Hypothesis-free high-throughput profiling allows relative quantification of thousands of proteins or transcripts across samples and thereby identification of differentially expressed genes. It is used in many biological contexts to characterize differences between cell lines and tissues, identify drug mode of action or drivers of drug resistance, among others. Changes in gene expression can also be due to confounding factors that were not accounted for in the experimental plan, such as change in cell proliferation. We combined the analysis of 1,076 and 1,040 cell lines in five proteomics and three transcriptomics data sets to identify 157 genes that correlate with cell proliferation rates. These include actors in DNA replication and mitosis, and genes periodically expressed during the cell cycle. This signature of cell proliferation is a valuable resource when analyzing high-throughput data showing changes in proliferation across conditions. We show how to use this resource to help in interpretation of in vitro drug screens and tumor samples. It informs on differences of cell proliferation rates between conditions where such information is not directly available. The signature genes also highlight which hits in a screen may be due to proliferation changes; this can either contribute to biological interpretation or help focus on experiment-specific regulation events otherwise buried in the statistical analysis.

SUMMARY: With the advent of fully automated sample preparation robots for Hydrogen-Deuterium eXchange coupled to Mass Spectrometry (HDX-MS), this method has become paramount for ligand binding or epitope mapping screening, both in academic research and biopharmaceutical industries. However, bridging the gap between commercial HDX-MS software (for raw data interpretation) and molecular viewers (to map experiment results onto a 3D structure for biological interpretation) remains laborious and requires simple but sometimes limiting coding skills. We solved this bottleneck by developing HDX-Viewer, an open-source web-based application that facilitates and quickens HDX-MS data analysis. This user-friendly application automatically incorporates HDX-MS data from a custom template or commercial HDX-MS software in PDB files, and uploads them to an online 3D molecular viewer, thereby facilitating their visualization and biological interpretation. AVAILABILITY AND IMPLEMENTATION: The HDX-Viewer web application is released under the CeCILL (http://www.cecill.info) and GNU LGPL licenses and can be found at https://masstools.ipbs.fr/hdx-viewer. The source code is available at https://github.com/david-bouyssie/hdx-viewer.

SUMMARY: VisioProt-MS is designed to summarize and analyze intact protein and top-down proteomics data. It plots the molecular weights of eluting proteins as a function of their retention time, thereby allowing inspection of runs from liquid chromatography coupled to mass spectrometry (LC-MS). It also overlays MS/MS identification results. VisioProt-MS is compatible with outputs from many different top-down dedicated software. To our knowledge, this is the only open source standalone application that allows the dynamic comparison of several MS files, a prerequisite for comparative analysis of different biological conditions. With its dynamic rendering, this user-friendly web application facilitates inspection, comparison and export of publication quality 2 D maps from deconvoluted LC-MS run(s) and top-down proteomics data. AVAILABILITY AND IMPLEMENTATION: The Shiny-based web application VisioProt-MS is suitable for non-R users. It can be found at https://masstools.ipbs.fr/mstools/visioprot-ms/ and the corresponding scripts are downloadable at https://github.com/mlocardpaulet/VisioProt-MS. It is governed by the CeCILL license (http://www.cecill.info).