ChiMera: an easy to use pipeline for bacterial genome based metabolic network reconstruction, evaluation and visualization.

BACKGROUND: Genome-scale metabolic reconstruction tools have been developed in the last decades. They have helped to reconstruct eukaryotic and prokaryotic metabolic models, which have contributed to fields, e.g., genetic engineering, drug discovery, prediction of phenotypes, and other model-driven discoveries. However, the use of these programs requires a high level of bioinformatic skills. Moreover, the functionalities required to build models are scattered throughout multiple tools, requiring knowledge and experience for utilizing several tools. RESULTS: Here we present ChiMera, which combines tools used for model reconstruction, prediction, and visualization. ChiMera uses CarveMe in the reconstruction module, generating a gap-filled draft reconstruction able to produce growth predictions using flux balance analysis for gram-positive and gram-negative bacteria. ChiMera also contains two modules for metabolic network visualization. The first module generates maps for the most important pathways, e.g., glycolysis, nucleotides and amino acids biosynthesis, fatty acid oxidation and biosynthesis and core-metabolism. The second module produces a genome-wide metabolic map, which can be used to retrieve KEGG pathway information for each compound in the model. A module to investigate gene essentiality and knockout is also present. CONCLUSIONS: Overall, ChiMera uses automation algorithms to combine a variety of tools to automatically perform model creation, gap-filling, flux balance analysis (FBA), and metabolic network visualization. ChiMera models readily provide metabolic insights that can aid genetic engineering projects, prediction of phenotypes, and model-driven discoveries.

Metagenomic Insights for Antimicrobial Resistance Surveillance in Soils with Different Land Uses in Brazil.

Land-use conversion changes soil properties and their microbial communities, which, combined with the overuse of antibiotics in human and animal health, promotes the expansion of the soil resistome. In this context, we aimed to profile the resistome and the microbiota of soils under different land practices. We collected eight soil samples from different locations in the countryside of São Paulo (Brazil), assessed the community profiles based on 16S rRNA sequencing, and analyzed the soil metagenomes based on shotgun sequencing. We found differences in the communities' structures and their dynamics that were correlated with land practices, such as the dominance of Staphylococcus and Bacillus genera in agriculture fields. Additionally, we surveyed the abundance and diversity of antibiotic resistance genes (ARGs) and virulence factors (VFs) across studied soils, observing a higher presence and homogeneity of the vanRO gene in livestock soils. Moreover, three ß-lactamases were identified in orchard and urban square soils. Together, our findings reinforce the importance and urgency of AMR surveillance in the environment, especially in soils undergoing deep land-use transformations, providing an initial exploration under the One Health approach of environmental levels of resistance and profiling soil communities.

Nosocomial Outbreak of Extensively Drug-Resistant (Polymyxin B and Carbapenem) Klebsiella pneumoniae in a Collapsed University Hospital Due to COVID-19 Pandemic.

We correlated clinical, epidemiological, microbiological, and genomic data of an outbreak with polymyxin B (PB)- and carbapenem-resistant Klebsiella pneumoniae during the COVID-19 pandemic. Twenty-six PB- and carbapenem-resistant K. pneumoniae were isolated from patients in the COVID-19 ICU (Intensive Care Unit), non-COVID-19 ICU (Intensive Care Unit), clinical, or surgical ward. Bacterial identification, drug susceptibility tests, and DNA sequencing were performed, followed by in silico resistance genes identification. All isolates showed extensively drug-resistant (XDR) phenotypes. Four different sequence types (ST) were detected: ST16, ST11, ST258, and ST437. Nineteen isolates were responsible for an outbreak in the ICU in September 2020. They belong to ST258 and harbored the 42Kb IncX3plasmid (pKP98M3N42) with the same genomic pattern of two K. pneumoniae identified in 2018. Twenty-four isolates carried bla-KPC-2 gene. No plasmid-mediated colistin (mcr) resistance genes were found. Eight isolates presented mgrB gene mutation. The clonal isolates responsible for the outbreak came from patients submitted to pronation, with high mortality rates in one month. XDR-K. pneumoniae detected during the outbreak presented chromosomal resistance to PB and plasmid-acquired carbapenem resistance due to KPC production in most isolates and 42Kb IncX3(pKP98M3N42) plasmid carrying blaKPC-2 was associated with ST258 isolates. The outbreak followed the collapse of the local healthcare system with high mortality rates.