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Single-Cell Proteomics Reveal that Quantitative Changes in Co-expressed Lineage-Specific Transcription Factors Determine Cell Fate.

ABSTRACT: Hematopoiesis provides an accessible system for studying the principles underlying cell-fate decisions in stem cells. Proposed models of hematopoiesis suggest that quantitative changes in lineage-specific transcription factors (LS-TFs) underlie cell-fate decisions. However, evidence for such models is lacking as TF levels are typically measured via RNA expression rather than by analyzing temporal changes in protein abundance. Here, we used single-cell mass cytometry and absolute quantification by mass spectrometry to capture the temporal dynamics of TF protein expression in individual cells during human erythropoiesis. We found that LS-TFs from alternate lineages are co-expressed, as proteins, in individual early progenitor cells and quantitative changes of LS-TFs occur gradually rather than abruptly to direct cell-fate decisions. Importantly, upregulation of a megakaryocytic TF in early progenitors is sufficient to deviate cells from an erythroid to a megakaryocyte trajectory, showing that quantitative changes in protein abundance of LS-TFs in progenitors can determine alternate cell fates.

SUBMITTER: Palii CG

PROVIDER: S-EPMC6886472 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Single-Cell Proteomics Reveal that Quantitative Changes in Co-expressed Lineage-Specific Transcription Factors Determine Cell Fate.

Palii Carmen G CG Cheng Qian Q Gillespie Mark A MA Shannon Paul P Mazurczyk Michalina M Napolitani Giorgio G Price Nathan D ND Ranish Jeffrey A JA Morrissey Edward E Higgs Douglas R DR Brand Marjorie M

Cell stem cell 20190314 5

Hematopoiesis provides an accessible system for studying the principles underlying cell-fate decisions in stem cells. Proposed models of hematopoiesis suggest that quantitative changes in lineage-specific transcription factors (LS-TFs) underlie cell-fate decisions. However, evidence for such models is lacking as TF levels are typically measured via RNA expression rather than by analyzing temporal changes in protein abundance. Here, we used single-cell mass cytometry and absolute quantification b ...[more]

PMID: 30880026

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Project description:Marfan syndrome (MFS) is a connective tissue disorder caused by mutations in the FBN1 gene that produces wide disease phenotypic variability. The lack of ample genotype-phenotype correlation hinders translational study development aimed at improving disease prognosis. In response to this need, an induced pluripotent stem cell (iPSC) disease model has been used to test patient-specific cells by a proteomic approach. This model has the potential to risk stratify patients to make clinical decisions, including timing for surgical treatment. The regional propensity for aneurysm formation in MFS may be related to distinct smooth muscle cell (SMC) embryologic lineages. Thus, peripheral blood mononuclear cell (PBMC)-derived induced pluripotent stem cells (iPSC) were differentiated into lateral mesoderm (LM, aortic root) and neural crest (NC, ascending aorta/transverse arch) SMC lineages to model MFS aortic pathology. Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) proteomic analysis by tandem mass spectrometry was applied to profile LM and NC iPSC SMCs from four MFS patients and two healthy controls. Analysis revealed 45 proteins with lineage-dependent expression in MFS patients, many of which were specific to diseased samples. Single protein-level data from both iPSC SMCs and primary MFS aortic root aneurysm tissue confirmed elevated integrin ?V and reduced MRC2 in clinical disease specimens, validating the iPSC iTRAQ findings. Functionally, iPSC SMCs exhibited defective adhesion to a variety of extracellular matrix proteins, especially laminin-1 and fibronectin, suggesting altered cytoskeleton dynamics. This study defines the aortic embryologic origin-specific proteome in a validated iPSC SMC model to identify novel protein markers associated with MFS aneurysm phenotype. Translating iPSC findings into clinical aortic aneurysm tissue samples highlights the potential for iPSC-based methods to model MFS disease for mechanistic studies and therapeutic discovery in vitro.

Project description:BackgroundBone marrow stromal cells protect hematopoietic cells and provide drug resistance by delivering bunch of variable proteins. Thus, alterations of protein expression are typically associated with cell-cell signal transduction and regulation of cellular functions.MethodsCo-culture models of bone marrow stromal cells and hematopoietic cells are often used in studies of their crosstalk. Studies of altered protein expression initiated by stromal cell/hematopoietic cell interactions are an important new trend in microenvironmental research. There has been no report to date of global quantitative proteomics analysis of crosstalk between hematopoietic cells and stromal cells. In this study, we analyzed quantitative proteomes in a co-culture system of stromal HS5 cells and hematopoietic KG1a cells, and simultaneously tracked differentially expressed proteins in two types of cells before and after co-culture by stable isotope labeling by amino acids in cell culture (SILAC) method.ResultsWe have shown that in co-cultured KG1a, 40 proteins (including CKAP4, LMNA, and SERPINB2) were upregulated and 64 proteins (including CD44, CD99, and NCAM1) were downregulated relative to KG1a alone. We utilized IPA analysis to discover that the NOD-like receptor signaling pathway was upregulated, whereas platelet activation was downregulated in co-cultured KG1a cells. Furthermore, 95 proteins (including LCP1, ARHGAP4, and UNCX) were upregulated and 209 proteins (including CAPG, FLNC, and MAP4) were downregulated in co-cultured HS5 relative to HS5 alone. The tight junction pathway was downregulated and glycolysis/gluconeogenesis pathway was dysfunctional in co-cultured HS5. Most importantly, the significantly differentially expressed proteins can also be confirmed using different co-cultured cell lines.ConclusionAltogether, we recommend such quantitative proteomics approach for the studies of the hematopoietic-stroma cross-talk, differentially expressed proteins and related signaling pathways identification. The differentially expressed proteins identified from this current SILAC method will provide a useful basis for ongoing studies of crosstalk between stromal cells and hematopoietic cells in co-culture systems. All these result suggested our ongoing studies can focus on the mechanisms underlying CKAP4 increase and CD44 decrease in co-cultured hematopoietic cells, and the increase of LCP1 and decrease of CAPG in co-cultured stromal cell. The proteomic profiles from the KG1a/stromal cell co-culture system give new molecular insights into the roles of these cells in MDS pathophysiology and related bone disease.

Dataset Information

Single-Cell Proteomics Reveal that Quantitative Changes in Co-expressed Lineage-Specific Transcription Factors Determine Cell Fate.

Publications

Single-Cell Proteomics Reveal that Quantitative Changes in Co-expressed Lineage-Specific Transcription Factors Determine Cell Fate.

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