Biology subjects

Hatos, A.

Publications and source records attributed to Hatos, A..

6 recordsLinked to original sources

bioRxiv2026

ButterflyVI: enabling high-throughput variant interpretation and biomarker discovery with functional genomics

Characterizing the functional and therapeutic relevance of cancer mutations is a primary goal and a major challenge in precision oncology. Whereas predictive approaches exist, they often lack functional validation, which cannot scale to large numbers of cancer-associated variants. Here, we integrated statistical learning with experimental evidence from high-throughput functional screenings to annotate >20000 unique variants. We defined a variant as functional if it altered the effect of gene loss, and classified four possible outcomes: oncogene and tumor suppressor dependencies, mutation tolerance, and bypass-of-essentiality. Up-to-60% of variants annotated as functional were previously considered of unknown significance. Paradoxically, bypass-of-essentiality was common among loss-of-function (LoF) variants at several tumor suppressors, including VHL, ARID1A, and RBM10. In these cases, loss of the wild-type genes was deleterious, independently of the tissue of origin, but not when they already harbored recurrent LoF variants, suggesting loss of these tumor suppressors provides a context-specific advantage. Using our annotations, we discovered somatic variants that increased sensitivity to loss of therapeutically targetable genes, representing new candidate biomarkers. Among these, we validated RPL5 LoF mutations as a biomarker of response to selective MDM2 inhibitors. A dedicated web portal (butterflyvi.unil.ch) enables exploration of all variant annotations and candidate biomarkers. This study highlights the potential and need to expand large-scale functional screenings to empower variant interpretation in the clinic.

cancer biology↗

bioRxiv2024

Compositional restrictions in the flanking regions give potential specificity and strength boost to binding in short linear motifs

Short linear motif (SLiM)-mediated protein-protein interactions play important roles in several biological processes where transient binding is needed. They usually reside in intrinsically disordered regions (IDRs), which makes them accessible for interaction. Although information about the possible necessity of the flanking regions surrounding the motifs is increasingly available, it is still unclear if there are any generic amino acid attributes that need to be functionally preserved in these segments. Here, we describe the currently known ligand-binding SLiMs and their flanking regions with biologically relevant residue features and analyse them based on their simplified characteristics. Our bioinformatics analysis reveals several important properties in the widely diverse motif environment that presumably need to be preserved for proper motif function, but remained hidden so far. Our results will facilitate the understanding of the evolution of SLiMs, while also hold potential for expanding and increasing the precision of current motif prediction methods. Author summaryProtein-protein interactions between short linear motifs and their binding domains play key roles in several molecular processes. Mutations in these binding sites have been linked to severe diseases, therefore, the interest in the motif research field has been dramatically increasing. Based on the accumulated knowledge, it became evident that not only the short motif sequences themselves, but their surrounding flanking regions also play crucial roles in motif structure and function. Since most of the motifs tend to be located within highly variable disordered protein regions, searching for functionally important physico-chemical properties in their proximity could facilitate novel discoveries in this field. Here we show that the investigation of the motif flanking regions based on different amino acid attributes can provide further information on motif function. Based on our bioinformatics approach we have found so far hidden features that are generally present within certain motif categories, thus could be used as additional information in motif searching methods as well.

bioinformatics↗

bioRxiv2022

3D-Beacons: Decreasing the gap between protein sequences and structures through a federated network of protein structure data resources

While scientists can often infer the biological function of proteins from their 3-dimensional quaternary structures, the gap between the number of known protein sequences and their experimentally determined structures keeps increasing. A potential solution to this problem is presented by ever more sophisticated computational protein modelling approaches. While often powerful on their own, most methods have strengths and weaknesses. Therefore, it benefits researchers to examine models from various model providers and perform comparative analysis to identify what models can best address their specific use cases. To make data from a large array of model providers more easily accessible to the broader scientific community, we established 3D-Beacons, a collaborative initiative to create a federated network with unified data access mechanisms. The 3D-Beacons Network allows researchers to collate coordinate files and metadata for experimentally determined and theoretical protein models from state-of-the-art and specialist model providers and also from the Protein Data Bank.

bioinformatics↗

bioRxiv2022

MIADE metadata guidelines: Minimum Information About a Disorder Experiment

An unambiguous description of an experimental setup and analysis, and the subsequent biological observation is vital for accurate data interpretation and reproducible results. Consequently, experimental analyses should be described in a concise, unequivocal, and digestible manner. The aim of minimum information guidelines is to define the fundamental complement of data that can support an unambiguous conclusion on experimental observations. In this document, we present the Minimum Information About Disorder Experiments (MIADE) guidelines to define the minimal fundamental parameters required for non-experts to understand the key findings of an experiment studying intrinsically disordered proteins (IDPs) or intrinsically disordered protein 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. We give examples of the application of these guidelines in common use cases and describe the implementation of an update to the DisProt IDP database to allow MIADE-compliant annotation. 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 standardise the dissemination of the key metadata on an IDP experiment by IDP data sources.

scientific communication and education↗

bioRxiv2021

APICURON: a database to credit and acknowledge the work of biocurators

APICURON is an open and freely accessible resource that tracks and credits the work of biocurators across multiple participating knowledgebases. Biocuration is essential to extract knowledge from research data and make it available in a structured and standardized way to the scientific community. However, processing biological data - mainly from literature - requires a huge effort which is difficult to quantify and acknowledge. APICURON collects biocuration events from third party resources and aggregates this information, spotlighting biocurator contributions. APICURON promotes biocurator engagement implementing gamification concepts like badges, medals and leaderboards and at the same time provides a monitoring service for registered resources and for biocurators themselves. APICURON adopts a data model that is flexible enough to represent and track the majority of biocuration activities. Biocurators are identified through their ORCID. The definition of curation events, scoring systems and rules for assigning badges and medals are resource-specific and easily customizable. Registered resources can transfer curation activities on the fly through a secure and robust Application Programming Interface (API). Here we show how simple and effective it is to connect a resource to APICURON describing the DisProt database of intrinsically disordered proteins as a use case. We believe APICURON will provide biological knowledgebases with a service to recognize and credit the effort of their biocurators, monitor their activity and promote curators engagement. Database URL: https://apicuron.org

bioinformatics↗

bioRxiv2020

Assessing predictors for new post translational modification sites: a case study on hydroxylation

Post-translational modification (PTM) sites have become popular for predictor development. However, with the exception of phosphorylation and a handful of other examples, PTMs suffer from a limited number of available training examples and their sparsity in protein sequences. Here, proline hydroxylation is taken as an example to compare different methods and evaluate their performance on new experimentally determined sites. As a proxy for an effective experimental design, predictors require both high specificity and sensitivity. However, the self-reported performance is often not indicative of prediction quality and detection of new sites is not guaranteed. We have benchmarked seven published hydroxylation site predictors on two newly constructed independent datasets. The self-reported performance widely overestimates the real accuracy measured on independent datasets. No predictor performs better than random on new examples, indicating the refined models are not sufficiently general to detect new sites. The number of false positives is high and precision low, in particular for non-collagen proteins whose motifs are not conserved. In short, existing predictors for hydroxylation sites do not appear to generalize to new data. Caution is advised when dealing with PTM predictors in the absence of independent evaluations, in particular for unique specific sites such as those involved in signalling. Author SummaryMachine learning methods are extensively used by biologists to design and interpret experiments. Predictors which take the only sequence as input are of particular interest due to the large amount of sequence data available and self-reported performance is often very high. In this work, we evaluated post-translational modification (PTM) predictors for hydroxylation sites and found that they perform no better than random, in strong contrast to performances reported in the original publications. PTMs are chemical amino acids alterations providing the cell with conditional mechanisms to fine tune protein function, thereby regulating complex biological processes such as signalling and cell cycle. Hydroxylation sites are a good PTM test case due to the availability of a range of predictors and an abundance of newly experimentally detected modification sites. Poor performances in our results highlight the overlooked problem of predicting PTMs when best practices are not followed and training data are likely incomplete. Experimentalists should be careful when using PTM predictors blindly and more independent assessments are needed to separate the wheat from the chaff in the field.

bioinformatics↗