An atlas of protein homo-oligomerization across domains of life.

Protein structures are essential to understanding cellular processes in molecular detail. While advances in artificial intelligence revealed the tertiary structure of proteins at scale, their quaternary structure remains mostly unknown. We devise a scalable strategy based on AlphaFold2 to predict homo-oligomeric assemblies across four proteomes spanning the tree of life. Our results suggest that approximately 45% of an archaeal proteome and a bacterial proteome and 20% of two eukaryotic proteomes form homomers. Our predictions accurately capture protein homo-oligomerization, recapitulate megadalton complexes, and unveil hundreds of homo-oligomer types, including three confirmed experimentally by structure determination. Integrating these datasets with omics information suggests that a majority of known protein complexes are symmetric. Finally, these datasets provide a structural context for interpreting disease mutations and reveal coiled-coil regions as major enablers of quaternary structure evolution in human. Our strategy is applicable to any organism and provides a comprehensive view of homo-oligomerization in proteomes.

Proteomic analysis reveals the direct recruitment of intrinsically disordered regions to stress granules in S. cerevisiae.

Stress granules (SGs) are stress-induced membraneless condensates that store non-translating mRNA and stalled translation initiation complexes. Although metazoan SGs are dynamic compartments where proteins can rapidly exchange with their surroundings, yeast SGs seem largely static. To gain a better understanding of yeast SGs, we identified proteins that sediment after heat shock using mass spectrometry. Proteins that sediment upon heat shock are biased toward a subset of abundant proteins that are significantly enriched in intrinsically disordered regions (IDRs). Heat-induced SG localization of over 80 proteins were confirmed using microscopy, including 32 proteins not previously known to localize to SGs. We found that several IDRs were sufficient to mediate SG recruitment. Moreover, the dynamic exchange of IDRs can be observed using fluorescence recovery after photobleaching, whereas other components remain immobile. Lastly, we showed that the IDR of the Ubp3 deubiquitinase was critical for yeast SG formation. This work shows that IDRs can be sufficient for SG incorporation, can remain dynamic in vitrified SGs, and can play an important role in cellular compartmentalization upon stress.This article has an associated First Person interview with the first author of the paper.

YeastRGB: comparing the abundance and localization of yeast proteins across cells and libraries.

The ability to measure the abundance and visualize the localization of proteins across the yeast proteome has stimulated hypotheses on gene function and fueled discoveries. While the classic C' tagged GFP yeast library has been the only resource for over a decade, the recent development of the SWAT technology has led to the creation of multiple novel yeast libraries where new-generation fluorescent reporters are fused at the N' and C' of open reading frames. Efficient access to these data requires a user interface to visualize and compare protein abundance, localization and co-localization across cells, strains, and libraries. YeastRGB (www.yeastRGB.org) was designed to address such a need, through a user-friendly interface that maximizes informative content. It employs a compact display where cells are cropped and tiled together into a 'cell-grid.' This representation enables viewing dozens of cells for a particular strain within a display unit, and up to 30 display units can be arrayed on a standard high-definition screen. Additionally, the display unit allows users to control zoom-level and overlay of images acquired using different color channels. Thus, YeastRGB makes comparing abundance and localization efficient, across thousands of cells from different strains and libraries.

Exhaustive search of linear information encoding protein-peptide recognition.

High-throughput in vitro methods have been extensively applied to identify linear information that encodes peptide recognition. However, these methods are limited in number of peptides, sequence variation, and length of peptides that can be explored, and often produce solutions that are not found in the cell. Despite the large number of methods developed to attempt addressing these issues, the exhaustive search of linear information encoding protein-peptide recognition has been so far physically unfeasible. Here, we describe a strategy, called DALEL, for the exhaustive search of linear sequence information encoded in proteins that bind to a common partner. We applied DALEL to explore binding specificity of SH3 domains in the budding yeast Saccharomyces cerevisiae. Using only the polypeptide sequences of SH3 domain binding proteins, we succeeded in identifying the majority of known SH3 binding sites previously discovered either in vitro or in vivo. Moreover, we discovered a number of sites with both non-canonical sequences and distinct properties that may serve ancillary roles in peptide recognition. We compared DALEL to a variety of state-of-the-art algorithms in the blind identification of known binding sites of the human Grb2 SH3 domain. We also benchmarked DALEL on curated biological motifs derived from the ELM database to evaluate the effect of increasing/decreasing the enrichment of the motifs. Our strategy can be applied in conjunction with experimental data of proteins interacting with a common partner to identify binding sites among them. Yet, our strategy can also be applied to any group of proteins of interest to identify enriched linear motifs or to exhaustively explore the space of linear information encoded in a polypeptide sequence. Finally, we have developed a webserver located at http://michnick.bcm.umontreal.ca/dalel, offering user-friendly interface and providing different scenarios utilizing DALEL.

The HIV gp41 pocket binding domain enables C-terminal heptad repeat transition from mediating membrane fusion to immune modulation.

For successful infection and propagation viruses must overcome many obstacles such as the immune system and entry into their host cells. HIV utilizes its trimeric envelope protein gp160, specifically the gp41 subunit, to enter its host cell. During this process, a gp41-central coiled coil is formed from three N- and three C-terminal heptad repeats, termed the six-helix bundle (SHB), which drives membrane fusion. Recently, T-cell suppression has been reported as an additional function for several regions of gp41 by interfering with the T-cell receptor (TCR) signalling cascade. One of these regions encompasses the conserved pocket binding domain (PBD) that is situated in the C-terminal heptad repeat (CHR) and stabilizes SHB formation. This could indicate that the PBD plays a role in T-cell suppression in addition to its role in membrane fusion. To investigate this dual function, we used two independent cell cultures coupled with biophysical techniques. The data reveal that the PBD mediates T-cell suppression by stabilizing a TCR-binding conformation in the membrane. Moreover, we show that the clinically used HIV fusion inhibitor T-20 did not show suppressive abilities, in contrast with the potent fusion inhibitor C34. In addition, by focusing on SHB conformation after its assembly, we shed light on a mechanism by which gp41's function alternates from membrane fusion facilitation to suppression of TCR activation.

Abundance Imparts Evolutionary Constraints of Similar Magnitude on the Buried, Surface, and Disordered Regions of Proteins.

An understanding of the forces shaping protein conservation is key, both for the fundamental knowledge it represents and to allow for optimal use of evolutionary information in practical applications. Sequence conservation is typically examined at one of two levels. The first is a residue-level, where intra-protein differences are analyzed and the second is a protein-level, where inter-protein differences are studied. At a residue level, we know that solvent-accessibility is a prime determinant of conservation. By inverting this logic, we inferred that disordered regions are slightly more solvent-accessible on average than the most exposed surface residues in domains. By integrating abundance information with evolutionary data within and across proteins, we confirmed a previously reported strong surface-core association in the evolution of structured regions, but we found a comparatively weak association between disordered and structured regions. The facts that disordered and structured regions experience different structural constraints and evolve independently provide a unique setup to examine an outstanding question: why is a protein's abundance the main determinant of its sequence conservation? Indeed, any structural or biophysical property linked to the abundance-conservation relationship should increase the relative conservation of regions concerned with that property (e.g., disordered residues with mis-interactions, domain residues with misfolding). Surprisingly, however, we found the conservation of disordered and structured regions to increase in equal proportion with abundance. This observation implies that either abundance-related constraints are structure-independent, or multiple constraints apply to different regions and perfectly balance each other.

Protein Abundance Biases the Amino Acid Composition of Disordered Regions to Minimize Non-functional Interactions.

In eukaryotes, disordered regions cover up to 50% of proteomes and mediate fundamental cellular processes. In contrast to globular domains, where about half of the amino acids are buried in the protein interior, disordered regions show higher solvent accessibility, which makes them prone to engage in non-functional interactions. Such interactions are exacerbated by the law of mass action, prompting the question of how they are minimized in abundant proteins. We find that interaction propensity or "stickiness" of disordered regions negatively correlates with their cellular abundance, both in yeast and human. Strikingly, considering yeast proteins where a large fraction of the sequence is disordered, the correlation between stickiness and abundance reaches R=-0.55. Beyond this global amino-acid composition bias, we identify three rules by which amino-acid composition of disordered regions adjusts with high abundance. First, lysines are preferred over arginines, consistent with the latter amino acid being stickier than the former. Second, compensatory effects exist, whereby a sticky region can be tolerated if it is compensated by a distal non-sticky region. Third, such compensation requires a lower average stickiness at the same abundance when compared to a scenario where stickiness is homogeneous throughout the sequence. We validate these rules experimentally, employing them as different strategies to rescue an otherwise sticky protein fragment from aggregation. Our results highlight that non-functional interactions represent a significant constraint in cellular systems and reveal simple rules by which protein sequences adapt to that constraint. Data from this work are deposited in Figshare, at https://doi.org/10.6084/m9.figshare.8068937.v3.

Fast and accurate discovery of degenerate linear motifs in protein sequences.

Linear motifs mediate a wide variety of cellular functions, which makes their characterization in protein sequences crucial to understanding cellular systems. However, the short length and degenerate nature of linear motifs make their discovery a difficult problem. Here, we introduce MotifHound, an algorithm particularly suited for the discovery of small and degenerate linear motifs. MotifHound performs an exact and exhaustive enumeration of all motifs present in proteins of interest, including all of their degenerate forms, and scores the overrepresentation of each motif based on its occurrence in proteins of interest relative to a background (e.g., proteome) using the hypergeometric distribution. To assess MotifHound, we benchmarked it together with state-of-the-art algorithms. The benchmark consists of 11,880 sets of proteins from S. cerevisiae; in each set, we artificially spiked-in one motif varying in terms of three key parameters, (i) number of occurrences, (ii) length and (iii) the number of degenerate or "wildcard" positions. The benchmark enabled the evaluation of the impact of these three properties on the performance of the different algorithms. The results showed that MotifHound and SLiMFinder were the most accurate in detecting degenerate linear motifs. Interestingly, MotifHound was 15 to 20 times faster at comparable accuracy and performed best in the discovery of highly degenerate motifs. We complemented the benchmark by an analysis of proteins experimentally shown to bind the FUS1 SH3 domain from S. cerevisiae. Using the full-length protein partners as sole information, MotifHound recapitulated most experimentally determined motifs binding to the FUS1 SH3 domain. Moreover, these motifs exhibited properties typical of SH3 binding peptides, e.g., high intrinsic disorder and evolutionary conservation, despite the fact that none of these properties were used as prior information. MotifHound is available (http://michnick.bcm.umontreal.ca or http://tinyurl.com/motifhound) together with the benchmark that can be used as a reference to assess future developments in motif discovery.