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Here, we present a peptide-based linear mixed models tool—PBLMM, a standalone desktop application for differential expression analysis of proteomics data. We also provide a Python package that allows streamlined data analysis workflows implementing the PBLMM algorithm. PBLMM is easy to use without scripting experience and calculates differential expression by peptide-based linear mixed regression models. We show that peptide-based models outperform classical methods of statistical inference of differentially expressed proteins. In addition, PBLMM exhibits superior statistical power in situations of low effect size and/or low sample size. Taken together our tool provides an easy-to-use, high-statistical-power method to infer differentially expressed proteins from proteomics data.
Cell-free therapy using extracellular vesicles (EVs) from adipose-derived mesenchymal stromal/stem cells (ASCs) seems to be a safe and effective therapeutic option to support tissue and organ regeneration. The application of EVs requires particles with a maximum regenerative capability and hypoxic culture conditions as an in vitro preconditioning regimen has been shown to alter the molecular composition of released EVs. Nevertheless, the EV cargo after hypoxic preconditioning has not yet been comprehensively examined. The aim of the present study was the characterization of EVs from hypoxic preconditioned ASCs. We investigated the EV proteome and their effects on renal tubular epithelial cells in vitro. While no effect of hypoxia was observed on the number of released EVs and their protein content, the cargo of the proteins was altered. Proteomic analysis showed 41 increased or decreased proteins, 11 in a statistically significant manner. Furthermore, the uptake of EVs in epithelial cells and a positive effect on oxidative stress in vitro were observed. In conclusion, culture of ASCs under hypoxic conditions was demonstrated to be a promising in vitro preconditioning regimen, which alters the protein cargo and increases the anti-oxidative potential of EVs. These properties may provide new potential therapeutic options for regenerative medicine.
Regulation of translation is essential during stress. However, the precise sets of proteins regulated by the key translational stress responses—the integrated stress response (ISR) and mTORC1—remain elusive. We developed multiplexed enhanced protein dynamics (mePROD) proteomics, adding signal amplification to dynamic-SILAC and multiplexing, to enable measuring acute changes in protein synthesis. Treating cells with ISR/mTORC1-modulating stressors, we showed extensive translatome modulation with ∼20% of proteins synthesized at highly reduced rates. Comparing translation-deficient sub-proteomes revealed an extensive overlap demonstrating that target specificity is achieved on protein level and not by pathway activation. Titrating cap-dependent translation inhibition confirmed that synthesis of individual proteins is controlled by intrinsic properties responding to global translation attenuation. This study reports a highly sensitive method to measure relative translation at the nascent chain level and provides insight into how the ISR and mTORC1, two key cellular pathways, regulate the translatome to guide cellular survival upon stress.