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Single-Cell RNA Sequencing Reveals Metallothionein Heterogeneity during hESC Differentiation to Definitive Endoderm [RNA-Seq]

ABSTRACT: Differentiation of human pluripotent stem cells toward definitive endoderm (DE) is the critical first step for generating cells comprising organs such as the gut, liver, pancreas and lung. This in-vitro differentiation process generates a heterogeneous population with a proportion of cells failing to differentiate properly and maintaining expression of pluripotency factors such as Oct4. RNA sequencing of single cells collected at four time points during a 4-day DE differentiation identified high expression of metallothionein genes in the residual Oct4-positive cells that failed to differentiate to DE. Using X-ray fluorescence microscopy and multi-isotope mass spectrometry, we discovered that high intracellular zinc level corresponds with persistent Oct4 expression and failure to differentiate. This study improves our understanding of the cellular heterogeneity during in-vitro directed differentiation and provides a valuable resource to improve DE differentiation efficiency.

ORGANISM(S): Homo sapiens

PROVIDER: GSE109658 | GEO | 2018/02/15

REPOSITORIES: GEO

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Project description:Chavez2009 - a core regulatory network of OCT4 in human embryonic stem cells A core OCT4-regulated network has been identified as a test case, to analyase stem cell characteristics and cellular differentiation. This model is described in the article: In silico identification of a core regulatory network of OCT4 in human embryonic stem cells using an integrated approach. Chavez L, Bais AS, Vingron M, Lehrach H, Adjaye J, Herwig R BMC Genomics, 2009, 10:314 Abstract: BACKGROUND: The transcription factor OCT4 is highly expressed in pluripotent embryonic stem cells which are derived from the inner cell mass of mammalian blastocysts. Pluripotency and self renewal are controlled by a transcription regulatory network governed by the transcription factors OCT4, SOX2 and NANOG. Recent studies on reprogramming somatic cells to induced pluripotent stem cells highlight OCT4 as a key regulator of pluripotency. RESULTS: We have carried out an integrated analysis of high-throughput data (ChIP-on-chip and RNAi experiments along with promoter sequence analysis of putative target genes) and identified a core OCT4 regulatory network in human embryonic stem cells consisting of 33 target genes. Enrichment analysis with these target genes revealed that this integrative analysis increases the functional information content by factors of 1.3 - 4.7 compared to the individual studies. In order to identify potential regulatory co-factors of OCT4, we performed a de novo motif analysis. In addition to known validated OCT4 motifs we obtained binding sites similar to motifs recognized by further regulators of pluripotency and development; e.g. the heterodimer of the transcription factors C-MYC and MAX, a prerequisite for C-MYC transcriptional activity that leads to cell growth and proliferation. CONCLUSION: Our analysis shows how heterogeneous functional information can be integrated in order to reconstruct gene regulatory networks. As a test case we identified a core OCT4-regulated network that is important for the analysis of stem cell characteristics and cellular differentiation. Functional information is largely enriched using different experimental results. The de novo motif discovery identified well-known regulators closely connected to the OCT4 network as well as potential new regulators of pluripotency and differentiation. These results provide the basis for further targeted functional studies. This model is hosted on BioModels Database and identified by: MODEL1305010000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:The paper describes a basic model of effect of cellular de-differentiation on the dynamics and evolution of tissue and tumor cells. Created by COPASI 4.25 (Build 207) This model is described in the article: Effect of cellular de-differentiation on the dynamics and evolution of tissue and tumor cells in mathematical models with feedback regulation Dominik Wodarz J Theor Biol. 2018 July 07; 448: 86–93 Abstract: Tissues are maintained by adult stem cells that self-renew and also differentiate into functioning tissue cells. Homeostasis is achieved by a set of complex mechanisms that involve regulatory feedback loops. Similarly, tumors are believed to be maintained by a minority population of cancer stem cells, while the bulk of the tumor is made up of more differentiated cells, and there is indication that some of the feedback loops that operate in tissues continue to be functional in tumors. Mathematical models of such tissue hierarchies, including feedback loops, have been analyzed in a variety of different contexts. Apart from stem cells giving rise to differentiated cells, it has also been observed that more differentiated cells can de-differentiate into stem cells, both in healthy tissue and tumors, aspects of which have also been investigated mathematically. This paper analyses the effect of de-differentiation on the basic and evolutionary dynamics of cells in the context of tissue hierarchy models that include negative feedback regulation of the cell populations. The models predict that in the presence of de-differentiation, the fixation probability of a neutral mutant is lower than in its absence. Therefore, if de-differentiation occurs, a mutant with identical parameters compared to the wild-type cell population behaves like a disadvantageous mutant. Similarly, the process of de-differentiation is found to lower the fixation probability of an advantageous mutant. These results indicate that the presence of de- differentiation can lower the rates of tumor initiation and progression in the context of the models considered here. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Single-Cell RNA Sequencing Reveals Metallothionein Heterogeneity during hESC Differentiation to Definitive Endoderm [RNA-Seq]

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