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.

Studying the Association of TKS4 and CD2AP Scaffold Proteins and Their Implications in the Partial Epithelial-Mesenchymal Transition (EMT) Process.

Colon cancer is a leading cause of death worldwide. Identification of new molecular factors governing the invasiveness of colon cancer holds promise in developing screening and targeted therapeutic methods. The Tyrosine Kinase Substrate with four SH3 domains (TKS4) and the CD2-associated protein (CD2AP) have previously been linked to dynamic actin assembly related processes and cancer cell migration, although their co-instructive role during tumor formation remained unknown. Therefore, this study was designed to investigate the TKS4-CD2AP interaction and study the interdependent effect of TKS4/CD2AP on oncogenic events. We identified CD2AP as a novel TKS4 interacting partner via co-immunoprecipitation-mass spectrometry methods. The interaction was validated via Western blot (WB), immunocytochemistry (ICC) and proximity ligation assay (PLA). The binding motif of CD2AP was explored via peptide microarray. To uncover the possible cooperative effects of TKS4 and CD2AP in cell movement and in epithelial-mesenchymal transition (EMT), we performed gene silencing and overexpressing experiments. Our results showed that TKS4 and CD2AP form a scaffolding protein complex and that they can regulate migration and EMT-related pathways in HCT116 colon cancer cells. This is the first study demonstrating the TKS4-CD2AP protein-protein interaction in vitro, their co-localization in intact cells, and their potential interdependent effects on partial-EMT in colon cancer.

Minimum information guidelines for experiments structurally characterizing intrinsically disordered protein regions.

An unambiguous description of an experiment, and the subsequent biological observation, is vital for accurate data interpretation. Minimum information guidelines define the fundamental complement of data that can support an unambiguous conclusion based on experimental observations. We present the Minimum Information About Disorder Experiments (MIADE) guidelines to define the parameters required for the wider scientific community to understand the findings of an experiment studying the structural properties of intrinsically disordered regions (IDRs). MIADE guidelines provide recommendations for data producers to describe the results of their experiments at source, for curators to annotate experimental data to community resources and for database developers maintaining community resources to disseminate the data. The MIADE guidelines will improve the interpretability of experimental results for data consumers, facilitate direct data submission, simplify data curation, improve data exchange among repositories and standardize the dissemination of the key metadata on an IDR experiment by IDR data sources.

Challenges in describing the conformation and dynamics of proteins with ambiguous behavior.

Traditionally, our understanding of how proteins operate and how evolution shapes them is based on two main data sources: the overall protein fold and the protein amino acid sequence. However, a significant part of the proteome shows highly dynamic and/or structurally ambiguous behavior, which cannot be correctly represented by the traditional fixed set of static coordinates. Representing such protein behaviors remains challenging and necessarily involves a complex interpretation of conformational states, including probabilistic descriptions. Relating protein dynamics and multiple conformations to their function as well as their physiological context (e.g., post-translational modifications and subcellular localization), therefore, remains elusive for much of the proteome, with studies to investigate the effect of protein dynamics relying heavily on computational models. We here investigate the possibility of delineating three classes of protein conformational behavior: order, disorder, and ambiguity. These definitions are explored based on three different datasets, using interpretable machine learning from a set of features, from AlphaFold2 to sequence-based predictions, to understand the overlap and differences between these datasets. This forms the basis for a discussion on the current limitations in describing the behavior of dynamic and ambiguous proteins.

Charged sequence motifs increase the propensity towards liquid-liquid phase separation.

Protein phase separation is a major governing factor in multiple cellular processes, such as RNA metabolism and those involving RNA-binding proteins. Despite many key observations, the exact structural characteristics of proteins involved in the phase separation process are still not fully deciphered. In this work, we show that proteins harbouring sequence regions with specific charged residue patterns are significantly associated with liquid-liquid phase separation. In particular, regions with repetitive arrays of alternating charges show the strongest association, whereas segments with generally high charge density and single α-helices also show detectable but weaker connections.

DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation.

The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure.

dNTPpoolDB: a manually curated database of experimentally determined dNTP pools and pool changes in biological samples.

Stimulated by the growing interest in the role of dNTP pools in physiological and malignant processes, we established dNTPpoolDB, the database that offers access to quantitative data on dNTP pools from a wide range of species, experimental and developmental conditions (https://dntppool.org/). The database includes measured absolute or relative cellular levels of the four canonical building blocks of DNA and of exotic dNTPs, as well. In addition to the measured quantity, dNTPpoolDB contains ample information on sample source, dNTP quantitation methods and experimental conditions including any treatments and genetic manipulations. Functions such as the advanced search offering multiple choices from custom-built controlled vocabularies in 15 categories in parallel, the pairwise comparison of any chosen pools, and control-treatment correlations provide users with the possibility to quickly recognize and graphically analyse changes in the dNTP pools in function of a chosen parameter. Unbalanced dNTP pools, as well as the balanced accumulation or depletion of all four dNTPs result in genomic instability. Accordingly, key roles of dNTP pool homeostasis have been demonstrated in cancer progression, development, ageing and viral infections among others. dNTPpoolDB is designated to promote research in these fields and fills a longstanding gap in genome metabolism research.

The Eukaryotic Linear Motif resource: 2022 release.

Almost twenty years after its initial release, the Eukaryotic Linear Motif (ELM) resource remains an invaluable source of information for the study of motif-mediated protein-protein interactions. ELM provides a comprehensive, regularly updated and well-organised repository of manually curated, experimentally validated short linear motifs (SLiMs). An increasing number of SLiM-mediated interactions are discovered each year and keeping the resource up-to-date continues to be a great challenge. In the current update, 30 novel motif classes have been added and five existing classes have undergone major revisions. The update includes 411 new motif instances mostly focused on cell-cycle regulation, control of the actin cytoskeleton, membrane remodelling and vesicle trafficking pathways, liquid-liquid phase separation and integrin signalling. Many of the newly annotated motif-mediated interactions are targets of pathogenic motif mimicry by viral, bacterial or eukaryotic pathogens, providing invaluable insights into the molecular mechanisms underlying infectious diseases. The current ELM release includes 317 motif classes incorporating 3934 individual motif instances manually curated from 3867 scientific publications. ELM is available at: http://elm.eu.org.

Integration of Data from Liquid-Liquid Phase Separation Databases Highlights Concentration and Dosage Sensitivity of LLPS Drivers.

Liquid-liquid phase separation (LLPS) is a molecular process that leads to the formation of membraneless organelles, representing functionally specialized liquid-like cellular condensates formed by proteins and nucleic acids. Integrating the data on LLPS-associated proteins from dedicated databases revealed only modest agreement between them and yielded a high-confidence dataset of 89 human LLPS drivers. Analysis of the supporting evidence for our dataset uncovered a systematic and potentially concerning difference between protein concentrations used in a good fraction of the in vitro LLPS experiments, a key parameter that governs the phase behavior, and the proteomics-derived cellular abundance levels of the corresponding proteins. Closer scrutiny of the underlying experimental data enabled us to offer a sound rationale for this systematic difference, which draws on our current understanding of the cellular organization of the proteome and the LLPS process. In support of this rationale, we find that genes coding for our human LLPS drivers tend to be dosage-sensitive, suggesting that their cellular availability is tightly regulated to preserve their functional role in direct or indirect relation to condensate formation. Our analysis offers guideposts for increasing agreement between in vitro and in vivo studies, probing the roles of proteins in LLPS.

Computational resources for identifying and describing proteins driving liquid-liquid phase separation.

One of the most intriguing fields emerging in current molecular biology is the study of membraneless organelles formed via liquid-liquid phase separation (LLPS). These organelles perform crucial functions in cell regulation and signalling, and recent years have also brought about the understanding of the molecular mechanism of their formation. The LLPS field is continuously developing and optimizing dedicated in vitro and in vivo methods to identify and characterize these non-stoichiometric molecular condensates and the proteins able to drive or contribute to LLPS. Building on these observations, several computational tools and resources have emerged in parallel to serve as platforms for the collection, annotation and prediction of membraneless organelle-linked proteins. In this survey, we showcase recent advancements in LLPS bioinformatics, focusing on (i) available databases and ontologies that are necessary to describe the studied phenomena and the experimental results in an unambiguous way and (ii) prediction methods to assess the potential LLPS involvement of proteins. Through hands-on application of these resources on example proteins and representative datasets, we give a practical guide to show how they can be used in conjunction to provide in silico information on LLPS.

A generic approach to study the kinetics of liquid-liquid phase separation under near-native conditions.

Understanding the kinetics, thermodynamics, and molecular mechanisms of liquid-liquid phase separation (LLPS) is of paramount importance in cell biology, requiring reproducible methods for studying often severely aggregation-prone proteins. Frequently applied approaches for inducing LLPS, such as dilution of the protein from an urea-containing solution or cleavage of its fused solubility tag, often lead to very different kinetic behaviors. Here we demonstrate that at carefully selected pH values proteins such as the low-complexity domain of hnRNPA2, TDP-43, and NUP98, or the stress protein ERD14, can be kept in solution and their LLPS can then be induced by a jump to native pH. This approach represents a generic method for studying the full kinetic trajectory of LLPS under near native conditions that can be easily controlled, providing a platform for the characterization of physiologically relevant phase-separation behavior of diverse proteins.

Phase separation by ssDNA binding protein controlled via protein-protein and protein-DNA interactions.

Bacterial single-stranded (ss)DNA-binding proteins (SSB) are essential for the replication and maintenance of the genome. SSBs share a conserved ssDNA-binding domain, a less conserved intrinsically disordered linker (IDL), and a highly conserved C-terminal peptide (CTP) motif that mediates a wide array of protein-protein interactions with DNA-metabolizing proteins. Here we show that the Escherichia coli SSB protein forms liquid-liquid phase-separated condensates in cellular-like conditions through multifaceted interactions involving all structural regions of the protein. SSB, ssDNA, and SSB-interacting molecules are highly concentrated within the condensates, whereas phase separation is overall regulated by the stoichiometry of SSB and ssDNA. Together with recent results on subcellular SSB localization patterns, our results point to a conserved mechanism by which bacterial cells store a pool of SSB and SSB-interacting proteins. Dynamic phase separation enables rapid mobilization of this protein pool to protect exposed ssDNA and repair genomic loci affected by DNA damage.

A guide to regulation of the formation of biomolecular condensates.

Cellular organelles that lack a surrounding lipid bilayer, such as the nucleolus and stress granule, represent a newly recognized, general paradigm of cellular organization. The formation of such biomolecular condensates that include 'membraneless organelles' (MLOs) by liquid-liquid phase separation (LLPS) has been in the focus of a surge of recent studies. Through a combination of in vitro and in vivo approaches, thousands of potential phase-separating proteins have been identified, and it was found that different cellular MLOs share many common components. These perplexing observations raise the question of how cells regulate the timing and specificity of LLPS, and ensure that different MLOs form and disperse at the right moment and cellular location and can preserve their identity and physical separation. This guide gives an overview of basic regulatory mechanisms, which manifest through the action of intrinsic regulatory elements, alternative splicing, post-translational modifications, and a broad range of phase-separating partners. We also elaborate on the cellular integration of these different mechanisms and highlight how complex regulation can orchestrate the parallel functioning of a dozen or so different MLOs in the cell.

DisProt: intrinsic protein disorder annotation in 2020.

The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the 'dark' proteome.

ELM-the eukaryotic linear motif resource in 2020.

The eukaryotic linear motif (ELM) resource is a repository of manually curated experimentally validated short linear motifs (SLiMs). Since the initial release almost 20 years ago, ELM has become an indispensable resource for the molecular biology community for investigating functional regions in many proteins. In this update, we have added 21 novel motif classes, made major revisions to 12 motif classes and added >400 new instances mostly focused on DNA damage, the cytoskeleton, SH2-binding phosphotyrosine motifs and motif mimicry by pathogenic bacterial effector proteins. The current release of the ELM database contains 289 motif classes and 3523 individual protein motif instances manually curated from 3467 scientific publications. ELM is available at: http://elm.eu.org.

PhaSePro: the database of proteins driving liquid-liquid phase separation.

Membraneless organelles (MOs) are dynamic liquid condensates that host a variety of specific cellular processes, such as ribosome biogenesis or RNA degradation. MOs form through liquid-liquid phase separation (LLPS), a process that relies on multivalent weak interactions of the constituent proteins and other macromolecules. Since the first discoveries of certain proteins being able to drive LLPS, it emerged as a general mechanism for the effective organization of cellular space that is exploited in all kingdoms of life. While numerous experimental studies report novel cases, the computational identification of LLPS drivers is lagging behind, and many open questions remain about the sequence determinants, composition, regulation and biological relevance of the resulting condensates. Our limited ability to overcome these issues is largely due to the lack of a dedicated LLPS database. Therefore, here we introduce PhaSePro (https://phasepro.elte.hu), an openly accessible, comprehensive, manually curated database of experimentally validated LLPS driver proteins/protein regions. It not only provides a wealth of information on such systems, but improves the standardization of data by introducing novel LLPS-specific controlled vocabularies. PhaSePro can be accessed through an appealing, user-friendly interface and thus has definite potential to become the central resource in this dynamically developing field.

Disorder-to-order transition in PE-PPE proteins of Mycobacterium tuberculosis augments the pro-pathogen immune response.

A growing body of evidence supports the hypothesis that intrinsically disordered proteins often mediate host-pathogen interactions and modulate host functions for pathogen survival and virulence. Mycobacterium tuberculosis (M.tb) has evolved largely through reductive evolution, with a few exceptions such as the glycine-alanine-rich PE-PPE/PGRS protein family, which has been expanding in pathogenic mycobacteria. Here, our analyses of the M.tb proteome and secretome revealed that the PE-PGRS subfamily is enriched for disordered regions and disordered binding sites, pointing to their importance in host-pathogen interactions. As a case study, the secondary structure of PE35-PPE68 and PE32-PPE65 of the pathogenesis-related RD1 and RD8 regions was analyzed through Fourier-transform infrared spectroscopy. These disordered proteins displayed a considerable structural shift from disordered to ordered while engaged in the formation of complexes. While these proteins are immunogenic individually and enhance the pro-pathogen response, their corresponding complexes enhanced the responses manifold as displayed here by PE35 and PPE68. It is likely that M.tb exploits such disorder-order structural dynamics as a strategy to mount a pro-pathogen response and subvert host defense for productive infection. This functional gain also serves as a means to compensate genomic content loss due to reductive evolution.

An intrinsically disordered proteins community for ELIXIR.

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) are now recognised as major determinants in cellular regulation. This white paper presents a roadmap for future e-infrastructure developments in the field of IDP research within the ELIXIR framework. The goal of these developments is to drive the creation of high-quality tools and resources to support the identification, analysis and functional characterisation of IDPs. The roadmap is the result of a workshop titled "An intrinsically disordered protein user community proposal for ELIXIR" held at the University of Padua. The workshop, and further consultation with the members of the wider IDP community, identified the key priority areas for the roadmap including the development of standards for data annotation, storage and dissemination; integration of IDP data into the ELIXIR Core Data Resources; and the creation of benchmarking criteria for IDP-related software. Here, we discuss these areas of priority, how they can be implemented in cooperation with the ELIXIR platforms, and their connections to existing ELIXIR Communities and international consortia. The article provides a preliminary blueprint for an IDP Community in ELIXIR and is an appeal to identify and involve new stakeholders.

Author Correction: Exploring the Sequence-based Prediction of Folding Initiation Sites in Proteins.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.