The iPSC proteomic compendium

Abstract

Induced pluripotent stem cell (iPSC) technology holds great potential for therapeutic and research purposes. The Human Induced Pluripotent Stem Cell Initiative (HipSci) was established to generate a panel of high-quality iPSCs, from healthy and disease cohorts, with accompanying multi-omics and phenotypic data. Here, we present a proteomic analysis of 217 HipSci iPSC lines obtained from 163 donors.This dataset provides a comprehensive proteomic map of iPSCs, identifying >16,000 protein groups. We analyse how the expression profiles of proteins involved in cell cycle, metabolism and DNA repair contribute to key features of iPSC biology and we identify potential new regulators of the primed pluripotent state. To facilitate access, all these data have been integrated into the Encyclopedia of Proteome Dynamics (www.peptracker.com/epd), where it can be browsed interactively. Additionally, we generated an iPSC specific spectral library for DIA which we deposited in PRIDE along with the raw and processed mass-spectrometry data.

Population-scale proteome variation in human induced pluripotent stem cells

“…A set of 217 iPSC lines from the HipSci project ( Kilpinen et al, 2017 ), derived from 163 distinct donors, was selected for protein analysis, using material from the identical batches of cells that were used for RNA-Seq and other assays (Materials and methods). Quantitative mass spectrometry was carried out in batches of 10 lines, using tandem mass tagging (TMT, Thompson et al, 2003 ), with one common reference sample shared across batches ( Brenes et al, 2018 ) (Materials and methods). Collectively, we identified 255,015 distinct (unmodified) peptide sequences, corresponding to 16,773 protein groups (groups of protein isoforms with no discriminating peptides; hereon denoted proteins) with median sequence coverage of 46%.…”

Optimising multi-batch TMT analysis to mitigate inflation of missing values, false positives and diminished inter batch accuracy

“…In this manuscript, we analyse a recent data set from a proteomic study of human iPSC cells, involving 24 separate 10-plex TMT batches 17 . We compare the quantitation of data both within and between separate 10-plex batches and focus our analysis on 3 main issues: (i) missing values, (ii) accuracy of quantification and (iii) the effect of both reporter ion interference (RII) and co-isolation interference (CII).…”

“…We calculated protein copy numbers for 216 different iPSCs lines, and 24 technical replicates of a single, control iPSC line, across 24 separate 10-plex TMT batches 17 . We then proceeded to calculate Lin's concordance correlation coefficient 19 for every iPSC line within each TMT 10-plex batch, and for all the technical replicates of the control line, channel TMT 10 126, across all the 24 10-plex TMT batches ( Fig.…”

“…The iPSC dataset 17,21 provided us with an excellent opportunity to study the widely recognised effect on data quality and quantitation of both co-isolation interference (CII) and reporter ion interference (RII) within a multi-plex TMT batch. The study utilised iPSC lines derived from both male and female donors within twenty-two of the twenty-four 10-plex TMT batches analysed here.…”

“…The data analysed within this study used a SPS-MS3 method for LC-MS on an Orbitrap Fusion Tribid mass spectrometer (Thermo Fisher). For details regarding sample preparation and LC-MS methods see 17 .…”