REVIEW
ThymusandTCellDevelopmentFocus
Transcriptional network dynamics in early T cell
development
Boyoung Shin
1
, Samantha J. Chang
1
, Brendan W. MacNabb
1
, and Ellen V. Rothenberg
1
The rate at which cells enter the T cell pathway depends not only on the immigration of hematopoietic precursors into the
strong Notch signaling environment of the thymus but also on the kinetics with which each individual precursor cell reaches
T-lineage commitment once it arrives. Notch triggers a complex, multistep gene regulatory network in the cells in which the
steps are stereotyped but the transition speeds between steps are variable. Progenitor-associated transcription factors delay
T-lineage differentiation even while Notch-induced transcription factors within the same cells push differentiation forward.
Progress depends on regulator cross-repression, on breaching chromatin barriers, and on shifting, competitive collaborations
between stage-specific and stably expressed transcription factors, as reviewed here.
Introduction
Early thymic T cell development orchestrates a one-way tran-
sition between two states, from a multipotent state to a T-lineage
committed state (
Hosokawa and Rothenberg, 2021
;
Li et al.,
2010a
,
2010b
;
Yui et al., 2010
). It entails both the installation
of the T cell identity program (activation) and the successful
shutdown of plasticity toward no
n-T cell fates (repression). Pro-
found switches in gene expression programs, chromatin accessi-
bility profiles, demarcation of active and repressive histone
marks, and three-dimensional (3D) chromatin architectures all
occur during this cell type conversion event (
Belyaev et al., 2012
;
Hu et al., 2018
;
Isoda et al., 2017
;
Yui and Rothenberg, 2014
;
Zhang
et al., 2012b
;
Zhou et al., 2019
). Intriguingly, the speed at which
this conversion occurs can vary
greatly, with a major slowdown
between the process in the fetal thymus and the corresponding
events in the postnatal thymus (
Lu et al., 2005
;
Ramond et al.,
2014
). Thus, even when the regulatory drivers of T cell commit-
ment are defined, the responses to them may be governed by
variable sets of rules.
Years of research by many groups have identified a group of
transcription factors (TFs) that are distinctively active in the
T cell lineage. TCF-1 (encoded by the
Tcf7
gene), GATA-3, and the
zinc finger TF Bcl11b, working together with the more broadly
expressed basic helix-loop-helix (bHLH) E proteins, E2A (
Tcf3
)
and HEB (
Tcf12
), and Runx family TFs and their common partner
CBF
β
are indispensable within the thymus to generate the pre-
cursors of all or nearly all T cell subsets (
Bain et al., 1997
;
Barndt
et al., 2000
;
Del Real and Rothenberg, 2013
;
Engel et al., 2001
;
Guo et al., 2008
;
Hattori et al., 1996
;
Li et al., 2010a
,
2010b
;
Scripture-Adams et al., 2014
;
Weber et al., 2011
;
Zhou et al.,
2022
). They act under the influence of Notch signaling to acti-
vate the genes essential for T cell identity. In addition, Ikaros
(
Ikzf
) family factors, Myb, Gfi1, and a shifting set of ETS (E26
transformation-specific) family factors play roles at multiple
developmental timepoints (
Anderson et al., 1999
;
Arenzana
et al., 2015
;
Bender et al., 2004
;
Chari and Winandy, 2008
;
Eyquem et al., 2004
;
Lieu et al., 2004
;
Oravecz et al., 2015
;
Phelan et al., 2013
;
Yu et al., 2010
;
Yucel et al., 2003
;
Zamisch
et al., 2009
). The T cell precursors thus generated then undergo
T cell receptor (TCR)
–
dependent selection and later diversify
through expression of additional factors including Th-POK
(
Zbtb7b
), T-bet and its relative Eomesodermin (
Eomes
), ROR
γ
t,
Foxp3, and/or PLZF (
Zbtb16
), together with contributions by dif-
ferent activation-driven TFs, especially STAT family factors, basic
leucine zipper factors such as Batf and Maf subfamily members,
and interferon-response factors (
Alonzo et al., 2010
;
Ciofani et al.,
2012
;
Egawa and Littman, 2008
;
He et al., 2000
,
2005
;
Jenkinson
et al., 2007
;
Kreslavsky et al., 2009
;
Muroi et al., 2008
;
Narayan
et al., 2012
;
Savage et al., 2008
;
Wang et al., 2008
,
2011
;
Xi et al.,
2006
;
Yosefetal.,2013
;
Zhao et al., 2022b
). However, the shared
origin of all these subsets of T cells springs from the actions of
TCF-1, GATA-3, Runx factors, the E proteins, and Bcl11b,
collaborating under the influence of strong Notch pathway
signaling in the thymus. All of these factors also work later in
thymic repertoire selection (
Jones-Mason et al., 2012
;
Kojo
et al., 2017
,
2018
;
Steier et al., 2023
;
Steinke et al., 2014
;
...............................................................................................................................
..............................................
1
Division of Biology and Biological Engineering California Institute of Technology, Pasadena, CA, USA.
Correspondence to Ellen V. Rothenberg:
evroth@its.caltech.edu
.
© 2024 Shin et al. This article is available under a Creative Commons License (Attribution 4.0 International, as described at
https://creativecommons.org/licenses/by/4.0/
).
Rockefeller University Press
https://doi.org/10.1084/jem.20230893
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Xiong et al., 2013
) and go on to play roles in the peripheral
T cells as well (
Bevington et al., 2017
;
Zhong et al., 2022
).
T cell identity itself is stable once established during
early thymocyte stages. An intrinsic core of T cell defining
gene expression (
Cd3g
,
Cd3d
,
Cd3e
,
Cd247
[also known as
TCR
ζ
],
Itk
,
Lck
,
Zap70
,and
Bcl11b
) persists throughout all of
the dynamic responses of mature T cells in their in vivo
environments (
Mingueneau et al., 2013
;
Yoshida et al., 2019
),
even despite the potential of memory T cells to undergo virtu-
ally unlimited rounds of proliferation (
Soerens et al., 2023
).
Notably though, the persistent expression of these core T cell
identity genes does not entirely depend on the persistence of the
original TFs responsible for turning on these genes during
early T cell development. In fact, some of these original TFs
are downregulated to near undetectability in some mature
T cell subsets, e.g., TCF-1 and LEF-1 in some subsets of ef-
fector T cells, and GATA-3 in many CD8 T cells (
Gounari and
Khazaie, 2022
;
Yoshida et al., 2019
;
Zhao et al., 2022a
). Thus,
some TF actions in T cell development must be hit-and-run,
stabilized later by other factors and/or epigenetic mecha-
nisms yet to be defined.
Thecentralfocusofthisreviewishowtheinitialmultipotency
epigenetic state can be pushed into a new, T-lineage
–
promoting
configuration, opening new T-lineage
–
associated enhancers and
shutting down progenitor cell enhancers. The basic question we
consider is how this process can be coordinated despite taking
highly varied lengths of time for the cells to escape from the
multipotent progenitor-cell state. Most of the data reviewed come
from the mouse system where detailed genetic and cellular ma-
nipulations are easier, but key results will be compared with
corresponding evidence that has emerged from the human sys-
tem. Recent evidence fills out the picture of a Notch-driven,
feed-forward gene network promoting T-lineage entry, but also
indicates that the individual ce
lls starting the T cell program are
initially held back in their response to Notch signaling by the
continuing operation of stem-pro
genitor factors. A regulatory
struggle between the progenitor-factor network and the Notch-
driven T cell gene network is seen to cause a staggered, asyn-
chronous entry of the cells into
the T cell program. Key factors
affecting the balance between the multipotent progenitor state
and the new T-lineage program have now been identified to-
gether with a rapidly clarifying picture of the genomic binding
patterns that confer their functional linkages within both net-
works. These factors are implicated as major positive and nega-
tive controllers of the speed with which cells launch the T cell
program.
Brief review of early thymic T cell development
Major stages of early T cell development in vivo
Thymic T cell development in postnatal mammals begins with
small numbers of lymphoid-lineage primed multipotent pro-
genitor cells from the bone marrow that migrate to the thymus
for their differentiation (
Ezine et al., 1984
;
Foss et al., 2001
;
Zietara et al., 2015
). These thymus-seeding cells may include
both common lymphoid progenitors (CLP) and lymphoid-primed
multipotent precursors (LMPP), which converge on the same
developmental pathway once in the thymus but differentiate
with different kinetics (
Benz et al., 2008
;
Saran et al., 2010
).
Thymic cortical epithelial cells provide Notch ligands and cyto-
kine signaling that ultimately instruct T cell development while
supporting cell proliferation (
Besseyrias et al., 2007
;
Felli et al.,
1999
;
Kyewski, 1987
;
Prockop et al., 2002
;
Sambandam et al.,
2005
). The developmental status of intrathymic T progenitor
cells at each stage can be marked by each cell
’
s transcriptional
programs, partially represented by sets of surface protein
markers. Initially, thymic pro-T cells are double negative (DN)
for CD4 and CD8 and do not express TCR chains because none of
the TCR coding loci are yet assembled by recombination. The
developmental steps of mouse DN cells encompass DN1 through
DN4 stages (DN1, DN2a, DN2b, DN3a, DN3b, and DN4) (
Fig. 1 A
).
These stages are traditionally distinguished by cKit, CD44, and
CD25 surface marker expression, along with additional surface
markers and TF reporters (e.g., Flt3, HSA, Ly6d, Thy1, CD27,
CD28, Bcl11b, etc.) (
Ceredig et al., 1985
;
Godfrey et al., 1993
;
Hosokawa and Rothenberg, 2021
;
Kueh et al., 2016
;
Ramond
et al., 2014
;
Sambandam et al., 2005
;
Taghon et al., 2006
;
Teague et al., 2010
;
Zhou et al., 2019
)(
Fig. 1 B
). Here, we use
“
DN1
”
only for the early thymic progenitor subset of CD44
+
CD25
−
cells, called ETP, marked as cKit
high
CD44
+
CD25
−
.Thecells
that have just seeded the thymus are a subset of this DN1 pop-
ulation, usually distinguished by the expression of Flt3.
Upon engaging with the thymic microenvironment, the DN1
and DN2a (cKit
high
CD44
+
CD25
+
) cells begin to execute the
T-lineage
–
specific developmental program, inducing a wave of
TFs necessary for T-lymphoid identity programs (discussed in
detail below). However, DN1 and DN2a cells are still capable of
generating other types of immune cells besides T cells. This does
not require any genetic modification (
“
reprogramming
”
)ofthe
cells, but simply moving them to Notch ligand-deprived envi-
ronmental conditions, thus demonstrating their intrinsically
“
uncommitted
”
states (
Balciunaite et al., 2005
;
Bell and Bhandoola,
2008
;
Kueh et al., 2016
;
Shen et al., 2003
;
Shortman et al., 1998
;
Wada et al., 2008
;
Yui et al., 2010
). This plasticity was long known
to be gone by the DN3 stage, and it is now clear that lineage
commitment to the T cell fate is normally finalized within the DN2
stage, during the DN2a to DN2b (cKit
int
CD44
+
CD25
+
) transition, as
pro-T cells from the DN2b stage onward no longer maintain the
potential to generate non-T cells (
Kueh et al., 2016
;
Yui et al.,
2010
). Forced genetic manipulation of DN3 cells can still enable
them to switch to alternative fates, and this has been useful in
elucidating the functions that underlie or oppose the com-
mitment process (
Del Real and Rothenberg, 2013
;
Franco et al.,
2006
;
Hosokawa et al., 2018a
;
Ikawa et al., 2010
,
2016
;
Laiosa
et al., 2006
;
Lefebvre et al., 2005
;
Li et al., 2010a
,
2010b
;
Qian
et al., 2019
;
Steier et al., 2023
;
Taghon et al., 2007
;
Ungerb
̈
ack et al.,
2018
); nevertheless, such genetic reprogramming depends on
breaking the endogenous regulatory state of the DN3 cells and not
on exploring the potentials it naturally affords. During and after
T-lineage commitment, DN2b and DN3 (cKit
low
CD44
−
CD25
+
)
progenitors establish the T-identity gene expression program
(
Fig. 1
) as an increasing number of T cell fate
–
promoting TFs is
turned on and cells upregulate the genes encoding the main ap-
paratus for TCR signaling:
Cd3g
,
Cd3d
,
Cd3e
,
Lck
,
Lat
,
Itk
,and
others (
Mingueneau et al., 2013
;
Zhang et al., 2012b
). One key
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outcome of the T-identity program in DN2b and DN3 stages is the
rearrangement and expression of TCR genes, enabled by strong
upregulation of
Rag1
and
Rag2
expression from DN2b to DN3a
stage.
Pro-T cells on the trajectory to generate conventional
αβ
T
cells rearrange the TCR
β
coding locus and perform a quality
check by inducing apoptosis of the cells that fail to express TCR
β
.
This quality checkpoint, called
β
-selection, marks the boundary
between DN3a (CD27
low
CD28
−
DN3) and DN3b (CD27
high
CD28
+
DN3) stages (
Taghon et al., 2006
;
Teague et al., 2010
)(
Fig. 1 B
).
Descendants successfully crossing this threshold proliferate
extensively, become CD4
+
CD8
+
“
double positive
”
thymocytes,
and undergo TCR repertoire selection. Other T-progenitors at
the DN2
–
3 stages recombine and express genes encoding TCR
γ
and TCR
δ
instead and become
γδ
Tcells(
Capone et al., 1998
;
Munoz-Ruiz et al., 2017
). The decision between
γδ
Tand
αβ
T
trajectories is a complex one that integrates intrinsic biases due
to alternative TF activities together with the cells
’
experience of
strength of TCR/CD3 complex signaling. Through most of this
review, we will treat both
αβ
and
γδ
T cells as emerging from the
same pool of DN1 and DN2a intrathymic precursors, but note
that some fetal-specific
γδ
T lineages probably arise from sepa-
rate prethymic sources (
Beaudin et al., 2016
;
Elsaid et al., 2021
;
Ikuta et al., 1990
).
The DN stages when T cell identity is formed have been in-
tensively studied by many groups to determine the extent and
order of gene expression and chromatin state changes (
Arenzana
et al., 2015
;
Hosoya et al., 2018
;
Hu et al., 2018
;
Oravecz et al.,
2015
;
Yoshida et al., 2019
;
Zhang et al., 2012b
). Because differ-
entiation is coupled with proliferation until the
β
-selection
checkpoint, at steady state, the fraction of DN cells within the
DN1 (ETP) stage(s) is minuscule, and it has been important to
use single-cell transcriptomics to characterize these early cells
fully. In mice (
Kernfeld et al., 2018
;
Sagar et al., 2020
;
Zhou et al.,
2019
) and humans (
Lavaert et al., 2020
;
Le et al., 2020
;
Zeng
et al., 2019
), a continuum of thymus-induced gene expression
changes is seen to begin within the DN1 stage, where a differ-
ence is already evident between initial thymus-seeding pro-
genitor (TSP) immigrants and more advanced DN1 (ETP) cells.
New genes are upregulated and progenitor legacy genes de-
crease expression in several stages as the cells enter the DN2a
stage and proceed up to
β
-selection, similarly in mice and hu-
mans overall, despite some species differences (
Le et al., 2020
;
Rothenberg, 2021
;
Taghon and Rothenberg, 2008
).
The chromatin accessibility, interaction, and compartment
landscapes of DN1 and DN2a cells are remarkably similar to
those of hematopoietic stem and multipotent progenitor cells
(
Hu et al., 2018
;
Yoshida et al., 2019
). However, there is a sharp
climax of gene expression change in the DN2a to DN2b transi-
tion coinciding with a particularly widespread shift in chro-
matin accessibility patterns across the genome (
Hu et al., 2018
;
Yoshida et al., 2019
) as the chromatin landscape flips from a
progenitor-like pattern to one resembling later T-lineage stages.
This discontinuity indicates that
“
commitment
”
is not just an-
other step in an incremental process but a global regulatory
transformation. Therefore, the developmental stages before
T-lineage commitment (DN1 and DN2a) are referred to here as
“
Phase 1
”
and the stages after T-commitment until
β
-selection
(DN2b and DN3a) are defined as
“
Phase 2
”
(
Yui and Rothenberg,
2014
)(
Fig. 1
).
In vivo versus in vitro models
In vivo, thymocytes migrate through a succession of anatomical
compartments during their progression from TSP to the com-
mitted DN3 stage, and this complex 3D stromal architecture
could certainly provide distinctive inductive signals at different
Figure 1.
Early thymic T cell development
stages and gene expression programs. (A)
The
diagram shows different T cell developmental
stages from bone marrow (BM) progenitors en-
tering the thymus and progressing through DN,
double positive (DP), and single positive (SP)
stages. The focus of this review, Phase 1 (un-
committed) and Phase 2 (T-lineage committed
but not yet assembled TCR
β
) are shown in green
and purple bubbles. The instructive Notch sig-
naling strengths are shown in light brown color.
The kinetics and amplitude of different gene
expression programs are represented in gray
boxes at the bottom.
(B)
The informative protein
markers utilized to identify different DN stages
are shown with flow cytometry plot diagrams.
The gray arrows represent developmental pro-
gression directions. Critical checkpoints (e.g.,
T-lineage commitment,
β
-selection) are also shown.
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stages along the way (
Buono et al., 2016
;
Lancaster et al., 2018
;
Lind et al., 2001
;
Love and Bhandoola, 2011
). Furthermore, the
organization of the fetal thymus when it is first populated is also
different from that of the postnatal thymus (
Anderson et al.,
2006
;
Holl
̈
ander et al., 2006
). Despite this, however, it is re-
markable that the succession of transcriptional states found
in vivo is very well replicated by purified hematopoietic pro-
genitors entering the T cell pathway in vitro (
Zhou et al., 2022
),
whether induced by monolayer cocultures with OP9-DLL1
(
Schmitt and Z
́
uñiga-Pflücker, 2002
)orTSt4-DLL1stroma
(
Miyazaki et al., 2005
), or with MS5-DLL4 stroma in artificial
thymic organoids (
Montel-Hagen et al., 2020
;
Seet et al., 2017
).
This indicates that a great part of the blueprint for the T cell
commitment process is based on cell-intrinsic gene network
circuitry operating in broadly permissive conditions of Notch
signaling, more than on a precisely choreographed sequence of
distinct, extrinsic signals.
While the stromal cocultures generally drive more prolifer-
ation in the earliest stages than the thymus microenvironment
does in vivo, the gene expression patterns they induce at each
DN stage match in vivo stages extremely closely (
Zhou et al.,
2022
). Furthermore, they enable precursor cells to differentiate
into T-lineage cells while preserving distinctive intrinsic fea-
tures of their T cell precursor activities. For example, they
faithfully preserve the cell-intrinsic differentiation speed dif-
ferences between CLP and LMPP precursors (
Montel-Hagen
et al., 2020
;
Taghon et al., 2007
) as well as the marked differ-
entiation speed differences between early fetal, late fetal, and
postnatal precursors (
Ramond et al., 2014
;
Scripture-Adams
et al., 2014
) (unpublished data) described below. This broad
concordance between in vivo and in vitro differentiation is
important in practical terms because it has allowed the roles of
particular regulators of the T cell developmental process to be
measured within rigorously defined developmental time win-
dows, something that is difficult if not impossible in vivo, and
has enabled cause and effect relationships and kinetics to be
demonstrated directly in real-time.
T lineage entry dynamics
The molecular events promoting the transition to T-lineage
identity occur in the context of rapid cell proliferation, in re-
sponse to signals from the thymic microenvironment including
Notch (throughout Phase 1 and Phase 2) and IL-7 signaling
(starting before T-lineage commitment) (
Garcia-Peydro et al.,
2006
;
Hare et al., 2000
;
Huang et al., 2003
;
Magri et al., 2009
;
Spolski et al., 2023
;
Tani-ichi et al., 2013
). In vivo in steady state,
the observed distribution of offspring cell numbers among each
stage, between precursor entry and the generation of T-lineage
committed precursors, is affected by the number of cell cycles
that thymic progenitor cells spend during each stage and the cell
death rate experienced at each stage (
Krueger et al., 2017
;
Manesso et al., 2013
;
Olariu et al., 2021
), not only the rate (or
efficiency) at which individual cells differentiate from one stage
to the next. This makes it difficult to gauge effects on develop-
mental speed as such from steady-state subset distributions
in vivo, as they can be mimicked or masked by compensatory
population effects.
When a discrete cohort of cells can be followed in real time,
however, both classic work with chimeras in vivo and more
recent studies on developmental kinetics in vitro have shown
that the developmental transition from Phase 1 to Phase 2 is a
slow process, at least in cells from adult mice. Transferring bone
marrow
–
derived progenitors into non-irradiated hosts showed
that progenitor cells remained at the DN1 stage for 9
–
10 days
across 7
–
10 cell divisions (
Manesso et al., 2013
;
Porritt et al.,
2003
), and cells spent an additional 2
–
3 days, roughly four
more cell divisions, to undergo T-lineage commitment (
Olariu
et al., 2021
). Consistent with high proliferation rates, developing
T-progenitors
’
single-cell transcriptomes often show that thy-
mocytes in all developmental stages from TSP until DN3a in-
clude a full range of cell cycle stages in mice and humans
(
Lavaert et al., 2020
;
Park et al., 2020
;
Zhou et al., 2019
,
2022
).
Thus, these time intervals between developmental milestones
each represent multiple cell cycles.
At the clonal level, thymocytes differentiate from TSP to
Phase 2 asynchronously. Most dramatically, TSPs in postnatal
thymus take much longer to go through the same apparent
stages than TSPs in fetal thymus, proliferating more along the
way (
Lu et al., 2005
), even though the overall order of TF
changes matches closely, in the transcriptome studies (
Belyaev
et al., 2012
;
Kernfeld et al., 2018
;
Sagar et al., 2020
)recently
reviewed in detail (
MacNabb and Rothenberg, 2023
). While this
could partly reflect the differences between the fetal and adult
thymic stromata in vivo, the cells also reproduce these differ-
ences in timing to reach defined phenotypic milestones when
differentiating on the
“
level playing field
”
of the OP9-DLL1
stromal cocultures, as noted above. Furthermore, even a single
cohort of prethymic LMPP precursors or a highly purified subset
of intrathymic DN1 (ETP) cells differentiates asynchronously
over a fixed time window (
Zhou et al., 2019
,
2022
). When
starting with single purified DN1 (ETP) thymocytes from a
postnatal mouse, direct live imaging of individual clones over a
period of 1
–
6 days, as well as endpoint phenotyping of individual
clones, has shown that different clones differentiate at signifi-
cantly different speeds from ETP to DN2a and again from DN2a
to DN2b (
Olariu et al., 2021
;
Zhou et al., 2019
). This asynchrony
is evident in real time despite scRNA-seq demonstrating that the
cells follow the same trajectories among transcriptional states
(
Zhou et al., 2019
,
2022
). For cells crossing the boundary from
uncommitted DN2a to committed DN2b, detailed imaging-based
pedigree analysis shows that even cells derived from the same
clonal precursor differentiate at different speeds (
Kueh et al.,
2016
;
Ng et al., 2018
). Stochastically timed system behavior is
not surprising in the context of mature T cell responses to an-
tigen receptor stimuli (
Feinerman et al., 2008
;
Kakaradov et al.,
2017
;
Richard et al., 2018
), but differs markedly from the de-
terministic timing of well-studied embryonic developmental
programs (
Clark and Akam, 2016
;
Peter et al., 2012
), which are
highly coordinated at 0.2
–
5 h timescales despite stochastically
bursty transcription at much shorter timescales (
Berrocal et al.,
2020
;
Bothma et al., 2014
). Thus, early T cell development can
encompass varying numbers of days and cell divisions while
responding to Notch signaling before the cells activate the T cell
core program and proceed to lineage commitment.
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Transcription factors regulating cell fates in Phases 1 and 2
The Phase 1 ground state
A large set of TF actions has been shown to underlie gene ex-
pression changes in early T cell precursors, defining many
connections in a T-lineage gene regulatory network (reviewed
by
Kueh and Rothenberg [2012]
;
Longabaugh et al. [2017]
;
Rothenberg [2019]
;
Shin and Rothenberg [2023]
). Developmen-
tal cell fate transition from Phase 1 to Phase 2 is mediated by
dynamic changes among gene expression subprograms associ-
ated with T-identity, stem and progenitor properties, alternative
lineage potentials, and cell proliferation, respectively, all of
which are potentially active in cells before commitment. These
programs form a modular structure of gene regulatory network
subcircuits, in which the expression of a group of genes within
each module may be coherently regulated, as presented in detail
elsewhere (
Shin and Rothenberg, 2023
).
Fig. 2
offers a low-
resolution process diagram of the component gene regulatory
modules that slowly shift the cells from the multipotent, Phase 1
state(s) toward increasing T cell character and finally to
T-lineage commitment (Phase 2); more detailed aspects are
shown in
Fig. 3
. TFs in pro-T cells initiate, synergize, oppose,
stabilize, or repress various subprograms by providing distinct
directional inputs into different modules. (For additional details
about individual factors, see other reviews [
Bao et al., 2022
;
De Obaldia and Bhandoola, 2015
;
De Pooter and Kee, 2010
;
Hosokawa and Rothenberg, 2021
;
Naito et al., 2011
;
Shah and
Z
́
uñiga-Pflücker, 2014
;
Yui and Rothenberg, 2014
].) Impor-
tantly, both the
“
maintenance
”
and
“
switching
”
of these distinct
gene networks in Phase 1 and Phase 2 depend upon the coop-
erative activities of multiple TFs.
The Phase 1 program is shaped by an ensemble of TFs in-
herited from the bone marrow progenitor cells. In the early
Phase 1 stage, the TFs PU.1 (encoded by
Spi1
), Erg, Lmo2, Lyl1,
Hhex, and Bcl11a control gene expression programs and self-
renewal properties of the cells (
Cleveland et al., 2013
;
Hosokawa
et al., 2018b
;
McCormack et al., 2010
;
Thoms et al., 2011
;
Ungerb
̈
ack
et al., 2018
;
Zhou et al., 2022
). Binding of the pioneer factor PU.1
(
Frederick et al., 2023
;
Minderjahn et al., 2020
;
Pham et al., 2013
)
prominently contributes to the chromatin accessibility landscape
in these cells (
Ungerb
̈
ack et al., 2018
). Transcription factors Hoxa9,
Meis1, and Mef2c are also expressed in TSPs, while N-Myc (
Mycn
)
and Hhex remain active in the later ETP and DN2a Phase 1 cells. All
have their expression shut off at different points during progres-
sion through T lineage commitment or shortly thereafter
(
Mingueneau et al., 2013
;
Yoshida et al., 2019
;
Zhou et al., 2019
).
These factors support the expression of genes associated with
stem/progenitor programs and sustain intrinsic myeloid poten-
tials. However, their action within pro-T cells is impacted by the
strong influence of the thymic microenvironment.
Notch signaling and the Notch-induced repressor Hes1 alter
the activities of these legacy TFs, not only by directly regulating
their expression levels but also by indirectly promoting or an-
tagonizing their functions selectively, through repressing their
partner factors or directly altering the expression of some of
their target genes (
Cant
́
e-Barrettetal.,2022
;
Chari and Winandy,
2008
;
De Obaldia et al., 2013
;
DelRealandRothenberg,2013
;
Franco et al., 2006
;
Germar et al., 2011
;
Guo et al., 2008
;
Ikawa
et al., 2006
;
Laiosa et al., 2006
;
Romero-Wolfetal.,2020
). In
parallel, strong Notch signaling inhibits the expression of a key
contributor to the innate lympho
id alternative programs, namely
Id2, an antagonist of bHLH E proteins (
Chea et al., 2016
). Notch
signaling also sharply reduces the ability of PU.1 to promote my-
eloid differentiation, at least in pa
rt by inhibiting expression of the
obligatory myeloid partners of the C/EBP and IRF families, while
also inhibiting expression of
Id2
, which could otherwise promote
innate lymphoid fates (
De Obaldia et al., 2013
;
DelRealand
Rothenberg, 2013
;
Romero-Wolfetal.,2020
;
Rothenberg et al.,
2019
). Thus, while Notch signaling
persists, PU.1 at natural lev-
els initially appears to support the proliferation and expression of
progenitor genes without undermining T-lineage potential.
Initiation of T-identity program against retention of stem and
progenitor program in Phase 1
This is the Phase 1 context in which Notch signaling induces new
regulators, including TCF-1 (encoded by
Tcf7
)andGATA-3,
which are essential for initiating the T-identity program in a
nonredundant manner (
Besseyrias et al., 2007
;
Germar et al.,
2011
;
Harly et al., 2020
;
Hattori et al., 1996
;
Hozumi et al.,
2008
;
Romero-Wolf et al., 2020
;
Zhou et al., 2022
). TCF-1 and
GATA-3 are also essential for precursors of innate lymphoid cells
(ILCs), emphasizing the root connections between T and ILC
programs (
Cherrier et al., 2018
;
Harly et al., 2019
;
Kasal and
Bendelac, 2021
;
Zhong et al., 2020
). Notably, in DN1 thymo-
cytes, these key factors are induced in the same cells that are still
expressing the stem and progenitor module regulators (
Zhou et al.,
Figure 2.
Distinct groups of TFs shaping the Phase 1 and Phase 2 gene
networks.
TFs critically regulating Phase 1 (green) and Phase 2 (purple)
transcriptional states are shown in the overview; for detailed relationships,
see
Fig. 3
. TFs with similar expression kinetics are displayed in the same-
colored box (green, early Phase 1-expressed TFs; blue, TFs present in both
Phase 1 and Phase 2; purple, TFs show high activities in Phase 2). Thin arrows
indicate positive (
→
) or negative (
x
) regulatory inputs between the TFs.
Thick arrows represent broad regulatory effects by the sum of TFs
’
activities.
The dashed purple arrow shows negative inputs toward the early Phase 1
program (green).
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2019
)(
Fig. 2
). TCF-1 becomes profoundly important for bone
marrow
–
derived precursors to enter the T-lineage program from
the earliest stages, as shown by bulk and single-cell analyses of
the short-term impacts of TCF-1 knockouts on gene expression
(
Germar et al., 2011
;
Weber et al., 2011
;
Zhou et al., 2022
). TCF-1
positively regulates itself and GATA-3 under Notch instruction,
increasing their expression levels as pro-T cells progress from
Phase 1 to Phase 2. This positive feedback loop along with regula-
tory inputs from other TFs bolsters the transcriptional state sup-
porting the T-identity progra
m in developing pro-T cells (
Fig. 2
)
and ultimately promotes progr
ession from Phase 1 to Phase 2.
Notch signaling also enables new, T-lineage promoting func-
tions by TFs that are established already in pre-thymic bone
marrow progenitors, such as Runx family TFs (esp. Runx1 and
Runx3,
“
Runx1/3
”
), Ikaros (encoded by
Ikzf1
), and E proteins (E2A
and HEB, encoded by
Tcf3
and
Tcf12
respectively), which are nec-
essary to generate functional T c
ells. This change occurs through
factor
–
factor interactions by which newly induced factors influ-
ence the behavior of the pre-established TFs, recruiting them to
new sites and/or changing the local chromatin contexts. Ikzf, Runx,
and E protein family members are progenitor-inherited but not
typical Phase 1 factors, as their expression is sustained through
Phase 2 and their effects on target genes under Notch signaling
explicitly enhance the T cell program (
Figs. 2
and
3
). E proteins
appear to be needed for gene regulation in both Phase 1 and Phase 2
based on gene expression changes when they are deleted (
Miyazaki
et al., 2017
;
Xu et al., 2013
), but the signature gene expression
targets of the classic E2A:HEB E protein dimers, like
Rag1
and
Rag2
,
are only turned on in Phase 2 (
Miyazaki et al., 2011
,
2020
). Runx
binding motifs are among the top three motifs enriched at open
chromatin sites in both Phase 1 and Phase 2 cells alike (
Shin et al.,
2021
). However, these are not the sa
me sites in the two phases, and
the Runx factors do not play a static role. Instead, Runx factors and
Ikaros show remarkable abilities t
o switch their functional target
genes in each T-development stage (
Arenzana et al., 2015
;
Shin
et al., 2021
). Preliminary evidence indicates that this is true for
bHLH factors as well (unpublished data).
The shift has been analyzed in detail for Runx factors. Runx
factors have a variety of partners in binding the DNA, frequently
partnering with PU.1 in a PU.1 activation domain
–
dependent way
during Phase 1 (
Hosokawa et al., 2018b
;
Ungerb
̈
ack et al., 2018
)as
well as with Ets1 (
Goetz et al., 2000
;
Gu et al., 2000
;
Wotton
et al., 1994
;
Zhao et al., 2017
), TCF-1 (
Goldman et al., 2023
;
Shin et al., 2023
), and Bcl11b in Phase 2 (
Hosokawa et al., 2018a
;
Kojo et al., 2018
). During the Phase 1 to Phase 2 transition, Runx
factors relocate globally from sites enriched for co-binding with
PU.1 to new sites enriched for co-binding with TCF-1, E proteins,
and/or Bcl11b instead (
Shin et al., 2021
,
2023
). Thus, together Ikzf,
Runx, and E protein factors, guid
ed by Notch signaling, dynami-
cally transform existing gene networks to initiate the T identity
program despite the constancy of their own expression levels,
shifting their functional gene t
argets through interaction with
different binding partners.
Phase 2: Complete shutoff of multipotentiality and establishment
of T-identity
As the cells move into Phase 2, they extinguish the expression
of the stem/progenitor-associated TFs, sharply increase their
Figure 3.
Gene regulatory network con-
nections within cells transitioning from the
uncommitted, thymic precursor stage to a
committed T cell stage.
Displayed connections
reflect interactions between early Phase 1 regu-
lators (Hhex, Erg, Mef2c, Lmo2/Lyl1, PU.1,
Bcl11a), induced/maintained Phase 1 and 2 regu-
lators (Runx1/3, TCF-1, GATA3, Myb, Ikaros,
Notch signaling), and Phase 2 regulators (Bcl11b,
E2A/HEB, ETS-1, LEF-1), under conditions of
Notch signaling. All relationships shown repre-
sent functional gene expression impacts of per-
turbations of individual regulators; curated data
from
Shin and Rothenberg (2023)
. Arrows: pos-
itive regulation; boxes: negative regulation; bar
end: inhibition of DNA binding; broken lines:
weaker effects. Colors highlight core subsets of
interactions centered around PU.1 (orange), E
proteins (magenta), Notch signaling (blue), Runx/
TCF-1/GATA3 (green), and Bcl11b (purple).
“
Speed regulators
”
discussed in this review are in
tan bubbles: Bcl11b, Runx1/3, and TCF-1 have
network contributions to both the innate lym-
phocyte program and the T-specification pro-
gram, while PU.1 network contributions reach
the stem/progenitor, myeloid, T cell specifica-
tion, and innate lymphocyte programs. PU.1 has
additional repressive effects when Notch sig-
naling is reduced. Erg and Bcl11a are related to
the PU.1 network, but less is known about their
contributions to the other programs.
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expression of T-lineage genes, and also consolidate their T cell
identity by blocking access to the related ILC and natural killer
(NK) programs.
Three regulatory changes stand out in the transition from
Phase 1 to Phase 2 (
Figs. 2
and
3
). One is the sudden prominence
of a bHLH
“
E protein
”
TF family binding motif among the most
enriched in open chromatin (
Johnson et al., 2018
;
Shin et al.,
2021
;
Yoshida et al., 2019
). This is noteworthy because the E2A
protein at least is already fully expressed in Phase 1 cells and
HEB increases only three to fourfold. However, the motif evi-
dence indicates that the effective activities of E2A:HEB and E2A:
E2A dimers are sharply increased in Phase 2. This may reflect
the silencing of the gene encoding an alternative Phase 1 hetero-
dimerization partner, Lyl1, which confers a slightly different
DNA binding specificity (
Hoang et al., 2016
).
Second, although there is a complex population of ETS TF
family members expressed in the cells throughout early T cell
development, there is a particularly notable shift in family
member prevalence from Phase 1 to Phase 2 (
David-Fung et al.,
2009
). Through Phase 1, the ETS family member PU.1 dominates
the open chromatin landscape, but as it is downregulated, an-
other ETS factor, Ets1, becomes upregulated and predominant
within the cells thereafter. Since PU.1 represents an ETS sub-
family with a DNA binding specificity distinct from other ETS
factors, there is also a shift in the pattern of ETS sites in the
genome that are accessible (
Johnson et al., 2018
;
Shin et al., 2021
;
Yoshida et al., 2019
).
Third, the gene encoding the Bcl11b TF is abruptly induced
from a virtually silent state to high activity. Bcl11b rapidly be-
comes one of the strongest partners of Runx factors in Phase 2,
extensively overlapping with Runx in DNA binding sites across
the genome as Runx abandons many previous co-binding sites
with PU.1 (
Hosokawa et al., 2018b
;
Shin et al., 2021
). At select
sites, Runx stays but swaps a PU.1 partner for Bcl11b (
Gamble
et al., 2024
). By monitoring a nondisruptive fluorescent protein
reporter inserted into the
Bcl11b
3
9
-untranslated region,
Bcl11b
upregulation has been shown to coincide very closely with
functional commitment at the single-cell level (
Kueh et al.,
2016
). Thus, fluorescent protein Bcl11b reporters have become
valuable as an additional criterion with CD25, cKit, and CD44
expression to score those cells that have crossed the Phase 1/
Phase 2 boundary (
Kueh et al., 2016
;
Ng et al., 2018
;
Olariu et al.,
2021
;
Shin et al., 2023
).
Gene expression in Phase 2 reflects the activities of all these
factors. T-lineage gene expression is strongly dependent on
TCF-1, which also trends upward in expression from Phase 1 to
Phase 2 (
Goldman et al., 2023
;
Johnson et al., 2018
). Both TCF-1
and GATA-3 are required to turn on a large fraction of the dis-
tinctive T cell signature genes that become strongly expressed at
this stage (reviewed in
Shin and Rothenberg [2023]
), and the
landmark upregulation of
Bcl11b
at the transition to Phase 2 itself
cannot occur without prior action of TCF-1 and GATA-3
(
Goldman et al., 2023
;
Kueh et al., 2016
;
Shin et al., 2023
). Bcl11b
itself appears to exert two kinds of roles in murine T cells: it
contributes positively to the activation of T cell signature genes
including the CD3 complex and it also blocks diversion to the
NK or ILC fate by inhibiting expression of
Id2
and other innate
regulators (
Hosokawa et al., 2018b
;
Li et al., 2010b
). This latter
repressive role is important because the loss of PU.1 and other
Phase 1 factors at this point appears to leave the cells primed to
embark on an ILC and/or NK trajectory as well as a T cell tra-
jectory, and Bcl11b blocks this major alternative (
Zhou et al.,
2022
). Bcl11b also has positive regulatory impacts on T-lineage
gene targets such as the
Cd3
complex, although it is still un-
certain whether this impact is direct (
Hosokawa et al., 2018b
).
In the human system, positive regulatory roles of Bcl11b that
promote
αβ
T cell development appear more prominent (
Dolens
et al., 2020
;
Ha et al., 2017
). The Runx:ETS combination, mostly
representing Runx1 and Ets1 in Phase 2, is directly implicated in
opening the TCR
β
coding loci for rearrangement (
Majumder
et al., 2015
;
Zhao et al., 2017
). Meanwhile, the strong E pro-
tein activity drives both upregulations of the gene cluster that
encodes the CD3 components of the TCR and upregulation of
the gene cluster encoding Rag1 and Rag2, which will catalyze
TCR gene rearrangement (
Engel and Murre, 2004
;
Miyazaki
et al., 2020
).
Silencing of the Phase 1 genes is due to contributions from
multiple Phase 2 factors. Notably, these factors seem to be
working as positive regulators of T cell program genes in the
same cells where they are also working as negative regulators of
the Phase 1 regulators (
Figs. 2
and
3
). These are intrinsically
bifunctional factors, although posttranslational modification may
also affect the balance of their activating and repressive activities
(
Mizutani et al., 2015
;
Vu et al., 2013
;
Yamagata et al., 2000
;
Yamashita et al., 2005
;
Zhang et al., 2012c
;
Zhao et al., 2008
). TCF-
1 itself includes not only transactivating domains but also an
intrinsic histone deacetylase domain and a Groucho (Transducin-
like Enhancer of Split) corepressor binding domain (
Brantjes
et al., 2001
;
Xing et al., 2016
), enabling it to repress directly
as well as activate gene expression. TCF-1 isoforms using a
specific N-terminal domain appear to be required to silence a
prethymically expressed GATA factor, GATA-2 (
Goldman
et al., 2023
), which could otherwise transdifferentiate the
early T cells toward a mast cell fate (
Goldman et al., 2023
)(arare
but previously reported alternative [
Taghon et al., 2007
]). The
combination of Runx1 and high-level GATA-3, possibly with an
additional stage-specific corep
ressor, appears to repress PU.1 (
Spi1
)
(
Hosokawa et al., 2021
;
Huang et al., 2008
;
Scripture-Adams et al.,
2014
). Runx factors additionally inhibit other stem/progenitor TFs,
Lmo2
,
Bcl11a
,
Mef2c
,and
Lyl1
(
Shin et al., 2021
,
2023
). GATA-3 itself
appears to be most importa
nt for downregulating
Bcl11a
, the stem
and progenitor cell-associated paralog of
Bcl11b
(
Zhou et al., 2022
),
as well as PU.1 (
Spi1
). A mixture of active repression and activator
withdrawal can also be involved in the extinction of the stem and
progenitor cell program.
Speed control of T cell program entry
Stochastic speed control by epigenetic mechanisms and
TF antagonism
What controls the timing of the Phase 1
–
Phase 2 shift? TF-target
gene relationships have yielded the topology of a gene regulatory
network in a static form (
Fig. 3
), but with the strong roles for
factors with activities that cross the Phase 1
–
Phase 2 borders, the
dynamics are especially hard to predict or compute a priori. A
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direct experimental approach has been crucial to gain mecha-
nistic insight. In vitro differentiation cultures promoting early
T-lineage development (
Montel-Hagen et al., 2020
;
Schmitt and
Z
́
uñiga-Pflücker, 2002
;
Seet et al., 2017
) make it possible to
follow a cohort of defined precursors in real-time through the
Phase 1 stages and across the Phase 1
→
Phase 2 transition. By
introducing specific genetic perturbations at defined time points
in the culture, re-sorting the treated cells from a desired stage,
and returning them to culture for short times, the impacts of
individual regulators can be characterized in a stage-specific
way in real-time. These methods have been crucial in reveal-
ing that the same factor can control different genes at different
stages within this process (
Arenzana et al., 2015
;
Goldman et al.,
2023
;
Hosokawa et al., 2021
;
Romero-Wolf et al., 2020
;
Shin
et al., 2021
), and that a given target gene may only respond to
a particular factor in a stage-specific way (
Kueh et al., 2016
;
Romero-Wolf et al., 2020
;
Shin et al., 2021
). Such experiments
have also shown that a few specific TFs can have strong effects
on the absolute speeds of progression of individual cells through
the T-lineage specification trajectory.
Phase 1 factors play an active role in restraining T lineage
progression speed in the cells that coexpress them with early
T cell genes. Acute disruption of PU.1, Bcl11a, or Erg markedly
accelerates T-lineage progression of the treated cells in cell-
autonomous ways, as shown by sing
le-cell transcriptome analy-
sisofacohortofcellsafewdaysafterthedeletion(
Zhou et al.,
2022
). These Phase 1 factors each work through distinct target
genes(seebelow),andtheyarelikelynottobetheonlyPhase1
factors that restrain the T cell program. For example, in some
T-acute lymphoblastic leukemias,
elevated levels of other Phase 1
TFs like Lmo2, working as proto-oncogenes, are implicated in the
developmentally frozen immature phenotype (
Cleveland et al.,
2013
;
Smith et al., 2014
;
Treanor et al., 2014
), and a braking role
for Lmo2 at natural levels is suppo
rted by our preliminary data as
well (unpublished data
). Note that this Lmo2
-dependent retarda-
tion of T-lineage differentiation, per se, need not contradict evi-
denceforevenearlierpositiveeffectsofLmo2ontheprethymic
precursor compartment, reported recently (
Hirano et al., 2021
).
Lmo2 normally exerts its effects in complexes with SCL (Tal1) or
Lyl1, which can also inhibit T lineage differentiative progression
despite also playing po
sitive roles in maintaining self-renewal and
the viability of the Phase 1 population (
de Pooter et al., 2019
;
Hoang et al., 2016
;
McCormack et al., 2010
,
2013
;
Zohren et al.,
2012
).Thus,atleastfourPhase1TFsplayintegralrolesinslowing
the rate of T-lineage differentiative progression in the presence of
Notch signaling, even if they also p
romote enhanced proliferation
or survival.
On the other side, at least two factors have been shown to
accelerate T lineage progression in real time: TCF-1 and Runx
factors. As noted above, Phase 1 cells are induced by Notch
signaling to express TCF-1 while they are still expressing pro-
genitor genes (
Zhou et al., 2019
). Total loss of TCF-1 can abort
activation of the T cell program in bone marrow-derived pre-
cursors (
Germar et al., 2011
;
Zhou et al., 2022
) and eliminate
their competitiveness even to generate ETPs (
Weber et al., 2011
).
Although in steady state some thymocytes develop in TCF-
1
–
deficient
-
mice (<10% normal numbers), this is probably
attributable to compensation by the paralogous factor LEF-1,
which is activated to high levels in Phase 2 cells and could be
expressed early in a small percentage of Phase 1 cells (
Okamura
et al., 1998
;
Weber et al., 2011
). Notably, even a modest gain of
full-length, wild-type TCF-1 expression (
∼
3× normal) accelerates
progression in real-time from DN1 to DN2 stages (
Goldman et al.,
2023
), and strong forced TCF-1 expression can even bypass the
need for Notch signaling for many joint target genes (
Weber
et al., 2011
). Its potency may reflect its competence as a pio-
neer factor (
Johnson et al., 2018
). This response is specific to
TCF-1. In contrast, although GATA-3 is equally indispensable, the
range of GATA-3 levels that are tolerated by pro-T cells is much
narrower. Whereas some T-lineage accelerating effects of extra
GATA-3 can be seen in human cells (
Van de Walle et al., 2016
),
fetal liver-derived mouse precursors can be severely inhibited
from T-lineage progression by supraphysiological GATA-3 levels
(
Taghon et al., 2007
;
Xu et al., 2013
), even in the same stages
when they also abort if GATA-3 levels are
∼
3× reduced
(
Scripture-Adams et al., 2014
).
Runx factors act as specific, dose-dependent forward drivers
of the T cell program from Phase 1 onward, despite being needed
for aspects of gene expression both before and after commit-
ment. Not only is T cell development aborted by combined loss
of Runx factors
’
activity (
Guo et al., 2008
;
Shin et al., 2021
), but
also, even a modest elevation of Runx factor activity (
∼
2×) leads
to a notable acceleration of T-lineage differentiation within
2 days. Runx-increased cells then differentiate past each mile-
stone 1
–
2 days faster than controls through 2 wk of development
(
Shin et al., 2023
). Thus, in the presence of Notch signals, the
Runx activity level is a major accelerator of the T cell program.
This could seem surprising. In Phase 1 cells, Runx1 physically
interacts with PU.1 and co-occupies most PU.1 binding sites,
especially those that are found in open chromatin (
Hosokawa
et al., 2018b
;
Shin et al., 2021
;
Ungerb
̈
ack et al., 2018
). However,
from gene expression impacts of perturbation, Runx factors
more often oppose PU.1
’
s activity by restricting the cells
’
mye-
loid potentials and inhibiting other PU.1 activation target genes
(
Shin et al., 2023
). In the same cells, moreover, Runx factors
amplify the onset of the T-identity program by upregulating TCF-
1 and GATA-3 expression (
Guo et al., 2008
;
Shin et al., 2021
,
2023
).
Subsequently, the combination of Notch signaling, TCF-1, GATA-3,
and Runx factors activates the expression of
Bcl11b
,i.e.,theland-
mark of transition to Phase 2 (
Kueh et al., 2016
), with Runx factors
playing a particularly strong dose-dependent role (
Kueh et al.,
2016
;
Shin et al., 2023
). This indicates that even though Runx
levels hardly change from Phase 1 to Phase 2 (
Shin et al., 2021
),
Runx proteins under the influenc
e of Notch signaling actively
promote progression to Phase 2 and destabilize the stem/
progenitor state starting in Phase 1.
Combinatorial and epigenetic bases of TF dose dependence
The high dose dependence of the Runx effect is likely to reflect
two phenomena: the sensitivity of Runx DNA binding to open
and closed chromatin states and the association of Runx with
different partner factors in Phase 1 and Phase 2. The likelihood of
aTF
’
s binding to any given site depends on a combination of the
affinity it has for the site sequence (
“
quality
”
= match to optimal
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Speed control for the T cell commitment network
https://doi.org/10.1084/jem.20230893
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