Analysis of Single Mammalian Cells On-Chip
Christopher E. Sims and Nancy L. Allbritton*
Department of Physiology and Biophysics
University of California, Irvine, CA
*Correspondence: Nancy L. Allbritton, Department of Physiology and Biophysics, University of
California, Irvine, California, 92697
Email: [email protected]
Fax: 949-824-8540
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Abstract
A goal of modern biology is to understand the molecular mechanisms underlying cellular function.
The ability to manipulate and analyze single cells is crucial for this task.
The advent of
microengineering is providing biologists with unprecedented opportunities for cell handling and
investigation on a cell-by-cell basis. For this reason, Lab-on-a-Chip (LOC) technologies are emerging as
the next revolution in tools for biological discovery. In the current discussion, we seek to provide a
biological perspective on the importance and advantages of LOC devices in the performance of singlecell studies. In addition we will discuss the requirements and challenges in the development of robust,
facile assays and instrumentation that are required for widespread adoption of these technologies. The field
is expanding rapidly and we have focused on areas of broad interest to the biological community where
the technology is sufficiently far advanced to contemplate near-term application in biological
experimentation. Focus areas to be covered include flow cytometry, electrophoretic analysis of cell
contents, fluorescent indicator-based analyses, cells as small volume reactors, control of the cellular
microenvironment, and single-cell PCR.
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1. Introduction
1.1. Rationale for single cell analysis.
Most cell-based biological assays yield data averaged across large groups of cells, yet it is well
known that individual cells, even those identical in appearance, differ in numerous characteristics.
Variability in the expression of a particular gene, concentration of a critical metabolite or ion, or pattern of
response to a given stimulus are but a few of the well documented examples of cellular heterogeneity.1-5
Due to this heterogeneity, traditional biochemical assays which analyze cells in bulk often overlook the rich
information available when single cells are studied. For this reason, much emphasis has been placed over
the past few decades in technical advances to enable biologists to peer into the molecular machinery of
individual cells. In gene expression studies, single-cell PCR has made it possible to identify whether two
or more genes are co-expressed in the same cell or in different sub-populations of the cells.6, 7 Likewise, it
has been possible to understand whether a small increase in expression measured in the ensemble results
from a small, homogeneous increase across all cells or a large increase in a subset of cells. Microscopic
imaging and chemical separations have elucidated unique biological phenomena in single cells not
discoverable by bulk sampling procedures. For example, fluorescent indicators of calcium ion (Ca2+)
concentration have revealed that after certain stimuli some cells display unique patterns of repetitive
increases and decreases in Ca2+ concentration over time. These Ca2+ transients are believed to encode
informational content in their frequency, amplitude and organization.8-10 The unique patterns are hidden
when averaging Ca2+ concentration over a population due to differences in timing and response of
individual cells.
Another example of biological discovery from single-cell studies is the switch-like
activation of MAP kinase, an enzyme regulating growth in almost all cell types. The all-or-none pattern of
phosphorylation of MAP kinase in response to a linear increase in progesterone concentration was
discovered by gel electrophoresis of the contents of single Xenopus laevis oocytes, giant cells with a 1 µl
volume.1 When measurements were performed on pooled cell lysates, a linear increase in MAP kinase
activity in response to a linear increase in progesterone concentration was measured. The threshold level of
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progesterone to transition from the “off” state to the “on” state was different for each cell, so that the
switch-like activation of MAP kinase was not apparent. This on-off behavior is believed to be a critical
signal transducer in committing the cell to maturation.
Single-cell measurements are also of value in studying mixed cell populations. In studies of disease
states, analysis of a sample taken directly from a model organism or patient is complicated by the
admixture of normal cells with diseased cells. Single-cell studies of tumor biopsies have shown that the
majority of cells within a tumor may be normal, and that significant heterogeneity exists even among the
abnormal cells.6, 11 Determination of the molecular characteristics of most tumors is thus extremely limited
by analysis of pooled cell lysates. A caveat for single-cell approaches is that stochastic biological events or
the chance analysis of a very rare cell can create noise which may confound observations. Thus, in
addition to extending biological measurements beyond population averages, single-cell measurement
techniques must retain the capacity to perform population statistics. It is in the area of single-cell assays
that Lab-on-a-Chip (LOC) technologies are envisioned to have one of their most significant impacts as bioanalytical tools.
1.2. Specifications and challenges for single-cell analyses.
The technical specifications for single-cell analysis are strict, but LOC designs are ideally
suited to meet these requirements. A single mammalian cell weighs only 3-4 ng, the majority being
water by weight and volume.12 These cells possesses a cell body on the order of tens of microns in
diameter with a volume of ~1 pL.13 In addition to water, inorganic ions and small organic molecules
(sugars, vitamins and fatty acids) make up most of the cellular contents. Macromolecules, such as
DNA/RNA and protein, make up less than 25% by weight of the molecular species within a single
cell.12 Since 1-2 copies of a specific DNA sequence exists in a normal cell, the molar concentration of
a gene is only on the order of 10-12 M.12 An individual cell’s total cellular protein content is quite high,
averaging 8×109 molecules per cell (700 pg). Nevertheless, each cell contains an estimated 104
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different proteins with a wide disparity in their abundance with <100 molecules of many receptors,
1000-10,000 molecules for various signaling enzymes, and 108 molecules of some structural proteins. 12
Microfluidic LOC devices possess the dimensions and volume handling capacities to manipulate and
sample single mammalian cells; however, the small absolute amount and low concentrations of the
cellular species of interest present significant challenges for detection. Although not a trivial task, the
small amount of DNA or RNA collected from a single cell can be amplified by PCR methods to
achieve adequate quantities for detection by a variety of means.7 Unfortunately, proteins and most
other analytes cannot be readily amplified, so that their detection, usually accomplished with
fluorescence-based strategies, is more stringent.
Further complicating the study of single cells is that cellular constituents exist in a complex
cytoplasmic milieu or tethered to lipid membranes. This state of affairs often requires employment of
purification or separation strategies prior to analysis, but doing so with minimal loss or dilution of the
sample remains a challenge in the chemical analysis of individual cells. In addition, the mixed
hydrophobic-hydrophilic nature of many biological macromolecules leads to their adsorption to a
variety of surfaces. This characteristic results in significant loss of sample for analysis or diminished
resolution in chemical separations. Cells themselves may stick to the non-natural surfaces of LOC
devices. At times this behavior can be used to advantage in positioning a cell for analysis, but may
also result in loss of target cells during manipulation or in device clogging. Related to this topic is that
cells in their native state may exist in a nonadherent or adherent state. Blood cells typically survive
well in suspension, and are easily manipulated by fluidic means; however, the vast majority of
mammalian cells grow adherent to a surface and may undergo apoptosis (programmed cell death)
when detached from their growth surface for greater than a few minutes.14 In addition, the act of
placing normally adherent cells into suspension for transfer into an analytical device damages cell
membranes and activates many signaling pathways that may perturb the biological process to be
studied.15
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The tendency for living cells to be perturbed by manipulation imposes stringent requirements in
performing a successful biological experiment. Artifacts related to perturbations or membrane damage
during cell sampling are a potential pitfall of analyses performed on live cells.16,
17
Biological
molecules are in a constant state of flux and changes in the cell’s environment such as pH, ionic
strength, and temperature can lead to variation in the intracellular concentrations of many molecular
species. Ion concentration and protein phosphorylation can vary dramatically on subsecond to second
timescales, whereas RNA and protein concentrations can change over minutes to hours. Studies of cell
physiology require analysis of live cells, and mandate that the cells be maintained in a high salt, neutral
pH, aqueous solution until the time of analysis to prevent artifacts from damage or stress to the cell.
The many biological complexities of live cells require technical innovation in order to perform
reproducible and valid cell-based assays with LOC devices, particularly when studying dynamic
cellular characteristics.
Owing to the burgeoning investigation and rapid progress in LOC technologies for cell-based
assays, numerous reviews have been published in just the last few years.18-29 These excellent reviews
cover the tremendous technical advances that have been made in the critical areas of on-chip cell
cultivation, manipulation, treatment, sampling, and analysis. In the current review, we do not seek to
reiterate these often extensive compilations of the state-of-the-art, but rather provide a biological
perspective and examples as to the importance and advantages of LOC devices in the performance of
single-cell analyses. Due to space constraints, we will limit our discussion largely to light-based
analyses of mammalian cells or their contents. Nevertheless, we recognize that much important work
has been performed using bacteria and yeast, and the same holds true for other analysis strategies such
as patch clamp and electrochemical sensing.
We will highlight technical advances in areas of
particular interest to the biological community where it appears that LOC technologies are far enough
advanced to contemplate near-term application for general use in biological experimentation. Topics
to be covered include flow cytometry, electrophoretic analysis of cell contents, microscopic analyses
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with indicators, cells as small volume reactors, interplay of cells with the microenvironment, and
single-cell PCR.
2. Flow cytometry for on-chip analyses of single mammalian cells
2.1. Flow cytometry overview.
Flow cytometry is a common and well-established method for analyzing hundreds of thousands
of individual cells. The technique uses one or more focused laser beams directed at a glass capillary
tube through which a high-speed stream of cells in suspension flow in single file.30 The procedure is
often performed using fluorescent probes that act as indicators of cellular constituents or functions.
Given that a fluidic system lies at the heart of this technology, it is not surprising that flow cytometry is
one of the more mature cell-based bioanalytical applications performed on LOC devices. In the past
decade hundreds of papers have described a variety of exciting techniques and novel strategies for
cytometric analyses and sorting based on microfabricated flow systems.29, 31 At least three companies
(Agilent, Evotec and Micronics) are currently marketing microfabricated devices for basic flow
cytometry assays. Despite this success, to date LOC devices have seen only minimal use for flow
cytometry applications by investigators in the biological sciences (see for example Wheeler et al. 2006
and Gerdts et al. 2006). 32, 33 One reason for this limited adoption is that almost fifty years of continual
development and recent technical advances have reduced the cost, size and complexity of traditional
flow cytometers.
Elegant systems combining custom configurations, 16-parameter analyses, and
single-cell sorting capabilities are now the state-of-the-art in flow cytometry, while models capable of
interrogating tens-of-thousands of cells per second with 6-to-8 parameter analyses are available at
prices affordable for individual labs.34, 35 Indeed, simplified and robust bench-top and portable systems
capable of meeting the basic needs of many biology labs can now be purchased for the price of a
fluorescence microscope.
Additionally, most new flow-based assays are demonstrated on flow
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cytometers rather than on LOC devices which slows adoption in the biology community where data
gathering is often prized over technical progress.
2.2. Current state of LOC devices for flow cytometry.
Despite the current sophistication, relative affordability, and widespread adoption of modern
flow cytometers, microengineering offers considerable opportunities for technical advancement in this
field. Most standard flow-based assays have now been recapitulated in microfluidic systems, but to
date these systems lack the throughput and multiparametric capabilities of standard flow cytometers. 22
Miniaturization and parallel processing offered by LOC technologies provide the means to enhance the
throughput of analyses; however, the development of miniaturized, parallel technologies for flow
cytometry has yet to be accomplished.36 Furthermore, the vast body of work regarding on-chip detection
for flow-based assays has been limited to single variable analysis.23,
29
There have now been a few
examples of interrogating cells for two parameters, and these will be highlighted in the current review.
Given that LOC technology has the potential for producing devices with a high level of integration,
significant opportunities for accomplishing multiparameter analyses exist. Especially important in this
regard are examples of miniaturized, embedded optics which can provide stable, high-precision light
detection.29, 37 Another topic of importance in chip-based flow analysis is manipulation and processing
of the cell sample. A number of novel fluid handling schemes, for example on-chip pumps, have been
introduced for movement of cells on-chip, although to date only a few studies have combined these
new methods with flow cytometry.31 These efforts are crucial for integration of sample preparation
and analysis, an area in need of innovation.24 Miniaturization and precise cell manipulation also
enable the utilization of very small samples which is especially critical when clinical samples are
contemplated. This subject has been broached, but few careful studies of small cell populations have
been performed.38 In the near future, innovation and technological advances can be expected to bring
sweeping improvements to LOC-based flow cytometry. It is predicted that costs of integrated devices
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will be reduced through standard manufacturing techniques using inexpensive polymers for
fabrication. The parallel design and integration of mixers, incubators, cytometers and sorters coupled
together under computer control are envisioned to carry out automated handling, processing, analysis,
and sorting of cells.24 In the following discussion a topical review of single-cell analysis by flow
cytometry is covered, but cell sorting is omitted. The reader is referred to one of several excellent
reviews describing the current state of microfabricated cell sorters for an appraisal of that topic. 22-24, 29,
31, 36, 37
2.3. On-chip cell preparation.
One prominent issue in the analysis of single cells by flow cytometry is sample preparation. To
date sample preparation steps for on-chip cytometry are almost always carried out prior to introducing
the sample into the device adding labor and consuming sample. Various steps are taken to prepare the
cells for analysis depending on the type of sample. For cytometric analysis, cells must be placed in
suspension which requires disaggregating cells that grow adherently. Even cells that grow naturally in
suspension require filtering to remove cell clumps. Such preparation has not yet been described onchip. Preparation of whole blood by removal of red blood cells (RBCs) has been accomplished by a
variety of on-chip schemes, including selective RBC lysis by ammonium chloride or separation of
RBCs from white blood cells by dielectrophoresis, magnetic interactions, or optical trapping.26,
39
Research-related flow cytometric assays generally require fluorescence staining of cells prior to
analysis. Time-consuming and laborious protocols are required for fluorescence labeling and the use
of multiple fluorescent labels increases this effort. The feasibility of on-chip cell labeling prior to flow
analysis has been demonstrated.40,
41
Lancaster et al. used a sheath flow arrangement to bathe a
continuously flowing sample of white blood cells in a solution containing a fluorescent antibody
against the CD4 cell surface antigen. Labeling time was controlled by flow rate and channel length
with typical dwell times in the labeling region lasting only 15 s. Cells were detected immediately
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downstream by laser-induced fluorescence detection. Despite the brief labeling time and the fact that
the cells remained in the labeling solution during the analysis step, labeled cells could be detected.
Dual labeling of cells with a viability dye (calcein) and a fluorescent antibody directed against the cell
surface protein CD86 has also been demonstrated.42, 43 On-chip staining was performed by combining
cells and staining reagents into the sample well by hand followed by vortexing the entire chip during
the incubation period to achieve adequate mixing. The cells were then transferred by hydrodynamic
flow to the cytometer region of the chip and analyzed directly without further manipulation. While
cells could be detected despite the absence of a wash step, no comparison of sensitivity with detection
of cells stained and washed by standard protocols was made. This on-chip staining procedure reduced
sample handling times and consumption of cells and reagents compared with standard methods.
Reduction in sample size is one area where LOC devices are expected to have a significant advantage
over standard flow cytometers. In a traditional flow cytometry experiment, losses due to sample
preparation and instrument calibration typically require sample sizes of 0.5 – 1×106 cells to generate
data on 104 cells.44 Preckel et al. demonstrated that samples containing as few as 20,000 lymphocytes
could be readily analyzed on-chip.38 These studies were done with cells pre-stained off-chip. No
careful studies of cell loss from on-chip sample preparation or analysis efficiency vs. sample size have
yet been described. From these examples, it is clear that further efforts need to be made in addressing
the significant challenges faced for sample preparation. Particular areas requiring technical advances
include staining of cells with multiple labels, separation of cells from labeling reagents prior to
analysis, and efficient handling of cells during sample prep and downstream analysis. Precise and
rapid manipulation of cells and control of fluid flows provided by microfabricated platforms should
enable creative solutions to achieve these goals.
2.4. On-chip analysis of mammalian cells.
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Analysis of single cells in a microfabricated flow cytometer has been accomplished with a
variety of techniques. As mentioned above, numerous examples of standard flow assays have been
published since the late 1990’s, including Coulter-type counting, light scatter analysis, and
fluorescence detection.29,
31, 45, 46
The throughput of these systems while still well below that of
modern flow cytometers has continually improved with rates of up to 30,000 beads per second
reported.47 These studies will not be further expounded upon in this topical review, rather recent
efforts at multi-parametric approaches and novel cell analyses will be discussed herein.
Multiparametric analysis. Surprisingly few LOC devices have attempted to acquire more
than one variable during flow analysis. A number of investigators have successfully coupled flow
cytometry to measurements of bacterial or yeast fluorescence at two wavelengths.48-50
Few
investigators have attempted dual color, fluorescence measurements with mammalian cells.
The
commercially available Agilent 2100 Bioanalyzer possesses two-color capability to assess cell
fluorescence in flow-based assays.32,
38, 42, 43, 51-53
In these studies, comparison of dual-labeled
mammalian cells against a standard flow cytometer showed good agreement. The Agilent system uses
a glass substrate and fluid flow is controlled hydrodynamically.38
Fluorescence excitation and
emission are performed by off-chip optics. Also using a glass chip, Ramsey’s group described a twocolor coincidence detection scheme for a flow-based toxicity assay for leukemic cells.54 The 488-nm
line from an argon ion laser was used to excite calcein- and propidium-iodide-stained cells.
Fluorescence detection was performed using a microscope objective, spectral filtering optics, and two
photomultiplier tubes. Even greater integration of on-chip optics was demonstrated by Wolff’s group
with an LOC device that used SU-8 as the material for optical waveguides and lens within a
PDMS/glass hybrid chip.55
All of the channels and optical elements were defined by standard
lithography in the SU-8 photoresist using a single mask process.
These microstructures were
fabricated on a glass substrate and a PDMS lid served to seal the device.
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The investigators
demonstrated simultaneous collection of forward scatter, large angle scatter and extinction signals to
measure the size and surface roughness of polystyrene beads, but not cells.
Other analyses. In addition to the more traditional optical-based assays described above,
investigators have pursued alternative single-cell analysis schemes on microfluidic cytometers.
Spectral impedance measurements using the Coulter particle-counter principle have been performed
with integrated electrodes in a flow channel. The spectral impedance of a cell or particle is an
integrative function of size, membrane capacitance, cytoplasmic resistance, and ion channel flux. 26
Differentiation of RBCs from other cell types has been demonstrated.56, 57 Capacitance measurements
of eukaryotic cells within a 1-kHz electric field produced by integrated on-chip electrodes
demonstrated that quantification of the DNA content of single cells could be performed.58 The results
were shown to be consistent with standard analyses performed using fluorescent DNA probes in a
traditional flow cytometer. Another approach that depends on the intrinsic physical properties of cells,
in this case their optical properties, is the analysis of cells under the influence of an optical field.
Zhang et al. implemented a non-invasive microfluidic-based analysis technique based on changes in
transit time of cells flowing through an optical gradient field.59
With this approach, differences
between tissue culture cells from normal skin and melanoma lines were observable.
Integration for flow-based analysis of cells. As well as the efforts already mentioned, other
work aimed at integration deserves reference. Lee’s group has utilized a microfabricated double-layer
structure of SU-8 and spin-on-glass to produce integrated optical waveguides for excitation and
detection in the channel of a glass chip to perform particle counting by light scatter.60 This group has
also detected RBCs using guides fabricated in bonded glass substrates to house and align etched
single-mode fibers.61
This optical arrangement was combined with integrated electrodes for
electrokinetic focusing and flow switching, with the device being used to perform RBC counting by
light-scatter detection. The description by Wolff et al. of a microfabricated device for flow cytometry
is one of the most advanced integration efforts to date.62 This silicon-based device incorporated a
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sheath flow system, a cytometer/cell sorter, integrated optical wave guides, and post analysis cell
collection and culture chamber into one structure. The device was tested on chicken RBCs and yeast
cells expressing green fluorescent protein, but has yet to be demonstrated with mammalian cells.
Ongoing efforts toward integration of functional components on microfabricated platforms will
undoubtedly lead to some of the most significant advances for LOC-based flow cytometry.
3. Electrophoretic analysis of single, mammalian cells on-chip
3.1. Overview of single-cell-based chemical separations.
Microcolumn separations of analytes derived from single cells were first demonstrated in a
capillary by Kennedy and Jorgenson using the neuron of the sea snail.63 The first such analysis of a
mammalian cell was performed in 1994 by Yeung’s group with the separation and detection of lactate
dehydrogenase isoforms in red blood cells.64 Since that time, a substantial body of literature has been
published demonstrating the measurement of other analytes from single cells.65,
66
These analyses
include DNA, RNA, proteins, protein activity, and metabolites with perhaps the most technically
impressive separations to date being the 2-D protein separations achieved by Dovichi’s group. 67
Despite the potential for microanalytical chemical separations in furthering single-cell measurements,
adoption of the method by the biologic community has been very limited. Reasons for the slow
implementation are that current, capillary-based methods are labor intensive and low in throughput.
However, incorporation of these methods into an LOC format has the potential to increase throughput
dramatically by automating cell movement and buffer exchange, decreasing analyte separation times,
and implementing parallel and serial analyses of cells.
3.2. On-chip washing and positioning of cells prior to content separation.
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Positioning a cell within a microfluidic device necessitates a strategy to move the cell about the
device without perturbing the analyte of interest in the cell. While a large number of LOC strategies
exist to manipulate cells, few have been successfully combined with electrophoretic separation. The
most popular and successful strategy is hydrodynamic flow since it is easily accomplished and can be
combined with the analysis of any analyte with minimal to no alterations in cellular physiology.
McClain et al. and Wu et al. utilized hydrodynamic flow to position leukemic cells prior to analysis;
while Kelparnik and colleagues used a negative pressure to load cardiac myocytes onto a device.49, 68, 69
Cell positioning using optical tweezers was successfully integrated with electrophoretic analysis by
both Anselmetii and Lilge’s groups, although optical tweezers are inherently low in throughput. 70-73
Electrophoretic/electroosmotic-driven movement has been employed by Fang and collaborators.74-76
This strategy is limited to analytes not altered by the application of an electric field to the cells,
typically DNA, RNA, and some proteins.
After movement through the microfluidic channels, the cell must be positioned near the entry to
the separation channel and lysed. Positioning the cell by entrapment at a flow restriction such as a
weir or channel constriction has been accomplished.71-73, 77 Fang and colleagues have used nonspecific
adhesion to the channel wall while Wu et al. captured a cell between two valves prior to lysis and
analysis.69, 74-76 Cell immobilization also facilitates the exchange of a physiologic buffer with a lysis,
reaction, or electrophoretic buffer, or permits selective application of stimuli to the immobilized cell.
The caveat is that cell immobilization greatly reduces throughput to rates of 25 cells/hour or slower.
An elegant solution which avoids this disadvantage was developed by Ramsey and colleagues.49 Cells
flowed through a field-free channel under a hydrodynamic force until they entered a channel region
possessing both AC and DC electric fields plus an inflow of detergent. Cells were lysed and their
contents immediately steered into a separation channel. This continuous flow of cells permitted
analysis rates up to 15 cells/min.
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Since cells must be moved to a predetermined location near or into a separation channel,
microfluidic-based, electrophoretic separations of single cells have been limited to cells that are
mobile, i.e. not attached to a surface. Most investigators have focused on blood cells or their leukemic
counterparts since these cells growth naturally without adhesion to a surface.49, 69, 72, 74-76 The contents
of cells that grow attached to a surface have been separated in a microfluidic device, but only after first
stripping the cells from their growth surface. For example, Sun and Yin measured reactive oxygen
species in single cells of a liver carcinoma line after surface detachment.77 Kleparnik and Horky
measured DNA fragmentation in disaggregated cardiac myocytes.68
Until new strategies are
developed, the requirement to move and pre-position a cell near or within a channel limits LOC-based
electrophoretic separations of single cells to those that are nonadherent or are detached from their
growth substrate.
3.3. On-chip lysis and separation technologies.
Both chemical and electrical lysis of cells has been successfully mated with electrophoretic
analysis of the contents of single cells. Chemical lysis alone typically requires several tenths of a
second to many seconds.71, 72, 77 Cell lysis in less than 33 ms has been achieved by McClain et al. by
pairing electrical and chemical lysis.49
A wide range of strategies for cell lysis have been
demonstrated within microfluidic channels, and it is expected that many of these will be combined
with the separation of the contents of a single mammalian cell in the future.23, 24, 29
A variety of different analytes from single cells have been successfully separated by
electrophoresis in an LOC format.
As described above, reactive oxygen species and DNA
fragmentation have been measured at the single-cell level using fluorescent indicators.68,
74-77
Fluorescently labeled amino acids were detected by Wu and colleagues while Munce et al. and
McClain et al. measured the metabolism of esterified dyes.49, 69, 72 Glutathione has been quantified in
single cells by Fang and coworkers.74,
75
Proteins linked to a green fluorescent protein have been
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detected in single insect cells, although not in single mammalian cells.73 These demonstrations suggest
that there are no inherent barriers to the microfluidic-based separation of cellular contents and the
ultimate range of analytes will be as broad as that for capillaries.
LOC-based separations have been shown to offer a greatly enhanced rate of analysis compared
to capillary-based measurements with a throughput greater than 10 cells per minute demonstrated by
Ramsey’s group.49 This enhanced throughput compared with capillary systems was primarily due to
the faster exchange of buffer around the cell prior to lysis and the use of shorter separation channels.
Additional speed enhancements were gained by performing serial separations of multiple cells within
the same channel. Arrays of channels will permit the separation of many cells in a parallel manner as
illustrated by Munce et al.72 The incorporation of cell loading strategies and analyte reactions on-chip
described by Wu et al. can be expected to provide further speed benefits.69 Although in its early
stages, LOC-based electrophoretic separation of single-cell contents may enable increased adoption of
this powerful technique by providing a tool for automated, high-throughput separations.
4. Indicator-based analyses of single, mammalian cells on-chip
4.1. Current state of fluorescence-based indicators for single-cell analysis.
Fluorescence microscopy of single cells has long been a valuable tool for cell biologists. A
wide array of fluorescent probes or indicators are now available to investigate a plethora of cellular
parameters including gene expression, protein synthesis and degradation, protein activity, and
metabolite synthesis and degradation.78 Small organic dyes such as fluorescein, rhodamine and their
derivatives have long been used to tag and track proteins. Modified versions of these molecules are
used routinely as sensors for ions such as Ca2+, Mg2+, and Zn2+.79, 80 Fluorescent proteins such as green
fluorescent protein, red fluorescent protein, and their variants have revolutionized the study of single
cells by enabling genetic fusions of these fluorophores with other proteins to create a fluorescent
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protein fully synthesized within the cell.78 Transfection of the DNA for these fluorescent hybrid
proteins into cells permits measurements of gene expression and protein behavior at the single-cell
level. Sensors based on the energy transfer between two fluorescent proteins have been developed to
monitor ion concentrations, nucleotide concentrations, enzymatic activity, protein-protein interactions,
and other attributes within cells. Newer probes such as quantum dots and the tetracysteine-biarsenical
probes are also proving their utility in the investigation of single cells.81, 82 These probes combined
with the imaging capabilities of fluorescence microscopy permit the analysis of single cells even when
the cell is in the midst of many other cells.
The combination of these powerful probes with
microfluidics will make increasingly important contributions to our understanding of the behavior of
the individual cell.
Fluorescent indicators have now been used in conjunction with microchip devices to analyze
both adherent and nonadherent single cells within an array of cells, to manipulate isolated single cells,
and to investigate the contents of disrupted single cells. Analyses of arrays of individual adherent cells
using indicators have been described extensively in the literature and will not be reviewed here.83-85
The generation of arrays of single nonadherent cells followed by analysis of the cells has been more
challenging than that for adherent cells. One reason is that the nonadherent cells are difficult to retain
at a known location during manipulation and interrogation of the array.
4.2. Electrical positioning of single, nonadherent cells for on-chip analysis.
Nonadherent cells have been arrayed by a variety of electrical methods and their behavior
analyzed using fluorescent indicators. Chief among the trapping methods is dielectrophoresis (DEP)
which confines cells via their inducible electric dipole in a potential well created by an electric field
gradient.86-90 Arrays of electrodes on silicon or glass chips can stably trap cells even in the presence of
a fluid stream. Recently Voldman and Taff developed a scalable array for DEP with the number of
electrical connections to the chip increasing as the square root of the single-cell trapping sites.89 Single
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cells in these arrays were analyzed for their ability to react with different fluorescent Cell-Tracker dyes
which covalently label intracellular proteins. Voldman and colleagues also used DEP traps to measure
calcein-AM uptake and esterase activity in single cells.90 A system utilizing electrophoresis rather
than DEP to place cells at gold electrodes was developed by Toriello and colleagues.91 In this system,
cell adhesion to the electrode was enhanced by prior thiolation of the cells, thus enabling the cells to
remain localized in the presence of fluid flow. While the fabrication process was simpler than that for
the DEP traps, the number of electrodes was proportional to the number of independently addressable
array sites. The uptake of Cell-Tracker dyes as well as the intracellular free Ca2+ concentration was
measured in single cells on the array using fluorescence microscopy.
4.3. Flow-based positioning of single cells on-chip for analysis.
Microfluidic strategies to array nonadherent cells have the advantage of simplicity compared to
electrical methods since electrical connections are not needed. However, the ability to controllably
place and remove each cell in an array is generally sacrificed in microfluidics.
Two different
microfluidic strategies have been combined with the analysis of indicators in single cells. In the first,
single or arrays of weirs or dams are used to entrap cells as they move through a fluidic device either
under hydrodynamic or electroosmotic forces.92-98 Cell entrapment occurs at constrictions within the
fluid flow path that narrow to less than the size of the cell. Cells are then held in place against the
surrounding rigid support by hydrodynamic or electric forces. In the second strategy, single cells are
loaded into individual depressions or wells on a surface.99-102 These are regions of static or low flow
that shield the cell from nearby faster moving fluid streams. In addition, the wells form a gravitational
potential well that aids in filling the wells with cells. For both types of methods, the properties of
fluorescent probes have been assayed in single cells over time.
Weirs and Dams. Perhaps the most elegant version of the weir or dam strategy is that
developed by DiCarlo and colleagues.92 High density arrays of trapping sites that held either single or
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multiple cells were constructed. The cells were loaded with a viability indicator and the metabolism of
that indicator followed over time. Since the cells were at known locations determined by the trapping
sites, large numbers of single cells could be easily studied to yield insight into population dynamics. A
number of other applications of docking sites and weirs have demonstrated the potential for the
integration of multiple biologic steps on one device.94, 96-98 Van den Berg and collaborators followed
apoptosis in docked cells after applying an electrical field to initiate programmed cell death. 96 Yang
and colleagues developed an integrated device to trap cells and then expose the trapped cells to a
gradient of agonist concentration.94, 98 Using this strategy, it was possible to rapidly to determine the
threshold of agonist needed to increase the intracellular Ca2+ concentration in cells. A version of the
dam strategy has also been employed to examine the exchange of molecules through gap junctionconnected cells.93 In this case two cells were trapped at the entry of opposing, but nearby, fluidic
channels which placed the two trapped cells in physical contact. A fluorescent dye was then observed
to move from one cell to the other. These applications demonstrate many of the advantages when
existing cell assays are integrated onto a microchip format.
These assets include integration of
different washing and cell handling steps, precise delivery of reagents to cells, higher throughput
derived from performing parallel assays, and new functionalities enabled by the microchips.
Microwells. The microwell format to trap and then analyze single, nonadherent cells on-chip
is exemplified by the recent work of Deutsh and colleagues.99 High density arrays of hemispherical
cavities were fabricated on a glass surface and loaded with cells. The cells remained in place during a
variety of wash and cell-loading steps. In addition the cells could be fixed within the microwells to
enable assays such as antibody-based staining of intracellular antigens. Alternatively, cells were lysed
within the microwells leaving their nuclei available for analysis within the microwell.
A
microfabricated platform composed of micron-size wells and simple fluidics based on this technology
is now commercially available (LiveCell Array™, NUNC). The device is being marketed with a series
of reagents and protocols optimized for carrying out cell-based assays on the array. A similar strategy
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has been described using SU-8 patterned on a coverslip to create wells for trapping stem cells whose
differentiation could be followed by virtue of their stable localization.103 A variety of other methods
have been demonstrated to construct microwells in materials such as PDMS or cross-linked PEG.100, 101
Most of these methods have not been combined with subsequent assays on-chip, but the potential
clearly exists for the use of these microwell-based arrays for many types of single-cell analyses. A
clear advantage of these microwell assays is the simplified fabrication process relative to that of the
docking or weir strategy. Wheeler et al. utilized a hybrid version of the docking/microwell methods to
trap and analyze a single cell.102 In this report the microwell was formed by a cavity in the side of the
channel wall. Small drain channels in either side of the cavity stabilized the fluid stream and assisted
in retaining the cell, but did not subject the cell to the pressure drop generally present at a weir or dam.
While on the microchip, a cell was loaded with a calcium-indicator dye, washed and exposed to stimuli
or inhibitors. As with the weir and dam strategies, clear advantages arise for cell manipulation,
throughput, and integrated functions.
5. On-chip analysis of perforated or encapsulated single cells
A strength of microfluidics is the ease with which small reaction volumes are partitioned and
manipulated. Individual cells have been combined with LOC devices to create confined cell extracts
or lysates for biochemical reactions and analyses. Gao et al. demonstrated a novel technique to
segregate the enzymatic reactions of one perforated cell from another as the cells moved through a
microfluidic channel.104 Chemical permeabilization of the cells’ membranes permitted diffusion of
small molecules into and out of the cell with retention inside the cell of large biomolecules such as
proteins. When hydroquinone, a small molecule substrate for neutrophil intracellular peroxidase, was
introduced into the solution containing the cells, zones of the product benzoquinone that surrounded
each perforated cell were detected electrochemically. The strength of this method is that cellular
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reactions utilizing membrane-impermeable substrates can be assayed.
A limitation is the
nonphysiological conditions required, i.e. membrane permeabilization, and the difficulty in measuring
the concentrations of the substrate and product in and around the cell at the time of the reaction.
Ocvirk et al. developed a single-cell biochemical assay for β-galactosidase by lysing cells as they
flowed through a mixing region containing a lysis buffer doped with a fluorogenic substrate for βgalactosidase.105 When cells possessed β-galactosidase, the reaction products from individual cells
were detected as migrating bands of fluorescence. The strengths and limitations of this method are
similar to that of the prior study. In addition, the denaturing effects of the lysis buffer may compromise
the activity of many enzymes. The above formats do have the potential for fast serial analysis of
cellular enzyme activities; however, the ultimate throughput will be limited by the width of the product
zone around each cell or cell lysate.
Partitioning by encapsulation of cells in picoliter-volume droplets or immiscible fluids has been
used to perform biochemical assays of single cells while minimally diluting cellular reactants. These
strategies have the advantage that the volume occupied by an enzymatic product is physically limited
and not broadened by diffusion and hydrodynamic flow as in the prior methods.
However, the
detection methods coupled to these strategies are limited to those compatible with the encapsulated cell
and are typically light-based techniques. Irmia et al. described a format to create liquid droplets
surrounded by air.106 Each droplet contained a single cell loaded with an indicator dye in a physiologic
buffer.
The droplet was then fused with a bead of lysis solution via on-chip thermopneumatic
actuators. The resultant cell lysate was confined to a 50 pL final volume. Fluorescence measurements
of the indicator were used to estimate cellular uptake of the dye and actin content in the lysed cell, but
the approach can potentially be extended to other assays.
Shortcomings of this device are the
complexity of manufacture and difficulties in capturing a cell.
Using laser trapping, He et al.
encapsulated single cells inside an aqueous droplet suspended in an immiscible oil.107 A second laser
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was used to lyse the cell within the droplet in the presence of a fluorogenic substrate of βgalactosidase.
The generation of fluorescent product within the droplet was used to follow the
enzymatic reaction. The technique should enable individual cells or organelles to be sorted from a
population so that selective biochemical assays can be performed. Practical drawbacks include the low
throughput resulting from laser trapping/positioning, and the significant costs from the multiple lasers
used to carry out the procedure. Tan et al. have recently reported a droplet-based microfluidic device
to encapsulate single cells in phospholipid vesicles.108 Droplets containing single cells were generated
when an aqueous stream surrounded by an immiscible oil solution was directed into an expanding
nozzle. Phospholipids in the oil solution were forced to assemble around the aqueous droplet and cell
by dissolution of the oil in an ethanol/water mixture. Single encapsulated cells were then assayed for
mitochondrial function using a fluorescent indicator.
This method has the potential for high-
throughput assay of cellular functions provided that the oil and ethanol/water exposure do not perturb
the cellular properties of interest.
6. On-chip analysis of single cells in microengineered environments
6.1. Overview of traditional methods.
Established methods that allow biologists to manipulate the environment around individual
cells suffer severe limitations due to their poor spatial resolution and imprecision. For example,
studies of cellular responses to a chemical gradient have been hampered by the ability to shape the
gradient in time and space.
Conventional pipet-based approaches which generate a gradient by
diffusion from a point source provide only the most rudimentary control of the temporal-spatial aspects
of chemical signals in the vicinity of a cell.109 Another case in point involves investigations of forces
exerted by cells on their growth substrate as the cells migrate. To measure these forces, traction force
microscopy is performed by measuring the deformation of a flexible, unpatterned polymer substrate as
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cells attach or migrate over the pliable surface.110, 111 These studies have provided important insights
into the mechanisms of cell adhesion and chemotaxis; nevertheless, they are generally semiquantitative in nature and lack the sensitivity to measure the forces exerted by many cell types. In
contrast, the technical progress made possible by microengineering now enables exquisite, quantitative
control of the cellular environment on the micron scale.
Microfluidic platforms can generate
geometric and time varying alterations in the composition of extracellular fluid and are proving to be
powerful tools in the study of biological responses to spatial and temporal cues. The recent advent of
mechanosensors constructed on the dimensions of single cells makes it possible to perform direct
measurements of the forces involved in single-cell adhesion and motility. The control of numerous
aspects of the cellular microenvironment made possible by LOC devices will have tremendous utility
in almost all areas of single cell biology from stem cell differentiation and neuronal regeneration to
cancer metastasis.
6.2. Control of the fluidic microenvironment.
Local control.
The ability of microfluidic systems to present highly defined spatial and
temporal cues in solution to individual cells is without peer. The versatility of modern designs allows
ready bulk exchange of extracellular fluid in the near vicinity of individual cells, as well as more
refined experimental manipulation involving stepwise variations in concentration using simple laminar
flow streams or application of continuous gradients over micron dimensions. Importantly, all of these
manipulations can be varied easily with time. For example, Peterman et al. used a silicon-based device
for application of a chemical stimulus to localized regions of an open cell chamber.112 Cells were
cultured in the vicinity of apertures connected to microfluidic channels below the cell attachment
surface and electroosmotic pumping was used to meter fluid flow through one or more 5-µm apertures.
This device was used to pulse minute quantities of a bradykinin onto single cells. The investigators
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demonstrated repeated stimulation of individual cells adjacent to the aperture using a Ca2+-sensitive
fluorescent dye to measure changes in the cells’ intracellular Ca2+ concentration. Devices such as
these to control the bulk composition of fluid surrounding a cell over time have many potential
applications in biology, particularly when applied reagents are expensive or in short supply. Nielson
and Shear described a unique approach to perform a similar type of experiment.113 Cells were cultured
on a Mylar membrane that served as a barrier between two stacked laminar-flow channels: one
containing cells in culture and the other used as a flow reservoir containing a biologically active
reagent. A focused laser was used to create pores of only a few microns diameter in the Mylar just
upstream of desired cellular targets. Each pore acted as an entry point for the reagent to bathe a
downstream cell. Membrane ablation was performed in the presence of living cells so that sub-regions
of cells were selectively loaded with fluorescent indicator dyes flowing through the pores. Analysis of
dye movement throughout a single cell was then performed. The investigators also demonstrated a
clever method to dam the agonist stream by photo-crosslinking a protein plug over the pore. This
procedure provides a new capability for gating reagent exposure to cells without requiring a complex,
prefabricated microfluidic network.
Laminar flow.
Laminar flow in microfluidic devices can be used to vary the spatial
concentration of soluble factors in a highly discrete manner. An elegant demonstration of the power of
carefully controlled biological experimentation combined with an LOC-generated gradient comes from
the work of Sawano et al.114 These investigators used laminar flow composed of two merging fluid
streams to expose selective regions of a cell to the soluble hormone epidermal growth factor. This
hormone initiates a signaling pathway involving tyrosine phosphorylation of proteins and the
activation of Ras family G proteins critical to cell growth and survival. 115 Single cells genetically
engineered to express fluorescent indicators of either tyrosine phosphorylation or Ras activation were
cultured in the microfluidic device and were imaged during exposure to the hormone. Biasing the
streams forming the laminar flow with respect to the hormone concentration enabled the investigators
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to selectively expose only a portion of the downstream cell to the hormone. They convincingly
demonstrated that receptor signaling remained localized to the region of the cell exposed to the
hormone under normal conditions. However, in cells over-expressing the hormone’s receptor, as
occurs in a number of tumors, the signal spread throughout the cell. This study has significant
implications for the molecular mechanisms of disordered signal transduction in cancer. A similar
approach was used by Takayama et al. to study the subcellular movement of mitochondria and changes
in cytoskeletal structure.116 The investigators used a laminar flow (comprised of two merging streams)
to label the mitochondria in each half of a single cell with a different fluorescent dye. The mixing of
the two populations of the fluorescently labeled mitochondria was then measured over time. They also
showed disruption of actin filaments in selected regions of the cell after treatment with a membranepermeable inhibitor of actin polymerization. The above examples suggest the vast potential for the use
of multiple laminar streams in a microfluidic channel to deliver soluble molecules to selected cellular
regions.
Gradients. A major technical innovation in single-cell analysis enabled by microfluidics is the
generation of concentration gradients of soluble molecules.24, 85, 117-122 To produce a gradient, a series
of flow streams are brought together. Sequential segregation and re-addition of the streams gives rise
to a smooth gradient across a fluidic channel. This gradient can be modified spatially and temporally
by control of upstream differences in concentration or flow rates. A number of investigations have
paired these microfluidic gradient generators with microscopic examination of single cell motility to
study chemotaxis.117, 123-126 Recently, novel devices for gradient generation have been reported. Jeon’s
group has developed microfluidic systems capable of producing temporal and spatial gradients in the
concentration of soluble molecules, although this multifunctional system has not yet been used for cellbased experiments.127, 128 This group has also recently described the application of spatial gradients in
a microfluidic system for the study of stem cell differentiation.129 Proliferation rather than chemotaxis
was measured at different concentrations of growth factors. Similarly Thompson and colleagues
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measured gene expression in single cells in response to different concentrations of inflammatory
cytokines.130 Pihl et al. has described a gradient generating device combined with an open chamber
enabling a single patch-clamped cell to act as a sensor in the fluid streams.131
Testing of
pharmacologic inhibitors using electrophysiology readouts of voltage- and ligand-gated channels in the
patched cell were used to demonstrate the potential of the device for drug screening. Folch’s group has
also recently reported measurement of chemotaxis in chemical gradients without subjecting the cells to
fluid flow.132,
133
The devices utilized diffusive mixing of one stationary fluid with another. The
absence of flow insures that cell secreted factors are not removed and eliminates cell perturbations that
may result from the shear forces of moving fluids. The downside is that the shape of the gradient can
no longer be actively controlled in time and space. These gradient generating chips provide some of
the clearest examples of the benefits of microfluidics to biomedical research. Most of the single-cell
analyses now performed routinely with these devices were simply not possible without the aid of these
chip-based technologies.
6.3. Microengineered, 3-dimensional substrates.
Cells interact with their physical environment through focal adhesions, macromolecular
assemblies on the cell surface that mediate the cell’s contact with the extracellular matrix (ECM).134
Studies of focal adhesions and cell motility have been performed using microfabrication techniques to
improve upon the substrates used in traction force microscopy experiments. Arrays of micromachined
cantilevers enabled Galbraith and Sheetz to measure subcellular forces of single cells as each cell
migrated across the cantilevers.135, 136 Deflections of the cantilevers embedded in the surface of the
silicon-based substrate were measured by microscopic imaging with 0.02 µm resolution and used to
calculate the forces applied by the cell to the cantilever. The results demonstrated that the majority of
forward forces were generated in the rear or trailing region of a migrating cell. Balaban et al. also
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measured the forces generated by a cell as the cell migrated across a PDMS membrane patterned with
arrays of elevated dots. The degree of distortion of the array pattern was used to determine the forces
exerted by the cell.137
By combining this analysis with the measurement of GFP-tagged focal
adhesions in the cell, the forces generated at individual focal adhesions were calculated. Tan et al.
performed similar studies following cells moving across a bed of closely spaced posts fabricated in
PDMS.138 The lateral deflection of the posts was used to measure the force exerted by the cell on that
post. The investigators were able for the first time to correlate the subcellular force distribution with
cell shape and estimate multidirectional forces across the entire cell surface. A similar strategy was
used by Tanaka et al. to study contractile forces of cultured cardiac muscle cells attached to PDMS
pillars.139 Displacement of pillars caused by oscillatory contraction of single cardiomyocytes attached
between the pillar and a substrate could be correlated with the applied force with subsecond temporal
resolution. A more sophisticated MEMS device incorporating electrical and mechanical components
has been reported by Lin et al. for measuring cardiomyocyte contraction.140 A single cell was attached
to a micron-scale strain gauge and gauge deformation was converted to an electrical signal upon cell
contraction and relaxation. Similar to the PDMS pillars described above, the device permitted force
measurements to be performed in real-time. Li et al. have implemented an acoustic wave sensor on a
microfluidic chip to analyze cell contractility.141 This novel method relies on perturbations of standing
waves in a quartz crystal due to variations in the stiffness (i.e. contractile state) of a cardiomyocyte
attached to the crystal. Unfortunately, the five second temporal resolution of the analysis step is
greater that the oscillatory behavior of the cell limiting its value for real-time measurements. The
above studies demonstrated that many cells such as fibroblasts generate forces of the order of ten’s of
nanonewtons. Not unexpectedly, cardiac cells are the strongest producing peak forces of the order of a
few micronewtons. Although not yet implemented, an obvious application exists for the LOC devices
discussed in this paragraph as effective bioassays for drug testing, particularly for cardiovascular
disorders, wound healing or other states requiring cell movement or motion.
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7. Alternative imaging modalities for on-chip analysis of single, mammalian cells
Molecular imaging is an emerging field that strives to reveal the presence or activity of a
biological target at the molecular level. The prominent tool for molecular imaging remains the optical
microscope and corresponding fluorescent indicators, but the field is expanding towards a diverse
collection of imaging modalities.142 Tamaki et al. have used a microfluidic cell culture platform to
analyze single cells by scanning thermal lens microscopy (TLM).143 These investigators were able to
perform label-free, single-cell detection of cytochrome C due to its strong visible absorbance and
relatively high concentration in cells. Mitochondrial release of cytochrome-C into the cytosol was
measured in real-time as a single cell was exposed to an apoptosis-inducing agent. The microfluidic
platform provided a controlled cell culture environment over several hours permitting the performance
of reproducible analyses. Raman spectroscopy of single cells on a PDMS microfluidic chip has also
been accomplished.144 The oxygenation cycle of hemoglobin in a red blood cell was monitored in realtime as the cell was exposed to various buffer exchanges. Both of these examples demonstrate the
ability of chip-based devices to control the extracellular milieu of cells as well as to mate with diverse
analytical tools.
8. On-chip analysis of RNA from single mammalian cells
Microarray analysis is now an established tool to assess transcription levels in a population of
cells.145, 146 A disadvantage of the technique is the requirement for significant amounts of high quality
RNA to achieve acceptable sensitivity and reproducibility. While tissue samples can generate the
necessary amounts of RNA species, the adequacy of that RNA is compromised by the admixture of
subpopulations of various cell types.6, 7 In addition, the quantity of RNA harvested from a single cell,
estimated to be approximately 0.1–1.0 pg, is not sufficient for standard RNA extraction procedures.7
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Amplification of the target nucleotides is therefore required, most commonly via the reversetranscriptase polymerase-chain reaction (RT-PCR).7, 147 This effort entails collection of single cells by
microaspiration or laser microdissection followed by RNA extraction and amplification. Each step is
plagued by the potential for sample loss or contamination making this task problematic and labor
intense.
Microfluidic devices are ideal for the analysis of single-cell RNA by virtue of their small
reaction volumes, low-loss sample handling, and the potential for integrating the necessary steps in an
automated format. Performance of RT-PCR on-chip has been widely reported in the literature, often
using bacteria as the sample source. 148-152 To date, however, few reports describe the use of LOC
technologies for mRNA purification and amplification from single mammalian cells.
Two
collaborative groups have led the effort in the development of integrated devices to perform RT-PCR
for expression profiling of individual mammalian cells.3,
153-156
The laboratories of Pilarski and
Backhouse reported off-chip RT-PCR of transcripts from single myeloma cells followed by on-chip
electrophoretic separation and fluorescence detection of the DNA product.155 The integration of this
on-chip separation step with an RT-PCR microfluidic device developed by the group should enable a
fully chip-based method in the future.156
Anderson and Quake demonstrated an integrated chip
capable of purifying mRNA from a single cell.153 Valves fabricated using multilayer soft lithography
permitted a number of different functions to be performed on-chip including cell isolation and lysis,
reagent metering and mixing, and affinity capture of RNA onto beads. The RNA was then amplified
and analyzed off-chip. In a second collaborative effort, Anderson and Quake also used a PDMS-based
device to purify mRNA and synthesize cDNA from single cells on an integrated LOC system.154 The
functions of cell capture, cell lysis, mRNA isolation, cDNA synthesis and purification were
reproducibly performed on samples of 1-4 cells. Moreover, these investigators have described other
PDMS-based devices capable of up to 72 RT-PCR reactions performed in parallel utilizing amounts of
mRNA equivalent to that obtained from single cells.3
This demonstration suggests that higher-
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throughput, single-cell nucleic acid analysis will be feasible in the near term. One caveat to the work
reported here is that the on-chip PCR reactions used to demonstrate the technology used highabundance targets. Improved sensitivity to achieve successful results from low abundance targets will
be a necessary goal for widespread applicability of single-cell PCR on-chip.
9. Potential for the future
In the current review, we have endeavored to illustrate both the challenges and potential of
LOC devices in the analysis of single mammalian cells. To date these advanced, miniaturized tools
have yet to be fully embraced by the biology community, but their adoption is increasing.157 Since the
biologist is focused on the generation of new data, rather than the advance of new technology, a novel
technique that provides the same data obtained by traditional and time-tested means will not generate
widespread excitement among biologists unless it offers significant advantages. Microarrays for
genomic and proteomic studies and microfluidic devices for biochemical assays have been adopted by
virtue of their demonstrated high-throughput capacity, ease of use and favorable cost/benefit ratio. In
many instances, the potential for enhancing cell-based assays with LOC devices is present, but not
fully undemonstrated. The strongest driving force for adoption comes about when a new technology
enables biologic discovery.
LOC devices for single-cell analysis offer innovative technological
opportunities for such discovery to take place; however, the potential for these devices can only be
realized if cell-based assays are developed and optimized in a collaborative effort between the
technologist and the biologist. The real challenge in achieving this outcome is to foster synergistic
collaborations at the interface of technology and biology. These types of collaborations are certain to
lead to technological breakthroughs that dramatically advance the life sciences.
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Acknowledgements
This work was supported by NIH (EB004436 and EB004597).
References
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(13)
(14)
(15)
(16)
(17)
(18)
(19)
(20)
(21)
(22)
(23)
(24)
(25)
(26)
(27)
(28)
(29)
(30)
(31)
(32)
(33)
(34)
(35)
(36)
Ferrell, J. E.; Machleder, E. M. Science 1998, 280, 895-896.
Huang, T. Y.; Chu, T. F.; Chen, H. I.; Jen, C. J. FASEB J. 2000, 14, 797-804.
Marcus, J. S.; Anderson, W. F.; Quake, S. R. Anal. Chem. 2006, 78, 956-958.
Negulescu, P. A.; Shastri, N.; Cahalan, M. D. PNAS 1994, 91, 2873-2877.
Teruel, M. N.; Meyer, T. Science 2002, 295, 1910-1912.
Fink, L.; Kwapiszewska, G.; Wilhelm, J.; Bohle, R. M. Exp. Toxicol. Path. 2006, 57, 25-29.
Ginsberg, S. D. Methods 2005, 37, 229-237.
Berridge, M. J.; Bootman, M. D.; Roderick, H. L. Nat. Rev. 2003, 4, 517-529.
Fink, C. C.; Meyer, T. Curr. Op. Neurobiol. 2002, 12, 293-299.
Lewis, R. S. Biochem. Soc. Trans. 2003, 31, 925-999.
Bodey, B. Exp. Opin. Biol. Ther. 2002, 2, 371-393.
Lodish, H.; Berk, A.; Zipursky, L. S.; Matsudaira, P.; Baltimore, D.; Darnell, J., Eds.
Molecular Cell Biology, 4th ed.; W. H. Freeman: New York, 2000.
Zhang, Z.; Krylov, S. N.; Arriaga, E. A.; Polakowski, R.; Dovichi, N. J. Anal. Chem. 2000, 72,
318-322.
Reddig, P. J.; Juliano, R. L. Cancer Metastasis Rev. 2005, 24, 425-439.
Seidl, J.; Knuechel, R.; Kunz-Schughart, L. A. Cytometry 1999, 36, 102-111.
Li, H.; Sims, C. E.; Wu, H. Y.; Allbritton, N. L. Anal. Chem. 2001, 73, 4625-4631.
McNeil, P. L.; Steinhardt, R. A. Annu. Rev. Cell Dev. Biol. 2003, 19, 697-731.
Andersson, H.; van den Berg, A. Sensors Actuators B 2003, 92, 315-325.
Andersson, H.; Van den Berg, A. Curr. Op. Biotechnol. 2004, 15, 44-49.
Andersson, H.; Van den Berg, A. Proc. IEEE 2005, 5718, 1-12.
Breslauer, D. N.; Lee, P. J.; Lee, L. P. Mol. Biosyst. 2006, 2, 97-112.
Dittrich, P. S.; Manz, A. Nat. Rev. 2006, 5, 210-218.
Dittrich, P. S.; Tachikawa, K.; Manz, A. Anal. Chem. 2006, 78, 3887-3908.
El-Ali, J.; Sorger, P. K.; Jensen, K. F. Nature 2006, 442, 403-411.
Lu, X.; Huang, W.-H.; Wang, Z.-L.; Cheng, J.-K. Analytica Chimica Acta 2004, 510, 127-138.
Toner, M.; Irimia, D. Annu. Rev. Biomed. Eng. 2005, 7, 77–103.
Vilkner, T.; Janasek, D.; Manz, A. Anal. Chem. 2004, 76, 3373-3386.
Walker, G. M.; Zeringue, H. C.; Beebe, D. J. Lab Chip 2004, 4, 91-97.
Yi, C.; Li, C.-W.; Ji, S.; Yang, M. Analytica Chimica Acta 2006, 560, 1-23.
Shapiro, H. M. Practical Flow Cytometry, 4th ed.; Wiley-Liss: New York, 2003.
Huh, D.; Gu, W.; Kamotani, Y.; Grotberg, J. B.; Takayama, S. Physiol. Meas. 2005, 26, R73–
R98.
Gerdts, G.; Luedke, G. J. Microbiolog. Meth. 2006, 64, 232– 240.
Wheeler, M. B.; Rutledge, J. J.; Amy Fischer-Brown, A.; VanEtten, T.; Samantha Malusky, S.;
Beebe, D. J. Theriogenology 2006, 65, 219–227.
Bonetta, L. Nat. Meth. 2005, 2, 785-795.
Minerd, J. Scientist 2005, 28-29.
Leary, J. F. Cytometry 2005, 67, 76-85.
31
PRIVILEGED DOCUMENT FOR REVIEW PURPOSES ONLY
(37)
(38)
(39)
(40)
(41)
(42)
(43)
(44)
(45)
(46)
(47)
(48)
(49)
(50)
(51)
(52)
(53)
(54)
(55)
(56)
(57)
(58)
(59)
(60)
(61)
(62)
(63)
(64)
(65)
(66)
Erickson, D.; Li, D. Analytica Chimica Acta 2004, 507, 11-26.
Preckel, T.; Luedke, G.; Chan, S. D. H.; Wang, B. N.; Dubrow, R.; Buhlmann, C. JALA 2002,
7, 85-89.
Battrell, F.; Hayenga, J.; R., B.; Morris, C.; Graham, P.; Kesler, N.; Lancaster, C.; Schulte, T.;
Weigl, B.; Saltsman, P.; M., S., Eds. Cell lysing and cytometry in an integrated microfluidic
card system; Kluwer Academic Publishers: Dordrecht, 2002.
Farinas, J.; Chow, A. W.; Wada, H. G. Anal. Biochem. 2001, 295, 138-142.
Lancaster, C.; Kokoris, M.; Nabavi, M.; Clemmens, J.; Maloney, P.; Capadanno, J.; Gerdes, J.;
Battrell, C. F. Methods 2005, 37, 120–127.
Buhlmann, C.; Preckel, T.; Chan, S.; Luedke, G.; Valera, M. J. Biomolec. Tech. 2003, 14, 119–
127.
Chan, S. D. H.; Luedke, G.; Valer, M.; Buhlmann, C.; Preckel, T. Cytometry 2003, 55, 119–
125.
Givan, A. L. Flow Cytometry First Principles, 2nd ed.; Wiley-Liss: New York, 2001.
Blankenstein, G.; Larsen, U. D. Biosensors Bioelectronics 1998, 13, 427-438.
Huang, M.-C.; Afromowitz, M.; van den Engh, G.; Weigl, B. H.; Yager, P. SPIE 1998, 3256,
178-185.
Wood, D. K.; Oh, S.-H.; Lee, S.-H.; Soh, H. T.; Cleland, A. N. Appl. Phys. Lett. 2005, 87,
184106.
Dittrich, P. S.; Schwille, P. Anal. Chem. 2003, 75, 5767-5774.
McClain, M. A.; Culbertson, C. T.; Jacobson, S. C.; Allbritton, N. L.; Sims, C. E.; Ramsey, J.
M. Anal. Chem. 2003, 75, 5646-5655.
Tung, Y.-C.; Zhang, M.; Lin, C.-T.; Kurabayashi, K.; Skerlos, S. J. Sensors Actuators 2004, 98,
356–367.
Gottwald, E.; Lahni, B.; Ludke, G.; Preckel, T.; Buhlmann, C. Biotechniques 2003, 35, 358367.
Kataoka, M.; Fukura, Y.; Shinohara, Y.; Baba, Y. Electrophoresis 2005, 26, 3025–3031.
Paklova, Z.; Vachova, L.; Valer, M.; Preckel, T. Cytometry 2004, 59A, 246-253.
Poulsen, C. R.; Culbertson, C. T.; Jacobson, S. C.; Ramsey, J. M. Anal. Chem. 2005, 77, 667672.
Wang, Z.; El-Ali, J.; Engelund, M.; Gotsæd, T.; Perch -Nielsen, I. R.; Mogensen, K. B.;
Snakenborg, D.; Kutter, J. P.; Wolff, A. Lab Chip 2004, 4, 372-377.
Cheung, K.; Gawad, S.; Renaud, P. Cytometry 2005, 65A, 124-132.
Gawad, S.; Schildb, L.; Renaud, P. Lab Chip 2001, 1, 76-82.
Sohn, L. L.; Saleh, O. A.; G. R. Facer, G. R.; Beavis, A. J.; Allan, R. S.; Notterman, D. A.
PNAS 2000, 97, 10687–10690.
Zhang, H.; Tu, E.; Hagen, N. D.; Schnabel, C. A.; Paliotti, M. J.; Hoo, W. S.; Nguyen, P. M.;
Kohrumel, J. R.; Butler, W. F.; Chachisvillis, M.; Marchand, P. J. Biomed Microdevices 2004,
6, 11-21.
Lee, G.-B.; Lin, C.-H.; Chang, G.-L. Sensors Actuators A 2003, 103, 165–170.
Fu, L.-M.; Yang, R.-J.; Lin, C.-H.; Pan, Y.-J.; Lee, G.-B. Anal. Chim. Acta 2004, 507, 163-169.
Wolff, A.; Perch-Nielsen, I. R.; Larsen, U. D.; Friis, P.; Goranovic, G.; Poulsen, C. R.; Kuttera,
J. P.; Telleman, P. Lab Chip 2003, 3, 22–27.
Kennedy, R. T.; Oates, M. D.; Cooper, B. R.; Nickerson, B.; Jorgenson, J. W. Science 1989,
246, 57-63.
Xue, Q.; Yeung, E. S. Anal. Chem. 1994, 66, 1175-1178.
Dovichi, N. J.; Hu, S. Curr. Op. Chem. Biol. 2003, 7, 603-608.
Woods, L. A.; Roddy, T. P.; Ewing, A. G. Electrophoresis 2004, 25, 1181-1187.
32
PRIVILEGED DOCUMENT FOR REVIEW PURPOSES ONLY
(67)
Kraly, J. R.; Jones, M. R.; Gomez, D. J.; Dickerson, J. A.; Harwood, M. M.; Eggertson, M.;
Paulson, T. G.; Sanchez, C. A.; Odze, R.; Feng, Z.; Reid, B. J.; Dovichi, N. J. Anal. Chem.
2006, 78, 5977-5986.
(68) Kleparnik, K.; Horky, M. Electrophoresis 2003, 24, 3778-3783.
(69) Wu, H. Y.; Wheeler, A. R.; Zare, R. N. PNAS 2004, 101, 12809-12813.
(70) Hellmich, W.; Greif, D.; Pelargus, C.; Anselmetti, D.; Ros, A. J. Chromatogr. A 2006, 1130,
195-200.
(71) Hellmich, W.; Pelargus, C.; Leffhalm, K.; Ros, A.; Anselmetti, D. Electrophoresis 2005, 26,
3689-3696.
(72) Munce, N. R.; Li, J.; Herman, P. R.; Lilge, L. Anal. Chem. 2004, 76, 4083-4989.
(73) Ros, A.; Hellmich, W.; Regtmeier, J.; Duong, T. T.; Anselmetti, D. Electrophoresis 2006, 27,
2651-2658.
(74) Gao, G.; Yin, X.-F.; Fang, Z.-L. Lab Chip 2004, 4, 47-52.
(75) Ling, Y.-Y.; Yin, X.-F.; Fang, Z.-L. Electrophoresis 2005, 26, 4759-4766.
(76) Sun, Y.; Yin, X.-F.; Ling, Y.-Y.; Fang, Z.-L. Anal. Bioanal. Chem. 2005, 382, 1472-1476.
(77) Sun, Y.; Yin, X.-F. J. Chromatogr. A 2006, 1117, 228-233.
(78) Giepmans, B. N. G.; Adams, S. R.; Ellisman, M. H.; Tsien, R. Y. Science 2006, 312, 217-224.
(79) Gonzalez, J. E.; Maher, M. P. Receptors Channels 2002, 8, 283-295.
(80) Moreton, R. B. Scanning Microsc. Suppl. 1994, 8, 371-390.
(81) Martin, B. R.; Giepmans, B. N. G.; Adams, S. R.; Tsien, R. Y. Nat. Biotechnol. 2005, 23, 13081314.
(82) Smith, A. M.; Ruan, G.; Rhyner, M. N.; Nie, S. Ann. Biomed. Eng. 2006, 34, 3-14.
(83) Bhadriraju, K.; Chen, C. S. Drug Discovery Today 2002, 7, 612-620.
(84) Jung, D. R.; Kapur, R.; Adams, T.; Giuliano, K. A.; Mrksich, M.; Craighead, H. G.; Taylor, D.
L. Crit. Rev. Biotech. 2001, 21, 111-154.
(85) Whitesides, G. M.; Ostuni, E.; Takayama, S.; Jiang, X.; Ingber, D. E. Annu. Rev. Biomed. Eng.
2001, 3, 335-373.
(86) Fuchs, A. B.; Romano, A.; Freida, D.; Medoro, G.; Abonnenc, M.; Altomare, L.; Chartier, I.;
Guergour, D.; Villiers, C.; Marche, P. N.; Tartagni, M.; Guerrieri, R.; Chatelain, F.; Manaresi,
N. Lab Chip 2006, 6, 121-126.
(87) Gascoyne, P. R.; Vykoukal, J. Electrophoresis 2002, 23, 1973-1983.
(88) Gonzalez, C. F.; Remcho, V. T. J. Chromatogr. A 2005, 1079, 59-68.
(89) Taff, B. M.; Voldman, J. Anal. Chem. 2005, 77, 87-94.
(90) Voldman, J.; Gray, M. L.; Toner, M.; Schmidt, M. A. Anal. Chem. 2002, 74, 3984-3990.
(91) Toriello, N. M.; Douglas, E. S.; Mathies, R. A. Anal. Chem. 2005, 77, 6935-6941.
(92) Di Carlo, D.; Aghdam, N.; Lee, L. P. Anal. Chem. 2006, 78, 4925-4930.
(93) Lee, P. J.; Hung, P. J.; Shaw, R.; Jan, L.; Lee, L. P. Appl. Phys. Lett. 2005, 86, 223902.
(94) Li, C.-W.; Yang, J.; Yang, M. Lab Chip 2006, 6, 921-929.
(95) Li, X.; Li, P. C. H. Anal. Chem. 2005, 77, 4315-4322.
(96) Munoz-Pinedo, C.; Green, D. R.; Van den Berg, A. Lab Chip 2005, 5, 628-633.
(97) Valero, A.; Merino, F.; Wolbers, F.; Luttge, R.; Vermes, I.; Andersson, H.; van den Berg, A.
Lab Chip 2005, 5, 49-55.
(98) Yang, M.; Li, C.-W.; Yang, J. Anal. Chem. 2002, 74, 3991-4001.
(99) Deutsch, M.; Deutsch, A.; Shirihai, O.; Hurevich, I.; Afrimzon, E.; Shafrana, Y.; Zurgila, N.
Lab Chip 2006, 6, 995-1000.
(100) Rettig, J. R.; Folch, A. Anal. Chem. 2005, 77, 5628-5634.
(101) Revzin, A.; Sekine, K.; Sin, A.; Tompkins, R. G.; Toner, M. Lab Chip 2005, 5, 30-37.
(102) Wheeler, A. R.; Throndset, W. R.; Whelan, R. J.; Leach, A. M.; Zare, R. N.; Liao, Y. H.;
Farrell, K.; Manger, I. D.; Daridon, A. Anal. Chem. 2003, 75, 3581-3586.
33
PRIVILEGED DOCUMENT FOR REVIEW PURPOSES ONLY
(103) Chin, V. I.; Taupin, P.; Sanga, S.; Scheel, J.; Gage, F. H.; Bhatia, S. N. Biotechnol. Bioeng.
2004, 88, 399-415.
(104) Gao, N.; Wang, W.; Zhang, X.; Jin, X.; Yin, X.-F.; Fang, Z.-L. Anal. Chem. 2006, 78, 32133220.
(105) Ocvirk, G.; Salimi-Moosavi, H.; Szarka, R. J.; Arriaga, E. A.; Andersson, P. E.; Smith, R.;
Dovichi, N. J.; Harrison, D. J. Proc. IEEE 2004, 92, 115-125.
(106) Irimia, D.; Tompkins, R. G.; Toner, M. Anal. Chem. 2004, 76, 6137-6143.
(107) He, M.; Edgar, J. S.; Jeffries, G. D. M.; Lorenz, R. M.; Shelby, J. P.; Chiu, D. T. Anal. Chem.
2005, 77, 1539-1544.
(108) Tan, Y.-C.; Hettiarachchi, K.; Siu, M.; Pan, Y.-R.; Lee, A. P. J. Am. Chem. Soc. 2006, 128,
5656-5658.
(109) Goodhill, G. J. Eur. J. Neurosci. 1997, 9, 1414-1421.
(110) Harris, A. K.; Wild, P.; Stopak, D. Science 1980, 208, 177-179.
(111) Oliver, T.; Dembo, M.; Jacobson, K. Cell Motility Cytoskeleton 1995, 31, 225-240.
(112) Peterman, M. C.; Noolandi, J.; Blumenkranz, M. S.; Fishman, H. A. PNAS 2004, 101, 99519954.
(113) Nielson, R.; Shear, J. B. Anal. Chem. 2006, 78, 5987-5993.
(114) Sawano, A.; Takayama, S.; Matsuda, M.; Miyawaki, A. Dev. Cell 2002, 3, 245-257.
(115) Edwin, F.; Wiepz, G. J.; Singh, R.; Peet, C. R.; Chaturvedi, D.; Bertics, P. J.; Patel, T. B. Meth.
Mol. Biol. 2006, 327, 1-24.
(116) Takayama, S.; Ostuni, E.; LeDuc, P.; Naruse, K.; Ingber, D. E.; Whitesides, G. M. Nature
2001, 411, 1016.
(117) Jeon, N. L.; Baskaran, H.; Dertinger, S. K. W.; Whitesides, G. M.; Van de Water, L.; Toner, M.
Nature Biotech. 2002, 20, 826-830.
(118) Biddiss, E.; Li, D. J. Colloid Interface Sci. 2005, 288, 606-615.
(119) Irimia, D.; Geba, D. A.; Toner, M. Anal. Chem. 2006, 78, 3472-3477.
(120) Wu, H.; Huang, B.; Zare, R. N. J. Am. Chem. Soc. 2006, 128, 4194-4195.
(121) Yang, M.; Yang, J.; Li, C.-W.; Zhao, J. Lab Chip 2002, 2, 158-163.
(122) Zhu, X.; Chu, L. Y.; Chueh, B.; Shen, M.; Hazarika, B.; Phadke, N.; Takayama, S. Analyst
2004, 129, 1026-1031.
(123) Irimia, D.; Liu, S.-Y.; Tharp, W. G.; Samadani, A.; Toner, M.; Poznansky, M. C. Lab Chip
2006, 6, 191-198.
(124) Lin, F.; Nguyen, C. M.-C.; Wang, S.-J.; Saadi, W.; Gross, S. P.; Jeon, N. L. Biochem. Biophys.
Res. Comm. 2004, 319, 576-581.
(125) Walker, G. M.; Sai, J.; Richmond, A.; Stremler, M.; Chung, C. Y.; Wikswo, J. P. Lab Chip
2005, 5, 611-618.
(126) Wang, S.-J.; Saadi, W.; Lin, F.; Nguyen, C. M.-C.; Jeon, N. L. Exp. Cell Res. 2004, 300, 180189.
(127) Chung, B. G.; Lin, F.; Jeon, N. L. Lab Chip 2006, 6, 764-768.
(128) Lin, F.; Saadi, W.; Rhee, S. W.; Wang, S.-J.; Mittal, S.; Jeon, N. L. Lab Chip 2004, 4, 164-167.
(129) Chung, B. G.; Flanagan, L. A.; Rhee, S. W.; Schwartz, P. H.; Lee, A. P.; Monuki, E. S.; Jeon,
N. L. Lab Chip 2005, 5, 401-406.
(130) Thompson, D. M.; King, K. R.; Wieder, K. J.; Toner, M.; Yarmush, M. L.; Ja yaraman, A. Anal.
Chem. 2004, 76, 4098-4103.
(131) Pihl, J.; Sinclair, J.; Sahlin, E.; Karlsson, M.; Petterson, F.; Olofsson, J.; Orwar, O. Anal. Chem.
2005, 77, 3897-3903.
(132) Abhyankar, V. V.; Lokuta, M. A.; Huttenlocher, A.; Beebe, D. J. Lab Chip 2006, 6, 389–393.
(133) Frevert, C. W.; Boggy, G.; Keenan, T. M.; Folch, A. Lab Chip 2006, 6, 849–856.
(134) Romer, L. H.; Konstantin, G. B.; Garcia, J. G. N. Circ. Res. 2006, 98, 606-616.
34
PRIVILEGED DOCUMENT FOR REVIEW PURPOSES ONLY
(135) Galbraith, C. G.; Sheetz, M. P. PNAS 1997, 94, 9114-9118.
(136) Galbraith, C. G.; Sheetz, M. P. J. Cell Biol. 1999, 147, 1313-1323.
(137) Balaban, N. Q.; Schwarz, U. S.; Riveline, D.; Goichberg, P.; Tzur, G.; Sabanay, I.; Mahalu, D.;
Safran, S.; Bershadsky, A.; Addadi, L.; Geiger, B. Nat. Cell Biol. 2001, 3, 466-472.
(138) Tan, J. L.; Tien, J.; Pirone, D. M.; Gray, D. S.; Bhadriraju, K.; Chen, C. S. PNAS 2003, 100,
1484-1489.
(139) Tanaka, Y.; Morishima, K.; Shimizu, T.; Kikuchi, A.; Yamato, M.; Okanobe, T.; Kitamori, T.
Lab Chip 2006, 6, 230-235.
(140) Lin, G.; Palmer, R. E.; Pister, K. S. J.; Roos, K. P. IEEE Trans. Biomed. Eng. 2001, 48, 9961006.
(141) Li, P. C. H.; Wanga, W.; Parameswaran, M. Analyst 2003, 128, 225-231.
(142) Cassidy, P. J.; Radda, G. K. J. R. Soc. Interface. 2005, 2, 133-144.
(143) Tamaki, E.; Sato, K.; Tokeshi, M.; Sato, K.; Aihara, M.; Kitamori, T. Anal. Chem. 2002, 74,
1560-1564.
(144) Ramser, K.; Enger, J.; Goksor, M.; Hanstorp, D.; Logg, K.; Kall, M. Lab Chip 2005, 5, 431–
436.
(145) Bulyk, M. L. Curr. Opin. Biotechnol. 2006, 17, 422-430.
(146) Jares, P. Ultrastruct. Pathol. 2006, 30, 209-219.
(147) Liss, B. Nucleic Acid Res. 2002, 30, e89.
(148) Auroux, P. A.; Koc, Y.; deMello, A.; Manz, A.; Day, P. J. Lab Chip 2004, 4, 534-546.
(149) Monis, P. T.; Giglio, S. Infection Genetics Evolution 2006, 6, 2-12.
(150) Paegl, B. M.; Blazej, R. G.; Mathies, R. A. Curr. Op. Biotechnol. 2003, 14, 42-50.
(151) Zhang, C.; Xu, J.; Ma, W.; Zheng, W. Biotechnol. Adv. 2006, 24, 243-284.
(152) Liu, C. N.; Toriello, N. M.; Mathies, R. A. Anal. Chem. 2006, 78, 5474-5479.
(153) Hong, J. W.; Studer, V.; Hang, G.; Anderson, W. F.; Quake, S. R. Nature Biotech. 2004, 22,
435-439.
(154) Marcus, J. S.; Anderson, W. F.; Quake, S. R. Anal. Chem. 2006, 78, 3084-3089.
(155) Pilarski, L. M.; Lauzon, J.; Strachan, E.; Adamia, S.; Atrazhev, A.; Belch, A. R.; Backhouse, C.
J. J. Immunol. Meth. 2005, 305, 94-105.
(156) Pilarski, P. M.; Adamia, S.; Backhouse, C. J. J. Immunol. Meth. 2005, 305, 48-58.
(157) Andersson, H.; Van den Berg, A. Lab Chip 2006, 6, 467-470.
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Figure 1. Complex signaling patterns in single cells. A) The concentration of free Ca2+ in a single
hepatocyte was measured over time. Vasopressin was added for the times marked by the bars at the top
of the graph. During the intervening times, the vasopressin was washed from the solution around the
cells. Pulsatile increases (spiking) in free Ca2+ are observed with each addition of vasopressin. The
frequency of the spikes increases with the concentration of the hormone. Individual cells within a
population spike asynchronously. B) The amount of phosphorylated MAPK (MAPK-P) was measured
in single cells after addition of different concentrations of progesterone. The y axis of the bar graphs
represents the proportion of the population possessing different percentages of phosphorylated MAPK
(x axis). N is the number of single cells used to generate the bar graph at each concentration of
progesterone. Remarkably, each cell has either none or all of the MAPK phosphorylated. C) The
phosphorylation of MAPK in each cell is “all or none”. Open circles represent cells with no
phosphorylated MAPK while solid circles reflect cells with all MAPK phosphorylated. A) Adapted by
permission from Macmillan Publishers, Ltd: Woods et al, Nature. 319:600-2, copyright 1986. B & C)
Reprinted with permission from Ferrell & Machleder, 1998 Science. 280: 895-8.
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Figure 2. Flow cytometry on-chip. A) Shown is a schematic of the Agilent microfluidic chip. The
upper insets illustrate cells (circles, triangles) at different locations in the chip. The far right inset
shows cells near the channel side wall as the cells pass through the detection zone. The abbreviations
are: sample wells (S), buffer wells (B), reference dye well (D), and the priming well (P) B) Shown are
cells (circled in red) as the cells are directed to the edge of the channel prior to detection. C) Normal
human dermal fibroblasts were loaded with calcein and stained with antibodies directed against HLA
ABC antigen. The fluorescence of calcein and the labeled antibody was measured using the Agilent
chip. Shown are graphs with different total numbers (1250 and 650) of cells analyzed on the chip
demonstrating the low numbers of cells needed for analysis. A) & C) Reprinted with permission from
Chan et al, 2003 Cytometry A. 55A:119-25. B) Reprinted with permission from Preckel et al, 2002
JALA. 7:85-9.
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Figure 3. Electrophoretic analysis of single cells. A) A cell (yellow object within the white circle) in
suspension was loaded with a fluorescent analyte (Oregon Green and fluorescein) and transported into
the cell lysis zone. B) The cell was rapidly lysed under the influence of an electric field and a
detergent introduced from an accessory channel, and the fluorescent analytes were injected into the
separation channel by electrophoresis. The white arrow marks the separation channel and the direction
of analyte movement. C) Separation of the fluorescent analytes (marked by asterisks) occurred in the
separation channel. D) An electropherogram of the fluorescent analytes contained within 8 different
cells is shown. The y axis is the analyte fluorescence. Reprinted with permission from McClain et al,
Anal. Chem. 75:5646-55. Copyright 2003 American Chemical Society.
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Figure 4. Measurement of esterase activity in arrays of nonadherent cells loaded with a fluorescent
indicator. A) Phase contrast image of an array of individual cells each docked at a suspended obstacle.
B) Histogram of the estimated concentration of carboxylesterase per cell for three different cell types
(293T, HeLa, and Jurkat cells). The enzyme concentration was calculated based on the rate of calcein
AM metabolism of individual cells in an array as shown in (A). C) Leukemic cells loaded into an
array of microwells or cell retainers fabricated in glass. D) Measurement of the metabolism of
fluorescein diacetate in individual cells in a microwell array shown in (C). Each line of red circles
represents data points (fluorescence) from a single cell. The blue lines highlight the data from one cell
as different concentrations of fluorescein diacetate were washed onto the array of cells. A & B)
Reprinted with permission from Di Carlo et al, Anal. Chem. 78:4925-30. Copyright 2006 American
Chemical Society.
C & D) From Deutsch et al, 2006 Lab Chip. 6:995-1000 - reproduced by
permission of The Royal Society of Chemistry.
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Figure 5. Single-cell partitioning for enzyme assays. A)-D) Shown are sequential images in the
encapsulation of a single lymphocyte within an aqueous droplet surrounded by oil. E) A mast cell is
encapsulated in an aqueous droplet containing a fluorogenic substrate for an intracellular enzyme. F)
Prior to cell lysis the droplet and cell remain nonfluorescent since the intracellular enzyme is
physically segregated by the cell membrane from the impermeable substrate. G) Using a laser pulse
the cell membrane is disrupted exposing the enzyme to its substrate. H) Product formation within the
confined cell lysate can be quantified by fluorescence imaging. Reprinted with permission from He et
al, Anal. Chem. 77: 1539-44. Copyright 2005 American Chemical Society.
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Figure 6. Single cell analysis in a microengineered environment. A) Schematic of a micromachined
substrate to measure the forces exerted by a migrating cell. The lateral displacement of a pad attached
to a lever and the stiffness of the lever were used to determine the force exerted on the pad. B) Shown
is a sequence of images of a keratinocyte migrating across the pad. The numbers in the lower right
corners represent the migration time in seconds. C) Plotted is the measured force (nN) exerted by the
cell shown in (B) over time. D) Shown is a microfluidic network used for localized stimulation of a
cell. A solution of epidermal growth factor (EGF) is represented in red in the microfluidic channels.
E) Measurement of Ras activity in a cell over time. The cell is situated in the bottom channel shown in
(D) such that only the left half of the cell is exposed to EGF. The time in minutes after EGF-exposure
is shown in the upper right corner. Red indicates high levels of Ras activity while blue is indicative of
low Ras activity. Ras activity is increased only in the region of the cell exposed to EGF. A) From
Galbraith and Sheetz, PNAS. 94: 9114-18, copyright 1997 National Academy of Sciences, U.S.A. B
& C) Reprinted with permission from Galbraith & Sheetz, 1999 J. Cell Biol. 147: 1313-23. D & E)
Reprinted from Sawano et al, Dev. Cell. 3:245-57, Copyright 2002, with permission from Elsevier.
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Figure 7. mRNA isolation from single mammalian cells. A) Schematic of the device with 4 parallel
stations for mRNA isolation.
The device possesses stations for cell capture, cell lysis, mRNA
purification, cDNA synthesis, and cDNA purification. B) Shown is an NIH3T3 cell at the lysis station
or ring on the device. C) The level of GAPDH gene expression was measured in different numbers
(1-4) of NIH3T3 cells (red circles fitted with red line) on the microchip shown in (A). Averaged data
from measurements on a bulk population of cells is represented by the green line. Reprinted with
permission from Marcus et al, Anal. Chem. 78: 3084-9. Copyright 2006 American Chemical Society.
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