1 Laboratory for Stem Cell Biology, RIKEN Center for Developmental Biology,
2-2-3 Minatojima Minami-machi, Kobe, Hyogo 650-0047, Japan
2 Molecular Oncology, Swiss Institute for Experimental Cancer Research, National
Center of Competence in Research, 1066 Epalinges, Switzerland
* Author for correspondence (e-mail: mosawa{at}cdb.riken.jp)
Accepted 12 October 2005
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SUMMARY |
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Key words: Stem cells, Melanocytes, Gene expression profile, Stem cell niche, Hair follicle
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Introduction |
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It is widely accepted that SCs are maintained by a specialized
microenvironment known as the SC niche
(Fuchs et al., 2004;
Schofield, 1978
;
Spradling et al., 2001
;
Watt and Hogan, 2000
).
Although recently the importance of the niche in regulating SCs has been
clarified intensively, the niche itself has remained a hypothetical entity for
many SC systems, especially in vertebrates. This is in clear contrast to
germline SCs (GSCs) in the Drosophila ovary or testis, where the
nature of the cells comprising the niche and their role in the maintenance of
GSCs have been well characterized, at both the cellular and the molecular
level (Kiger et al., 2001
;
Spradling et al., 2001
;
Tulina and Matunis, 2001
;
Xie and Spradling, 2000
). One
clear difference between the Drosophila GSC system from those of
vertebrates is the ability to identify individual SCs and the cells comprising
the niche by their location and morphology. These features of
Drosophila GSCs offer experimental advantages in understanding the
exact molecular interactions between the SCs and the niche. By contrast, in
vertebrates, it is often the case that the SC compartment consists of
extremely rare populations of cells, and that the microenvironment surrounding
the SCs has a complicated anatomical structure that is occupied by many of the
SC progeny in the TA/DC compartment. It is therefore difficult to identify the
exact location of individual SCs and their niche, and to determine whether the
surrounding SC progeny or different cell types are involved in the niche.
These difficulties in the vertebrate SC systems hamper the detailed analysis
of SC regulation by the niche.
Melanocytes (MCs) provide an attractive model with which to understand the
molecular basis of various cellular regulations, as dysfunction of the
molecules implicated in MC regulation (i.e. in survival, proliferation,
migration or differentiation) can be easily identified by the coat color
defect. Such understanding also provides a cue to define the molecular
mechanism of SC regulation, as it has been reported recently that improper
maintenance of MSCs causes hair to turn gray
(Nishimura et al., 2005).
Indeed, more than 90 different loci have currently been identified as coat
color mutants in the mouse (Nakamura et
al., 2002
). Among these loci, Pax3, Sox10, Mitf, Kit
(previously known as c-Kit) and Ednrb have been shown to be
particularly critical for the development of immature MCs, melanoblasts (Mbs)
(Goding, 2000
;
Nishikawa et al., 1991
;
Potterf et al., 2001
;
Shin et al., 1999
).
Mbs emerge in the neural crest and migrate through the epidermis towards
newly developing hair follicles (HFs) until all the Mbs in the hairy skin
region become specifically localized in the HF. Once localized in the HF, they
are separated into two populations: differentiated MCs, which are localized in
the hair matrix region and are responsible for hair pigmentation; and MSCs,
which are localized at the lower permanent portion of the HF and are
responsible for the repopulation of the MC system in subsequent hair cycles.
Previously, we demonstrated that MSCs are identified as the LRCs, and that
they can survive even after blocking Kit signaling with a specific
antagonistic antibody against Kit, which is normally essential for the
proliferation and survival of all other subsets of MCs
(Nishimura et al., 2002).
However, except for this phenomenon, little is known about MSCs.
MSCs exemplify one SC system in which the SC compartment is anatomically
segregated from the SC progeny in the TA/DC compartment
(Nishimura et al., 2002). For
these SCs, the cells comprising the niche, if they exist, should not be of the
MC lineage because MSCs are scattered in the lower permanent portion of the HF
without forming into cell clusters. This simple architecture of MSCs is
expected to be advantageous for the investigation of molecular interactions
between SCs and the niche, as has been learnt from examples of GSCs in
Drosophila. The ultimate goal of our studies on MSCs is to define the
exact molecular mechanisms of SC regulation in the niche. To achieve this
goal, it is important to characterize the MSCs and to isolate them
specifically, which would thus enable us to obtain a series of gene expression
profiles of MSCs in the niche. Here, we describe (1) the molecular markers
distinguishing MSCs from other cells, (2) the isolation of single MSCs from
transgenic mice with MCs marked by GFP, and (3) the gene expression profiling
of individual MSCs using a single-cell cDNA amplification technique.
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Materials and methods |
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Immunohistochemistry and in situ hybridization
To analyze the molecular markers for MSCs, immunofluorescent staining was
performed using dorsal skin sections prepared from postnatal day 6 (P6)
Dct-lacZ mice that were pre-treated with the anti-c-Kit antibody
(Ack2) at P0, P2 and P4, as described previously
(Nishimura et al., 2002). For
the immunohistochemical analysis of TA cells/DCs in the hair matrix,
non-treated P6 skin samples were used. Frozen skin sections were prepared as
described previously (Nishimura et al.,
2002
). After treatment with a blocking solution containing 5% skim
milk (Difco), 1% donkey serum (Chemicon) and 0.1% Triton X-100
(Nakarai-Tesque, Japan) in PBS, skin sections were incubated with primary
antibodies diluted in the blocking solution. The following primary antibodies
were used in the analysis: rabbit-anti-ß-gal (Chemicon),
goat-anti-ß-gal (Biogenesis, UK), rabbit-anti-Dct, rabbit-anti-Tyrp1,
rabbit-anti-Si (pMel17) (gifts from Dr V. Hearing, NIH, USA), goat-anti-Dct,
goat-anti-Tyrosinase (Santa Cruz), mouse-anti-Lef1 (Upstate), mouse anti-Sox10
(a gift from Dr M. Wegner, University of Erlangen-Nurnberg, Germany),
rabbit-anti-Sox10 (Chemicon), rabbit-anti-Pax3 (a gift from Dr G. Grosveld,
St. Jude Children's Research Hospital, USA), rat-anti-c-Kit (Ack4, prepared in
our laboratory) and rabbit-anti-Mitf (a gift from Dr H. Yamamoto, Tohoku
University, Japan). The sections were then washed three times in PBS
containing 0.1% Triton X-100, and incubated with an appropriate combination of
the following secondary antibodies diluted in blocking solution containing
TO-PRO3 (Molecular Probes): Alexa488-conjugated donkey anti-rabbit IgG,
Alexa488-conjugated donkey anti-goat IgG, Alexa546-conjugated donkey
anti-rabbit IgG, Alexa546-conjugated donkey anti-goat IgG (Molecular Probes)
and Alexa488-conjugated donkey anti-mouse IgG (Jackson Laboratory). After
washing three times with PBS, the slides were mounted with a ProLong Antifade
kit (Molecular Probes) and observed under a confocal microscope (Bio-Rad
Radiuns 2100 or Zeiss LSM510 Meta).
For in situ hybridization/immunohistochemical double staining, in situ
hybridization was performed as described previously
(Wilkinson and Nieto, 1993),
with a digoxigenin-labeled antisense probe using skin sections from
Dct-lacZ mice. A Sox10 antisense probe was synthesized from
rat Sox10 cDNA (a gift from Dr M Wegner, University of
Erlangen-Nurnberg, Germany). The Sox10 probe was detected with goat
peroxidase-conjugated anti-digoxigenin antibody (Roche) using the TSA plus
Fluorescein system (Perkin Elmer Life Sciences), according to the
manufacturer's protocol. After in situ hybridization, the sections were
incubated with diluted rabbit anti-ß-gal antibody (Chemicon), washed
three times in PBS and then incubated with donkey Alexa 546-conjugated
anti-Rabbit IgG (Molecular Probes) to visualize lacZ+
MCs.
Isolation of single MCs
Dorsal skin was isolated from P6 CAG-CAT-EGFP;
Dcttm1(Cre)Bee mice that were either pre-treated or not
treated with Ack2. Embryonic skin (E16.5) was incubated in PBS containing 5 mM
EDTA for 1 hour at 37°C and then the dermis was removed from the epidermis
under stereomicroscopy. The embryonic epidermis was further dissociated by
treatment with 0.25% Trypsin and 1 mM EDTA in PBS for 5 minutes at 37°C to
obtain a single-cell suspension. Dorsal skin was incubated with 1 mg/ml
collagenase type VI (Gibco) for 1 hour at 37°C and then the dermis was
removed. Single HFs were isolated from the epidermis and micro-dissected to
separate the lower permanent portion and the hair matrix regions. The lower
permanent portion and hair matrix were then dissociated into single cells by
treatment with 0.05% trypsin and 1 mM EDTA for 5 minutes at 37°C.
Following neutralization with ice-cold PBS containing 20% FCS and 1 mM
CaCl2, single GFP+ MCs were individually picked with
capillary pipettes.
Single-cell PCR
Single cells were seeded separately into PCR tubes with 4.5 µl lysis
buffer containing 50 mM Tris-HCl, 75 mM KCl, 5 units Super RNaseIN (Ambion),
7.5 units PrimeRNase Inhibitor (Eppendorf), 0.5% NP40, 1 mM DTT, 50 µM
dNTP, and 15 nM MO-dT30 primer
(AAGCAGTGGTATCAACGCAGAGTGGCCATTACGGCCGTACTT-(dT)30). Tubes were
then incubated at 65°C for 5 minutes and cooled to 45°C for 2 minutes.
Reverse transcription was then carried out by the addition of 25 units of
Reverse-iT Blend (AB Gene). After incubation at 50°C for 5
minutes, the reaction was terminated by heating at 70°C for 10 minutes.
Next, 5 µl of reaction mixture [1xPCR buffer (Invitrogen), 1.5 mM
MgCl2, 3 mM dATP, 15 units TdT (Promega) and 2 units RNaseH
(Invitrogen)] was added into each tube and poly (A) tailing and RNA digestion
performed by incubating at 37°C for 15 minutes, and then inactivating at
70°C for 10 minutes. cDNA amplification was carried out using HS ExTaq
polymerase (Takara Biochemicals, Japan). Briefly, polyA-tailed cDNA (10 µl)
was split into two tubes containing 45 µl of primary PCR reaction solution
containing ExTaq PCR buffer (Takara Biochemicals), 5 mM MgCl2, 2 mM
dNTP, 2 µM MO-dT30 primer and 5 units of HS ExTaq polymerase (Takara
Biochemicals). PCR was performed with one cycle of 1 minute at 94°C, 2
minutes at 50°C and 2 minutes at 68°C, followed by 24 cycles of 30
seconds at 94°C, 30 seconds at 65°C, and 2 minutes at 72°C. After
combining split tubes into one tube, cDNA was purified with Qiagen PCR
purification kit according to manufacturer's procedure.
Real-time PCR analysis
Real-time PCR analysis was carried out using a Qiagen QuantiTect SYBR Green
PCR Kit according to the manufacturer's protocol. Briefly, cDNA was added to
14 µl of real-time PCR mix containing 2xQuantitect SYBR green master
mix and 0.3 µM each of specific primer pairs. PCR was performed at 95°C
for 15 minutes for the initial activation of HotStarTaq polymerase, then with
40 cycles of 20 seconds at 95°C and 1 minute at 60°C using a ABI PRISM
7900 HT sequence detection system. Information on the PCR primer sets used in
this study is available upon request. To test the fidelity of our cDNA
amplification, we estimated the relative gene expression levels of individual
genes in the amplified cDNA and examined how these correlated with the
corresponding values obtained with unamplified cDNA. For this purpose, total
RNA was extracted from a Mb cell line, Melb-a (a gift from Dr D. Bennett, St.
George's Hospital, UK) (Sviderskaya et
al., 1995), using Isogen (Nippon Gene, Japan) according to the
manufacturer's protocol. To generate unamplified cDNA, 100 ng of total RNA was
reverse transcribed with 5 µM (dT)20 primer (Invitrogen) with 25
units of Reverse-iT Blend (AB Gene) containing 5x first strand
buffer (Invitorgen), 5 mM DTT, 0.5 mM dNTP and 40 units RNaseOUT (Invitrogen),
and then incubated at 45°C for 60 minutes and treated with 2 units of
RNaseH at 37°C for 15 minutes. The unamplified cDNA was purified with a
Qiagen PCR purification Kit and 1 ng of cDNA was used for real-time PCR
analysis as described above. To generate amplified cDNA, 10 pg of total RNA
was used for the cDNA amplification as described above. Relative expression
values were calculated by dividing the expression value of each target gene by
that of a mRNA spike as described below.
Spiking experiments
Poly(A)-tailed Arabidopsis thaliana LTP4 (GenBank Accession number
AF159801), LTP6 (GenBank Accession number AF159803), NAC1 (GenBank Accession
number AF198054) and TIM (GenBank Accession number AF247559) RNA was purchased
from Stratagene and added into the lysis buffer containing either a single
cell or 10 pg of total RNA prepared from the cultured melanoblast cell line
Melb-a, to the following final concentrations: LTP4, 10-1
pg/sample; LTP6, 10-2 pg/sample; NAC1, 10-3 pg/sample;
TIM, 10-4 pg/sample. Assuming 1 µg of RNA with an average length
of 500 bp is equal to 6 pmol, these concentrations correspond to
4x104, 4x103, 4x102 and 40
copies/sample, respectively. Each sample was reverse transcribed and amplified
as described. Relative expression value was determined by Q-PCR using a primer
pair specific for each spike RNA. For the normalization of each spike RNA and
the melanogenic gene, LTP4 was used as a standard.
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Results |
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To compare the molecular expression profile of MSCs with that of TA/DC
subsets of MCs localized at the hair matrix region, we prepared skin sections
either from the Ack2-treated or the control mice and analyzed the expression
of Dct, Tyr, Si, Tyrp1, Kit, Pax3, Mitf, Sox10 and Lef1 in these MC subsets by
multicolor immunohistochemical staining. Consistent with our previous studies,
and with those of other groups (Botchkareva
et al., 2001; Nishimura et
al., 2002
), ß-galactosidase+
(ß-gal+) MCs localized either at the lower permanent portion
of the HF in the Ack2-treated skin or in the hair matrix region of the HF in
the control skin. However, expression of Tyr, Si, Tyrp1, Kit, Mitf, Sox10 and
Lef1 was undetectable in MSCs, whereas all of these molecules were expressed
in the MCs at the hair matrix region (Fig.
1). Contrastingly, expression of Dct and Pax3 was observed in MCs
in both populations (Fig. 1).
Mki67 was undetectable in MSCs, whereas some TA subsets in the hair matrix
were positive for Mki67 (Fig.
1), indicating that MSCs are resting, whereas certain populations
of the matrix MCs are actively proliferating. Thus, the MSC and TA/DC subsets
were clearly distinguishable by their molecular expression patterns; the MSC
subset being Dct+, Pax3+, Tyr-,
Si-, Tyrp1-, Kit-, Mitf-,
Sox10-, Lef1- and Mki67-, while, in contrast,
the TA/DC subset was positive for all these markers.
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From these observations, Sox10 expression was shown to delimit the boundary between MSCs and other subsets of MCs in the HF. Thus, it is clear that MSCs display a distinct molecular expression profile from that of epidermal Mbs or the MCs at the hair matrix, which suggests the existence of discrete molecular expression programs among these populations.
Isolation of MSCs from single HFs
These molecular expression analyses raised the possibility that MSCs could
be further defined by their own gene expression profile, in addition to their
biological properties (i.e. resistance against Ack2 treatment and specific
localization at the lower permanent region of the HF). To obtain the gene
expression profile of the individual MSCs, we developed the following
procedure to isolate single MCs from specific regions of the HF.
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Next, to mark all the MCs in the epidermis, we engineered transgenic mice
to express GFP in a MC-specific manner, by crossing Dct/Cre knock-in
mice (Dcttm1(Cre)Bee)
(Guyonneau et al., 2004) with
CAG-CAT-EGFP reporter mice
(Kawamoto et al., 2000
) that
express GFP under the control of a strong ubiquitous promoter,
CAG, after the Cre-mediated removal of a Floxed chloramphenicol
acetyl transferase (CAT) gene cassette
(Fig. 3B). MC-specific GFP
expression was confirmed in a single HF
(Fig. 3C) and in embryonic
epidermis (Fig. 3D) obtained
from the transgenic mice. FACS analysis using embryonic epidermal cells
revealed that the Cre-mediated recombination efficiency in the transgenic mice
was more than 50%, as judged from the frequency of GFP+ cells in
the CD45-, Kit+ Mbs
(Fig. 3E).
To isolate individual MCs, single guard hairs of stage 8 HF morphogenesis were prepared from either Ack2-treated mice or non-treated mice. We regarded MSCs as the MCs remaining at the lower permanent portion of the HF in Ack2-treated mice, and TA/DCs as the MCs localizing at the hair matrix in non-treated mice. The single HFs were further micro-dissected into the lower permanent portion and the hair matrix region under stereomicroscopy. After dissociation of each region into single cells by trypsin-EDTA treatment, individual GFP+ cells were picked from the single-cell suspension under fluorescent microscopy. For comparison, single Mbs obtained from E16.5 embryonic epidermis were also picked. These cells were seeded into lysis buffer-containing PCR tubes and processed for gene expression analysis as described in the next section.
Validation of the single-cell-based gene expression profiling technique
In order to perform high-throughput gene expression analysis from a limited
amount of cells, a single-cell-based gene profiling strategy for the
individual MCs was designed by combining single-cell cDNA amplification and a
real-time PCR quantification assay (Q-PCR). We optimized and modified previous
cDNA amplification methods (Iscove et al.,
2002) to profile gene expression patterns by Q-PCR. Particularly,
we modified the reverse transcription and PCR amplification steps to obtain
the conditions that allowed the preservation of the initial representation of
transcripts in Q-PCR assays, by maximizing the efficiency in the reverse
transcription and minimizing the bias in amplification of transcripts during
the cDNA amplification (see Materials and methods).
A crucial issue for the validation of our amplification technique was to
determine whether the relative expression value of each transcript in the
amplified cDNA is representative of that of the original single-cell
transcript in a reproducible fashion. To test the fidelity of cDNA
amplification, we estimated the relative gene expression levels of individual
genes in the amplified cDNA and examined how these correlated with the
corresponding values obtained from unamplified cDNA. For this purpose, total
RNA was prepared from a clonal Mb cell line, Melb-a
(Sviderskaya et al., 1995),
and cDNA was constructed either by conventional (unamplified) reverse
transcription from 100 ng of the total RNA, or by performing PCR amplification
with 10 pg of the total RNA, which is thought to be equivalent to half of that
in a single cell. Relative gene expression values of 11 individual melanogenic
genes were determined by Q-PCR using specific primers. Although there was a
tendency for a distortion of the abundance relationships in some lower
abundance transcripts, the estimated expression values of target genes in the
amplified cDNA were roughly comparable to those in the unamplified cDNA
(Fig. 4A). As shown in
Fig. 4B, a significant
correlation in the relative expression value of these 11 genes was observed
between amplified and unamplified cDNA, indicating that the abundance
relationships are relatively preserved by our cDNA amplification protocol.
Thus, consistent with previous reports
(Iscove et al., 2002
;
Makrigiorgos et al., 2002
), it
is clear that our strategy preserved the abundance relationships by allowing
semi-quantitative gene profiling, even at the single-cell level.
|
To assess the sensitivity of our single-cell transcript analysis, we mixed
various amounts of the four distinct RNA spikes into a constant amount (10 pg)
of the total RNA and amplified cDNA by PCR amplification. As shown in
Fig. 4D, subsequent Q-PCR
analysis using the primers specific for each spike mRNA indicated that the
abundance relationships were preserved between the Q-PCR quantification and
the input copy number of each spike mRNA, allowing quantification assessment
of mRNA copy numbers ranging from 40 to 4x105.
These data illustrate the ability of our cDNA amplification and Q-PCR quantification techniques to preserve the respective ratios of transcripts between the original RNA in a single cell and the amplified cDNA. Moreover, they demonstrate the capability of our single-cell transcript analysis system to detect low abundance transcripts; for example, less than 40 copies of mRNA.
Single-cell transcriptional analysis of MSCs
Using this cDNA amplification method, we prepared cDNA from three different
subsets of MCs, as described in previous section, and investigated the gene
expression profiles in each subset. We also included four different
concentrations of mRNA spikes (from 40 to 4x104 copies) in
the reaction mixture to ensure that the abundance relationships were preserved
in each cDNA amplification. To avoid possible differences in the expression of
the housekeeping genes that are normally used as internal standards for
relative quantification in Q-PCR assay, we normalized the expression value of
each gene to one of the mRNA spikes in order to perform accurate relative
quantification by Q-PCR. cDNA was further evaluated to eliminate those failing
to display significant expression of housekeeping genes such as Gapd
and Actb, and/or failing to preserve the abundance relationships. In
total, cDNA generated from 27/32 MSCs, 14/16 matrix MCs and 19/24 Mbs
underwent gene profiling by Q-PCR using specific primer pairs
(Fig. 5).
Various melanosome-organizing genes, including Si, Tyrp1, Tyr, Mlana and Oa1 were downregulated in MSCs; however, their extensive expression was observed in the matrix MCs, reflecting the active melanin synthesis in matrix MCs. By contrast, the expression of these melanosome genes fluctuated in Mbs, suggesting that, in terms of melanosome maturation, Mbs are heterogeneous. Si, which is one of the earliest markers for melanosome maturation, was expressed in both Mbs and the matrix MCs. Consistent with immunohistochemical staining, quite a few MSCs express a low level of Si (3/27). Expression of cell surface receptors, including Kit and Ednrb, was dramatically downregulated in the MSC population, whereas their expression was detected in the majority of Mbs (17/19 and 15/19, respectively) and in all of the matrix MCs. Mc1r was predominantly expressed in the matrix MCs, although its expression was detected in a few of the Mbs and MSCs (1/19 and 2/27, respectively). As would be expected from the immunostaining (Fig. 1) and in situ hybridization analysis (Fig. 2A-F), Sox10 expression was dramatically reduced in the MSC population (a low level of the expression was detected in 6/27), whereas extensive expression of Sox10 was observed in Mbs (17/19) and in all of the matrix MCs. Expression of Mitf was detected in many MCs throughout all of the subsets; however, its expression fluctuated greatly in these subsets.
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Discussion |
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We believe that this strategy for the isolation of SCs has the following
advantages over other possible cell separation techniques, such as FACS.
First, it should be the most accurate and precise way to isolate SCs, if SCs
are anatomically or morphologically identifiable. The strategy is expected to
be applicable for the isolation of SCs, such as spermatogonial SCs, muscle
satellite cells or SCs for the intestinal epithelium, whose location has been
well defined. Second, it is expected to be advantageous for the isolation of
niche-forming cells, which are thought to be closely associated with SCs. The
niche-forming cells for GSCs in the Drosophila ovary
(Xie and Spradling, 2000) and
for HSCs in murine bone marrow (Calvi et
al., 2003
; Zhang et al.,
2003
) have been already demonstrated. However, except for these
few examples, niche cells are still conceptual for most SCs. Under such
circumstances, the only way to harvest niche-forming cells, if they exist, is
to collect cells located around the SCs. Gene profiling of the cells that
surround the GFP+ MSCs is currently under way in our
laboratory.
Single-cell-based gene expression analysis
In this study, we applied cDNA amplification to obtain gene expression
profiles for individual MSCs. We adopted single-cell-derived cDNA
amplification for Q-PCR assay, which allowed the simple and high-throughput
quantification of gene expression at single-cell level. The validation of our
cDNA amplification demonstrated that this procedure is reproducible,
faithfully represents the gene expression profile of a single cell, and
maintains the abundance relationships of transcripts, ranging from 40 to
4x105 copies in an individual cell.
Unlike microarray analysis, which allows the expression of 30,000
genes to be profiled at a time, this technique is suitable for analyzing the
gene expression of
100 individual genes simultaneously. Because the
number of PCR cycles in the cDNA amplification step is restricted to 25, the
total yield of cDNA in our amplification is less than
50 ng, which is
several orders of magnitude less than the amount required for microarray
hybridization. We tried to increase the number of amplification cycles to
obtain more cDNA; however, this resulted in distortion of the abundance
relationships of spike mRNAs in the Q-PCR analysis.
Like all gene expression analysis methods, the strategy described here has
limitations. Because our single-cell cDNAs represent 600 bp from the
3' ends of the transcripts, the primer set should be designed within
this range to obtain a PCR product. However, despite the massive effort to
define entire genome sequences, the information on 3'-end transcripts in
the databases is still poor. This limitation is sometimes critical for our
strategy. Indeed, we never detected a Pax3 transcript, in any of our MC
subsets, with any of the primer pairs that were designed to be specific for
the 3'-end region of Pax3 using information from the Ensembl Mouse
Genome Database, although all of the primer pairs worked nicely with
conventional RT-PCR. One possible explanation for this might be that the Pax3
3'-end information in the database is incomplete.
Another possible limitation of single-cell profiling stems from the fact
that, in clonal population, cells can exhibit substantial phenotypic
variation, particularly in the expression of low copy number molecules. It has
been reported that both intrinsic and extrinsic noise affects gene expression
in a stochastic manner (Elowitz et al.,
2002; McAdams and Arkin,
1997
). In addition to this stochasticity in transcription, recent
studies have revealed that the levels of cellular mRNA transcripts are
temporally regulated by active mRNA decay
(Wilusz et al., 2001
). The
regulation of mRNA decay is critically important to determine the abundance of
cellular transcripts. As shown in the previous report
(Herrick et al., 1990
), decay
rates of individual mRNA transcripts differ extensively; some vital mRNAs are
degraded rapidly by certain destabilizing protein complexes or by RNA
interference machinery, whereas other mRNAs are maintained for several
generations. As a consequence of these combinatory regulations, mRNA
transcripts in individual cells could vary dynamically over time. These
differences in gene expression may account for the cell-cell variation
observed in clonal populations, and are thought to play crucial roles in
fundamental biological processes (Heitzler
and Simpson, 1991
). These variations are not evident when gene
expression profiling is performed at the population level; however, they are
critical for single-cell based analysis. In this study, we noticed
fluctuations in the expression of several genes, such as Mitf. Consistent with
our data, several other reports (Chiang and
Melton, 2003
; Peixoto et al.,
2004
; Saitou et al.,
2002
; Theilgaard-Monch et al.,
2001
; Tietjen et al.,
2003
) also showed considerable cell-to-cell variations in their
single-cell transcript analysis. Taken together with these single-cell
transcript analyses, our data clearly indicate that mRNA transcripts in
individual cells intrinsically fluctuate, which may require a new paradigm of
transcript analysis to understand its biological significance.
In addition to these cell-autonomous fluctuations, variations in gene
expression in MSCs may arise from the differences in hair cycles or hair types
in which the MSCs are localized. Because hair follicle morphogenesis follows a
rather precise time-scale, we focused our analysis on the MCs localized in
guard hairs at stage 8 of hair follicle morphogenesis to standardize the stage
and the type of HF. However, we could not exclude the possibility that gene
expression is affected by the difference in the precise location of MSCs in
the niche, as it has been demonstrated that several different types of
epidermal SCs are localized at different positions within the bulge region
(Blanpain et al., 2004).
In these circumstances, the key issue for single-cell transcript analysis is to distinguish the biologically significant transcriptional differences from the intrinsic fluctuations in the mRNA copy number in single cells. We therefore performed multiple gene expression profiling using 62 single cells, ensuring the gene expression profile by immunohistochemical staining or in situ staining. We could not detect the expression of some crucial genes for melanogenesis, including Sox10 and Kit, in the stem cell population reproducibly, which was consistent with the immunostaining results. Thus the data convincingly demonstrates that the gene expression profile of the melanocyte stem cells is significantly different from the intrinsic fluctuations observed in gene expression in other populations, although we cannot completely exclude the possibility that random inaccuracies in the reverse transcription and cDNA amplification distort the real expression patterns in low abundance transcripts (less than 40 copies).
Besides these limitations, we expect this strategy to be advantageous over microarray analysis for obtaining a quick sketch of the gene expression profile in a given cell species; microarray analysis may deliver comprehensive gene expression data, but it requires multiple samples to obtain reproducible data and complicated statistical analysis. In particular, our strategy allows us to understand the diversity of individual cells on a transcriptional basis among a given population located in a restricted area, such as the SC niche.
Signature of MSCs
To confirm that MSCs were harvested properly, it was necessary to
distinguish the SC compartment from other compartments. For this purpose, we
stained HFs with antibodies against proteins whose roles have been implicated
in MC development. We identified the following two groups of protein. The
first group included Dct and Pax3, whose expression was observed both in MSCs
and in TA cells/DCs. The second group of molecules was highly expressed only
in the TA cells/DCs, and included Kit, Si, Tyr, Tyrp1, Mki67, Lef1, Sox10 and
Mitf. We could not specify molecules expressed only in MSCs. Nevertheless, we
used this expression pattern as a signature for distinguishing MCSs from cells
from other compartments, and examined whether this pattern was consistent with
that in each available single-cell cDNA.
As shown in Fig. 5, the SC signature defined by immunohistochemistry (Fig. 1) was basically represented in the gene expression profiles of MSCs (Fig. 5), although some discrepancies were observed. For instance, low levels of Si and Tyrp1 transcripts were detected in few MSCs even though protein expression was not detected in the SCs. These discrepancies might be explained by the level of these proteins being below the detection limit of our immunostaining, or by the existence of post-transcriptional regulation in the SCs, as has been reported in various SCs and progenitors.
While defining the signature of the SCs, we observed that Sox10
expression was far lower in the SCs than in the TA cells/DCs. This observation
was confirmed by both in situ hybridization and gene expression profiling.
Decreased Sox10 expression in the SCs could be due to repression or
to a lack of activation of its transcription. Moreover, our analysis of
Sox10 expression during development of the HF strongly suggests that
Sox10 is actively downregulated upon Mb colonization of the lower
permanent region. This is consistent with our previous study showing that the
MSC niche plays a dominant role in directing MC fate
(Nishimura et al., 2002).
Although further studies are needed to understand the significance of this
observation, we expect the repression of Sox10 transcription in the MSCs to
provide an important clue for understanding the mechanism underlying the
maintenance of resting SCs by the niche.
Regulation of SCs by the niche
We demonstrated the molecular expression profile of MSCs in the niche.
Here, by combining immunostaining and gene expression profiling, we have
observed the downregulation of various key melanogenic factors and genes,
including Sox10, Mitf, Kit, Lef1 and Ednrb, indicating that MSCs
utilize a different biochemistry from that of TA cells/DCs to maintain their
physiological features. Interestingly, our gene expression analysis also shows
the downregulation of some housekeeping genes in MSCs
(Fig. 5). Taken together with
the relative quiescence of MSCs (Nishimura
et al., 2002), these data support the idea that basal
transcription is downregulated in the SC population, as it is characterized
that cellular quiescence is a state accompanied by lower rates of
transcription, translation and metabolism
(Yusuf and Fruman, 2003
).
Thus, these data clearly suggest a role for the niche in regulating molecular
expression in MSCs, both at the transcriptional and translational level. In
MCs, molecular interactions among these key melanogenic molecules have been
well documented (Goding, 2000
;
Lin and Spradling, 1997
;
McGill et al., 2002
;
Saito et al., 2002
;
Takeda et al., 2000
), and it
is obvious that their downregulation in the SC compartment blocks the growth
and/or differentiation cues in MCs. Taken together with recent genetic studies
of epidermal SCs (Blanpain et al.,
2004
; Morris et al.,
2004
; Tumbar et al.,
2004
), we propose that one of the key strategies of SC regulation
by the niche is to insulate SCs from various activation stimuli that promote
growth and/or differentiation cues in the SC compartment, by downregulating
their receptors or key signaling mediators, and/or by inducing inhibitory
factors against the activating stimuli.
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ACKNOWLEDGMENTS |
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