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Ionotropic glutamate receptors (iGluRs) are a highly conserved family of ligand-gated ion channels present in animals, plants, and bacteria, which are best characterized for their roles in synaptic communication in vertebrate nervous systems. A variant subfamily of iGluRs, the Ionotropic Receptors (IRs), was recently identified as a new class of olfactory receptors in the fruit fly, Drosophila melanogaster, hinting at a broader function of this ion channel family in detection of environmental, as well as intercellular, chemical signals. Here, we investigate the origin and evolution of IRs by comprehensive evolutionary genomics and in situ expression analysis. In marked contrast to the insect-specific Odorant Receptor family, we show that IRs are expressed in olfactory organs across Protostomia--a major branch of the animal kingdom that encompasses arthropods, nematodes, and molluscs--indicating that they represent an ancestral protostome chemosensory receptor family. Two subfamilies of IRs are distinguished: conserved \"antennal IRs,\" which likely define the first olfactory receptor family of insects, and species-specific \"divergent IRs,\" which are expressed in peripheral and internal gustatory neurons, implicating this family in taste and food assessment. Comparative analysis of drosophilid IRs reveals the selective forces that have shaped the repertoires in flies with distinct chemosensory preferences. Examination of IR gene structure and genomic distribution suggests both non-allelic homologous recombination and retroposition contributed to the expansion of this multigene family. Together, these findings lay a foundation for functional analysis of these receptors in both neurobiological and evolutionary studies. Furthermore, this work identifies novel targets for manipulating chemosensory-driven behaviours of agricultural pests and disease vectors.

The pathogenic, tropical Leishmania flagellates belong to an early-branching eukaryotic lineage (Kinetoplastida) with several unique features. Unfortunately, they are poorly understood from a molecular biology perspective, making development of mechanistically novel and selective drugs difficult. Here, we explore three functionally critical targeting short linear motif systems as well as their receptors in depth, using a combination of structural modeling, evolutionary sequence divergence and deep learning. Secretory signal peptides, endoplasmic reticulum (ER) retention motifs (KDEL motifs), and autophagy signals (motifs interacting with ATG8 family members) are ancient and essential components of cellular life. Although expected to be conserved amongst the kinetoplastids, we observe that all three systems show a varying degree of divergence from their better studied equivalents in animals, plants, or fungi. We not only describe their behaviour, but also build models that allow the prediction of localization and potential functions for several uncharacterized Leishmania proteins. The unusually Ala/Val-rich secretory signal peptides, endoplasmic reticulum resident proteins ending in Asp-Leu-COOH and atypical ATG8-like proteins are all unique molecular features of kinetoplastid parasites. Several of their critical protein-protein interactions could serve as targets of selective antimicrobial agents against Leishmaniasis due to their systematic divergence from the host.

Multiple sequence alignments are fundamental to many sequence analysis methods. Most alignments are computed using the progressive alignment heuristic. These methods are starting to become a bottleneck in some analysis pipelines when faced with data sets of the size of many thousands of sequences. Some methods allow computation of larger data sets while sacrificing quality, and others produce high‐quality alignments, but scale badly with the number of sequences. In this paper, we describe a new program called Clustal Omega, which can align virtually any number of protein sequences quickly and that delivers accurate alignments. The accuracy of the package on smaller test cases is similar to that of the high‐quality aligners. On larger data sets, Clustal Omega outperforms other packages in terms of execution time and quality. Clustal Omega also has powerful features for adding sequences to and exploiting information in existing alignments, making use of the vast amount of precomputed information in public databases like Pfam. Multiple sequence alignments are fundamental to many sequence analysis methods. The new program Clustal Omega can align virtually any number of protein sequences quickly and has powerful features for adding sequences to existing precomputed alignments.

Structural resolution of protein interactions enables mechanistic and functional studies as well as interpretation of disease variants. However, structural data is still missing for most protein interactions because we lack computational and experimental tools at scale. This is particularly true for interactions mediated by short linear motifs occurring in disordered regions of proteins. We find that AlphaFold-Multimer predicts with high sensitivity but limited specificity structures of domain-motif interactions when using small protein fragments as input. Sensitivity decreased substantially when using long protein fragments or full length proteins. We delineated a protein fragmentation strategy particularly suited for the prediction of domain-motif interfaces and applied it to interactions between human proteins associated with neurodevelopmental disorders. This enabled the prediction of highly confident and likely disease-related novel interfaces, which we further experimentally corroborated for FBXO23-STX1B, STX1B-VAMP2, ESRRG-PSMC5, PEX3-PEX19, PEX3-PEX16, and SNRPB-GIGYF1 providing novel molecular insights for diverse biological processes. Our work highlights exciting perspectives, but also reveals clear limitations and the need for future developments to maximize the power of Alphafold-Multimer for interface predictions. Synopsis Based on thorough benchmarking of AlphaFold-Multimer a strategy for structure prediction was developed and applied to 62 protein interactions linked to neurological disease. Six novel protein interfaces were further experimentally corroborated. AlphaFold-Multimer (AF) largely fails to predict structures of interacting proteins involving short linear motifs when using full length sequences. A prediction strategy was developed based on protein fragmentation, which boosts AF sensitivity at costs of specificity. Application of this strategy to 62 protein interactions linked to neurological disease resulted in 18 correct or likely correct structural models. Six novel protein interfaces were further supported by experiments. Based on thorough benchmarking of AlphaFold-Multimer a strategy for structure prediction was developed and applied to 62 protein interactions linked to neurological disease. Six novel protein interfaces were further experimentally corroborated.

Alternative usage of exons provides genomes with plasticity to produce different transcripts from the same gene, modulating the function, localization, and life cycle of gene products. It affects most human genes. For a limited number of cases, alternative functions and tissue-specific roles are known. However, recent high-throughput sequencing studies have suggested that much alternative isoform usage across tissues is nonconserved, raising the question of the extent of its functional importance. We address this question in a genome-wide manner by analyzing the transcriptomes of five tissues for six primate species, focusing on exons that are 1:1 orthologous in all six species. Our results support a model in which differential usage of exons has two major modes: First, most of the exons show only weak differences, which are dominated by interspecies variability and may reflect neutral drift and noisy splicing. These cases dominate the genome-wide view and explain why conservation appears to be so limited. Second, however, a sizeable minority of exons show strong differences between tissues, which are mostly conserved. We identified a core set of 3,800 exons from 1,643 genes that show conservation of strongly tissue-dependent usage patterns from human at least to macaque. This set is enriched for exons encoding protein-disordered regions and untranslated regions. Our findings support the theory that isoform regulation is an important target of evolution in primates, and our method provides a powerful tool for discovering potentially functional tissue-dependent isoforms.

The modulation of actin-binding effectors that regulate the activity of this fundamental cellular protein is a common theme among bacterial pathogens. The neural Wiskott–Aldrich syndrome protein (N-WASP) is a protein that several pathogens target to hijack actin dynamics. The highly adapted intracellular bacterium Brucella has evolved a wide repertoire of virulence factors that modulate many activities of the host cell to establish successful intracellular replication niches, but, to date, no effector proteins have been implicated in the modulation of actin dynamics. We present here the identification of a virulence factor that harbors a short linear motif (SLiM) present within an amphipathic alpha helix that has been described to bind the GTPase-binding domain (GBD) of N-WASP stabilizing its autoinhibited state. We demonstrate that this protein is a Type IV secretion effector that targets N-WASP-promoting intracellular survival and niche formation.

Many aspects of cell signalling, trafficking, and targeting are governed by interactions between globular protein domains and short peptide segments. These domains often bind multiple peptides that share a common sequence pattern, or \"linear motif\" (e.g., SH3 binding to PxxP). Many domains are known, though comparatively few linear motifs have been discovered. Their short length (three to eight residues), and the fact that they often reside in disordered regions in proteins makes them difficult to detect through sequence comparison or experiment. Nevertheless, each new motif provides critical molecular details of how interaction networks are constructed, and can explain how one protein is able to bind to very different partners. Here we show that binding motifs can be detected using data from genome-scale interaction studies, and thus avoid the normally slow discovery process. Our approach based on motif over-representation in non-homologous sequences, rediscovers known motifs and predicts dozens of others. Direct binding experiments reveal that two predicted motifs are indeed protein-binding modules: a DxxDxxxD protein phosphatase 1 binding motif with a KD of 22 microM and a VxxxRxYS motif that binds Translin with a KD of 43 microM. We estimate that there are dozens or even hundreds of linear motifs yet to be discovered that will give molecular insight into protein networks and greatly illuminate cellular processes.

Much of what is known about mammalian cell regulation has been achieved with the aid of transiently transfected cells. However, overexpression can violate balanced gene dosage, affecting protein folding, complex assembly and downstream regulation. To avoid these problems, genome engineering technologies now enable the generation of stable cell lines expressing modified proteins at (almost) native levels.

Linear motifs are short modules of protein sequences that play a crucial role in mediating and regulating many protein-protein interactions. The function of linear motifs strongly depends on the context, e.g. functional instances mainly occur inside flexible regions that are accessible for interaction. Sometimes linear motifs appear as isolated islands of conservation in multiple sequence alignments. However, they also occur in larger blocks of sequence conservation, suggesting an active role for the neighbouring amino acids. The evolution of regions flanking 116 functional linear motif instances was studied. The conservation of the amino acid sequence and order/disorder tendency of those regions was related to presence/absence of the instance. For the majority of the analysed instances, the pairs of sequences conserving the linear motif were also observed to maintain a similar local structural tendency and/or to have higher local sequence conservation when compared to pairs of sequences where one is missing the linear motif. Furthermore, those instances have a higher chance to co-evolve with the neighbouring residues in comparison to the distant ones. Those findings are supported by examples where the regulation of the linear motif-mediated interaction has been shown to depend on the modifications (e.g. phosphorylation) at neighbouring positions or is thought to benefit from the binding versatility of disordered regions. The results suggest that flanking regions are relevant for linear motif-mediated interactions, both at the structural and sequence level. More interestingly, they indicate that the prediction of linear motif instances can be enriched with contextual information by performing a sequence analysis similar to the one presented here. This can facilitate the understanding of the role of these predicted instances in determining the protein function inside the broader context of the cellular network where they arise.

Ataxin-1 (Atx1), a member of the polyglutamine (polyQ) expanded protein family, is responsible for spinocerebellar ataxia type 1. Requirements for developing the disease are polyQ expansion, nuclear localization and phosphorylation of S776. Using a combination of bioinformatics, cell and structural biology approaches, we have identified a UHM ligand motif (ULM), present in proteins associated with splicing, in the C-terminus of Atx1 and shown that Atx1 interacts with and influences the function of the splicing factor U2AF65 via this motif. ULM comprises S776 of Atx1 and overlaps with a nuclear localization signal and a 14-3-3 binding motif. We demonstrate that phosphorylation of S776 provides the molecular switch which discriminates between 14-3-3 and components of the spliceosome. We also show that an S776D Atx1 mutant previously designed to mimic phosphorylation is unsuitable for this aim because of the different chemical properties of the two groups. Our results indicate that Atx1 is part of a complex network of interactions with splicing factors and suggest that development of the pathology is the consequence of a competition of aggregation with native interactions. Studies of the interactions formed by non-expanded Atx1 thus provide valuable hints for understanding both the function of the non-pathologic protein and the causes of the disease.