Conserved degronome features governing quality control associated proteolysis

Abstract

SummaryThe eukaryotic proteome undergoes constant surveillance by quality control systems that either sequester, refold, or eliminate aberrant proteins by ubiquitin-dependent mechanisms. Ubiquitin-conjugation necessitates the recognition of degradation determinants, termed degrons, by their cognate E3 ubiquitin-protein ligases. To learn about the distinctive properties of quality control degrons, we performed an unbiased peptidome stability screen in yeast. The search identified a large cohort of proteome-derived degrons., some of which exhibited broad E3 ligase specificity. Consequent application of a machine-learning algorithm established constraints governing degron potency, including the amino acids composition and secondary structure propensities. According to the set criteria, degrons with transmembrane domain-like characteristics are the most probable sequences to act as degrons. Similar quality control degrons were identified in viral and human proteins, suggesting for conserved degradation mechanisms. Altogether, the emerging data indicate that transmembrane domain-like degron features have been preserved in evolution as key quality control determinants of proteins’ half-life.

Prediction of quality-control degradation signals in yeast proteins

“…We aimed to develop a prediction algorithm to determine which protein sequences, when exposed to the cytosolic PQC system, can be recognized and targeted for degradation. As input to our model, we used data from an assay in which 23,600 17-residues long peptides from the yeast proteome had been fused to GFP in a reporter construct (Mashahreh et al, 2022). In this construct, peptides with strong degron properties cause degradation of GFP which, when normalized by an expression control, can be distinguished from non-degron peptides using FACS and quantified by sequencing.…”

“…AUC values were retained in 10-fold cross validations. We term the final model QCDPred because the peptides were selected to represent the signals recognized by the PQC system (Mashahreh et al, 2022). Python and R code to run QCDPred is available at https://github.com/KULL-Centre/papers/tree/main/2022/degron-predict-Johansson-et-al.…”

“…In summary, we conclude that the approach we have developed provides a first, key step in understanding and predicting the sequence properties of PQC degrons. We hope that the computational model, QCDPred, the experimental data (Mashahreh et al, 2022) and the application to the yeast proteome will be useful to understand better the determinants of protein abundance and quality control.…”

“…To validate the high-throughput experiment and test QCDPred experimentally, we selected ten peptide sequences that we studied-one at a time-using the same reporter system and flow cytometry readout (Fig. 1C) (Mashahreh et al, 2022). Since these ten peptides originated from yeast proteins, we first retrained our model on a set of peptides without any sequence overlap to these (see Methods).…”

“…In a new set of experiments, we extended these ideas to map more systematically degrons in Saccharomyces cerevisiae (Mashahreh et al, 2022). Specifically, we used a fluorescence-based reporter system coupled to fluorescence-activated cell sorting (FACS) and sequencing to study the degradation of 23,600 17-residue long peptides.…”