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HEMATOPOIESIS
The hematopoietic stem compartment consists of a limited number of discrete
stem cell subsets
Hans B. Sieburg, Rebecca H. Cho, Brad Dykstra, Naoyuki Uchida, Connie J. Eaves, and Christa E. Muller-Sieburg
Hematopoietic stem cells (HSCs) display
extensive heterogeneity in their behavior
even when isolated as phenotypically homogeneous populations. It is not clear
whether this heterogeneity reflects inherently diverse subsets of HSCs or a homogeneous population of HSCs diversified
by their response to different external
stimuli. To address this, we analyzed 97
individual HSCs in long-term transplantation assays. HSC clones were obtained
from unseparated bone marrow (BM)
through limiting dilution approaches. Fol-
lowing transplantation into individual
hosts, donor-type cells in blood were
measured bimonthly and the resulting
repopulation kinetics were grouped according to overall shape. Only 16 types of
repopulation kinetics were found among
the HSC clones even though combinatorially 54 groups were possible. All HSC
clones, regardless of their origin, could
be assigned to this subset of groups, and
the probability of finding new patterns is
negligible. Thus, the full repertoire of
repopulating HSCs was covered. These
data indicate that the HSC compartment
consists of a limited number of distinct
HSC subsets, each with predictable behavior. Enrichment of HSCs (LinⴚRhoⴚSP)
changes the representation of HSC types
by selecting for distinct subsets of HSCs.
These data from the steady-state HSC
repertoire could provide a basis for the
diagnosis of perturbed patterns of HSCs
potentially caused by disease or aging.
(Blood. 2006;107:2311-2316)
© 2006 by The American Society of Hematology
Introduction
Hematopoietic stem cells (HSCs), like all stem cells, are defined by
their undifferentiated state and their self-renewal capacity. Although HSCs have been extensively studied, the mechanisms that
control these HSC functions are not well understood. The slow
pace of progress in this area is due to a number of experimental
limitations. These include the low numbers of HSCs that can be
accessed, the lack of methods for their long-term propagation in
vitro, and the functional and phenotypic heterogeneity of HSCs. In
particular, the molecular basis of the intriguing functional heterogeneity of HSCs has been difficult to investigate.
In vivo, in vitro, and in silico studies have revealed extensive
heterogeneity in the phenotypes and behaviors of HSCs.1-9 HSCs
can differ in self-renewal capacity, clone size (number of differentiated progeny per HSC), differentiation capacity (contribution to the
hematopoietic lineages), migration patterns, and primitiveness.4,6,9-16 These HSC qualities can be assessed in repopulation
assays, by following over time the appearance of mature progeny
derived from an engrafted HSC (repopulation kinetics). For
example, primitive HSCs are characterized by a slow onset of repopulation leading to sustained production of mature cells.9,17 Thus, repopulation patterns are highly informative for HSC function.
Nevertheless, it is unclear just how heterogeneous the HSC
compartment is and the basis of this heterogeneity has remained
speculative. According to one model, heterogeneity could be
explained as the behavior of a population of homogeneous HSCs
where individual HSCs respond to extrinsic stimuli but the
response is reversible.18-23 Such flexibility should lead to a
continuum of HSC function in the HSC compartment. Similarly, a
continuum of HSC functions should arise if stochastic mechanisms
control HSC behavior.20-23 Inherent in the idea of an HSC
continuum is the idea that every HSC behavior possible should
actually be observable. Support for reversible HSC behaviors
derives from studies where HSCs exposed to cytokines transiently
lose the ability to engraft when the cells proceed through the active
phases of the cell cycle.24 Similarly, reversible expression of the
cell surface antigen CD34 on HSCs has been documented.25
Yet, there is increasing evidence that HSCs can be more
predictable and less flexible than previously appreciated. Many
HSC behaviors are fixed intrinsically through genetic or epigenetic
mechanisms.4,15,26-31 Genetic differences in HSC behavior were
documented when different inbred strains of mice were shown to
have different frequencies of HSCs in their BM.32,33 Similarly,
genetic manipulation of HSCs, for example through overexpression of homeobox genes, can profoundly affect their behavior.34,35
Epigenetic effects cause heterogeneity in genetically identical cells.
A striking example of epigenetically fixed heterogeneity among
HSCs is found in myeloid-biased HSCs. These HSCs make typical
levels of myeloid cells but generate too few lymphocytes. This is
caused by epigenetic changes on the level of the myeloid-biased
HSC, which predetermines its lymphoid progeny to have a blunted
response to IL-7.4,13 Similar to the ability to differentiate, the
overall repopulation patterns can be fixed on the level of each HSC.
From the Sidney Kimmel Cancer Center, San Diego, CA; the Terry Fox
Laboratory, British Columbia Cancer Agency; and the University of British
Columbia, Vancouver, BC.
the Canadian Institutes of Health Research (CIHR), and NCIC Studentships.
N.U. was supported by CIHR and Kirin Fellowships.
Submitted July 25, 2005; accepted October 30, 2005. Prepublished online as Blood
First Edition Paper, November 15, 2005; DOI 10.1182/blood-2005-07-2970.
Supported by grants from the National Institutes of Health NIH-DK48015 and
NIH-AG023197 (C.E.M.-S.) and grants from the National Cancer Institute of
Canada (NCIC), with funds from the Terry Fox Run, the Stem Cell Network, and
the NHLBI/NIH P01-55435 (C.J.E.). B.D. was supported by Stem Cell Network,
BLOOD, 15 MARCH 2006 䡠 VOLUME 107, NUMBER 6
Reprints: Christa E. Muller-Sieburg, Sidney Kimmel Cancer Center, 10835
Altman Row, San Diego, CA 92112; e-mail: [email protected].
The publication costs of this article were defrayed in part by page charge
payment. Therefore, and solely to indicate this fact, this article is hereby
marked ‘‘advertisement’’ in accordance with 18 U.S.C. section 1734.
© 2006 by The American Society of Hematology
2311
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2312
BLOOD, 15 MARCH 2006 䡠 VOLUME 107, NUMBER 6
SIEBURG et al
For example, daughter HSCs (from a clonally derived HSC)
behaved remarkably similar to each other in the kinetics of
repopulation, their ability to contribute to the different hematopoietic lineages, and their life spans.4,13 Overall, these data support the
idea that the HSC compartment is composed of functionally
distinct subpopulations of HSCs. This model makes the prediction
that HSC behaviors should be predictable, that is, the behaviors of
an HSC should cluster in discrete (not continuous) patterns.
To begin to distinguish between these models, we analyzed the
in vivo repopulation behavior of 97 individual clonally derived
HSCs. The results show that all repopulation kinetics can be
grouped into a limited number of families, suggesting that these
families represent discrete subpopulations of HSCs with predictable behaviors. The major and novel conclusion is that the HSC
compartment consists of a limited number of clonotypes each with
predictable behavior. We conclude that the heterogeneity in the
HSC compartment is predetermined and not due to the random
manifestations of a single type of HSC. The complete description
of the HSC repertoire is likely to be valuable as a benchmark for
defining the clonal consequences of treatment and disease.
Materials and methods
Generation of clonally repopulated mice
Adult mouse bone marrow (BM) HSCs were isolated by 3 different
methods: (1) In vivo limiting dilution (LD) transplants of BM cells: 2000 to
5000 BM cells containing limiting (0.2-0.5) numbers of HSCs36,37 were
injected directly into recipients. Mice were considered to be clonally
repopulated only if 40% or less of the injected hosts in a group showed
repopulation. (2) Transplants of HSCs following in vitro LD: BM cells were
seeded onto preformed layers of the stromal line S1738 for 4 weeks in
limiting dilution conditions exactly as described.4,39 Conditions were
chosen so that less than 20% of the wells contained a colony of small
granulocytic cells after 4 weeks of culture. This leads to a conditional
probability of 90% or more that each positive well (identified as containing
a colony of small granulocytic cells) is initiated by a single cell. Individual
positive wells were harvested by vigorous pipetting and injected intravenously into individual mice.4,39 (3) Purified HSCs: Single-lineage Rhodamine-123⫺Hoechst 33342⫺ side population cells (Lin⫺Rho⫺SP) cells
isolated from adult mouse BM were injected directly into individual
recipients. The approach, evaluation, and results from the single HSC
studies were described in detail by Uchida et al.7 For all LD experiments,
B6 mice, congenic for either CD45 or GFP, served as donors. Hosts were
sublethally irradiated W41/W41 (500 rads [5 Gy]) or lethally irradiated (2
doses of 550 rads [5.5 Gy], 2 hours apart) B6 mice.4,7,39 Whenever B6 hosts
were used, a genetically distinguishable source of radioprotecting cells was
coinjected as described.39 There were no differences in HSC function
between B6 and W41/W41 hosts, and data were pooled from both systems.
All mice were bled in regular intervals and the fraction of donor-type cells
in the lymphoid and myeloid lineages was measured by flow cytometry as
described.4,7,13,39 Briefly, purified white blood cells from each mouse at each
time point were split into 3 tubes and cells in each tube were either stained
for the CD45.1 donor-type marker or GFP expression was used as
donor-type marker. Thus, each time point had 3 measurements of donortype cells, and the resulting error of measurement is used in the symbolization of the kinetics. At each time point, cells were also stained with Thy-1 to
detect T cells, B220 for B cells, or Mac-1 and Gr-1 for myeloid cells.
Lin⫺Rho⫺SP repopulated mice were analyzed as described.7 Mice
were considered to be repopulated if their blood contained 3% or
more donor-type cells at least at any one time point and if donor-type T
and B lymphocytes and macrophages and granulocytes were found at the
same time.39
Classification of clone types and statistics
Based on the level of donor-type cells measured over time in blood,
individual HSC clones were classified according to the shape of the
repopulation curve as described previously.4,40 Briefly, donor-type cell data
were plotted as a function of time. Individual slopes of each of the
repopulation curves were then symbolized, where an increase in repopulation is denoted by “⫹,” a decrease by “⫺,” and a flat segment by “␲.” A
segment was called flat if the difference between the adjacent values of the
2 points was equal to or smaller than the standard error of the measurements
of corresponding donor-type cells.4,40 The relative Hamming distance41 for
all kinetics was then pair-wise calculated, and kinetics with a Hamming
distance of 0 were sorted into groups. Therefore, each group contains only
kinetics with identical shapes. As described previously in detail,4,40 the
Hamming distance measures the number of mismatches in the comparison
of 2 aligned strings of equal length formed over a fixed alphabet of symbols.
More formally, assigning the value m(x, y) ⫽ 0 to a match (x ⫽ y) and the
value m(x, y) ⫽ 1 to a mismatch (x ⫽ y), the Hamming distance of 2 strings
A ⫽ a1 a2 . . . aN, B ⫽ b1 b2 . . . bN is given as the sum over m(ai, bi) for
1 ⱕ i ⱕ N. Hence, with n ⫽ 3 and the alphabet (⫹, ⫺), the sequence “⫹ ⫹
⫹” has Hamming distance 0 to itself, but Hamming distance 1 to the
sequence “⫹ ⫺ ⫹.”
To approximate the output of differentiated cells per HSC clone during
the first 7 months after transplantation, we used the area under the curve
(AUC). The AUC values of all clones examined followed a roughly
biphasic distribution. Accordingly, AUCs were classified as low (ⱕ 200;
range, 14-196) or high (⬎ 200; range, 227-513).
We used an add-constant estimator to determine the probability of new
kinetics occurring after a number of kinetics has already been observed.42
The probability of a seen kinetic x is Pseen (x) ⫽ (c(x) ⫹ ␭)/(N ⫹ ␭X),
where ␭ is the estimator constant, c(x) is the number of times that the kinetic
x is observed, N is the total number of events already seen, and X denotes
the size of the corpus of all events. Hence, the probability that the next event
is an as-yet-unseen kinetic is Punseen ⫽ 1 ⫺ Pseen. We chose ␭ ⫽ 1/X .
Results
Previously, we described a highly efficient method for isolating
repopulating HSCs on the clonal level. For this, BM cells were
allowed to repopulate stromal cell–supported cultures in limiting
dilution. After 4 to 5 weeks, individual cultures were injected into
individual ablated congenic hosts.4,39 Donor-type cells in blood
were measured bimonthly by flow cytometry, and the mice were
followed for at least 7 months following transplantation. As
previously described, a high frequency of the mice showed
donor-type cells in blood, indicating that these mice had received
an HSC. Here, we used this approach to generate a large panel of
clonally repopulated hosts. Fifty-seven clones were followed for at
least 7 months. The kinetics of repopulation of all of these 57 HSC
clones are depicted in Figure 1A. The data emphasize the extensive
fluctuations and heterogeneity expected when individual HSC
clones are monitored over time. There appears to be no underlying
order or patterns in this set of kinetics.
The average of these clonal kinetics shows a curve that
reaches a plateau early and then stays flat (Figure 1B). This is
reminiscent of the kinetics of repopulation obtained when mice
receive transplants of high numbers of HSCs.43 This supports
the interpretation that population-based analyses of HSCs mask
the behavior of individual HSC clones. At the same time, the
data (Figure 1B) indicate that the behavior of populations of
HSCs reflects a reasonable superposition of the behavior of the
individual clones.
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BLOOD, 15 MARCH 2006 䡠 VOLUME 107, NUMBER 6
Figure 1. Individual repopulating kinetics of clonally derived HSCs. Shown are
the percent donor-type cells in blood at the indicated time points after the clones
received injections. (A) Fifty-seven clonal HSCs isolated after in vitro LD. All clones
(repopulated mice) obtained by this approach in our lab that yielded at least 7 months
of data are shown (a few clones have been described previously4,13). (B) The mean
repopulation curve (⫾ SD) of all clonal curves. The arithmetic mean of the data in
Figure 1A is shown for each time point.
Families of repopulation kinetics
A visual inspection of the clonal repopulation kinetics (Figure 1A)
revealed no obvious patterns. Previously, we described a powerful
method to quantify similarities based on the shape of kinetics.4,40
For this approach, individual segments of each repopulation curve
(Figure 1) were symbolized. A positive slope is assigned a “⫹,” a
flat segment a “␲,” and “⫺” indicates a negative slope. The
resulting symbolized sequences are then pair-wise compared and
their Hamming distance was calculated. The Hamming distance is
a quantitative classifier of similarities among short time-series—in
this case HSC repopulation kinetics. Kinetics that have the same
sequence of symbols have a Hamming distance of 0 and are
considered to be identical.
This approach was applied to the repopulation kinetics shown in
Figure 1, and HSC kinetics that were identical by these criteria
Figure 2. The repertoire of clonal HSC repopulation kinetics.
Each graph depicts a different family of repopulation kinetics,
identified after comparison of symbolized kinetics by Hamming
distance. The symbolized slopes for each group of kinetics are
indicated in each panel, where the slope of each segment is
expressed as positive (⫹), negative (⫺), or flat (␲). Groups were
further subdivided according to whether their AUC value was high
(1) or low (2). Solid lines indicate data from the same 57 mice
shown in Figure 1A. The dashed lines portray similarly analyzed
data from 27 HSC clones followed in mice that received injections
of freshly isolated BM cells (in vivo LD).
CLONAL REPERTOIRE OF STEM CELL FUNCTION
2313
were sorted into groups. Figure 2 depicts the groups of repopulation kinetics identified by this approach. The symbolized shapes of
the kinetics are indicated for each group. It is clear that the
approach identifies discrete families of kinetics (Figure 2).
Because each repopulation kinetic consists of 3 segments or
slopes, combinatorially, this approach allows for 27 possible types
of kinetics. Yet, only 12 kinetics (ie, about 40%) were identified
among the HSC clones tested (Figure 3A). As an additional
parameter, we classified clones as large or small based on their
AUC value. The AUC was used as a rough measure of the number
of differentiated progeny produced from each HSC clone over the 7
months of follow-up. The slopes together with the AUC generated a
quadruple of meta data. In this case, the total number of possible
families is 54. Strikingly, the kinetics observed did not show all
possible behaviors—rather only 16 discrete families of kinetics
(29%) were seen (Figure 2).
If this classification of the kinetics is a meaningful description
of HSC behavior, then the results should be independent of the way
the HSCs are isolated. To test this, we generated HSC clones by
injecting limiting numbers of freshly explanted BM cells directly
into ablated hosts.36 We analyzed 27 HSC clones, obtained from 4
independent in vivo LD experiments. All of these clones (Figure 2,
dashed lines) readily fell into the existing families. The distributions of the kinetics of HSC clones from the in vivo and the in vitro
LD approaches (Figure 3A) showed a high degree of correlation
(r2 ⫽ 0.80; P ⬍ .001). Thus, the 2 approaches yielded similar
results, indicating that both methods identified the same types of
HSC. The HSC clones from the in vivo and in vitro LD were
combined to create a set of 84 unmanipulated HSC clones
(Figure 2).
To estimate the probability that examination of additional
clones would reveal new groups, we used the add-constant
estimator. This determines the probability of new events occurring
after a number of events has already been observed.42 For both
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2314
BLOOD, 15 MARCH 2006 䡠 VOLUME 107, NUMBER 6
SIEBURG et al
Predicting self-renewal capacity
Our analysis focused on the kinetics of repopulation for the first 7
to 8 months after transplantation. Does the classification of HSC
clones during this time have predictive value for their long-term
behavior? To test this, we followed the self-renewal capacity of the
HSC clones in serial transplantation. The data are summarized in
Table 1. The analysis of the ⫹ ⫹ ⫹ groups is perhaps the most
complete: All 10 HSC clones examined from these groups were
capable of self-renewal and generated daughter HSCs that repopulated secondary hosts, and 70% of these clones repopulated tertiary
hosts. A marked reduction (33% of the clones) in the ability to
repopulate tertiary hosts was seen for HSCs with kinetics that
flattened or declined after 5 months. HSCs with kinetics that
flattened even earlier—after 3 months—repopulated secondary
hosts, but none self-renewed sufficiently to repopulate tertiary
hosts. Clones in the ⫺ ⫺ ⫺ group failed to repopulate even
secondary hosts (Table 1). Overall, HSC clones with an initial
positive slope are more likely to contribute long term than HSC
clones with an initial negative slope. While the number of clones
followed is too low to arrive at definitive conclusions at this point,
the data support the concept that the initial kinetics predict the
long-term behavior of HSCs.
Figure 3. Distribution of HSC groups from different sources. The percent of
clones of each type for each origin of HSC studied is shown. The kinetic families as
defined in Figure 2 are shown on the horizontal axis. Here, the AUC subclassification
was not used because of the low number of clones derived from in vivo LD (n ⫽ 27)
and from purified HSCs (n ⫽ 13). Vertically, each bar represents the percent of
kinetics that fall within the indicated family. (A) Comparison of HSC groups derived
after in vitro and in vivo LD. (B) Comparison of groups derived from unpurified HSCs
(data for in vivo and in vitro LD combined) and purified Lin⫺Rho⫺SP HSCs.
classifications (with and without the AUC parameter), the probability of finding new kinetics is approximately 1% (P ⬍ .001). In
other words, on average one new group would be expected if an
additional 100 sets of 84 clones each were analyzed. The negligible
probability of finding new groups indicates that the analysis
covered the complete repertoire of repopulation behaviors of HSCs
in adult B6 mice.
Discussion
We present here a systematic and complete analysis of HSC
heterogeneity as assessed by clonal repopulation patterns obtained
in rigorous long-term transplantation assays of a large number (97)
of clonally derived HSCs. The results indicate that only a fraction
of all possible patterns of repopulation is actually observed and that
any additional patterns are likely to be extremely rare. Furthermore,
we show a positive association between self-renewal and continuously increasing repopulation levels in the first 7 months after
transplantation in the primary recipient. These findings are not
consistent with a model in which HSCs are viewed as a homogeneous population of cells that respond to the conditions in vivo in a
stochastic manner. Such models would be expected to give a
functional continuum of clonal kinetic and self-renewal patterns.
Such models also predict that each HSC clone should be able to
Purified HSCs
Since we wished to include all types of HSCs found in BM, we had
so far avoided a phenotypic definition of HSCs. Next, we examined
repopulation data from mice that received transplants of single
freshly isolated, but purified, Lin⫺Rho⫺SP cells. Single cells were
injected into individual mice and mice were followed at a different
center.7 All of the 13 clones available for analysis fell into groups
that had already been seen (Figure 2), and no new clonal patterns
were identified (Figure 3B). Thus, data from 2 different labs and 3
different methods of purification generated HSCs that fell into the
same categories. However, the population of Lin⫺Rho⫺SP cells
contained fewer families of kinetics, and the distribution of the
remaining families was significantly skewed when compared with
those found in unseparated BM (r2 ⫽ 0.31, P ⫽ .05). For example,
Lin⫺Rho⫺SP cells were enriched for HSCs with ⫺ ⫺ ⫺ and ⫹ ⫹
⫺ kinetics (Figure 3B). Since the Lin⫺Rho⫺SP cells were directly
injected into the hosts, we also compared their kinetics with the
subset of 27 HSC clones isolated following in vivo LD. Again,
there is a noticeable lack of correlation (r2 ⫽ 0.08, P ⫽ .58).
Overall, the data suggest that the Lin⫺Rho⫺SP purification protocol
selectively enriches some subsets of all the HSCs found in BM.
Table 1. Long-term repopulation behaviors of HSC clones in
different groups
Repopulation*
Group
No. tested
Secondary
Tertiary
⫹⫹⫹1
6
6
4
⫹⫹⫹2
4
4
3
⫹⫹␲1
2
2
1
⫹⫹⫺1
3
3
1
⫹⫹⫺2
1
1
0
⫹⫺⫹1
4
3
2
⫹⫺⫹2
1
0
ND
⫹⫺⫺1
2
2
0
⫹⫺⫺2
2
2
0
⫺⫺⫹
1
0
ND
⫺⫺⫺
1
0
ND
ND indicates not done; tertiary transfers were not attempted if secondary hosts
were not repopulated.
*BM cells were isolated from primary and secondary hosts at least 7 months after
transplantation for transfer into secondary and tertiary hosts, respectively. In each
case, 5 ⫻ 106 BM cells were injected and the same methods and criteria were used to
identify repopulated mice as for primary hosts (“Materials and methods”). Data are
extended and modified from Muller-Sieburg et al.13
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BLOOD, 15 MARCH 2006 䡠 VOLUME 107, NUMBER 6
CLONAL REPERTOIRE OF STEM CELL FUNCTION
regenerate the heterogeneity seen in the HSC compartment.
However, as shown previously,4 when clonally derived HSCs
self-renew in a primary host, they generate daughter HSCs that
are remarkably similar to each other in repopulation kinetics as
shown in multiple secondary hosts. Thus, self-renewal did
perpetuate predetermined clonal patterns and did not generate
heterogeneity.4 Overall, the data favor a model where the HSC
compartment consists of a limited number of distinct types of
HSCs, each with predictable, epigenetically fixed repopulation
and self-renewal behavior.
The interpretation that HSCs show only a limited number of
repopulation behaviors of course assumes that many repopulation
patterns are realizable in the transplantation model. That this is the
case is supported by a quick survey of repopulation kinetics found
after transplantation with multiclonal HSC grafts. Just from data
published from this laboratory,4,40,44 an additional 9 kinetics (not
considering AUC) can readily be identified following transplantation of polyclonal grafts. Additional repopulation kinetics can be
estimated from multiclonally repopulated hosts described by
others.3,8,9,45 Thus, as expected (Figure 1B), combinations of clonal
patterns can generate new kinetics seen after polyclonal transplants. This confirms that the transplantation assay can reveal many
different patterns and emphasizes that individual HSCs realize only
a subset of the possible kinetics.
HSC repopulation kinetics were compared here based on the 3
slopes of the repopulation kinetics and the AUC as an estimate of
the clone size. The data suggest that these parameters are reasonably good predictors for self-renewal capacity and overall production of differentiated progeny by the HSC. These are arguably the
most important functions of HSCs. Yet, it may be interesting to add
more biologic parameters to the analysis, such as homing ability46
or the ability to respond to external stimuli,7,15 to refine the
classification of the HSC compartment. It is also possible to add
more parameters to the mathematic analysis. For example, some of
the groups in Figure 2 appear to be less homogeneous than most
others. This is mostly caused by differences in the steepness of the
2315
slopes (eg, Figure 2 the ⫹ ⫺ ⫺ 1 group, initial segments). When
additional parameters were added to classify the angle of the
slopes, a visually more homogeneous picture emerges. Yet, each
new classifier dramatically increases the number of possible groups
with a concurrent increase in the probability that the HSC kinetics
show only a limited subset of possible behaviors. Thus, adding
more classifiers strengthens the interpretation.
An unexpected finding was that purified Lin⫺Rho⫺SP cells
were selectively enriched for certain subsets of HSCs. There were
few kinetics in the group of Lin⫺Rho⫺SP cells, and it is possible
that an extended analysis would fill in the missing groups. Yet, it is
likely that the kinetics published are the most prevalent in these
populations and reflect the distribution of the HSCs in this
population. This would support the idea that phenotype-based
enrichment protocols deplete some and enrich other HSC subsets.
It will be interesting to look at additional phenotypically defined
populations that are enriched for HSCs. That a rigorous description
of the composition of HSC populations is important was highlighted by the disparate results obtained by different groups that
attempted to catalog the expressed gene program of HSCs.47-49 The
(statistically) complete description of repopulation patterns of
HSCs from adult B6 BM reported here now can serve as a standard
against which the clonal composition of different populations of
purified HSCs can be compared.
It is worth noting that the analysis shown here does not address
how the diversity of HSC behaviors is generated or whether it
changes during development and aging. It might be possible to
isolate prospectively the different subsets of HSCs that define the
different families. This would undoubtedly help in dissecting the
molecular basis for these functional differences. Such functional
differences would be of some interest for future applications of
HSCs for therapeutic purposes. For example, HSCs that repopulate
rapidly but for short time periods would be ideally suited for
supportive therapy after myeloablation, whereas HSCs with long
life spans would be the most desirable candidates for gene therapy.
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2006 107: 2311-2316
doi:10.1182/blood-2005-07-2970 originally published online
November 15, 2005
The hematopoietic stem compartment consists of a limited number of
discrete stem cell subsets
Hans B. Sieburg, Rebecca H. Cho, Brad Dykstra, Naoyuki Uchida, Connie J. Eaves and Christa E.
Muller-Sieburg
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