation between the travel time, τ,
and the distance, x, is given by:
Dx2
2
=τ (1.1)
This equation describes the movement of a target molecule under diffusion, which is
independent of the concentration gradient. The concentration gradient only determines the
rate of mass transfer. For a typical 19 base pair oligonucleotide with diffusion coefficient of
9.5 × 10-7 cm2 s-1, it takes more than 1.5 hours to travel a distance of only 1 mm. The
dependence on diffusion of target oligonucleotides for hybridization necessitates the use of
relatively large amounts of sample and long hybridization time to achieve reproducible and
reliable hybridization signals. For this reason, a number of strategies for mixing and
alternative transport have been proposed to improve the speed and sensitivity of DNA
detection [19-24].
Moreover, probes of different sequence length and base composition intrinsically
have various melting temperatures [25]. From spot to spot the kinetics and selectivity of
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DNA hybridization will vary according to specific set of environmental conditions. It is
therefore extremely challenging to optimize hybridization conditions at all spots for
mismatch discrimination, and it is virtually impossible to engineer the chemistry of the
system so that one environmental condition concurrently optimizes selectivity at all spots.
1.1.7 Transducers for DNA detection
Transducers play a fundamental role in DNA biosensors and assays. Detection can be
categorized based on the transduction method. The most common transduction methods are
optical, electrochemical and mass based.
Electrochemical transducers have several advantages such as low cost, low power
requirements, simple instrumentation and are relatively easy to miniaturize [26-34]. Mass
based transducers including quartz crystal microbalance (QCM) and surface acoustic wave
(SAW) devices offer label-free methods and have the ability to carry out both steady state
and real time measurements [35-37]. However, they are prone to false positive results due to
non-specific adsorption. For more detailed discussion of transduction using electrochemical
and mass based methods, readers are referred to articles in references [33, 34, 38-43][40].
The most common optical methods are surface plasmon resonance (SPR) and
fluorescence. SPR experiments typically measure the change of the angle of the reflected
light as a function of change of optical mass at the interface. It is considered a label-free
detection method. The ability to carry out both steady state and real time measurements is
advantageous. However, SPR is prone to have false positive results due to non-specific
adsorption [44, 45]. In addition, the mass transport limitation and the heterogeneity of the
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surface probe spots are common issues that contribute to limiting the accuracy of surface
binding kinetics derived from SPR experiments for determining biomolecular affinity and
kinetic rate constants [46, 47].
Fluorescence based assays have many advantages including high sensitivity and
ability to multiplex using multiple fluorophores. Many DNA assay methods and detection
platforms use fluorescence intensity as the analytical signal, with examples being
fluorescence in situ hybridization (FISH), fiber optic-based biosensors and nucleic acid
microarrays. A variety of fluorescence detection schemes can be used for signal generation
using direct fluorescence measurements through optical fibers and waveguides or by using
evanescent wave methods [48]. For fluorescence detection, usually either nucleic acid probes
or targets are labelled directly with fluorophores (such as cyanine dyes used in this thesis)
and increased fluorescence intensity can be detected after hybridization events. Fluorescence
detection can also be achieved by using intercalating dye such as ethidium bromide (EB) and
picogreen. These intercalating dyes will experience a substantial increase in quantum yield
while intercalated into the nucleobase stacking region of DNA duplexes. The use of an
intercalating dye can avoid the requirement of a labeling step. However, this approach
introduces background signal into an experiment due to the presence of free dyes, and a weak
interaction the dyes with single-stranded DNA, resulting in reduction of performance in the
area of limit-of-detection (LOD). Many nucleic acid assay methods such as Taqman® and
molecular beacon techniques are also fluorescence transduction methods based on
fluorescence resonance energy transfer (FRET). A detailed introduction of FRET is in section
1.3.4. There are also many other fluorescence-based nucleic acid detection methods, and a
detailed review has been published [49]. Because of the great sensitivity offered by
fluorescence methods, they are the techniques used in this thesis. Cy5 dye, working as a
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direct label, was used in the study of DNA hybridization kinetics. Green quantum dots and
Cy3 dye were used as a FRET pair for the quantum dot study.
1.2 Microfluidics for nucleic acid hybridization assay
1.2.1 Introduction of microfluidics
Today, “Microfluidics is the science and technology of systems that process or
manipulate small (10-9 to 10-18 liters) amount of liquids, using channels with dimensions of
tens to hundreds of micrometers.” [50]. The study of microfluidic systems is also referred to
as lab-on-a-chip or micro total analysis systems (μTAS) which is a fast growing area in
modern analytical science. Microfluidic systems offer many important capabilities including:
portability; speed; high resolution; sensitivity; small quantities of samples and reagents; and
low fabrication cost. Because of these capabilities, areas such as genomic [51, 52], proteomic
[53], clinical and forensic analysis are all developing methods to take advantage of
microfluidic systems. The fluidic flow control can be achieved in various ways such as
pressure differential, electrical potential and centrifugal force. Fluidic flow control by
electroosmotic flow (EOF) is a widely used method. Although the performance of EOF is
often not satisfactory in a complex microfluidic system, its ease of use by just applying
different voltages without any pumps and valves makes EOF a rational choice for the work in
this thesis. It is noteworthy that the similarities of the dimension of the microfluidic channel
and capillaries used in electrophoresis suggest that many of the development in theory that
are applicable to capillaries can also be applied to microfluidic systems.
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1.2.1.1 Electrophoresis
Charged species such as DNA and quantum dots will move through aqueous solution
under the influence of an electrical field. This motion caused by electrical field is called
electrophoresis. Depending on the charges of the species, positively charged species will
move following the direction of the electrical field while negatively charged species will
move countering the direction of the electrical field. During electrophoresis, charged species
experience two forces: one is the electrostatic columbic force that arises from the applied
electrical field. The other is the frictional force created between charged species and the
surrounding aqueous solution that hinders movement. The two forces have same magnitude
but opposite direction in steady state, and the electrophoretic movement of charged species
will maintain at a constant velocity.
The velocity, ve, of the charged species is proportional to the magnitude of electrical
field E and electrophoretic mobility, µe:
ee Ev μ= (1.2)
The electrophoretic mobility µe is a function of charges on the species, z, viscosity of
the aqueous solution, η, and the radius of the sphere of hydration, r. The relation between
these parameters is shown in equation 1.3:
rz
e πημ
6= (1.3)
The electrophoretic mobility µe is proportional to charge density, z/r (charge/size), of
the species. Species with different charge density will have different electrophoretic mobility
and can be separated using electrophoresis, while species with similar charge density will
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have similar electrophoretic mobility and can not be separated using electrophoresis in
aqueous solution. DNA falls into the latter situation since DNA with different numbers of
bases have similar charge density. DNA with different lengths can not be separated
efficiently using only electrophoresis. Separation can be achieved using gels (such as
polyacrylamide gels) or sieving media which separates DNA with different lengths based on
size. Although, we did not separate different oligonucleotides in our experiments, the ability
of the gel electrophoresis which can separate DNA with different lengths based on their size
and mass to charge ratio offers us the potential opportunity to process complex real samples
before the step of analytical detection.
1.2.1.2 Electroosmotic flow (EOF)
The concept of electroosmotic flow (EOF) originally became important from its role
in capillary electrophoresis. In a capillary made by bare fused silica, the functional groups on
the inner wall of the capillary are silanol (SiOH) groups. In a buffer solution of neutral pH,
these silanol groups are deprotonated to exist as SiO-. The inner wall of the capillary is
therefore negatively charged. Cations in the buffer solution will move to the surface to form
an electrical double layer (as shown in Figure 1.1). The electrical double layer is composed
of a compact layer which tightly binds with the deprontonated silanol groups and a diffuse
layer which is loosely bound and mobile. Upon applying voltage across the length of the
capillary column, cations in the loosely bound diffuse layer move towards the cathode. Such
movement concurrently drags the bulk buffer solution in the capillary. This flow of solution
caused by the combination of surface charge, electrical double layer and electrical potential is
called electroosmotic flow (EOF).
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Figure 1.1 Schematic picture of the electrical double layer which is composed of a compact
layer and a diffuse layer. (adopted from ref. [54])
The channels in a microfluidic system have similar dimensions to those of a capillary,
and EOF can occur in microfluidic channels even if they are not cylindric as would be the
case in a capillary. The channels in the microfluidic system are usually fabricated using
techniques that originated in building microelectronic circuits. The solution displacement
using EOF in rectangular microchannels has also been simulated using mathematical models
[55]. EOF can even be observed in a microfluidic system completely fabricated from
polydimethylsiloxane (PDMS). This may seem anomalous because PDMS is a polymer with
hydrophobic properties. The functional groups on the PDMS surface are hydrophobic methyl
groups instead of ionizable groups. However, it has been suggested that ions in the buffer
solution may adsorb onto PDMS to form a charged surface which can support EOF [56].
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A unique feature of EOF is its flat velocity profile in capillary which is different from
the parabolic velocity profile of hydrodynamic flow. The flat velocity profile of EOF flow
provides the advantage of superior separation resolution in comparison to hydrodynamic flow
since it virtually has no band broadening caused by the velocity profile.
The EOF velocity veo is proportional to the magnitude of electrical field E and EOF
mobility µeo:
eoeo Ev μ= (1.4)
EOF mobility is also a function of buffer solution pH as this affects the surface charge
density.
1.2.1.3 Controlling of EOF and DNA transport
The EOF mobility is related to the surface charge density and the choice of buffer
solution. Control of the surface properties of the capillary/microfluidic channel by surface
modification is therefore an important element of design of microfluidic systems. Surface
modifications includes covalent surface derivatization [57-59], and surface dynamic coating
[60, 61] by including additives in running buffer solution.
In a capillary/microfluidic channel, the net velocity vnet of a charged species is the
vector sum of its electrophoretic velocity ve and the EOF velocity veo both of which are
proportional to the mobility, and the magnitude of the electrical field:
Evvv eoeeoenet )(→→→→→
+=+= μμ (1.5)
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Since DNA is negatively charged, it will be driven towards the anode by the
electrophoretic force when electrical potential is applied. The EOF in a glass-PDMS hybrid
microfluidic channel moves to the cathode when using a neutral pH buffer, which is opposite
to the DNA movement caused by the electrophoretic force. Therefore, the DNA transport
velocity can be represented by:
Ev eoenetDNA )( μμ −=− (1.6)
This suggests that the DNA transport velocity in a microfluidic channel can be controlled by
EOF mobility which can be changed using different surface modification methods.
1.2.2 Microfluidic system for DNA analysis
Aside from the shortcomings described earlier, DNA microarray has other
disadvantages including: (1) large amount of sample material is required for the analysis,
since large detection area need to be fully covered by the sample solution. (2) The linkage
chemistry of the probe to the substrate can undergo solution-dependant cleavage over the
extended incubation time, lowering the reproducibility and sensitivity of the assay. By using
microfluidic systems for DNA analysis, there are a number of advantages such as, reduction
in reagent costs (sample consumption reduced from more than hundreds of μL to several μL),
reduction in the hybridization assay time, and automation for the whole analysis. Many
researchers are using microfluidic systems to improve the speed and sensitivity of DNA
analysis.
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Microfluidic systems offer opportunity to detect DNA with high speed. Several
techniques have been used to enhance mass transport of targets and to reduce diffusion
distances to decrease the hybridization time. Continuous flow of targets by hydrodynamic
pumping within microfluidic channels has been used to improve DNA hybridization [19-22].
Flow of the target solution over the probe surface provides enhanced mass transport of targets
to surface-immobilized probes. In this case, the target transport does not solely depend on
diffusion but also on convection, which leads to reduction of hybridization time.
Introduction of DNA samples with high velocity can induce extensional strain on
targets, which will reduce hybridization time and increase hybridization efficiency [23, 24]. It
has been suggested that long DNA targets tend to change into a super coil form in solution,
which reduces hybridization efficiency due to the inaccessibility of the target sequence by
probes. However, extensional strain created by flow can help to uncoil long DNA targets,
which leads to improved hybridization efficiency. By using this method, a nearly nine-fold
increase of hybridization signal was acquired for a 1.4 kbp single-stranded DNA target.
Active mixing of samples can also be used to reduce hybridization time. The small
dimensions of the microfluidic channel set conditions for small Reynolds number and
resulting laminar flow. This means that the only mixing is by molecular diffusion. The
hybridization speed can be improved by active mixing because it can replenish the target
molecules in the proximity of probes which is depleted by hybridization. Yuen et al. used
fluidic circulation and mixing to improve hybridization reaction efficiency on DNA arrays
[62]. Vijayendran et al. evaluated a three-dimensional micromixer for the purpose of a
surface-based biosensor [63]. Liu et al. observed enhanced signals and fast nucleic acid
hybridization using chaotic mixing [64].
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The rapid detection of DNA target sequences by hybridization has also been
demonstrated by using microfluidic systems with other liquid controlling methods such as
centrifugal pumping [65] and electrokinetic pumping [66]. The detection of single nucleotide
polymorphisms (SNPs) was also demonstrated by using electrokinetically controlled
microfluidic system [67].
There are also some significant challenges associated with the microfluidic systems
for DNA analysis such as provision of effective macro-to-micro interfaces, minimization of
non-specific analyte/wall interactions due to the high surface-to-volume ratio of the
microfluidics, development of low-cost manufacturing methods for microfluidic chips, and
developing materials that concurrently are compatible with biological samples and suitable
for the selected means of transduction.
1.2.3 Electrokinetically driven microfluidic system
1.2.3.1 Advantages of electrokinetically driven microfluidic system
Electrokinetically driven flow is a widely used method that does not require any
pumps and valves. Fluid control can be accomplished by changing applied voltages. The
EOF in a network of channels has been modeled by the electric current flowing in a network
of resistors using Kirchoff’s rules. The proper voltages for fluidic control can be easily
obtained by simple calculation.
The electrokinetically controlled microfluidic system can effectively deliver samples
to the reaction region. Because of its flat velocity profile, the electrokinetically driven flow is
more efficient at delivering targets to probes on the surface compared to the pressure-driven
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flow which has a parabolic velocity profile. It was shown that reaction equilibrium time
could be reduced by 20% using electrokinetically driven flow in comparison to pressure-
driven flow with the same bulk flow rate [68]. Also, it was suggested by Erickson et al. that
non-specific adsorption of DNA targets in the electrokinetically driven microfluidic channel
is minimal due to high surface shearing force [66]. This is a unique benefit since non-specific
analyte/wall interactions due to the high surface-to-volume ratio of the microfluidics are quite
common. With little or no non-specific surface adsorption, the detection limit can be greatly
increased. Moreover, Joule heating phenomena can also be used to control the stringency of
the hybridization condition to attain mismatch discrimination [67].
Electrokinetically driven flow is also well suited for point-of-care and field
applications since control requires only a single voltage supply. Pumps and valves for
conventional fluid handling techniques are not required. The potential usage of a small sized
power supply for fluidic flow control is a great fit for portable applications. Since our
microfluidic system is quite simple, the fluidic flow control using EOF is a rational choice.
1.2.3.2 Joule heating
While electrokinetic pumping can greatly simplify the fluidic flow control in
microfluidic systems, a significant drawback is Joule heating. Joule heating a unique
phenomenon associated with electrokinetic pumping and is caused by electrical current
through the buffer solution. A direct effect of Joule heating is the increase of the temperature
within the microfluidic channel. Since the temperature increase can destabilize the nucleic
acid duplex, and can lead to band broadening for separation caused by increasing the
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diffusion rate, it is very important to control Joule heating in terms of achieving stable DNA
hybridization and reproducible and effective separation in electrokinetically driven
microfluidic systems [69, 70]. Microfluidic systems must have the ability to rapidly transport
heat to the surroundings to maintain uniform and controlled buffer temperature. In fact, it is
the ability to dissipate this heat that limits the strength of the applied electrical field and thus
the maximum flow speed.
The extent of Joule heating is proportional to the applied electrical field and
conductivity of the buffer solution. The conductivity is also a function of temperature. When
Joule heating increases the temperature it will increase the buffer conductivity, which in turn
increases the current and results in more Joule heating.
Joule heating can be controlled by either using buffer with low conductivity or
improving heat dissipation by the microfluidic system. It was suggested by Erickson that
polymeric materials used for microfluidic system fabrication had lower thermal
conductivities than traditionally used glass and silicon. Experimental results suggested that
heat transfer for a PDMS/glass hybrid microfluidic system was more effective than for a
microfluidic system made purely from PDMS. Under high electrical field conditions, they
observed a 5-fold temperature increase in the PDMS/PDMS microfluidic system compared to
a PDMS/glass system [71]. Although the microfluidic system used in the thesis is made of
the PDMS/glass, a buffer with lower conductivity is still preferred to maintain uniform and
controlled buffer temperature within the microfluidic channel and maximizes flow speed.
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1.2.4 Microfluidic device fabrication
In the early 1990s, microfluidic devices were initially fabricated from silicon and
glass [72]. These substrates were used based on well established photolithography and
etching techniques that had been refined for the fabrication processes used in the
microelectronics industry. Glass has a number of properties that make it the ideal substrate
for microfluidic devices, such as stable and well known surface chemistry and optical
transparency. However, it is expensive and sealing of individual devices can be challenging
Since the late 1990s, polymeric materials have become widely used for fabricating
microfluidic devices. The primary attractiveness of polymers is that they typically require
simpler and significantly less expensive manufacturing techniques. Polymeric devices can be
manufactured in large numbers with lower cost by injection molding, casting, or hot
embossing using a high-resolution mold. These devices can be made cheaply enough to be
disposable, which can avoid cross contamination. Polymeric materials are also amenable to
surface modification and the wide variety of chemical and physical properties allows the
matching of specific polymers to particular applications [73]. There are many polymers that
have been used for microfluidic device fabrication including polyethylene (PE),
polypropylene (PP), polymethyl methacrylate (PMMA), polystyrene (PS), polycarbonate
(PC), polyethylenetetraphthalate glycol (PETG), polyvinylchloride (PVC), cycloolefin
copolymer (COC) and polydimethylsiloxane (PDMS).
Although many polymeric devices can be manufactured in large numbers with lower
cost, they are not cost effective in term of making a few prototype microfluidic devices. The
introduction of the soft lithography method by Duffy et al. solved this problem [74]. By using
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an elastomeric polymer, PDMS, it is possible to carry out a complete cycle of design,
fabrication and testing of microfluidic systems rapidly.
1.2.5 PDMS, plasma treatment and its aging effects
Soft lithography is a rapid and flexible method to fabricate microfluidic devices [75].
PDMS is one of the most widely used polymers for fabricating microfluidic devices using the
soft lithography method. PDMS is composed of an inorganic siloxane backbone that supports
organic methyl groups, which combine to offer unique properties including being relatively
chemically inert, non-flammable, non-toxic, and optically transparent.
PDMS is not an ideal polymer for an electrokinetically driven microfluidic system
due to its hydrophobic surface covered by methyl groups. However, using reactive plasma
treatment, PDMS surface can easily be made hydrophilic by the formation of surface silanol
groups [76, 77]. This hydrophilic PDMS can better support electrokinetic pumping and
simplifies aqueous solution filling within the microfluidic channel. A hydrophilic surface can
also help form an irreversible seal with other materials such as glass and silicon [74]. This
hydrophilic PDMS surface is not very stable when in contact with air and can gradually
regain the original hydrophobic property within an hour [78]. However, the hydrophilicity of
the surface can be maintained if the PDMS was placed in aqueous solution immediately after
plasma treatment, which is probably due to the silanol groups tending to stay in a more
hydrophilic environment [59, 79, 80]. Because of PDMS hydrophobic recovery, bringing two
bonding surfaces into contact immediately after plasma treatment is required to make an
irreversible seal. The surface properties of PDMS can also be changed by further chemical
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modification [57-59]. In addition, dynamic surface coating is an option for controlling
surface properties [60].
1.2.6 Kinetic model of nucleic acid surface hybridization and its
relation to convective flow
1.2.6.1 Factors affecting surface hybridization kinetics and equilibrium
In solid-phase analysis, hybridization happens between targets in solution phase and
probes immobilized on a solid support. It is also called heterogeneous hybridization since the
probes and targets are in different phases. Before modeling the nucleic acid surface
hybridization kinetics, it is important to consider each of the major factors that contribute.
The most obvious factor that affects surface hybridization is the concentration of the
reactants. As for most chemical reactions, rates depend on the concentration of the reactants
in solid-phase assays. So, the surface concentration of the probes and the concentration of the
target in the bulk solution are important factors for surface hybridization. Non-specific
surface adsorption of the targets also has an effect on surface hybridization. In fact,
adsorption precedes hybridization in solid-phase assays. The process involves a 2D surface
diffusion followed by hybridization and is particularly significant for surfaces supporting low
densities of immobilized probes [81]. However, when the surface probe density is high, then
hybridization through this mechanism is less likely to happen.
Conformation of the probes on the surface is also related to surface hybridization
processes. Oligonucleotide probes on the surface with secondary structures such as hairpins
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have an energy barrier to cross before they can hybridize with targets in bulk solution. This
has an effect on the overall process of surface hybridization. The conformation of the probes
on a surface can be affected by electrical fields. This is particularly important since the
electrical potential was used to control fluidic flow and movement of target DNA molecules
in our microfluidic system. Since DNA oligonucleotide is a non-spherical particle, its
orientation parallel to the external electrical field is often attributed to the interactions
between the external electrical field and the induced dipole of DNA. Also, a DNA molecule
stretches in an external electrical field [82]. When DNA molecules are immobilized on the
surface, they are align in parallel and stretch in the direction of the external electrical field
[83]. Since the conformation of the probes have an effect on surface hybridization, it is likely
that such alignment and stretching will have an impact on the surface hybridization. Such
alignment and stretching is expected to increase the surface hybridization rate by extending
and unfolding probe strands similar to the extensional strain created by flow which can help
to uncoil long DNA targets and lead to improved hybridization efficiency [23, 24]. At the
same time, the external electrical field could also have an effect on the stability of DNA
hybrids. It was estimated that an external force up to 150 pN is required to melt DNA hybrids
of λ DNA molecule [84]. Smaller forces of tens of pN are required to melt shorter DNA
hybrids. The force exerted on a DNA by external electrical field was estimated as well. With
applied field strength of 1000 V/cm, the force is around 0.2 pN which appears to be at least
one to two orders of magnitude smaller than the force required to melt DNA hybrids [85]. So
the influence of the external force induced by the electrical field on DNA hybrids is at best
marginal.
The target diffusion coefficient and convective delivery in the solution also play a
role in the surface hybridization process. The DNA diffusion coefficient is a function of its
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length, where longer DNA strands have smaller diffusion coefficients. Convective delivery
can enhance the rate of surface hybridization, and the enhancement depends on the relative
rate of target diffusion and the surface hybridization reaction. If the target diffusion rate is
much smaller than the surface hybridization reaction rate, then enhancement by convective
delivery can be great.
Sequences composition, solution composition, ionic strength, pH of solution, and
temperature are also related to surface hybridization, as discussed in 1.1.2. To accurately
model DNA surface hybridization, all of these factors need to be considered. Simplification
is achieved by considering only the most significant factors while neglecting others.
1.2.6.2 Kinetic models of nucleic acid surface hybridization
Several attempts have been made to develop comprehensive models of nucleic acid
hybridization kinetics between immobilized probes on a surface and free targets in bulk
solution. An early model was published by Chan et al. in 1995 [86], which was based on the
receptor-ligand model developed by Axelrod et al [87]. The model developed by Chan et al.
proposed two mechanisms for surface hybridization: 1) direct hybridization between targets
in the bulk solution with probes immobilized on surface; 2) non-specific adsorption of the
targets on surface followed by two-dimensional diffusion towards the probes on surface and
subsequent hybridization. They are referred to as direct and indirect hybridization,
respectively. Several assumptions were made by Chan et al. to build the model including: a)
fixed number of probe molecules immobilized on surface that are equally spaced and
exposed to the same chemical environment; b) each immobilized probe reacts irreversibly
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with only one target molecule in solution (no DNA hybrids dissociate); c) surface coverage
of non-specifically adsorbed target molecules is well below a monolayer so that the lateral
interactions between adsorbed molecules can be neglected; d) the number of available probes
is constant throughout the hybridization process and is independent to the hybridization
reaction rate. The assumption of constant probe numbers is only valid initially. As the
hybridization reaction progresses, the number of available probes inevitably changes. So the
model can only predict the initial rate of hybridization. Also, the authors believed that for all
hybridization reactions, hybridization was the rate limiting reaction. Actually, many surface
hybridization reactions are target diffusion limited due to depletion which makes the
hybridization enhancement by convective target delivery a mechanism to improve surface
hybridization rates.
A comprehensive model developed by Erickson et al. considers both direct and
indirect hybridization mechanisms [81]. The authors suggested that the indirect hybridization
mechanism is an important part of the overall surface hybridization. Instead of providing only
the initial rate of hybridization, this model can be applied to provide quantitative dynamic
predictions of surface hybridization. The model uses a numerical simulation method (finite
element method) to quantitatively calculate the evolution of the surface hybridization
process. However, many parameters required for the model are difficult to measure
quantitatively and may change over the course of the surface hybridization reaction,
including such details as the two-dimensional surface diffusion coefficients, and the
adsorption and desorption rate constants.
Surface hybridization models for competitive multiple hybridization reactions were
published by Zhang et al. [88] and Bishop et al. [89]. Diffusion effects of targets were not
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considered in the model by Zhang et al. They considered the situation where one form of
target hybridized with two types of differently immobilized probes on the surface. The two
forward hybridization reactions were considered the same while the dissociation constants of
the hybrids were different. Bishop et al. used a similar model to simulate surface
hybridization reactions between one type of immobilized probe and two types of different
targets (matched and mismatched targets) [89]. Thus two types of targets were in competition
for hybridization with the same probes. Diffusion effects were considered in this model, but
only the direct hybridization mechanism was considered. They observed that the
hybridization process had two stages: in an early stage, both targets were bound with the
same probes; in a later stage, the matched targets gradually displaced the mismatched targets
from the surface due to thermodynamic stability considerations. Such predictions were
confirmed experimentally by the authors [90].
Alternative approaches have been used for building surface hybridization models.
Vainrub et al. modeled electrostatic charging effects of DNA surface hybridization by
treating DNA targets as ion-penetrable charged spheres interacting with a charged surface
immersed in electrolyte. This corresponds to the hybridization system characterized by a low
surface density of immobilized probes. The authors concluded that the surface electrostatic
interactions (even at zero surface charge or potential) drastically affected binding parameters
[91-94]. The Langmuir isotherm has also been applied as the basis for a surface hybridization
model. The appropriate Langmuir isotherm for surface hybridization is:
1eq
eqeq
xCK
x=
− (1.7)
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where xeq is the equilibrium fraction of hybridized probes, C is the initial concentration of the
target and Keq is the equilibrium constant for the hybridization reaction at the surface which is
independent of xeq. This form applies to a small spot limit, where the hybridization at the
surface does not affect C in the bulk solution. Halperin et al. investigated the role of
electrostatic interactions and competitive surface hybridization using modified Langmuir
isotherms for a polyelectrolyte brush layer with finite thickness [13, 95-97]. Wong et al.
modeled surface hybridization at high DNA densities accounting for the changing
electrostatic interactions within the surface layer which alters rapidly as hybridization
proceeds. The application of positive voltages allowed highly enhanced hybridization and
accelerated kinetics at very high DNA probe density [98]. These models focus on
hybridization equilibrium and seldom consider dynamic target transport effects and the
changing density of hybrids as the hybridization process continues over time. Static models
can not be applied to provide dynamic predictions of surface hybridization.
1.2.6.3 Models coupled with convective flow
Diffusion of DNA targets to a surface coated with immobilized probes has been
recognized as a rate limiting step in the DNA surface hybridization. Such mass transport
limitations arise when the surface hybridization reaction is faster than the rate of delivery of
DNA targets to the surface due to diffusion. The relative rates of surface hybridization
reaction and target diffusion can be represented by Damköhler number Da,
0
/onk PDa
D h= (1.8)
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where kon is the hybridization association constant, P0 is the initial probe density on the
surface, D is the diffusion coefficient of DNA target and h is the characteristic length.
Several attempts have been made to couple surface hybridization models with convective
flow for target delivery. The model based on both direct and indirect hybridization developed
by Erickson et al. has been coupled to convective flow. The coupled model was used to
model the dynamics of hybridization on a biochip surface that had a temperature gradient. It
is shown how the dynamic transport of DNA targets is likely to affect the rate and location of
hybridization [81]. Bishop et al. also coupled their competitive surface hybridization model
with convective flow. When the rate of surface hybridization was much higher than diffusion
transport, convective flow enhanced mass transport and caused higher hybridization rates.
The convective enhancements for a multi-component sample are controlled by target
concentrations, association rate constants, and the dissociation constant of the lower affinity
species through competitive displacement [99][90]. Models of other surface reactions have