Meier-Menches, S. | bioRxiv Science

bioRxiv2026

RegulomeXplorer: Interactive exploration of drug effects on subcellularly resolved proteomes

Mass spectrometry-based proteomics allows the quantification of drug-induced changes in protein abundance. However, the integration of perturbation data across subcellular compartments remains a challenging bottleneck. Here, we present RegulomeXplorer, a web-based tool for automated processing and interactive exploration of subcellular compartment-resolved proteomics data. RegulomeXplorer employs MaxQuant output files to determine differential protein regulations upon drug perturbation, performs functional enrichment analysis, and visualizes enriched terms on a two-dimensional cytoplasmic-nuclear plane, called regulome. The data visualization by means of regulomes allows to simultaneously assess the magnitude of drug perturbation effects within separate subcellular compartments as well as the contribution of regulated proteins to the position of each enriched term in the regulome plane. We validated RegulomeXplorer against previously published, manually curated regulome analyses. It was then applied on subcellular compartment resolved breast cancer cell line proteomes, revealing drug- and cell-line-specific responses to Doxorubicin and Taxol, both in line with their described mode of action. RegulomeXplorer provides an accessible workflow for interpreting compartment-resolved perturbation proteomics and generating mode of action hypotheses in drug-response studies. RegulomeXplorer is freely available without registration at https://chemnettools.anc.univie.ac.at/RegulomeExplorer/. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=155 SRC="FIGDIR/small/735319v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@a7824org.highwire.dtl.DTLVardef@155a141org.highwire.dtl.DTLVardef@cdb523org.highwire.dtl.DTLVardef@12f29f7_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2023

Multilevel Omics-Readouts of in vitro Perturbation Studies are Determined by Memory Effects from Subculture

Mass spectrometry-based omics technologies are increasingly used to map drug effects to biological pathways by identifying significant molecular events. Significance is influenced by the effect size and the variation of each molecular parameter. While the former is largely determined by the biological system, the latter can be tuned by the experimental workflow. Here, we unequivocally show that memory effects originating from subculture of colon carcinoma cells before treating with arsenic trioxide exacerbate the variation of multiple omics levels, including eicosadomics, proteomics and phosphoproteomics, without necessarily impacting on effect size. Real-time monitoring of individual samples enables control over subculture homogeneity and improves the median variation >2-fold across omics levels. This considerably facilitated mode of action deconvolution and resulted in a bilevel perturbation network of 321 causal conjectures. Controlling memory effects from subculture revealed key signaling cascades and transcriptional regulatory events that extend the molecular understanding of arsenic trioxide in solid tumors.

systems biology↗