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Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states.

ABSTRACT: The complexity of gene regulatory networks that lead multipotent cells to acquire different cell fates makes a quantitative understanding of differentiation challenging. Using a statistical framework to analyze single-cell transcriptomics data, we infer the gene expression dynamics of early mouse embryonic stem (mES) cell differentiation, uncovering discrete transitions across nine cell states. We validate the predicted transitions across discrete states using flow cytometry. Moreover, using live-cell microscopy, we show that individual cells undergo abrupt transitions from a naïve to primed pluripotent state. Using the inferred discrete cell states to build a probabilistic model for the underlying gene regulatory network, we further predict and experimentally verify that these states have unique response to perturbations, thus defining them functionally. Our study provides a framework to infer the dynamics of differentiation from single cell transcriptomics data and to build predictive models of the gene regulatory networks that drive the sequence of cell fate decisions during development.

SUBMITTER: Jang S

PROVIDER: S-EPMC5352225 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states.

Jang Sumin S Choubey Sandeep S Furchtgott Leon L Zou Ling-Nan LN Doyle Adele A Menon Vilas V Loew Ethan B EB Krostag Anne-Rachel AR Martinez Refugio A RA Madisen Linda L Levi Boaz P BP Ramanathan Sharad S

eLife 20170315

The complexity of gene regulatory networks that lead multipotent cells to acquire different cell fates makes a quantitative understanding of differentiation challenging. Using a statistical framework to analyze single-cell transcriptomics data, we infer the gene expression dynamics of early mouse embryonic stem (mES) cell differentiation, uncovering discrete transitions across nine cell states. We validate the predicted transitions across discrete states using flow cytometry. Moreover, using liv ...[more]

PMID: 28296635

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Project description:Induction of differentiation in cancer stem cells by drug treatment represents an important approach for cancer therapy. The understanding of the mechanisms that regulate such a forced exit from malignant pluripotency is fundamental to enhance our knowledge of tumour stability. Certain nucleoside analogues, such as 2'-deoxy-5-azacytidine and 1?-arabinofuranosylcytosine, can induce the differentiation of the embryonic cancer stem cell line NTERA 2 D1 (NT2). Such induced differentiation is associated with drug-dependent DNA-damage, cellular stress and the proteolytic depletion of stem cell factors. In order to further elucidate the mode of action of these nucleoside drugs, we monitored differentiation-specific changes of the dielectric properties of growing NT2 cultures using electric cell-substrate impedance sensing (ECIS). We measured resistance values of untreated and retinoic acid treated NT2 cells in real-time and compared their impedance profiles to those of cell populations triggered to differentiate with several established substances, including nucleoside drugs. Here we show that treatment with retinoic acid and differentiation-inducing drugs can trigger specific, concentration-dependent changes in dielectric resistance of NT2 cultures, which can be observed as early as 24 hours after treatment. Further, low concentrations of nucleoside drugs induce differentiation-dependent impedance values comparable to those obtained after retinoic acid treatment, whereas higher concentrations induce proliferation defects. Finally, we show that impedance profiles of substance-induced NT2 cells and those triggered to differentiate by depletion of the stem cell factor OCT4 are very similar, suggesting that reduction of OCT4 levels has a dominant function for differentiation induced by nucleoside drugs and retinoic acid. The data presented show that NT2 cells have specific dielectric properties, which allow the early identification of differentiating cultures and real-time label-free monitoring of differentiation processes. This work might provide a basis for further analyses of drug candidates for differentiation therapy of cancers.

Dataset Information

Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states.

Publications

Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states.

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