Sequencing and description of the genome of a strain of Stenotrophomonas geniculata isolated from a patient infected with COVID-19 at Hospital Regional No.1 de Charo, Michoacán, México.

Stenotrophomonas is a bacterial genus that can be found in various environments, such as water, soil, and clinical samples. Due to their high genetic and phenotypic diversity, it is difficult to properly identify and classify all isolates. The COVID-19 pandemic caused an increase in nosocomial infections, which played a major role in the high mortality rate among patients in intensive care. This is the first report of the identification of S. geniculata as a nosocomial opportunistic pathogen isolated from a patient with COVID-19. Their genome was isolated, sequenced, and assembled, and it consists of 4,488,090 bp in 24 contigs, 4,103 coding sequences, and a G+C content of 66.58%.

Genomic Analysis Reveals the Genetic Determinants Associated With Antibiotic Resistance in the Zoonotic Pathogen Campylobacter spp. Distributed Globally.

The genus Campylobacter groups 32 Gram-negative bacteria species, several being zoonotic pathogens and a major cause of human gastroenteritis worldwide. Antibiotic resistant Campylobacter is considered by the World Health Organization as a high priority pathogen for research and development of new antibiotics. Genetic elements related to antibiotic resistance in the classical C. coli and C. jejuni species, which infect humans and livestock, have been analyzed in numerous studies, mainly focused on local geographical areas. However, the presence of these resistance determinants in other Campylobacter species, as well as in C. jejuni and C. coli strains distributed globally, remains poorly studied. In this work, we analyzed the occurrence and distribution of antibiotic resistance factors in 237 Campylobacter closed genomes available in NCBI, obtained from isolates collected worldwide, in different dates, from distinct hosts and comprising 22 Campylobacter species. Our data revealed 18 distinct genetic determinants, genes or point mutations in housekeeping genes, associated with resistance to antibiotics from aminoglycosides, ß-lactams, fluoroquinolones, lincosamides, macrolides, phenicols or tetracyclines classes, which are differentially distributed among the Campylobacter species tested, on chromosomes or plasmids. Three resistance determinants, the bla OXA-493 and bla OXA-576 genes, putatively related to ß-lactams resistance, as well as the lnu(AN2) gene, putatively related to lincosamides resistance, had not been reported in Campylobacter; thus, they represent novel determinants for antibiotic resistance in Campylobacter spp., which expands the insight on the Campylobacter resistome. Interestingly, we found that some of the genetic determinants associated with antibiotic resistance are Campylobacter species-specific; e.g., the bla OXA-493 gene and the T86V mutation in gyrA were found only in the C. lari group, whereas genes associated with aminoglycosides resistance were found only in C. jejuni and C. coli. Additional analyses revealed how are distributed the resistance and multidrug resistance Campylobacter genotypes assessed, with respect to hosts, geographical locations, and collection dates. Thus, our findings further expand the knowledge on the factors that can determine or favor the antibiotic resistance in Campylobacter species distributed globally, which can be useful to choose a suitable antibiotic treatment to control the zoonotic infections by these bacteria.

Genomic diversity of prevalent Staphylococcus epidermidis multidrug-resistant strains isolated from a Children's Hospital in México City in an eight-years survey.

Staphylococcus epidermidis is a human commensal and pathogen worldwide distributed. In this work, we surveyed for multi-resistant S. epidermidis strains in eight years at a children's health-care unit in México City. Multidrug-resistant S. epidermidis were present in all years of the study, including resistance to methicillin, beta-lactams, fluoroquinolones, and macrolides. To understand the genetic basis of antibiotic resistance and its association with virulence and gene exchange, we sequenced the genomes of 17 S. epidermidis isolates. Whole-genome nucleotide identities between all the pairs of S. epidermidis strains were about 97% to 99%. We inferred a clonal structure and eight Multilocus Sequence Types (MLSTs) in the S. epidermidis sequenced collection. The profile of virulence includes genes involved in biofilm formation and phenol-soluble modulins (PSMs). Half of the S. epidermidis analyzed lacked the ica operon for biofilm formation. Likely, they are commensal S. epidermidis strains but multi-antibiotic resistant. Uneven distribution of insertion sequences, phages, and CRISPR-Cas immunity phage systems suggest frequent horizontal gene transfer. Rates of recombination between S. epidermidis strains were more prevalent than the mutation rate and affected the whole genome. Therefore, the multidrug resistance, independently of the pathogenic traits, might explain the persistence of specific highly adapted S. epidermidis clonal lineages in nosocomial settings.

Phylogenomic Rhizobium Species Are Structured by a Continuum of Diversity and Genomic Clusters.

The bacterial genus Rhizobium comprises diverse symbiotic nitrogen-fixing species associated with the roots of plants in the Leguminosae family. Multiple genomic clusters defined by whole genome comparisons occur within Rhizobium, but their equivalence to species is controversial. In this study we investigated such genomic clusters to ascertain their significance in a species phylogeny context. Phylogenomic inferences based on complete sets of ribosomal proteins and stringent core genome markers revealed the main lineages of Rhizobium. The clades corresponding to R. etli and R. leguminosarum species show several genomic clusters with average genomic nucleotide identities (ANI > 95%), and a continuum of divergent strains, respectively. They were found to be inversely correlated with the genetic distance estimated from concatenated ribosomal proteins. We uncovered evidence of a Rhizobium pangenome that was greatly expanded, both in its chromosomes and plasmids. Despite the variability of extra-chromosomal elements, our genomic comparisons revealed only a few chromid and plasmid families. The presence/absence profile of genes in the complete Rhizobium genomes agreed with the phylogenomic pattern of species divergence. Symbiotic genes were distributed according to the principal phylogenomic Rhizobium clades but did not resolve genome clusters within the clades. We distinguished some types of symbiotic plasmids within Rhizobium that displayed different rates of synonymous nucleotide substitutions in comparison to chromosomal genes. Symbiotic plasmids may have been repeatedly transferred horizontally between strains and species, in the process displacing and substituting pre-existing symbiotic plasmids. In summary, the results indicate that Rhizobium genomic clusters, as defined by whole genomic identities, might be part of a continuous process of evolutionary divergence that includes the core and the extrachromosomal elements leading to species formation.

Complete Genome Sequences of Eight Rhizobium Symbionts Associated with Common Bean (Phaseolus vulgaris).

We present here the high-quality complete genome sequences of eight strains of Rhizobium-nodulating Phaseolus vulgaris Comparative analyses showed that some of them belonged to different genomic and evolutionary lineages with common symbiotic properties. Two novel symbiotic plasmids (pSyms) with P. vulgaris specificity are reported here.

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.

Extracting regulatory networks of Escherichia coli from RegulonDB.

RegulonDB contains the largest and currently best-known data set on transcriptional regulation in a single free-living organism, that of Escherichia coli K-12 (Gama-Castro et al. Nucleic Acids Res 36:D120-D124, 2008). This organized knowledge has been the gold standard for the implementation of bioinformatic predictive methods on gene regulation in bacteria (Collado-Vides et al. J Bacteriol 191:23-31, 2009). Given the complexity of different types of interactions, the difficulty of visualizing in a single figure of the whole network, and the different uses of this knowledge, we are making available different views of the genetic network. This chapter describes case studies about how to access these views, via precomputed files, web services and SQL, including sigma-gene relationships corresponding to transcription of alternative RNA polymerase holoenzyme promoters; as well as, transcription factor (TF)-genes, TF-operons, TF-TF, and TF-regulon interactions. 17.

RegulonDB (version 6.0): gene regulation model of Escherichia coli K-12 beyond transcription, active (experimental) annotated promoters and Textpresso navigation.

RegulonDB (http://regulondb.ccg.unam.mx/) is the primary reference database offering curated knowledge of the transcriptional regulatory network of Escherichia coli K12, currently the best-known electronically encoded database of the genetic regulatory network of any free-living organism. This paper summarizes the improvements, new biology and new features available in version 6.0. Curation of original literature is, from now on, up to date for every new release. All the objects are supported by their corresponding evidences, now classified as strong or weak. Transcription factors are classified by origin of their effectors and by gene ontology class. We have now computational predictions for sigma(54) and five different promoter types of the sigma(70) family, as well as their corresponding -10 and -35 boxes. In addition to those curated from the literature, we added about 300 experimentally mapped promoters coming from our own high-throughput mapping efforts. RegulonDB v.6.0 now expands beyond transcription initiation, including RNA regulatory elements, specifically riboswitches, attenuators and small RNAs, with their known associated targets. The data can be accessed through overviews of correlations about gene regulation. RegulonDB associated original literature, together with more than 4000 curation notes, can now be searched with the Textpresso text mining engine.

Automatic reconstruction of a bacterial regulatory network using Natural Language Processing.

BACKGROUND: Manual curation of biological databases, an expensive and labor-intensive process, is essential for high quality integrated data. In this paper we report the implementation of a state-of-the-art Natural Language Processing system that creates computer-readable networks of regulatory interactions directly from different collections of abstracts and full-text papers. Our major aim is to understand how automatic annotation using Text-Mining techniques can complement manual curation of biological databases. We implemented a rule-based system to generate networks from different sets of documents dealing with regulation in Escherichia coli K-12. RESULTS: Performance evaluation is based on the most comprehensive transcriptional regulation database for any organism, the manually-curated RegulonDB, 45% of which we were able to recreate automatically. From our automated analysis we were also able to find some new interactions from papers not already curated, or that were missed in the manual filtering and review of the literature. We also put forward a novel Regulatory Interaction Markup Language better suited than SBML for simultaneously representing data of interest for biologists and text miners. CONCLUSION: Manual curation of the output of automatic processing of text is a good way to complement a more detailed review of the literature, either for validating the results of what has been already annotated, or for discovering facts and information that might have been overlooked at the triage or curation stages.

RegulonDB (version 5.0): Escherichia coli K-12 transcriptional regulatory network, operon organization, and growth conditions.

RegulonDB is the internationally recognized reference database of Escherichia coli K-12 offering curated knowledge of the regulatory network and operon organization. It is currently the largest electronically-encoded database of the regulatory network of any free-living organism. We present here the recently launched RegulonDB version 5.0 radically different in content, interface design and capabilities. Continuous curation of original scientific literature provides the evidence behind every single object and feature. This knowledge is complemented with comprehensive computational predictions across the complete genome. Literature-based and predicted data are clearly distinguished in the database. Starting with this version, RegulonDB public releases are synchronized with those of EcoCyc since our curation supports both databases. The complex biology of regulation is simplified in a navigation scheme based on three major streams: genes, operons and regulons. Regulatory knowledge is directly available in every navigation step. Displays combine graphic and textual information and are organized allowing different levels of detail and biological context. This knowledge is the backbone of an integrated system for the graphic display of the network, graphic and tabular microarray comparisons with curated and predicted objects, as well as predictions across bacterial genomes, and predicted networks of functionally related gene products. Access RegulonDB at http://regulondb.ccg.unam.mx.