Jaime A Castro-Mondragon

RegulonDB version 9.0: high-level integration of gene regulation, coexpression, motif clustering and beyond

RegulonDB (http://regulondb.ccg.unam.mx) is one of the most useful and important resources on bacterial gene regulation,as it integrates the scattered scientific knowledge of the best-characterized organism, Escherichia coli K-12, in a database that organizes large amounts of data. Its electronic format enables researchers to compare their results with the legacy of previous knowledge and supports bioinformatics tools and model building. Here, we summarize our progress with RegulonDB since our last Nucleic Acids Research publication describing RegulonDB, in 2013. In addition to maintaining curation up-to-date, we report a collection of 232 interactions with small RNAs affecting 192 genes, and the complete repertoire of 189 Elementary Genetic Sensory-Response units (GENSOR units), integrating the signal, regulatory interactions, and metabolic pathways they govern. These additions represent major progress to a higher level of understanding of regulated processes. We have updated the computationally predicted transcription factors, which total 304 (184 with experimental evidence and 120 from computational predictions); we updated our position-weight matrices and have included tools for clustering them in evolutionary families. We describe our semiautomatic strategy to accelerate curation, including datasets from high-throughput experiments, a novel coexpression distance to search for ‘neighborhood’ genes to known operons and regulons, and computational developments.

JASPAR 2018: update of the open-access database of transcription factor binding profiles and its web framework

Abstract JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) and TF flexible models (TFFMs) for TFs across multiple species in six taxonomic groups. In the 2018 release of JASPAR, the CORE collection has been expanded with 322 new PFMs (60 for vertebrates and 262 for plants) and 33 PFMs were updated (24 for vertebrates, 8 for plants and 1 for insects). These new profiles represent a 30% expansion compared to the 2016 release. In addition, we have introduced 316 TFFMs (95 for vertebrates, 218 for plants and 3 for insects). This release incorporates clusters of similar PFMs in each taxon and each TF class per taxon. The JASPAR 2018 CORE vertebrate collection of PFMs was used to predict TF-binding sites in the human genome. The predictions are made available to the scientific community through a UCSC Genome Browser track data hub. Finally, this update comes with a new web framework with an interactive and responsive user-interface, along with new features. All the underlying data can be retrieved programmatically using a RESTful API and through the JASPAR 2018 R/Bioconductor package.

Genome-wide characterization of mammalian promoters with distal enhancer functions

Gene expression in mammals is precisely regulated by the combination of promoters and gene-distal regulatory regions, known as enhancers. Several studies have suggested that some promoters might have enhancer functions. However, the extent of this type of promoters and whether they actually function to regulate the expression of distal genes have remained elusive. Here, by exploiting a high-throughput enhancer reporter assay, we unravel a set of mammalian promoters displaying enhancer activity. These promoters have distinct genomic and epigenomic features and frequently interact with other gene promoters. Extensive CRISPR–Cas9 genomic manipulation demonstrated the involvement of these promoters in the cis regulation of expression of distal genes in their natural loci. Our results have important implications for the understanding of complex gene regulation in normal development and disease.

Genomic basis of symbiovar mimosae in Rhizobium etli

BackgroundSymbiosis genes (nod and nif) involved in nodulation and nitrogen fixation in legumes are plasmid-borne in Rhizobium. Rhizobial symbiotic variants (symbiovars) with distinct host specificity would depend on the type of symbiosis plasmid. In Rhizobium etli or in Rhizobium phaseoli, symbiovar phaseoli strains have the capacity to form nodules in Phaseolus vulgaris while symbiovar mimosae confers a broad host range including different mimosa trees.ResultsWe report on the genome of R. etli symbiovar mimosae strain Mim1 and its comparison to that from R. etli symbiovar phaseoli strain CFN42. Differences were found in plasmids especially in the symbiosis plasmid, not only in nod gene sequences but in nod gene content. Differences in Nod factors deduced from the presence of nod genes, in secretion systems or ACC-deaminase could help explain the distinct host specificity. Genes involved in P. vulgaris exudate uptake were not found in symbiovar mimosae but hup genes (involved in hydrogen uptake) were found. Plasmid pRetCFN42a was partially contained in Mim1 and a plasmid (pRetMim1c) was found only in Mim1. Chromids were well conserved.ConclusionsThe genomic differences between the two symbiovars, mimosae and phaseoli may explain different host specificity. With the genomic analysis presented, the term symbiovar is validated. Furthermore, our data support that the generalist symbiovar mimosae may be older than the specialist symbiovar phaseoli.

RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections

Abstract Transcription factor (TF) databases contain multitudes of binding motifs (TFBMs) from various sources, from which non-redundant collections are derived by manual curation. The advent of high-throughput methods stimulated the production of novel collections with increasing numbers of motifs. Meta-databases, built by merging these collections, contain redundant versions, because available tools are not suited to automatically identify and explore biologically relevant clusters among thousands of motifs. Motif discovery from genome-scale data sets (e.g. ChIP-seq) also produces redundant motifs, hampering the interpretation of results. We present matrix-clustering, a versatile tool that clusters similar TFBMs into multiple trees, and automatically creates non-redundant TFBM collections. A feature unique to matrix-clustering is its dynamic visualisation of aligned TFBMs, and its capability to simultaneously treat multiple collections from various sources. We demonstrate that matrix-clustering considerably simplifies the interpretation of combined results from multiple motif discovery tools, and highlights biologically relevant variations of similar motifs. We also ran a large-scale application to cluster ∼11 000 motifs from 24 entire databases, showing that matrix-clustering correctly groups motifs belonging to the same TF families, and drastically reduced motif redundancy. matrix-clustering is integrated within the RSAT suite (http://rsat.eu/), accessible through a user-friendly web interface or command-line for its integration in pipelines.

RSAT::Plants: Motif discovery within clusters of upstream sequences in plant genomes

The plant-dedicated mirror of the Regulatory Sequence Analysis Tools (RSAT, http://plants.rsat.eu ) offers specialized options for researchers dealing with plant transcriptional regulation. The website contains whole-sequenced genomes from species regularly updated from Ensembl Plants and other sources (currently 40), and supports an array of tasks frequently required for the analysis of regulatory sequences, such as retrieving upstream sequences, motif discovery, motif comparison, and pattern matching. RSAT::Plants also integrates the footprintDB collection of DNA motifs. This protocol explains step-by-step how to discover DNA motifs in regulatory regions of clusters of co-expressed genes in plants. It also explains how to empirically control the significance of the result, and how to associate the discovered motifs with putative binding factors.

RSAT 2018: regulatory sequence analysis tools 20th anniversary

Abstract RSAT (Regulatory Sequence Analysis Tools) is a suite of modular tools for the detection and the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, including from genome-wide datasets like ChIP-seq/ATAC-seq, (ii) motif scanning, (iii) motif analysis (quality assessment, comparisons and clustering), (iv) analysis of regulatory variations, (v) comparative genomics. Six public servers jointly support 10 000 genomes from all kingdoms. Six novel or refactored programs have been added since the 2015 NAR Web Software Issue, including updated programs to analyse regulatory variants (retrieve-variation-seq, variation-scan, convert-variations), along with tools to extract sequences from a list of coordinates (retrieve-seq-bed), to select motifs from motif collections (retrieve-matrix), and to extract orthologs based on Ensembl Compara (get-orthologs-compara). Three use cases illustrate the integration of new and refactored tools to the suite. This Anniversary update gives a 20-year perspective on the software suite. RSAT is well-documented and available through Web sites, SOAP/WSDL (Simple Object Access Protocol/Web Services Description Language) web services, virtual machines and stand-alone programs at http://www.rsat.eu/.

RSAT::Plants: Motif Discovery in ChIP-Seq Peaks of Plant Genomes

In this protocol, we explain how to run ab initio motif discovery in order to gather putative transcription factor binding motifs (TFBMs) from sets of genomic regions returned by ChIP-seq experiments. The protocol starts from a set of peak coordinates (genomic regions) which can be either downloaded from ChIP-seq databases, or produced by a peak-calling software tool. We provide a concise description of the successive steps to discover motifs, cluster the motifs returned by different motif discovery algorithms, and compare them with reference motif databases. The protocol is documented with detailed notes explaining the rationale underlying the choice of options. The interpretation of the results is illustrated with an example from the model plant Arabidopsis thaliana.

Proteins in the periplasmic space and outer membrane vesicles of Rhizobium etli CE3 grown in minimal medium are largely distinct and change with growth phase

Rhizobium etli CE3 grown in succinate-ammonium minimal medium (MM) excreted outer membrane vesicles (OMVs) with diameters of 40 to 100 nm. Proteins from the OMVs and the periplasmic space were isolated from 6 and 24 h cultures and identified by proteome analysis. A total of 770 proteins were identified: 73.8 and 21.3 % of these occurred only in the periplasm and OMVs, respectively, and only 4.9 % were found in both locations. The majority of proteins found in either location were present only at 6 or 24 h: in the periplasm and OMVs, only 24 and 9 % of proteins, respectively, were present at both sampling times, indicating a time-dependent differential sorting of proteins into the two compartments. The OMVs contained proteins with physiologically varied roles, including Rhizobium adhering proteins (Rap), polysaccharidases, polysaccharide export proteins, auto-aggregation and adherence proteins, glycosyl transferases, peptidoglycan binding and cross-linking enzymes, potential cell wall-modifying enzymes, porins, multidrug efflux RND family proteins, ABC transporter proteins and heat shock proteins. As expected, proteins with known periplasmic localizations (phosphatases, phosphodiesterases, pyrophosphatases) were found only in the periplasm, along with numerous proteins involved in amino acid and carbohydrate metabolism and transport. Nearly one-quarter of the proteins present in the OMVs were also found in our previous analysis of the R. etli total exproteome of MM-grown cells, indicating that these nanoparticles are an important mechanism for protein excretion in this species.