K29-linked free polyubiquitin chains affect ribosome biogenesis and direct ribosomal proteins to the intranuclear quality control compartment.

Ribosome assembly requires precise coordination between the production and assembly of ribosomal components. Mutations in ribosomal proteins that inhibit the assembly process or ribosome function are often associated with ribosomopathies, some of which are linked to defects in proteostasis. In this study, we examine the interplay between several yeast proteostasis enzymes, including deubiquitylases (DUBs) Ubp2 and Ubp14, and E3 ligases Ufd4 and Hul5, and we explore their roles in the regulation of the cellular levels of K29-linked unanchored polyubiquitin (polyUb) chains. Accumulating K29-linked unanchored polyUb chains associate with maturing ribosomes to disrupt their assembly, activate the ribosome assembly stress response (RASTR), and lead to the sequestration of ribosomal proteins at the intranuclear quality control compartment (INQ). These findings reveal the physiological relevance of INQ and provide insights into mechanisms of cellular toxicity associated with ribosomopathies.

A reference map of the human binary protein interactome.

Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships1,2. Here we present a human 'all-by-all' reference interactome map of human binary protein interactions, or 'HuRI'. With approximately 53,000 protein-protein interactions, HuRI has approximately four times as many such interactions as there are high-quality curated interactions from small-scale studies. The integration of HuRI with genome3, transcriptome4 and proteome5 data enables cellular function to be studied within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying the specific subcellular roles of protein-protein interactions. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases. HuRI is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes.

QATS: an ImageJ plugin for the quantification of toroidal nuclei in biological images.

MOTIVATION: The toroidal nucleus is a novel chromosomal instability (CIN) biomarker which complements the micronucleus. Understanding the specific biological stresses leading to the formation of each CIN-associated phenotype requires the evaluation of large panels of biological images collected from different genetic backgrounds and environmental conditions. However, the quantification of toroidal nuclei is currently a manual process which is unviable on a large scale. RESULTS: Here, we present QATS (QuAntification of Toroidal nuclei in biological imageS), a tool that automates the identification of toroidal nuclei, minimizing false positives while highly agreeing with the manual quantifications. Additionally, QATS identifies micronuclei for a convenient comparison of both CIN biomarkers. QATS is an open-source ImageJ plugin with a user-friendly interface that enables a wide scientific community to easily assess the frequency of CIN biomarkers for the determination of CIN levels in cellular models. AVAILABILITY AND IMPLEMENTATION: QATS is an ImageJ plugin freely available at http://www.toroidalnucleus.org/qats. The user manual and the images used for the evaluation of QATS are included in the website. Supplementary data are available at Bioinformatics online.

Analysing the yeast complexome-the Complex Portal rising to the challenge.

The EMBL-EBI Complex Portal is a knowledgebase of macromolecular complexes providing persistent stable identifiers. Entries are linked to literature evidence and provide details of complex membership, function, structure and complex-specific Gene Ontology annotations. Data are freely available and downloadable in HUPO-PSI community standards and missing entries can be requested for curation. In collaboration with Saccharomyces Genome Database and UniProt, the yeast complexome, a compendium of all known heteromeric assemblies from the model organism Saccharomyces cerevisiae, was curated. This expansion of knowledge and scope has led to a 50% increase in curated complexes compared to the previously published dataset, CYC2008. The yeast complexome is used as a reference resource for the analysis of complexes from large-scale experiments. Our analysis showed that genes coding for proteins in complexes tend to have more genetic interactions, are co-expressed with more genes, are more multifunctional, localize more often in the nucleus, and are more often involved in nucleic acid-related metabolic processes and processes where large machineries are the predominant functional drivers. A comparison to genetic interactions showed that about 40% of expanded co-complex pairs also have genetic interactions, suggesting strong functional links between complex members.

Natural variants suppress mutations in hundreds of essential genes.

The consequence of a mutation can be influenced by the context in which it operates. For example, loss of gene function may be tolerated in one genetic background, and lethal in another. The extent to which mutant phenotypes are malleable, the architecture of modifiers and the identities of causal genes remain largely unknown. Here, we measure the fitness effects of ~ 1,100 temperature-sensitive alleles of yeast essential genes in the context of variation from ten different natural genetic backgrounds and map the modifiers for 19 combinations. Altogether, fitness defects for 149 of the 580 tested genes (26%) could be suppressed by genetic variation in at least one yeast strain. Suppression was generally driven by gain-of-function of a single, strong modifier gene, and involved both genes encoding complex or pathway partners suppressing specific temperature-sensitive alleles, as well as general modifiers altering the effect of many alleles. The emerging frequency of suppression and range of possible mechanisms suggest that a substantial fraction of monogenic diseases could be managed by modulating other gene products.

Systematic genetics and single-cell imaging reveal widespread morphological pleiotropy and cell-to-cell variability.

Our ability to understand the genotype-to-phenotype relationship is hindered by the lack of detailed understanding of phenotypes at a single-cell level. To systematically assess cell-to-cell phenotypic variability, we combined automated yeast genetics, high-content screening and neural network-based image analysis of single cells, focussing on genes that influence the architecture of four subcellular compartments of the endocytic pathway as a model system. Our unbiased assessment of the morphology of these compartments-endocytic patch, actin patch, late endosome and vacuole-identified 17 distinct mutant phenotypes associated with ~1,600 genes (~30% of all yeast genes). Approximately half of these mutants exhibited multiple phenotypes, highlighting the extent of morphological pleiotropy. Quantitative analysis also revealed that incomplete penetrance was prevalent, with the majority of mutants exhibiting substantial variability in phenotype at the single-cell level. Our single-cell analysis enabled exploration of factors that contribute to incomplete penetrance and cellular heterogeneity, including replicative age, organelle inheritance and response to stress.

Systematic analysis of bypass suppression of essential genes.

Essential genes tend to be highly conserved across eukaryotes, but, in some cases, their critical roles can be bypassed through genetic rewiring. From a systematic analysis of 728 different essential yeast genes, we discovered that 124 (17%) were dispensable essential genes. Through whole-genome sequencing and detailed genetic analysis, we investigated the genetic interactions and genome alterations underlying bypass suppression. Dispensable essential genes often had paralogs, were enriched for genes encoding membrane-associated proteins, and were depleted for members of protein complexes. Functionally related genes frequently drove the bypass suppression interactions. These gene properties were predictive of essential gene dispensability and of specific suppressors among hundreds of genes on aneuploid chromosomes. Our findings identify yeast's core essential gene set and reveal that the properties of dispensable essential genes are conserved from yeast to human cells, correlating with human genes that display cell line-specific essentiality in the Cancer Dependency Map (DepMap) project.

Extensive rewiring and complex evolutionary dynamics in a C. elegans multiparameter transcription factor network.

Gene duplication results in two identical paralogs that diverge through mutation, leading to loss or gain of interactions with other biomolecules. Here, we comprehensively characterize such network rewiring for C. elegans transcription factors (TFs) within and across four newly delineated molecular networks. Remarkably, we find that even highly similar TFs often have different interaction degrees and partners. In addition, we find that most TF families have a member that is highly connected in multiple networks. Further, different TF families have opposing correlations between network connectivity and phylogenetic age, suggesting that they are subject to different evolutionary pressures. Finally, TFs that have similar partners in one network generally do not in another, indicating a lack of pressure to retain cross-network similarity. Our multiparameter analyses provide unique insights into the evolutionary dynamics that shaped TF networks.

Lack of almagate interference in breath test results for Helicobacter pylori diagnosis (Almatest study). / Ausencia de interferencia de almagato en los resultados de la prueba de aliento para el diagnóstico de Helicobacter pylori (estudio Almatest).

OBJECTIVE: The 13C-urea breath test (UBT) is the most widely used non-invasive diagnostic test for Helicobacter pylori. Debate continues to surround the possible interference of antacid intake on its result. This study aims to confirm the non-interference of almagate in the determination of H. pylori by UBT. PATIENTS AND METHODS: Observational, multicentre study in adult patients treated with almagate in whom a UBT (TAUKIT®) was indicated. When the UBT result was negative, use of almagate was stopped for 30 days and the UBT was repeated. When the result was positive, no further determinations were made. The primary endpoint was the percentage of patients who, having had a negative result in the first breath test, were positive in the second after having stopped taking almagate (UBT false negatives, possibly attributable to almagate). RESULTS: Of the 167 evaluable patients, 59% were female, average age was 49 and 97% had gastrointestinal symptoms. The result of the first UBT was negative in 71% of cases. Of these, in the second UBT test after stopping the almagate, the negative result was confirmed in 97.5%. Out of the total number of cases evaluated, the rate of false negatives was 1.8%. CONCLUSIONS: Taking almagate has minimal or no interference in the result of UBT for the diagnosis of H. pylori infection. It can therefore be used in the weeks prior to a UBT.

Bioactivity Profile Similarities to Expand the Repertoire of COVID-19 Drugs.

Until a vaccine becomes available, the current repertoire of drugs is our only therapeutic asset to fight the SARS-CoV-2 outbreak. Indeed, emergency clinical trials have been launched to assess the effectiveness of many marketed drugs, tackling the decrease of viral load through several mechanisms. Here, we present an online resource, based on small-molecule bioactivity signatures and natural language processing, to expand the portfolio of compounds with potential to treat COVID-19. By comparing the set of drugs reported to be potentially active against SARS-CoV-2 to a universe of 1 million bioactive molecules, we identify compounds that display analogous chemical and functional features to the current COVID-19 candidates. Searches can be filtered by level of evidence and mechanism of action, and results can be restricted to drug molecules or include the much broader space of bioactive compounds. Moreover, we allow users to contribute COVID-19 drug candidates, which are automatically incorporated to the pipeline once per day. The computational platform, as well as the source code, is available at https://sbnb.irbbarcelona.org/covid19.

Mechanisms of suppression: The wiring of genetic resilience.

Recent analysis of genome sequences has identified individuals that are healthy despite carrying severe disease-associated mutations. A possible explanation is that these individuals carry a second genomic perturbation that can compensate for the detrimental effects of the disease allele, a phenomenon referred to as suppression. In model organisms, suppression interactions are generally divided into two classes: genomic suppressors which are secondary mutations in the genome that bypass a mutant phenotype, and dosage suppression interactions in which overexpression of a suppressor gene rescues a mutant phenotype. Here, we describe the general properties of genomic and dosage suppression, with an emphasis on the budding yeast. We propose that suppression interactions between genetic variants are likely relevant for determining the penetrance of human traits. Consequently, an understanding of suppression mechanisms may guide the discovery of protective variants in healthy individuals that carry disease alleles, which could direct the rational design of new therapeutics.

A PanorOmic view of personal cancer genomes.

The massive molecular profiling of thousands of cancer patients has led to the identification of many tumor type specific driver genes. However, only a few (or none) of them are present in each individual tumor and, to enable precision oncology, we need to interpret the alterations found in a single patient. Cancer PanorOmics (http://panoromics.irbbarcelona.org) is a web-based resource to contextualize genomic variations detected in a personal cancer genome within the body of clinical and scientific evidence available for 26 tumor types, offering complementary cohort- and patient-centric views. Additionally, it explores the cellular environment of mutations by mapping them on the human interactome and providing quasi-atomic structural details, whenever available. This 'PanorOmic' molecular view of individual tumors, together with the appropriate genetic counselling and medical advice, should contribute to the identification of actionable alterations ultimately guiding the clinical decision-making process.

A framework for exhaustively mapping functional missense variants.

Although we now routinely sequence human genomes, we can confidently identify only a fraction of the sequence variants that have a functional impact. Here, we developed a deep mutational scanning framework that produces exhaustive maps for human missense variants by combining random codon mutagenesis and multiplexed functional variation assays with computational imputation and refinement. We applied this framework to four proteins corresponding to six human genes: UBE2I (encoding SUMO E2 conjugase), SUMO1 (small ubiquitin-like modifier), TPK1 (thiamin pyrophosphokinase), and CALM1/2/3 (three genes encoding the protein calmodulin). The resulting maps recapitulate known protein features and confidently identify pathogenic variation. Assays potentially amenable to deep mutational scanning are already available for 57% of human disease genes, suggesting that DMS could ultimately map functional variation for all human disease genes.

Genetic Interactions Implicating Postreplicative Repair in Okazaki Fragment Processing.

Ubiquitination of the replication clamp proliferating cell nuclear antigen (PCNA) at the conserved residue lysine (K)164 triggers postreplicative repair (PRR) to fill single-stranded gaps that result from stalled DNA polymerases. However, it has remained elusive as to whether cells engage PRR in response to replication defects that do not directly impair DNA synthesis. To experimentally address this question, we performed synthetic genetic array (SGA) analysis with a ubiquitination-deficient K164 to arginine (K164R) mutant of PCNA against a library of S. cerevisiae temperature-sensitive alleles. The SGA signature of the K164R allele showed a striking correlation with profiles of mutants deficient in various aspects of lagging strand replication, including rad27Δ and elg1Δ. Rad27 is the primary flap endonuclease that processes 5' flaps generated during lagging strand replication, whereas Elg1 has been implicated in unloading PCNA from chromatin. We observed chronic ubiquitination of PCNA at K164 in both rad27Δ and elg1Δ mutants. Notably, only rad27Δ cells exhibited a decline in cell viability upon elimination of PRR pathways, whereas elg1Δ mutants were not affected. We further provide evidence that K164 ubiquitination suppresses replication stress resulting from defective flap processing during Okazaki fragment maturation. Accordingly, ablation of PCNA ubiquitination increased S phase checkpoint activation, indicated by hyperphosphorylation of the Rad53 kinase. Furthermore, we demonstrate that alternative flap processing by overexpression of catalytically active exonuclease 1 eliminates PCNA ubiquitination. This suggests a model in which unprocessed flaps may directly participate in PRR signaling. Our findings demonstrate that PCNA ubiquitination at K164 in response to replication stress is not limited to DNA synthesis defects but extends to DNA processing during lagging strand replication.

A gene-centered C. elegans protein-DNA interaction network provides a framework for functional predictions.

Transcription factors (TFs) play a central role in controlling spatiotemporal gene expression and the response to environmental cues. A comprehensive understanding of gene regulation requires integrating physical protein-DNA interactions (PDIs) with TF regulatory activity, expression patterns, and phenotypic data. Although great progress has been made in mapping PDIs using chromatin immunoprecipitation, these studies have only characterized ~10% of TFs in any metazoan species. The nematode C. elegans has been widely used to study gene regulation due to its compact genome with short regulatory sequences. Here, we delineated the largest gene-centered metazoan PDI network to date by examining interactions between 90% of C. elegans TFs and 15% of gene promoters. We used this network as a backbone to predict TF binding sites for 77 TFs, two-thirds of which are novel, as well as integrate gene expression, protein-protein interaction, and phenotypic data to predict regulatory and biological functions for multiple genes and TFs.

pyDockSAXS: protein-protein complex structure by SAXS and computational docking.

Structural characterization of protein-protein interactions at molecular level is essential to understand biological processes and identify new therapeutic opportunities. However, atomic resolution structural techniques cannot keep pace with current advances in interactomics. Low-resolution structural techniques, such as small-angle X-ray scattering (SAXS), can be applied at larger scale, but they miss atomic details. For efficient application to protein-protein complexes, low-resolution information can be combined with theoretical methods that provide energetic description and atomic details of the interactions. Here we present the pyDockSAXS web server (http://life.bsc.es/pid/pydocksaxs) that provides an automatic pipeline for modeling the structure of a protein-protein complex from SAXS data. The method uses FTDOCK to generate rigid-body docking models that are subsequently evaluated by a combination of pyDock energy-based scoring function and their capacity to describe SAXS data. The only required input files are structural models for the interacting partners and a SAXS curve. The server automatically provides a series of structural models for the complex, sorted by the pyDockSAXS scoring function. The user can also upload a previously computed set of docking poses, which opens the possibility to filter the docking solutions by potential interface residues or symmetry restraints. The server is freely available to all users without restriction.

pyDockWEB: a web server for rigid-body protein-protein docking using electrostatics and desolvation scoring.

UNLABELLED: pyDockWEB is a web server for the rigid-body docking prediction of protein-protein complex structures using a new version of the pyDock scoring algorithm. We use here a new custom parallel FTDock implementation, with adjusted grid size for optimal FFT calculations, and a new version of pyDock, which dramatically speeds up calculations while keeping the same predictive accuracy. Given the 3D coordinates of two interacting proteins, pyDockWEB returns the best docking orientations as scored mainly by electrostatics and desolvation energy. AVAILABILITY AND IMPLEMENTATION: The server does not require registration by the user and is freely accessible for academics at http://life.bsc.es/servlet/pydock. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Almagate interference in breath test results for the diagnosis of Helicobacter pylori infection.

BACKGROUND: Infection by Helicobacter pylori is common and affects both genders at any age. The 13C-urea breath test is a widely used test for the diagnosis of this infection. However, multiple drugs used for the treatment of Helicobacter pylori infection symptoms have interactions with this breath test that generate false negative results. This observational study was to assess the potential interaction between almagate and the breath test. METHODS: Thirty subjects on almagate therapy who underwent a breath test were included. If the result was negative, almagate was withdrawn for a month and the breath test was then repeated. RESULTS: In general, 51.9 % of assessed subjects had a negative result after the first test, and 100 % of these also had a negative result after the second test. CONCLUSIONS: It was concluded that the use of almagate does not interfere in breath test results. These results provide a drug therapy option for the treatment of symptoms associated with Helicobacter pylori infection during the diagnostic process.

Meta-analysis of dispensable essential genes and their interactions with bypass suppressors.

Genes have been historically classified as essential or non-essential based on their requirement for viability. However, genomic mutations can sometimes bypass the requirement for an essential gene, challenging the binary classification of gene essentiality. Such dispensable essential genes represent a valuable model for understanding the incomplete penetrance of loss-of-function mutations often observed in natural populations. Here, we compiled data from multiple studies on essential gene dispensability in Saccharomyces cerevisiae to comprehensively characterize these genes. In analyses spanning different evolutionary timescales, dispensable essential genes exhibited distinct phylogenetic properties compared with other essential and non-essential genes. Integration of interactions with suppressor genes that can bypass the gene essentiality revealed the high functional modularity of the bypass suppression network. Furthermore, dispensable essential and bypass suppressor gene pairs reflected simultaneous changes in the mutational landscape of S. cerevisiae strains. Importantly, species in which dispensable essential genes were non-essential tended to carry bypass suppressor mutations in their genomes. Overall, our study offers a comprehensive view of dispensable essential genes and illustrates how their interactions with bypass suppressors reflect evolutionary outcomes.

Expanding the frontiers of protein-protein modeling: from docking and scoring to binding affinity predictions and other challenges.

In addition to protein-protein docking, this CAPRI edition included new challenges, like protein-water and protein-sugar interactions, or the prediction of binding affinities and ΔΔG changes upon mutation. Regarding the standard protein-protein docking cases, our approach, mostly based on the pyDock scheme, submitted correct models as predictors and as scorers for 67% and 57% of the evaluated targets, respectively. In this edition, available information on known interface residues hardly made any difference for our predictions. In one of the targets, the inclusion of available experimental small-angle X-ray scattering (SAXS) data using our pyDockSAXS approach slightly improved the predictions. In addition to the standard protein-protein docking assessment, new challenges were proposed. One of the new problems was predicting the position of the interface water molecules, for which we submitted models with 20% and 43% of the water-mediated native contacts predicted as predictors and scorers, respectively. Another new problem was the prediction of protein-carbohydrate binding, where our submitted model was very close to being acceptable. A set of targets were related to the prediction of binding affinities, in which our pyDock scheme was able to discriminate between natural and designed complexes with area under the curve = 83%. It was also proposed to estimate the effect of point mutations on binding affinity. Our approach, based on machine learning methods, showed high rates of correctly classified mutations for all cases. The overall results were highly rewarding, and show that the field is ready to move forward and face new interesting challenges in interactomics.