Biology subjects

Vogel, C.

Publications and source records attributed to Vogel, C..

5 recordsLinked to original sources

bioRxiv2018

Site-specific K63 ubiquitinomics reveals post-initiation regulation of ribosomes under oxidative stress

During oxidative stress, K63-linked polyubiquitin chains accumulate in the cell and modify a variety of proteins including ribosomes. Knowledge of the precise sites of K63 ubiquitin is key to understanding its function during the response to stress. To identify the sites of K63 ubiquitin, we developed a new mass-spectrometry based method that quantified >1,100 K63 ubiquitination sites in yeast responding to oxidative stress induced by H2O2. We determined that under stress, K63 ubiquitin modified proteins involved in several cellular functions including ion transport, protein trafficking, and translation. The most abundant ubiquitination sites localized to the head of the 40S subunit of the ribosome, modified assembled polysomes, and affected the binding of translation factors. The results suggested a new pathway of post-initiation control of translation during oxidative stress and illustrated the importance of high-resolution mapping of noncanonical ubiquitination events.

molecular biology↗

bioRxiv2018

Quantifying multi-layered expression regulation in response to stress of the endoplasmic reticulum

The mammalian response to endoplasmic reticulum (ER) stress dynamically affects all layers of gene expression regulation. We quantified transcript and protein abundance along with footprints of ribosomes and non-ribosomal proteins for thousands of genes in cervical cancer cells responding to treatment with tunicamycin or hydrogen peroxide over an eight hour time course. We identify shared and stress-specific significant regulatory events at the transcriptional and post-transcriptional level and at different phases of the experiment. ER stress regulators increase transcription and translation at different times supporting an adaptive response. ER stress also induces translation of genes from serine biosynthesis and one-carbon metabolism indicating a shift in energy production. Discordant regulation of DNA repair genes suggests transcriptional priming in which delayed translation fine-tunes the early change in the transcriptome. Finally, case studies on stress-dependent alternative splicing and protein-mRNA binding demonstrate the ability of this resource to generate hypotheses for new regulatory mechanisms.

systems biology↗

bioRxiv2018

PTMscape: an open source tool to predict generic post-translational modifications and map hotspots of modification crosstalk

While tandem mass spectrometry can now detect post-translational modifications (PTM) at the proteome scale, reported modification sites are often incomplete and include false positives. Computational approaches can complement these datasets by additional predictions, but most available tools are tailored for single modifications and each tool uses different features for prediction. We developed an R package called PTMscape which predicts modifications sites across the proteome based on a unified and comprehensive set of descriptors of the physico-chemical microenvironment of modified sites, with additional downstream analysis modules to test enrichment of individual or pairs of modifications in functional protein regions. PTMscape is generic in the ability to process any major modifications, such as phosphorylation and ubiquitination, while achieving the sensitivity and specificity comparable to single-PTM methods and outperforming other multi-PTM tools. Maintaining generalizability of the framework, we expanded proteome-wide coverage of five major modifications affecting different residues by prediction and performed combinatorial analysis for spatial co-occurrence of pairs of those modifications. This analysis revealed potential modification hotspots and crosstalk among multiple PTMs in key protein domains such as histone, protein kinase, and RNA recognition motifs, spanning various biological processes such as RNA processing, DNA damage response, signal transduction, and regulation of cell cycle. These results provide a proteome-scale analysis of crosstalk among major PTMs and can be easily extended to other modifications.\n\nContactall correspondence should be addressed to hwchoi@nus.edu.sg.

bioinformatics↗

bioRxiv2017

Integrative meta-analysis reveals that most yeast proteins are very stable

Measurements for protein half-lives in yeast Saccharomyces cerevisiae reported large discrepancies, with median values between minutes to several hours. We present a unifying analysis that provides a consistent half-life estimate, based on our re-analysis of three published and one new dataset of cells grown under similar conditions. We found that degradation of many proteins can be approximated by exponential decay. Protein disappearance was primarily driven by dilution due to cell division, with cell doubling times ranging from [~]2 to 3.5 hours across the four experiments. After adjusting for doubling time, protein half-lives increased to median values between [~]7.5 to [~]40 hours. Half-lives correlated with cell doubling time even after adjustment, implying that slow growth also slows protein degradation. All estimates were validated by multiple means and were robust to different analysis methods. Overall, protein stability correlated with abundance and showed weak enrichment for degradation signals such as degrons and disordered regions. Long-lived proteins often functioned in oxidation-reduction and amino acid synthesis. Short-lived proteins often functioned in ribosome biogenesis. Despite some overall differences in behavior, all methods were able to resolve subtle difference in half-lives of ribosomal proteins, e.g. the short lifespan of RPL10. Finally, our results help the design of future experiments: time series measurements need to cover at least two to three cell doubling times for accurate estimates, exponential decay provides a reasonable proxy for protein stability, and it can be sufficiently estimated with four measurement points.

systems biology↗

bioRxiv2017

Explicit Modeling of RNA Stability Improves Large-Scale Inference of Transcription Regulation

Inference of eukaryotic transcription regulatory networks remains challenging due to the large number of regu-lators, combinatorial interactions, and redundant pathways. Even in the model system Saccharomyces cerevisiae, inference has performed poorly. Most existing inference algorithms ignore crucial regulatory components, like RNA stability and post-transcriptional modulation of regulators. Here we demonstrate that explicitly modeling tran-scription factor activity and RNA half-lives during inference of a genome-wide transcription regulatory network in yeast not only advances prediction performance, but also produces new insights into gene-and condition-specific variation of RNA stability. We curated a high quality gold standard reference network that we use for priors on network structure and model validation. We incorporate variation of RNA half-lives into the Inferelator inference framework, and show improved performance over previously described algorithms and over implementations of the algorithm that do not model RNA degradation. We recapitulate known condition-and gene-specific trends in RNA half-lives, and make new predictions about RNA half-lives that are confirmed by experimental data.

biophysics↗