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Parallelized multidimensional analytic framework, PAMAF, applied to mammalian cells uncovers novel regulatory principles in EMT

ABSTRACT: Painting a holistic picture of disease etiology will require longitudinal systems-scale reconstruction of the multitiered architecture of eukaryotic signaling. As opposed to ‘one omic at a time’, which provides an incomplete view on disease mechanisms, here we developed an experimental and analytics framework, PAMAF, to simultaneously acquire and analyze twelve omic modalities from the same set of samples, i.e., protein abundance from whole-cells, nucleus, exosomes, secretome and membrane; peptidome; N-glycosylation, phosphorylation; metabolites; mRNA, miRNA; and, in parallel, single-cell transcriptomes. We applied PAMAF in a well-studied in vitro model of TGFβ-induced EMT to generate the EMT-ExMap dataset, cataloguing >61,000 expression profiles (>10,000 differential) over 12 days. PAMAF revealed that EMT is more complex than currently understood and identified numerous stage-specific mechanisms and vulnerabilities not captured in literature. Broad application of PAMAF will provide unprecedented insights into multifaceted biological processes relevant to human health and disease.

ORGANISM(S): Human Homo Sapiens

TISSUE(S): Breast Cancer Cells

SUBMITTER: Indranil Paul

PROVIDER: ST001861 | MetabolomicsWorkbench | Tue Jun 22 00:00:00 BST 2021

REPOSITORIES: MetabolomicsWorkbench

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