New papers with
focus on single-cell gene expression noise:
Method of the year - Methods to watch -
methods - Improved single-cell methods are helping to unravel
present important methods and areas of methodological
development worth watching in the coming years.
Nature Methods -
VOL.9 NO.1 - JANUARY 2012 - 35
The heterogeneity of cells in culture and in organisms poses a
challenge for many experi-mental measurements. Population measure-ments
are necessarily averages, masking the behavior of minority
subpopulations and effectively blinding researchers to possibly
interesting differences between cells.The alternative is to make
measure-ments on single cells. Methodologically speaking, this, too, is
challenging on sever-al fronts. Molecular analyses, whether on a
particular macromolecule or at an ‘omic’ scale, can be difficult (or
even impossible) to accomplish on the amount of mate-rial extracted
from one cell. Methods with increased sensitivity are therefore in
demand. Throughput is also a bottle-neck. Basing firm conclusions on
single-cell measurements means that one must be able to quickly and
accurately analyze many cells. Finally, it is often necessary to
analyze single cells in a mul-tiplexed fash-ion, either because the
cells exist in a heteroge-neous pop-ulation or because one wants to
measure many parameters at the same time.There continue to be
methodologi-cal advances on all of these fronts. Mass cytometry, for
instance - in which iso-topes are used as antibody labels instead of
fluorescent probes—considerably extends the multiplexing capabilities
of flow cytometry (Science 332, 687–695; 2011). Is the
measurement of gene expression, digital reverse-transcriptase PCR
in a microfluidics device makes it possible to simultaneously monitor
the expres-sion of hundreds of genes in hundreds of single cells. As
demonstrated in a recent study of tumor heterogeneity, this can be
combined with single cell sorting and with statistical clustering
methods to begin to dissect the cellular subpopulations that constitute
a tissue (Nat. Biotechnol. 29, 1120–1127; 2011).
SPECIAL ISSUE -- Single-Cell Biology -- L.
Cells Go Solo -- Science 6 Dec 2013 Vol.
342 no. 6163 p. 1187
INTRODUCTION - The scientific literature contains an enormous body of
work in which
large numbers of cells have been broken open and homogenized to prepare
samples for biochemical characterization and, certainly, much has been
learned from such studies. But more recently, it has become possible to
monitor events in single cells, thus allowing investigators to test
whether existing “averaged” readings of the state of many cells from
traditional large-scale assays accurately represent the behavior of the
individual cells being studied. Such single-cell measurements are
providing a wealth of information—sometimes unanticipated and often
previously obscured—about how cells respond to perturbations or
signals. In this special issue, three Reviews provide examples of
fundamental insights into cellular regulation that are revealed when it
is possible to measure enzymatic activity, transcriptional responses,
or the metabolic state in individual cells.
An obvious advantage of single-cell measurements is the ability to
measure variations or “noise” in the responses of the individual cells
to similar or identical conditions. In many instances, it is possible
to monitor the time course of cellular responses. Gene transcription
can be particularly noisy, with bursts of RNA synthesis occurring in
some cells but not others of the same population. Thus, fundamental
questions arise about the nature of these systems. Perhaps variation in
response is advantageous in conserving resources or in assuring that
some cells survive in a changing environment. Or it may be that
biophysical constraints of small numbers of molecules and the
characteristics of the enzymes at work dictate such variability as
unavoidable. Sanchez and Golding review recent work in model systems,
from bacteria to animal cells, that attempts to resolve whether the
kinetics of transcription are encoded in the architecture of promoter
sequences in DNA—and might therefore vary throughout the genome—or are
determined by physical or biophysical properties that would impose more
global constraints throughout the cell.
Levine et al. explore another previously
hidden phenomenon. Continuous
measurements of protein activation show that many undergo asynchronous
pulsatile responses, which are obscured in average measurements from a
population of cells. They discuss how cellular circuits are wired to
produce such responses and what the advantages of such control systems
Zenobi highlights methodological advances, particularly in mass
spectrometry, that are enabling quantitation of the abundance of
molecular components of single cells. Challenges abound for the goal of
making simultaneous measurements to characterize the rapid ly changing
metabolic state of individual cells. But the promise of new insights
across a broad range of disciplines is sustaining a steady effort to
tap into the large store of new knowledge lying hidden within the
confines of single cells.
|Microfluidics and Single Cells
03/25/2014 Sarah C.P. Williams
Growing evidence suggests that biochemical assays don’t capture the
complexity of cell cultures. Now, researchers are turning to
microfluidics to assay one cell at a time. Learn more...
probe for single-cell analysis in adherent tissue culture
Sarkar A, Kolitz S, Lauffenburger DA, Han J
Nat Commun. 2014 (5): 3421
Single-cell analysis provides information critical to understanding key
disease processes that are characterized by significant cellular
heterogeneity. Few current methods allow single-cell measurement
without removing cells from the context of interest, which not only
destroys contextual information but also may perturb the process under
study. Here we present a microfluidic probe that lyses single adherent
cells from standard tissue culture and captures the contents to perform
single-cell biochemical assays. We use this probe to measure kinase and
housekeeping protein activities, separately or simultaneously, from
single human hepatocellular carcinoma cells in adherent culture. This
tool has the valuable ability to perform measurements that clarify
connections between extracellular context, signals and responses,
especially in cases where only a few cells exhibit a characteristic of
|Simultaneous quantification of
alternatively spliced transcripts in a single droplet digital PCR
Bing Sun, Lian Tao, and Yun-Ling Zheng
BioTechniques, Vol. 56, No. 6, June 2014, pp. 319–325
Humans synthesize ~150,000 different proteins from 25,000–30,000 genes
by alternative splicing. It is estimated that more than 70% of human
protein-coding genes produce multiple alternatively spliced mRNA
transcripts (1). When these mRNAs are translated, they produce an array
of proteins with diverse and even antagonistic functions. A large
proportion of human genetic disorders are the result of abnormal
splicing, with abnormal splicing variants thought to even contribute to
the development of cancer (2, 3). Given the importance of alternative
splicing in regulating cellular function, accurate quantification of
multiple alternatively spliced transcripts could facilitate the
discovery of new biomarkers for clinical applications and thus enhance
our understanding of the role of alternative splicing in health and
|Validation of high-throughput single cell
Devonshire AS1, Baradez MO2, Morley G2, Marshall D2, Foy CA2.
Anal Biochem. 2014 (1) 452: 103-113
High-throughput quantitative polymerase chain reaction (qPCR)
approaches enable profiling of multiple genes in single cells, bringing
new insights to complex biological processes and offering opportunities
for single cell-based monitoring of cancer cells and stem cell-based
therapies. However, workflows with well-defined sources of variation
are required for clinical diagnostics and testing of tissue-engineered
products. In a study of neural stem cell lines, we investigated the
performance of lysis, reverse transcription (RT), preamplification
(PA), and nanofluidic qPCR steps at the single cell level in terms of
efficiency, precision, and limit of detection. We compared protocols
using a separate lysis buffer with cell capture directly in RT-PA
reagent. The two methods were found to have similar lysis efficiencies,
whereas the direct RT-PA approach showed improved precision. Digital
PCR was used to relate preamplified template copy numbers to Cq values
and reveal where low-quality signals may affect the analysis. We
investigated the impact of calibration and data normalization
strategies as a means of minimizing the impact of inter-experimental
variation on gene expression values and found that both approaches can
improve data comparability. This study provides validation and guidance
for the application of high-throughput qPCR workflows for gene
expression profiling of single cells.
|Block-Cell-Printing for live single-cell
Zhang K1, Chou CK, Xia X, Hung MC, Qin L.
Proc Natl Acad Sci U S A. 2014 111(8): 2948-2953
A unique live-cell printing technique, termed "Block-Cell-Printing"
(BloC-Printing), allows for convenient, precise, multiplexed, and
high-throughput printing of functional single-cell arrays. Adapted from
woodblock printing techniques, the approach employs microfluidic arrays
of hook-shaped traps to hold cells at designated positions and directly
transfer the anchored cells onto various substrates. BloC-Printing has
a minimum turnaround time of 0.5 h, a maximum resolution of 5 µm,
close to 100% cell viability, the ability to handle multiple cell
types, and efficiently construct protrusion-connected single-cell
arrays. The approach enables the large-scale formation of heterotypic
cell pairs with controlled morphology and allows for material transport
through gap junction intercellular communication. When six types of
breast cancer cells are allowed to extend membrane protrusions in the
BloC-Printing device for 3 h, multiple biophysical characteristics of
cells--including the protrusion percentage, extension rate, and cell
length--are easily quantified and found to correlate well with their
migration levels. In light of this discovery, BloC-Printing may serve
as a rapid and high-throughput cell protrusion characterization tool to
measure the invasion and migration capability of cancer cells.
Furthermore, primary neurons are also compatible with BloC-Printing.
|Quantitative assessment of single-cell
Wu AR, Neff NF, Kalisky T, Dalerba P, Treutlein B, Rothenberg ME, Mburu
FM, Mantalas GL, Sim S, Clarke MF, Quake SR
Nat Methods. 2014 Jan;11(1):41-46
Interest in single-cell whole-transcriptome analysis is growing
rapidly, especially for profiling rare or heterogeneous populations of
cells. We compared commercially available single-cell RNA amplification
methods with both microliter and nanoliter volumes, using sequence from
bulk total RNA and multiplexed quantitative PCR as benchmarks to
systematically evaluate the sensitivity and accuracy of various
single-cell RNA-seq approaches. We show that single-cell RNA-seq can be
used to perform accurate quantitative transcriptome measurement in
individual cells with a relatively small number of sequencing reads and
that sequencing large numbers of single cells can recapitulate bulk
|The workflow of single-cell expression
profiling using quantitative real-time PCR
Ståhlberg A1, Kubista M.
Expert Rev Mol Diagn. 2014 (3):3323-331
Biological material is heterogeneous and when exposed to stimuli the
various cells present respond differently. Much of the complexity can
be eliminated by disintegrating the sample, studying the cells one by
one. Single-cell profiling reveals responses that go unnoticed when
classical samples are studied. New cell types and cell subtypes may be
found and relevant pathways and expression networks can be identified.
The most powerful technique for single-cell expression profiling is
currently quantitative reverse transcription real-time PCR (RT-qPCR). A
robust RT-qPCR workflow for highly sensitive and specific measurements
in high-throughput and a reasonable degree of multiplexing has been
developed for targeting mRNAs, but also microRNAs, non-coding RNAs and
most recently also proteins. We review the current state of the art of
single-cell expression profiling and present also the improvements and
developments expected in the next 5 years.
|Single-cell sequencing-based technologies
will revolutionize whole-organism science
Shapiro E, Biezuner T, Linnarsson S.
Nat Rev Genet. 2013 (9): 618-630
The unabated progress in next-generation sequencing technologies is
fostering a wave of new genomics, epigenomics, transcriptomics and
proteomics technologies. These sequencing-based technologies are
increasingly being targeted to individual cells, which will allow many
new and longstanding questions to be addressed. For example,
single-cell genomics will help to uncover cell lineage relationships;
single-cell transcriptomics will supplant the coarse notion of
marker-based cell types; and single-cell epigenomics and proteomics
will allow the functional states of individual cells to be analysed.
These technologies will become integrated within a decade or so,
enabling high-throughput, multi-dimensional analyses of individual
cells that will produce detailed knowledge of the cell lineage trees of
higher organisms, including humans. Such studies will have important
implications for both basic biological research and medicine.
|Genetic determinants and cellular
constraints in noisy gene expression
Sanchez A, Golding I
Science. 2013 342(6163): 1188-1193
In individual cells, transcription is a random process obeying
single-molecule kinetics. Often, it occurs in a bursty, intermittent
manner. The frequency and size of these bursts affect the magnitude of
temporal fluctuations in messenger RNA and protein content within a
cell, creating variation or "noise" in gene expression. It is still
unclear to what degree transcriptional kinetics are specific to each
gene and determined by its promoter sequence. Alternative scenarios
have been proposed, in which the kinetics of transcription are governed
by cellular constraints and follow universal rules across the genome.
Evidence from genome-wide noise studies and from systematic
perturbations of promoter sequences suggest that both scenarios-namely
gene-specific versus genome-wide regulation of transcription
kinetics-may be present to different degrees in bacteria, yeast, and
|Transcriptional profiling of cells sorted
by RNA abundance
Klemm S, Semrau S, Wiebrands K, Mooijman D, Faddah DA, Jaenisch R, van
Nat Methods. 2014 May;11(5): 549-551
We have developed a quantitative technique for sorting cells on the
basis of endogenous RNA abundance, with a molecular resolution of 10-20
transcripts. We demonstrate efficient and unbiased RNA extraction from
transcriptionally sorted cells and report a high-fidelity transcriptome
measurement of mouse induced pluripotent stem cells (iPSCs) isolated
from a heterogeneous reprogramming culture. This method is broadly
applicable to profiling transcriptionally distinct cellular states
without requiring antibodies or transgenic fluorescent proteins.
|Validation of noise models for single-cell
Grün D, Kester L, van Oudenaarden A
Nat Methods. 2014 (6): 637-640
Single-cell transcriptomics has recently emerged as a powerful
technology to explore gene expression heterogeneity among single cells.
Here we identify two major sources of technical variability: sampling
noise and global cell-to-cell variation in sequencing efficiency. We
propose noise models to correct for this, which we validate using
single-molecule FISH. We demonstrate that gene expression variability
in mouse embryonic stem cells depends on the culture condition.
|Image-based transcriptomics in thousands of
single human cells at single-molecule resolution
Battich N, Stoeger T, Pelkmans L.
Nat Methods. 2013 (11): 11127-11133
Fluorescence in situ hybridization (FISH) is widely used to obtain
information about transcript copy number and subcellular localization
in single cells. However, current approaches do not readily scale to
the analysis of whole transcriptomes. Here we show that branched DNA
technology combined with automated liquid handling, high-content
imaging and quantitative image analysis allows highly reproducible
quantification of transcript abundance in thousands of single cells at
single-molecule resolution. In addition, it allows extraction of a
multivariate feature set quantifying subcellular patterning and spatial
properties of transcripts and their cell-to-cell variability. This has
multiple implications for the functional interpretation of cell-to-cell
variability in gene expression and enables the unbiased identification
of functionally relevant in situ signatures of the transcriptome
without the need for perturbations. Because this method can be
incorporated in a wide variety of high-throughput image-based
approaches, we expect it to be broadly applicable.
|Cell Biology. Using cell-to-cell
variability - a new era in molecular biology
Institute of Molecular Life Sciences, University of Zurich,
Science. 2012 Apr 27;336(6080): 425-426
|Genomic analysis at the single-cell level
Kalisky T, Blainey P, Quake SR.
Department of Bioengineering, Stanford University and Howard Hughes
Medical Institute, Stanford, California 94305, USA
Annu Rev Genet. 2011;45: 431-445
Studying complex biological systems such as a developing embryo, a
tumor, or a microbial ecosystem often involves understanding the
behavior and heterogeneity of the individual cells that constitute the
system and their interactions. In this review, we discuss a variety of
approaches to single-cell genomic analysis.
|A single molecule view of gene expression
Larson DR, Singer RH, Zenklusen D.
Department of Anatomy and Structural Biology and The Gruss-Lipper
Biophotonics Center, Albert Einstein College of Medicine, Bronx, New
York 10461, USA.
Trends Cell Biol. 2009 Nov;19(11):630-637
Analyzing the expression of single genes in single cells appears
minimalistic in comparison to gene expression studies based on more
global approaches. However, stimulated by advances in imaging
technologies, single-cell studies have become an essential tool in
understanding the rules that govern gene expression. This quantitative
view of single-cell gene expression is based on counting mRNAs in
single cells, monitoring transcription in real time, and visualizing
single proteins. Parallel advances in mathematical models based on
stochastic, discrete descriptions of biochemical processes have
provided crucial insights into the underlying cellular mechanisms that
control expression. The view that has emerged is rooted in a
probabilistic understanding of cellular processes that quantitatively
explains both the mean and the variation observed in gene-expression
patterns among single cells. Thus, the close coupling between imaging
and mathematical theory has established single-cell analysis as an
essential branch of systems biology.
|Single-cell gene-expression profiling and
its potential diagnostic applications
Ståhlberg A, Kubista M, Aman P.
Sahlgrenska Cancer Center, Department of Pathology, Sahlgrenska Academy
at University of Gothenburg, Box 425, 40530 Gothenburg, Sweden
Expert Rev Mol Diagn. 2011 (7): 735-740
Gene-expression profiling has been successfully applied in various
diagnostic applications, but its full capacity is yet to be realized.
Samples are generally prepared from a mixture of different cells that
are present in unknown proportions. Cells are, in many aspects, unique
in their characteristics and this heterogeneity confounds the
expression profile. The development of new and robust techniques to
measure gene expression in single cells opens new avenues in molecular
medicine. Today, gene-expression profiles of individual cells can be
measured with high precision and accuracy, identifying different cell
types as well as revealing heterogeneity among cells of the same kind.
Here, we review practical aspects of single-cell gene-expression
profiling using reverse transcription quantitative real-time PCR and
its potential use in diagnostics.
|Multimarker gene analysis of circulating
tumor cells in pancreatic cancer patients: a feasibility study
de Albuquerque A, Kubisch I, Breier G, Stamminger G, Fersis N, Eichler
A, Kaul S, Stölzel U.
Department of Pathology, Technische Universität Dresden, Dresden,
Oncology. 2012;82(1): 3-10
OBJECTIVE: The aim of this study was to develop an
immunomagnetic/real-time reverse transcriptase polymerase chain
reaction (RT-PCR) assay and assess its clinical value for the molecular
detection of circulating tumor cells (CTCs) in peripheral blood of
pancreatic cancer patients.
METHODS: The presence of CTCs was evaluated in 34 pancreatic cancer
patients before systemic therapy and in 40 healthy controls, through
immunomagnetic enrichment, using the antibodies BM7 and VU1D9
[targeting mucin 1 and epithelial cell adhesion molecule (EpCAM),
respectively], followed by real-time RT-PCR analysis of the genes
KRT19, MUC1, EPCAM, CEACAM5 and BIRC5.
RESULTS: The developed assay showed high specificity, as none of the
healthy controls were found to be positive for the multimarker gene
panel. CTCs were detected in 47.1% of the pancreatic cancer patients
before the beginning of systemic treatment. Shorter median
progression-free survival (PFS) was observed for patients who had at
least one detectable tumor-associated transcript, compared with
patients who were CTC negative. Median PFS time was 66.0 days [95%
confidence interval (CI) 44.8-87.2] for patients with baseline CTC
positivity and 138.0 days (95% CI 124.1-151.9) for CTC-negative
patients (p = 0.01, log-rank test).
CONCLUSION: Our results suggest that in addition to the current
prognostic methods, CTC analysis represents a potential complementary
tool for prediction of outcome in pancreatic cancer patients.
|Mammalian genes are transcribed with widely
different bursting kinetics
Suter DM, Molina N, Gatfield D, Schneider K, Schibler U, Naef F.
Department of Molecular Biology, Sciences III, University of Geneva, 30
Quai Ernest Ansermet, 1211 Geneva, Switzerland.
Science. 2011 332(6028): 472-474
In prokaryotes and eukaryotes, most genes appear to be transcribed
during short periods called transcriptional bursts, interspersed by
silent intervals. We describe how such bursts generate gene-specific
temporal patterns of messenger RNA (mRNA) synthesis in mammalian cells.
To monitor transcription at high temporal resolution, we established
various gene trap cell lines and transgenic cell lines expressing a
short-lived luciferase protein from an unstable mRNA, and recorded
bioluminescence in real time in single cells. Mathematical modeling
identified gene-specific on- and off-switching rates in transcriptional
activity and mean numbers of mRNAs produced during the bursts.
Transcriptional kinetics were markedly altered by cis-regulatory DNA
elements. Our analysis demonstrated that bursting kinetics are highly
gene-specific, reflecting refractory periods during which genes stay
inactive for a certain time before switching on again.
|Measuring single-cell gene expression
dynamics in bacteria using fluorescence time-lapse microscopy
Young JW, Locke JC, Altinok A, Rosenfeld N, Bacarian T, Swain PS,
Mjolsness E, Elowitz MB.
Division of Biology, California Institute of Technology, Pasadena, USA.
Nat Protoc. 2011 7(1): 80-88
Quantitative single-cell time-lapse microscopy is a powerful method for
analyzing gene circuit dynamics and heterogeneous cell behavior. We
describe the application of this method to imaging bacteria by using an
automated microscopy system. This protocol has been used to analyze
sporulation and competence differentiation in Bacillus subtilis, and to
quantify gene regulation and its fluctuations in individual Escherichia
coli cells. The protocol involves seeding and growing bacteria on small
agarose pads and imaging the resulting microcolonies. Images are then
reviewed and analyzed using our laboratory's custom MATLAB analysis
code, which segments and tracks cells in a frame-to-frame method. This
process yields quantitative expression data on cell lineages, which can
illustrate dynamic expression profiles and facilitate mathematical
models of gene circuits. With fast-growing bacteria, such as E. coli or
B. subtilis, image acquisition can be completed in 1 d, with an
additional 1-2 d for progressing through the analysis procedure.
|Quantification noise in single cell
Reiter M, Kirchner B, Müller H, Holzhauer C, Mann W, Pfaffl MW.
Nucleic Acids Res. 2011 Oct;39(18):e124
In quantitative single-cell studies, the critical part is the low
amount of nucleic acids present and the resulting experimental
variations. In addition biological data obtained from heterogeneous
tissue are not reflecting the expression behaviour of every
single-cell. These variations can be derived from natural biological
variance or can be introduced externally. Both have negative effects on
the quantification result. The aim of
this study is to make quantitative single-cell studies more transparent
and reliable in order to fulfil the MIQE guidelines at the single-cell
level. The technical variability introduced by RT,
pre-amplification, evaporation, biological material and qPCR itself was
evaluated by using RNA or DNA standards. Secondly, the biological
expression variances of GAPDH, TNFα, IL-1β, TLR4 were measured by mRNA
profiling experiment in single lymphocytes. The used quantification
setup was sensitive enough to detect single standard copies and
transcripts out of one solitary cell. Most variability was introduced
by RT, followed by evaporation, and pre-amplification. The qPCR
analysis and the biological matrix introduced only minor variability.
Both conducted studies impressively demonstrate the heterogeneity of
expression patterns in individual cells and showed clearly today's
limitation in quantitative single-cell expression analysis.
molecular programs by stochastic profiling
Janes KA, Wang CC, Holmberg KJ, Cabral K, Brugge JS.
Department of Cell Biology, Harvard Medical School, Boston,
Nat Methods. 2010 Apr;7(4): 311-317
Cells in tissues can be morphologically indistinguishable yet show
molecular expression patterns that are remarkably heterogeneous. Here
we describe an approach to comprehensively identify co-regulated,
heterogeneously expressed genes among cells that otherwise appear
identical. The technique, called stochastic profiling, involves
repeated, random selection of very small cell populations via
laser-capture microdissection followed by a customized single-cell
amplification procedure and transcriptional profiling. Fluctuations in
the resulting gene-expression measurements are then analyzed
statistically to identify transcripts that are heterogeneously
coexpressed. We stochastically profiled matrix-attached human
epithelial cells in a three-dimensional culture model of mammary-acinar
morphogenesis. Of 4,557 transcripts, we identified 547 genes with
strong cell-to-cell expression differences. Clustering of this
heterogeneous subset revealed several molecular 'programs' implicated
in protein biosynthesis, oxidative-stress responses and NF-kappaB
signaling, which we independently confirmed by RNA fluorescence in situ
hybridization. Thus, stochastic profiling can reveal single-cell
heterogeneities without the need to measure expression in individual
|High-throughput microfluidic single-cell
White AK, VanInsberghe M, Petriv OI, Hamidi M, Sikorski D, Marra MA,
Piret J, Aparicio S, Hansen CL.
Centre for High-Throughput Biology, University of British Columbia,
Vancouver, BC, Canada V6T 1Z4.
Proc Natl Acad Sci U S A. 2011 Aug 23;108(34): 13999-134004
A long-sought milestone in microfluidics research has been the
development of integrated technology for scalable analysis of
transcription in single cells. Here we present a fully integrated
microfluidic device capable of performing high-precision RT-qPCR
measurements of gene expression from hundreds of single cells per run.
Our device executes all steps of single-cell processing, including cell
capture, cell lysis, reverse transcription, and quantitative PCR. In
addition to higher throughput and reduced cost, we show that nanoliter
volume processing reduced measurement noise, increased sensitivity, and
provided single nucleotide specificity. We apply this technology to
3,300 single-cell measurements of (i) miRNA expression in K562 cells,
(ii) coregulation of a miRNA and one of its target transcripts during
differentiation in embryonic stem cells, and (iii) single nucleotide
variant detection in primary lobular breast cancer cells. The core
functionality established here provides the foundation from which a
variety of on-chip single-cell transcription analyses will be developed.
|RNA-Seq analysis to capture the
transcriptome landscape of a single cell
Tang F, Barbacioru C, Nordman E, Li B, Xu N, Bashkirov VI, Lao K,
Wellcome Trust/Cancer Research UK Gurdon Institute of Cancer and
Developmental Biology, University of Cambridge, Cambridge, UK.
Nat Protoc. 2010 Mar;5(3): 516-535
We describe here a protocol for digital transcriptome analysis in a
single mouse oocyte and blastomere using a deep-sequencing approach. In
this method, individual cells are isolated and transferred into lysate
buffer by mouth pipette, followed by reverse transcription carried out
directly on the whole cell lysate. Free primers are removed by
exonuclease I and a poly(A) tail is added to the 3' end of the
first-strand cDNAs by terminal deoxynucleotidyl transferase.
Single-cell cDNAs are then amplified by 20 + 9 cycles of PCR. The
resulting 100-200 ng of amplified cDNAs are used to construct a
sequencing library, which can be used for deep sequencing using the
SOLiD system. Compared with cDNA microarray techniques, our assay can
capture up to 75% more genes expressed in early embryos. This protocol
can generate deep-sequencing libraries for 16 single-cell samples
within 6 d.
|Development and applications of single-cell
Tang F, Lao K, Surani MA.
Wellcome Trust/Cancer Research UK Gurdon Institute of Cancer and
Developmental Biology, University of Cambridge, Cambridge, UK.
Nat Methods. 2011 8(4 Suppl): S6-11
Dissecting the relationship between genotype and phenotype is one of
the central goals in developmental biology and medicine. Transcriptome
analysis is a powerful strategy to connect genotype to phenotype of a
cell. Here we review the history, progress, potential applications and
future developments of single-cell transcriptome analysis. In
combination with live cell imaging and lineage tracing, it will be
possible to decipher the full gene expression network underlying
physiological functions of individual cells in embryos and adults, and
to study diseases.
|Quantitative RT-PCR gene expression
analysis of laser microdissected tissue samples
Erickson HS, Albert PS, Gillespie JW, Rodriguez-Canales J, Marston
Linehan W, Pinto PA, Chuaqui RF, Emmert-Buck MR.
Pathogenetics Unit, Laboratory of Pathology and Urologic Oncology
Branch, National Cancer Institute, NIH, Bethesda, MD, USA.
Nat Protoc. 2009; 4(6): 902-922
Quantitative reverse transcription-polymerase chain reaction (qRT-PCR)
is a valuable tool for measuring gene expression in biological samples.
However, unique challenges are encountered when studies are performed
on cells microdissected from tissues derived from animal models or the
clinic, including specimen-related issues, variability of RNA template
quality and quantity, and normalization. qRT-PCR using small amounts of
mRNA derived from dissected cell populations requires adaptation of
standard methods to allow meaningful comparisons across sample sets.
The protocol described here presents the rationale, technical steps,
normalization strategy and data analysis necessary to generate reliable
gene expression measurements of transcripts from dissected samples. The
entire protocol from tissue microdissection through qRT-PCR analysis
requires approximately 16 h.
|mRNA and microRNA expression profiles in
circulating tumor cells and primary tumors of metastatic breast cancer
Sieuwerts AM, Mostert B, Bolt-de Vries J, Peeters D, de Jongh FE,
Stouthard JM, Dirix LY, van Dam PA, Van Galen A, de Weerd V, Kraan J,
van der Spoel P, Ramírez-Moreno R, van Deurzen CH, Smid M, Yu
JX, Jiang J, Wang Y, Gratama JW, Sleijfer S, Foekens JA, Martens JW.
Department of Medical Oncology, Josephine Nefkens Institute and Cancer
Genomics Centre, Rotterdam, The Netherlands.
Clin Cancer Res. 2011 Jun 1;17(11): 3600-3618
PURPOSE: Molecular characterization of circulating tumor cells (CTC)
holds great promise. Unfortunately, routinely isolated CTC fractions
currently still contain contaminating leukocytes, which makes
CTC-specific molecular characterization extremely challenging. In this
study, we determined mRNA and microRNA (miRNA) expression of
potentially CTC-specific genes that are considered to be clinically
relevant in breast cancer.
EXPERIMENTAL DESIGN: CTCs were isolated with the epithelial cell
adhesion molecule-based CellSearch Profile Kit. Selected genes were
measured by real-time reverse transcriptase PCR in CTCs of 50
metastatic breast cancer patients collected before starting first-line
systemic therapy in blood from 53 healthy blood donors (HBD) and in
primary tumors of 8 of the patients. The molecular profiles were
associated with CTC counts and clinical parameters and compared with
the profiles generated from the corresponding primary tumors.
RESULTS: We identified 55 mRNAs and 10 miRNAs more abundantly expressed
in samples from 32 patients with at least 5 CTCs in 7.5 mL of blood
compared with samples from 9 patients without detectable CTCs and HBDs.
Clustering analysis resulted in 4 different patient clusters
characterized by 5 distinct gene clusters. Twice the number of patients
from cluster 2 to 4 had developed both visceral and nonvisceral
metastases. Comparing transcript levels in CTCs with those measured in
corresponding primary tumors showed clinically relevant discrepancies
in estrogen receptor and HER2 levels.
CONCLUSIONS: Our study shows that molecular profiling of low numbers of
CTCs in a high background of leukocytes is feasible and shows promise
for further studies on the clinical relevance of molecular
characterization of CTCs.
|Comprehensive qPCR profiling of gene
expression in single neuronal cells
Citri A, Pang ZP, Südhof TC, Wernig M, Malenka RC.
Department of Psychiatry and Behavioral Sciences, Stanford University
School of Medicine, California, USA
Nat Protoc. 2011 Dec 22;7(1): 118-127
A major challenge in neuronal stem cell biology lies in
characterization of lineage-specific reprogrammed human neuronal cells,
a process that necessitates the use of an assay sensitive to the
single-cell level. Single-cell gene profiling can provide definitive
evidence regarding the conversion of one cell type into another at a
high level of resolution. The protocol we describe uses Fluidigm
Biomark dynamic arrays for high-throughput expression profiling from
single neuronal cells, assaying up to 96 independent samples with up to
96 quantitative PCR (qPCR) probes (equivalent to 9,216 reactions) in a
single experiment, which can be completed within 2-3 d. The protocol
enables simple and cost-effective profiling of several hundred
transcripts from a single cell, and it could have numerous utilities.
|Single cell transcriptomics of neighboring
hyphae of Aspergillus niger
de Bekker C, Bruning O, Jonker MJ, Breit TM, Wösten HA.
Microbiology and Kluyver Centre for Genomics of Industrial
Fermentations, Institute of Biomembranes, Utrecht University, Padualaan
8, 3584 CH Utrecht, The Netherlands.
Genome Biol. 2011 12(8): R71
Single cell profiling was performed to assess differences in RNA
accumulation in neighboring hyphae of the fungus Aspergillus niger. A
protocol was developed to isolate and amplify RNA from single hyphae or
parts thereof. Microarray analysis resulted in a present call for 4 to
7% of the A. niger genes, of which 12% showed heterogeneous RNA levels.
These genes belonged to a wide range of gene categories.
|RT-qPCR based quantitative analysis of gene
expression in single bacterial cells
Gao W, Zhang W, Meldrum DR.
Center for Ecogenomics, The Biodesign Institute, Arizona State
University, Tempe, AZ 85287-6501, United States.
J Microbiol Methods. 2011 Jun;85(3): 221-227
Recent evidence suggests that cell-to-cell difference at the gene
expression level is an order of magnitude greater than previously
thought even for isogenic bacterial populations. Such gene expression
heterogeneity determines the fate of individual bacterial cells in
populations and could also affect the ultimate fate of populations
themselves. To quantify the heterogeneity and its biological
significance, quantitative methods to measure gene expression in single
bacterial cells are needed. In this work, we developed two SYBR
Green-based RT-qPCR methods to determine gene expression directly in
single bacterial cells. The first method involves a single-tube
operation that can analyze one gene from each bacterial cell. The
second method is featured by a two-stage protocol that consists of RNA
isolation from a single bacterial cell and cDNA synthesis in the first
stage, and qPCR in the second stage, which allows determination of
expression level of multiple genes simultaneously for single bacterial
cells of both gram-positive and negative. We applied the methods to
stress-treated (i.e. low pH and high temperature) Escherichia coli
populations. The reproducible results demonstrated that the method is
sensitive enough not only for measuring cellular responses at the
single-cell level, but also for revealing gene expression heterogeneity
among the bacterial cells. Furthermore, our results showed that the
two-stage method can reproducibly measure multiple highly expressed
genes from a single E. coli cell, which exhibits important foundation
for future development of a high throughput and lab-on-chips
whole-genome RT-qPCR methodology for single bacterial cells.
|Circulating tumor cells in breast cancer:
detection systems, molecular characterization, and future challenges
Lianidou ES, Markou A.
Laboratory of Analytical Chemistry, Department of Chemistry, University
of Athens, Athens, Greece
Clin Chem. 2011 Sep;57(9): 1242-1255
BACKGROUND: Circulating tumor cell (CTC) analysis is a promising new
diagnostic field for estimating the risk for metastatic relapse and
metastatic progression in patients with cancer.
CONTENT: Different analytical systems for CTC isolation and detection
have been developed as immunocytochemical and molecular assays, most
including separation steps by size or biological characteristics, such
as expression of epithelial- or cancer-specific markers. Recent
technical advancements in CTC detection and characterization include
methods based on multiplex reverse-transcription quantitative PCR and
approaches based on imaging and microfilter and microchip devices. New
areas of research are directed toward developing novel assays for CTC
molecular characterization. QC is an important issue for CTC analysis,
and standardization of micrometastatic cell detection and
characterization methodologies is important for the incorporation of
CTCs into prospective clinical trials to test their clinical utility.
The molecular characterization of CTCs can provide important
information on the molecular and biological nature of these cells, such
as the status of hormone receptors and epidermal and other growth
factor receptor family members, and indications of stem-cell
characteristics. This information is important for the identification
of therapeutic targets and resistance mechanisms in CTCs as well as for
the stratification of patients and real-time monitoring of systemic
SUMMARY: CTC analysis can be used as a liquid biopsy approach for
prognostic and predictive purposes in breast and other cancers. In this
review we focus on state-of-the-art technology platforms for CTC
isolation, imaging, and detection; QC of CTC analysis; and ongoing
challenges for the molecular characterization of CTCs.
|Molecular characterization of circulating
tumor cells in breast cancer: challenges and promises for
individualized cancer treatment
Lianidou ES, Markou A, Strati A.
Analysis of Circulating Tumor Cells Lab, Laboratory of Analytical
Chemistry, Department of Chemistry, University of Athens, 15771,
Cancer Metastasis Rev. 2012 Jun 13
Blood testing using Circulating Tumor Cells (CTCs) has emerged as one
of the hottest fields in cancer diagnosis. Research on CTCs present
nowadays a challenge, as these cells are well defined targets for
understanding tumour biology and improving cancer treatment. The
presence of tumor cells in patient's bone marrow or peripheral blood is
an early indicator of metastasis and may signal tumor spread sooner
than clinical symptoms appear and imaging results confirm a poor
prognosis. CTC enumeration can serve as a "liquid biopsy" and an early
marker to assess response to systemic therapy. Definition of biomarkers
based on comprehensive characterization of CTCs has a strong potential
to be translated to individualized targeted treatments and spare breast
cancer patients unnecessary and ineffective therapies but also to
reduce the costs for the health system and to downsize the extent and
length of clinical studies. In this review, we briefly summarize recent
studies on the molecular characterization of circulating tumor cells in
breast cancer and discuss challenges and promises of CTCs for
individualized cancer treatment.
|Gene expression profile of circulating
tumor cells in breast cancer by RT-qPCR
Strati A, Markou A, Parisi C, Politaki E, Mavroudis D, Georgoulias V,
Department of Chemistry, University of Athens, University Campus, 15771
BMC Cancer. 2011 11:422.
BACKGROUND: Circulating tumor cells (CTCs) have been associated with
prognosis especially in breast cancer and have been proposed as a
liquid biopsy for repeated follow up examinations. Molecular
characterization of CTCs is difficult to address since they are very
rare and the amount of available sample is very limited.
METHODS: We quantified by RT-qPCR CK-19, MAGE-A3, HER-2, TWIST1, hTERT
α+β+, and mammaglobin gene transcripts in immunomagnetically positively
selected CTCs from 92 breast cancer patients, and 28 healthy
individuals. We also compared our results with the CellSearch system in
33 of these patients with early breast cancer.
RESULTS: RT-qPCR is highly sensitive and specific and can detect the
expression of each individual gene at the one cell level. None of the
genes tested was detected in the group of healthy donors. In 66
operable breast cancer patients, CK-19 was detected in 42.4%, HER-2 in
13.6%, MAGE-A3 in 21.2%, hMAM in 13.6%, TWIST-1 in 42.4%, and hTERT
α+β+ in 10.2%. In 26 patients with verified metastasis, CK-19 was
detected in 53.8%, HER-2 in 19.2%, MAGE-A3 in 15.4%, hMAM in 30.8%,
TWIST-1 in 38.5% and hTERT α+β+in 19.2%. Our preliminary data on the
comparison between RT-qPCR and CellSearch in 33 early breast cancer
patients showed that RT-qPCR gives more positive results in respect to
CONCLUSIONS: Molecular characterization of CTCs has revealed a
remarkable heterogeneity of gene expression between breast cancer
patients. In a small percentage of patients, CTCs were positive for all
six genes tested, while in some patients only one of these genes was
expressed. The clinical significance of these findings in early breast
cancer remains to be elucidated when the clinical outcome for these
patients is known.
|Single-cell gene-expression profiling
reveals qualitatively distinct CD8 T cells elicited by different
Flatz L, Roychoudhuri R, Honda M, Filali-Mouhim A, Goulet JP, Kettaf N,
Lin M, Roederer M, Haddad EK, Sékaly RP, Nabel GJ.
Vaccine Research Center, National Institute for Allergy and Infectious
Diseases, National Institutes of Health, Bethesda, MD 20892-3005, USA.
Proc Natl Acad Sci U S A. 2011 108(14): 5724-5729
CD8 T cells play a key role in mediating protective immunity against
selected pathogens after vaccination. Understanding the mechanism of
this protection is dependent upon definition of the heterogeneity and
complexity of cellular immune responses generated by different
vaccines. Here, we identify previously unrecognized subsets of CD8 T
cells based upon analysis of gene-expression patterns within single
cells and show that they are differentially induced by different
vaccines. Three prime-boost vector combinations encoding HIV Env
stimulated antigen-specific CD8 T-cell populations of similar
magnitude, phenotype, and functionality. Remarkably, however, analysis
of single-cell gene-expression profiles enabled discrimination of a
majority of central memory (CM) and effector memory (EM) CD8 T cells
elicited by the three vaccines. Subsets of T cells could be defined
based on their expression of Eomes, Cxcr3, and Ccr7, or Klrk1, Klrg1,
and Ccr5 in CM and EM cells, respectively. Of CM cells elicited by DNA
prime-recombinant adenoviral (rAd) boost vectors, 67% were Eomes(-)
Ccr7(+) Cxcr3(-), in contrast to only 7% and 2% stimulated by rAd5-rAd5
or rAd-LCMV, respectively. Of EM cells elicited by DNA-rAd, 74% were
Klrk1(-) Klrg1(-)Ccr5(-) compared with only 26% and 20% for rAd5-rAd5
or rAd5-LCMV. Definition by single-cell gene profiling of specific CM
and EM CD8 T-cell subsets that are differentially induced by different
gene-based vaccines will facilitate the design and evaluation of
vaccines, as well as enable our understanding of mechanisms of
|High throughput single cell expression
profiling: Taking a closerlook on biological response
Mikael Kubista, Linda Strömbom, David Svec,Vendula Rusnakova &
TATAA Biocenter, Gothenburg, Sweden and the Institute of Biotechnology,
European Pharmaceutical ReviewVolume 16, Issue 2, 2011
Molecular analysis of tissue and in most cases also of bodily fluids is
complicatedbecause of tissue heterogeneity and the presence of many
different cell types.Even cells of apparently the same type show
substantial variation in geneexpression under virtually identical
conditions. When analysing classical samplesbased on tens of thousands
of cells, this natural variability among cells is lost.With the advent
of real-time quantitative polymerase chain reaction (qPCR), wehave a
most powerful tool to study diversity on the single cell level and
candetect rare cells that are critical to treatment or survival.
|Quantification of circulating endothelial
and progenitor cells: comparison of quantitative PCR and four-channel
Steurer M, Kern J, Zitt M, Amberger A, Bauer M, Gastl G, Untergasser G,
Tumor Biology and Angiogenesis Laboratory, Division of Hematology and
Oncology, Innrain 66, Innsbruck Medical University, 6020 Innsbruck,
BMC Res Notes. 2008 Aug 28;1:71.
BACKGROUND: Circulating endothelial cells (CEC) and endothelial
precursor cells (CEP) have been suggested as markers for angiogenesis
in cancer. However, CEC/CEP represent a tiny and heterogeneous cell
population, rendering a standardized monitoring in peripheral blood
difficult. Thus, we investigated whether a PCR-based detection method
of CEC/CEP might overcome the limitations of rare-event flow cytometry.
FINDINGS: To test the sensitivity of both assays endothelial colony
forming cell clones (ECFC) and cord blood derived CD45- CD34+
progenitor cells were spiked into peripheral blood mononuclear cells
(PBMNC) of healthy volunteers. Samples were analyzed for the expression
of CD45, CD31, CD34, KDR or CD133 by 4-color flow cytometry and for the
expression of CD34, CD133, KDR and CD144 by qPCR. Applying flow
cytometry, spiked ECFC and progenitor cells were detectable at
frequencies >/= 0.01%, whereas by qPCR a detection limit of 0.001%
was achievable. Furthermore, PBMNC from healthy controls (n = 30),
patients with locally advanced rectal cancer (n = 20) and metastatic
non-small cell lung cancer (NSCLC, n = 25) were analyzed. No increase
of CEC/CEP was detectable by flow cytometry. Furthermore, only CD34 and
KDR gene expression was significantly elevated in patients with
metastatic NSCLC. However, both markers are not specific for
CONCLUSION: QPCR is more sensitive, but less specific than 4-channel
flow cytometry for the detection of CEC/CEP cell types. However, both
methods failed to reliably detect an increase of CEC/CEP in tumor
patients. Thus, more specific CEC/CEP markers are needed to validate
and improve the detection of these rare cell types by PCR-based assays.
blastocysts derived from cumulus-free in vitro matured human oocytes
McElroy SL, Byrne JA, Chavez SL, Behr B, Hsueh AJ, Westphal LM, Pera RA.
Center for Human Embryonic Stem Cell Research and Education, Institute
for Stem Cell Biology and Regenerative Medicine, Stanford University,
Palo Alto, California, United States of America.
PLoS One. 2010 Jun 7;5(6):e10979.
BACKGROUND: Approximately 20% of oocytes are classified as immature and
discarded following intracytoplasmic sperm injection (ICSI) procedures.
These oocytes are obtained from gonadotropin-stimulated patients, and
are routinely removed from the cumulus cells which normally would
mature the oocytes. Given the ready access to these human oocytes, they
represent a potential resource for both clinical and basic science
application. However culture conditions for the maturation of
cumulus-free oocytes have not been optimized. We aimed to improve
maturation conditions for cumulus-free oocytes via culture with ovarian
paracrine/autocrine factors identified by single cell analysis.
METHODOLOGY/PRINCIPAL FINDING: Immature human oocytes were matured in
vitro via supplementation with ovarian paracrine/autocrine factors that
were selected based on expression of ligands in the cumulus cells and
their corresponding receptors in oocytes. Matured oocytes were
artificially activated to assess developmental competence. Gene
expression profiles of parthenotes were compared to IVF/ICSI embryos at
morula and blastocyst stages. Following incubation in medium
supplemented with ovarian factors (BDNF, IGF-I, estradiol, GDNF, FGF2
and leptin), a greater percentage of oocytes demonstrated nuclear
maturation and subsequently, underwent parthenogenesis relative to
control. Similarly, cytoplasmic maturation was also improved as
indicated by development to blastocyst stage. Parthenogenic blastocysts
exhibited mRNA expression profiles similar to those of blastocysts
obtained after IVF/ICSI with the exception for MKLP2 and PEG1.
CONCLUSIONS/SIGNIFICANCE: Human cumulus-free oocytes from
hormone-stimulated cycles are capable of developing to blastocysts when
cultured with ovarian factor supplementation. Our improved IVM culture
conditions may be used for obtaining mature oocytes for clinical
purposes and/or for derivation of embryonic stem cells following
parthenogenesis or nuclear transfer.