MLOsMetaDB, a meta-database to centralize the information on liquid-liquid phase separation proteins and membraneless organelles.

Over the past few years, there has been a focus on proteins that create separate liquid phases in the intracellular liquid environment, known as membraneless organelles (MLOs). These organelles allow for the spatiotemporal associations of macromolecules that dynamically exchange within the cellular milieu. They provide a form of compartmentalization crucial for organizing key functions in many cells. Metabolic processes and signaling pathways in both the cytoplasm and nucleus are among the functions performed by MLOs, which are facilitated by diverse combinations of proteins and nucleic acids. However, disruptions in these liquid-liquid phase separation processes (LLPS) may lead to several diseases, such as neurodegenerative disorders and cancer, among others. To foster the study of this process and MLO function, we present MLOsMetaDB (http://mlos.leloir.org.ar), a comprehensive resource of information on MLO- and LLPS-related proteins. Our database integrates and centralizes available information for every protein involved in MLOs, which is otherwise disseminated across a plethora of different databases. Our manuscript outlines the development and features of MLOsMetaDB, which provides an interactive and user-friendly environment with modern biological visualizations and easy and quick access to proteins based on LLPS role, MLO location, and organisms. In addition, it offers an advanced search for making complex queries to generate customized information. Furthermore, MLOsMetaDB provides evolutionary information by collecting the orthologs of every protein in the same database. Overall, MLOsMetaDB is a valuable resource as a starting point for researchers studying the many processes driven by LLPS proteins and membraneless organelles.

BID expression determines the apoptotic fate of cancer cells after abrogation of the spindle assembly checkpoint by AURKB or TTK inhibitors.

BACKGROUND: Drugs targeting the spindle assembly checkpoint (SAC), such as inhibitors of Aurora kinase B (AURKB) and dual specific protein kinase TTK, are in different stages of clinical development. However, cell response to SAC abrogation is poorly understood and there are no markers for patient selection. METHODS: A panel of 53 tumor cell lines of different origins was used. The effects of drugs were analyzed by MTT and flow cytometry. Copy number status was determined by FISH and Q-PCR; mRNA expression by nCounter and RT-Q-PCR and protein expression by Western blotting. CRISPR-Cas9 technology was used for gene knock-out (KO) and a doxycycline-inducible pTRIPZ vector for ectopic expression. Finally, in vivo experiments were performed by implanting cultured cells or fragments of tumors into immunodeficient mice. RESULTS: Tumor cells and patient-derived xenografts (PDXs) sensitive to AURKB and TTK inhibitors consistently showed high expression levels of BH3-interacting domain death agonist (BID), while cell lines and PDXs with low BID were uniformly resistant. Gene silencing rendered BID-overexpressing cells insensitive to SAC abrogation while ectopic BID expression in BID-low cells significantly increased sensitivity. SAC abrogation induced activation of CASP-2, leading to cleavage of CASP-3 and extensive cell death only in presence of high levels of BID. Finally, a prevalence study revealed high BID mRNA in 6% of human solid tumors. CONCLUSIONS: The fate of tumor cells after SAC abrogation is driven by an AURKB/ CASP-2 signaling mechanism, regulated by BID levels. Our results pave the way to clinically explore SAC-targeting drugs in tumors with high BID expression.

Pipeline for transferring annotations between proteins beyond globular domains.

DisProt is the primary repository of Intrinsically Disordered Proteins (IDPs). This database is manually curated and the annotations there have strong experimental support. Currently, DisProt contains a relatively small number of proteins highlighting the importance of transferring annotations regarding verified disorder state and corresponding functions to homologous proteins in other species. In such a way, providing them with highly valuable information to better understand their biological roles. While the principles and practicalities of homology transfer are well-established for globular proteins, these are largely lacking for disordered proteins. We used DisProt to evaluate the transferability of the annotation terms to orthologous proteins. For each protein, we looked for their orthologs, with the assumption that they will have a similar function. Then, for each protein and their orthologs, we made multiple sequence alignments (MSAs). Disordered sequences are fast evolving and can be hard to align, therefore, we implemented alignment quality control steps ensuring robust alignments before mapping the annotations. We have designed a pipeline to obtain good-quality MSAs and to transfer annotations from any protein to their orthologs. Applying the pipeline to DisProt proteins, from the 1731 entries with 5623 annotations, we can reach 97,555 orthologs and transfer a total of 301,190 terms by homology. We also provide a web server for consulting the results of DisProt proteins and execute the pipeline for any other protein. The server Homology Transfer IDP (HoTIDP) is accessible at http://hotidp.leloir.org.ar.

Easy Not Easy: Comparative Modeling with High-Sequence Identity Templates.

Homology modeling is the most common technique to build structural models of a target protein based on the structure of proteins with high-sequence identity and available high-resolution structures. This technique is based on the idea that protein structure shows fewer changes than sequence through evolution. While in this scenario single mutations would minimally perturb the structure, experimental evidence shows otherwise: proteins with high conformational diversity impose a limit of the paradigm of comparative modeling as the same protein sequence can adopt dissimilar three-dimensional structures. These cases present challenges for modeling; at first glance, they may seem to be easy cases, but they have a complexity that is not evident at the sequence level. In this chapter, we address the following questions: Why should we care about conformational diversity? How to consider conformational diversity when doing template-based modeling in a practical way?

MobiDB: 10 years of intrinsically disordered proteins.

The MobiDB database (URL: https://mobidb.org/) is a knowledge base of intrinsically disordered proteins. MobiDB aggregates disorder annotations derived from the literature and from experimental evidence along with predictions for all known protein sequences. MobiDB generates new knowledge and captures the functional significance of disordered regions by processing and combining complementary sources of information. Since its first release 10 years ago, the MobiDB database has evolved in order to improve the quality and coverage of protein disorder annotations and its accessibility. MobiDB has now reached its maturity in terms of data standardization and visualization. Here, we present a new release which focuses on the optimization of user experience and database content. The major advances compared to the previous version are the integration of AlphaFoldDB predictions and the re-implementation of the homology transfer pipeline, which expands manually curated annotations by two orders of magnitude. Finally, the entry page has been restyled in order to provide an overview of the available annotations along with two separate views that highlight structural disorder evidence and functions associated with different binding modes.

orsai, the Drosophila homolog of human ETFRF1, links lipid catabolism to growth control.

BACKGROUND: Lipid homeostasis is an evolutionarily conserved process that is crucial for energy production, storage and consumption. Drosophila larvae feed continuously to achieve the roughly 200-fold increase in size and accumulate sufficient reserves to provide all energy and nutrients necessary for the development of the adult fly. The mechanisms controlling this metabolic program are poorly understood. RESULTS: Herein we identified a highly conserved gene, orsai (osi), as a key player in lipid metabolism in Drosophila. Lack of osi function in the larval fat body, the regulatory hub of lipid homeostasis, reduces lipid reserves and energy output, evidenced by decreased ATP production and increased ROS levels. Metabolic defects due to reduced Orsai (Osi) in time trigger defective food-seeking behavior and lethality. Further, we demonstrate that downregulation of Lipase 3, a fat body-specific lipase involved in lipid catabolism in response to starvation, rescues the reduced lipid droplet size associated with defective orsai. Finally, we show that osi-related phenotypes are rescued through the expression of its human ortholog ETFRF1/LYRm5, known to modulate the entry of ß-oxidation products into the electron transport chain; moreover, knocking down electron transport flavoproteins EtfQ0 and walrus/ETFA rescues osi-related phenotypes, further supporting this mode of action. CONCLUSIONS: These findings suggest that Osi may act in concert with the ETF complex to coordinate lipid homeostasis in the fat body in response to stage-specific demands, supporting cellular functions that in turn result in an adaptive behavioral response.

Genome Sequencing Variations in the Octodon degus, an Unconventional Natural Model of Aging and Alzheimer's Disease.

The degu (Octodon degus) is a diurnal long-lived rodent that can spontaneously develop molecular and behavioral changes that mirror those seen in human aging. With age some degu, but not all individuals, develop cognitive decline and brain pathology like that observed in Alzheimer's disease including neuroinflammation, hyperphosphorylated tau and amyloid plaques, together with other co-morbidities associated with aging such as macular degeneration, cataracts, alterations in circadian rhythm, diabetes and atherosclerosis. Here we report the whole-genome sequencing and analysis of the degu genome, which revealed unique features and molecular adaptations consistent with aging and Alzheimer's disease. We identified single nucleotide polymorphisms in genes associated with Alzheimer's disease including a novel apolipoprotein E (Apoe) gene variant that correlated with an increase in amyloid plaques in brain and modified the in silico predicted degu APOE protein structure and functionality. The reported genome of an unconventional long-lived animal model of aging and Alzheimer's disease offers the opportunity for understanding molecular pathways involved in aging and should help advance biomedical research into treatments for Alzheimer's disease.

DisPhaseDB: An integrative database of diseases related variations in liquid-liquid phase separation proteins.

Motivation: Proteins involved in liquid-liquid phase separation (LLPS) and membraneless organelles (MLOs) are recognized to be decisive for many biological processes and also responsible for several diseases. The recent explosion of research in the area still lacks tools for the analysis and data integration among different repositories. Currently, there is not a comprehensive and dedicated database that collects all disease-related variations in combination with the protein location, biological role in the MLO, and all the metadata available for each protein and disease. Disease-related protein variants and additional features are dispersed and the user has to navigate many databases, with a different focus, formats, and often not user friendly. Results: We present DisPhaseDB, a database dedicated to disease-related variants of liquid-liquid phase separation proteins. It integrates 10 databases, contains 5,741 proteins, 1,660,059 variants, and 4,051 disease terms. It also offers intuitive navigation and an informative display. It constitutes a pivotal starting point for further analysis, encouraging the development of new computational tools.The database is freely available at http://disphasedb.leloir.org.ar.

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.

Insight into membraneless organelles and their associated proteins: Drivers, Clients and Regulators.

In recent years, attention has been devoted to proteins forming immiscible liquid phases within the liquid intracellular medium, commonly referred to as membraneless organelles (MLO). These organelles enable the spatiotemporal associations of cellular components that exchange dynamically with the cellular milieu. The dysregulation of these liquid-liquid phase separation processes (LLPS) may cause various diseases including neurodegenerative pathologies and cancer, among others. Until very recently, databases containing information on proteins forming MLOs, as well as tools and resources facilitating their analysis, were missing. This has recently changed with the publication of 4 databases that focus on different types of experiments, sets of proteins, inclusion criteria, and levels of annotation or curation. In this study we integrate and analyze the information across these databases, complement their records, and produce a consolidated set of proteins that enables the investigation of the LLPS phenomenon. To gain insight into the features that characterize different types of MLOs and the roles of their associated proteins, they were grouped into categories: High Confidence MLO associated (including Drivers and reviewed proteins), Potential Clients and Regulators, according to their annotated functions. We show that none of the databases taken alone covers the data sufficiently to enable meaningful analysis, validating our integration effort as essential for gaining better understanding of phase separation and laying the foundations for the discovery of new proteins potentially involved in this important cellular process. Lastly, we developed a server, enabling customized selections of different sets of proteins based on MLO location, database, disorder content, among other attributes (https://forti.shinyapps.io/mlos/).

Panels and models for accurate prediction of tumor mutation burden in tumor samples.

Immune checkpoint blockade (ICB) is becoming standard-of-care in many types of human malignancies, but patient selection is still imperfect. Tumor mutation burden (TMB) is being evaluated as a biomarker for ICB in clinical trials, but most of the sequencing panels used to estimate it are inadequately designed. Here, we present a bioinformatics-based method to select panels and mathematical models for accurate TMB prediction. Our method is based on tumor-specific, forward-step selection of genes, generation of panels using a linear regression algorithm, and rigorous internal and external validation comparing predicted with experimental TMB. As a result, we propose cancer-specific panels for 14 malignancies which can offer reliable, clinically relevant estimates of TMBs. Our work facilitates a better prediction of TMB that can improve the selection of patients for ICB therapy.

PED in 2021: a major update of the protein ensemble database for intrinsically disordered proteins.

The Protein Ensemble Database (PED) (https://proteinensemble.org), which holds structural ensembles of intrinsically disordered proteins (IDPs), has been significantly updated and upgraded since its last release in 2016. The new version, PED 4.0, has been completely redesigned and reimplemented with cutting-edge technology and now holds about six times more data (162 versus 24 entries and 242 versus 60 structural ensembles) and a broader representation of state of the art ensemble generation methods than the previous version. The database has a completely renewed graphical interface with an interactive feature viewer for region-based annotations, and provides a series of descriptors of the qualitative and quantitative properties of the ensembles. High quality of the data is guaranteed by a new submission process, which combines both automatic and manual evaluation steps. A team of biocurators integrate structured metadata describing the ensemble generation methodology, experimental constraints and conditions. A new search engine allows the user to build advanced queries and search all entry fields including cross-references to IDP-related resources such as DisProt, MobiDB, BMRB and SASBDB. We expect that the renewed PED will be useful for researchers interested in the atomic-level understanding of IDP function, and promote the rational, structure-based design of IDP-targeting drugs.

Chasing coevolutionary signals in intrinsically disordered proteins complexes.

Intrinsically disordered proteins/regions (IDPs/IDRs) are crucial components of the cell, they are highly abundant and participate ubiquitously in a wide range of biological functions, such as regulatory processes and cell signaling. Many of their important functions rely on protein interactions, by which they trigger or modulate different pathways. Sequence covariation, a powerful tool for protein contact prediction, has been applied successfully to predict protein structure and to identify protein-protein interactions mostly of globular proteins. IDPs/IDRs also mediate a plethora of protein-protein interactions, highlighting the importance of addressing sequence covariation-based inter-protein contact prediction of this class of proteins. Despite their importance, a systematic approach to analyze the covariation phenomena of intrinsically disordered proteins and their complexes is still missing. Here we carry out a comprehensive critical assessment of coevolution-based contact prediction in IDP/IDR complexes and detail the challenges and possible limitations that emerge from their analysis. We found that the coevolutionary signal is faint in most of the complexes of disordered proteins but positively correlates with the interface size and binding affinity between partners. In addition, we discuss the state-of-art methodology by biological interpretation of the results, formulate evaluation guidelines and suggest future directions of development to the field.

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.

The role of P-type IIA and P-type IIB Ca2+-ATPases in plant development and growth.

As sessile organisms, plants have evolved mechanisms to adapt to variable and rapidly fluctuating environmental conditions. Calcium (Ca2+) in plant cells is a versatile intracellular second messenger that is essential for stimulating short- and long-term responses to environmental stresses through changes in its concentration in the cytosol ([Ca2+]cyt). Increases in [Ca2+]cyt direct the strength and length of these stimuli. In order to terminate them, the cells must then remove the cytosolic Ca2+ against a concentration gradient, either taking it away from the cell or storing it in organelles such as the endoplasmic reticulum (ER) and/or vacuoles. Here, we review current knowledge about the biological roles of plant P-type Ca2+-ATPases as potential actors in the regulation of this cytosolic Ca2+ efflux, with a focus the IIA ER-type Ca2+-ATPases (ECAs) and the IIB autoinhibited Ca2+-ATPases (ACAs). While ECAs are analogous proteins to animal sarcoplasmic-endoplasmic reticulum Ca2+-ATPases (SERCAs), ACAs are equivalent to animal plasma membrane-type ATPases (PMCAs). We examine their expression patterns in cells exhibiting polar growth and consider their appearance during the evolution of the plant lineage. Full details of the functions and coordination of ECAs and ACAs during plant growth and development have not yet been elucidated. Our current understanding of the regulation of fluctuations in Ca2+ gradients in the cytoplasm and organelles during growth is in its infancy, but recent technological advances in Ca2+ imaging are expected to shed light on this subject.

Characterization of intellectual disability and autism comorbidity through gene panel sequencing.

Intellectual disability (ID) and autism spectrum disorder (ASD) are clinically and genetically heterogeneous diseases. Recent whole exome sequencing studies indicated that genes associated with different neurological diseases are shared across disorders and converge on common functional pathways. Using the Ion Torrent platform, we developed a low-cost next-generation sequencing gene panel that has been transferred into clinical practice, replacing single disease-gene analyses for the early diagnosis of individuals with ID/ASD. The gene panel was designed using an innovative in silico approach based on disease networks and mining data from public resources to score disease-gene associations. We analyzed 150 unrelated individuals with ID and/or ASD and a confident diagnosis has been reached in 26 cases (17%). Likely pathogenic mutations have been identified in another 15 patients, reaching a total diagnostic yield of 27%. Our data also support the pathogenic role of genes recently proposed to be involved in ASD. Although many of the identified variants need further investigation to be considered disease-causing, our results indicate the efficiency of the targeted gene panel on the identification of novel and rare variants in patients with ID and ASD.

Comutation and exclusion analysis in human tumors: A tool for cancer biology studies and for rational selection of multitargeted therapeutic approaches.

Malignant tumors originate from somatic mutations and other genomic and epigenomic alterations, which lead to loss of control of the cellular circuitry. These alterations present patterns of co-occurrence and mutual exclusivity that can influence prognosis and modify response to drugs, highlighting the need for multitargeted therapies. Studies in this area have generally focused in particular malignancies and considered whole genes instead of specific mutations, ignoring the fact that different alterations in the same gene can have widely different effects. Here, we present a comprehensive analysis of co-dependencies of individual somatic mutations in the whole spectrum of human tumors. Combining multitesting with conditional and expected mutational probabilities, we have discovered rules governing the codependencies of driver and nondriver mutations. We also uncovered pairs and networks of comutations and exclusions, some of them restricted to certain cancer types and others widespread. These pairs and networks are not only of basic but also of clinical interest, and can be of help in the selection of multitargeted antitumor therapies. In this respect, recurrent driver comutations suggest combinations of drugs that might be effective in the clinical setting, while recurrent exclusions indicate combinations unlikely to be useful.

On the dynamical incompleteness of the Protein Data Bank.

Major scientific challenges that are beyond the capability of individuals need to be addressed by multi-disciplinary and multi-institutional consortia. Examples of these endeavours include the Human Genome Project, and more recently, the Structural Genomics (SG) initiative. The SG initiative pursues the expansion of structural coverage to include at least one structural representative for each protein family to derive the remaining structures using homology modelling. However, biological function is inherently connected with protein dynamics that can be studied by knowing different structures of the same protein. This ensemble of structures provides snapshots of protein conformational diversity under native conditions. Thus, sequence redundancy in the Protein Data Bank (PDB) (i.e. crystallization of the same protein under different conditions) is therefore an essential input contributing to experimentally based studies of protein dynamics and providing insights into protein function. In this work, we show that sequence redundancy, a key concept for exploring protein dynamics, is highly biased and fundamentally incomplete in the PDB. Additionally, our results show that dynamical behaviour of proteins cannot be inferred using homologous proteins. Minor to moderate changes in sequence can produce great differences in dynamical behaviour. Nonetheless, the structural and dynamical incompleteness of the PDB is apparently unrelated concepts in SG. While the first could be reversed by promoting the extension of the structural coverage, we would like to emphasize that further focused efforts will be needed to amend the incompleteness of the PDB in terms of dynamical information content, essential to fully understand protein function.

MISTIC2: comprehensive server to study coevolution in protein families.

Correlated mutations between residue pairs in evolutionarily related proteins arise from constraints needed to maintain a functional and stable protein. Identifying these inter-related positions narrows down the search for structurally or functionally important sites. MISTIC is a server designed to assist users to calculate covariation in protein families and provide them with an interactive tool to visualize the results. Here, we present MISTIC2, an update to the previous server, that allows to calculate four covariation methods (MIp, mfDCA, plmDCA and gaussianDCA). The results visualization framework has been reworked for improved performance, compatibility and user experience. It includes a circos representation of the information contained in the alignment, an interactive covariation network, a 3D structure viewer and a sequence logo. Others components provide additional information such as residue annotations, a roc curve for assessing contact prediction, data tables and different ways of filtering the data and exporting figures. Comparison of different methods is easily done and scores combination is also possible. A newly implemented web service allows users to access MISTIC2 programmatically using an API to calculate covariation and retrieve results. MISTIC2 is available at: https://mistic2.leloir.org.ar.