Human haematopoietic stem cell lineage commitment is a
continuous process
Lars Velten
1,#
, Simon F. Haas
2,3,4,#
, Simon Raffel
2,4,5,#
, Sandra Blaszkiewicz
2,3
, Saiful
Islam
6
, Bianca P. Hennig
1
, Christoph Hirche
2,3
, Christoph Lutz
5
, Eike C. Buss
5
, Daniel
Nowak
7
, Tobias Boch
7
, Wolf-Karsten Hofmann
7
, Anthony D. Ho
5
, Wolfgang Huber
1
,
Andreas Trumpp
2,4,8,10,*
, Marieke A.G. Essers
2,3,10,*
, and Lars M. Steinmetz
1,6,9,10,*
1
European Molecular Biology Laboratory (EMBL), Genome Biology Unit, 69117 Heidelberg,
Germany
2
Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH),
69120 Heidelberg, Germany
3
Division of Stem Cells and Cancer, Haematopoietic Stem Cells and Stress Group, German
Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
4
Division of Stem Cells and Cancer, German Cancer Research Center (DKFZ), 69120
Heidelberg, Germany
5
Department of Internal Medicine V, University of Heidelberg, 69120 Heidelberg, Germany
6
Department of Genetics, Stanford University School of Medicine, Stanford, California 94305,
USA
7
Department of Hematology and Oncology, Medical Faculty Mannheim, University of Heidelberg,
68167 Mannheim, Germany
8
German Cancer Consortium (DKTK)
9
Stanford Genome Technology Center, Palo Alto, California 94304, USA
Abstract
Blood formation is believed to occur through step-wise progression of haematopoietic stem cells
(HSCs) following a tree-like hierarchy of oligo-, bi- and unipotent progenitors. However, this
model is based on the analysis of predefined flow-sorted cell populations. Here we integrated flow
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*
Correspondence should be addressed to AT (a.trumpp@dkfz-heidelberg.de), MAGE (m.essers@dkfz-heidelberg.de) or LMS
(larsms@embl.de).
10
Co-senior author
#
These authors contributed equally to this work
Author Contributions
S.F.H., S.R., L.V., S.B and C.H. performed the experiments. L.V. analysed the data, with conceptual input from S.F.H., S.R., L.M.S.,
M.A.G.E. and A.T., and analytical advice from W.H.. S.I. and B.P.H. optimized genomics methods. C.L., E.C.B., D.N., T.B., W.K.H.
and A.D.H. obtained bone marrow aspirates. L.V., S.F.H., S.R., M.A.G.E., L.M.S. and A.T. jointly conceived and designed the study,
and wrote the manuscript.
Author information
The authors declare no competing financial interests.
HHS Public Access
Author manuscript
Nat Cell Biol
. Author manuscript; available in PMC 2017 September 20.
Published in final edited form as:
Nat Cell Biol
. 2017 April ; 19(4): 271–281. doi:10.1038/ncb3493.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
cytometric, transcriptomic and functional data at single-cell resolution to quantitatively map early
differentiation of human HSCs towards lineage commitment. During homeostasis, individual
HSCs gradually acquire lineage biases along multiple directions without passing through discrete
hierarchically organized progenitor populations. Instead, unilineage-restricted cells emerge
directly from a “Continuum of LOw primed UnDifferentiated hematopoietic stem- and progenitor
cells” (CLOUD-HSPCs). Distinct gene expression modules operate in a combinatorial manner to
control stemness, early lineage priming and the subsequent progression into all major branches of
haematopoiesis. These data reveal a continuous landscape of human steady state haematopoiesis
downstream of HSCs and provide a basis for the understanding of hematopoietic malignancies.
INTRODUCTION
All mature blood and immune cells are thought to derive from self-renewing and multipotent
HSCs. According to the current model, initiation of differentiation is associated with the loss
of self-renewal and generation of discrete multipotent, oligopotent and subsequently
unipotent progenitor cell stages
1,2
. These lineage-restricted progenitors are thought to be
generated in a stepwise manner by several subsequent binary branching decisions leading to
the classical hierarchical tree-like model of haematopoiesis
1-6
. However, this model is
mainly based on analyses of FACS-purified cell populations. Even if followed up by single
cell assays
3,4,7
, such analyses derive average properties of predefined cell populations and
thereby miss both quantitative changes within gates as well as transition states falling
between often subjectively set gates.
Moreover, the lineage contribution associated with each population is typically determined
by assays such as colony formation or transplantation. While these assays read out lineage
potential, the actual cell fate during homeostasis
in vivo
may be different
8,9
. Depending on
the assays and markers used, partly conflicting branching points and hierarchies have been
proposed
10-14
.
Recent studies based on novel single-cell approaches have challenged more fundamental
aspects of this classical model. For instance, unipotent progenitors can derive directly from
HSCs without proceeding through oligopotent progenitors
14,15
and lineage commitment was
observed in progenitors proposed to be oligopotent
7,10,16
. However, many of these studies
focused on more differentiated compartments
7,10,16
or used predefined subpopulations to
investigate single-cell heterogeneity
7,17
, impeding the characterization of transitions
between cell stages. Therefore, it remains unclear how individual HSCs enter lineage
commitment during homeostasis
in vivo
. To establish a comprehensive model of
haematopoiesis that can reconcile previous findings, a combined view of transcriptomic and
functional changes along the developmental progression of individual cells is required. Here
we developed an approach that integrates the reconstruction of developmental
trajectories
18,19
with the quantitative linkage between transcriptomic and functional single
cell data
17
and thus provides a detailed view on lineage commitment of individual
haematopoietic stem and progenitor cells (HSPCs) into all major branches of human
haematopoiesis.
Velten et al. Page 2
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RESULTS
Healthy human bone marrow cells were labelled with a panel of up to 11 FACS surface
markers commonly used to characterize human HSPCs
5,6
(see Methods, Supplementary
Table 1). All HSPCs, defined by the absence of lineage markers (Supplementary Table 1)
and expression of CD34 (Lin
-
CD34
+
), were individually sorted and enriched for immature
cells (see supplementary methods). The surface marker fluorescence intensities of all
markers were recorded to retrospectively reconstruct immunophenotypes (CD10, CD38,
CD45RA, CD90, CD135, and depending on the experiment CD2, CD7, CD49f, CD71,
CD130, FCER1A, ITGA5 and KEL, Supplementary Fig. 1a). Such index-sorted HSPCs
derived from the bone marrow of two healthy individuals were subjected to RNA-Seq
analysis (index-omics, 1034 and 379 single cells; see Supplementary Fig. 1b for the
distribution of cells within classically defined gates
5,6
and Supplementary Fig. 2 for quality
metrics of single cell RNA-Seq) to determine their transcriptomes or individually cultured
ex
vivo
(“index-culture”, 2038 single cells) to quantify megakaryocytic, erythroid and myeloid
lineage potential. Subsequently, the functional and transcriptomic data sets were integrated
by regression models using commonly indexed surface marker expression to identify the
molecular and cellular events associated with the differentiation of human HSCs at the
single cell level (Fig. 1). To make this data type accessible, we developed
indeXplorer
, a
web-based platform that combines features of FACS software (e.g. custom gating) with tools
for single-cell transcriptomics data analysis (e.g. differential expression analysis, clustering,
principal component analysis) in a single graphical user interface (Supplementary Fig. 3 and
http://steinmetzlab.embl.de/shiny/indexplorer/?launch=yes).
Early haematopoiesis is a continuous process
HSCs and their immediate progeny, such as multipotent progenitors (MPPs) or
multilymphoid progenitors (MLPs), are located in the Lin
-
CD34
+
CD38
-
compartment,
whereas more differentiated progenitors reside in the Lin
-
CD34
+
CD38
+
compartment
5,7
.
Global gene expression analysis of single cells within these two compartments revealed
fundamentally different transcriptomic structures. In both individuals, the Lin
-
CD34
+
CD38
+
progenitors could be separated into clusters corresponding to distinct progenitor cell types of
all major branches of haematopoiesis (Fig. 2a and see below). In contrast, clustering within
the Lin
-
CD34
+
CD38
-
compartment was largely unstable, as demonstrated by cluster stability
analysis (Supplementary Fig. 4a), the absence of clusters according to Gap statistics
(Supplementary Fig. 4b), and a recently published algorithm for the clustering of single
cells
20
(Supplementary Fig. 4c). A simulated series of random steps from an individual cell
to one of its nearest neighbours (see methods) revealed that the majority of
Lin
-
CD34
+
CD38
-
cells were highly interconnected, contrasting the disconnected cell types
from the Lin
-
CD34
+
CD38
+
compartment (Fig. 2b). Unsupervised visualization of all
individual cells irrespective of FACS markers by t-SNE confirmed that Lin
-
CD34
+
CD38
-
cells formed a single continuously connected entity. In contrast, Lin
-
CD34
+
CD38
+
cells
emerged into locally clustered cell populations, with the exception of some phenotypic
CMPs and CD10
+
MLPs, suggesting that the classification based on differential CD38
expression is excellent, but not absolute (Fig. 2c).
Velten et al. Page 3
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Notably, the absence of hierarchical structures in the primitive Lin
-
CD34
+
CD38
-
compartment was due to the gradual nature of differences between cells in that
compartment, and not due to insufficient data quality or a lack of transcriptomic
heterogeneity: A principal component analysis of Lin
-
CD34
+
CD38
-
cells resolved more than
10 distinct, variable biological processes in this compartment, such as cell cycle activation
and lineage priming (Supplementary Fig. 4d-f). These processes are tightly correlated to
surface marker expression (Supplementary Fig. 4g).
Collectively, these observations are incompatible with the classical model of early
haematopoiesis, which assumes a hierarchical tree-like structure of discrete progenitors
downstream of HSCs. In contrast, our data suggest that HSCs and their immediate progeny
are initially part of a Continuum of LOw-primed UnDifferentiated (“CLOUD”)-HSPCs
within the Lin
-
CD34
+
CD38
-
compartment (see also below). Discrete populations are only
established when differentiation has progressed to the level of restricted progenitors
typically associated with the up-regulation of CD38.
Lineage-restriction downstream of the HSPC continuum
To characterize the discrete populations in the Lin
-
CD34
+
CD38
+
compartment, we
performed gene expression and cell surface marker analyses as well as functional validations
at the single cell level. Our analyses revealed that these populations correspond to lineage-
restricted progenitors of all major branches of bone marrow haematopoiesis, including B-
cell progenitors of distinct stages, megakaryocyte/erythrocyte committed progenitors (ME,
Ery, Mk), neutrophil-primed progenitors (Neutro), monocyte/dendritic cell (Mono/DC)
progenitors, and eosinophil/basophil/mast cell progenitors (Eo/Baso/Mast), as well as
immature myeloid progenitors (Fig. 3a, Supplementary Table 2). Importantly, populations
cluster by cell type and not by individual in a cross-individual comparison (Fig. 3b). The
comparison of the surface marker expression of these populations to the commonly applied
gating scheme
5
using our indexed data set showed that immunophenotypically defined
oligopotent progenitor populations (megakaryocyte-erythroid progenitors, MEPs;
granulocyte-monocyte progenitors, GMPs; B cell–NK cell progenitors, B-NKPs) were
mainly comprised of cell types with unilineage-specific gene expression profiles (Fig. 3c)
and functional unipotency (Fig. 4a,b).
Cells within the classic GMP compartment were separated into several neutrophil-primed
progenitors (N0-N3), as well as into monocyte/dendritic cell progenitors (Mono/DC). The
distinct neutrophil-primed progenitors likely represent progenitors at different
developmental stages and granule composition (Fig. 4c, Supplementary Fig. 4h)
21,22
.
Immunophenotypically, all neutrophil- primed progenitors express the surface markers
CD135 and CD45RA, which are progressively upregulated during maturation (Fig. 4c). In
contrast to neutrophil-primed progenitors, Eo/Baso/Mast progenitors did not fall into the
classical GMP gate but displayed a Lin
-
CD34
+
CD38
+
CD10
-
CD45RA
-
CD135
mid
immunophenotpye (Fig. 3c), and expressed transcription factors important for early MEP
commitment (GATA2 and TAL1) supporting a recent study suggesting that granulocyte
subtypes might derive from distinct hematopoietic lineages
12
.
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The MEP gate consisted of megakaryocytic (Mk) progenitors expressing typical Mk genes,
of erythroid-committed (E1, E2) progenitors of distinct developmental stages, differing in
haemoglobin and GATA1 expression, as well as of subpopulations showing combined
expression of megakaryocytic and erythroid genes (M/E). Our single-cell transcriptome data
suggested CD71 (TRFC) and the red blood cell antigen KEL to be highly indicative for
erythroid fate, which was confirmed by single-cell culture assays using CD71 and KEL as
indexing antibodies (Fig. 4d).
For individual 2, two CD10
+
B-cell progenitor clusters (small pre-B cells, sB and large pre-
B cells, lB) were observed. sB was characterized by high CD9 mRNA expression, high
CD10 surface expression and small cell size (FSC), whereas lB showed high expression of
interleukin-7 receptor (IL7RA) mRNA, intermediate CD10 surface levels, expression of cell
cycle related genes and large cell size (Fig. 4e, Supplementary Fig. 4i, Supplementary Table
2). This suggests that sB corresponds to small pre-B cells, and lB to large pre-B cells,
progenitor populations which have been well characterized in the murine system, but to a
lesser extent in the human system
23
. To validate and prospectively isolate large pre-B-cells
and small pre-B-cells, we used IL7RA and CD9 FACS markers, which allowed us to
recapitulate the levels of CD10 surface expression, cell size and cell cycle activity as
predicted from the index-omics data (Fig. 4f, Supplementary Fig. 4j). In contrast to
individual 2, in individual 1, only small pre-B-cells were observed (Fig. 3b).
For both individuals, we also observed CD38-positive HSPCs with a gene expression profile
of rather immature cells (Im) (Fig 3a). These clustered globally with the Lin
-
CD34
+
CD38
-
compartment in t-SNE analyses, and expressed lower levels of CD38 (Supplementary Fig.
4k). Most of these cells displayed an immunophenotype typical for CMPs
(Lin
-
CD34
+
CD38
+
CD45RA
-
CD135
+
), however the composition of the cell types present in
the CMP gate depends strongly on the exact gating strategy applied (see below,
Supplementary Fig. 5h, i).
Based on these analyses, we provide markers and gating strategies for the prospective
isolation of several of these newly defined populations using standard flow cytometry.
Developmental trajectories of early human haematopoiesis
To obtain a detailed view on the transition from stem cells to lineage-restricted progenitors
in the continuous HSPC landscape, we developed STEMNET, a new dimensionality
reduction algorithm. STEMNET identifies genes specific to the six Lin
-
CD34
+
CD38
+
restricted progenitor populations defined above (Neutro, Eo/Baso/Mast, B-cell, Mono/DC,
Ery and Mk; see Supplementary Table 3 for a list of genes used by STEMNET) and then
computes the probability that each primitive (“CLOUD”) HSPC can be assigned to any of
these classes. STEMNET thereby places the six developmental endpoints on the corners of a
simplex. This resulted in the arrangement of the least primed HSCs, such as CD49f
+
HSCs,
to the centre, and the remaining HSPCs localizing in between according to their degree of
priming (Fig. 5a, and see Supplementary Fig. 5a, b for individual 2). To describe the position
of each cell we computed the
predominant direction of priming d
as the developmental
endpoint closest to the cell and the
degree of lineage priming
S
rel
as the (Kullback-Leibler)
distance from the least-primed cell.
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