MBROLE3: improved functional enrichment of chemical compounds for metabolomics data analysis.

MBROLE (Metabolites Biological Role) facilitates the biological interpretation of metabolomics experiments. It performs enrichment analysis of a set of chemical compounds through statistical analysis of annotations from several databases. The original MBROLE server was released in 2011 and, since then, different groups worldwide have used it to analyze metabolomics experiments from a variety of organisms. Here we present the latest version of the system, MBROLE3, accessible at http://csbg.cnb.csic.es/mbrole3. This new version contains updated annotations from previously included databases as well as a wide variety of new functional annotations, such as additional pathway databases and Gene Ontology terms. Of special relevance is the inclusion of a new category of annotations, 'indirect annotations', extracted from the scientific literature and from curated chemical-protein associations. The latter allows to analyze enriched annotations of the proteins known to interact with the set of chemical compounds of interest. Results are provided in the form of interactive tables, formatted data to download, and graphical plots.

Predicting biological pathways of chemical compounds with a profile-inspired approach.

BACKGROUND: Assignment of chemical compounds to biological pathways is a crucial step to understand the relationship between the chemical repertory of an organism and its biology. Protein sequence profiles are very successful in capturing the main structural and functional features of a protein family, and can be used to assign new members to it based on matching of their sequences against these profiles. In this work, we extend this idea to chemical compounds, constructing a profile-inspired model for a set of related metabolites (those in the same biological pathway), based on a fragment-based vectorial representation of their chemical structures. RESULTS: We use this representation to predict the biological pathway of a chemical compound with good overall accuracy (AUC 0.74-0.90 depending on the database tested), and analyzed some factors that affect performance. The approach, which is compared with equivalent methods, can in addition detect those molecular fragments characteristic of a pathway. CONCLUSIONS: The method is available as a graphical interactive web server http://csbg.cnb.csic.es/iFragMent .

Characteristics and evolution of the ecosystem of software tools supporting research in molecular biology.

Daily work in molecular biology presently depends on a large number of computational tools. An in-depth, large-scale study of that 'ecosystem' of Web tools, its characteristics, interconnectivity, patterns of usage/citation, temporal evolution and rate of decay is crucial for understanding the forces that shape it and for informing initiatives aimed at its funding, long-term maintenance and improvement. In particular, the long-term maintenance of these tools is compromised because of their specific development model. Hundreds of published studies become irreproducible de facto, as the software tools used to conduct them become unavailable. In this study, we present a large-scale survey of >5400 publications describing Web servers within the two main bibliographic resources for disseminating new software developments in molecular biology. For all these servers, we studied their citation patterns, the subjects they address, their citation networks and the temporal evolution of these factors. We also analysed how these factors affect the availability of these servers (whether they are alive). Our results show that this ecosystem of tools is highly interconnected and adapts to the 'trendy' subjects in every moment. The servers present characteristic temporal patterns of citation/usage, and there is a worrying rate of server 'death', which is influenced by factors such as the server popularity and the institutions that hosts it. These results can inform initiatives aimed at the long-term maintenance of these resources.

Phosphorylation-Related Crosstalk Between Distant Regions of the Core Region of the Coat Protein Contributes to Virion Assembly of Plum Pox Virus.

Eukaryotic proteins are often targets of posttranslational modifications (PTMs). Capsid protein (CP) of plum pox virus (PPV), a member of genus Potyvirus, has been reported to be prone to phosphorylation in four serines at the N-terminal region. CP phosphorylation has been proposed to influence PPV infection by regulating CP accumulation in coordination with a second PTM, O-GlcNAcylation. In this study, a further proteomic characterization of PPV CP phosphorylation revealed additional phospho-targets, thus evidencing even greater complexity of the network of PTMs affecting this protein. In particular, two new phosphorylation targets, T254 and T313, at protein distal core, appear to be highly relevant for infection. Although abolishing phosphorylation at these positions does not have a severe effect on infectivity or viral accumulation, phospho-mimicking at either of these targets disrupts cell-to-cell movement. Strand-specific reverse transcription-quantitative PCR analysis and fractionation by centrifugation in a continuous sucrose gradient enabled us to conclude that such a deleterious effect is not related to failures in replication but is a consequence of inaccurate virion assembly. The analysis of spontaneous compensatory mutations at the CP core identified in a multiple phospho-mimicking mutant disclosed a functional dialogue between distant phospho-targets, which was further supported by an in silico PPV virion model, built on the watermelon mosaic virus atomic structure. Therefore, whereas joint and opposite action of O-GlcNAcylation and phosphorylation at the N-terminal disordered protrusion of CP appears to regulate protein stability, we propose that phosphorylations at the core region control assembly and disassembly of viral particles.

Bacterial Feature Finder (BaFF)-a system for extracting features overrepresented in sets of prokaryotic organisms.

MOTIVATION: The results of some experimental and computational techniques are given in terms of large sets of organisms, especially prokaryotic. While their distinctive features can provide useful data regarding specific phenomenon, there are no automated tools for extracting them. RESULTS: We present here the Bacterial Feature Finder web server, a tool to automatically interrogate sets of prokaryotic organisms provided by the user to evaluate their specific biological features. At the core of the system is a searchable database of qualitative and quantitative features compiled for more than 23 000 prokaryotic organisms. Both the input set of organisms and the background set used to calculate the enriched features can be directly provided by the user, or they can be obtained by searching the database. The results are presented via an interactive graphical interface, with links to external resources. AVAILABILITY AND IMPLEMENTATION: The web server is freely available at http://csbg.cnb.csic.es/BaFF. It has been tested in the main web browsers and does not require any especial plug-ins or additional software. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Complex genetic and epigenetic regulation deviates gene expression from a unifying global transcriptional program.

Environmental or genetic perturbations lead to gene expression changes. While most analyses of these changes emphasize the presence of qualitative differences on just a few genes, we now know that changes are widespread. This large-scale variation has been linked to the exclusive influence of a global transcriptional program determined by the new physiological state of the cell. However, given the sophistication of eukaryotic regulation, we expect to have a complex architecture of specific control affecting this program. Here, we examine this architecture. Using data of Saccharomyces cerevisiae expression in different nutrient conditions, we first propose a five-sector genome partition, which integrates earlier models of resource allocation, as a framework to examine the deviations from the global control. In this scheme, we recognize invariant genes, whose regulation is dominated by physiology, specific genes, which substantially depart from it, and two additional classes that contain the frequently assumed growth-dependent genes. Whereas the invariant class shows a considerable absence of specific regulation, the rest is enriched by regulation at the level of transcription factors (TFs) and epigenetic modulators. We nevertheless find markedly different strategies in how these classes deviate. On the one hand, there are TFs that act in a unique way between partition constituents, and on the other, the action of chromatin modifiers is significantly diverse. The balance between regulatory strategies ultimately modulates the action of the general transcription machinery and therefore limits the possibility of establishing a unifying program of expression change at a genomic scale.

Practical analysis of specificity-determining residues in protein families.

Determining the residues that are important for the molecular activity of a protein is a topic of broad interest in biomedicine and biotechnology. This knowledge can help understanding the protein's molecular mechanism as well as to fine-tune its natural function eventually with biotechnological or therapeutic implications. Some of the protein residues are essential for the function common to all members of a family of proteins, while others explain the particular specificities of certain subfamilies (like binding on different substrates or cofactors and distinct binding affinities). Owing to the difficulty in experimentally determining them, a number of computational methods were developed to detect these functional residues, generally known as 'specificity-determining positions' (or SDPs), from a collection of homologous protein sequences. These methods are mature enough for being routinely used by molecular biologists in directing experiments aimed at getting insight into the functional specificity of a family of proteins and eventually modifying it. In this review, we summarize some of the recent discoveries achieved through SDP computational identification in a number of relevant protein families, as well as the main approaches and software tools available to perform this type of analysis.

MBROLE 2.0-functional enrichment of chemical compounds.

Metabolites Biological Role (MBROLE) is a server that performs functional enrichment analysis of a list of chemical compounds derived from a metabolomics experiment, which allows this list to be interpreted in biological terms. Since its release in 2011, MBROLE has been used by different groups worldwide to analyse metabolomics experiments from a variety of organisms. Here we present the latest version of the system, MBROLE2, accessible at http://csbg.cnb.csic.es/mbrole2 MBROLE2 has been supplemented with 10 databases not available in the previous version, which allow analysis over a larger, richer set of vocabularies including metabolite-protein and drug-protein interactions. This new version performs automatic conversion of compound identifiers from different databases, thus simplifying usage. In addition, the user interface has been redesigned to generate an interactive, more intuitive representation of the results.

Factors affecting interactome-based prediction of human genes associated with clinical signs.

BACKGROUND: Clinical signs are a fundamental aspect of human pathologies. While disease diagnosis is problematic or impossible in many cases, signs are easier to perceive and categorize. Clinical signs are increasingly used, together with molecular networks, to prioritize detected variants in clinical genomics pipelines, even if the patient is still undiagnosed. Here we analyze the ability of these network-based methods to predict genes that underlie clinical signs from the human interactome. RESULTS: Our analysis reveals that these approaches can locate genes associated with clinical signs with variable performance that depends on the sign and associated disease. We analyzed several clinical and biological factors that explain these variable results, including number of genes involved (mono- vs. oligogenic diseases), mode of inheritance, type of clinical sign and gene product function. CONCLUSIONS: Our results indicate that the characteristics of the clinical signs and their related diseases should be considered for interpreting the results of network-prediction methods, such as those aimed at discovering disease-related genes and variants. These results are important due the increasing use of clinical signs as an alternative to diseases for studying the molecular basis of human pathologies.

Characterization of clinical signs in the human interactome.

MOTIVATION: Many diseases are related by shared associated molecules and pathways, exhibiting comorbidities and common phenotypes, an indication of the continuous nature of the human pathological landscape. Although it is continuous, this landscape is always partitioned into discrete diseases when studied at the molecular level. Clinical signs are also important phenotypic descriptors that can reveal the molecular mechanisms that underlie pathological states, but have seldom been the subject of systemic research. Here, we quantify the modular nature of the clinical signs associated with genetic diseases in the human interactome. RESULTS: We found that clinical signs are reflected as modules at the molecular network level, to at least to the same extent as diseases. They can thus serve as a valid complementary partition of the human pathological landscape, with implications for etiology research, diagnosis and treatment. CONTACT: monica.chagoyen@cnb.csic.es SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Strigolactone promotes degradation of DWARF14, an α/ß hydrolase essential for strigolactone signaling in Arabidopsis.

Strigolactones (SLs) are phytohormones that play a central role in regulating shoot branching. SL perception and signaling involves the F-box protein MAX2 and the hydrolase DWARF14 (D14), proposed to act as an SL receptor. We used strong loss-of-function alleles of the Arabidopsis thaliana D14 gene to characterize D14 function from early axillary bud development through to lateral shoot outgrowth and demonstrated a role of this gene in the control of flowering time. Our data show that D14 distribution in vivo overlaps with that reported for MAX2 at both the tissue and subcellular levels, allowing physical interactions between these proteins. Our grafting studies indicate that neither D14 mRNA nor the protein move over a long range upwards in the plant. Like MAX2, D14 is required locally in the aerial part of the plant to suppress shoot branching. We also identified a mechanism of SL-induced, MAX2-dependent proteasome-mediated degradation of D14. This negative feedback loop would cause a substantial drop in SL perception, which would effectively limit SL signaling duration and intensity.

Rare disease relations through common genes and protein interactions.

ODCs (Orphan Disease Connections), available at http://csbg.cnb.csic.es/odcs, is a novel resource to explore potential molecular relations between rare diseases. These molecular relations have been established through the integration of disease susceptibility genes and human protein-protein interactions. The database currently contains 54,941 relations between 3032 diseases.

Functional signature for the recognition of specific target mRNAs by human Staufen1 protein.

Cellular messenger RNAs (mRNAs) are associated to proteins in the form of ribonucleoprotein particles. The double-stranded RNA-binding (DRB) proteins play important roles in mRNA synthesis, modification, activity and decay. Staufen is a DRB protein involved in the localized translation of specific mRNAs during Drosophila early development. The human Staufen1 (hStau1) forms RNA granules that contain translation regulation proteins as well as cytoskeleton and motor proteins to allow the movement of the granule on microtubules, but the mechanisms of hStau1-RNA recognition are still unclear. Here we used a combination of affinity chromatography, RNAse-protection, deep-sequencing and bioinformatic analyses to identify mRNAs differentially associated to hStau1 or a mutant protein unable to bind RNA and, in this way, defined a collection of mRNAs specifically associated to wt hStau1. A common sequence signature consisting of two opposite-polarity Alu motifs was present in the hStau1-associated mRNAs and was shown to be sufficient for binding to hStau1 and hStau1-dependent stimulation of protein expression. Our results unravel how hStau1 identifies a wide spectrum of cellular target mRNAs to control their localization, expression and fate.

Tools for the functional interpretation of metabolomic experiments.

The so-called 'omics' approaches used in modern biology aim at massively characterizing the molecular repertories of living systems at different levels. Metabolomics is one of the last additions to the 'omics' family and it deals with the characterization of the set of metabolites in a given biological system. As metabolomic techniques become more massive and allow characterizing larger sets of metabolites, automatic methods for analyzing these sets in order to obtain meaningful biological information are required. Only recently the first tools specifically designed for this task in metabolomics appeared. They are based on approaches previously used in transcriptomics and other 'omics', such as annotation enrichment analysis. These, together with generic tools for metabolic analysis and visualization not specifically designed for metabolomics will for sure be in the toolbox of the researches doing metabolomic experiments in the near future.

Structural characterization of the bacteriophage T7 tail machinery.

Most bacterial viruses need a specialized machinery, called "tail," to inject their genomes inside the bacterial cytoplasm without disrupting the cellular integrity. Bacteriophage T7 is a well characterized member of the Podoviridae family infecting Escherichia coli, and it has a short noncontractile tail that assembles sequentially on the viral head after DNA packaging. The T7 tail is a complex of around 2.7 MDa composed of at least four proteins as follows: the connector (gene product 8, gp8), the tail tubular proteins gp11 and gp12, and the fibers (gp17). Using cryo-electron microscopy and single particle image reconstruction techniques, we have determined the precise topology of the tail proteins by comparing the structure of the T7 tail extracted from viruses and a complex formed by recombinant gp8, gp11, and gp12 proteins. Furthermore, the order of assembly of the structural components within the complex was deduced from interaction assays with cloned and purified tail proteins. The existence of common folds among similar tail proteins allowed us to obtain pseudo-atomic threaded models of gp8 (connector) and gp11 (gatekeeper) proteins, which were docked into the corresponding cryo-EM volumes of the tail complex. This pseudo-atomic model of the connector-gatekeeper interaction revealed the existence of a common molecular architecture among viruses belonging to the three tailed bacteriophage families, strongly suggesting that a common molecular mechanism has been favored during evolution to coordinate the transition between DNA packaging and tail assembly.

Molecular determinants of the ATP hydrolysis asymmetry of the CCT chaperonin complex.

The eukaryotic cytosolic chaperonin CCT is a molecular machine involved in assisting the folding of proteins involved in important cellular processes. Like other chaperonins, CCT is formed by a double-ring structure but, unlike all of them, each ring is composed of eight different, albeit homologous subunits. This complexity has probably to do with the specificity in substrate interaction and with the mechanism of protein folding that takes place during the chaperonin functional cycle, but its detailed molecular basis remains unknown. We have analyzed the known proteomes in search of residues that are differentially conserved in the eight subunits, as predictors of functional specificity (specificity-determining positions; SDPs). We have found that most of these SDPs are located near the ATP binding site, and that they define four CCT clusters, corresponding to subunits CCT3, CCT6, CCT8 and CCT1/2/4/5/7. Our results point to a spatial organisation of the CCT subunits in two opposite areas of the ring and provide a molecular explanation for the previously described asymmetry in the hydrolysis of ATP.

CoMentG: comprehensive retrieval of generic relationships between biomedical concepts from the scientific literature.

The CoMentG resource contains millions of relationships between terms of biomedical interest obtained from the scientific literature. At the core of the system is a methodology for detecting significant co-mentions of concepts in the entire PubMed corpus. That method was applied to nine sets of terms covering the most important classes of biomedical concepts: diseases, symptoms/clinical signs, molecular functions, biological processes, cellular compartments, anatomic parts, cell types, bacteria and chemical compounds. We obtained more than 7 million relationships between more than 74 000 terms, and many types of relationships were not available in any other resource. As the terms were obtained from widely used resources and ontologies, the relationships are given using the standard identifiers provided by them and hence can be linked to other data. A web interface allows users to browse these associations, searching for relationships for a set of terms of interests provided as input, such as between a disease and their associated symptoms, underlying molecular processes or affected tissues. The results are presented in an interactive interface where the user can explore the reported relationships in different ways and follow links to other resources. Database URL: https://csbg.cnb.csic.es/CoMentG/.

PMIDigest: Interactive Review of Large Collections of PubMed Entries to Distill Relevant Information.

Scientific knowledge is being accumulated in the biomedical literature at an unprecedented pace. The most widely used database with biomedicine-related article abstracts, PubMed, currently contains more than 36 million entries. Users performing searches in this database for a subject of interest face thousands of entries (articles) that are difficult to process manually. In this work, we present an interactive tool for automatically digesting large sets of PubMed articles: PMIDigest (PubMed IDs digester). The system allows for classification/sorting of articles according to different criteria, including the type of article and different citation-related figures. It also calculates the distribution of MeSH (medical subject headings) terms for categories of interest, providing in a picture of the themes addressed in the set. These MeSH terms are highlighted in the article abstracts in different colors depending on the category. An interactive representation of the interarticle citation network is also presented in order to easily locate article "clusters" related to particular subjects, as well as their corresponding "hub" articles. In addition to PubMed articles, the system can also process a set of Scopus or Web of Science entries. In summary, with this system, the user can have a "bird's eye view" of a large set of articles and their main thematic tendencies and obtain additional information not evident in a plain list of abstracts.

Each Cellular Compartment Has a Characteristic Protein Reactive Cysteine Ratio Determining Its Sensitivity to Oxidation.

Signaling and detoxification of Reactive Oxygen Species (ROS) are important patho-physiologcal processes. Despite this, we lack comprehensive information on individual cells and cellular structures and functions affected by ROS, which is essential to build quantitative models of the effects of ROS. The thiol groups from cysteines (Cys) in proteins play a major role in redox defense, signaling, and protein function. In this study, we show that the proteins in each subcellular compartment contain a characteristic Cys amount. Using a fluorescent assay for -SH in thiolate form and amino groups in proteins, we show that the thiolate content correlates with ROS sensitivity and signaling properties of each compartment. The highest absolute thiolate concentration was found in the nucleolus, followed by the nucleoplasm and cytoplasm whereas protein thiolate groups per protein showed an inverse pattern. In the nucleoplasm, protein reactive thiols concentrated in SC35 speckles, SMN, and the IBODY that accumulated oxidized RNA. Our findings have important functional consequences, and explain differential sensitivity to ROS.

MBRole: enrichment analysis of metabolomic data.

UNLABELLED: While many tools exist for performing enrichment analysis of transcriptomic and proteomic data in order to interpret them in biological terms, almost no equivalent tools exist for metabolomic data. We present Metabolite Biological Role (MBRole), a web server for carrying out over-representation analysis of biological and chemical annotations in arbitrary sets of metabolites (small chemical compounds) coming from metabolomic data of any organism or sample. AVAILABILITY AND IMPLEMENTATION: The web server is freely available at http://csbg.cnb.csic.es/mbrole. It was tested in the main web browsers.