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New papers with
focus on single-cell gene expression noise:
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Stochastic gene
expression in a single cell
Elowitz MB, Levine AJ, Siggia ED, Swain PS.
Science. 2002 Aug 16;297(5584): 1183-1186.
Laboratory of Cancer Biology, Center for Studies in
Physics and Biology, Rockefeller University, New York, NY 10021, USA
Clonal populations
of cells exhibit substantial phenotypic variation. Such heterogeneity
can be essential for many biological processes and is conjectured to
arise from stochasticity, or noise, in gene expression. We constructed
strains of Escherichia coli that enable detection of noise and
discrimination between the two mechanisms by which it is generated.
Both stochasticity inherent in the biochemical process of gene
expression (intrinsic noise) and fluctuations in other cellular
components (extrinsic noise) contribute substantially to overall
variation. Transcription rate, regulatory dynamics, and genetic factors
control the amplitude of noise. These results establish a quantitative
foundation for modeling noise in genetic networks and reveal how low
intracellular copy numbers of molecules can fundamentally limit the
precision of gene regulation.
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Nature, nurture, or
chance: stochastic gene expression and its consequences
Raj A, van Oudenaarden A.
Cell. 2008 Oct 17;135(2):216-26.
Department of Physics, Massachusetts Institute of
Technology, Cambridge, MA 02139, USA.
Gene expression is
a fundamentally stochastic process, with randomness in transcription
and translation leading to cell-to-cell variations in mRNA and protein
levels. This variation appears in organisms ranging from microbes to
metazoans, and its characteristics depend both on the biophysical
parameters governing gene expression and on gene network structure.
Stochastic gene expression has important consequences for cellular
function, being beneficial in some contexts and harmful in others.
These situations include the stress response, metabolism, development,
the cell cycle, circadian rhythms, and aging.
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Noise in Gene
Expression: Origins, Consequences, and Control
Jonathan M. Raser & Erin K. O'Shea
Science 23 September 2005:
Vol. 309. no. 5743, pp. 2010 - 2013
Genetically
identical cells and organisms exhibit remarkable diversity even when
they have identical histories of environmental exposure. Noise, or
variation, in the process of gene expression may contribute to this
phenotypic variability. Recent studies suggest that this noise has
multiple sources, including the stochastic or inherently random nature
of the biochemical reactions of gene expression. In this review, we
summarize noise terminology and comment on recent investigations into
the sources, consequences, and control of noise in gene expression.
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Use of high
throughput sequencing to observe genome dynamics at a single cell level
Parkhomchuk D, Amstislavskiy V, Soldatov A, Ogryzko
V.
Proc Natl Acad Sci U S A. 2009 Nov 23.
Department of Vertebrate Genomics, Max Planck
Institute for Molecular Genetics, Berlin, Germany.
With the
development of high throughput sequencing technology, it becomes
possible to directly analyze mutation distribution in a genome-wide
fashion, dissociating mutation rate measurements from the traditional
underlying assumptions. Here, we sequenced several genomes of
Escherichia coli from colonies obtained after chemical mutagenesis and
observed a strikingly nonrandom distribution of the induced mutations.
These include long stretches of exclusively G to A or C to T
transitions along the genome and orders of magnitude intra- and
intergenomic differences in mutation density. Whereas most of these
observations can be explained by the known features of enzymatic
processes, the others could reflect stochasticity in the molecular
processes at the single-cell level. Our results demonstrate how
analysis of the molecular records left in the genomes of the
descendants of an individual mutagenized cell allows for genome-scale
observations of fixation and segregation of mutations, as well as
recombination events, in the single genome of their progenitor.
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Transcriptional
noise and cellular heterogeneity in mammalian macrophages
Ramsey S, Ozinsky A, Clark A, Smith KD, de Atauri P,
Thorsson V, Orrell D, Bolouri H.
Philos Trans R Soc Lond B Biol Sci. 2006 Mar
29;361(1467):495-506.
Institute for Systems Biology 1441 North 34th
Street, Seattle, WA 98103-8904, USA.
Transcriptional
noise is known to play a crucial role in heterogeneity in bacteria and
yeast. Mammalian macrophages are known to exhibit cell-to-cell
variation in their responses to pathogens, but the source of this
heterogeneity is not known. We have developed a detailed stochastic
model of gene expression that takes into account scaling effects due to
cell size and genome complexity. We report the results of applying this
model to simulating gene expression variability in mammalian
macrophages, demonstrating a possible molecular basis for heterogeneity
in macrophage signalling responses. We note that the nature of
predicted transcriptional noise in macrophages is different from that
in yeast and bacteria. Some molecular interactions in yeast and
bacteria are thought to have evolved to minimize the effects of the
high-frequency noise observed in these species. Transcriptional noise
in macrophages results in slow changes to gene expression levels and
would not require the type of spike-filtering circuits observed in
yeast and bacteria.
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Stochastic
gene expression during cell differentiation: order from disorder?
Paldi A.
Cell Mol Life Sci. 2003 Sep;60(9): 1775-1778.
Institut Jacques Monod, INSERM E0367, Ecole Pratique
des Hautes Etudes, 2, place Jussieu, 75005 Paris, France.
Understanding cell
differentiation in multicellular organ-isms remains one of the central
questions of biology. Ac-cording to the prevailing view of contemporary
develop-mental biology, differentiation of multicellular organismsis
based on precisely regulated communication betweencells via diffusible
molecules or direct cell-to-cell con-tacts. These signals are the basis
of embryonic induction,where one cell instructs others to adopt a
particular de-velopmental fate. A molecular signal is supposed to
initi-ate differentiation by specifically activating one or sev-eral
regulatory genes, which, in turn, also specifically ac-tivate other
downstream regulator and/or effector genes. The activation of such a
regulatory cascade leads to theexpression of a new set of genes that
progressively guidesthe cell toward commitment into a lineage and
ultimatelyto its differentiated state. This process of
hierarchicallyordered and sequential expression of genes is usually
re-ferred to as a ‘genetic program’. The role of the regula-tory genes
is, of course, crucial, since they code for the‘instructions’of the
program in the form of transcriptionfactors that are able to bind
nucleotide sequence motifs inthe regulatory regions of the target genes
and initiate theprocess of transcription by recruiting the other
compo-nents of the transcription machinery. ... ... ...
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Resolving cell
population heterogeneity: real-time PCR for simultaneous multiplexed
gene detection in multiple single-cell samples
Diercks A, Kostner H, Ozinsky A.
PLoS One. 2009 Jul 27;4(7):e6326.
Institute for Systems Biology, Seattle, WA, USA.
Decoding the
complexity of multicellular organisms requires analytical procedures to
overcome the limitations of averaged measurements of cell populations,
which obscure inherent cell-cell heterogeneity and restrict the ability
to distinguish between the responses of individual cells within a
sample. For example, defining the timing, magnitude and the
coordination of cytokine responses in single cells is critical for
understanding the development of effective immunity. While approaches
to measure gene expression from single cells have been reported, the
absolute performance of these techniques has been difficult to assess,
which likely has limited their wider application. We describe a
straightforward method for simultaneously measuring the expression of
multiple genes in a multitude of single-cell samples using flow
cytometry, parallel cDNA synthesis, and quantification by real-time
PCR. We thoroughly assess the performance of the technique using mRNA
and DNA standards and cell samples, and demonstrate a detection
sensitivity of approximately 30 mRNA molecules per cell, and a
fractional error of 15%. Using this method, we expose unexpected
heterogeneity in the expression of 5 immune-related genes in sets of
single macrophages activated by different microbial stimuli. Further,
our analyses reveal that the expression of one 'pro-inflammatory'
cytokine is not predictive of the expression of another
'pro-inflammatory' cytokine within the same cell. These findings
demonstrate that single-cell approaches are essential for studying
coordinated gene expression in cell populations, and this generic and
easy-to-use quantitative method is applicable in other areas in biology
aimed at understanding the regulation of cellular responses.
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Circulating
tumour cells in clinical practice: Methods of detection and possible
characterization
Alunni-Fabbroni M, Sandri MT.
Methods. 2010 Apr;50(4):289-97. Epub 2010 Jan 29.
Beckman Coulter Biomedical GmbH, Sauerbruchstrasse
50 - 81377 Munich, Germany
Circulating Tumour
Cells (CTCs) can be released from
the primary tumour into the bloodstream and may colonize distant organs
giving rise to metastasis. The presence of CTCs in the blood has been
documented more than a century ago, and in the meanwhile various
methods have been described for their detection. Most of them require
an initial enrichment step, since CTCs are a very rare event. The
different technologies and also the differences among the screened
populations make the clinical significance of CTCs detection difficult
to interprete. Here we will review the different assays up to now
available for CTC detection and analysis. Moreover, we will focus on
the relevance of the clinical data, generated so far and based on the
CTCs analysis. Since the vast majority of data have been produced in
breast cancer patients, the review will focus especially on this
malignancy.
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Quantitative
transcription factor analysis of undifferentiated single human
embryonic stem cells.
Ståhlberg A, Bengtsson M, Hemberg M, Semb H.
Clin Chem. 2009 Dec;55(12): 2162-2170
Lundberg Laboratory for Cancer, Department of
Pathology, Sahlgrenska Academy at University of Gothenburg, Gothenburg,
Sweden.
BACKGROUND: Human
embryonic stem cells (hESCs) require expression of transcription factor
genes POU5F1 (POU class 5 homeobox 1), NANOG (Nanog homeobox), and SOX2
[SRY (sex determining region Y)-box 2] to maintain their capacity for
self-renewal and pluripotency. Because of the heterogeneous nature of
cell populations, it is desirable to study the gene regulation in
single cells. Large and potentially important fluctuations in a few
cells cannot be detected at the population scale with microarrays or
sequencing technologies. We used single-cell gene expression profiling
to study cell heterogeneity in hESCs.
METHODS: We
collected 47 single hESCs from cell line SA121 manually by glass
capillaries and 57 single hESCs from cell line HUES3 by flow cytometry.
Single hESCs were lysed and reverse-transcribed. Reverse-transcription
quantitative real-time PCR was then used to measure the expression
POU5F1, NANOG, SOX2, and the inhibitor of DNA binding genes ID1, ID2,
and ID3. A quantitative noise model was used to remove measurement
noise when pairwise correlations were estimated.
RESULTS: The
numbers of transcripts per cell varied >100-fold between cells and
showed lognormal features. POU5F1 expression positively correlated with
ID1 and ID3 expression (P < 0.05) but not with NANOG or SOX2
expression. When we accounted for measurement noise, SOX2 expression
was also correlated with ID1, ID2, and NANOG expression (P < 0.05).
CONCLUSIONS: We demonstrate an accurate method for transcription
profiling of individual hESCs. Cell-to-cell variability is large and is
at least partly nonrandom because we observed correlations between core
transcription factors. High fluctuations in gene expression may explain
why individual cells in a seemingly undifferentiated cell population
have different susceptibilities for inductive cues.
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Single cell analysis
of transcriptional activation dynamics
Rafalska-Metcalf IU, Powers SL, Joo LM, LeRoy G,
Janicki SM.
PLoS One. 2010 Apr 21;5(4): e10272.
Gene Expression and Regulation Program, The Wistar
Institute, Philadelphia, Pennsylvania, United States of America.
BACKGROUND: Gene
activation is thought to occur through a series of temporally defined
regulatory steps. However, this process has not been completely
evaluated in single living mammalian cells.
METHODOLOGY/PRINCIPAL FINDINGS: To investigate the
timing and coordination of gene activation events, we tracked the
recruitment of GCN5 (histone acetyltransferase), RNA polymerase II,
Brd2 and Brd4 (acetyl-lysine binding proteins), in relation to a
VP16-transcriptional activator, to a transcription site that can be
visualized in single living cells. All accumulated rapidly with the
VP16 activator as did the transcribed RNA. RNA was also detected at
significantly more transcription sites in cells expressing the
VP16-activator compared to a p53-activator. After alpha-amanitin
pre-treatment, the VP16-activator, GCN5, and Brd2 are still recruited
to the transcription site but the chromatin does not decondense.
CONCLUSIONS/SIGNIFICANCE: This study demonstrates
that a strong activator can rapidly overcome the condensed chromatin
structure of an inactive transcription site and supercede the expected
requirement for regulatory events to proceed in a temporally defined
order. Additionally, activator strength determines the number of cells
in which transcription is induced as well as the extent of chromatin
decondensation. As chromatin decondensation is significantly reduced
after alpha-amanitin pre-treatment, despite the recruitment of
transcriptional activation factors, this provides further evidence that
transcription drives large-scale chromatin decondensation.
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Single-cell gene
expression profiling using reverse transcription quantitative real-time
PCR
Ståhlberg A, Bengtsson M.
Methods. 2010 Apr;50(4): 282-288
Lundberg Laboratory for Cancer, Department of
Pathology, Sahlgrenska Academy at University of Gothenburg, Gula
Straket 8, 413 45 Gothenburg, Sweden
Even in an
apparently homogeneous population of cells there are considerable
differences between individual cells. A response to a stimulus of a
cell population or tissue may be consistent and gradual while the
single-cell response might be binary and apparently irregular. The
origin of this variability may be preprogrammed or stochastic and a
study of this phenomenon will require quantitative measurements of
individual cells. Here, we describe a method to collect dispersed
single cells either by glass capillaries or flow cytometry, followed by
quantitative mRNA profiling using reverse transcription and real-time
PCR. We present a single cell lysis protocol and optimized priming
conditions for reverse transcription. The large cell-to-cell
variability in single-cell gene expression measurements excludes it
from standard data analysis. Correlation studies can be used to find
common regulatory elements that are indistinguishable at the population
level. Single-cell gene expression profiling has the potential to
become common practice in many laboratories and a powerful research
tool for deeper understanding of molecular mechanisms.
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Spatial expression
profiles in the Xenopus laevis oocytes measured with qPCR tomography
Sindelka R, Sidova M, Svec D, Kubista M.
Methods. 2010 May;51(1): 87-91
Whitehead Institute, Cambridge, USA.
qPCR tomography
was developed to study mRNA localization in complex biological samples
that are embedded and cryo-sectioned. After total RNA extraction and
reverse transcription, the spatial profiles of mRNAs and other
functional RNAs were determined by qPCR. The Xenopus laevis oocyte was
selected as model, because of its large size (more than 1mm) and large
amount of total RNA (approximately 5microg). Fifteen sections along the
animal-vegetal axis were cut and prepared for quantification of 31 RNA
targets using the high-throughput real-time RT-PCR (qPCR) BioMark
platform. mRNAs were found to have two localization patterns,
animal/central or vegetal. Because of the high resolution in
sectioning, it was possible to distinguish two subgroups of the vegetal
gene patterns: germ plasm determinant pattern and profile of other
vegetal genes.
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Quantitative RT-PCR
gene expression analysis of laser microdissected tissue samples
Heidi S Erickson, Paul S Albert, John W Gillespie,
Jaime Rodriguez-Canales, W Marston Linehan, Peter A Pinto, Rodrigo F
Chuaqui & Michael R Emmert-Buck
Nature Protocols 4, - 902 - 922 (2009)
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 approx 16 h.
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Laser capture
microdissection and single-cell RT-PCR without RNA purification
Keays KM, Owens GP, Ritchie AM, Gilden DH, Burgoon
MP.
J Immunol Methods. 2005 Jul;302(1-2):90-8.
Department of Neurology, University of Colorado
Health Sciences Center,
4200 East 9th Avenue, Mail Stop B182, Denver, CO 80262, United States.
Chronic infectious
diseases of the central nervous system (CNS) are
characterized by intrathecal synthesis of increased amounts of
immunoglobulin G (IgG) directed against the agent that causes disease.
In other inflammatory CNS diseases such as multiple sclerosis and CNS
sarcoid, the targets of the humoral immune response are uncertain. To
identify the IgGs expressed by individual CD38(+) plasma cells seen in
human brain sections, we merged the techniques of laser capture
microdissection (LCM) and single-cell RT-PCR. Frozen brain sections
from a patient who died of subacute sclerosing panencephalitis (SSPE),
were rapidly immunostained and examined by LCM to dissect individual
CD38(+) cells. After cell lysis, we developed two techniques for
reverse-transcription (RT) of unpurified total RNA in the cell lysates.
The first method performed repeated and rapid freeze-thawing, followed
by centrifugation of the cell lysate into tubes for subsequent RT. The
second, more successful method performed RT in situ on
detergent-solubilized cells directly on the cap surface; subsequent
nested PCR identified heavy and light chain sequences expressed by
two-thirds of individually isolated plasma cells. These techniques will
streamline the identification of gene expression products in single
cells from complex tissues and have the potential to identify IgGs
expressed in the CNS of inflammatory diseases of unknown etiology.
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Imaging
intracellular RNA distribution and dynamics in living cells.
Sanjay Tyagi
Nature Methods vol 6 no 5 2009: 331
Powerful methods
now allow the imaging of specific mRNAs in living cells. These methods
enlist fluorescent proteins to illuminate mRNAs, use labeled
oligonucleotide probes and exploit aptamers that render organic dyes
fluorescent. The intracellular dynamics of mRNA synthesis, transport
and localization can be analyzed at higher temporal resolution with
these methods than has been possible with traditional fixed-cell or
biochemical approaches. These methods have also been adopted to
visualize and track single mRNA molecules in real time. This review
explores the promises and limitations of these methods.
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mRNA-Seq
whole-transcriptome analysis of a single cell.
Tang F, Barbacioru C, Wang Y, Nordman E, Lee C, Xu N, Wang X, Bodeau J,
Tuch BB, Siddiqui A, Lao K, Surani MA.
Wellcome Trust-Cancer Research UK Gurdon Institute of Cancer and
Developmental
Biology, University of Cambridge, Cambridge, UK.
Nat Methods. 2009 6(5): 377-82
Next-generation
sequencing technology is a powerful tool for transcriptome analysis.
However, under certain conditions, only a small amount of material is
available, which requires more sensitive techniques that can preferably
be used at the single-cell level. Here we describe a single-cell
digital gene expression profiling assay. Using our mRNA-Seq assay with
only a single mouse blastomere, we detected the expression of 75%
(5,270) more genes than microarray techniques and identified 1,753
previously unknown splice junctions called by at least 5 reads.
Moreover, 8-19% of the genes with multiple known transcript isoforms
expressed at least two isoforms in the same blastomere or oocyte, which
unambiguously demonstrated the complexity of the transcript variants at
whole-genome scale in individual cells. Finally, for Dicer1(-/-) and
Ago2(-/-) (Eif2c2(-/-)) oocytes, we found that 1,696 and 1,553 genes,
respectively, were abnormally upregulated compared to wild-type
controls, with 619 genes in common.
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Quantitative
analysis of gene expression in a single cell by qPCR.
Taniguchi K, Kajiyama T, Kambara H.
Hitachi Central Research Laboratory, Tokyo, Japan.
Nat Methods. 2009 6(7): 503-506
supl.
We developed a quantitative PCR method featuring a
reusable single-cell cDNA library immobilized on beads for measuring
the expression of multiple genes in a single cell. We used this method
to analyze multiple cDNA targets (from several copies to several
hundred thousand copies) with an experimental error of 15.9% or less.
This method is sufficiently accurate to investigate the heterogeneity
of single cells.
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Genomic
expression analysis by single-cell mRNA differential display of
quiescent
CD8
T cells from tumour-infiltrating lymphocytes obtained from in vivo
liver tumours.
Zhang W, Ding J, Qu Y, Hu H, Lin M, Datta A, Larson A, Liu GE, Li B.
Department of Biochemistry, Case Western Reserve University School of
Medicine,
Cleveland, OH 44106-4935, USA.
Immunology. 2009 May;127(1): 83-90.
We performed a genomic study combining single-cell
mRNA differential display and RNA subtractive hybridization to
elucidate CD8 T-cell quiescence/ignorance. By comparing actively
maintained quiescent CD8 T cells from liver tumour tumour-infiltrating
lymphocytes (TILs) with quiescent T cells at the single-cell level, we
identified differentially expressed candidate genes by high-throughput
screening and comparative analysis of expressed sequence tags (ESTs).
While genes for the T-cell receptor, tumour necrosis factor (TNF)
receptor, TNF-related apoptosis inducing ligand (TRAIL) and perforin
were down-regulated, key genes such as Tob, transforming growth factor
(TGF)-beta, lung Krüpple-like factor (LKLF), Sno-A, Ski, Myc,
Ets-2 repressor factor (ERF) and RE1-silencing transcription factor
(REST/NRSF) complex were highly expressed in the quiescent TIL CD8
cells. Real-time polymerase chain reaction (PCR) further confirmed
these results. A regulation model is proposed for actively maintained
quiescence in CD8 T cells, including three components: up-regulation of
the TGF-beta pathway, a shift in the MYC web and inhibition of the cell
cycle.
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Rac1
regulates pancreatic islet morphogenesis.
Greiner TU, Kesavan G, Stahlberg A, Semb H.
Stem Cell and Pancreas Developmental Biology, Stem
Cell Center, Lund University,
BMC B10, Klinikgatan 26, SE-221 84 Lund, Sweden.
BMC Dev Biol. 2009 Jan 6;9:2.
BACKGROUND:
Pancreatic islets of Langerhans originate from endocrine progenitors
within the pancreatic ductal epithelium. Concomitant with
differentiation of these progenitors into hormone-producing cells such
cells delaminate, aggregate and migrate away from the ductal
epithelium. The cellular and molecular mechanisms regulating islet cell
delamination and cell migration are poorly understood. Extensive
biochemical and cell biological studies using cultured cells
demonstrated that Rac1, a member of the Rho family of small GTPases,
acts as a key regulator of cell migration.
RESULTS: To address the functional role of Rac1 in
islet morphogenesis, we generated transgenic mice expressing dominant
negative Rac1 under regulation of the Rat Insulin Promoter. Blocking
Rac1 function in beta cells inhibited their migration away from the
ductal epithelium in vivo. Consistently, transgenic islet cell
spreading was compromised in vitro. We also show that the EGF-receptor
ligand betacellulin induced actin remodelling and cell spreading in
wild-type islets, but not in transgenic islets. Finally, we demonstrate
that cell-cell contact E-cadherin increased as a consequence of
blocking Rac1 activity.
CONCLUSION: Our data support a model where Rac1 signalling controls
islet cell migration by modulating E-cadherin-mediated cell-cell
adhesion. Furthermore, in vitro experiments show that betacellulin
stimulated islet cell spreading and actin remodelling is compromised in
transgenic islets, suggesting that betacellulin may act as a regulator
of Rac1 activity and islet migration in vivo. Our results further
emphasize Rac1 as a key regulator of cell migration and cell adhesion
during tissue and organ morphogenesis.
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A
novel single-cell quantitative real-time RT-PCR method for quantifying
foot-and-mouth disease viral RNA.
Huang X, Li Y, Zheng CY.
State Key Laboratory of Virology, College of Life
Sciences, Wuhan University, Wuhan 430072, China.
J Virol Methods. 2009 155(2): 150-156
Foot-and-mouth disease virus is a positive-sense,
single-stranded RNA virus with a negative strand as its replication
intermediate, which can cause severe acute infection in sensitive cell
lines. To investigate better the actual state of virus infection, there
is a need to measure the amount of FMDV RNA in a single acutely
infected cell rather than in a large number of cells. Therefore, in the
present study, a strand-specific single-cell quantitative real-time
RT-PCR was developed to analyze the RNA or FMDV. This new method uses
two techniques in concert with each other: a technique for isolating
single cells with micromanipulators, which is coupled to an assay for
detecting viral RNA by real-time RT-PCR. In the assay of acute
infection, 185 of 224 (82.6%) single-cell samples were positive and
contained viral genome copies ranging from several to thousands, and up
to 1,000,000 copies. However, not all cells were infected and there
were differences in the number of viral RNA copies between cells. A
single-cell quantitative RT-PCR was validated to be feasible and
effective.
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Quantification
of circulating endothelial and progenitor cells: comparison of
quantitative PCR and four-channel flow cytometry.
Steurer M, Kern J, Zitt M, Amberger A, Bauer M, Gastl G, Untergasser G,
Gunsilius E.
Tumor Biology and Angiogenesis Laboratory, Division of Hematology and
Oncology,
Innrain 66, Innsbruck Medical University, 6020 Innsbruck, Austria.
BMC Res Notes. 2008 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 endothelial cells.
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.
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Prognosis
of non-small cell lung cancer patients by detecting circulating cancer
cells
in the peripheral blood with multiple marker genes.
Sher YP, Shih JY, Yang PC, Roffler SR, Chu YW, Wu
CW, Yu CL, Peck K.
Institute of Biomedical Sciences, Academia Sinica,
Taipei, Taiwan, Republic of China.
Clin Cancer Res. 2005 Jan 1;11(1): 173-179
PURPOSE: Current
lung cancer staging and prognosis methods are based on imaging methods,
which may not be sensitive enough for early and accurate detection of
metastasis. This study aims to validate the use of a panel of markers
for circulating cancercell detection to
improve the accuracy of cancer staging, prognosis, and
as a rapid assessment of therapeutic response.
EXPERIMENTAL DESIGN: We analyzed the National Cancer
Institute-Cancer Genome Anatomy Project database to identify potential
marker genes for the detection of circulating cancer cells in
peripheral blood. Nested real-time quantitative PCR and a scoring
method using cancer cell load Lc were employed to correlate the amount
of circulating cancer cells with clinical outcomes in 54 non-small cell
lung cancer (NSCLC) patients. The Kaplan-Meier method was employed for
analysis of prognostic variables.
RESULTS: A panel of four marker genes was identified and experimentally
validated. With these marker genes, we achieved an overall positive
detection rate of 72% for circulating cancer cells in the peripheral
blood of NSCLC patients. Patients who had higher Lc values had worse
outcomes and shorter survival times. Patients with poor therapeutic
response were revealed by positive detection of circulating cancer
cells after therapy. The results correlated well with the patients'
survival time.
CONCLUSION: Circulating cancer cell detection by a panel of markers and
the Lc scoring method can supplement the current tumor, node,
metastasis staging method for improved prognosis and for rapid
assessment of therapeutic response. Together, they may facilitate the
design of better therapeutic strategies for the treatment of NSCLC
patients.
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Nanoliter
reactors improve multiple displacement amplification of genomes from
single cells.
Marcy Y, Ishoey T, Lasken RS, Stockwell TB, Walenz
BP, Halpern AL, Beeson KY, Goldberg SM, Quake SR.
Department of Bioengineering, Stanford University,
Stanford, California, USA.
PLoS Genet. 2007 Sep;3(9): 1702-1708
Since only a small
fraction of environmental bacteria are amenable to laboratory culture,
there is great interest in genomic sequencing directly from singlecells.
Sufficient DNA for sequencing can be obtained from one cell by theMultiple
Displacement Amplification (MDA) method, thereby eliminating the need todevelop
culture methods. Here we used a microfluidic device to isolate
individual Escherichia coli and amplify genomic DNA by
MDA in 60-nl reactions. Our resultsconfirm a report that
reduced MDA reaction volume lowers nonspecific synthesis that
can result from contaminant DNA templates and unfavourable interaction between
primers. The quality of the genome amplification was assessed by qPCR
and compared favourably to single-cell amplifications
performed in standard 50-microl volumes. Amplification
bias was greatly reduced in nanoliter volumes, thereby providing
a more even representation of all sequences. Single-cell amplicons from
both microliter and nanoliter volumes
provided high-quality sequence data by high-throughput
pyrosequencing, thereby demonstrating a straightforward route to sequencing
genomes from single cells.
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Fluidigm
Dynamic Arrays provide a platform for single-cell gene expression
analysis.
Fluidigm application note 2009 (1)
Historically,
single-cell gene expression experiments have been difficult and
expensive to perform. Now, however, single-cell gene expression results
from single-cell samples can be inexpensive and easily reproducible
using Fluidigm’s Dynamic Array™ integrated fluidic circuits and
BioMark™ system for genetic analysis. This method is ideally suited for
high-throughput cell-line studies to determine individual cell behavior
in a homozygous population. To demonstrate this capability, we chose
single human cells from eight-cell-stage embryos, collected and
analyzed for expression of 46 developmental genes.
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Quantification
of
mRNA in single cells and modelling of RT-qPCR induced noise.
Bengtsson M, Hemberg M, Rorsman P, Stahlberg A.
BMC Mol Biol. 2008 9: 63.
Oxford Centre for Diabetes, Endocrinology and
Metabolism, University of Oxford,
The Churchill Hospital, Oxford, OX3 7LJ, UK.
BACKGROUND:
Gene
expression has a strong stochastic element resulting in highly variable
mRNA levels between individual cells, even in a seemingly homogeneous
cell population. Access to fundamental information about cellular
mechanisms, such as correlated gene expression, motivates measurements
of multiple genes in individual cells. Quantitative reverse
transcription PCR (RT-qPCR) is the most accessible method which
provides sufficiently accurate measurements of mRNA in single cells.
RESULTS: Low
concentration of guanidine thiocyanate
was used to fully lyse single pancreatic beta-cells followed by RT-qPCR
without the need for purification. The
accuracy of the measurements was determined by a quantitative
noise-model of the reverse transcription and PCR. The noise is
insignificant for initial copy numbers >100 while at lower copy
numbers the noise intrinsic of the PCR increases sharply, eventually
obscuring quantitative measurements. Importantly, the model allows us
to determine the RT efficiency without using artificial RNA as a
standard. The experimental setup was applied on single endocrine cells,
where the technical and biological noise levels were determined.
CONCLUSION: Noise
in single-cell RT-qPCR is insignificant compared to biological
cell-to-cell variation in mRNA levels for medium and high abundance
transcripts. To minimize the technical noise in single-cell RT-qPCR,
the mRNA should be analyzed with a single RT reaction, and a single
qPCR reaction per gene.
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Intracellular
expression profiles measured by real-time PCR tomography in the Xenopus
laevis oocyte.
Sindelka R, Jonák J, Hands R, Bustin SA,
Kubista M.
Nucleic Acids Res. 2008 36(2):387-92.
Laboratory of Gene Expression, Institute of
Molecular Genetics, Academy of
Sciences of the Czech Republic, Videnska 1083, 14220
Prague 4, Czech Republic.
Real-time PCR
tomography is a novel, quantitative method for measuring localized RNA
expression profiles within single cells. We demonstrate its usefulness
by dissecting an oocyte from Xenopus laevis into slices along its
animal-vegetal axis, extracting its RNA and measuring the levels of 18
selected mRNAs by real-time RT-PCR. This identified two classes of
mRNA, one preferentially located towards the animal,
the other towards the vegetal pole. mRNAs within each group show
comparable intracellular gradients, suggesting they are produced by
similar mechanisms. The polarization is substantial, though not
extreme, with around 5% of vegetal gene mRNA molecules
detected at the animal pole, and around 50% of the molecules in the far
most vegetal section. Most animal pole mRNAs were found in the second
section from the animal pole and in the central section, which is where
the nucleus is located. mRNA expression profiles did not change
following in vitro fertilization and we conclude that the cortical
rotation that follows fertilization has no detectable
effect on intracellular mRNA gradients.
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Intracellular
Gene Expression Profi les Revealed with Real-time PCR Tomography
The BioMark system enabled measuring diffenntiation on the single-cell
level with high accuracy and throughput.
Fluidigm application note 2009 (2)
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