Stress-Triggered Phase Separation Is an Adaptive, Evolutionarily Tuned Response.

In eukaryotic cells, diverse stresses trigger coalescence of RNA-binding proteins into stress granules. In vitro, stress-granule-associated proteins can demix to form liquids, hydrogels, and other assemblies lacking fixed stoichiometry. Observing these phenomena has generally required conditions far removed from physiological stresses. We show that poly(A)-binding protein (Pab1 in yeast), a defining marker of stress granules, phase separates and forms hydrogels in vitro upon exposure to physiological stress conditions. Other RNA-binding proteins depend upon low-complexity regions (LCRs) or RNA for phase separation, whereas Pab1's LCR is not required for demixing, and RNA inhibits it. Based on unique evolutionary patterns, we create LCR mutations, which systematically tune its biophysical properties and Pab1 phase separation in vitro and in vivo. Mutations that impede phase separation reduce organism fitness during prolonged stress. Poly(A)-binding protein thus acts as a physiological stress sensor, exploiting phase separation to precisely mark stress onset, a broadly generalizable mechanism.

Dying mRNA Tells a Story of Its Life.

In this issue of Cell, Pelechano et al. report that sequencing of mRNA decay intermediates shows surprisingly tight coupling of a major decay pathway to the movement of the last translating ribosome, revealing stress- and starvation-dependent modulation of translation elongation.

Reversible, Specific, Active Aggregates of Endogenous Proteins Assemble upon Heat Stress.

Heat causes protein misfolding and aggregation and, in eukaryotic cells, triggers aggregation of proteins and RNA into stress granules. We have carried out extensive proteomic studies to quantify heat-triggered aggregation and subsequent disaggregation in budding yeast, identifying >170 endogenous proteins aggregating within minutes of heat shock in multiple subcellular compartments. We demonstrate that these aggregated proteins are not misfolded and destined for degradation. Stable-isotope labeling reveals that even severely aggregated endogenous proteins are disaggregated without degradation during recovery from shock, contrasting with the rapid degradation observed for many exogenous thermolabile proteins. Although aggregation likely inactivates many cellular proteins, in the case of a heterotrimeric aminoacyl-tRNA synthetase complex, the aggregated proteins remain active with unaltered fidelity. We propose that most heat-induced aggregation of mature proteins reflects the operation of an adaptive, autoregulatory process of functionally significant aggregate assembly and disassembly that aids cellular adaptation to thermal stress.

Stressful steps: Progress and challenges in understanding stress-induced mRNA condensation and accumulation in stress granules.

Stress-induced condensation of mRNA and protein into massive cytosolic clusters is conserved across eukaryotes. Known as stress granules when visible by imaging, these structures remarkably have no broadly accepted biological function, mechanism of formation or dispersal, or even molecular composition. As part of a larger surge of interest in biomolecular condensation, studies of stress granules and related RNA/protein condensates have increasingly probed the biochemical underpinnings of condensation. Here, we review open questions and recent advances, including the stages from initial condensate formation to accumulation in mature stress granules, mechanisms by which stress-induced condensates form and dissolve, and surprising twists in understanding the RNA components of stress granules and their role in condensation. We outline grand challenges in understanding stress-induced RNA condensation, centering on the unique and substantial barriers in the molecular study of cellular structures, such as stress granules, for which no biological function has been firmly established.

Chaperones directly and efficiently disperse stress-triggered biomolecular condensates.

Stresses such as heat shock trigger the formation of protein aggregates and the induction of a disaggregation system composed of molecular chaperones. Recent work reveals that several cases of apparent heat-induced aggregation, long thought to be the result of toxic misfolding, instead reflect evolved, adaptive biomolecular condensation, with chaperone activity contributing to condensate regulation. Here we show that the yeast disaggregation system directly disperses heat-induced biomolecular condensates of endogenous poly(A)-binding protein (Pab1) orders of magnitude more rapidly than aggregates of the most commonly used misfolded model substrate, firefly luciferase. Beyond its efficiency, heat-induced condensate dispersal differs from heat-induced aggregate dispersal in its molecular requirements and mechanistic behavior. Our work establishes a bona fide endogenous heat-induced substrate for long-studied heat shock proteins, isolates a specific example of chaperone regulation of condensates, and underscores needed expansion of the proteotoxic interpretation of the heat shock response to encompass adaptive, chaperone-mediated regulation.

HDX-MS finds that partial unfolding with sequential domain activation controls condensation of a cellular stress marker.

Eukaryotic cells form condensates to sense and adapt to their environment [S. F. Banani, H. O. Lee, A. A. Hyman, M. K. Rosen, Nat. Rev. Mol. Cell Biol. 18, 285-298 (2017), H. Yoo, C. Triandafillou, D. A. Drummond, J. Biol. Chem. 294, 7151-7159 (2019)]. Poly(A)-binding protein (Pab1), a canonical stress granule marker, condenses upon heat shock or starvation, promoting adaptation [J. A. Riback et al., Cell 168, 1028-1040.e19 (2017)]. The molecular basis of condensation has remained elusive due to a dearth of techniques to probe structure directly in condensates. We apply hydrogen-deuterium exchange/mass spectrometry to investigate the mechanism of Pab1's condensation. Pab1's four RNA recognition motifs (RRMs) undergo different levels of partial unfolding upon condensation, and the changes are similar for thermal and pH stresses. Although structural heterogeneity is observed, the ability of MS to describe populations allows us to identify which regions contribute to the condensate's interaction network. Our data yield a picture of Pab1's stress-triggered condensation, which we term sequential activation (Fig. 1A), wherein each RRM becomes activated at a temperature where it partially unfolds and associates with other likewise activated RRMs to form the condensate. Subsequent association is dictated more by the underlying free energy surface than specific interactions, an effect we refer to as thermodynamic specificity. Our study represents an advance for elucidating the interactions that drive condensation. Furthermore, our findings demonstrate how condensation can use thermodynamic specificity to perform an acute response to multiple stresses, a potentially general mechanism for stress-responsive proteins.

Pervasive, conserved secondary structure in highly charged protein regions.

Understanding how protein sequences confer function remains a defining challenge in molecular biology. Two approaches have yielded enormous insight yet are often pursued separately: structure-based, where sequence-encoded structures mediate function, and disorder-based, where sequences dictate physicochemical and dynamical properties which determine function in the absence of stable structure. Here we study highly charged protein regions (>40% charged residues), which are routinely presumed to be disordered. Using recent advances in structure prediction and experimental structures, we show that roughly 40% of these regions form well-structured helices. Features often used to predict disorder-high charge density, low hydrophobicity, low sequence complexity, and evolutionarily varying length-are also compatible with solvated, variable-length helices. We show that a simple composition classifier predicts the existence of structure far better than well-established heuristics based on charge and hydropathy. We show that helical structure is more prevalent than previously appreciated in highly charged regions of diverse proteomes and characterize the conservation of highly charged regions. Our results underscore the importance of integrating, rather than choosing between, structure- and disorder-based approaches.

Heat Shock Factor 1: From Fire Chief to Crowd-Control Specialist.

HSF1 is the supposed master regulator of the heat shock response. In this issue of Molecular Cell, Solís et al. reveal that it has a much narrower job description: organizing a small team of molecular chaperones that keep the proteome moving.

Mistranslation-induced protein misfolding as a dominant constraint on coding-sequence evolution.

Strikingly consistent correlations between rates of coding-sequence evolution and gene expression levels are apparent across taxa, but the biological causes behind the selective pressures on coding-sequence evolution remain controversial. Here, we demonstrate conserved patterns of simple covariation between sequence evolution, codon usage, and mRNA level in E. coli, yeast, worm, fly, mouse, and human that suggest that all observed trends stem largely from a unified underlying selective pressure. In metazoans, these trends are strongest in tissues composed of neurons, whose structure and lifetime confer extreme sensitivity to protein misfolding. We propose, and demonstrate using a molecular-level evolutionary simulation, that selection against toxicity of misfolded proteins generated by ribosome errors suffices to create all of the observed covariation. The mechanistic model of molecular evolution that emerges yields testable biochemical predictions, calls into question the use of nonsynonymous-to-synonymous substitution ratios (Ka/Ks) to detect functional selection, and suggests how mistranslation may contribute to neurodegenerative disease.

Cellular sensing by phase separation: Using the process, not just the products.

Phase separation creates two distinct liquid phases from a single mixed liquid phase, like oil droplets separating from water. Considerable attention has focused on how the products of phase separation-the resulting condensates-might act as biological compartments, bioreactors, filters, and membraneless organelles in cells. Here, we expand this perspective, reviewing recent results showing how cells instead use the process of phase separation to sense intracellular and extracellular changes. We review case studies in phase separation-based sensing and discuss key features, such as extraordinary sensitivity, which make the process of phase separation ideally suited to meet a range of sensory challenges cells encounter.

How infidelity creates a sticky situation.

Errors in translation cause cytotoxic protein misfolding and aggregation. In this issue, Ling et al. (2012) show that scavenging or suppression of reactive oxygen species in E. coli reduces the cellular costs of error-induced aggregation.

An Escherichia coli Nitrogen Starvation Response Is Important for Mutualistic Coexistence with Rhodopseudomonas palustris.

Microbial mutualistic cross-feeding interactions are ubiquitous and can drive important community functions. Engaging in cross-feeding undoubtedly affects the physiology and metabolism of individual species involved. However, the nature in which an individual species' physiology is influenced by cross-feeding and the importance of those physiological changes for the mutualism have received little attention. We previously developed a genetically tractable coculture to study bacterial mutualisms. The coculture consists of fermentative Escherichia coli and phototrophic Rhodopseudomonas palustris In this coculture, E. coli anaerobically ferments sugars into excreted organic acids as a carbon source for R. palustris In return, a genetically engineered R. palustris strain constitutively converts N2 into NH4+, providing E. coli with essential nitrogen. Using transcriptome sequencing (RNA-seq) and proteomics, we identified transcript and protein levels that differ in each partner when grown in coculture versus monoculture. When in coculture with R. palustris, E. coli gene expression changes resembled a nitrogen starvation response under the control of the transcriptional regulator NtrC. By genetically disrupting E. coli NtrC, we determined that a nitrogen starvation response is important for a stable coexistence, especially at low R. palustris NH4+ excretion levels. Destabilization of the nitrogen starvation regulatory network resulted in variable growth trends and, in some cases, extinction. Our results highlight that alternative physiological states can be important for survival within cooperative cross-feeding relationships.IMPORTANCE Mutualistic cross-feeding between microbes within multispecies communities is widespread. Studying how mutualistic interactions influence the physiology of each species involved is important for understanding how mutualisms function and persist in both natural and applied settings. Using a bacterial mutualism consisting of Rhodopseudomonas palustris and Escherichia coli growing cooperatively through bidirectional nutrient exchange, we determined that an E. coli nitrogen starvation response is important for maintaining a stable coexistence. The lack of an E. coli nitrogen starvation response ultimately destabilized the mutualism and, in some cases, led to community collapse after serial transfers. Our findings thus inform on the potential necessity of an alternative physiological state for mutualistic coexistence with another species compared to the physiology of species grown in isolation.

Correction: A nutrient-driven tRNA modification alters translational fidelity and genome-wide protein coding across an animal genus.

[This corrects the article DOI: 10.1371/journal.pbio.1002015.].

Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast.

Cells respond to their environment by modulating protein levels through mRNA transcription and post-transcriptional control. Modest observed correlations between global steady-state mRNA and protein measurements have been interpreted as evidence that mRNA levels determine roughly 40% of the variation in protein levels, indicating dominant post-transcriptional effects. However, the techniques underlying these conclusions, such as correlation and regression, yield biased results when data are noisy, missing systematically, and collinear---properties of mRNA and protein measurements---which motivated us to revisit this subject. Noise-robust analyses of 24 studies of budding yeast reveal that mRNA levels explain more than 85% of the variation in steady-state protein levels. Protein levels are not proportional to mRNA levels, but rise much more rapidly. Regulation of translation suffices to explain this nonlinear effect, revealing post-transcriptional amplification of, rather than competition with, transcriptional signals. These results substantially revise widely credited models of protein-level regulation, and introduce multiple noise-aware approaches essential for proper analysis of many biological phenomena.

A nutrient-driven tRNA modification alters translational fidelity and genome-wide protein coding across an animal genus.

Natural selection favors efficient expression of encoded proteins, but the causes, mechanisms, and fitness consequences of evolved coding changes remain an area of aggressive inquiry. We report a large-scale reversal in the relative translational accuracy of codons across 12 fly species in the Drosophila/Sophophora genus. Because the reversal involves pairs of codons that are read by the same genomically encoded tRNAs, we hypothesize, and show by direct measurement, that a tRNA anticodon modification from guanosine to queuosine has coevolved with these genomic changes. Queuosine modification is present in most organisms but its function remains unclear. Modification levels vary across developmental stages in D. melanogaster, and, consistent with a causal effect, genes maximally expressed at each stage display selection for codons that are most accurate given stage-specific queuosine modification levels. In a kinetic model, the known increased affinity of queuosine-modified tRNA for ribosomes increases the accuracy of cognate codons while reducing the accuracy of near-cognate codons. Levels of queuosine modification in D. melanogaster reflect bioavailability of the precursor queuine, which eukaryotes scavenge from the tRNAs of bacteria and absorb in the gut. These results reveal a strikingly direct mechanism by which recoding of entire genomes results from changes in utilization of a nutrient.

The evolutionary consequences of erroneous protein synthesis.

Errors in protein synthesis disrupt cellular fitness, cause disease phenotypes and shape gene and genome evolution. Experimental and theoretical results on this topic have accumulated rapidly in disparate fields, such as neurobiology, protein biosynthesis and degradation and molecular evolution, but with limited communication among disciplines. Here, we review studies of error frequencies, the cellular and organismal consequences of errors and the attendant long-range evolutionary responses to errors. We emphasize major areas in which little is known, such as the failure rates of protein folding, in addition to areas in which technological innovations may enable imminent gains, such as the elucidation of translational missense error frequencies. Evolutionary responses to errors fall into two broad categories: adaptations that minimize errors and their attendant costs and adaptations that exploit errors for the organism's benefit.

Estimating selection on synonymous codon usage from noisy experimental data.

A key goal in molecular evolution is to extract mechanistic insights from signatures of selection. A case study is codon usage, where despite many recent advances and hypotheses, two longstanding problems remain: the relative contribution of selection and mutation in determining codon frequencies and the relative contribution of translational speed and accuracy to selection. The relevant targets of selection--the rate of translation and of mistranslation of a codon per unit time in the cell--can only be related to mechanistic properties of the translational apparatus if the number of transcripts per cell is known, requiring use of gene expression measurements. Perhaps surprisingly, different gene-expression data sets yield markedly different estimates of selection. We show that this is largely due to measurement noise, notably due to differences between studies rather than instrument error or biological variability. We develop an analytical framework that explicitly models noise in expression in the context of the population-genetic model. Estimates of mutation and selection strength in budding yeast produced by this method are robust to the expression data set used and are substantially higher than estimates using a noise-blind approach. We introduce per-gene selection estimates that correlate well with previous scoring systems, such as the codon adaptation index, while now carrying an evolutionary interpretation. On average, selection for codon usage in budding yeast is weak, yet our estimates show that genes range from virtually unselected to average per-codon selection coefficients above the inverse population size. Our analytical framework may be generally useful for distinguishing biological signals from measurement noise in other applications that depend upon measurements of gene expression.

Good codons, bad transcript: large reductions in gene expression and fitness arising from synonymous mutations in a key enzyme.

Biased codon usage in protein-coding genes is pervasive, whereby amino acids are largely encoded by a specific subset of possible codons. Within individual genes, codon bias is stronger at evolutionarily conserved residues, favoring codons recognized by abundant tRNAs. Although this observation suggests an overall pattern of selection for translation speed and/or accuracy, other work indicates that transcript structure or binding motifs drive codon usage. However, our understanding of codon bias evolution is constrained by limited experimental data on the fitness effects of altering codons in functional genes. To bridge this gap, we generated synonymous variants of a key enzyme-coding gene in Methylobacterium extorquens. We found that mutant gene expression, enzyme production, enzyme activity, and fitness were all significantly lower than wild-type. Surprisingly, encoding the gene using only rare codons decreased fitness by 40%, whereas an allele coded entirely by frequent codons decreased fitness by more than 90%. Increasing gene expression restored mutant fitness to varying degrees, demonstrating that the fitness disadvantage of synonymous mutants arose from a lack of beneficial protein rather than costs of protein production. Protein production was negatively correlated with the frequency of motifs with high affinity for the anti-Shine-Dalgarno sequence, suggesting ribosome pausing as the dominant cause of low mutant fitness. Together, our data support the idea that, although a particular set of codons are favored on average across a genome, in an individual gene selection can either act for or against codons depending on their local context.

Misfolded proteins impose a dosage-dependent fitness cost and trigger a cytosolic unfolded protein response in yeast.

Evolving lineages face a constant intracellular threat: most new coding sequence mutations destabilize the folding of the encoded protein. Misfolded proteins form insoluble aggregates and are hypothesized to be intrinsically cytotoxic. Here, we experimentally isolate a fitness cost caused by toxicity of misfolded proteins. We exclude other costs of protein misfolding, such as loss of functional protein or attenuation of growth-limiting protein synthesis resources, by comparing growth rates of budding yeast expressing folded or misfolded variants of a gratuitous protein, YFP, at equal levels. We quantify a fitness cost that increases with misfolded protein abundance, up to as much as a 3.2% growth rate reduction when misfolded YFP represents less than 0.1% of total cellular protein. Comparable experiments on variants of the yeast gene orotidine-5'-phosphate decarboxylase (URA3) produce similar results. Quantitative proteomic measurements reveal that, within the cell, misfolded YFP induces coordinated synthesis of interacting cytosolic chaperone proteins in the absence of a wider stress response, providing evidence for an evolved modular response to misfolded proteins in the cytosol. These results underscore the distinct and evolutionarily relevant molecular threat of protein misfolding, independent of protein function. Assuming that most misfolded proteins impose similar costs, yeast cells express almost all proteins at steady-state levels sufficient to expose their encoding genes to selection against misfolding, lending credibility to the recent suggestion that such selection imposes a global constraint on molecular evolution.

Single-molecule fluorescence multiplexing by multi-parameter spectroscopic detection of nanostructured FRET labels.

Multiplexed, real-time fluorescence detection at the single-molecule level is highly desirable to reveal the stoichiometry, dynamics, and interactions of individual molecular species within complex systems. However, traditionally fluorescence sensing is limited to 3-4 concurrently detected labels, due to low signal-to-noise, high spectral overlap between labels, and the need to avoid dissimilar dye chemistries. We have engineered a palette of several dozen fluorescent labels, called FRETfluors, for spectroscopic multiplexing at the single-molecule level. Each FRETfluor is a compact nanostructure formed from the same three chemical building blocks (DNA, Cy3, and Cy5). The composition and dye-dye geometries create a characteristic F\"orster Resonance Energy Transfer (FRET) efficiency for each construct. In addition, we varied the local DNA sequence and attachment chemistry to alter the Cy3 and Cy5 emission properties and thereby shift the emission signatures of an entire series of FRET constructs to new sectors of the multi-parameter detection space. Unique spectroscopic emission of each FRETfluor is therefore conferred by a combination of FRET and this site-specific tuning of individual fluorophore photophysics. We show single-molecule identification of a set of 27 FRETfluors in a sample mixture using a subset of constructs statistically selected to minimize classification errors, measured using an Anti-Brownian ELectrokinetic (ABEL) trap which provides precise multi-parameter spectroscopic measurements. The ABEL trap also enables discrimination between FRETfluors attached to a target (here: mRNA) and unbound FRETfluors, eliminating the need for washes or removal of excess label by purification. We show single-molecule identification of a set of 27 FRETfluors in a sample mixture using a subset of constructs selected to minimize classification errors.