Low cell number proteomic analysis using in-cell protease digests reveals a robust signature for cell cycle state classification

ABSTRACT: Comprehensive proteome analysis of rare cell phenotypes remains a significant challenge. We report a method for low cell number mass spectrometry (MS)-based proteomics using protease digestion of mildly formaldehyde-fixed cells in cellulo, which we call the ‘in-cell digest’. We combined this with AMPL (Averaged MS1 Precursor Library Matching) to make a major advance in the proteome coverage obtained from low cell numbers compared with previous methods. ~4,500 proteins were quantitated from 2,000 human lymphoblasts. ~2,500 proteins or >55% coverage was obtained using 200 lymphoblasts, i.e. an order of magnitude fewer cells. We applied the workflow to measure the proteomes of 16 cell cycle states (8 interphase, 8 mitotic) isolated from an asynchronous human lymphoblast culture (TK6), avoiding synchronisation. We identified 119 high confidence cell cycle-regulated proteins in 8 replicates. These proteins, including well-characterized and novel cell cycle-regulated factors, segregated into five clusters that differed in mitotic abundance patterns and regulatory short linear sequence motifs. We identified predictive protein signatures that accurately classified cell cycle states. These signatures enabled classification of an unexpected cell subset having 4N DNA content and low cyclin B levels as similar to early G0/G1 and telophase cells. These cells also exhibited low levels of APC/C substrates and evidence of a DNA damage response, consistent with a DNA damage-induced senescent state. This study demonstrates an advance in sensitivity in MS-based proteomics using the streamlined in-cell digest workflow. This is a powerful approach to obtain molecular definitions of important, rare cell phenotypes.

INSTRUMENT(S): LTQ Orbitrap Elite

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Van Kelly  

LAB HEAD: Tony Ly

PROVIDER: PXD028117 | Pride | 2021-11-25

REPOSITORIES: Pride