Ultra-sensitive proteome profiling of FACS-isolated cell populations by data-independent acquisition-MS: Application to human hematopoietic stem and progenitor cells

Abstract

Physiological processes in multicellular organisms depend on the function and interactions of a multitude of specialized cell types operating in context. Fluorescence-activated cell sorting (FACS) provides a powerful tool to determine the cell type composition of complex mixtures and to purify highly homogeneous cell populations using a small number of differentially expressed marker proteins. These populations can be further characterized, e.g. by phenotypic or molecular analyses.\n\nWe describe an ultra-sensitive mass spectrometric method for the robust quantitative and reproducible proteomic analysis of cohorts of FACS-isolated cell samples. It uses a minimum of post-sorting sample processing steps prior to data-independent acquisition MS on a current generation Orbitrap hybrid mass spectrometer. The method provides highly accurate and reproducible quantitative proteome profiles across the cohort with an average coefficient of variance <15% from as little as 150 ng of total peptide mass. We quantified the proteome of 25,000 sorted human hematopoietic stem/multipotent progenitor cell and three committed progenitor cell subpopulations (common myeloid progenitors, megakaryocyte-erythrocyte progenitors and granulocyte-macrophage progenitors) isolated from five healthy donors. On average, 5,851 protein groups were identified per sample. After stringent filtering, a subset of 4,131 protein groups ([≥]2 peptides) was used for differential comparison across the 20 samples, defining unique proteomic signatures for each cell type tested. A comparison of proteomic and transcriptomic profiles of the four cell types indicated hematopoietic stem/multipotent progenitor cell-specific divergent regulation of biochemical processes that are essential for maintaining stemness and were detected at the proteome rather than the transcriptome level.\n\nThe technology supports the generation of extensive and accurate quantitative proteomic profiles from low numbers of FACS-purified cells providing new information about the biochemical state of the analyzed cell types that is essential for basic and translational research.