Oxidative stress induces a number of cellular responses. Silva et al. uncover a peroxide-mediated K63-linked polyubiquitination pathway, and identify its targets and regulators. Ubiquitination is a post-translational modification that signals multiple processes, including protein degradation, trafficking and DNA repair. Polyubiquitin accumulates globally during the oxidative stress response, and this has been mainly attributed to increased ubiquitin conjugation and perturbations in protein degradation. Here we show that the unconventional Lys63 (K63)-linked polyubiquitin accumulates in the yeast Saccharomyces cerevisiae in a highly sensitive and regulated manner as a result of exposure to peroxides. We demonstrate that hydrogen peroxide inhibits the deubiquitinating enzyme Ubp2, leading to accumulation of K63 conjugates assembled by the Rad6 ubiquitin conjugase and the Bre1 ubiquitin ligase. Using linkage-specific isolation methods and stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative proteomics, we identified >100 new K63-polyubiquitinated targets, which were substantially enriched in ribosomal proteins. Finally, we demonstrate that impairment of K63 ubiquitination during oxidative stress affects polysome stability and protein expression, rendering cells more sensitive to stress, and thereby reveal a new redox-regulatory role for this modification.

The relative importance of regulation at the mRNA versus protein level is subject to ongoing debate. To address this question in a dynamic system, we mapped proteomic and transcriptomic changes in mammalian cells responding to stress induced by dithiothreitol over 30 h. Specifically, we estimated the kinetic parameters for the synthesis and degradation of RNA and proteins, and deconvoluted the response patterns into common and unique to each regulatory level using a new statistical tool. Overall, the two regulatory levels were equally important, but differed in their impact on molecule concentrations. Both mRNA and protein changes peaked between two and eight hours, but mRNA expression fold changes were much smaller than those of the proteins. mRNA concentrations shifted in a transient, pulse‐like pattern and returned to values close to pre‐treatment levels by the end of the experiment. In contrast, protein concentrations switched only once and established a new steady state, consistent with the dominant role of protein regulation during misfolding stress. Finally, we generated hypotheses on specific regulatory modes for some genes.

Oxidative stress is known to affect both translation and protein turnover, but very few large scale studies describe protein expression under stress. We measure protein concentrations in Saccharomyces cerevisiae over the course of 2 h in response to a mild oxidative stress induced by diamide, providing detailed time-resolved information for 815 proteins, with additional data for another ∼1,100 proteins. For the majority of proteins, we discover major differences between the global transcript and protein response. Although mRNA levels often return to baseline 1 h after treatment, protein concentrations continue to change. Integrating our data with features of translation and protein degradation, we are able to predict expression patterns for 41% of the proteins in the core data set. Predictive features include, among others, targeting by RNA-binding proteins (Lhp1 and Khd1), RNA secondary structures, RNA half-life, and translation efficiency under unperturbed conditions and in response to oxidative reagents, but not chaperone binding. We are able to both describe general dynamics of protein concentration changes and suggest possible regulatory mechanisms for individual proteins.

Technological advances now enable routine measurement of mRNA and protein abundances, and estimates of their rates of synthesis and degradation that inform on their values and the degree of change in response to stimuli. Importantly, more and more data on time-series experiments are emerging, e.g. of cells responding to stress, enabling first insights into a new dimension of gene expression regulation – its dynamics and how it allows for very different response signals across genes. This review discusses recently published methods and datasets, their impact on what we now know about the relationships between concentrations and synthesis rates of mRNAs and proteins in yeast and mammalian cells, their evolution, and new hypotheses on translation regulatory mechanisms generated by approaches that involve ribosome footprinting.