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Hospital bloodstream infection (BSI) caused by methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of morbidity and mortality and is frequently related to invasive procedures and medically complex patients. An important feature of MRSA is the clonal structure of its population. Specific MRSA clones may differ in their pathogenic, epidemiological, and antimicrobial resistance profiles. Whole-genome sequencing is currently the most robust and discriminatory technique for tracking hypervirulent/well-adapted MRSA clones. However, it remains an expensive and time-consuming technique that requires specialized personnel. In this work, we describe a pangenome protocol, based on binary matrix (1,0) of open reading frames (ORFs), that can be used to quickly find diagnostic, apomorphic sequence mutations that can serve as biomarkers. We use this technique to create a diagnostic screen for MRSA isolates circulating in the Rio de Janeiro metropolitan area, the RdJ clone, which is prevalent in BSI. The method described here has 100% specificity and sensitivity, eliminating the need to use genomic sequencing for clonal identification. The protocol used is relatively simple and all the steps, formulas and commands used are described in this work, such that this strategy can also be used to identify other MRSA clones and even clones from other bacterial species.

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Background: Advancements in DNA sequencing technology have transformed the field of bacterial genomics, allowing for faster and more cost effective chromosome level assemblies compared to a decade ago. However, transforming raw reads into a complete genome model is a significant computational challenge due to the varying quality and quantity of data obtained from different sequencing instruments, as well as intrinsic characteristics of the genome and desired analyses. To address this issue, we have developed a set of container-based pipelines using Nextflow, offering both common workflows for inexperienced users and high levels of customization for experienced ones. Their processing strategies are adaptable based on the sequencing data type, and their modularity enables the incorporation of new components to address the community's evolving needs. Methods: These pipelines consist of three parts: quality control, de novo genome assembly, and bacterial genome annotation. In particular, the genome annotation pipeline provides a comprehensive overview of the genome, including standard gene prediction and functional inference, as well as predictions relevant to clinical applications such as virulence and resistance gene annotation, secondary metabolite detection, prophage and plasmid prediction, and more. Results: The annotation results are presented in reports, genome browsers, and a web-based application that enables users to explore and interact with the genome annotation results. Conclusions: Overall, our user-friendly pipelines offer a seamless integration of computational tools to facilitate routine bacterial genomics research. The effectiveness of these is illustrated by examining the sequencing data of a clinical sample of Klebsiella pneumoniae.

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Antimicrobial resistance (AMR) mechanisms, especially those conferring resistance to critically important antibiotics, are a great concern for public health. 16S rRNA methyltransferases (16S-RMTases) abolish the effectiveness of most clinically used aminoglycosides, but some of them are considered sporadic, such as RmtE. The main goals of this work were the genomic analysis of bacteria producing 16S-RMTases from a 'One Health' perspective in Venezuela, and the study of the epidemiological and evolutionary scenario of RmtE variants and their related mobile genetic elements (MGEs) worldwide. A total of 21 samples were collected in 2014 from different animal and environmental sources in the Cumaná region (Venezuela). Highly aminoglycoside-resistant Enterobacteriaceae isolates were selected, identified and screened for 16S-RMTase genes. Illumina and Nanopore whole-genome sequencing data were combined to obtain hybrid assemblies and analyse their sequence type, resistome, plasmidome and pan-genome. Genomic collections of rmtE variants and their associated MGEs were generated to perform epidemiological and phylogenetic analyses. A single 16S-RMTase, the novel RmtE4, was identified in five Klebsiella isolates from wastewater samples of Cumaná. This variant possessed three amino acid modifications with respect to RmtE1-3 (Asn152Asp, Val216Ile and Lys267Ile), representing the most genetic distant among all known and novel variants described in this work, and the second most prevalent. rmtE variants were globally spread, and their geographical distribution was determined by the associated MGEs and the carrying bacterial species. Thus, rmtE4 was found to be confined to Klebsiella isolates from South America, where it was closely related to ISVsa3 and an uncommon IncL plasmid related with hospital environments. This work uncovered the global scenario of RmtE and the existence of RmtE4, which could potentially emerge from South America. Surveillance and control measures should be developed based on these findings in order to prevent the dissemination of this AMR mechanism and preserve public health worldwide.

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Bacterial adaptation to stressful environments often produces evolutionary constraints whereby increases in resistance are associated with reduced fitness in a different environment. The exploitation of this resistance-cost trade-off has been proposed as the basis of rational antimicrobial treatment strategies designed to limit the evolution of drug resistance in bacterial pathogens. Recent theoretical, laboratory, and clinical studies have shown that fluctuating selection can maintain drug efficacy and even restore drug susceptibility, but can also increase the rate of adaptation and promote cross-resistance to other antibiotics. In this paper, we combine mathematical modeling, experimental evolution, and whole-genome sequencing to follow evolutionary trajectories towards ß-lactam resistance under fluctuating selective conditions. Our experimental model system consists of eight populations of Escherichia coli K12 evolving in parallel to a serial dilution protocol designed to dynamically control the strength of selection for resistance. We implemented adaptive ramps with mild and strong selection, resulting in evolved populations with similar levels of resistance, but with different evolutionary dynamics and diverging genotypic profiles. We found that mutations that emerged under strong selection are unstable in the absence of selection, in contrast to resistance mutations previously selected in the mild selection regime that were stably maintained in drug-free environments and positively selected for when antibiotics were reintroduced. Altogether, our population dynamics model and the phenotypic and genomic analysis of the evolved populations show that the rate of resistance adaptation is contingent upon the strength of selection, but also on evolutionary constraints imposed by prior drug exposures.

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This review gathers recent information about genomic and transcriptomic studies in the Corynebacterium genus, exploring, for example, prediction of pathogenicity islands and stress response in different pathogenic and non-pathogenic species. In addition, is described several phylogeny studies to Corynebacterium, exploring since the identification of species until biological speciation in one species belonging to the genus Corynebacterium. Important concepts associated with virulence highlighting the role of Pld protein and Tox gene. The adhesion, characteristic of virulence factor, was described using the sortase mechanism that is associated to anchorage to the cell wall. In addition, survival inside the host cell and some diseases, were too addressed for pathogenic corynebacteria, while important biochemical pathways and biotechnological applications retain the focus of this review for non-pathogenic corynebacteria. Concluding, this review broadly explores characteristics in genus Corynebacterium showing to have strong relevance inside the medical, veterinary, and biotechnology field.

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Leptospirosis is an emerging zoonosis with important economic and public health consequences and is caused by pathogenic leptospires. The genus Leptospira belongs to the order Spirochaetales and comprises saprophytic (L. biflexa), pathogenic (L. interrogans) and host-dependent (L. borgpetersenii) members. Here, we present an in silico search for DNA repair pathways in Leptospira spp. The relevance of such DNA repair pathways was assessed through the identification of mRNA levels of some genes during infection in animal model and after exposition to spleen cells. The search was performed by comparison of available Leptospira spp. genomes in public databases with known DNA repair-related genes. Leptospires exhibit some distinct and unexpected characteristics, for instance the existence of a redundant mechanism for repairing a chemically diverse spectrum of alkylated nucleobases, a new mutS-like gene and a new shorter version of uvrD. Leptospira spp. shares some characteristics from Gram-positive, as the presence of PcrA, two RecQ paralogs and two SSB proteins; the latter is considered a feature shared by naturally competent bacteria. We did not find a significant reduction in the number of DNA repair-related genes in both pathogenic and host-dependent species. Pathogenic leptospires were enriched for genes dedicated to base excision repair and non-homologous end joining. Their evolutionary history reveals a remarkable importance of lateral gene transfer events for the evolution of the genus. Up-regulation of specific DNA repair genes, including components of SOS regulon, during infection in animal model validates the critical role of DNA repair mechanisms for the complex interplay between host/pathogen.

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