Systematic Discovery of Short Linear Motifs Decodes Calcineurin Phosphatase Signaling.
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ABSTRACT:
SUBMITTER: Wigington CP
PROVIDER: S-EPMC7416808 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Short linear motifs (SLiMs) form dynamic protein-protein interactions essential for signaling; however, sequence degeneracy and low binding affinities make them difficult to identify. In this study, we employed multiple, unbiased systematic approaches for SLiM discovery to elucidate the regulatory network of calcineurin (CN), the Ca2+-regulated phosphatase that recognizes LxVP and PxIxIT motifs. In vitro proteome-wide detection of CN-binding peptides, in situ SLiM-dependent proximity labeling, as well as in silico modeling of motif determinants uncovered unanticipated CN interactors, including centrosomal and nuclear pore complex (NPC) proteins – structures where Ca2+ signaling is largely uncharacterized. Here, we show that CN binds to and dephosphorylates NPC proteins (nucleoporins) in vitro and promotes the accumulation of a nuclear transport reporter in HeLa cells. Furthermore, IP/MS analyses on HeLa cells treated with DMSO or the CN inhibitor, Cyclosporin A (CsA), reveal multiple CN-dependent phosphosites on key transport nucleoporins in vivo. Together, these data suggest that CN positively regulates nuclear transport by dephosphorylating key transport nucleoporins. In summary, the CN network assembled here provides a resource to investigate Ca2+ and CN signaling and the demonstrated synergy between experimental and computational methods establishes a blueprint for examining SLiM-based networks.
2020-12-02 | PXD017868 | Pride
Project description:BackgroundThe effort to characterize intrinsically disordered regions of signaling proteins is rapidly expanding. An important class of disordered interaction modules are ubiquitous and functionally diverse elements known as short linear motifs (SLiMs).ResultsTo further examine the role of SLiMs in signal transduction, we used a previously devised bioinformatics method to predict evolutionarily conserved SLiMs within a well-characterized pathway in S. cerevisiae. Using a single cell, reporter-based flow cytometry assay in conjunction with a fluorescent reporter driven by a pathway-specific promoter, we quantitatively assessed pathway output via systematic deletions of individual motifs. We found that, when deleted, 34% (10/29) of predicted SLiMs displayed a significant decrease in pathway output, providing evidence that these motifs play a role in signal transduction. Assuming that mutations in SLiMs have quantitative effects on mechanisms of signaling, we show that perturbations of parameters in a previously published stochastic model of HOG signaling could reproduce the quantitative effects of 4 out of 7 mutations in previously unknown SLiMs.ConclusionsOur study suggests that, even in well-characterized pathways, large numbers of functional elements remain undiscovered, and that challenges remain for application of systems biology models to interpret the effects of mutations in signaling pathways.
| S-EPMC6029073 | biostudies-literature
Project description:The function of proteins is often mediated by short linear segments of their amino acid sequence, called Short Linear Motifs or SLiMs, the identification of which can provide important information about a protein function. However, the short length of the motifs and their variable degree of conservation makes their identification hard since it is difficult to correctly estimate the statistical significance of their occurrence. Consequently, only a small fraction of them have been discovered so far. We describe here an approach for the discovery of SLiMs based on their occurrence in evolutionarily unrelated proteins belonging to the same biological, signalling or metabolic pathway and give specific examples of its effectiveness in both rediscovering known motifs and in discovering novel ones. An automatic implementation of the procedure, available for download, allows significant motifs to be identified, automatically annotated with functional, evolutionary and structural information and organized in a database that can be inspected and queried. An instance of the database populated with pre-computed data on seven organisms is accessible through a publicly available server and we believe it constitutes by itself a useful resource for the life sciences (http://www.biocomputing.it/modipath).
| S-EPMC3140502 | biostudies-literature
Project description:Short linear motifs (SLiMs) are small protein sequence patterns that mediate a large number of critical protein-protein interactions, involved in processes such as complex formation, signal transduction, localisation and stabilisation. SLiMs show rapid evolutionary dynamics and are frequently the targets of molecular mimicry by pathogens. Identifying enriched sequence patterns due to convergent evolution in non-homologous proteins has proven to be a successful strategy for computational SLiM prediction. Tools of the SLiMSuite package use this strategy, using a statistical model to identify SLiM enrichment based on the evolutionary relationships, amino acid composition and predicted disorder of the input proteins. The quality of input data is critical for successful SLiM prediction. Cytoscape provides a user-friendly, interactive environment to explore interaction networks and select proteins based on common features, such as shared interaction partners. SLiMScape embeds tools of the SLiMSuite package for de novo SLiM discovery (SLiMFinder and QSLiMFinder) and identifying occurrences/enrichment of known SLiMs (SLiMProb) within this interactive framework. SLiMScape makes it easier to (1) generate high quality hypothesis-driven datasets for these tools, and (2) visualise predicted SLiM occurrences within the context of the network. To generate new predictions, users can select nodes from a protein network or provide a set of Uniprot identifiers. SLiMProb also requires additional query motif input. Jobs are then run remotely on the SLiMSuite server ( http://rest.slimsuite.unsw.edu.au) for subsequent retrieval and visualisation. SLiMScape can also be used to retrieve and visualise results from jobs run directly on the server. SLiMScape and SLiMSuite are open source and freely available via GitHub under GNU licenses.
| S-EPMC4670012 | biostudies-literature
Project description:Mitogen-activated protein kinases (MAPK) are broadly used regulators of cellular signaling. However, how these enzymes can be involved in such a broad spectrum of physiological functions is not understood. Systematic discovery of MAPK networks both experimentally and in silico has been hindered because MAPKs bind to other proteins with low affinity and mostly in less-characterized disordered regions. We used a structurally consistent model on kinase-docking motif interactions to facilitate the discovery of short functional sites in the structurally flexible and functionally under-explored part of the human proteome and applied experimental tools specifically tailored to detect low-affinity protein-protein interactions for their validation in vitro and in cell-based assays. The combined computational and experimental approach enabled the identification of many novel MAPK-docking motifs that were elusive for other large-scale protein-protein interaction screens. The analysis produced an extensive list of independently evolved linear binding motifs from a functionally diverse set of proteins. These all target, with characteristic binding specificity, an ancient protein interaction surface on evolutionarily related but physiologically clearly distinct three MAPKs (JNK, ERK, and p38). This inventory of human protein kinase binding sites was compared with that of other organisms to examine how kinase-mediated partnerships evolved over time. The analysis suggests that most human MAPK-binding motifs are surprisingly new evolutionarily inventions and newly found links highlight (previously hidden) roles of MAPKs. We propose that short MAPK-binding stretches are created in disordered protein segments through a variety of ways and they represent a major resource for ancient signaling enzymes to acquire new regulatory roles.
| S-EPMC4670726 | biostudies-literature
Project description:Short sequence motifs are ubiquitous across the three major types of biomolecules: hundreds of classes and thousands of instances of DNA regulatory elements, RNA motifs and protein short linear motifs (SLiMs) have been characterised. The increase in complexity of transcriptional, post-transcriptional and post-translational regulation in higher Eukaryotes has coincided with a significant expansion of motif use. But how did the eukaryotic cell acquire such a vast repertoire of motifs? In this review, we curate the available literature on protein motif evolution and discuss the evidence that suggests SLiMs can be acquired by mutations, insertions and deletions in disordered regions. We propose a mechanism of ex nihilo SLiM evolution - the evolution of a novel SLiM from "nothing" - adding a functional module to a previously non-functional region of protein sequence. In our model, hundreds of motif-binding domains in higher eukaryotic proteins connect simple motif specificities with useful functions to create a large functional motif space. Accessible peptides that match the specificity of these motif-binding domains are continuously created and destroyed by mutations in rapidly evolving disordered regions, creating a dynamic supply of new interactions that may have advantageous phenotypic novelty. This provides a reservoir of diversity to modify existing interaction networks. Evolutionary pressures will act on these motifs to retain beneficial instances. However, most will be lost on an evolutionary timescale as negative selection and genetic drift act on deleterious and neutral motifs respectively. In light of the parallels between the presented model and the evolution of motifs in the regulatory segments of genes and (pre-)mRNAs, we suggest our understanding of regulatory networks would benefit from the creation of a shared model describing the evolution of transcriptional, post-transcriptional and post-translational regulation.
| S-EPMC4654906 | biostudies-literature
Project description:Colorectal tumorigenesis is driven by alterations in genes and proteins responsible for cancer initiation, progression, and invasion. This multistage process is based on a dense network of protein-protein interactions (PPIs) that become dysregulated as a result of changes in various cell signaling effectors. PPIs in signaling and regulatory networks are known to be mediated by short linear motifs (SLiMs), which are conserved contiguous regions of 3-10 amino acids within interacting protein domains. SLiMs are the minimum sequences required for modulating cellular PPI networks. Thus, several in silico approaches have been developed to predict and analyze SLiM-mediated PPIs. In this review, we focus on emerging evidence supporting a crucial role for SLiMs in driver pathways that are disrupted in colorectal cancer (CRC) tumorigenesis and related PPI network alterations. As a result, SLiMs, along with short peptides, are attracting the interest of researchers to devise small molecules amenable to be used as novel anti-CRC targeted therapies. Overall, the characterization of SLiMs mediating crucial PPIs in CRC may foster the development of more specific combined pharmacological approaches.
| S-EPMC9737320 | biostudies-literature
Project description:BACKGROUND: Short linear protein motifs are attracting increasing attention as functionally independent sites, typically 3-10 amino acids in length that are enriched in disordered regions of proteins. Multiple methods have recently been proposed to discover over-represented motifs within a set of proteins based on simple regular expressions. Here, we extend these approaches to profile-based methods, which provide a richer motif representation. RESULTS: The profile motif discovery method MEME performed relatively poorly for motifs in disordered regions of proteins. However, when we applied evolutionary weighting to account for redundancy amongst homologous proteins, and masked out poorly conserved regions of disordered proteins, the performance of MEME is equivalent to that of regular expression methods. However, the two approaches returned different subsets within both a benchmark dataset, and a more realistic discovery dataset. CONCLUSIONS: Profile-based motif discovery methods complement regular expression based methods. Whilst profile-based methods are computationally more intensive, they are likely to discover motifs currently overlooked by regular expression methods.
| S-EPMC3534220 | biostudies-literature
Project description:The spindle assembly checkpoint (SAC) maintains genomic integrity by preventing progression of mitotic cell division until all chromosomes are stably attached to spindle microtubules. The SAC critically relies on the paralogues Bub1 and BubR1/Mad3, which integrate kinetochore-spindle attachment status with generation of the anaphase inhibitory complex MCC. We previously reported on the widespread occurrences of independent gene duplications of an ancestral 'MadBub' gene in eukaryotic evolution and the striking parallel subfunctionalization that lead to loss of kinase function in BubR1/Mad3-like paralogues. Here, we present an elaborate subfunctionalization analysis of the Bub1/BubR1 gene family and perform de novo sequence discovery in a comparative phylogenomics framework to trace the distribution of ancestral sequence features to extant paralogues throughout the eukaryotic tree of life. We show that known ancestral sequence features are consistently retained in the same functional paralogue: GLEBS/CMI/CDII/kinase in the Bub1-like and KEN1/KEN2/D-Box in the BubR1/Mad3-like. The recently described ABBA motif can be found in either or both paralogues. We however discovered two additional ABBA motifs that flank KEN2. This cassette of ABBA1-KEN2-ABBA2 forms a strictly conserved module in all ancestral and BubR1/Mad3-like proteins, suggestive of a specific and crucial SAC function. Indeed, deletion of the ABBA motifs in human BUBR1 abrogates the SAC and affects APC/C-Cdc20 interactions. Our detailed comparative genomics analyses thus enabled discovery of a conserved cassette of motifs essential for the SAC and shows how this approach can be used to uncover hitherto unrecognized functional protein features.
| S-EPMC5204127 | biostudies-literature
Project description:Short linear motifs (SLiMs) play an important role in protein-protein interactions. However, SLiM patterns are intrinsically permissive and result into many matches that occur just by chance, specially when targeting large datasets. To prioritize these matches as candidates for functional testing, we developed Wregex (Weighted regular expression), which uses a position-specific scoring matrix (PSSM) to order a list of regular expression matches according to a PSSM-derived score. Here we present Wregex 3.0, an improved version with new functionalities such as the support for a second auxiliary motif to help refining prediction of a primary SLiM, and post-translational modifications (PTMs) enrichment taking into account that many regulatory SLiM-mediated interactions are modulated by one or more PTMs. This version also incorporates a number of new features such as a convenient use of subproteomes, showing UniProt annotations such as disordered regions, searching for all known motifs and generating decoy databases for enrichment analysis. We provide case studies to illustrate how these new Wregex functionalities enhance prediction of short linear protein motifs. The Wregex 3.0 server is freely accessible at https://ehubio.ehu.eus/wregex3/.
| S-EPMC11318550 | biostudies-literature