Biology subjects

Tamasco, G.

Publications and source records attributed to Tamasco, G..

2 recordsLinked to original sources

bioRxiv2022

Metagenomic insights for antimicrobial resistance surveillance in soils with different land uses in Brazil

Anthropization in terrestrial environments commonly leads to land use transformation, changing soil properties and their microbial communities. This, combined with the exacerbated use of antibiotics in human and animal health promotes the expansion of the soil resistome. Considering the urgent need for surveillance of antimicrobial resistance (AMR), we aimed to evaluate how different land practices (urban, farming and forest) can affect the soil resistome and the dynamics of their bacterial communities. We collected eight soil samples from different locations in the countryside of Sao Paulo (Brazil), assessed the community profiles based on 16S rRNA sequencing and analyzed the soil metagenomes based on shotgun sequencing. Our results highlight differences in the communities structure and their dynamics which were correlated with land practices. Additionally, differences were observed in the abundance and diversity of antibiotic resistance genes (ARGs) and virulence factors (VFs) across studied soils, where a higher presence and homogeneity of vanRO, mtrA and rbpA genes were detected in livestock soils. We observed that Staphylococcus and Bacillus are positively correlated with each other and are markers for agricultural communities. Moreover, the abundance and diversity of ARGs and VFs observed in farming soils raises concerns regarding the potential spread of these genes in the environment. Together, our findings reinforce the importance and urgency of AMR surveillance in the environment, especially in soils undergoing deep land use transformations due to anthropic activity.

microbiology↗

bioRxiv2021

ChiMera: An easy to use pipeline for Bacterial Genome Based Metabolic Network Reconstruction, Evaluation and Visualization

Several genome scale metabolic reconstruction tools have been developed in the last decades. They have helped to construct many metabolic models, which have contributed to a variety of fields, e.g., genetic engineering, drug discovery, prediction of phenotypes, and other model-driven discoveries. However, the use of these programs requires a higher level of bioinformatic skills, and most of them are not scalable for multiple genomes. Moreover, the functionalities required to build models are generally scattered through multiple tools, requiring knowledge of their utilization. Here, we present ChiMera, which combines the most efficient tools in model reconstruction, prediction, and visualization. ChiMera uses CarveMe top-down approach based on genomic evidence to prune a global model with a high level of curation, generating a draft genome able to produce growth predictions using flux balance analysis for gram-positive and gram-negative bacteria. ChiMera also contains two modules of visualization implemented, predefined and universal. The first generates maps for the most important pathways, e.g., core-metabolism, fatty acid oxidation and biosynthesis, nucleotides and amino acids biosynthesis, glycolysis, and others. The second module produces a genome-wide metabolic map, which can be used to harvest KEGG pathway information for each compound in the model. A module of gene essentiality and knockout is also present. Overall, ChiMera combines model creation, gap-filling, FBA and metabolic visualization to create a simulation ready genome-scale model, helping genetic engineering projects, prediction of phenotypes, and other model-driven discoveries in a friendly manner.

bioinformatics↗