scholarly journals Integrated time-lapse and single-cell transcription studies highlight the variable and dynamic nature of human hematopoietic cell fate commitment

2017 ◽  
Author(s):  
Alice Moussy ◽  
Jérémie Cosette ◽  
Romuald Parmentier ◽  
Cindy da Silva ◽  
Guillaume Corre ◽  
...  

AbstractIndividual cells take lineage commitment decisions in a way that is not necessarily uniform. We address this issue by characterizing transcriptional changes in cord blood derived CD34+ cells at the single-cell level and integrating data with cell division history and morphological changes determined by time-lapse microscopy. We show, that major transcriptional changes leading to a multilineage-primed gene expression state occur very rapidly during the first cell cycle. One of the two stable lineage-primed patterns emerges gradually in each cell with variable timing. Some cells reach a stable morphology and molecular phenotype by the end of the first cell cycle and transmit it clonally. Others fluctuate between the two phenotypes over several cell cycles. Our analysis highlights the dynamic nature and variable timing of cell fate commitment in hematopoietic cells, links the gene expression pattern to cell morphology and identifies a new category of cells with fluctuating phenotypic characteristics, demonstrating the complexity of the fate decision process, away from a simple binary switch between two options as it is usually envisioned.

2020 ◽  
Author(s):  
Ivan Croydon Veleslavov ◽  
Michael P.H. Stumpf

AbstractSingle cell transcriptomics has laid bare the heterogeneity of apparently identical cells at the level of gene expression. For many cell-types we now know that there is variability in the abundance of many transcripts, and that average transcript abun-dance or average gene expression can be a unhelpful concept. A range of clustering and other classification methods have been proposed which use the signal in single cell data to classify, that is assign cell types, to cells based on their transcriptomic states. In many cases, however, we would like to have not just a classifier, but also a set of interpretable rules by which this classification occurs. Here we develop and demonstrate the interpretive power of one such approach, which sets out to establish a biologically interpretable classification scheme. In particular we are interested in capturing the chain of regulatory events that drive cell-fate decision making across a lineage tree or lineage sequence. We find that suitably defined decision trees can help to resolve gene regulatory programs involved in shaping lineage trees. Our approach combines predictive power with interpretabilty and can extract logical rules from single cell data.


PLoS Biology ◽  
2017 ◽  
Vol 15 (7) ◽  
pp. e2001867 ◽  
Author(s):  
Alice Moussy ◽  
Jérémie Cosette ◽  
Romuald Parmentier ◽  
Cindy da Silva ◽  
Guillaume Corre ◽  
...  

2017 ◽  
Author(s):  
Britta Werthmann ◽  
Wolfgang Marwan

AbstractThe developmental switch to sporulation inPhysarum polycephalumis a phytochrome-mediated far-red light-induced cell fate decision that synchronously encompasses the entire multinucleate plasmodial cell and is associated with extensive reprogramming of the transcriptome. By repeatedly taking samples of single cells after delivery of a light stimulus pulse, we analysed differential gene expression in two mutant strains and in a heterokaryon of the two strains all of which display a different propensity for making the cell fate decision. Multidimensional scaling of the gene expression data revealed individually different single cell trajectories eventually leading to sporulation. Characterization of the trajectories as walks through states of gene expression discretized by hierarchical clustering allowed the reconstruction of Petri nets that model and predict the observed behavior. Structural analyses of the Petri nets indicated stimulus- and genotype-dependence of both, single cell trajectories and of the quasipotential landscape through which these trajectories are taken. The Petri net-based approach to the analysis and decomposition of complex cellular responses and of complex mutant phenotypes may provide a scaffold for the data-driven reconstruction of causal molecular mechanisms that shape the topology of the quasipotential landscape.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 2903-2903
Author(s):  
Chad D Sanada ◽  
Elizabeth Min ◽  
Siying Zou ◽  
Huiyan Jin ◽  
Ping-Xia Zhang ◽  
...  

Abstract Megakaryocyte-Erythroid Progenitors (MEPs) are bipotent cells capable of generating megakaryocytic (Mk) or erythroid (E) progeny. However, neither the cell fate-determining componentry nor the initial molecular consequences of lineage specification have been defined. To elucidate this, it is critical to rigorously purify MEP from primary cell sources. Unfortunately, existing purification strategies to do this fail to yield pure, bipotent cells. To improve upon existing approaches for the enrichment of primary human MEPs from G-CSF mobilized peripheral blood (MPB) and BM, we used the cell surface markers CD36 and CD110 in order to further enrich MEP from CD34+CD38+Lin-Flt3-CD45RA- cells. We then quantitated the Mk and E potential of those cells using single cell colony assays. Using this approach demonstrated that CD36/CD110 selection led to an increase of biphenotypic MEP (assessed as CFU-Mk/E) from ~15% to ~40% of colonies that grew. However, it was unclear from colony assay data alone whether or not the heterogeneity of the underlying population was accurately reflected. To address this, we subjected the FACS-sorted MEP-enriched population to single cell mRNA deep sequencing using the Fluidigm C1 platform. For comparison to MEP, we also performed single cell deep sequencing of CD34+CD38+CD41+Flt3- and CD34+CD38+Flt3-CD36+ cells, which are highly enriched for megakaryocyte progenitors (MkP) and erythroid progenitors (ErP), respectively. A total of 150 single cells were captured and sequenced with an average of 3 million reads per cell (1x100bp sequencing). The mRNA deep sequencing data was analyzed by a combination of gene and cell bi-clustering approach to identify both transcripts and cells that exhibited shared or differential patterning. Initial expression patterns and cell groups were identified using stringent expression filtering for transcripts that exhibited >10 FPKM in at least one cell, and iteratively defined and refined based on known E, Mk, and other hematopoietic genes, and then extended for all strongly expressed transcripts. For the MkP and ErP groups, the resulting clusters of cells expressed genes indicative of commitment to E or Mk differentiation. In contrast, within the MEP-enriched population, while a few cells clustered with MkP and ErP, the vast majority of cells fell into distinct subsets of uncommitted cells, supporting the idea that the MEP-enriched population was unique and distinct from MkP or ErP. Analysis of the gene expression patterns from the MEP, ErP and MkP revealed two remarkable trends. First, the transcription factors GATA1 and GATA2 showed distinct expression patterns in the different clusters of cells; there was a subset of MEP that had high GATA2 expression with little to no GATA1 expression (GATA2 cluster), and an opposite cluster containing high GATA1 expression and low or absent GATA2 expression (GATA1 cluster). The genes most positively correlated with GATA2 expression were also low or absent in the GATA 1 cluster. Closer analysis revealed that the GATA 1 cluster cells were predominantly erythroid and megakaryocyte committed, while the GATA2 cluster appeared uncommitted. A third cluster was present, containing intermediate expression of both GATA1 and GATA2. This cluster is as yet undefined, but appears to contain both MkP and MEP, suggesting a possible link between these two cell types. The second pattern we noted was that the genes in the GATA1 cluster correlated very strongly with cell cycle activity and cell cycle progression while the GATA2 cluster geneset had very low cell cycle activity. This suggested that the commitment of the MEP to E or Mk fates could not be unlinked from their cell cycling status. Such a finding could only be ascertained using single cell sequencing. Using single cell sequencing also provided us with a gene expression signature for primary human MkP, something which was not possible before because there is no reliable way to sort pure human MkP. Regarding GATA1 and GATA2 clusters, real time RT-PCR analysis of primary human ErP, MkP, and MEP point to a scenario where the ratio of GATA2/GATA1 is critical to determining the E vs. Mk fate decision. These findings will be further addressed in future studies aiming to understand the link between cell cycle and the MEP fate decision. Our new findings will help clarify genetic events critical for the E/Mk fate decision. Disclosures No relevant conflicts of interest to declare.


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 3828-3828
Author(s):  
Yi-Chien Lu ◽  
Diane S. Krause ◽  
Juliana Xavier-Ferrucio ◽  
Lin Wang ◽  
Nathan Salomonis ◽  
...  

Abstract Megakaryocytic-Erythroid Progenitors (MEP) produce megakaryocytes (Mk) and erythroid (E) cells. The detailed molecular mechanisms underlying the MEP fate decision have not been determined. One of the challenges in studying the fate decisions in MEP has been the lack of high purity populations of the specific cell type. We established an improved method for enriching primary adult human MEP, in which CFU-Mk/E (single cells that give rise to colonies containing exclusively Mk and E) are enriched to ~50% with the remaining cells being CFU-Mk and BFU-E.. We applied single cell RNA sequencing to identify the molecular signature of this enriched MEP population, and compared this to that of CMP, and enriched populations of Mk or E committed progenitors (MKP or ERP), which produce >90% Mk or E colonies in CFU assays). Single cell sequencing results indicate that MEP have a unique gene expression signature consistent with a transition state from CMP to MKP and ERP. MEP have random co-expression of a fraction of 60 genes that are otherwise expressed exclusively in CMP, MKP or ERP. Amongst the most differentially expressed groups of genes between MEP, MKP, and ERP are those related to cell cycle. Bioinformatic analysis suggested that MYC and E2F may accelerate MEP cell cycling as cells commit toward the E or Mk lineage.To determine whether the change in cell cycle is the consequence of cell fate determinant or itself can also regulate the cell fate decision, we used chemical and molecular approaches to modify cell cycling of MEP. Our data show that ATRA and mTOR can each reduce the MEP proliferation rate, and bias MEP toward Mk lineage differentiation (see Figure, > 1.65-fold increased in Mk colony number). We tested whether effect is mediated by downstream MYC pathways, and found that suppression of MYC or MAX (heterodimeric partner of MYC) similarly slowed proliferation and induced an Mk bias in primary human MEP (1.5 and 1.8 fold increased in Mk colony number). If slowing the cell cycle promotes Mk fate commitment, then acceleration of the cell cycle may promote erythroid fate commitment. Indeed, MEP cycling was enhanced by lentiviral-mediated overexpression of Cyclins-CDKs or shRNA mediated p53, and these MEP were significantly (p < 0.05) biased toward erythroid lineage differentiation (> 1.7-fold increased in E colony number). These results support that the speed or frequency of the cell cycle regulates cell fate decisions. In summary, we apply single cell sequencing on pure human CMP, MEP, MKP and ERP and identify the unique MEP gene signature. Thus, by enriching primary human subpopulations, functionally confirming their fate commitment potential, performing single cell RNA sequencing, analyzing the data for gene expression patterns, and testing by both genetic and pharmacological approaches, we have confirmed that the fate commitment of primary human bipotent MEP can be toggled by cell cycle speed. Now that we have proven that cell cycle activity mechanistically controls MEP fate decisions, specific genetic and epigenetic mechanisms by which Mk vs erythroid specification is determined are being explored. The data obtained from healthy cells can now be applied to the mechanisms underlying benign and malignant disease states of Mk and E production. Figure. Figure. Disclosures No relevant conflicts of interest to declare.


2010 ◽  
Vol 18 (4) ◽  
pp. 675-685 ◽  
Author(s):  
Guoji Guo ◽  
Mikael Huss ◽  
Guo Qing Tong ◽  
Chaoyang Wang ◽  
Li Li Sun ◽  
...  

2021 ◽  
Vol 118 (46) ◽  
pp. e2104297118
Author(s):  
Sameena Nikhat ◽  
Anurupa D. Yadavalli ◽  
Arpita Prusty ◽  
Priyanka K. Narayan ◽  
Dasaradhi Palakodeti ◽  
...  

The commitment of hematopoietic multipotent progenitors (MPPs) toward a particular lineage involves activation of cell type–specific genes and silencing of genes that promote alternate cell fates. Although the gene expression programs of early–B and early–T lymphocyte development are mutually exclusive, we show that these cell types exhibit significantly correlated microRNA (miRNA) profiles. However, their corresponding miRNA targetomes are distinct and predominated by transcripts associated with natural killer, dendritic cell, and myeloid lineages, suggesting that miRNAs function in a cell-autonomous manner. The combinatorial expression of miRNAs miR-186-5p, miR-128-3p, and miR-330-5p in MPPs significantly attenuates their myeloid differentiation potential due to repression of myeloid-associated transcripts. Depletion of these miRNAs caused a pronounced de-repression of myeloid lineage targets in differentiating early–B and early–T cells, resulting in a mixed-lineage gene expression pattern. De novo motif analysis combined with an assay of promoter activities indicates that B as well as T lineage determinants drive the expression of these miRNAs in lymphoid lineages. Collectively, we present a paradigm that miRNAs are conserved between developing B and T lymphocytes, yet they target distinct sets of promiscuously expressed lineage-inappropriate genes to suppress the alternate cell-fate options. Thus, our studies provide a comprehensive compendium of miRNAs with functional implications for B and T lymphocyte development.


Methods ◽  
2018 ◽  
Vol 133 ◽  
pp. 81-90 ◽  
Author(s):  
Katja M. Piltti ◽  
Brian J. Cummings ◽  
Krystal Carta ◽  
Ayla Manughian-Peter ◽  
Colleen L. Worne ◽  
...  

2021 ◽  
Author(s):  
Pengcheng Ma ◽  
Xingyan Liu ◽  
Huimin Liu ◽  
Zaoxu Xu ◽  
Xiangning Ding ◽  
...  

Abstract Vertebrate evolution was accompanied with two rounds of whole genome duplication followed by functional divergence in terms of regulatory circuits and gene expression patterns. As a basal and slow-evolving chordate species, amphioxus is an ideal paradigm for exploring the origin and evolution of vertebrates. Single cell sequencing has been widely employed to construct the developmental cell atlas of several key species of vertebrates (human, mouse, zebrafish and frog) and tunicate (sea squirts). Here, we performed single-nucleus RNA sequencing (snRNA-seq) and single-cell assay for transposase accessible chromatin sequencing (scATAC-seq) for different stages of amphioxus (covering embryogenesis and adult tissues). With the datasets generated we constructed the developmental tree for amphioxus cell fate commitment and lineage specification, and revealed the underlying key regulators and genetic regulatory networks. The generated data were integrated into an online platform, AmphioxusAtlas, for public access at http://120.79.46.200:81/AmphioxusAtlas.


2020 ◽  
Author(s):  
Nadia M. V. Sampaio ◽  
Caroline M. Blassick ◽  
Jean-Baptiste Lugagne ◽  
Mary J. Dunlop

AbstractCell-to-cell heterogeneity in gene expression and growth can have critical functional consequences, such as determining whether individual bacteria survive or die following stress. Although phenotypic variability is well documented, the dynamics that underlie it are often unknown. This information is critical because dramatically different outcomes can arise from gradual versus rapid changes in expression and growth. Using single-cell time-lapse microscopy, we measured the temporal expression of a suite of stress response reporters in Escherichia coli, while simultaneously monitoring growth rate. In conditions without stress, we found widespread examples of pulsatile expression. Single-cell growth rates were often anti-correlated with gene expression, with changes in growth preceding changes in expression. These pulsatile dynamics have functional consequences, which we demonstrate by measuring survival after challenging cells with the antibiotic ciprofloxacin. Our results suggest that pulsatile expression and growth dynamics are common in stress response networks and can have direct consequences for survival.


Sign in / Sign up

Export Citation Format

Share Document