Inflammatory signals directly instruct PU.1 in HSCs via TNF.

The molecular mechanisms governing the transition from hematopoietic stem cells (HSCs) to lineage-committed progenitors remain poorly understood. Transcription factors (TFs) are powerful cell intrinsic regulators of differentiation and lineage commitment, while cytokine signaling has been shown to instruct the fate of progenitor cells. However, the direct regulation of differentiation-inducing hematopoietic TFs by cell extrinsic signals remains surprisingly difficult to establish. PU.1 is a master regulator of hematopoiesis and promotes myeloid differentiation. Here we report that tumor necrosis factor (TNF) can directly and rapidly upregulate PU.1 protein in HSCs in vitro and in vivo. We demonstrate that in vivo, niche-derived TNF is the principal PU.1 inducing signal in HSCs and is both sufficient and required to relay signals from inflammatory challenges to HSCs.

Transcriptionally dynamic progenitor populations organised around a stable niche drive axial patterning.

The elongating mouse anteroposterior axis is supplied by progenitors with distinct tissue fates. It is not known whether these progenitors confer anteroposterior pattern to the embryo. We have analysed the progenitor population transcriptomes in the mouse primitive streak and tail bud throughout axial elongation. Transcriptomic signatures distinguish three known progenitor types (neuromesodermal, lateral/paraxial mesoderm and notochord progenitors; NMPs, LPMPs and NotoPs). Both NMP and LPMP transcriptomes change extensively over time. In particular, NMPs upregulate Wnt, Fgf and Notch signalling components, and many Hox genes as progenitors transit from production of the trunk to the tail and expand in number. In contrast, the transcriptome of NotoPs is stable throughout axial elongation and they are required for normal axis elongation. These results suggest that NotoPs act as a progenitor niche whereas anteroposterior patterning originates within NMPs and LPMPs.

Inductive and Selective Effects of GSK3 and MEK Inhibition on Nanog Heterogeneity in Embryonic Stem Cells.

Embryonic stem cells (ESCs) display heterogeneous expression of pluripotency factors such as Nanog when cultured with serum and leukemia inhibitory factor (LIF). In contrast, dual inhibition of the signaling kinases GSK3 and MEK (2i) converts ESC cultures into a state with more uniform and high Nanog expression. However, it is so far unclear whether 2i acts through an inductive or selective mechanism. Here, we use continuous time-lapse imaging to quantify the dynamics of death, proliferation, and Nanog expression in mouse ESCs after 2i addition. We show that 2i has a dual effect: it both leads to increased cell death of Nanog low ESCs (selective effect) and induces and maintains high Nanog levels (inductive effect) in single ESCs. Genetic manipulation further showed that presence of NANOG protein is important for cell viability in 2i medium. This demonstrates complex Nanog-dependent effects of 2i treatment on ESC cultures.

On the statistical analysis of single cell lineage trees.

Stem cells play a central role in the regeneration and repair of multicellular organisms. However, it remains far from trivial to reliably identify them. Despite decades of work, current techniques to isolate hematopoietic stem cells (HSCs) based on cell-surface markers only result in 50% purity, i.e. half of the sorted cells are not stem cells when functionally tested. Modern microscopy techniques allow us to follow single cells and their progeny for up to weeks in vitro, while recording the cell fates and lifetime of each individual cell. This cell tracking generates so-called lineage trees. Here, we propose statistical techniques to determine if the initial cell in a lineage tree was a HSC. We apply these techniques to murine hematopoietic lineage trees, revealing that 18% of the trees in our HSC dataset display a unique signature, and this signature is compatible with these trees having started from a true stem cell. Assuming 50% purity of HSC empirical datasets, this corresponds to a 0.35 power of the test, and the type-1-error is estimated to be 0.047. In summary, this study shows that statistical analysis of lineage trees could improve the classification of cells, which is currently done based on bio-markers only. Our statistical techniques are not limited to mammalian stem cell biology. Any type of single cell lineage trees, be it from bacteria, single cell eukaryotes, or single cells in a multicellular organism can be investigated. We expect this to contribute to a better understanding of the molecules influencing cellular dynamics at the single cell level.

CSF-1-induced Src signaling can instruct monocytic lineage choice.

Controlled regulation of lineage decisions is imperative for hematopoiesis. Yet, the molecular mechanisms underlying hematopoietic lineage choices are poorly defined. Colony-stimulating factor 1 (CSF-1), the cytokine acting as the principal regulator of monocyte/macrophage (M) development, has been shown to be able to instruct the lineage choice of uncommitted granulocyte M (GM) progenitors toward an M fate. However, the intracellular signaling pathways involved are unknown. CSF-1 activates a multitude of signaling pathways resulting in a pleiotropic cellular response. The precise role of individual pathways within this complex and redundant signaling network is dependent on cellular context, and is not well understood. Here, we address which CSF-1-activated pathways are involved in transmitting the lineage-instructive signal in primary bone marrow-derived GM progenitors. Although its loss is compensated for by alternative signaling activation mechanisms, Src family kinase (SFK) signaling is sufficient to transmit the CSF-1 lineage instructive signal. Moreover, c-Src activity is sufficient to drive M fate, even in nonmyeloid cells.

Challenges in long-term imaging and quantification of single-cell dynamics.

Continuous analysis of single cells, over several cell divisions and for up to weeks at a time, is crucial to deciphering rare, dynamic and heterogeneous cell responses, which would otherwise be missed by population or single-cell snapshot analysis. Although the field of long-term single-cell imaging, tracking and analysis is constantly advancing, several technical challenges continue to hinder wider implementation of this important approach. This is a particular problem for mammalian cells, where in vitro observation usually remains the only possible option for uninterrupted long-term, single-cell observation. Efforts must focus not only on identifying and maintaining culture conditions that support normal cellular behavior while allowing high-resolution imaging over time, but also on developing computational methods that enable semiautomatic analysis of the data. Solutions in microscopy hard- and software, computer vision and specialized theoretical methods for analysis of dynamic single-cell data will enable important discoveries in biology and beyond.

Identification of factors promoting ex vivo maintenance of mouse hematopoietic stem cells by long-term single-cell quantification.

The maintenance of hematopoietic stem cells (HSCs) during ex vivo culture is an important prerequisite for their therapeutic manipulation. However, despite intense research, culture conditions for robust maintenance of HSCs are still missing. Cultured HSCs are quickly lost, preventing their improved analysis and manipulation. Identification of novel factors supporting HSC ex vivo maintenance is therefore necessary. Coculture with the AFT024 stroma cell line is capable of maintaining HSCs ex vivo long-term, but the responsible molecular players remain unknown. Here, we use continuous long-term single-cell observation to identify the HSC behavioral signature under supportive or nonsupportive stroma cocultures. We report early HSC survival as a major characteristic of HSC-maintaining conditions. Behavioral screening after manipulation of candidate molecules revealed that the extracellular matrix protein dermatopontin (Dpt) is involved in HSC maintenance. DPT knockdown in supportive stroma impaired HSC survival, whereas ectopic expression of the Dpt gene or protein in nonsupportive conditions restored HSC survival. Supplementing defined stroma- and serum-free culture conditions with recombinant DPT protein improved HSC clonogenicity. These findings illustrate a previously uncharacterized role of Dpt in maintaining HSCs ex vivo.

Network plasticity of pluripotency transcription factors in embryonic stem cells.

Transcription factor (TF) networks are thought to regulate embryonic stem cell (ESC) pluripotency. However, TF expression dynamics and regulatory mechanisms are poorly understood. We use reporter mouse ESC lines allowing non-invasive quantification of Nanog or Oct4 protein levels and continuous long-term single-cell tracking and quantification over many generations to reveal diverse TF protein expression dynamics. For cells with low Nanog expression, we identified two distinct colony types: one re-expressed Nanog in a mosaic pattern, and the other did not re-express Nanog over many generations. Although both expressed pluripotency markers, they exhibited differences in their TF protein correlation networks and differentiation propensities. Sister cell analysis revealed that differences in Nanog levels are not necessarily accompanied by differences in the expression of other pluripotency factors. Thus, regulatory interactions of pluripotency TFs are less stringently implemented in individual self-renewing ESCs than assumed at present.

Reprogramming Roadblocks Are System Dependent.

Since the first generation of induced pluripotent stem cells (iPSCs), several reprogramming systems have been used to study its molecular mechanisms. However, the system of choice largely affects the reprogramming efficiency, influencing our view on the mechanisms. Here, we demonstrate that reprogramming triggered by less efficient polycistronic reprogramming cassettes not only highlights mesenchymal-to-epithelial transition (MET) as a roadblock but also faces more severe difficulties to attain a pluripotent state even post-MET. In contrast, more efficient cassettes can reprogram both wild-type and Nanog(-/-) fibroblasts with comparable efficiencies, routes, and kinetics, unlike the less efficient reprogramming systems. Moreover, we attribute a previously reported variation in the N terminus of KLF4 as a dominant factor underlying these critical differences. Our data establish that some reprogramming roadblocks are system dependent, highlighting the need to pursue mechanistic studies with close attention to the systems to better understand reprogramming.

Distinct Wnt-driven primitive streak-like populations reflect in vivo lineage precursors.

During gastrulation, epiblast cells are pluripotent and their fate is thought to be constrained principally by their position. Cell fate is progressively restricted by localised signalling cues from areas including the primitive streak. However, it is unknown whether this restriction accompanies, at the individual cell level, a reduction in potency. Investigation of these early transition events in vitro is possible via the use of epiblast stem cells (EpiSCs), self-renewing pluripotent cell lines equivalent to the postimplantation epiblast. Strikingly, mouse EpiSCs express gastrulation stage regional markers in self-renewing conditions. Here, we examined the differentiation potential of cells expressing such lineage markers. We show that undifferentiated EpiSC cultures contain a major subfraction of cells with reversible early primitive streak characteristics, which is mutually exclusive to a neural-like fraction. Using in vitro differentiation assays and embryo grafting we demonstrate that primitive streak-like EpiSCs are biased towards mesoderm and endoderm fates while retaining pluripotency. The acquisition of primitive streak characteristics by self-renewing EpiSCs is mediated by endogenous Wnt signalling. Elevation of Wnt activity promotes restriction towards primitive streak-associated lineages with mesendodermal and neuromesodermal characteristics. Collectively, our data suggest that EpiSC pluripotency encompasses a range of reversible lineage-biased states reflecting the birth of pioneer lineage precursors from a pool of uncommitted EpiSCs similar to the earliest cell fate restriction events taking place in the gastrula stage epiblast.

Simple derivation of transgene-free iPS cells by a dual recombinase approach.

Mammalian cells can be reprogrammed into induced pluripotent stem cells (iPSCs), a valuable tool for in vitro disease modeling and regenerative medicine. These applications demand for iPSCs devoid of reprogramming factor transgenes, but current procedures for the derivation of transgene-free iPSCs are inefficient and cumbersome. Here, we describe a new approach for the simple derivation of transgene-free iPSCs by the sequential use of two DNA recombinases, C31 Integrase and Cre, to control the genomic insertion and excision of a single, non-viral reprogramming vector. We show that such transgene-free iPSCs exhibit gene expression profiles and pluripotent developmental potential comparable to genuine, blastocyst-derived embryonic stem cells. As shown by a reporter iPSC line for the differentiation into midbrain dopaminergic neurons, the dual recombinase approach offers a simple and efficient way to derive transgene-free iPSCs for studying disease mechanisms and cell replacement therapies.

High-resolution analysis with novel cell-surface markers identifies routes to iPS cells.

The generation of induced pluripotent stem (iPS) cells presents a challenge to normal developmental processes. The low efficiency and heterogeneity of most methods have hindered understanding of the precise molecular mechanisms promoting, and roadblocks preventing, efficient reprogramming. Although several intermediate populations have been described, it has proved difficult to characterize the rare, asynchronous transition from these intermediate stages to iPS cells. The rapid expansion of minor reprogrammed cells in the heterogeneous population can also obscure investigation of relevant transition processes. Understanding the biological mechanisms essential for successful iPS cell generation requires both accurate capture of cells undergoing the reprogramming process and identification of the associated global gene expression changes. Here we demonstrate that in mouse embryonic fibroblasts, reprogramming follows an orderly sequence of stage transitions, marked by changes in the cell-surface markers CD44 and ICAM1, and a Nanog-enhanced green fluorescent protein (Nanog-eGFP) reporter. RNA-sequencing analysis of these populations demonstrates two waves of pluripotency gene upregulation, and unexpectedly, transient upregulation of several epidermis-related genes, demonstrating that reprogramming is not simply the reversal of the normal developmental processes. This novel high-resolution analysis enables the construction of a detailed reprogramming route map, and the improved understanding of the reprogramming process will lead to new reprogramming strategies.

Recurrent transcriptional clusters in the genome of mouse pluripotent stem cells.

A number of studies have shown that transcriptome analysis in terms of chromosomal location can reveal regions of non-random transcriptional activity within the genome. Genomic clusters of differentially expressed genes can identify genomic patterns of structural organization, underlying copy number variations or long-range epigenetic regulation such as X-chromosome inactivation. Here we apply an integrative bioinformatics analysis to a collection of 315 freely available mouse pluripotent stem cell samples to discover transcriptional clusters in the genome. We show that over half of the analysed samples (56.83%) carry whole or partial-chromosome spanning clusters which recur in genomic regions previously implicated in chromosomal imbalances. Strikingly, we found that the presence of such large-clusters is linked to the differential expression of a limited number of genes, common to all samples carrying clusters irrespectively of the chromosome where the cluster is found. We have used these genes to train and test classification models that can predict samples that carry large-scale clusters on any chromosome with over 90% accuracy. Our findings suggest that there is a common downstream activation in these cells that affects a limited number of nodes. We propose that this effect is linked to selective advantage and identify potential driver genes.