Development and characterization of nanopore system for nano-vesicle analysis
A Thesis
submitted to the faculty of
Drexel University
By
Gaurav Goyal
in partial fulfilment of the
requirements for the degree
of
Doctor of Philosophy
December 2015
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© Copyright 2015
Gaurav Goyal. All rights reserved.
ii
Acknowledgements
I would like to express my gratitude to my teachers, my family, friends and peers
who have directly or indirectly contributed to my research and my pursuit of the doctoral
degree.
First and foremost, I would like to thank my thesis advisor Dr. Min Jun Kim
who introduced me to solid-state nanopore research and supported, inspired and
challenged me during my research endeavors. Under his guidance, I have grown as a
researcher and developed an analytical bent of mind. He has always encouraged me to
explore new ideas and challenge the existing state of technology. The hardship and the
uncertainty are an integral part of doctoral research but the understanding, the trust and
the support I received from Dr. Kim made this journey comfortable and worthwhile.
Secondly, I would like to thank Dr. Ming Xiao for his willingness to co-advise my
research. I have learnt a lot from him over the years which has helped me to make
progress on research and professional fronts. I would also like to thank my doctoral
committee members Dr. Margaret Wheatley, Dr. Sriram Balasubramanian, Dr. Kambiz
Pourrezaei, Dr. Marek Swoboda and Dr. Leo Han for sparing time to meet with me and
give me important feedback which has helped me to shape up my research to meet the
requirements for graduation in the School of Biomedical Engineering, Science and
Health Systems.
I would also like to thank my research collaborators Dr. Chi Won Ahn and Dr.
Yong Bok Lee at National NanoFab Center; Dr. Seung-Wook Chi and his lab at KRIBB
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in Daejeon, South Korea. I would also thank past and present members of BAST Lab:
Kevin Freedman, Anmiv Prabhu, Wonjin Jo, Armin Darvish, Hoyeon Kim, Paul Kim,
Ukei Cheang, Jamel Ali and Dharma Varapula for their help and support during my
research.
A special thanks to the staff in the Office of Graduate Studies, MEM department
and School of Biomed for being there to help, advise and always promptly solving my
problems.
I would also like to thank my undergraduate mentors who prepared me for a
future in research and my master’s thesis advisor Dr. Yoonkey Nam, who gave me the
first taste of research and supported me to come to the United States to pursue the
doctoral degree.
On the personal front, I would like to thank my parents, my sister and my lovely
wife who supported my goal for doctoral studies and patiently waited for me to progress
through the program. They always offered their love, support and encouragement which
kept me happy and kept me going.
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Table of contents
List of Tables…………………………………………………………………………vii
List of Figures……………………………………………………………..…………viii
Abstract…………………………………………………………………………...….xiii
1. Motivation, Specific Aims and Background……................................................1
1.1 Motivation...............................................................................................1
1.2 Specific Research Aims ………………………………………………..3
1.3 Background
1.3.1 Nanoparticle characterization techniques....................................5
1.3.2 Resistive pulse sensing and development of solid-state
nanopores………………………………………..………..........7
1.3.3 Solid-state nanopore fabrication………………………………..9
1.3.4 Nanopore operational principles………………………………13
1.3.5 Deformation of lipid vesicles in strong electric fields…………16
2. Investigation of nanopore translocation of sub-100 nm particles at low salt
concentration …………………………………………………………………19
2.1 Introduction…………………………………………………………...19
2.2 Materials and methods………………………………………………...23
2.2.1 Gold nanoparticle fabrication…………………………………23
2.2.2 Gold nanoparticle characterization……………………………24
2.2.3 Experimental set-up and single channel recordings…………..24
2.2.4 Multiphysics simulations……………………………………...26
2.3 Results and discussion………………………………………………...29
2.3.1 Gold nanoparticle characterization……………………………29
2.3.2 Effect of low ionic strength electrolyte and the stability of
colloidal gold………………………………………………….30
2.3.3 Non-canonical translocation signals obtained both at positive and
negative transmembrane voltages……………………………..33
v
2.3.4 Effect of salt concentration and relative pore geometry on
translocation signals…………………………………………..36
2.3.5 Multiphysics simulations to explore the effects of different
experimental parameters………………………………………39
2.4 Conclusions…………………………………………………………...45
3. Use of solid-state nanopores to study co-translocational deformation of nano-
liposomes……………………………………………………………………..47
3.1 Introduction…………………………………………………………...47
3.2 Materials and methods………………………………………………..50
3.2.1 Nanopore fabrication…………………………………………50
3.2.2 Analyte preparation and characterization…………………….51
3.2.3 Experimental set-up…………………………………………..52
3.3 Results and discussion………………………………………………..53
3.3.1 Nanopore drilled in silicon nitride windows…………………53
3.3.2 Characterization of liposomes and polystyrene particles using
TEM and DLS…………………………….…………………..54
3.3.3 Detection of liposome translocation………………………......55
3.3.4 Detection of polystyrene particles translocation………………60
3.3.5 Comparison of voltage dependent translocation behavior of
liposomes and polystyrene particles…………………………..64
3.4 Conclusions…………………………………………………………...70
4. Exosome deformation detection and molecular profiling using solid-state
nanopores…………………………………………………………………......71
4.1 Introduction………………………………………………………...…71
4.2 Materials and methods………………………………………………..76
4.2.1 Nanopore fabrication………………………………………….76
4.2.2 Analyte preparation and characterization……………………..76
4.3 Results and discussion………………………………………………...79
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4.3.1 Characterization of free and immunogold labeled exosomes
using TEM…………………………………………………….79
4.3.2 Detection of exosome translocation…………………………...83
4.3.3 Deformation behavior of exosomes…………………………...86
4.3.4 Detection of exosomes labeled with immunogold for CD63
endosomal marker…………………………………………….90
4.4 Conclusions…………………………………………………………...94
5. Conclusions and future directions………………………………………….…96
5.1 Conclusions…………………………………………………………...97
5.2 Future directions………………………………………………………98
5.2.1 Numerical analysis and quantification of deformation………..98
5.2.2 Comparison of deformation of vesicles with different lipid
bilayer composition and diameters……………………………98
5.2.3 Expansion of experimental repertoire to answer biologically
relevant questions……………………………………………..99
List of references ........................................................................................................100
Vita .............................................................................................................................114
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List of Tables
Table 2.1 Comparison of published literature on nanoparticle translocation through
nanopores……………………………………………………………………………..21
Table 4.1 Fit parameters of log-normal distribution fitting to voltage dependent
exosome translocation data shown in Figure 4.8……………………………………...89
Table 4.2 Fit parameters of log-normal distribution fitting to free and labeled exosome
data shown in Figure 4.11…………………………………………………………….93
viii
List of Figures
1.1. Modes of interactions between nano-vesicles and the recipient cells……………..2
1.2 Process flow for fabricating the solid-state pores. See text for details…………….11
1.3. Solid-state nanopores in a 50 nm thick SixNy membrane supported by silicon. 1.8
nm (a) and 10 nm (b) diameter pores drilled by TEM, and 150 nm (c) diameter pore
drilled by the FIB……………………………………………………………………...12
1.4 (a) Typical experimental set-up wherein particle suspended in electrolyte solution
are electrophoretically driven through nanopore. (b) Resulting current signals obtained.
The current signals are defined the magnitudes of the current drop and residence time
inside the pore…………………………………………………………………………14
1.5 (a) When transmembrane voltage is applied, translocation of electrolyte ions across
the nanopore constitute the baseline current. (b) When a small particle transiently
occupies the nanopore, it results in current drop or a ‘resistive pulse’. (c-e) The
amplitude and duration of the current drop is governed by the dimensions and
orientation of analyte translocation. The current signatures corresponding to
translocation events help to learn about the translocating particles……………………16
1.6 Charge polarity and vesicle deformation as a function of time and the ratio of
𝜆𝑖𝑛/𝜆𝑒𝑥. (a) and (b) represent the transient phases during capacitive charging, for (a) t <
𝜏𝑐ℎ𝑎𝑟𝑔𝑒 and 𝜆𝑖𝑛/𝜆𝑒𝑥 > 1 and for (b) t < 𝜏𝑐ℎ𝑎𝑟𝑔𝑒 and 𝜆𝑖𝑛/𝜆𝑒𝑥 < 1. (c) represents the steady
state when the capacitor is fully charged at t > 𝜏𝑐ℎ𝑎𝑟𝑔𝑒 irrespective of 𝜆𝑖𝑛/𝜆𝑒𝑥. Solid
black lines and dashed black lines indicate original and field induced deformed shape
of the vesicle. Solid blue lines indicate electric field lines…………………………….18
2.1 (a) Micropore chip assembly in the flow cell. (b) Experimental set-up for detection
and recording. ………………………………………………………………………...25
2.2 Geometry used for Multiphysics simulations of particle translocation across the
nanopore. (a) A 1 µm diameter circular domain embedded with 50 nm thick insulating
membrane was used for simulation. (b) Zoomed representation of relative dimensions
of particle and pore……………………………………………………………………28
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2.3 Transmission electron micrograph of gold nanoparticles used for translocation.
Scale bar 25 nm……………………………………………………………………….30
2.4 (a) Electrical double layer around a 20 nm particle suspended in 20 mM KCl
solution. (b) Ion distribution profile along the red dashed line shown in (a). The ion
concentration close to the surface reaches as much as 6 times the bulk concentration.
The surface charge used for the particle was -0.02 C/m2……………………………..32
2.5 Single nanoparticle translocations accompanied by current enhancement. (a) When
a positive electrical potential was applied to the -trans chamber, particles translocated
with conductive spikes. (b) Conductive spikes shown in (a) at higher resolution. Spikes
can be characterized by conduction current amplitude ΔI, and spike duration td. (c)
Represents the conductive spikes recorded when a negative potential was applied. (d)
Spikes shown in (c) at higher resolution. …………………………………………….35
2.6 The dynamics of particle translocation simulated using COMSOL Multiphysics
modeling. A 20 nm diameter particle was simulated to translocate through a 30 nm pore
drilled in a 50 nm insulating membrane. The electrolyte strength was 10 mM KCl and
surface charge density for both particle and the membrane were -0.02 C/m2. The
distribution of counter ions the solid surfaces is color coded and the Surface charge
density is presented in mmol/L. ………………………………………………………40
2.7 Effect of pore diameter on polarity of spikes. Translocation of 20 nm particle was
compared using a 30 nm and a 60 nm diameter pore. For smaller pore, new charge
carriers are introduced in the pore which result in conductive spikes (b), while for the
60 nm pore ions displaced from the pore volume are greater in number than the new
charge carriers bought into the pore, resulting in resistive spikes (d). See text for
details…………………………………………………………………………………42
2.8 Effect of electrolyte strength. For a given pore geometry, balance between the new
charge carriers brought into the pore and the ions displaced from the pore determine the
polarity of the spikes. When using low strength electrolytes, new ions (G) > ions
displaced (R), resulting in conductive spikes (a) where as in case of higher ionic
concentration, new ions (G) < ions displaced (R), resulting in resistive spikes………43
2.9 Effect of particle surface charge density. Particles with higher surface charge density
show higher ionic concentration at the solid surface and are expected to bring more ions
into the nanopore during translocation………………………………………………..45
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3.1 Representative scanning electron micrographs of 250 nm pores drilled in 200 nm
thick silicon nitride membranes. Scale bars are 1 µm and 500 nm for a and b
respectively…………………………………………………………………………...53
3.2. (a) TEM image (Scale bar: 100 nm) of liposomes back stained with 2% uranyl
acetate and the size histogram obtained from measuring liposome diameter in TEM
images. (b) Histogram of liposome hydrodynamic diameter measured using dynamic
light scattering (DLS). (c) TEM image and size histogram for polystyrene particles.
Sample was prepared and imaged similar to liposomes. (d) Hydrodynamic size
histogram for nanoparticles…………………………………………………………...55
3.3 (a) Liposome translocation detection set-up. 250 nm diameter pore drilled in 200
nm thick silicon nitride membrane was used to detect liposome translocation. (b) The
behavior of ionic current before and after adding liposome sample to one side of the
nanopore. Inset shows a high resolution current signature for one of the translocation
events…………………………………………………………………………………56
3.4. Event characteristics for liposome translocations. a. Scatter plot for current drop
versus translocation time at 200 and 300 mV shows very similar population distribution.
Translocation time is plotted on log scale. b. Percentage current drop values show a
decline with increasing transmembrane voltage suggesting deformation of liposomes
during nanopore translocation………………………………………………………...59
3.5. (a) Current drop (ΔI) versus translocation time (Δt) scatter plot for polystyrene
particle translocations at voltages 200 and 300 mV. (b) Percentage current drop
histograms with Gaussian fits for the two voltages. (c) Translocation time histograms
for the two voltages. N=303 and 334 for 200 and 300 mV respectively………………61
3.6 Comparison of translocation behavior of liposomes and polystyrene particles at 300
mV. Both current drop and translocation time in the scatter plot are plotted on log
scale…………………………………………………………………………………...63
3.7 Translocation time versus relative current drop scatter plot for liposome
translocations at different applied voltages. The relative current drop value decreases
steadily with the increasing transmembrane voltage………………………………….65
3.8 (a) Deformation trend observed for liposomes as compared to the polystyrene
particles for 100 -600 mV applied voltages. The rigid polystyrene particles show no
xi
deformation whereas liposome follow an exponential trend and their percent current
drop values decrease with increasing voltages. (b) & (c) Simulation results for electric
field strength inside a nanopore at 600 mV. See text for details………………………66
3.9 Comparison of translocation activity of liposomes and polystyrene particle at high
voltages. For liposomes no activity was seen above 600 mV applied voltage (left panel)
whereas polystyrene particles show translocation well above 600 mV……………….68
3.10. Change in inter-event time with applied voltage for liposome translocations.
Lower and upper whiskers represent 10th and 90th percentile respectively. The median
value decreases steadily from 100 mV to 400 mV and then increases for 500 and 600
mV. No translocations were detected for V > 600 mV……………………………….69
4.1. Different type of membrane vesicles released by the eukaryotic cell…………….73
4.2 Representative TEM images of exosomes stained with phosphotungstic acid and
imaged using JOEL 2100 at 120 keV. ………………………………………………..81
4.3 Size distribution of free exosomes based on the TEM imaging data. The size
histogram was fitted with the Gaussian distribution function with Mean: 91.27 nm and
Standard deviation: 25.46 nm. The r-square value for the Gaussian fit was 0.9582…..82
4.4 Immunogold labeling of exosomes. The CD63 markers on vesicle surface were
bound with biotinylated anti-CD63 antibody, which were then bound with streptavidin
coated 15 nm gold nano particles. The labeled vesicles were imaged using JOEL 2100
TEM operated at 120 keV…………………………………………………………….83
4.5 (a) Representative current drop signals obtained during exosome experiments. (b)
High-resolution current signature for the translocation events………………………..85
4.6 Nanopore clogging by exosomes and unclogging using changing the transmembrane
polarity. Multiple such clogging events were observed during exosome
experiments…………………………………………………………………………...86
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4.7 (a) Scatterplot showing current drop and translocation time distributions of events
recorded at 400, 600 and 800 mV transmembrane voltages using a 250 nm diameter
pore. (b-d) show two dimensional histograms for the translocation data at 400. 600 and
800 mV respectively…………………………………………………………………..87
4.8 Long-normal distribution curves fitted to current drop and translocation time
population distributions at 400, 600 and 800 mV…………………………………….88
4.9 Exponential distribution fitting of the normal percentage current drop data. The data
was normalized to percentage current drop values obtained at 400 mV………………90
4.10 Scatter plot show the population distribution for the free and immunogold labeled
exosomes. The labeled exosomes show higher current drop and translocation time
compared to the free exosomes as expected from their larger size. ………………….91
4.11 Current drop and translocation time populations of free and labeled exosomes fitted
with log-normal distribution functions. ………………………………………...94
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Abstract
Development and characterization of nanopore system for nano-vesicles analysis
Gaurav Goyal
Advisors: Min Jun Kim, Ph.D. and Ming Xiao, Ph.D.
Nano-vesicles have recently attracted a lot of attention in research and medical
communities and are very promising next-generation drug delivery vehicles. This is
due to their biocompatibility, biodegradability and their ability to protect drug cargo and
deliver it to site-specific locations, while maintaining the desired pharmacokinetic
profile. The interaction of these drug loaded vesicles with the recipient cells via
adsorption, endocytosis or receptor mediated internalization involve significant bending
and deformation and is governed by mechanical properties of the nano-vesicles.
Currently, the mechanical characteristics of nano-vesicles are left unexplored because
of the difficulties associated with vesicle analysis at sub-100 nm length scale. The need
for a complete understanding of nano-vesicle interaction with each other and the
recipient cells warrants development of an analytical tool capable of mechanical
investigation of individual vesicles at sub-100 nm scale. This dissertation presents
investigation of nano-vesicle deformability using resistive pulse sensing and solid-state
nanopore devices.
The dissertation is divided into four chapters. Chapter 1 discusses the
motivation, specific aims and presents an overview of nanoparticle characterization
xiv
techniques, resistive pulse sensing background and principles, techniques for fabricating
solid-state nanopores, as well the deformation behavior of giant vesicles when placed
in electric field. Chapter 2 is dedicated to understanding of the scientific principles
governing transport of sub-100 nm particles in dilute solutions. We investigated the
translocation of rigid nanoparticles through nanopores at salt concentrations < 50 mM.
When using low electrolyte strength, surface effects become predominant and resulted
in unconventional current signatures in our experiments. It prompted us to explore the
effects of different experimental parameters using Multiphysics simulations, in order to
optimize our system for nano-vesicle detection and analysis. Chapter 3, discusses
translocation of ~85 nm DOPC liposomes through the nanopore and their co-
translocational deformation due to high field strength and confinement/ flow induced
strain inside the nanopore. The behavior of liposomes was compared to the rigid
polystyrene particles which maintained their shape and did not exhibit any deformation.
Chapter 4 extends the vesicle deformation analysis to exosomes derived from human
breast cancer cell line. Exosomes also exhibit co-translocational deformation behavior;
however, they appear to be less affected by the deforming force inside the nanopore
compared to the DOPC liposomes.
We believe, the results of this research will bring about a novel nano-
bioanalytical platform that can be used to capture comprehensive size and deformability
data on nano-vesicles with high temporal resolution.
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Chapter 1: Motivation, Specific Aims and Background
1.1 Motivation
Nanoparticles are objects with dimensions in a few billionths of a meter (10-9 m
= 1 nm). At this size range, properties of materials differ significantly from their
properties at larger length scales, making nanoscale objects exhibit extraordinary
physical, chemical, optical, electronic and surface properties [1]. In past few decades,
nanoscale objects have been extensively explored as drug delivery vehicles and
particular attention has been paid to nano-vesicles. These objects are spherical and self-
closed structures with diameters in the range of 20 nm – 1000 nm. They consist of a
lipid bilayer encapsulating an aqueous solution and sequestering it from dispersant in
which the vesicles are suspended. These vesicles can be natural (for example exosomes)
or can be synthetically fabricated (liposomes). The liposomes can consist of multiple
concentric lipid bilayer structures and accordingly are classified as unilamellar (single
bilayer) or multilamellar (multiple bilayers) vesicles. Their surface is amenable to
custom functionalization enabling site-specific drug delivery and evasion from immune
recognition and subsequent clearance [2]. The nanoscale dimensions also increase
cellular uptake and improve drug bioavailability [3, 4].
The performance of nano-vesicles as drug delivery vehicles is governed by their
physiochemical characteristics like size, surface charge, lipid composition and stability,
along with their other biological attributes like surface proteins and uptake by the target
cells. The interaction between nano-vesicles and target cells takes place either by
adsorption on cell membrane followed by endocytosis or through receptor-ligand
2
binding and subsequent endocytosis or by direct fusion with the cell membrane as
depicted in Figure 1.1.
Figure 1.1. Modes of interactions between nano-vesicles and the recipient cells.
Adapted from [5].
During all of the above interaction scenarios, nano-vesicles undergo significant
bending and deformation, which is governed by their mechanical properties. Moreover,
when liposomes are used for topical delivery of drugs or cosmetics, their penetration
through stratum corneum into the epidermal layer depends on their flexibility. Despite
the fact that nano-vesicles are very important means of inter-cellular communication
and one of the most studied class of drug delivery vehicles and that their mechanical
3
properties play a key role in cargo delivery to the recipient cells, their nano scale
dimension has prevented their mechanical characterization and investigation of their
deformation behavior. This dissertation focuses on the use of solid-state nanopore
devices to study mechanical deformation of nano-vesicles when they are subjected to
high electric field strength and hydrodynamic strain inside a nanopore.
1.2 Specific Research Aims
The motivation for this research is to demonstrate the use of solid state
nanopores for deformation analysis of nano-vesicles. The established top-down
micro/nano fabrication techniques will be used to fabricate solid-state nanopores, which
will then be used to study translocation of analytes under the influence of electrical
potential. First, we will investigate translocation of gold nano particles dispersed in low
electrolyte solution to understand the transport process of dilute species through a small
solitary nanopore and optimize the transport process for vesicle analysis. Next,
nanopores will be used to study translocation of liposomes and polystyrene particles of
similar size to explore the electric field induced deformation of soft vesicles during
nanopore translocation. These experiments will help lay foundations for deformability
analysis of exosomes. The research will be executed by completion of the following
specific aims:
4
Specific Aim 1: Investigate and optimize the translocation characteristics of nano
particles dispersed in low ionic strength electrolyte
a. Fabricate gold nanoparticles and study their transport behavior in low
concentration electrolyte.
b. Use Multiphysics simulations to study the effect of salt concentration and
relative pore geometry on translocation signals
Specific Aim 2: Study translocation of sub-100 nm liposomes through a solid-state
nanopore and compare their deformation behavior to similar sized rigid
nanoparticles
a. Investigate translocation characteristics of DOPC nano-liposomes and
polystyrene beads.
b. Compare voltage dependent translocation behavior of the two analytes and
detect of co-translocational deformation of liposomes
Specific Aim 3: Characterize exosome translocation, electric field induced
deformation and detect exosome interaction with antibodies against endosomal
markers
a. Detect exosome translocation through the pore and study voltage dependence of
translocation characteristics
b. Investigate interaction of surface protein with the complementary (anti-CD63 )
antibodies using translocation signals
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1.3 Background
1.3.1 Nanoparticle characterization techniques
Although several techniques exist for investigation of nanoscale objects;
however, the most direct method for determining size and particle distribution is
electron microscopy. For particles smaller than 100 nm, majority of size determination
and morphological characterization has been achieved using transmission electron
microscopy. It can enable us to obtain high resolution images of the nanoparticles,
which allows direct estimation of nanoparticle shape, size distribution and dispersity.
However, in the case of soft nano-vesicles [6] it requires sample fixation and contrast
staining which perturb their native structure. Moreover, it is a laborious process, and
requires significant amount of time for sample preparation and access to electron
microscopes. Other popular techniques used to characterize nanoparticles are dynamic
light scattering (DLS), nanoparticle tracking analysis (NTA), confocal microscopy, and
atomic force microscopy (AFM). Both DLS and NTA methods work by measuring the
fluctuation in scattering from the analyte particles caused by their Brownian motion.
The rate at which particles are moving at a given temperature can then be correlated to
their hydrodynamic diameter using the Stokes-Einstein equation. Since the intensity of
the scattered light is directly proportional to the sixth power of the particle diameter,
larger particles scatter more light making smaller particles undetectable, causing
problems especially when nanoparticle preparations are even slightly contaminated by
larger particles. In addition to size, the low refractive index of the vesicles also make
their characterization very challenging using scattering techniques like DLS and NTA.
6
Both these techniques can detect particles larger than 70 nm in diameter. Soft nano-
vesicles such as liposomes and exosomes have also been imaged using the confocal
microscopy technique. This method can be used to study their dynamic interactions with
live cells; however due to resolution limit of optical setup, it cannot provide accurate
information about their size distribution and morphology [7]. On the other hand, atomic
force microscopy (AFM) can provide high resolution information about exosome
morphology but it also requires sample immobilization on mica surface. The interaction
with the surface induces stress on the lipid membrane, resulting in deformation, fusion
or rupture of nano-vesicles. Newer analytical techniques like tunable resistive pulse
sensors (TRPS) and direct flow cytometry are also getting traction as characterizing
tools for nanoscale objects. While direct flow cytometry is difficult to set up for
nanoscale objects and requires very specialized skill, TRPS is easy to operate and shows
good performance for particles larger than 100 nm.
In addition to size estimation, there is also a need to study deformability of soft
nano-vesicles as liposome/ exosome fusion with their target cells or organelles directly
depends on their ability to deform [8]. Mechanical properties of the lipid bilayer have
also been shown to influence biological functions such as fusion and budding [9-11].
Despite much effort, current technologies are limited in their ability to study
deformation of soft particles at sub-micron levels. While a significant body of work
exists on giant vesicles and cells (14-30 µm in diameter [12, 13]), experimental data on
nanoscale biological carriers are limited. Force spectroscopy by AFM is currently the
only technique that can characterize mechanical deformation of nano-vesicles at high
7
resolution. Several researchers have used AFM to study the membrane bending rigidity
of liposomes and viruses [11, 14-20]. There have also been a few recent reports on
morphological analysis of exosomes using the atomic force microscope [21-23] making
it the current method of choice; however, the main drawback of AFM lies in its low-
throughput and the need to immobilize nano-vesicles on mica surface.
1.3.2 Resistive pulse sensing and the development of solid-state nanopores
Detection, counting, and discrimination of micron and nano sized particles find
applications in many different areas of research [24-28]. Devices based on resistive
pulse sensing have been used for high throughput particle analysis since this principle
was used by Wallace H. Coulter in 1953 [29]. In the classical work by Coulter, a small
aperture made in an insulating membrane was used to separate two electrolyte reservoirs
and electrodes placed in the two reservoirs were used to apply transmembrane electrical
potential. When the microparticles were driven under the applied pressure from one
reservoir to the other, they excluded the electrolyte solution from the aperture and
resulted in transient increase in resistance of the aperture. These events of high
resistance were termed as resistive pulses and the technique came to be known as
resistive pulse sensing technique. It provided a simple means for counting cells and
other particles in solution state and became a tool of choice for many biological and
industrial applications [30]. The technique was further developed to analytically
correlate the magnitude of resistive pulses with the size of the particles and to extend it
to include sensing of nano-sized particles. DeBlois et al. used nuclear track etched pores
to detect 90 nm polystyrene particles and nano-scale insect viruses [31, 32]. With the
8
advancements made in fabrication techniques and electrical instrumentation in the past
few decades, microfabricated coulter counters with sophisticated microfluidic interface
have been developed to detect and enumerate microparticles [33, 34], nanoparticles [35-
37], red blood cells [38], pollens [39], and circulating tumor cells [40, 41]. Resistive
pulse sensors based on dynamically resizable elastomeric pores have also been
developed for characterizing micro/nanoparticles [42-45].
These sensors also inspired the use of resistive pulse sensing principle for
detecting biological macromolecules. In late 1990s Kasianowicz et al. used
Staphylococcus transmembrane protein α-hemolysin, suspended in a lipid bilayer, as
the nanoscale orifice to detect the translocation of short polynucleotides at single
molecule resolution [46]. This seminal work by Kasianowicz et al. heralded a new era
in high throughput single molecule detection and resulted in this technique being applied
for DNA detection using α-hemolysin pore [47-49], MspA nanopore [50-52], for direct
RNA detection [53, 54] and towards DNA sequencing efforts [52, 55, 56]. Although
biological nanopores are good candidates for studying DNA and RNA translocations;
however, the pores and the lipid bilayer in which they are suspended suffer from several
limitations. The major shortcomings are fixed pore diameter (1.4 nm diameter for α-
hemolysin), mechanical instability and sensitivity to extreme pH and voltages. These
limitations of biological nanopores have been addressed by the use of solid-state
nanopores which are artificially drilled holes in silicon nitride (or silicon oxide, or
graphene) membranes. The solid state technology makes it possible to fabricate robust
nanopores with variable pore dimensions which can be used over a much wider range
9
of experimental conditions. The solid state pores have perfectly complemented the
biological nanopores for single molecule detection and analysis by expanding the
experimental repertoire; and by incorporating new electrical and/or optical detection
strategies. In the past 10 years, solid-state nanopores emerged as highly versatile sensors
for single molecule analysis and have been widely studied for detection of
polynucleotides [53, 57-62]. Though the big goal for these molecular sensors is to
achieve faster and cheaper next generation DNA sequencing, nanopore technology has
also been used to study protein binding and unbinding, [63] protein conformation
dynamics [64] and for DNA-protein interactions [65, 66]. The use of nanopore
technology for DNA and protein analysis has been extensively reviewed over the years
[67-71]. In addition to DNA and proteins, other analytes such as nanoparticles [72-79],
liposomes [80] and polymers [81, 82] have also been used. These synthetic analytes are
attractive candidates for nanopore analysis as they can be prepared in a variety of sizes
and with user defined chemical properties and can be used to understand the underlying
principles of nanopore translocation.
1.3.3 Solid-state nanopore fabrication
Solid-state nanopores have been fabricated in a variety of substrates [83, 84] but
most widely used substrate has been silicon nitride. For fabrication of solid-state
nanopores, a very thin free standing silicon nitride layer is first produced and then a
solitary nanopore is drilled in the membrane. The silicon nitride membrane is insulating
and is used to separate two electrolyte reservoirs while the solitary nanopore allows for
10
ions to flow from one reservoir to the other. It essentially is a nano version of Coulter
counter discussed above. The modern fabrication techniques allow control over the
thickness of silicon nitride membrane (5 nm – 500 nm) and the diameter of the nanopore
(2 nm – micron scale). The diameter and thickness of the nanopores influence signal to
noise ratio and resolution in these devices, and by controlling these two parameters
solid-state nanopores can be used for high resolution sensing of a variety of analytes
ranging from 2 nm in cross section (DNA/proteins and other biological molecules) to
several hundreds of nanometers in cross section.
The fabrication process for all nanopores for this research starts with fabricating
few nanometer thick free standing silicon nitride membranes, followed by drilling size
controlled pores in the membranes using focused electron or ion beams. The thickness
of the membrane and diameter of the pores is determined by the analyte. For fabricating
the thin free standing membrane, a SixNy layer (typically 50 nm or 200 nm thick) is
deposited on a 4 inch diameter, 375 μm thick silicon wafer using low pressure chemical
vapor deposition (LPCVD). This results in a silicon-rich nitride film, with a tensile
stress in the range of 50 – 150 MPa. This stress is low enough to allow the formation of
a free standing membrane and still allowing easy pore fabrication. A 50 × 50 μm2
window is then be fabricated in silicon using photolithography, Deep Reactive-Ion
Etching (DRIE), and KOH wet etching, resulting in the free standing membrane (Figure
1.2). Pores can be fabricated in the window using a FEI Strata DB 235 focused ion beam
(FIB). A 30 keV Ga+ focused ion beam with a beam current of 30 pA can used to etch
through the membrane. This method for producing solid-state pores provide visual
11
feedback during the formation process and allow controllable fabrication of the desired
sizes. However, the minimum size that can fabricated using FIB is ~30 nm and to
fabricate pores smaller than 30 nm electron beam of transmission electron microscope
is employed. For this research all nanopores are drilled using FIB. Figure 1.3 shows some
representative pores drilled using FIB and TEM methods.
Figure 1.2 Process flow for fabricating the solid-state pores. See text for details.
12
Figure 1.3. Solid-state nanopores in a 50 nm thick SixNy membrane supported by silicon.
1.8 nm (a) and 10 nm (b) diameter pores drilled by TEM, and 150 nm (c) diameter pore
drilled by the FIB. Adapted from [85].
The hallmark of solid-state nanopores is the through pores drilled in thin
insulating membrane, which limits the sensing zone to a very small region of size
commensurate with the dimensions of the particle under investigation. This prevents
multiple particles from occupying the nanopore at the same time, resulting in single
particle investigations. The localization of electric field inside the nanopore also results
in high field strength which cause the analytes to deform, stretch and unfold. This high
field strength inside the pores has been used to study protein-protein unbinding and
unfolding behavior. This dissertation will focus on using this localized electric field to
probe deformation behavior of soft nano-vesicles.
13
1.3.4 Nanopore operational principles
A nanopore sensor set-up typically involves placing an insulating membrane
(with a small nanopore) between two electrolyte chambers and applying a constant
transmembrane electrical potential (Figure 1.4 (a)). This results in a continuous flow of
electrolyte ions through the pore and a steady current in the circuit. When the analyte
particles dispersed in the same electrolyte solution are added to one side of the
membrane, they are electrophoretically driven across the pore and their translocations
result in transient changes in the ionic current that are proportional to the size of the
analyte particles. The drops in the ionic current are termed as ‘ionic current blockades’
or ‘resistive pulses’ (Figure 1.4 (b)).
14
Figure 1.4 (a) Typical experimental set-up wherein particle suspended in electrolyte
solution are electrophoretically driven through nanopore. (b) Resulting current signals
obtained. The current signals are defined the magnitudes of the current drop and
residence time inside the pore.
The shape, amplitude and duration of the blockade events can be used to obtain
information about the translocating particles. The length of resistive pulses (dwell time
inside the pore) and its frequency can give information about the particle charge,
concentration and its interaction with the pore; whereas amplitude of current drop and
the corresponding excluded volume calculations can tell us about particle size
ΔI
Δt
(a)
(b)
15
distribution, aggregation and multimerization. These sensors are especially
advantageous as they can be used to detect analytes in the solution state and at
physiological conditions. Moreover, since the pore is stationary and analyte molecules
are driven through it, hundreds of particles can be analyzed in a few seconds making
nanopores a high throughput detection platform. Furthermore, this sensing approach
provides single molecule/particle information about the analyte and reveal information
about subpopulations and subtle changes in structures and conformations, which are
usually hidden in metrology techniques relying on ensemble averaging.
Figure 1.5 illustrates the effect of particle size and geometry on the current
signature obtained during the translocation process. Particles larger in size result in
deeper ionic blockades (compare (b) & (c)) and high signal-noise-ratio. For spherical
particles, the drop ionic current is more gradual compared to a cylindrical particle,
which produces sharp decline in current leading to current signatures of square shape
(compare (c) and (d)). For two dimensional analytes such as rods or ellipsoids, the
orientation of translocation also affects the current signatures (compare (d) and (e)).
When the long axis of the particle is aligned with the long axis of the nanopore, it results
in long current blockade with small current drop; whereas when the long axes of the
particle and the pore are perpendicular to each other, resulting events are short with
deeper current blockade.
16
Figure 1.5 (a) When transmembrane voltage is applied, translocation of electrolyte ions
across the nanopore constitute the baseline current. (b) When a small particle transiently
occupies the nanopore, it results in current drop or a ‘resistive pulse’. (c-e) The
amplitude and duration of the current drop is governed by the dimensions and
orientation of analyte translocation. The current signatures corresponding to
translocation events help to learn about the translocating particles.
1.3.5 Deformation of lipid vesicles in strong electric fields
When the micron scale lipid vesicles interact with the electric fields a variety of
responses are observed such as deformation and electroporation (formation of transient
pores in the lipid bilayer). This behavior of vesicles has been extensively studied for
investigating the mechanics of cellular membranes and for applications such as
transfection, which involves introducing a foreign molecule into the cytosol to which
17
cellular membrane is otherwise impermeable. Majority of the research in this direction
has been carried out using giant vesicles as they can be directly visualized using
microscopy and their response to the electric field can be easily measured. Both AC
fields (‘referred to as working in the frequency domain’) and DC fields (‘referred to as
working in the time domain’) have been used to study field interaction with the vesicles.
When a vesicle made of charge-free lipid bilayer membrane is placed in a strong
DC electric field, charges accumulate on either side of the bilayer due membrane
impermeability and the vesicle acts as a capacitor whose charging time can be defined
as [86] :
𝜏𝑐ℎ𝑎𝑟𝑔𝑒 = 𝑅𝐶𝑚[1 𝜆𝑖𝑛 + 1 (2𝜆𝑒𝑥)] ⁄ ⁄ 1.1
Where membrane capacitance 𝐶𝑚 is defined as 𝐶𝑚 = 𝜀𝑚/d. Also, 𝜀𝑚is the dielectric
constant of the membrane, d is the membrane thickness, R is the vesicle radius and 𝜆𝑖𝑛
and 𝜆𝑒𝑥 are the conductivities of the internal and external vesicle solutions. Typically
the membrane capacitance is of the order of 1 µFcm-2 and the conductivity of salt-free
solution is on the order of λ ∼ 0.1 μS cm−1. If the radius of the vesicle is assumed to be
100 nm, we obtain a charging time scale 𝜏𝑐ℎ𝑎𝑟𝑔𝑒 ∼ 10 µs.
The membrane capacitance and charge build-up results in a transmembrane
potential, which can be given as:
𝑉𝑚 = 1.5𝑅|𝑐𝑜𝑠𝜃|𝐸[1 − exp(− 𝑡 𝜏𝑐ℎ𝑎𝑟𝑔𝑒⁄ )] 1.2
18
Where E is the amplitude of the applied electric field and 𝜃 is the angle between the
electric field and the surface normal of the vesicle. The charge polarity and vesicle
deformation as a function of time and the ratio of 𝜆𝑖𝑛/𝜆𝑒𝑥 is illustrated in Figure 1.6.
Figure 1.6 Charge polarity and vesicle deformation as a function of time and the ratio
of 𝜆𝑖𝑛/𝜆𝑒𝑥. (a) and (b) represent the transient phases during capacitive charging, for (a)
t < 𝜏𝑐ℎ𝑎𝑟𝑔𝑒 and 𝜆𝑖𝑛/𝜆𝑒𝑥 > 1 and for (b) t < 𝜏𝑐ℎ𝑎𝑟𝑔𝑒 and 𝜆𝑖𝑛/𝜆𝑒𝑥 < 1. (c) represents the
steady state when the capacitor is fully charged at t > 𝜏𝑐ℎ𝑎𝑟𝑔𝑒 irrespective of 𝜆𝑖𝑛/𝜆𝑒𝑥.
Solid black lines and dashed black lines indicate original and field induced deformed
shape of the vesicle. Solid blue lines indicate electric field lines. Adapted from [86]
19
Chapter 2: Investigation of nanopore translocation sub-100 nm particles at low salt
concentration
Specific Aim 1: Investigate and optimize the translocation characteristics of nano
particles dispersed in low ionic strength electrolyte
a. Fabricate gold nanoparticles and study their transport behavior in low
concentration electrolyte.
b. Use Multiphysics simulations to study the effect of salt concentration and
relative pore geometry on translocation signals
Hypothesis: Suspension of nanoparticles in low concentration electrolyte solutions
results in a thick counterion cloud around them, which maintains the colloidal state of
nanoparticles. During nanopore translocation, such experimental conditions could result
in conductive spikes if amount of counter ions brought into the pore exceed the amount
of ions replaced by the translocating particle from the nanopore volume.
2.1 Introduction
Although devices based on resistive pulse sensing can be used for high
resolution microparticle analysis, their real value lies in analyzing nano scale objects
since such analytes cannot be easily characterized using conventional metrological
techniques. A good volume of work exists on detection and analysis of inorganic
20
nanoparticle translocation using the solid-state nanopores. For nanopore experiments,
low concentration electrolytes are typically used to suspend nanoparticles in order to
enhance surface phenomenon like electrical double layer (EDL), which in turn promotes
stability and maintains nanoparticles in colloidal state. During translocation through
the nanopore, interactions between the analyte and the pore surfaces can also lead to
complex and non-canonical current signatures. For example, instead of current
blockade, analyte translocation can result in ‘current enhancement’ or ‘conductive
spike’ when using low concentration electrolytes. Table 2.1 summarizes findings from
some recent reports on particle translocation using solid state nanopores. Prabhu et al.
demonstrated the use of solid-state nanopores to separate 22 and 58 nm polystyrene
particles to model the process of low-density and high-density lipoprotein separation
[72]. The separation was achieved using 150 nm diameter chemically modified
nanopores and surface properties of the pore and the particles were harnessed to
preferentially translocate 22 nm particles through the pores. Lan et al. used chemically
modified conical nanopores (460-500 nm diameter) to study translocation current-time
characteristics of 160 and 320 nm diameter polystyrene beads [73]. Another study on
translocation dynamics of 85 nm silica nanoparticles as a function of applied voltage
was presented by Bacri et al. [75]. They observed increase in ionic current blockade and
event frequency with applied voltage. They also observed short and long-lived events
and reported increase in the ratio of long events at higher voltages. Tsutsui et al. used
low thickness-to-diameter aspect ratio nanopores (50 nm thick, 1200-1500 nm diameter
) to detect and discriminate between 780 nm and 900 nm polystyrene particles in order
21
to mimic graphene nanopore architecture [76]. Wang et al. also reported the use of 28
nm diameter nanopipettes for resistive pulse sensing of 10 nm gold nanoparticles
(GNPs) and GNP-peptides conjugates [77]. For 10 nm gold particles, they observed
resistive spikes; however, for GNP-peptide-antibody complexes the resistive pulses
turned to conductive pulses. Wang et al. attributed the switch from current blockades to
current enhancement to the change in surface charge of the particles when antibodies
were bound to it. Holden et al. also reported conductive spikes in their experiments with
soft hydrogel particles translocating (under applied pressure) through nanopipettes of
diameters smaller than the particles.
Table 2.1 Comparison of published literature on nanoparticle translocation through nanopores.
Author Particle
Diameter
Pore Diameter
and Length*
Dispersant 𝑫𝒑𝒐𝒓𝒆
𝑫𝒑𝒂𝒓𝒕𝒊𝒄𝒍𝒆
Spikes Ref
Prabhu et al. 22 and 58 nm
PS NP
150 nm dia/ 50
nm long
200 mM KCl + 1%
Triton X-100
6.81 and
2.58
resistive [72]
Lan et al. 160 and 320
nm PS NP
460-500 nm
Conical pores
10 mM KCl +
0.1% Triton X-100
~3.12 and
~1.56
resistive [73]
Bacri et al. 85 nm Silica
NP
175 nm dia/ 50
nm long
10 mM KCl 2.05 resistive [75]
Tsutsui et al. 780 and 900
nm PS NP
1200 nm and
1500 nm dia/ 50
nm long
Tris-EDTA buffer 1.53 and
1.66
resistive [76]
Wang et al. 10 nm GNP
modified
with MHDA
28 nm
Conical pores
15 mM NaCl +
10 mM PB
2.8 resistive [77]
10 nm GNP-
peptide (13.9
nm)
2.0 resistive
10 nm GNP-
peptide-IgY
(15.1 nm)
1.85 conductive
*Length refers to the thickness of SixNy membrane used. Not included for conical nanopores.
22
Although these reports provide a good insight into nanoparticle translocation
using solid-state nanopores; however, phenomena such as transport of dilute species at
nanoscale, analyte interaction with the pore surface and the stability of colloids in
different electrolyte and surfactant conditions need further exploration for optimizing
the use of nanopores for nano-vesicle characterization. In this section, we planned to
study gold nanoparticle translocation dynamics at low salt concentration to understand
the factors contributing to current enhancement or ‘conductive spikes’ during nanopore
translocation.
The sensitivity and resolution of resistive pulse sensors are governed by the
diameter and the length of the pore. The relative diameter of the particle and the pore
determines the magnitude of current perturbation caused by particle translocation. As a
rule of thumb, one can reliably detect particles with diameter 0.3-0.7 times the pore
diameter, with bigger particles resulting in higher signal to noise ratio (SNR). Based on
the literature analysis on nanoparticle translocation through solid-state pores, we
hypothesized that the relative size of the nanoparticles and the nanopore play a critical
role in the phenomenon of current enhancement. When using low strength electrolytes
and particles with diameters comparable to that of the nanopore, their surface have the
opportunity to interact during the translocation event which may result in current
enhancement. To explore this phenomenon we used 20 nm diameter gold nanoparticles
and 30 nm diameter nanopore drilled in 50 nm thick silicon nitride membrane. Along
with the pore diameter, the pore length also influences the detection resolution. The
particles size chosen is also smaller than the usual size range reported for liposomes and
23
exosomes and the experimental optimization achieved for this size particles would be
helpful in studying larger sized vesicles.
2.2 Materials and Methods
2.2.1 Gold nanoparticle fabrication
For the translocation experiments gold nanoparticles were prepared in house
using citrate reduction method reported by Frens et al. [87]. The protocol used for gold
nanoparticle fabrication was as below:
a. 50 ml of deionized water was heated in a very clean conical flask on a hot plate/
stirrer. The flask was cover with aluminum foil during the whole process to
prevent the water from evaporating.
b. 15 minutes after the water had started to boil, 500 µl of freshly prepared 1%
Gold (III) Chloride hydrate (HAuCl4) was added and the contents of the flask
were heated while stirring at 160⁰C for 30 min.
c. 1 ml of freshly prepared 1% citric acid solution was added to the flask and the
contents were vigorously stirred for 15 minutes. The color of the solution
changed to wine red indicating the formation of gold nanoparticles.
d. After the appearance of wine red color, heat was turned off and the liquid was
allowed to cool down under constant stirring.
e. After the solution had cooled down, it was transferred to a 50 ml storage tube
and stored in the refrigerator.
24
2.2.2 Gold nanoparticle characterization
Spectrophotometric analysis: The size and concentration of the synthesized
particles was estimated by spectrophotometry as reported by Haiss et al.[88]. It is based
on the fact that GNPs have distinct surface plasmonic resonance (SPR) based on the
size. Haiss et al. had reported standard table for size determination of GNPs based on
the ratio of SPR absorbance and absorbance at 450 nm.
Dynamic light scattering: The hydrodynamic diameter of gold nanoparticles was
determined using dynamic light scattering (DLS) device (Zetasizer Nano ZS, Malvern
Instruments Ltd.). All measurement data met the quality standards set by Malvern.
Transmission electron microscopy: For TEM analysis, 5 µl of as synthesized
colloidal solution was dispensed on a holey carbon coated TEM copper grid and was
allowed to adsorb at room temperature for 2 minutes. After 2 min, excess liquid was
wicked using a filter paper and the TEM grid was air dried. The grid was later loaded in
JOEL 2100 TEM and imaged at 200 keV accelerating voltage.
2.2.3 Experimental set-up and single channel recordings
For device setup, 2-3 mm holes were punched in 3 mm thick PDMS membranes
and these gaskets were used to sandwich the nanopore chips. This assembly was kept
in place using two acrylic flat pieces and fastening screws (Figure 2.1 (a)). The PDMS
gaskets were then filled with the electrolyte solution using fluid exchange holes in the
acrylic pieces. Ag/AgCl electrodes were inserted into the two electrolyte chambers and
were connected to a Molecular Devices Axopatch 200B patch clamp amplifier which
25
can clamp an electrical potential across the nanopore while recording the resulting ionic
current flow (Figure 2.1 (b)).
Figure 2.1 (a) Micropore chip assembly in the flow cell. (b) Experimental set-up for
detection and recording.
The current data was sampled at 200 kHz, digitized using a MD Digidata 1440A
digitizer, and analyzed using pClamp 10.3 software. Recorded data was pre-
conditioned for analysis by electronic low pass Bessel filtering (10 kHz) and manual
baseline correction. Before assembling into the flow cell, the nanopore chips were
sequentially cleaned using acetone, iso-propyl alcohol, and Piranha solution followed
by rinsing with water. Piranha solution used in the chip cleaning process was handled
and processed as per the safety protocol suggested by the Environmental Health and
Safety (EHS) Department of Drexel University.
(a) (b)
26
2.2.4 Multi-physics simulations
COMSOL Multiphysics simulation tool was used to simulate and study the
effect of different experimental parameters on particle translocation behavior. The
simulation model was based on the work by Prabhu et al. [72] and uses multi-ion model
(MIM) which uses Electrostatics and Transport of Diluted Species modules of
COMSOL to simultaneously solve Navier-Stokes, Nernst-Planck and Poisson’s
equations to obtain the distribution of electrical potential, ion distribution and ionic flux.
The governing equations used in MIM as described as follows:
The flow of incompressible fluid is governed by Navier-Stokes equation and the
equation of continuity:
𝜌𝑓 (𝜕��
𝜕𝑡+ (�� ∙ ∇)�� ) = −∇𝑃 + 𝜇∇2�� + 𝜌𝑒�� 2.1
∇ ∙ �� = 0 2.2
Where 𝜌𝑓, 𝑃 and 𝜇 are the electrolyte density, pressure and viscosity respectively. �� =
−∇𝜑, is the electric field and 𝜌𝑒 is surface charge density, given by 𝜌𝑒 = ∑ 𝐹𝑧𝑖𝐶𝑖𝑁1 ,
where 𝐹 is Faraday constant and 𝑧𝑖 and 𝐶𝑖 are the valancy and concentration of ith ion
species respectively.
The transport of ionic species is given by the Nernst-Plank equation:
𝜕𝐶𝑖
𝜕𝑡+ ∇ ∙ (−𝐷𝑖∇𝐶𝑖 + �� 𝐶𝑖 + 𝑧𝑖𝜔𝑖�� 𝐶𝑖 ) = 𝑅𝑖 2.3
27
Where 𝐷𝑖, 𝜔𝑖 and 𝑅𝑖 are the molecular diffusivity, mobility and the chemical reaction
rate of ith ionic species respectively. This model is simplified assuming quasi-steady
state where 𝜕𝐶𝑖
𝜕𝑡= 0 and 𝑅𝑖= 0.
And Poisson equation is used for determination of potential distribution within
the system
∇ ∙ (𝜀∇𝜑) = −𝜌𝑒 2.4
where 𝜀 is the dielectric constant of the electrolyte.
28
Figure 2.2 Geometry used for Multiphysics simulations of particle translocation across
the nanopore. (a) A 1 µm diameter circular domain embedded with 50 nm thick
insulating membrane was used for simulation. (b) Zoomed representation of relative
dimensions of particle and pore.
29
2.3 Results and Discussion
2.3.1 Gold nanoparticle characterization
During spectrophotometric analysis of GNP, surface plasmon resonance peak
was obtained at 519 nm with an absorbance value of 0.9464 and the absorbance at 450
nm was 0.547. The ratio of the absorbance at 519 nm and 450 nm gave the value 1.73
which corresponds to GNPs of 20 nm diameter. Concentration of GNPs was calculated
by taking a ratio of absorbance at 450 nm and extinction coefficient for 20 nm GNPs
and was estimated to be 1 nM.
The hydrodynamic diameter of citrate stabilized GNPs measured using DLS was
20.05 nm. Their diameter increased to 23.09 nm when GNPs were diluted in electrolyte
solution (20 mM potassium chloride (KCl) solution with 0.015% Triton X-100 at pH
5).
Gold nanoparticles were also using TEM. Some representative TEM images are
shown in Figure 2.3. The gold particles were very round and monodispersed as needed
for the translocation experiment. Their core diameter was estimated based on the TEM
images and was 18.2 nm.
30
Figure 2.3 Transmission electron micrograph of gold nanoparticles used for
translocation. Scale bar 25 nm.
2.3.2 Effect of low ionic strength electrolyte and the stability colloidal gold
When charged particles are suspended in an electrolyte, their surface charge is
screened by ions in the solution and it results in increased concentration of counterions
close to the particle surface. The characteristic length up to which the particle surface
charge is screened by the counterions is termed as Debye screening length and is given
by:
𝜅−1(𝑛𝑚) = √𝜀𝑟𝜀𝑜𝑘𝐵𝑇
2𝑁𝐴𝑒2𝐼 2.5
where 𝜀𝑟 is the dielectric constant, 𝜀𝑜 is the permittivity of free space, 𝑘𝐵 is the
Boltzmann constant, T is absolute temperature in kelvins, 𝑁𝐴 is Avogadro number and
e is the elementary charge and I is the ionic strength of the electrolyte in moles/m3. The
extent of the counterion cloud is mainly influenced by the ionic strength of the
31
electrolyte and when using room temperature (25⁰C) and 1:1 electrolyte such as KCl,
equation 2.5 can be simplified to 𝐷𝑒𝑏𝑦𝑒 𝑙𝑒𝑛𝑔𝑡ℎ(𝑛𝑚) ∝ 𝐼(𝑀)−1/2. This suggests that
the extent of the counterion cloud increases with decreasing salt concentration and at
KCl strength of 10-20 mM, a thick counterion cloud (extending 2-3 nm from particle
surface) is expected. Figure 2.3 shows electrical double layer simulated around a 20 nm
particle when it was suspended in 20 mM KCl solution. Figure 2.4 (a) shows the
distribution of counterions around a charged (-0.02 C/m2) 20 nm particle dispersed in
20 mM KCl solution obtained using Multiphysics simulation. Figure 2.4 (b) shows line
graph for concentration of K+ ions along the dashed red line in 2.4 (a). The ion
concentration right next to the solid surface is 6 times higher than the bulk and decreases
exponentially when moving away from the solid surface. The electrical double layer
extends for about 5 nm from the particle surface in this case.
32
Figure 2.4 (a) Electrical double layer around a 20 nm particle suspended in 20 mM KCl
solution. (b) Ion distribution profile along the red dashed line shown in (a). The ion
concentration close to the surface reaches as much as 6 times the bulk concentration.
The surface charge used for the particle was -0.02 C/m2.
When the GNPs are dispersed in high strength electrolytes, the counterion cloud
is very thin and particles tend to aggregate because the attractive van der Waal’s forces
become stronger than the repulsive electrostatic forces. We prevented particle
aggregation by using low salt concentration and by addition of nonionic surfactant
Triton X-100 (0.015% final concentration) to the electrolyte. Low salt concentration
helped in maintaining thick counterion cloud and the surfactant provided hydrodynamic
and steric shielding to the nanoparticles. Previous studies have reported the use of Triton
X-100 but at higher concentrations than used in this study [72, 73]; since the critical
micelle concentration (CMC) for Triton X-100 is 0.02% (w/v), it is expected to form 5-
33
7 nm diameter micelles in the solution when used at final concentration above 0.02%.
While using higher Triton concentrations, if the colloid is not carefully diluted, it can
compromise surfactant’s ability to stabilize the nanoparticles.
2.3.3 Non-canonical translocation signals obtained at both positive and negative
transmembrane voltages
Since GNPs have a negative charge, we anticipated the particles to traverse the
pore when positive voltage was applied to the trans chamber. But interestingly particle
translocations were observed both at negative and positive potential bias (Figure 2.5 (a)
and (c)). The phenomenon of negatively charged particles registering translocation
events when negative potential is applied has been reported previously [89] and was
well characterized by Firnkes et al.[90]. As reported by the authors, such phenomenon
is observed due to synergistic effect of electrophoretic, electroosmotic and diffusional
forces and is governed by relative charges on analyte and the silicon nitride membrane.
When a charged particle with its associated counterions is placed in an electric field, the
counterions also experience a force which acts in the direction opposite to the
electrophoretic force experienced by the particle. In such a situation, Stokes law cannot
completely estimate the retardation force acting on the particle and it moves much more
slowly than expected.[91]. Moreover, presence of surfactant molecules on GNPs (as
used in this study) also screen the surface charge, thereby lowering its zeta-potential
34
which further results in slower migration of the particles. The electrophoretic velocity
of a particle is given by:
𝑣 = 𝜇�� 2.6
where 𝑣 is the electrophoretic velocity, �� is the applied electric field and µ is the
electrophoretic mobility. Electrophoretic mobility is linked to the zeta potential by
Henry’s equation:
𝜇 =2
3𝜀𝑟𝜀𝑜𝜂
−1𝜁𝑓𝐻(𝜅𝑎) 2.7
where 𝜀𝑟 again is the dielectric constant, 𝜀𝑜 is the permittivity of free space, 𝜂 is
viscosity of the medium, 𝜁 is the zeta potential, and Henry’s function 𝑓𝐻(𝜅𝑎) is given
by [92]:
𝑓𝐻(𝜅𝑎) = {1 + 1
16 (𝜅𝑎)2 −
5
48 (𝜅𝑎)3 −
1
96 (𝜅𝑎)4 +
1
96 (𝜅𝑎)5 + [
1
8 (𝜅𝑎)4 −
1
96 (𝜅𝑎)6] 𝑒𝜅𝑎𝐸1(𝜅𝑎)} 2.8
provided (|𝜁| < 𝑘𝐵𝑇
𝑒⁄ ) and 𝐸1(𝜅𝑎) is exponential integral
In addition to this, flexible surfactant molecules on nanoparticle surface could
also be increasing the electrophoretic retardation force because the surfactant coated
particles may get hydrodynamically linked with the electroosmotic flow. We measured
electrophoretic mobility for our GNPs using DLS and it decreased from 2.68 µmcm/Vs
for citrate stabilized GNPs to 0.85 µmcm/Vs when they were dispersed in the electrolyte
solution with surfactant. Such a situation can result in diffusional motion of particles to
35
be the dominant mode of translocation and nanoparticles move across the pore down
their concentration gradient. And since the concentration gradient is not affected by
voltage bias, it can result in event detection both at negative and positive voltages. We
also expect formation of electroosmotic flow inside the nanopore at this low salt
concentration which can also contribute to particle translocation at either polarity of the
transmembrane voltage.
Figure 2.5 Single nanoparticle translocations accompanied by current enhancement. (a)
When a positive electrical potential was applied to the -trans chamber, particles
translocated with conductive spikes. (b) Conductive spikes shown in (a) at higher
resolution. Spikes can be characterized by conduction current amplitude ΔI, and spike
duration td. (c) Represents the conductive spikes recorded when a negative potential was
applied. (d) Spikes shown in (c) at higher resolution.
(a) (b)
(c) (d)
(e)Δt
36
2.3.4 Effect of salt concentration and relative pore geometry on translocation
signals
Even more interesting than observing translocation at both positive and negative
voltage was the current enhancement observed upon particle translocation. These
current enhancement signals can be characterized by amplitude of the spikes, which is
represented by conductive current, ΔI (ΔI=spike peak value, Ic - open pore current, Io)
and duration of the spikes Δt (Figure 2.5 (b)). As discussed earlier, the phenomenon of
conductive spikes has been observed in the past. It was first reported by Chang et al.
that translocation of dsDNA across silicon oxide nanopore channels resulted in current
enhancement when the experiments were carried out at 0.1 M KCl concentration [93].
In a later report, same research group studied the influence of different KCl
concentrations and different applied voltages on current enhancement. They attributed
the current enhancement effect to the counterion cloud associated with highly negative
DNA molecules at low salt concentrations [94]. Smeets et al. also reported on DNA
translocation through silicon oxide nanopores using KCl concentrations in the range of
50 mM to 1M. They concluded that DNA translocations result in decrease in ionic
current for [KCl] > 0.4 M and increase in ionic current for [KCl] < 0.4 M [95]. Similar
results have also been predicted by computer simulations recently [96]. The
phenomenon of current enhancement is not fully understood and may depend on several
factors but the most notable ones are electrolyte concentration [95], ratio of diameter of
nanopore and analyte particles and their surface charge [77]. We hypothesize that a low
salt concentration results in thick counterion cloud around the nanoparticle and the
37
nanopore wall and a sparse ion distribution inside the nanopore volume. When the
particle traverses the nanopore, it displaces the ions already present inside the pore but
it also brings its counterion cloud with it which may increase the ion density inside the
nanopore. If the amount of ions brought into the nanopore by the translocating particle
are greater in number than the amount of ions displaced by it, the translocation will
result in transient increase in current or ‘conductive spike’. This phenomenon can be
observed only at low salt concentrations because at such concentrations the amount of
new charge carriers introduced in the pore can exceed the amount of charge carriers
displaced by the translocating particles. The magnitude of current enhancement due to
DNA translocation can be estimated using following equations [95]. The open pore
conductance of a cylindrical nanopore at low salt concentrations is given by:
𝐺𝑜 =𝜋 𝑑𝑝𝑜𝑟𝑒
2
4 𝐿𝑝𝑜𝑟𝑒 ((𝜇𝐾 + 𝜇𝐶𝑙)𝑛𝐾𝐶𝑙𝑒 + 𝜇𝑘
4𝜎
𝑑𝑝𝑜𝑟𝑒) 2.9
where 𝑑𝑝𝑜𝑟𝑒 and 𝐿𝑝𝑜𝑟𝑒 are the diameter and the length of the nanopore, 𝜇𝐾 and 𝜇𝐶𝑙 are
the electrophoretic mobilities of potassium and chloride ions, 𝑛𝐾𝐶𝑙 is the number density
of potassium or chloride ions, e is the elementary charge and 𝜎 is the surface charge
density in the nanopore. The first term in this equation corresponds to bulk conductance
and is dominant at high salt concentrations. The second term in the equation represents
the conduction component due to counterions shielding the charge on nanopore surface
at low salt concentrations. The conductance of the pore when it is occupied by a
nanoparticle would be 𝐺𝑐 = 𝐺𝑜 − 𝐺𝑟𝑒𝑠𝑖𝑠𝑡 + 𝐺𝑐𝑜𝑛𝑑𝑢𝑐𝑡 , where 𝐺𝑟𝑒𝑠𝑖𝑠𝑡 is the decrease in
conductance because of ion displacement and 𝐺𝑐𝑜𝑛𝑑𝑢𝑐𝑡 is the increase in conductance
because of new ions brought into the pore by the nanoparticle. And then, ∆𝐺 = 𝐺𝑐 −
38
𝐺𝑜. As compared to DNA, it is difficult to perform quantitative estimation of
conductance enhancement accompanying nanoparticle translocation because estimation
of conductance of a sphere is non-trivial due to its complex geometry.
Previous reports on nanoparticle detection used low salt concentrations;
however, in only one of them authors observed current enhancement using nanoparticles
(when bound with proteins). Wang et al. observed resistive spikes upon translocation
of ~10 nm diameter Mercaptohexadecanoic acid (MHDA) functionalized GNPs through
28 nm diameter conical nanopores. When the same nanoparticles were bound by anti-
peanut antibody, it changed the surface charge of the complex and increased its
effective size to 15.1 ± 1.4 nm and translocation of this gold nanoparticle-antibody
complex resulted in current enhancement instead of current blockade [77]. This
observation provides a strong evidence for the role played by the charge on the analyte
and its diameter relative to nanopore diameter in observing current enhancement. In
majority of the earlier reports on nanoparticle translocation only resistive spikes were
observed and it could be because of using higher size ratio of nanopores to nanoparticle.
Based on our observations, we postulate that conductive spikes may be observed in a
nanopore experiment when using high surface charge nanoparticle with diameter < 100
nm, [KCl] ≈ 10-20 mM, (nonionic) surfactant concentration < CMC, and
𝐷𝑖𝑎𝑚𝑒𝑡𝑒𝑟𝑝𝑜𝑟𝑒 𝐷𝑖𝑎𝑚𝑒𝑡𝑒𝑟𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒⁄ < 2.
39
2.3.5 Multiphysics simulations to explore the effect of electrolyte strength,
relative geometry and charge on the particle in appearance of conductive spikes in
nanopore experiments
To further explore the factors leading to the detection of conductive spikes in
nanopore experiments and to validate our hypothesis, we performed Multiphysics
simulations which allowed for sequential variation of different experimental
parameters. We started with pore and particle geometry as used in the gold nanoparticle
translocation experiments. A 20 nm particle simulated to translocate through a 30 nm
diameter pore drilled in 50 nm thick membrane using 10 mM KCl as electrolyte. A
surface charge density of -0.02 C/m2 was chosen for both the nanoparticle and the
insulating membrane surface and a transmembrane voltage of 500 mV was used. The
distribution of electrolyte ions around the solid surfaces of the membrane and the
particle are shown in Figure 2.6. These experimental conditions resulted in surface
concentration of ions as high as 9 times the bulk concentration which dissipated in an
exponentially decaying fashion when moving away from the wall. This high
distribution of ions close to the solid surface resulted in a thick counterion cloud which
extended for ~ 5 nm away from the solid surface. When particle moved through the pore
(from down to upwards), transmembrane voltage caused concentration polarization for
the nanoparticle counterion cloud. This phenomenon can lead to pinching off of the
counterions from the particle surface which can lead to transient increase in
concentration of free ions inside the pore.
40
Figure 2.6 The dynamics of particle translocation simulated using COMSOL
Multiphysics modeling. A 20 nm diameter particle was simulated to translocate through
a 30 nm pore drilled in a 50 nm insulating membrane. The electrolyte strength was 10
mM KCl and surface charge density for both particle and the membrane were -0.02
41
C/m2. The distribution of counter ions the solid surfaces is color coded and the Surface
charge density is presented in mmol/L.
Other observations drawn from translocation dynamics shown in Figure 2.6
include interaction between the counterion clouds of the nanopore and the particle when
particle is at the narrowest constriction inside the nanopore (Figure 2.6 (b)). Such
interaction of the two ionic double layers create a continuous zone of high ionic
concentration and can result in conductive spikes. The phenomenon of interaction of
double layers strongly depends on the relative diameter of the nanoparticle and the
nanopore and was investigated by varying the pore diameter as shown in Figure 2.7.
The diameter of the nanopore was increased to 60 nm while keeping all other parameters
constant (Figure 2.7 (a) versus Figure 2.7 (c)). The distribution of ions along the red
dashed lines shown in Figure 2.7 (a) & (c) are plotted in 2.7 (b) & (d) respectively. Blue
curves shows the baseline ionic concentration when no particle is present inside the
nanopore and the area under the blue curves (Blue + Red area in Figure 2.7 (b)) would
correspond to the current through the nanopore. When a (neutral) particle is present
inside the nanopore, it takes up the pore volume and the ions can only occupy area
marked with blue color. This results in a resistive spike with magnitude corresponding
to the area marked in red. However, when the particle is charged and its counterion
cloud interacts with the counterion cloud of the pore, a continuous zone of high ionic
concentration is created (marked by Green area). This interaction adds new charge
42
carriers to the nanopore and if Green Area > Red Area, particle translocation would
result in conductive spikes else they would result in resistive spikes. In case of larger
pore size, the counterions of the pore and the particle do not interact and aforementioned
zone of high ionic concentration is not created. As evident from Figure 2.7 (d), area
bounded between the green and blue curves (Green area) is much smaller compared to
the area excluded due to particle inside the pore (Red area), and this configuration
invariably would result in resistive spikes.
Figure 2.7 Effect of pore diameter on polarity of spikes. Translocation of 20 nm particle
was compared using a 30 nm and a 60 nm diameter pore. For smaller pore, new charge
carriers are introduced in the pore which result in conductive spikes (b), while for the
43
60 nm pore ions displaced from the pore volume are greater in number than the new
charge carriers bought into the pore, resulting in resistive spikes (d). See text for details.
Following the same rationale, effect of ionic strength on producing conductive
or resistive spikes can be discussed. Figure 2.8 compares the ion distribution profiles
for 20 nm particle present inside a 30 nm pore when the ionic strength is 10 mM KCl
(a) or 150 mM KCl (b). When using 150 mM KCl, the charge carriers displaced by the
particle from the pore (Red area) are significantly larger than the new charge carriers
brought into the pore by the particle (Green area), and only resistive spikes can be
expected.
Figure 2.8 Effect of electrolyte strength. For a given pore geometry, balance between
the new charge carriers brought into the pore and the ions displaced from the pore
determine the polarity of the spikes. When using low strength electrolytes, new ions (G)
44
> ions displaced (R), resulting in conductive spikes (a) where as in case of higher ionic
concentration, new ions (G) < ions displaced (R), resulting in resistive spikes.
Finally, we compare the effect of particle surface charge on distribution of ions
inside the nanopore. For this simulation 20 nm particle dispersed in 10 mM KCl was
placed in a 30 nm pore like discussed earlier. The surface charge density of the
insulating membrane was kept constant at -0.02 C/m2 but the surface charge density of
the particle was varied to -0.02, -0.04 and -0.06 C/m2. In low ionic strength solutions,
the charge on the particle is the reason for accumulation of counterions around its
surface and higher surface charge density leads to higher ionic density close to the
surface. Figure 2.9 shows the effect of surface charge density on extent of counterion
cloud from the solid surface. Figure 2.9 (a) includes the ion distribution at the center of
the pore when a particle is present as was shown in Figures 2.7-2.8 while Figure 2.8 (b)
shows higher resolution plot of the same ion distribution profiles at the edge of the
nanoparticle. We observe a progressively increasing ionic concentration at the particle
surface with the increasing surface charge density. This also translated into
progressively increasing area under the curves with the increasing surface charge
density of the particles suggesting that particles with higher surface charge are expected
to bring more counter ions into the nanopore as compared to the particles with lower
surface charge.
45
Figure 2.9 Effect of particle surface charge density. Particles with higher surface charge
density show higher ionic concentration at the solid surface and are expected to bring
more ions into the nanopore during translocation.
2.4 Conclusions
We studied translocation behavior of ~20 nm GNP dispersed in 20 mM KCl
through 30 nm diameter silicon nitride pores. The experimental conditions resulted in
current enhancement instead of current blockades when the particles translocated across
the nanopore. The effect of different experimental parameters on current modulation
46
was studied using Multiphysics simulations and the conditions leading to current
enhancement are recognized. These experiment helped us to understand and optimize
the transport behavior of small nanoparticles at low salt concentrations.
47
Chapter 3: Use of solid-state nanopores to study co-translocational deformation of
nano-liposomes
Specific Aim 2: Study translocation of sub-100 nm liposomes through a solid-state
nanopore and compare their deformation behavior to similar sized rigid
nanoparticles
a. Investigate translocation characteristics of DOPC nano-liposomes and
polystyrene beads.
b. Compare voltage dependent translocation behavior of the two analytes and
detect of co-translocational deformation of liposomes
Hypothesis: Similar to the giant vesicles, when nano-vesicles are subjected to high
electric field strength and hydrodynamic stress due to confinement inside a nanopore,
they change shape from spherical to ellipsoidal particles and this shape change can be
detected using voltage dependent changes in ionic current drop values.
3.1 Introduction
Liposomes are artificial nanoscale sacs made up of lipid bilayers that have been
widely studied over the past decades as model biological membranes, or as nanocarriers
for drug delivery systems [97-102]. These nano-vesicles resemble the physical and
mechanical characteristics of biological nano-vesicles like exosomes and viruses.
Mechanical characterization of such vesicles is of great interest because their
48
mechanical properties play a crucial role in biological phenomena such as membrane
fusion, endocytosis, exocytosis and assembly of enveloped viruses. For example, the
fusion of biological carriers (vesicles, viruses, exosomes, etc.) with their target cells or
organelles directly depends on their ability to deform [8]. Mechanical properties of the
lipid bilayer have also been shown to influence biological functions such as fusion and
budding [9-11]. Furthermore, when using liposomes for delivery of drugs and cosmetics
into the skin, their penetration through stratum corneum into the deeper skin layers is
also directly related to the liposome deformability [103-109].
As discussed in Chapter 1, a significant amount of work has been done on
deformation of giant vesicles to study their mechanical properties. Interaction of
vesicles with both AC and DC electric fields has been shown to result in vesicle
deformation and transformation from spherical to ellipsoidal shape. In solid-state
nanopore set-up, since the nanopore is the only conduit for ionic transport from one
chamber to the other, all of the electric filed lines converge into the nanopore when a
transmembrane potential is applied. This confinement of electric filed inside the
nanopore results in a very high electric field strength which has been shown to influence
the structural integrity of the translocating analyte. Much of the work on this front has
been done to study single molecule protein unfolding when the protein molecules
translocate through the region of high electric field strength inside the nanopore. They
have a heterogeneous charge distribution and get polarized under the influence of
electric field as the positively and negatively charged amino acids are pulled in opposite
directions [110].
49
In this chapter we use solid-state nanopores to study deformation of nano-
vesicles. This technique allows single particle level investigation of liposomes at
physiological conditions and in the solution state. Moreover, hundreds of vesicles can
be driven through the pore making nanopore sensing an attractive technique for high
throughput characterization. Although there have been many reports on the use of
resistive pulse sensing technique for detection, sizing and separation of rigid non-
deformable metallic or polymeric nanoparticles [76, 79, 111-113], this technique has
only recently been applied to study soft hydrogel particles and liposomes [80, 114-116].
Holden et al. used conical pores embedded in glass capillaries to study translocational
dynamics of soft hydrated microgels [114, 115] and multilamellar liposomes [80]. The
microgel particles (570 nm radius) were pressure-driven through a nanopore of diameter
smaller than those of translocating particles. The applied pressure resulted in squeezing
of the microgel particles through the nanopore [114, 115]. For liposome translocation,
conical pores of variable sizes were used and liposome translocation as a function of
nanopore diameter and lipid bilayer transition temperature was studied [80]. When 367
± 79 nm radius liposomes (5% DPPG/ 95% DPPC, Transition temperature = 41 ⁰C)
were translocated through a 208 nm radius pore (at 10 mmHg pressure), liposome
deformation and translocation was observed at high temperatures (T > 47 ⁰C) where the
lipid membrane was highly flexible [80]. Pevarnik et al. reported the use of 12 µm long
track-etch PET pores with diameter 540 nm to study translocation of ~300 nm hydrogel
particles [116]. They observed change in hydrogel shape and attributed it to
concentration polarization due to the electric field inside the nanopore and the non-
50
homogeneous pressure distribution along the pore axis. Although, these reports provide
a good reference to soft-particle analysis using resistive pulse sensing, most of them
use long conical pores, hydrogel particles larger than ~400 nm diameter and high
pressure to squeeze them through the nanopore [80, 114-116].
For this study, we use pure DOPC (1, 2-dioleoyl-sn-glycero-3-phosphocholine)
liposomes and compare their deformation to rigid polystyrene particles. We chose
DOPC liposomes because of their low bending rigidity and easy deformability. The lipid
chain melting transition temperature of membranes increases with chain saturation
[117] and DOPC contains unsaturated long-chain (18:1) oleic acids inserted at the sn-1
and sn-2 positions. This unsaturation lowers the DOPC transition temperature to −16.5
⁰C [118] and consequently it exists in a fluid like liquid crystalline state (Lα) at room
temperature [119]. The fluid like state of DOPC makes the liposomes soft and easily
deformable. The experiments with DOPC liposomes and similarly sized polystyrene
particles helped us set experimental range for very soft and rigid particles and optimize
protocol for detection of soft vesicles.
3.2 Materials and Methods
3.2.1 Nanopore fabrication
For nanopore chip fabrication, a 200 nm thick film of silicon nitride (SixNy) was
deposited on a 4 inch diameter, 375 μm thick silicon wafer using low pressure chemical
vapor deposition (LPCVD). Then using photolithography, Reactive-Ion Etching (RIE),
51
and KOH wet etching a 50 × 50 μm2 window was fabricated in silicon wafer resulting
in 200 nm thick free standing silicon nitride membrane. 250 nm diameter nanopores
were then drilled in the SixNy membrane using a FEI Strata DB 235 FIB at an ion beam
current of 30 to 50 pA.
3.2.2 Analyte preparation and characterization
1, 2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) liposomes were purchased
from FormuMax Scientific Inc. (Palo Alto, CA, USA) and polystyrene particles were
purchased from Polysciences Inc. (Warrington, PA, USA). For translocation
experiments, liposomes were dispersed in 10 mM KCL (pH 7.0) and were filtered
through a 0.2 µm filter to get rid of any aggregates. The polystyrene particles were
dispersed in 50 mM KCl and sonicated for 5 minutes before translocation experiments.
For TEM imaging, 5 µl liposome sample was dispensed on a holey carbon TEM
grid for 5 minutes, followed by removal of excess liquid by wicking using a filter paper.
It was immediately followed by adding 2 µl of 2% uranyl acetate solution to back-stain
and preserve the liposomes. The excess staining solution was wicked with a filter paper
after 2 minutes and the TEM sample was air dried. The sample was loaded into and
imaged using JOEL 2100 TEM operating 120 keV accelerating voltage. A similar
sample preparation technique was used for TEM imaging of polystyrene particles and
they were imaged under same conditions.
52
The hydrodynamic diameter of liposomes and polystyrene particles was
determined using dynamic light scattering (DLS) device (Zetasizer Nano ZS, Malvern
Instruments Ltd.). The intensity-weighted diameters of analytes were recorded, plotted
as histogram spikes and fitted with Gaussian distribution. Zeta potential for the two
analytes was measured using zeta-potential measuring flow cell provided with the
instrument. All measurement data met the quality standards set by Malvern.
3.2.3 Experimental Setup
The nanopore chip was treated with air plasma on either side for 5 minutes to
improve wettability. The chip was then sandwiched between two PDMS gaskets and
was assembled in a custom built flow cell. The gaskets were filled with electrolyte
solution and they served as the -cis and the –trans chambers. Ag/AgCl electrodes were
inserted into the two electrolyte chambers and were connected to a Molecular Devices
Axopatch 200B patch clamp amplifier. The current data was sampled at 200 kHz,
digitized using a MD Digidata 1440A digitizer, and analyzed using pClamp 10.3
software. Recorded data was pre-conditioned for analysis by electronic low pass Bessel
filtering (10 kHz) and manual baseline correction. Data analysis, plotting and statistical
comparison were performed using Origin Pro and Graphpad Prism. After translocation
experiment with DOPC liposomes, the nanopore chip was cleaned by dipping in acetone
for 5 minutes followed by iso-propyl alcohol and water. The chip was then treated with
air plasma (5 minutes each side) and assembled again in the flow cell for experiments
with polystyrene particles.
53
3.3 Results and discussion
3.3.1 Nanopores drilled in silicon nitride windows
Figure 3.1 shows some representative scanning electron micrographs of the
solid-state pores drilled for this study. A 7 × 4 nanopore array shown in Figure 3.1 a,
was used to determine the reproducibility and variation in pore fabrication. As seen in
the images, our technique results in very round and uniform pore fabrication. We
obtained a mean diameter of 249.6 nm with a standard deviation of 1.27 nm and
coefficient of variation as 0.005 for the nanopore shown in Figure 3.1 a. For
translocation experiments, a solitary pore was drilled in the silicon nitride window.
Figure 3.1 Representative scanning electron micrographs of 250 nm pores drilled in 200
nm thick silicon nitride membranes. Scale bars are 1 µm and 500 nm for (a) and (b)
respectively.
54
3.3.2 Characterization of liposomes and polystyrene particles using transmission
electron microscopy and dynamic light scattering
First, we characterized the liposomes and polystyrene nanoparticles using TEM
and DLS for size determination. Figure 3.2 (a) and (c) show the TEM images and the
corresponding size histograms for the two analytes. The diameters of the vesicles and
the polystyrene particles were calculated from the TEM images and plotted as
histograms. The hydrodynamic diameters were measured using Malvern Zetasizer Nano
ZS and the resulting histograms are shown in Figure 3.2 (b) and (d) for liposomes and
nanoparticles respectively. The histograms were fitted with Gaussian curves to obtain
the mean and standard deviation values. For liposomes, we obtained a mean diameter
of 83.08 ± 5.1 nm using TEM and 86.54 ± 30.09 using DLS. For polystyrene particles,
we obtained a mean diameter of 75.0 ± 4.9 nm using TEM and 76.43 ± 23.28 nm using
DLS. It should be noted that the discrepancy in TEM and DLS sizes is because DLS
measures the hydrodynamic diameter of particles which is slightly larger than the actual
diameter. Although we get similar mean values using both techniques, the standard
deviation in DLS data is 5-6 times the standard deviation in TEM data, highlighting the
shortcoming of ensemble averaging used in DLS.
55
Figure 3.2. (a) TEM image (Scale bar: 100 nm) of liposomes back stained with 2%
uranyl acetate and the size histogram obtained from measuring liposome diameter in
TEM images. (b) Histogram of liposome hydrodynamic diameter measured using
dynamic light scattering (DLS). (c) TEM image and size histogram for polystyrene
particles. Sample was prepared and imaged similar to liposomes. (d) Hydrodynamic size
histogram for nanoparticles.
3.3.3 Detection of liposome translocation
For nanopore translocation experiments, a 250 nm diameter pore was used
(Figure 3.3 (a)). Soon after adding the liposome sample to the –cis chamber of the flow
(a) (b)
(c) (d)
56
cell and applying transmembrane voltage, current drop signals corresponding to
liposome translocations were detected (Figure 3.3 (b)). The current drop (ΔI) and
translocation time (Δt) values of the resistive pulses were extracted and used for further
analysis. The majority of the events observed were short (Δt < 0.6 ms) with low
magnitude current blockades (150 pA < ΔI < 350 pA); however, ~14% events observed
were longer with ΔI ranging from 350 pA – 700 pA. These longer and deeper events
can be attributed to liposomes sticking together during translocation.
Figure 3.3 (a) Liposome translocation detection set-up. 250 nm diameter pore drilled in
200 nm thick silicon nitride membrane was used to detect liposome translocation. (b)
The behavior of ionic current before and after adding liposome sample to one side of
the nanopore. Inset shows a high resolution current signature for one of the translocation
events.
57
We recorded and analyzed liposome translocation data at different
transmembrane voltages and it revealed a very interesting trend. The events
characteristics for experiments at 200 mV and 300 mV were extracted and plotted. As
seen in Figure 3.4 (a), when the current drop values (ΔI) were plotted against the
translocation times (Δt) for the two voltages, we observed a very similar population
distribution. In nanopore experiments, typically, the ΔI values increase with the
increasing transmembrane voltage due to an increase in the baseline current value (Io).
The current drop amplitude (ΔI) can be represented in terms of physical properties of
the translocating analyte. Based on volume displacement from the pore and neglecting
the surface charge effects, we can write [31, 120]:
∆𝐼 = 𝐼𝑜 Λ
𝐻𝑒𝑓𝑓𝐴𝑝𝑜𝑟𝑒[1 + 𝑓(𝑑𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒 𝐷𝑝𝑜𝑟𝑒⁄ , 𝐿𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒 𝐻𝑒𝑓𝑓⁄ )]
Where 𝛬 is the excluded volume, 𝐻𝑒𝑓𝑓 is the effective length of the nanopore and
𝑓(𝑑𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒 𝐷𝑝𝑜𝑟𝑒⁄ , 𝐿𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒 𝐻𝑒𝑓𝑓⁄ ) is the shape correction factor which depends on the
diameter of the particle (𝑑𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒), diameter of the pore (𝐷𝑝𝑜𝑟𝑒), length of the particle
(𝐿𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒) and effective length of the pore (𝐻𝑒𝑓𝑓). We also know that 𝑉𝑎𝑝𝑝𝑙𝑖𝑒𝑑 =
𝐼𝑜𝑅𝑝𝑜𝑟𝑒, where 𝑉𝑎𝑝𝑝𝑙𝑖𝑒𝑑 is transmembrane voltage, 𝐼𝑜 is baseline current and 𝑅𝑝𝑜𝑟𝑒 is
the resistance of nanopore. If shape and excluded volume of the translocating analyte
are constant then 𝛥𝐼 ∝ 𝑉𝑎𝑝𝑝𝑙𝑖𝑒𝑑 and in that case ΔI should scale up with the increasing
transmembrane voltage. However, we observe that ΔI values remain almost constant
despite the increase in Io when changing applied voltage from 200 mV to 300 mV. In
order to rule out the possibility that the non-existent change in ΔI values were due to a
58
small change in the transmembrane voltage, we transformed the ΔI values into percent
current drop ((ΔI/Io) × 100) values. The histograms were fitted with log-normal
distributions to obtain the most probable values. The percent current drop value is
directly related to the shape and excluded volume of the translocating analyte and it
typically remains constant at different applied voltages if the analyte excluded volume
remain the same. Our results show that percent current drop values decreased from a
mean value of 8.54 (Std. Dev.: 0.26) to 5.95 (Std. Dev.: 0.24) when the voltage was
changed from 200 mV to 300 mV (Figure 3.4 (b)). An inverse relationship between the
percent current drop and the applied voltage suggests co-translocational deformation of
liposomes, a phenomenon similar to protein stretching and unfolding during nanopore
translocation [63, 121-125]. Our group and others have previously reported that percent
current drop (also referred to as normalized current blockade ratio) decreases as a
function of applied voltage due to protein unfolding caused by strong electrical field
experienced by proteins inside the solid-state nanopores [63, 121-123]. During
nanopore translocation, liposomes also experience high electric field strength inside the
pore which may result in concentration polarization and eventual deformation of the
soft vesicles. Moreover, electrohydrodynamic forces can exert pressure on the
translocating particle and can further aid in vesicle deformation [12, 116].
59
Figure 3.4. Event characteristics for liposome translocations. a. Scatter plot for current
drop versus translocation time at 200 and 300 mV shows very similar population
distribution. Translocation time is plotted on log scale. b. Percentage current drop values
show a decline with increasing transmembrane voltage suggesting deformation of
liposomes during nanopore translocation.
(a)
(b)
60
3.3.4 Detection of polystyrene particles translocation
In order to validate our hypothesis, we performed translocation experiments with
polystyrene nanoparticles. The Young’s modulus of polystyrene is 3 – 3.5 GPa [126],
which makes the polystyrene nanoparticles very rigid as compared to liposomes (typical
Young’s modulus < 100 MPa [14]). The experiments were performed using the same
nanopore at 50 mM KCl. The particles were dispersed in the electrolyte and were
sonicated for 5 minutes before adding into the flow cell. When the transmembrane
voltage was applied, a stream of translocation events was observed. The current drop
values obtained for nanoparticle translocation were regular and more uniform compared
to the liposomes, perhaps, because of well dispersed single particle suspension
generated after sonication. Figure 3.5 (a) shows the scatter plot with current drop values
(ΔI) plotted against the translocation times (Δt) for transmembrane voltages of 200 mV
and 300 mV. As anticipated, the population cluster shifts with the voltage and we
observe higher current drop (ΔI) values at 300 mV compared to 200 mV. The
distributions for percentage current drops and translocation times were also plotted and
they did not exhibit any significant difference from 200 mV to 300 mV. The peak values
for Gaussian curves fit to the percent current drop distributions were 2.07 ± 0.72 and
1.99 ± 0.74 at 200 and 300 mV respectively. As discussed above, ΔI/Io = constant if the
shape and excluded volume of analyte does not change. This translocation behavior of
polystyrene particles is similar to what is observed for non-deforming analytes in typical
nanopore experiments. Based on our translocation data for both liposomes and
61
polystyrene particles we can conclude that liposomes undergo co-translocational
deformation in nanopores.
Figure 3.5. (a) Current drop (ΔI) versus translocation time (Δt) scatter plot for
polystyrene particle translocations at voltages 200 and 300 mV. (b) Percentage current
drop histograms with Gaussian fits for the two voltages. (c) Translocation time
histograms for the two voltages. N=303 and 334 for 200 and 300 mV respectively.
62
We directly compare the translocation behavior of liposomes and the
polystyrene particles in Figure 3.6 using a marginal histogram. The event data for the
two analytes were plotted for transmembrane voltage of 300 mV. As discussed above,
nanoparticles produced events with more uniform current drop values resulting in a tight
population distribution. On the other hand, liposomes produced wide population
distribution perhaps because of some heterogeneity in the sample. We observe well
separated and very distinct population clusters for the two analytes owing to the
difference in their hydrodynamic diameters and electrophoretic mobilities. As evident
from TEM and DLS characterization of the two analytes, liposomes are roughly 10 nm
larger than the polystyrene particles and they are observed to produce deeper current
blockades compared to the polystyrene particles. The percent current drop distributions
for the two analytes were fitted with log-normal functions are we obtained peak values
of 5.9 (Std. Dev: 0.26) and 1.99 (Std. Dev.: 0.74) for liposomes and polystyrene particles
respectively. The electrophoretic velocity of the particles in external electric field (E) is
related to their zeta potential (𝜉𝑝𝑟𝑜𝑡𝑒𝑖𝑛) by the relation:
𝑣 =𝜀
𝜂𝜉𝑝𝑟𝑜𝑡𝑒𝑖𝑛𝐸
Where 𝜀 = 𝜀𝑜𝜀𝑟 and 𝜀𝑜 is dielectric constant and 𝜀𝑟is permittivity of free space. We
measured the zeta-potential for the two analytes and obtained a considerably lower value
for liposomes (-8.78 mV) compared to the polystyrene particles (-12.0 mV). The
translocation time characteristics of the two analytes is supported by the zeta potential
readings, the polystyrene particles with higher zeta potential are expected to have higher
63
electrophoretic velocity and lower translocation time (Peak: 0.13 ms, Std. Dev: 0.17)
compared to liposomes (Peak: 0.36 ms, Std. Dev: 0.58), as seen in Figure 3.6.
Figure 3.6 Comparison of translocation behavior of liposomes and polystyrene particles
at 300 mV. Both current drop and translocation time in the scatter plot are plotted on
log scale.
64
3.3.5 Comparison of voltage dependent translocation behavior for liposomes and
polystyrene particles
We performed translocation experiments at a wider range of transmembrane
voltages (100 – 600 mV). Although liposome deformation behavior was clearly
observed when event distribution at 200 and 300 mV were compared, a wider range of
voltages revealed the complete trend. For this analysis, translocation of liposomes was
performed at 100, 200, 300, 400, 500 and 600 mV. We recorded and analyzed 58, 309,
361, 440, 397 and 197 events for liposome translocations at these voltages. Figure 3.7
shows scatter plot for obtained for percent current drop values obtained for liposome
translocation for voltages 100-600 mV. The progressive decrease in percent current drop
with the increasing applied voltage suggests a voltage dependent trend in vesicle
deformation inside the nanopore.
65
Figure 3.7 Translocation time versus relative current drop scatter plot for liposome
translocations at different applied voltages. The relative current drop value decreases
steadily with the increasing transmembrane voltage.
The voltage dependent deformation trend observed in case of liposomes was
compared with rigid polystyrene particles. PS-particle translocations were also
performed using the same nanopore and 442, 303, 334, 447, 403 and 130 events were
recorded at voltages 100 – 600 mV. For both liposomes and polystyrene particles, we
extracted the percentage current drop values and plotted their histograms, followed by
Gaussian or Log-Normal fitting to the data. The mean and standard deviation values at
66
different voltages obtained from curve fitting were normalized to the values obtained at
100 mV and plotted as a line graph (Figure 3.8 (a)). We obtained a linear fit to that
percentage current drop data for polystyrene particles suggesting no effect of voltage on
particle shape, as expected of the rigid nanoparticles.
Figure 3.8 (a) Deformation trend observed for liposomes as compared to the polystyrene
particles for 100 -600 mV applied voltages. The rigid polystyrene particles show no
deformation whereas liposome follow an exponential trend and their percent current
drop values decrease with increasing voltages. (b) & (c) Simulation results for electric
field strength inside a nanopore at 600 mV. See text for details.
(a) (b)
(c)
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On the other hand, an exponential decay trend (𝑦 = 1.417 𝑒−0.003353𝑥 + 0.028)
is observed for that percentage current drop data for liposome translocation suggesting
significant deformation of particles as they translocate through the nanopore. We also
performed mutiphysics simulation using COMSOL to determine the electric field
strength inside the nanopore. The simulations were performed with a geometry similar
to the dimensions of the nanopore used for translocation experiments. Figure 3.8 (b)
shows the results from the simulation performed at applied voltage of 600 mV. The
electric field strength in the geometry is color coded and the rainbow color bar shows
majority of electric field concentrated only inside the pore where it reaches a value of
1.46 × 106 V/m at 600 mV transmembrane voltage (Figure 3.8 (c)). This electric field
strength translates to 14 kV/cm which is significantly higher than the electric field
strength of 3.0 kV/cm [12] and 2.0 kV/cm [13] reported for deformation of giant
vesicles (14 to 30 µm diameter).
The comparison of translocation behavior of liposomes and polystyrene particles
was limited to 600 mV because almost no translocation events were observed for
liposomes for applied voltages higher than 600 mV. The left panel in Figure 3.9 shows
no liposome translocation was observed at 700 mV but translocation activity was seen
when the voltage was lowered to 400 mV, and it again disappeared when the voltage
was raised back to 700 mV. A similar trend was also observed at higher voltages and
no reliable translocation data was obtained above 600 mV. On the other hand,
translocation events were observed at much higher voltages for polystyrene beads
68
(Figure 3.9 right panel). We hypothesize that liposomes may be rupturing at voltages
higher than 600 mV which prevented their detection.
Figure 3.9 Comparison of translocation activity of liposomes and polystyrene particle
at high voltages. For liposomes no activity was seen above 600 mV applied voltage (left
panel) whereas polystyrene particles show translocation well above 600 mV.
The hypothesis of vesicles rupturing at high voltages is also supported by inter-
event time data for liposome translocation. Inter-event time is a measure of time
duration between two subsequent spikes. Typically, increasing transmembrane voltages
result in more frequent translocations and low inter-event time. When the inter-event
time for liposome translocation was plotted at different voltage (Figure 3.10), we
observed a progressive increase in inter-event time from 100-400 mV. After 400 mV
69
the inter-event time started to rise again indicating there were less frequent
translocations at 500 and 600 mV potential as compared to 400 mV. This could be due
to vesicle starting to rupture at 500 mV, which results in less frequent translocations and
the similar trend continues at 600 mV. After 600 mV almost all of the vesicles
attempting to translocate through the pore burst and no translocations are registered.
Figure 3.10. Change in inter-event time with applied voltage for liposome
translocations. Lower and upper whiskers represent 10th and 90th percentile respectively.
The median value decreases steadily from 100 mV to 400 mV and then increases for
500 and 600 mV. No translocations were detected for V > 600 mV.
70
3.4 Conclusions
We observed transmembrane voltage dependent deformation of the liposomes,
which followed an exponential trend. The voltage responsive behavior of liposomes was
observed from 100 – 600 mV applied voltage and no events were observed at voltages
higher than 600 mV. We believe the high electric field strength inside the nanopore
caused the vesicle to rupture at voltages higher than 600 mV. The polystyrene particles
were used as a control analyte and they did not show any deformation at voltages tested.
The electrohydrodynamic stress due to the concentrated electric field and the physical
confinement inside the nanopore are believed to cause the deformation of the vesicles.
We show for the first time detection and electric field induced deformation of sub-100
nanometer liposomes using nanopores.
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Chapter 4: Exosomes deformation detection and molecular profiling using solid
state nanopores
Specific Aim 3: Characterize exosome translocation, electric field induced
deformation and detect exosome interaction with antibodies against endosomal
markers
a. Detect exosome translocation through nanopore and study voltage dependence
of translocation characteristics
b. Investigate interaction of surface protein with the complementary (anti-CD63 )
antibody using translocation signals
Hypothesis: Similar to soft DOPC liposomes, when exosomes are subjected to high
strength electric field inside nanopores, they would exhibit voltage dependent
deformation behavior. Interaction of anti-CD63 antibody with the exosome surface
markers will increase the vesicle size, and free and antibody bound exosomes can be
distinguished based on the current signatures.
4.1 Introduction
Exosomes are membranous nano-vesicles (30-150 nm) secreted by a variety of
cells [127-129] into many body fluids including saliva [130], blood [131], urine [132],
breast milk[133] and in the cultured medium of cell cultures [134]. Their molecular
72
contents are derived from the parent cells and contain a variety of proteins, lipids, micro
and messenger RNA. Exosomes are produced by inward budding of endosomes and get
released into the extracellular space when endosomes fuse with the plasma membrane.
Exosomes have been widely investigated for their role in short and long range
intracellular signaling. After their release into the extracellular milieu, protein receptors
on exosome surface facilitate their uptake by proximal and distal cells [135]. The micro
and messenger RNA carried by the exosomes can then be incorporated and translated
in the recipient cells, thereby reprogramming their fate. Because of their ability to
efficiently deliver their contents to distal cells, exosomes act as mediators of
tumorigenesis [136] and proangiogenic remodeling of tissue matrices [137]. In addition
to cancer, exosomes have also been implicated in various other pathologies like
cardiovascular disease [138], inflammatory [139] and neurodegenerative disorders
[140]. The presence of cell specific molecular contents in exosomes and the ability to
easily harvest them from body fluids are driving the exosome centered pipeline for
clinical diagnosis and therapeutic monitoring using ‘liquid biopsies’ [141, 142].
Furthermore, given their ability to preserve the cargo and deliver it to specific cell types,
exosomes have been actively explored as next-generation drug delivery vehicles [143,
144].
73
Figure 4.1. Different type of membrane vesicles released by the eukaryotic cell. Adapted
from [20].
In order to use exosomes for diagnosis, disease monitoring and drug delivery,
we need techniques to accurately characterize their morphology and mechanical
deformability. Exosomes are recently discovered natural nano-vesicles and they exist at
the lowest limit of detection for techniques routinely used for nanoparticle
characterization, making their analysis very challenging. This research aims to develop
solid-state nanopore based technique for estimating size and deformability of soft nano-
vesicles and bridge the technology gap for particle analysis at sub-100 nm length scale.
Although size is an important morphological characteristic used to differentiate
exosomes from other extracellular vesicles (EVs), their size has been reported with a
74
large range of 30-150 nm. This variability in reported size comes from the source from
where they are isolated, the methods of isolation and the characterization techniques.
The methods of exosome isolation include ultracentrifugation, density gradient
isolation, immunoaffinity capture, solvent precipitation and size exclusion
chromatography [145, 146]. Based on the isolation method used, exosome preparation
may include microvesicle contaminants which can result in overestimation of the size.
Although consistency in exosome source and isolation methods can be achieved,
measurement techniques remain the bottleneck for accurate size estimation because
exosome size fall on the lower side of detection limit of majority of the techniques [147,
148] . Recently, resistive pulse sensors have been added to the exosome
characterization repertoire. These sensors typically estimate vesicle size by correlating
the current drop values obtained for vesicle translocation with the current drop values
obtained for control analytes (polystyrene beads) of known size. Majority of size
estimation for exosomes using resistive pulse sensing technique has been done on
commercially available tunable resistive pulse sensor (TRPS) qNano from iZon
Science, New Zealand. Lane et al. used TRPS for evaluating the potential of different
isolation techniques used for purifying exosomes [149]. They used liposomes as model
vesicles to evaluate the isolation efficiency and majority of data presented pertains to
liposome translocation; however, some exosome translocation data is also reported.
Maas et al. also used TRPS sensors for quantification and size estimation of exosomes
[150]. The lowest pore size available from iZon is NP100, which is suited for detection
and analysis of particles in the size range of 70-200 nm [150]. The lowest limit of
75
detection offered by iZon is significantly greater than the lower range of exosome size
(30-150 nm). Lane et al. reported exosome mean diameter as 78 nm and mode as 68 nm
(they report cut off value for NP100 as 56 nm) is very close if not below the lowest limit
of detection of the instrument [149]. Direct flow cytometry has also been used for
analysis of exosomes and other extracellular vesicles; however, it is very labor intensive
and time consuming compared to TRPS technique [151]. In addition, electric field and
hydrodynamic force inside the nanopore can cause the exosome to deform and size
estimation using resistive pulse sensing needs a corrective factor for the deformation.
Since the extracellular vesicles like exosomes originate from the cells, their lipid
bilayer composition is very similar to the cellular membrane. This makes them ideal
candidates for studying membrane mechanics at nanoscale. The technique of studying
mechanical behavior of extracellular vesicles can be further expanded to other nanoscale
entities like viruses.
Exosomes exhibit a variability in surface proteins based on their origin and
disease state of the parent cells. These surface receptors are typically quantified using
proteomic and transcriptional analysis which rely on ensemble averaging of large
population, overlooking particle to particle variability. So if there is an increase in the
total protein content from exosome preparation, it is difficult to determine if the increase
is due to higher concentration of exosomes or due to higher concentration of protein per
exosome. The absence of invariant housekeeping markers further complicate this
estimation. The use of single molecule technique like resistive pulse sensing can help to
76
obtain structural and surface molecular information about individual exosomes, which
in turn can be used to recognize subpopulations in exosome preparations.
4.2 Materials and Methods
4.2.1 Nanopore fabrication
For nanopore chip fabrication, method described in Chapter 1 and 2 were used.
250 and 350 nm diameter nanopores were then drilled in 200 nm thick SixNy membrane
using a FEI Strata DB 235 FIB.
4.2.2 Analyte preparation and characterization
Polystyrene particles were purchased from Polysciences Inc. (Warrington, PA,
USA) and purified exosomes from invasive human breast cancer cell line were
purchased from System Biosciences Inc. (Mountain View, CA). For translocation
experiments, both analytes were dispersed in PBS. The polystyrene particles were
sonicated for 5 minutes before translocation experiments.
For TEM imaging, exosome samples were fixed and negative stained. The
protocol followed for sample preparation is as below:
Free exosomes:
77
a. 5 µl of exosome sample (diluted 1:10 in PBS with 1% BSA) was mixed with 5
µl 4% paraformaldehyde and 5 µl of the mixture was dispensed on holey carbon
TEM grids (placed on parafilm) for 30 minutes.
b. Grids were then treated with 1% glutaraldehyde solution (prepared in PBS) for
30 min. Glutaraldehyde acts as a fixative and prevents exosomes from bursting.
c. 100 µl drops of DI water were dispensed on parafilm for washing the TEM grids.
The grids were washed 8 times for 3 min each. This washing step is important
to remove salt which can cause precipitation of contrast agent.
d. After washing, the exosomes were stained with 2% phosphotungstic acid for 10
min.
e. Any excess liquid was removed by wicking using a filter paper and the TEM
grids was air dried.
All steps were performed on ice.
For immunogold labeled exosomes:
a. 5 µl of exosome sample (diluted 1:10 in PBS with 1% BSA) was mixed with 5
µl 4% paraformaldehyde and 5 µl of the mixture was dispensed on holey carbon
TEM grids (placed on parafilm) for 30 minutes.
b. 100 µl drops of PBS were dispensed on parafilm for washing the TEM grids.
The grids were washed twice for 3 min each.
78
c. The grids were then washed 4 times (3 min each wash) with PBS + 50mM
glycine. It helps to quench any free aldehyde groups.
d. Then the grids were transferred to the blocking buffer- PBS + 5% BSA for 60
min.
e. After blocking, grids were transferred to 5 µl drop of antibody. We used
biotinylated anti-CD63 antibody and its isotype control, both purchased from
BioLegend, San Diego, CA. The antibodies were diluted to a final concentration
of 20 µg/ ml in PBS + 1% BSA.
f. The grids were transferred to the washing buffer (PBS + 1% BSA) and washed
6 times with 3 min for each wash.
g. The grids were then transferred to 50 µl drops of streptavidin coated gold
nanoparticles (5 or 15 nm diameter) diluted to 0.3 OD concentration in PBS +
1% BSA and incubated for 15 min. Streptavidin coated gold particles were
purchased from Cytodiagnostics Inc., Ontario, Canada.
h. The grids were then washed in fresh drops of PBS 8 times with 2 min for each
wash.
i. Grids were then treated with 1% glutaraldehyde solution (prepared in PBS) for
15 min. Glutaraldehyde helps preserve the exosomes and stabilizes the immune
complex.
j. Grids were then washed with DI water 8 times with 2 min for each wash. This
step is important to get rid of ions which can cause precipitation of the contrast
agents.
79
k. After washing, the exosomes were stained with 2% phosphotungstic acid for 10
min.
l. Any excess liquid was removed by wicking using a filter paper and the TEM
sample was air dried.
All steps were carried out on ice and for longer incubations samples were placed in
refrigerator.
4.3 Results and Discussion
4.3.1 Characterization of free and immunogold labeled exosomes using TEM
The fixed and stained exosomes were imaged with JOEL 2100 TEM at 120 keV
accelerating voltage. Since exosome are of biological origin and are isolated from cell
culture media, they are expected to exhibit a range of size distribution. Figure 4.2 shows
some representative TEM images obtained for the exosomes. In our analysis the size of
exosomes ranged from 45.28 nm to 225.38 nm. Although on occasion several smaller
particles of ~25 nm diameter were observed, but they were not included in the analysis.
We measured the diameter of exosomes from the TEM images using ImageJ and plotted
the histogram for the size distribution (Figure 4.3). The histogram was fitted with the
Gaussian distribution function with a mean value of 91.27 nm and standard deviation
25.46 nm. The size distribution obtained using TEM imaging is consistent with the
vendor supplied data on size estimation. It is challenging to perform electron
microscopy on exosomes because they have the tendency to burst when washed in water
80
or dried for analysis in vacuum. Their imaging is typically achieved using cryo-TEM
which involves freeze drying the sample to preserve vesicle morphology. However,
cryo-TEM instruments are rare and we did not have access to it, which made exosome
fixing and staining step very critical. In our TEM images we observed many burst
exosomes; nevertheless, we were able to capture good images to characterize the size
and morphology of these vesicles.
81
Figure 4.2 Representative TEM images of exosomes stained with phosphotungstic acid
and imaged using JOEL 2100 at 120 keV.
82
Figure 4.3 Size distribution of free exosomes based on the TEM imaging data. The size
histogram was fitted with the Gaussian distribution function with Mean: 91.27 nm and
Standard deviation: 25.46 nm. The r-square value for the Gaussian fit was 0.9582.
In addition to size variability, the exosome samples are also expected to be
contaminated by other micro/ nanovesicles. In order to establish the endosomal origin
of the vesicles and for molecular profiling of CD63 markers on exosome surface, we
reacted exosomes with biotinylated anti-CD63 antibodies which were further tagged
with streptavidin coated 15 nm gold nano particles. Figure 4.4 shows TEM images of
the immune-gold labeled exosomes.
0 50 100 150 200 2500
10
20
30
40
Diameter (nm)
Fre
qu
en
cy
83
Figure 4.4 Immunogold labeling of exosomes. The CD63 markers on vesicle surface
were bound with biotinylated anti-CD63 antibody, which were then bound with
streptavidin coated 15 nm gold nano particles. The labeled vesicles were imaged using
JOEL 2100 TEM operated at 120 keV.
4.3.2 Detection of exosome translocation
For nanopore translocation experiments, 250 and 350 nm diameter pores drilled
in a 200 nm free standing silicon nitride membrane were used. The nanopore chip was
assembled in a flow cell and the –cis and –trans chambers were filled with Ca2+/Mg2+
free PBS. As supplied exosomes were diluted 1:200 in Ca2+/Mg2+ free PBS and used for
translocation experiments. The final concentration of exosomes was approximately 3 ×
104 vesicles per ml. The exosome sample was added to the –cis chamber of the flow cell
84
and a 200 mV transmembrane voltage was applied. We did not observe any
translocation events for 100-300 mV transmembrane voltages. The absence of events at
these lower voltages can be attributed to their charge and low abundance in the solution.
When 400 mV voltage was applied, translocation events were observed which also
continued to appear at higher voltages. The current drop (ΔI) and translocation time (Δt)
values of the resistive pulses were extracted and used for further analysis. Figure 4.5
shows some representative current signatures obtained for exosome translocation at 400
mV. Due to the large variation in the vesicle size we often observed pore clogging and
reduction in baseline current as shown in Figure 4.6, but it was immediately corrected
using reverse voltage polarity (Figure 4.6). If reversing the polarity was not sufficient
to unclog the pore, the nanopore chip was disassembled and was cleaned with solvents
as described earlier in Chapter 3.
85
Figure 4.5 (a) Representative current drop signals obtained during exosome
experiments. (b) High-resolution current signature for the translocation events.
86
Figure 4.6 Nanopore clogging by exosomes and unclogging using changing the
transmembrane polarity. Multiple such clogging events were observed during exosome
experiments.
4.3.3 Deformation behavior of exosomes revealed under voltage dependent
translocation characteristics
We recorded and analyzed exosome translocation characteristics at different
transmembrane voltages to investigate their tendency to deform under concentrated
electric field inside the nanopore as observed for the case of liposomes (Chapter 3).
Figure 4.7 shows population distributions for translocation events at 400, 600 and 800
mV transmembrane voltages.
87
Figure 4.7 (a) Scatterplot showing current drop and translocation time distributions of
events recorded at 400, 600 and 800 mV transmembrane voltages using a 250 nm
diameter pore. (b-d) show two dimensional histograms for the translocation data at 400.
600 and 800 mV respectively.
88
As seen in Figure 4.7, the translocation time decreases with the increasing
transmembrane voltage but the current drop (ΔI) values are not much affected. As
discussed in Chapter 3, typically, the ΔI values increase with the increasing
transmembrane voltage due to an increase in the baseline current value (Io). However,
we observe that ΔI values remain almost constant despite the increase in Io when
increasing the transmembrane voltage. To further understand the variation in current
drop and translocation time quantitatively, the event distributions at the three voltages
were fitted with log-normal functions to obtain the mean and the standard deviation
values. The fitted log-normal distribution curves are shown in Figure 4.8 and the
corresponding fit parameters are shown in Table 4.1.
Figure 4.8 Long-normal distribution curves fitted to current drop and translocation time
population distributions at 400, 600 and 800 mV.
89
Table 4.1 Fit parameters of log-normal distribution fitting to voltage dependent
exosome translocation data shown in Figure 4.8
Voltages Mean SE of Mean Std. dev. R2
Current drop
(pA)
400 mV 414.34 6.08 0.17 0.902
600 mV 409.15 7.54 0.15 0.819
800 mV 415.62 5.41 0.12 0.860
Translocation
time (ms)
400 mV 0.324 0.014 0.45 0.932
600 mV 0.249 0.004 0.41 0.984
800 mV 0.191 0.003 0.39 0.977
Based on the current drop, percent current drop values at the three voltages were
calculated and were normalized to the value observed at 400 mV. The normalized values
were fitted with an exponential decay curve (𝑦 = 18.6 𝑒−0.009113𝑥 + 0.5141) and are
plotted in Figure 4.9. This trend in current drop values is very similar to the deformation
behavior seen for DOPC liposomes in Chapter 3. However, unlike the liposome
translocation data, we observe translocation events at voltages as high as 1000 mV. In
the current analysis, voltages up to 800 mV are used because at higher voltages
nanopore was more prone to clogging. The presence of events at high voltages is
expected because exosomes are not as soft and fragile as DOPC liposomes and can
withstand higher electric field density and shear force.
90
Figure 4.9 Exponential distribution fitting of the normal percentage current drop data.
The data was normalized to percentage current drop values obtained at 400 mV.
4.3.4 Detection of exosomes labeled with immunogold for CD63 endosomal
markers
Next, we performed experiments with immunogold labeled exosomes and
compared their translocation behavior to the free exosomes. The exosomes were labeled
using anti-CD63 antibodies and 15 nm gold nanoparticles. For both analytes,
experiments were performed using the same nanopore and the buffer conditions.
Translocation data was recorded at 500 mV transmembrane voltage. Figure 4.10 shows
overlaid scatter plot for free and labeled exosomes. For free exosomes (sample 1)
91
majority of the events resulted in current drop value < 1000 pA and translocation time
< 0.4 ms. However, when the exosomes were labeled with immunogold (sample 2), they
exhibit a bimodal distribution. Some fraction of translocation events are localized in the
same region of the plot as free exosomes but majority of them show increase in current
drop and translocation time. It suggests that the fraction of sample 2 with translocation
characteristics similar to those of sample 1 may not have been expressing CD63 markers
and were not labeled with the immunogold, highlighting the single molecule detection
ability of solid state nanopores to recognize subpopulations in the samples.
Figure 4.10 Scatter plot show the population distribution for the free and immunogold
labeled exosomes. The labeled exosomes show higher current drop and translocation
time compared to the free exosomes as expected from their larger size.
92
The event characteristics were also plotted as histograms and fitted with the log-
normal distribution functions as shown in Figure 4.11. The fitting analysis for the
population distribution confirmed the trends obseved in the scatter plot. The fitting
parameters for the log-normal functions are presented in Table 4.2. Although the curve
fit to the current drop histogram for the labeled exosomes could not be pefectly fit
because of the skewness and the bimodal nature of the distribution (R2=0.8), it indicated
a mean value of 972.53 pA, which is significantly higher than the mean current drop
vallue of 395.35 pA for the free exosomes. The long tail extending into several
thoudsands of picoamphere observed in case of labeled exosomes can be attributed to
formation of higher complexes because of multivalency of streptavidin. Similarly the
mean value for the translocation time increased from 0.22 ms for free exosomes to 0.45
ms for the immunogold labeled exosomes. The medians of distributions were also
compared using Mann-Whitney U Test, according to which both the current drop values
and translocation time values were significantly different for free and labeled exososmes
(p value <0.0001).
93
Table 4.2 Fit parameters of log-normal distribution fitting to free and labeled
exosome data shown in Figure 4.11
Mean SE of Mean Std. dev. R2
Free exosomes current
drop (pA)
395.35 3.51 0.18 0.943
Labeled exosomes current
drop (pA)
972.53 73.98 0.6 0.801
Free exosomes
translocation time (ms)
0.22 0.0002 0.38 0.999
Labeled exosomes
translocation time (ms)
0.453 0.015 0.74 0.981
94
Figure 4.11 Current drop and translocation time populations of free and labeled
exosomes fitted with log-normal distribution functions.
4.4 Conclusions
We demonstrate breast cancer cell line derived exosomes also exhibit
deformation behavior when subjected to high field strength inside nanopore. Unlike the
soft DOPC liposomes, translocation of exosomes could be detected at voltages as high
as 1V, suggesting they can withstand higher field and flow induced strain inside the
95
pore compared to DOPC liposomes. The vesicles were also characterized by
immunogold labeling for CD63 endosomal marker to establish their endosomal origin.
Their translocation characteristics were also used to distinguish between free and
immunogold labeled vesicles. The labeled vesicles resulted in deeper current blockades
due to their larger size compared to the free vesicles.
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Chapter 5: Conclusions and future directions
5.1 Conclusions
This dissertation presents results on investigation of co-translocational
deformation of soft-nanovesicles using resistive pulse sensing and solid-state
nanopores. First, the translocation behavior of small nanoparticles was studied using
low salt concentration. This investigation allowed to us to understand transport
principles governing translocation of sub-100 nm particles in dilute solutions. At low
electrolyte strength our experiments resulted in current enhancement upon particle
translocation instead of current blockades. The reversal in current characteristics was
explained by availability of new charge carriers brought into the nanopore by the
translocating nanoparticle. Low salt conditions resulted in thick counterion cloud
around the nanoparticles which resulted in introduction of new charge carriers into the
pore. The phenomenon of current enhancement and charge balance was systematically
investigated using Multiphysics modeling by sequentially varying different
experimental parameters. Based on the published literature, Multiphysics modeling and
experimentation we identified salt concentration, particle charge and the ratio of the
pore diameter to the particle diameter as the main contributing factors leading to current
enhancement. The understanding derived from this study helped us to optimize our
system for nano-vesicle detection and analysis.
For the experiments with liposomes, soft DOPC liposomes of ~ 85 nm diameter
were translocated through the nanopore and their co-translocational deformation caused
by high field strength and confinement/ flow induced strain inside the nanopore was
97
investigated. The deformation of vesicles was inferred from comparison of resistive
pulse current signatures obtained at different transmembrane voltages. We observed a
progressive decrease in percent current drop for liposome translocation with the
increasing transmembrane voltage (100-600 mV). No translocation events were
detected at voltages higher than 600 mV and it could be due to vesicle rupturing due to
high field strength. The deformation behavior of liposomes was compared to the rigid
polystyrene particles which maintained their shape and did not exhibit any deformation.
The deformation of liposomes is believed to be caused by charge separation and
membrane charging when placed in the electric field, a phenomenon similar to what has
been reported for the behavior of giant vesicles in DC electric fields.
Finally, the experiments and the analyses were extended to exosome samples
derived from human breast cancer cell line. Exosomes also exhibit co-translocational
deformation behavior; however, they appear to be less affected by the deforming force
inside the nanopore compared to the DOPC liposomes. Exosomes were also identified
by immunogold labeling with antibodies against the endosomal markers CD63. The
translocation of free and immunogold labeled exosomes was also compared and the two
populations could be distinguished based on their current drop and translocation time
values.
98
5.2 Future directions
5.2.1 Numerical analysis and quantification of deformation
Quantification of deformation in terms of standard mechanical properties like
Young’s modulus and bending rigidity is difficult because the deformation is caused by
both the concentrated electric field and the hydrodynamic stress as the soft vesicles
translocate through the pore. Moreover, the electric field inside the pore is non uniform
which makes the quantification more complex. We are working with biophysicists and
theoreticians to develop a theoretical framework to quantify the deformation and to use
this technique for wider applications.
5.2.2 Comparison of deformation of vesicles with different lipid bilayer
composition and diameters
The mechanical properties of lipid bilayers depend on their composition and
factors like the level of unsaturation in the lipids, the ratio of lipids and cholesterol and
the distribution of transmembrane proteins influence the mechanical properties. The
nanopore sensing technique can be used to study the correlation between vesicles
composition and deformation. Similarly, the deformability of vesicles is also a function
of their diameters as different diameters result in different membrane curvatures.
Nanopore sensing can also be used to investigate the effect of vesicle size on membrane
deformability.
99
5.2.3 Expansion of experimental repertoire to answer biologically relevant
questions
The vesicle deformation investigation using nanopore can be extended to answer more
biological questions such as:
a. Does the deformability of enveloped viruses change with the level of viral maturation?
b. Do exosomes derived from different cell sources have different deformability?
c. Does the disease state change the mechanical properties of exosomes or the protein
expression on their surfaces?
The above questions can be answered based on nanopore based investigations of
exosomes and they will establish nanopore sensing as a viable technique to study biologically
relevant properties of nano-vesicles.
100
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Vita
Gaurav Goyal
Education
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
M.S. in Bio and Brain Engineering, 2009
Ambala College of Engineering and Applied Research, Kurukshetra University, India
Bachelor of Technology in Biotechnology Engineering, 2006
Experience
Graduate Research Assistant, Sept’11 to Present
BAST Lab, Mechanical Engineering and Mechanics Department, Drexel University, Philadelphia
Fabricated and characterized solid-state nanopore devices. Obtained expertise in electron microscopy with over 200 hours of experience of using transmission electron microscope (Joel 2100).
Used solid-state nanopores for single molecule detection of DNA, proteins, liposomes, exosomes, polystyrene and gold-nano particles. Developed nanopore based method for mechanical characterization of soft nano liposomes (<100 nm diameter).
Oversaw general upkeep of the lab, generated and documented standard operating protocols and implemented laboratory policies and safety regulations.
Negotiated technical specifications and price for new microscopes purchased, and supervised the installation of the instruments by vendor personnel, including site preparation and working with appropriate teams.
Actively participated in student organizations and occupied several key leadership positions including president of Engineering Graduate Association in 2012-2014.
Visiting Researcher Nov’14 to Jan’15
National NanoFabrication Center, Daejeon, South Korea
Performed design verification and validation (V&V) for multilayer nanochannel device for DNA mapping
Worked on transfer and characterization of single layer graphene on arbitrary surfaces
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Visiting Researcher/ Consultant Nov’14 to Jan’15
Korea Research Institute of Bioscience and Biotechnology, Daejeon, South Korea
Trained personnel on single-molecule protein detection using solid-state nanopores
Designed research strategies for ultra-sensitive single molecule detection of cancer biomarkers
Graduate Research Assistant, Sept’10 to Aug’11 School of Biomedical Engineering, Drexel University, Philadelphia
Helped build neural tissue engineering lab ground up and oversaw general state of the laboratory, including instrument maintenance and chemical inventory management
Worked on primary neuron culture, neural stem cell culture, electrode implantation in rat brains followed by micro-sectioning and characterization using immunofluorescence microscopy.
Graduate Research Assistant, Mar’07 to Jan’10
Neural Engineering Lab, Department of Bio & Brain Engineering, KAIST, South Korea
Developed microfluidic devices for culturing mammalian cells. Improved culture length of rat primary neurons in closed microfluidic channels from 7 days to 1 month.
Obtained extensive microfabrication experience with over 100 hours of clean room experience.
Certifications
National Institutes of Health (NIH), Certification in Clinical and Translational Research
National Instruments, Certified LabView Associate Developer (CLAD)
National NanoFab Center, Daejeon, South Korea, Certification in basic Semi-conductor Processing Technology
Fellowships
Calhoun Fellowship, Drexel University (Sept’10-Sept’11)
Foreign Scholars Invitation Fellowship, Korea Research Foundation (KRF), Govt. of Republic of Korea (March’07-Aug’07)
Korea Advanced Institute of Science and Technology (KAIST) Foreign Scholars Fellowship (March’07-Feb’09)
CSIR Program on Youth for Leadership in Science Fellowship, Council of Scientific and Industrial Research, Govt. of India (Aug’00)
International Space School Fellowship, United Space School, Houston, TX (Aug’99)
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Journal Publications
Goyal, G., Darvish, A. and Kim, M. J. "Use of solid-state nanopores for sensing co-translocational deformation of nano-liposomes." Analyst 2015, 140(14):4865-73.
Goyal, G., Mulero, R., Ali, J., Darvish, A., and Kim, M. J. "Low aspect ratio micropores for single‐particle and single‐cell analysis." Electrophoresis 2015, 36 (9-10): 1164-1171.
Goyal, G., Freedman, K. J. and Kim, M. J. “Gold nanoparticle translocation dynamics and electrical detection of single particle diffusion using solid state nanopores.” Analytical Chemistry 2013, 85 (17): 8180–8187.
Goyal, G. and Nam, Y. “Neuronal micro-culture engineering by microchannel devices of cellular scale dimensions.” Biomedical Engineering Letters. 2011, 1(2):89-98.
Goyal, G., Lee, Y. B., Darvish, A., Ahn, C. W. and Kim, M. J. “Hydrophilic and size-controlled graphene nanopores for protein detection.” Submitted.
Book Chapters
Goyal, G., Freedman, K. J., Prabhu, A. S. and Kim, M. J. “Case studies using solid-state pores” in Engineered Nanopores for Bioanalytical Applications, Ed. J.B. Edel and T. Albrecht, Elsevier, 2013: 141-170.
Conference Proceedings
Goyal, G., Darvish, A. and Kim, M. J. “Controlled shrinking of nanopores in single layer graphene using electron beam irradiation.” Proceedings of μTAS 2014 Conference, San Antonio, USA (p.1838-1840)
Goyal, G., and Kim, M. J. “Use of solid-state nanopores to detect different conformational states of transferrin.” Proceedings of μTAS 2014 Conference, San Antonio, USA (p.1359-1361)
Goyal, G., Mulero, R. and Kim, M. J. “Low aspect ratio resistive pulse sensor for single cell analysis.” Proceedings of μTAS 2014 Conference, San Antonio, USA (p. 837-839)
