Reevaluation of the role of Pex1 and dynamin-related proteins in peroxisome membrane biogenesis

A recent model for peroxisome biogenesis postulates that peroxisomes form de novo continuously in wild-type cells by heterotypic fusion of endoplasmic reticulum–derived vesicles containing distinct sets of peroxisomal membrane proteins. This model proposes a role in vesicle fusion for the Pex1/Pex6 complex, which has an established role in matrix protein import. The growth and division model proposes that peroxisomes derive from existing peroxisomes. We tested these models by reexamining the role of Pex1/Pex6 and dynamin-related proteins in peroxisome biogenesis. We found that induced depletion of Pex1 blocks the import of matrix proteins but does not affect membrane protein delivery to peroxisomes; markers for the previously reported distinct vesicles colocalize in pex1 and pex6 cells; peroxisomes undergo continued growth if ission is blocked. Our data are compatible with the established primary role of the Pex1/Pex6 complex in matrix protein import and show that peroxisomes in Saccharomyces cerevisiae multiply mainly by growth and division

Co-regulation map of the human proteome enables identification of protein functions

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData availability: All mass spectrometry raw files generated in-house have been deposited in the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository36 with the dataset identifier PXD008888. The co-regulation map is hosted on our website at www.proteomeHD.net, and pair-wise co-regulation scores are available through STRING (https://string-db.org). A network of the top 0.5% co-regulated protein pairs can be explored interactively on NDEx (https://doi.org/10.18119/N9N30Q).Code availability: Data analysis was performed in R 3.5.1. R scripts and input files required to reproduce the results of this manuscript are available in the following GitHub repository: https://github.com/Rappsilber-Laboratory/ProteomeHD. R scripts related specifically to the benchmarking of the treeClust algorithm using synthetic data are available in the following GitHub repository: https://github.com/Rappsilber-Laboratory/treeClust-benchmarking. The R package data.table was used for fast data processing. Figures were prepared using ggplot2, gridExtra, cowplot and viridis.Note that the title of the AAM is different from the published versionThe annotation of protein function is a longstanding challenge of cell biology that suffers from the sheer magnitude of the task. Here we present ProteomeHD, which documents the response of 10,323 human proteins to 294 biological perturbations, measured by isotope-labelling mass spectrometry. We reveal functional associations between human proteins using the treeClust machine learning algorithm, which we show to improve protein co-regulation analysis due to robust selectivity for close linear relationships. Our co-regulation map identifies a functional context for many uncharacterized proteins, including microproteins that are difficult to study with traditional methods. Co-regulation also captures relationships between proteins which do not physically interact or co-localize. For example, co-regulation of the peroxisomal membrane protein PEX11β with mitochondrial respiration factors led us to discover a novel organelle interface between peroxisomes and mitochondria in mammalian cells. The co-regulation map can be explored at www.proteomeHD.net .Biotechnology & Biological Sciences Research Council (BBSRC)European Commissio