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Brenes, A.

Publications and source records attributed to Brenes, A..

3 recordsLinked to original sources

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

Multiplexing strategies for large-scale proteomic analyses have become increasingly prevalent, TMT in particular. Here we used a large iPSC proteomic experiment with twenty-four 10-plex TMT batches to evaluate the effect of integrating multiple TMT batches within a single analysis. We reveal a significant inflation rate of missing protein and peptide values and show that precision decreases as multiple batches are integrated. Additionally, we explore the effect of false positives using Y chromosome specific peptides as an internal control to quantify the effect of co-isolation interference, as well as primary and secondary reporter ion interference. Based on the results we suggest solutions to mitigate these effects. We show using a reference line can increase precision by normalising the quantification across batches and we propose experimental designs that minimise the effect of cross population reporter ion interference.

biochemistry↗

The iPSC proteomic compendium

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.\n\nThis 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.

biochemistry↗

Population-scale proteome variation in human induced pluripotent stem cells

Realising the potential of human induced pluripotent stem cell (iPSC) technology for drug discovery, disease modelling and cell therapy requires an understanding of variability across iPSC lines. While previous studies have characterized iPS cell lines genetically and transcriptionally, little is known about the variability of the iPSC proteome. Here, we present the first comprehensive proteomic iPSC dataset, analysing 202 iPSC lines derived from 151 donors. We characterise the major genetic determinants affecting proteome and transcriptome variation across iPSC lines and identify key regulatory mechanisms affecting variation in protein abundance. Our data identified >700 human iPSC protein quantitative trait loci (pQTLs). We mapped trans regulatory effects, identifying an important role for protein-protein interactions. We discovered that pQTLs show increased enrichment in disease-linked GWAS variants, compared with RNA-based eQTLs.

genomics↗