Proteome-scale characterisation of motif-based interactome rewiring by disease mutations.

Whole genome and exome sequencing are reporting on hundreds of thousands of missense mutations. Taking a pan-disease approach, we explored how mutations in intrinsically disordered regions (IDRs) break or generate protein interactions mediated by short linear motifs. We created a peptide-phage display library tiling ~57,000 peptides from the IDRs of the human proteome overlapping 12,301 single nucleotide variants associated with diverse phenotypes including cancer, metabolic diseases and neurological diseases. By screening 80 human proteins, we identified 366 mutation-modulated interactions, with half of the mutations diminishing binding, and half enhancing binding or creating novel interaction interfaces. The effects of the mutations were confirmed by affinity measurements. In cellular assays, the effects of motif-disruptive mutations were validated, including loss of a nuclear localisation signal in the cell division control protein CDC45 by a mutation associated with Meier-Gorlin syndrome. The study provides insights into how disease-associated mutations may perturb and rewire the motif-based interactome.

ELM-the Eukaryotic Linear Motif resource-2024 update.

Short Linear Motifs (SLiMs) are the smallest structural and functional components of modular eukaryotic proteins. They are also the most abundant, especially when considering post-translational modifications. As well as being found throughout the cell as part of regulatory processes, SLiMs are extensively mimicked by intracellular pathogens. At the heart of the Eukaryotic Linear Motif (ELM) Resource is a representative (not comprehensive) database. The ELM entries are created by a growing community of skilled annotators and provide an introduction to linear motif functionality for biomedical researchers. The 2024 ELM update includes 346 novel motif instances in areas ranging from innate immunity to both protein and RNA degradation systems. In total, 39 classes of newly annotated motifs have been added, and another 17 existing entries have been updated in the database. The 2024 ELM release now includes 356 motif classes incorporating 4283 individual motif instances manually curated from 4274 scientific publications and including >700 links to experimentally determined 3D structures. In a recent development, the InterPro protein module resource now also includes ELM data. ELM is available at: http://elm.eu.org.

Large-scale phage-based screening reveals extensive pan-viral mimicry of host short linear motifs.

Viruses mimic host short linear motifs (SLiMs) to hijack and deregulate cellular functions. Studies of motif-mediated interactions therefore provide insight into virus-host dependencies, and reveal targets for therapeutic intervention. Here, we describe the pan-viral discovery of 1712 SLiM-based virus-host interactions using a phage peptidome tiling the intrinsically disordered protein regions of 229 RNA viruses. We find mimicry of host SLiMs to be a ubiquitous viral strategy, reveal novel host proteins hijacked by viruses, and identify cellular pathways frequently deregulated by viral motif mimicry. Using structural and biophysical analyses, we show that viral mimicry-based interactions have similar binding strength and bound conformations as endogenous interactions. Finally, we establish polyadenylate-binding protein 1 as a potential target for broad-spectrum antiviral agent development. Our platform enables rapid discovery of mechanisms of viral interference and the identification of potential therapeutic targets which can aid in combating future epidemics and pandemics.

Proteome-scale mapping of binding sites in the unstructured regions of the human proteome.

Specific protein-protein interactions are central to all processes that underlie cell physiology. Numerous studies have together identified hundreds of thousands of human protein-protein interactions. However, many interactions remain to be discovered, and low affinity, conditional, and cell type-specific interactions are likely to be disproportionately underrepresented. Here, we describe an optimized proteomic peptide-phage display library that tiles all disordered regions of the human proteome and allows the screening of ~ 1,000,000 overlapping peptides in a single binding assay. We define guidelines for processing, filtering, and ranking the results and provide PepTools, a toolkit to annotate the identified hits. We uncovered >2,000 interaction pairs for 35 known short linear motif (SLiM)-binding domains and confirmed the quality of the produced data by complementary biophysical or cell-based assays. Finally, we show how the amino acid resolution-binding site information can be used to pinpoint functionally important disease mutations and phosphorylation events in intrinsically disordered regions of the proteome. The optimized human disorderome library paired with PepTools represents a powerful pipeline for unbiased proteome-wide discovery of SLiM-based interactions.

Systematic Discovery of Short Linear Motifs Decodes Calcineurin Phosphatase Signaling.

Short linear motifs (SLiMs) drive dynamic protein-protein interactions essential for signaling, but sequence degeneracy and low binding affinities make them difficult to identify. We harnessed unbiased systematic approaches for SLiM discovery to elucidate the regulatory network of calcineurin (CN)/PP2B, the Ca2+-activated phosphatase that recognizes LxVP and PxIxIT motifs. In vitro proteome-wide detection of CN-binding peptides, in vivo SLiM-dependent proximity labeling, and in silico modeling of motif determinants uncovered unanticipated CN interactors, including NOTCH1, which we establish as a CN substrate. Unexpectedly, CN shows SLiM-dependent proximity to centrosomal and nuclear pore complex (NPC) proteins-structures where Ca2+ signaling is largely uncharacterized. CN dephosphorylates human and yeast NPC proteins and promotes accumulation of a nuclear transport reporter, suggesting conserved NPC regulation by CN. The CN network assembled here provides a resource to investigate Ca2+ and CN signaling and demonstrates synergy between experimental and computational methods, establishing a blueprint for examining SLiM-based networks.

SIRT3 controls brown fat thermogenesis by deacetylation regulation of pathways upstream of UCP1.

OBJECTIVE: Brown adipose tissue (BAT) is important for thermoregulation in many mammals. Uncoupling protein 1 (UCP1) is the critical regulator of thermogenesis in BAT. Here we aimed to investigate the deacetylation control of BAT and to investigate a possible functional connection between UCP1 and sirtuin 3 (SIRT3), the master mitochondrial lysine deacetylase. METHODS: We carried out physiological, molecular, and proteomic analyses of BAT from wild-type and Sirt3KO mice when BAT is activated. Mice were either cold exposed for 2 days or were injected with the ß3-adrenergic agonist, CL316,243 (1 mg/kg; i.p.). Mutagenesis studies were conducted in a cellular model to assess the impact of acetylation lysine sites on UCP1 function. Cardiac punctures were collected for proteomic analysis of blood acylcarnitines. Isolated mitochondria were used for functional analysis of OXPHOS proteins. RESULTS: Our findings showed that SIRT3 absence in mice resulted in impaired BAT lipid use, whole body thermoregulation, and respiration in BAT mitochondria, without affecting UCP1 expression. Acetylome profiling of BAT mitochondria revealed that SIRT3 regulates acetylation status of many BAT mitochondrial proteins including UCP1 and crucial upstream proteins. Mutagenesis work in cells suggested that UCP1 activity was independent of direct SIRT3-regulated lysine acetylation. However, SIRT3 impacted BAT mitochondrial proteins activities of acylcarnitine metabolism and specific electron transport chain complexes, CI and CII. CONCLUSIONS: Our data highlight that SIRT3 likely controls BAT thermogenesis indirectly by targeting pathways upstream of UCP1.

PSSMSearch: a server for modeling, visualization, proteome-wide discovery and annotation of protein motif specificity determinants.

There is a pressing need for in silico tools that can aid in the identification of the complete repertoire of protein binding (SLiMs, MoRFs, miniMotifs) and modification (moiety attachment/removal, isomerization, cleavage) motifs. We have created PSSMSearch, an interactive web-based tool for rapid statistical modeling, visualization, discovery and annotation of protein motif specificity determinants to discover novel motifs in a proteome-wide manner. PSSMSearch analyses proteomes for regions with significant similarity to a motif specificity determinant model built from a set of aligned motif-containing peptides. Multiple scoring methods are available to build a position-specific scoring matrix (PSSM) describing the motif specificity determinant model. This model can then be modified by a user to add prior knowledge of specificity determinants through an interactive PSSM heatmap. PSSMSearch includes a statistical framework to calculate the significance of specificity determinant model matches against a proteome of interest. PSSMSearch also includes the SLiMSearch framework's annotation, motif functional analysis and filtering tools to highlight relevant discriminatory information. Additional tools to annotate statistically significant shared keywords and GO terms, or experimental evidence of interaction with a motif-recognizing protein have been added. Finally, PSSM-based conservation metrics have been created for taxonomic range analyses. The PSSMSearch web server is available at http://slim.ucd.ie/pssmsearch/.

SLiMSearch: a framework for proteome-wide discovery and annotation of functional modules in intrinsically disordered regions.

The extensive intrinsically disordered regions of higher eukaryotic proteomes contain vast numbers of functional interaction modules known as short linear motifs (SLiMs). Here, we present SLiMSearch, a motif discovery tool that scans a motif consensus, representing the specificity determinants of a motif-binding domain, against a proteome to discover putative novel motif instances. SLiMSearch applies several distinct and complementary approaches exploiting the common properties of SLiMs to predict novel motifs. Consensus matches are annotated with overlapping sequence annotation, including feature information describing protein modular architecture, post-translational modification, structure, sequence variation and experimental characterisation of functional regions. Discriminatory motif attributes such as conservation and accessibility are also calculated. In addition, SLiMSearch provides functional enrichment and evolutionary analysis tools. The enrichment tool analyses GO terms, keywords and interacting partner enrichment to indicate possible motif function. The evolutionary tool evaluates motif taxonomic range and the conservation of motif sequence context. Consensus matches can be filtered based on motif attributes such as accessibility and taxonomic range; or by the localisation, interacting partners or ontology annotation of the peptide-containing protein. SLiMSearch supports a range of species of experimental and therapeutic relevance and is available online at http://slim.ucd.ie/slimsearch/.

Discovery of short linear motif-mediated interactions through phage display of intrinsically disordered regions of the human proteome.

The intrinsically disordered regions of eukaryotic proteomes are enriched in short linear motifs (SLiMs), which are of crucial relevance for cellular signaling and protein regulation; many mediate interactions by providing binding sites for peptide-binding domains. The vast majority of SLiMs remain to be discovered highlighting the need for experimental methods for their large-scale identification. We present a novel proteomic peptide phage display (ProP-PD) library that displays peptides representing the disordered regions of the human proteome, allowing direct large-scale interrogation of most potential binding SLiMs in the proteome. The performance of the ProP-PD library was validated through selections against SLiM-binding bait domains with distinct folds and binding preferences. The vast majority of identified binding peptides contained sequences that matched the known SLiM-binding specificities of the bait proteins. For SHANK1 PDZ, we establish a novel consensus TxF motif for its non-C-terminal ligands. The binding peptides mostly represented novel target proteins, however, several previously validated protein-protein interactions (PPIs) were also discovered. We determined the affinities between the VHS domain of GGA1 and three identified ligands to 40-130 µm through isothermal titration calorimetry, and confirmed interactions through coimmunoprecipitation using full-length proteins. Taken together, we outline a general pipeline for the design and construction of ProP-PD libraries and the analysis of ProP-PD-derived, SLiM-based PPIs. We demonstrated the methods potential to identify low affinity motif-mediated interactions for modular domains with distinct binding preferences. The approach is a highly useful complement to the current toolbox of methods for PPI discovery.

Optimally choosing PWM motif databases and sequence scanning approaches based on ChIP-seq data.

BACKGROUND: For many years now, binding preferences of Transcription Factors have been described by so called motifs, usually mathematically defined by position weight matrices or similar models, for the purpose of predicting potential binding sites. However, despite the availability of thousands of motif models in public and commercial databases, a researcher who wants to use them is left with many competing methods of identifying potential binding sites in a genome of interest and there is little published information regarding the optimality of different choices. Thanks to the availability of large number of different motif models as well as a number of experimental datasets describing actual binding of TFs in hundreds of TF-ChIP-seq pairs, we set out to perform a comprehensive analysis of this matter. RESULTS: We focus on the task of identifying potential transcription factor binding sites in the human genome. Firstly, we provide a comprehensive comparison of the coverage and quality of models available in different databases, showing that the public databases have comparable TFs coverage and better motif performance than commercial databases. Secondly, we compare different motif scanners showing that, regardless of the database used, the tools developed by the scientific community outperform the commercial tools. Thirdly, we calculate for each motif a detection threshold optimizing the accuracy of prediction. Finally, we provide an in-depth comparison of different methods of choosing thresholds for all motifs a priori. Surprisingly, we show that selecting a common false-positive rate gives results that are the least biased by the information content of the motif and therefore most uniformly accurate. CONCLUSION: We provide a guide for researchers working with transcription factor motifs. It is supplemented with detailed results of the analysis and the benchmark datasets at http://bioputer.mimuw.edu.pl/papers/motifs/ .

Nencki Genomics Database--Ensembl funcgen enhanced with intersections, user data and genome-wide TFBS motifs.

We present the Nencki Genomics Database, which extends the functionality of Ensembl Regulatory Build (funcgen) for the three species: human, mouse and rat. The key enhancements over Ensembl funcgen include the following: (i) a user can add private data, analyze them alongside the public data and manage access rights; (ii) inside the database, we provide efficient procedures for computing intersections between regulatory features and for mapping them to the genes. To Ensembl funcgen-derived data, which include data from ENCODE, we add information on conserved non-coding (putative regulatory) sequences, and on genome-wide occurrence of transcription factor binding site motifs from the current versions of two major motif libraries, namely, Jaspar and Transfac. The intersections and mapping to the genes are pre-computed for the public data, and the result of any procedure run on the data added by the users is stored back into the database, thus incrementally increasing the body of pre-computed data. As the Ensembl funcgen schema for the rat is currently not populated, our database is the first database of regulatory features for this frequently used laboratory animal. The database is accessible without registration using the mysql client: mysql -h database.nencki-genomics.org -u public. Registration is required only to add or access private data. A WSDL webservice provides access to the database from any SOAP client, including the Taverna Workbench with a graphical user interface.