Dataset Information

Transcriptomic and Proteomic Signatures of Stemness and Differentiation in the Colon Crypt

ABSTRACT: The intestinal epithelium is replaced weekly by non-quiescent stem cells with kinetics that rely on a rapid loss of stemness and choice for secretory or absorptive lineage differentiation. To determine how the cellular transcriptome and proteome changes during these transitions, we developed a new cell sorting method to purify stem cells, secretory and absorptive progenitor cells, and mature, differentiated cells. Transcriptome analyses revealed that as stem cells transition to the progenitor stage, alternative mRNA splicing and polyadenylation dominate changes in the transcriptome. In contrast, as progenitors differentiate into mature cell types, alterations in gene expression and mRNA levels drive the changes. RNA processing targets mRNAs encoding regulators of cell cycle, RNA regulators, cell adhesion, SUMOylation, and Wnt and Notch signaling. Additionally, carrier-assisted mass spectrometry of sorted cell populations detected >2,800 proteins and revealed RNA:protein patterns of abundance and correlation. Paired together, these data highlight new potentials for autocrine and feedback regulation and provide new insights into cell state transitions in the crypt.

ORGANISM(S): Mus Musculus (mouse)

SUBMITTER: Marian L. Waterman

PROVIDER: PXD019351 | JPOST Repository | Wed Jul 15 00:00:00 BST 2020

REPOSITORIES: jPOST

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Publications

Transcriptomic and proteomic signatures of stemness and differentiation in the colon crypt.

Habowski Amber N AN Flesher Jessica L JL Bates Jennifer M JM Tsai Chia-Feng CF Martin Kendall K Zhao Rui R Ganesan Anand K AK Edwards Robert A RA Shi Tujin T Wiley H Steven HS Shi Yongsheng Y Hertel Klemens J KJ Waterman Marian L ML

Communications biology 20200819 1

Intestinal stem cells are non-quiescent, dividing epithelial cells that rapidly differentiate into progenitor cells of the absorptive and secretory cell lineages. The kinetics of this process is rapid such that the epithelium is replaced weekly. To determine how the transcriptome and proteome keep pace with rapid differentiation, we developed a new cell sorting method to purify mouse colon epithelial cells. Here we show that alternative mRNA splicing and polyadenylation dominate changes in the t ...[more]

PMID: 32814826

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Project description:Abstract: The intestinal epithelium is replaced weekly by non-quiescent stem cells with kinetics that rely on a rapid loss of stemness and choice for secretory or absorptive lineage differentiation. To determine how the cellular transcriptome and proteome changes during these transitions, we developed a new cell sorting method to purify stem cells, secretory and absorptive progenitor cells, and mature, differentiated cells. Transcriptome analyses revealed that as stem cells transition to the progenitor stage, alternative mRNA splicing and polyadenylation dominate changes in the transcriptome. In contrast, as progenitors differentiate into mature cell types, alterations in gene expression and mRNA levels drive the changes. RNA processing targets mRNAs encoding regulators of cell cycle, RNA regulators, cell adhesion, SUMOylation, and Wnt and Notch signaling. Additionally, carrier-assisted mass spectrometry of sorted cell populations detected >2,800 proteins and revealed RNA:protein patterns of abundance and correlation. Paired together, these data highlight new potentials for autocrine and feedback regulation and provide new insights into cell state transitions in the crypt. Sorting Protocol: To create a high-resolution profile of colon crypt stem cells and their daughter cells we developed a new flow sorting protocol using freshly dissected, wild-type C57Bl/6N mouse colons and antibodies to validated intestinal cell surface markers including Cd44. Upon discovery that Cd44 is highly sensitive to TrypLE, and other commonly used proteases, we developed a dissociation protocol that uses only EDTA and mechanical force. This change enabled a 10-fold greater range of Cd44 antigen surface expression and therefore higher resolution for cell sorting. Using additional commonly used cell surface markers, six cryptal populations were purified. A previously validated intestinal stem cell signature of Cd44 high, Cd24 low, and cKit negative was used to identify and isolate an abundant fraction of stem cells, a cell population that directly overlapped with Lgr5-EGFP+ cells from Lgr5-EGFP-IRES-creERT2 mice, confirming their stem cell identity. In addition to the stem cell population, five additional Epcam positive populations were collected, and the biological replicate samples of the six populations were processed for bulk RNA-seq. The clearly identified populations are stem cells, two distinct populations of progenitor cells (absorptive and secretory), and three mature, differentiated populations (enterocytes, Tuft cells and Enteroendocrine (EEC) cells). Thus, the new protocol for crypt isolation and the greater range of Cd44 surface expression it preserves, enables a significant improvement in the resolution and sorting of stem cells away from their daughter cells and differentiated progeny. Specifically, it is now possible to distinguish stem cells from Absorptive Progenitor cells (AbsPro; Cd44Med) and from mature Enterocytes (Ent; Cd44Low/-) because of the higher resolution of Cd44 surface expression. Secretory progenitors are identified as SecPDG as this population contains a majority of Secretory Progenitors and Deep Crypt Secretory cells, with a possible minor contribution of Goblet cells, a cell type that is largely missing in this procedure. Finally, preserved Cd44 expression (and cKit expression) enabled resolution of two rare Epcam+/Cd24high populations identified as Tuft cells and Enteroendocrine cells (EEC), mature cell types from the secretory lineage (EEC are predominantly Enterochromaffin; Tuft, comprise both Tuft-1 and Tuft-2 subtypes).

Project description:Hamey2017 - Blood stem cell regulatory network This model is described in the article: Reconstructing blood stem cell regulatory network models from single-cell molecular profiles Fiona K. Hamey, Sonia Nestorowa, Sarah J. Kinston, David G. Kent, Nicola K. Wilson, and Berthold Göttgens Proceedings of the National Academy of Sciences of the United States of America Abstract: Adult blood contains a mixture of mature cell types, each with specialized functions. Single hematopoietic stem cells (HSCs) have been functionally shown to generate all mature cell types for the lifetime of the organism. Differentiation of HSCs toward alternative lineages must be balanced at the population level by the fate decisions made by individual cells. Transcription factors play a key role in regulating these decisions and operate within organized regulatory programs that can be modeled as transcriptional regulatory networks. As dysregulation of single HSC fate decisions is linked to fatal malignancies such as leukemia, it is important to understand how these decisions are controlled on a cell-by-cell basis. Here we developed and applied a network inference method, exploiting the ability to infer dynamic information from single-cell snapshot expression data based on expression profiles of 48 genes in 2,167 blood stem and progenitor cells. This approach allowed us to infer transcriptional regulatory network models that recapitulated differentiation of HSCs into progenitor cell types, focusing on trajectories toward megakaryocyte–erythrocyte progenitors and lymphoid-primed multipotent progenitors. By comparing these two models, we identified and subsequently experimentally validated a difference in the regulation of nuclear factor, erythroid 2 (Nfe2) and core-binding factor, runt domain, alpha subunit 2, translocated to, 3 homolog (Cbfa2t3h) by the transcription factor Gata2. Our approach confirms known aspects of hematopoiesis, provides hypotheses about regulation of HSC differentiation, and is widely applicable to other hierarchical biological systems to uncover regulatory relationships. This model is hosted on BioModels Database and identified by: MODEL1610060000. 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:Hamey2017 - Blood stem cell regulatory network (LMPP network) This model is described in the article: Reconstructing blood stem cell regulatory network models from single-cell molecular profiles Fiona K. Hamey, Sonia Nestorowa, Sarah J. Kinston, David G. Kent, Nicola K. Wilson, and Berthold Göttgens Proceedings of the National Academy of Sciences of the United States of America Abstract: Adult blood contains a mixture of mature cell types, each with specialized functions. Single hematopoietic stem cells (HSCs) have been functionally shown to generate all mature cell types for the lifetime of the organism. Differentiation of HSCs toward alternative lineages must be balanced at the population level by the fate decisions made by individual cells. Transcription factors play a key role in regulating these decisions and operate within organized regulatory programs that can be modeled as transcriptional regulatory networks. As dysregulation of single HSC fate decisions is linked to fatal malignancies such as leukemia, it is important to understand how these decisions are controlled on a cell-by-cell basis. Here we developed and applied a network inference method, exploiting the ability to infer dynamic information from single-cell snapshot expression data based on expression profiles of 48 genes in 2,167 blood stem and progenitor cells. This approach allowed us to infer transcriptional regulatory network models that recapitulated differentiation of HSCs into progenitor cell types, focusing on trajectories toward megakaryocyte–erythrocyte progenitors and lymphoid-primed multipotent progenitors. By comparing these two models, we identified and subsequently experimentally validated a difference in the regulation of nuclear factor, erythroid 2 (Nfe2) and core-binding factor, runt domain, alpha subunit 2, translocated to, 3 homolog (Cbfa2t3h) by the transcription factor Gata2. Our approach confirms known aspects of hematopoiesis, provides hypotheses about regulation of HSC differentiation, and is widely applicable to other hierarchical biological systems to uncover regulatory relationships. This model is hosted on BioModels Database and identified by: MODEL1610060001. 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.

Dataset Information

Transcriptomic and Proteomic Signatures of Stemness and Differentiation in the Colon Crypt

Publications

Transcriptomic and proteomic signatures of stemness and differentiation in the colon crypt.

Similar Datasets

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