Lecaut et al 2012

Microfluidic single cell analysis: from promise to practice
Ve´ ronique Lecault1,2,3,5
, Adam K White1,5
, Anupam Singhal1,3,5
and
Carl L Hansen1,4
Methods for single-cell analysis are critical to revealing cell-to-
cell variability in biological systems, especially in cases where
relevant minority cell populations can be obscured by
population-averaged measurements. However, to date single
cell studies have been limited by the cost and throughput
required to examine large numbers of cells and the difficulties
associated with analyzing small amounts of starting material.
Microfluidic approaches are well suited to resolving these
issues by providing increased senstitivity, economy of scale,
and automation. After many years of development microfluidic
systems are now finding traction in a variety of single-cell
analytics including gene expression measurements, protein
analysis, signaling response, and growth dynamics. With newly
developed tools now being applied in fields ranging from
human haplotyping and drug discovery to stem cell and cancer
research, the long-heralded promise of microfluidic single cell
analysis is now finally being realized.
Addresses
1
Centre for High-Throughput Biology, University of British Columbia,
2185 East Mall, Vancouver, British Columbia, V6T 1Z4, Canada
2
Michael Smith Laboratories, University of British Columbia, 2125 East
Mall, Vancouver, British Columbia, V6T 1Z4, Canada
3
Department of Chemical and Biological Engineering, University of
British Columbia, 2360 East Mall, Vancouver, British Columbia, V6T 1Z3,
Canada
4
Department of Physics and Astronomy, University of British Columbia,
6224 Agricultural Road, East Mall, Vancouver, British Columbia, V6T
1Z1, Canada
Corresponding author: Hansen,
Carl L (chansen@physics.ubc.ca, chansen@phas.ubc.ca)
5
Authors contributed equally to this work.
Current Opinion in Chemical Biology 2012, 16:381–390
This review comes from a themed issue on Analytical techniques
Edited by Shana O Kelley and Petra S Dittrich
For a complete overview see the Issue and the Editorial
Available online 21st April 2012
1367-5931/$ – see front matter, # 2012 Elsevier Ltd. All rights
reserved.
http://dx.doi.org/10.1016/j.cbpa.2012.03.022
Introduction
Cells are the fundamental units of biological processes.
However, the vast majority of our understanding of bio-
chemistry and genetics has been gleaned through the bulk
analysis of large populations of cells, which are required to
obtain sufficient starting material for conventional analysis
methods. Interpretation of such data often implies the tacit
assumption that each cell in the population is similar. More
often than notthisisfalse.Cellular heterogeneityisinfacta
generalfeatureofbiologicalsystemsandhasbeenobserved
across all levels of life, from single bacterial cells to human
tissues. Even cells with identical functions generally
respondasynchronously, making precise studies of kinetics
and dynamics of cell populations impossible. Moreover, in
many important fields, minority subpopulations of cells are
often the most relevant. For instance, in microbial geno-
mics it is frequently impossible to selectively isolate or
culture a particular microbial species, thus necessitating
the study of DNA shrapnel derived from a mixture of
organisms. Similarly, in stem cell science even the most
advanced isolation methods can only provide enriched
populations of stem cells. In the best case, murine hema-
topoietic stem cells, functional purities are generally below
50% [1], and in many other systems they are much lower.
Thus, bulk measurements of the molecular signatures of
these important cells are obscured by significant, and often
overwhelming, contamination from other cell types of
unknown state and relative abundance. This scenario is
paralleled in numerous fields of research including cancer,
immunology and developmental biology. Understanding
the extent and importance of cellular heterogeneity is one
of the most vexing problems facing biological research.
The challenge of understanding cellular heterogeneity
has been a major thrust of technological development
over the past decade, resulting in an increasingly powerful
suite of instrumentation, protocols, and methods for ana-
lyzing single cells at the level of DNA sequence, RNA
expression and protein abundance [2–4]. Flow cytometry
and cell sorting have been widely adopted as a corner-
stone of cellular phenotyping and purification, allowing
for high-throughput quantitative analysis of protein
expression and phosphorylation state in single cells [5–
7]. Recent advances in coupling this technology with
metal labeling have now extended the analysis of fixed
cells to sensitive multiplexing of dozens of targets per run
[8]. At the same time, increasingly rapid and sensitive
imaging instrumentation now allows high-throughput
single cell measurements of proteins and nucleic acids
with single molecule resolution [9], and the precise
tracking of cellular growth and responses over extended
periods [10–13]. Sensitive PCR-based protocols for
measuring large panels of mRNA from single cells are
now well established and have been coupled to FACS
isolation and robotic assay assembly [14,15
,16–19]. At
the same time, the rise of high-throughput sequencing
Available online at www.sciencedirect.com
www.sciencedirect.com Current Opinion in Chemical Biology 2012, 16:381–390

instrumentation [20] has now made single-cell genomics a
practical proposition [21,22] and increasingly focus has
turned to the development of appropriate protocols for
high-fidelity amplification of DNA and RNA from single
cells [23–25]. Sequencing approaches have further been
coupled with virus-based molecular barcoding strategies
to dissect heterogeneity in cellular processes in vivo [26].
Despite this suite of available approaches we are still only
beginning to face the measurement challenges of cellular
heterogeneity. There is much work to be done, both in
enabling new modes of analysis, and in improving the
speed, throughput, and economy of those that exist.
Although each measurement application carries its own
specific requirements, the recurring challenge in single-
cell analysis is to simultaneously achieve the sensitivity,
precision, throughput, and economy needed to detect and
study complex subpopulations of cells. Microfluidic for-
mats are ideally suited to addressing these problems by
providing reduced reagent costs, high effective template
concentrations in small volumes, scalability, ease of auto-
mation, improved cell handling, and multi-step integration
(Table 1). Over a decade of interdisciplinary research and
development, spanning fields of engineering, molecular
biology, imaging, cell biology, and chemistry, has now
brought microfluidic single cell analysis to a turning point,
with technologies increasingly being adopted in biological
andbiomedicalresearch[27,28].Herewereviewhowthese
approaches are pushing new avenues of research and high-
light the next generation of advances that seem poised to
transition from the bread-board to the bench-top.
Microfluidic approaches to high-throughput
single-cell RT-qPCR
Reverse transcription quantitative PCR (RT-qPCR) pro-
vides both excellent specificity and sensitivity, making it
well suited to gene expression measurements in single
cells. New preamplification strategies [29] have enabled
RT-qPCR measurements, which were typically per-
formed on a modest numbers of target genes [30,31],
to be multiplexed for the analysis of many dozens of
transcripts from a single cell [32,33]. However, appli-
cation of this approach to the analysis of large numbers
of single cells creates a ‘tyranny of numbers’ with serious
challenges in both throughput and cost. A commercially
available valve-based microfluidic qPCR system, the
Dynamic ArrayTM
(Fluidigm), provides a low-volume
(nanoliter) and high-throughput (thousands of PCR reac-
tions per device) solution to this detection problem and
has become increasingly popular for large-scale single cell
studies. For instance, Guo et al. used microfluidic qPCR
arrays to measure the expression dynamics of 48 genes
over 500 individual cells harvested during the first four
days of mouse embryo development [17]. Correlation of
expression measurements with surface markers revealed
that co-expression of lineage-specific transcription factors
occurred at the 32-cell stage of development, but that
three distinct transcriptional programs emerged at the 64-
cell stage. Scalable single cell expression measurements
have also been used to provide new insights into cellular
heterogeneity that exists within rare populations isolated
from different developmental stages and across hierar-
chies of differentiation, both at the level of transcript and
miRNA expression [18,19,34,35]. Of particular interest
has been the implication of cellular heterogeneity within
cancer, both in terms of disease progression and optimal
treatment strategies [36,37]. Dalerba et al. identified dis-
tinct single cell gene expression signatures that are pre-
dictive of patient survival and clinical outcomes in colon
cancer patients [15
]. Diehn et al. used single-cell
analysis to identify a radioresistant subset of breast tumor
cells with increased capacity for reactive oxygen species
scavenging [16].
382 Analytical techniques
Table 1
Advantages of microfluidics for single cell analysis.
Application Challenges with traditional methods Advantages of microfluidics Examples
Single-cell RT-qPCR Limited abundance of starting template Concentration enhancement in small volumes [38
,40]
Cost and throughput required for analysis
of large numbers of cells and target genes
Parallelization, automation, and economy of scale [17,38
]
Single-cell genomics Amplification bias and sensitivity Improved reaction bias and sensitivity in nL volumes
and reduced contaminant DNA
[47]
Isolating individual cells Integrated microfluidic cell sorting and processing [48]
Single-cell measurements
of intracellular proteins
Movement of living cells Confinement of live cells in microfluidic structures [50
]
Low amount of signal Integrated single-cell handling allows lysate analysis [54,55
]
Single-cell measurements
of secreted proteins
Small amounts of secreted products from
single cells
Concentration enhancement in small volumes [57,58]
Difficult to co-localize multiple cells in
defined chemical environments
Ease of confinement in droplets or microchambers [62]
Signaling studies Mostly limited to static conditions Easy temporal stimulation [67,70
,71
]
Inability to rapidly exchange conditions
on suspension cells
Laminar flow and proper design enables cell
sequestration
[68,70
]
Live cell imaging Difficulties of tracking cells through
multiple frames
Confinement of clones facilitates cell tracking [76]
Current Opinion in Chemical Biology 2012, 16:381–390 www.sciencedirect.com

The examples above show how microfluidics can provide
scalability, reduced reagent consumption, and throughput
to enable large single cell studies that would otherwise be
impractical or prohibitively expensive. However, these
analyses still require off-chip cell handling and processing
steps to generate products needed for qPCR. The
inclusion of microfluidic cell handling and processing
thus offers important avenues to improved throughput
and cost, while also improving precision and sensitivity
through small-volume confinement. To this end White
et al. recently described a fully integrated microfluidic
RT-qPCR device that implements all steps of cell trap-
ping, lysis, cDNA synthesis, and qPCR analysis (Figure 1)
at a throughput of 300 cells per run [38
]. This system
achieves improved precision and sensitivity over large-
volume RT-qPCR analysis and offers a general solution
for cell-handling automation and integration that may be
adapted to a variety of amplification and analysis protocols
[39], including high-throughput microfluidic qPCR, high-
density digital PCR [40,41], sequencing, and microarray
analysis.
Single cell genomes
In addition to gene expression analysis, microfluidic
approaches are finding increasing applications in studying
diversity and variations in single cell genomes, with
applications spanning cancer biology to environmental
microbiology. While new high-throughput sequencing
instrumentation has made exome and whole-genome
shotgun sequencing standard practice in cancer research,
attention has now turned towards dissecting clonal
heterogeneity. In one approach the sequencing of ampli-
fied single nuclei was used to infer the clonal evolution of
a breast tumor by measuring single cell copy number
variations [24]. Scalable and low-cost implementations of
single cell/nuclei isolation and amplification are likely to
expand the power and pervasiveness of such analyses. In
this line, Fan et al. recently reported a haplotyping
approach on the basis of using a microfluidic device to
amplify and genotype individual chromosomes isolated
from a single cell [42
]. The isolation and lysis of a single
metaphase cell was used to distribute chromosomes
across an array of 20 nL reaction chambers, followed by
phi29 polymerase multiple displacement amplification
[43], recovery of the isolated amplified products, and
analysis on SNP arrays to establish haplotypes [42].
Beyond the utility in phasing genomes, more scalable
implementations of this technology may soon allow for
the study of heterogeneity in chromosome partitioning
and translocation events in cancer.
Single cell genome analysis is particularly compelling in
the study of microbial organisms and communities. The
vast majority of microorganisms on the planet have yet to
be isolated in culture, necessitating metagenomic strat-
egies that attempt to infer the identity and relative
abundance of constituent members by sequencing and
analysis of mixed pools of DNA. Microfluidic digital PCR
in valve-based devices has been used to help untangle
this genomic information by co-amplification of specific
genes in isolated individual bacteria cells. This has been
applied to establish co-existence of functional genes
within a single organism and to reveal virus–host relation-
ships in complex environments [44,45]. In a similar single
cell genotyping application, microfluidic droplet-based
systems for digital PCR have been used for the detection
Microfluidic single cell analysis Lecault et al. 383
Figure 1
i
ii
iv
iii
(a) (b) (c)
Current Opinion in Chemical Biology
A microfluidic device for high-throughput single-cell RT-qPCR. (a) Fluorescence image of entire device showing 300 reactions after 40 cycles of PCR.
(b) Enlarged view of individual reactors from (a) with dyes highlighting fluid paths (blue) and valves (red). Each array unit consists of (i) a reagent inlet, (ii)
a 0.6 nL cell capture region with integrated cell traps, (iii) a 10 nL RT chamber and (iv) a 50 nL PCR chamber. Scale bar: 400 mm. (c) Optical micrograph
of single cells trapped in the cell capture chambers (indicated by black arrows). Scale bar, 400 mm.
Adapted from [38
].

of pathogenic E. coli within a high background of non-
pathogenic cells, achieving a detection limit of 1/105
[46].
The coupling of new low-bias whole genome amplification
strategies [43] with sequencing provides a powerful
approach to global single cell genome analysis and has
been implemented in conventional tubes using single cell
isolation by FACS or micropipette [23]. Microfluidic sys-
tems offer an integrated ‘front-end’ solution to bacterial
imaging, isolation, and processing, and have been shown to
improve MDA performance by providing reduced ampli-
fication bias in nanoliter volume reactions and suppression
of contaminating DNA [23]. Although the physical separ-
ation of single cells remains an important obstacle for many
complex samples, this approach has been applied to obtain
highly enriched metagenomes for T7 microbes from the
human mouth [47], and has been further integrated with
optical tweezer manipulation to obtain a novel genome for
an ammonia-oxidizing archaeon [48]. Leung et al. have
recently developed a programmable droplet-based format
for single microbe isolation and multiparameter single-cell
analysis [49]. This system provides improvements in-
cluding facilitated single cell handling, flexible protocol
development, and significantly higher throughput, and was
used to dissect microbial diversity in environmental
samples by whole genome amplification and sequencing
of single cells and cell aggregates.
Microfluidic analysis of proteins in single cells
Beyond genomics applications, the scalability and small-
volume advantages of microfluidic methods have increas-
ingly found applications in the measurement of intra-
cellular and secreted proteins from single cells. Taniguchi
et al. used single molecule imaging in a parallel micro-
fluidic format to measure intracellular protein expression,
localization and abundance in a library of over 1018
Escherichia coli fluorescent protein fusion strains [50
]
(Figure 2a–c). Protein abundances were found to vary
from 0.1 to 104
molecules per cell, spanning a dynamic
range of over 5 orders of magnitude. At low copy numbers
(10), differences in protein expression were attributed
to intrinsic noise (e.g. stochastic binding of transcription
factors to DNA promoter sites), whereas variations in
higher expressed proteins, including almost all essential
proteins, was generally governed by extrinsic fluctuations
in cellular metabolites, ribosomes, and polymerases.
Interestingly, for any given gene, a single cell’s protein
and mRNA abundance were found to be uncorrelated,
likely reflecting the relatively rapid degradation of
mRNA compared to the long lifetimes of proteins in
the cell. In contrast, Cheong and colleagues exploited
the parallelization of microfluidic culture to reconstruct
signaling kinetics using endpoint staining of fixed cells at
different time points after stimulation, thereby enabling
the detection of multiple proteins on each cell [51]. With
Figure 2
Stage scan
PDMS
Bacteria
Coverslip
Objective lens
Strain n-1
Strain n+1
Strain n
25 μm
10 μm
Hybridoma
cellAntibody
capture beads
10 μm
150 μm
(a)
Side view
(b) (c)
(e)
Adk
Probability
NormalizedFluorescence
Protein copy number
Time (min)
(d)
0.1
0.08
0.06
0.04
0.02
0
1.2
1
0.8
0.6
0.4
0.2
0 20 40 60 80 100 120
0 500 1000 1500 2000
a = 6.8
b = 99
Microfluidic analysis of single cell intracellular (a)–(c) and extracellular (d) and (e) protein expression. (a) Microfluidic device for the parallel molecular
imaging of multiple bacterial strains with single protein resolution. (b) High-resolution fluorescence imaging to quantify protein abundance in single E.
coli cells using genetically fused fluorescent reporter strains. (c) Distribution of intracellular Adk protein in single E. coli cells. (d) A microfluidic
fluorescence bead assay to measure antibody–antigen binding kinetics from antibodies secreted by a single cell. (e) Binding kinetics of a mouse mAb
with hen egg lysozyme measured from a single bead.(a)–(c) Adapted from [50
] with permission. (d) and (e) adapted from [59].

this method, it was shown that JNK signaling exhibited a
binary switch-like response after anisomycin stimulation
in HeLa cells [52]. Microfluidic-based immunocyto-
chemistry has also been used to assess intratumoral
and intertumoral heterogeneity in brain tumor samples,
showing that cluster analysis of four intracellular sig-
naling proteins could predict tumor progression and
survival outcomes [53]. Single-cell protein measure-
ments have also been performed by integrating micro-
fluidic single-cell handling (i.e. sorting, lysis, labeling)
with electrophoretic separation [54] or micro-patterned
antibody capture arrays [55
] In the latter approach,
protein expression variability in a glioblastoma tumor
cell line was measured using a quantitative fluorescent
sandwich assay on multiple target proteins per cell [55
].
This single-cell barcode chip (SCBC) approach is scal-
able and has already been demonstrated at a throughput
of tens of cells per chip with duplicate measurements of
nine proteins.
The concentration enhancement and rapid diffusive mix-
ing afforded by subnanoliter microfluidic chambers has
enabled the single-cell analysis of secreted effector
proteins from immune cells (e.g. B cells, T cells, and
macrophage). Ma et al. applied the SCBC to simul-
taneously measure multiple cytokines (e.g. IL-10,
TNF-b, IFN-g) from human macrophages and cytotoxic
T lymphocytes (CTLs) obtained from both healthy
donors and a metastatic melanoma patient [56]. Although
not strictly microfluidic, open arrays of microfabricated
chambers have also been used to screen and select B cells
secreting antigen-specific antibodies from both immu-
nized humans and mice [57,58]. This approach can be
improved by using microfluidics to automate cell hand-
ling and fluid-exchange, allowing antibodies from single
cells to be directly screened by measuring antibody-
antigen binding kinetics and specificities to different
target antigens [59] (Figure 2d,e).
An alternative approach uses microfluidic devices for the
high-throughput analysis of secreted proteins from single
cells by encapsulating them in emulsions consisting of
subnanoliter aqueous droplets in oil [60,61]. Tumarkin
and colleagues used a variant of this approach to study
cellular paracrine signaling by co-encapsulating cells in
microfluidic-generated agarose beads, and demonstrating
that cell survival could be modulated by the ratio of
MBA2 IL-3 secreting cells to M07e factor-dependent
cells [62]. Microfluidic droplet generation is also being
developed for drug screening applications by measuring
viability of encapsulated single cells exposed to different
chemical compositions [63
].
Single cell growth and response phenotypes
In addition to facilitating multiplexed genetic and protein
analysis of single cells, microfluidic devices provide
numerous advantages to the study of live cells such as
precise spatio-temporal control of medium conditions,
parallelization, and cell confinement for improved ima-
ging. These capabilities are particularly well suited to
measuring the kinetics and cellular heterogeneity of cell
signaling. Because of the ease of genetic manipulation
and cell culture, microfluidic approaches have been used
extensively to study the response of archetypical protein
signaling networks in yeast, most notably the pheromone
and HOG mitogen activated protein kinase (MAPK)
networks. The combination of microfluidic flow control,
precise cell immobilization, fluorescent protein reporters,
and image processing has been used to access several
experimental regimes that are difficult or impossible to
implement in bulk: the study of cell signaling under
stable and precisely defined spatial gradients [64]; the
frequency analysis of signaling response under oscillating
stimulation conditions [65,66]; and the high-throughput
analysis of network response under combined chemical
and genetic perturbations [67,68]. Importantly, exper-
iments that track individual cells through time are critical
to understanding mechanisms of response heterogeneity,
including effects of cell cycle, cell age, and familial
relationships. For instance, Falconnet et al. found that
nonuniform gene expression and phenotypic responses
observed at intermediate concentrations of pheromone
were not random, but rather correlated with genealogical
relationships (Figure 3a), illustrating how nongenetic
heritable traits may influence the critical threshold for
cellular decision making [68].
In a similar vein, microfluidic approaches are becoming
increasingly important as an in vitro method for studying
complex and highly dynamic interactions that govern
growth and differentiation of mammalian cells in vivo.
These approaches have used both surface patterning of
microwells to more precisely dissect and mimic factors
present in the in vivo microenvironment [11,69], and
automated fluid control to examine temporally varying
medium conditions [70
,71
]. Tay and colleagues
exploited the later approach to demonstrate that single
3T3 mouse fibroblast cells respond to tumor necrosis
factor alpha (TNF-a) in a digital manner; that is, lower
numbers of cells responded to lower doses of TNF-a
even though the amplitude of transcription factor nuclear
factor (NF-kB) remained high [71
]. Pulse stimulation
studies showed that prior exposure to TNF-a played a
role in subsequent cellular responses, indicating that this
pathway is not a purely stochastic system. In addition to
deterministic control of applied factors, Molidena and
colleagues reported the use of varying microfluidic flows
to modulate the effect of endogenously secreted factors,
showing that endocrine signaling is an important deter-
minant of differentiation and cellular heterogeneity in
murine embryonic stem cells [72
].
Nonadherent cell types, including hematopoietic cells
and industrially important suspension-adapted cell lines,

present unique challenges for microfluidic analysis due to
the need for immobilization during medium exchange.
Lecault et al. reported a cell culture device optimized for
suspension cell types that solves this problem by using
gravity to drop cells into the bottom of high aspect ratio
chambers (Figure 3b,c), thereby sequestering them from
flow forces while maintaining the ability to exchange
medium conditions using diffusion [70
]. In addition, this
device featured a thin cell-culture layer that was overlaid
with a large medium reservoir, essentially blocking dehy-
dration effects and allowing for robust growth and the
selective recovery of viable cells following culture. The
ability to perform immunohistochemistry on live cells
without disturbing their spatial locations was used to
correlate heterogeneous clonal growth of preleukemic
cells with varying differentiation state. In a separate
study, exposure of rare primary hematopoietic stem cells
to temporally varying Steel factor (SF) concentrations
revealed that this growth factor is critical for cell survival
during a short window as cells exit quiescence, but does
not directly influence cell growth kinetics.
Single cell growth analysis
Microfluidic systems greatly facilitate long-term time-
lapse imaging studies of clonal growth and death kinetics
under different medium conditions. This is perhaps one
of the simplest and most underexploited assays of cellular
heterogeneity. For instance, the early division kinetics of
primary murine HSCs transduced with NUP98-HOXA10
homeodomain (NA10hd), a fusion gene known to stimu-
late stem cell expansion in vitro, was investigated using a
microfluidic cell culture array [73]. Clonal analysis of
infected and control populations has confirmed that
NA10hd did not affect cell cycling times, but that the
growth advantage of overexpressing cells was due to an
increase in self-renewal. In a different study, Albrecht
et al. used the expression of H2B-EGFP to facilitate
tracking of mitotic events in murine embryonic stem
cells and reported an apparent synchronization of division
events across the microfluidic device [74].
In addition to quantitative measures of clonal growth and
death,genealogicalanalysis,allowingfor thereconstruction
Figure 3
MAPK pathway GFP response320 min α-factor stimulation40 min α-factor stimulation
(a)
(b) (c)
Microfluidic cell culture devices for live analysis of clonal heterogeneity. (a) Example of heterogeneous MAPK responses to alpha-factor pheromone
being passed on from mother to daughter yeast cells. (b) Microfluidic chambers with high-aspect ratio for the culture of mammalian suspension cells.
(c) Microfluidic cell culture array and image analysis show intraclonal heterogeneity in hematopoietic progenitor NUP98-HOXD13 cells. Green labels
represent viable cells, red labels represent dead cells and blue lines highlight cell contours. Scale bar, 100 mm.
(a) Adapted from [68]. Reproduced by permission of the Royal Society of Chemistry (RSC). (b) Reproduced from [70
]. (c) Adapted from [70
].

of the ‘family tree’ in each clone, provides a rich phe-
notype for understanding cellular decision-making and
retrospectively assessing the heterogeneity of the starting
cell populations. Scherf and colleagues combined genea-
logical tracing and surface patterning in a microfluidic
device to show that the symmetry of human stem and
progenitor cell divisions could be altered by exposure to
exogenous factors [75]. The generation of division pedi-
grees from a large number of single cells is assisted by
microfluidic designs that confine clones in a limited space.
In one example, microfluidic chambers were used to grow
yeast colonies in linear geometries in order to facilitate
the assignment of mother-daughter relationships, showing
that observed bursts of heat shock protein expression are
synchronized between a cell and its immediate progeny
[76]. As a high-precision alternative to optical analysis of
cellular growth, the Manalis group have developed an
innovative approach that directly measures the mass of
single cells using microfabricated cantilevers with inte-
grated flow channels. This technique was used to show
that heavier cells grew faster than lighter cells [77], and that
cellular density could be used to distinguish subpopu-
lations of blood cells [78]. Although this approach has
not yet been adapted to high-throughput formats, it pro-
vides an excellent illustration of how microfluidic
approaches can enable previously inaccessible, and often
even unexpected, measurement tools for understanding
cellular heterogeneity.
Future impact of microfluidic technologies
Although microfluidic analysis methods have long been
a focus of technology development, it is only recently
that these tools are impacting biological and biomedical
research. These are auspicious times. The pace of de-
velopment and adoption is accelerating rapidly and the
next few years will see many important technological
developments and applications. Microfluidic cell proces-
sing will emerge as a cornerstone of single cell genomics,
enabling routine and scalable measurements of tran-
scription and DNA sequence with improved perform-
ance and economy. Although global proteomic analysis
of single cells is still far away, requiring major advances
in detection sensitivity and instrumentation, measure-
ments of specific protein panels using either antibody
capture or alternative specific reagents will continue to
develop and should enable new avenues of inquiry
ranging from immune response to cancer biology. Sim-
ilarly, the profiling of metabolites in single cells con-
stitutes an important area for continued advancement
[79]. Another exciting prospect for dissecting complex
cell populations is the integration of live-cell imaging
and genealogical analysis with transcriptional and
protein expression measurements, and the correlation
of these with functional assays. While these microfluidic
tools will be driven in the near term by interdisciplinary
research teams, broad adoption and long-term impact
will require increasing commercialization activities.
New developments in programmable microfluidic
devices will also be important in providing a general
fluid-handling platform that may be adapted to niche or
user-specific applications [49,80,81]. Given the rapid
pace of development, the enormous impact of single
cell approaches and the inherent advantages of micro-
fluidic analysis, it would seem that answers to many of
the biggest questions in single cell variability may very
well come on a tiny chip.
Acknowledgements
The authors would like to thank Marketa Ricikova for providing the original
images for Figure 3a. Funding support has been provided by grants from the
Natural Sciences and Engineering Research Council (NSERC), Genome
BC, Genome Canada, Western Diversification, the Terry Fox Foundation,
and the Canadian Institute for Health Research (CIHR). The authors also
thank the Michael Smith Foundation for Health Research (VL, AS, AKW,
CLH), NSERC (VL, AS, AKW), and CIHR (CLH) for salary support.
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