Distribution And Classification Of Serine Beta-Lactamases In Brazilian Hospital Sewage And Other Environmental Metagenomes Deposited In Public Databases

beta-lactam is the most used antibiotic class in the clinical area and it acts on blocking the bacteria cell wall synthesis, causing cell death. However, some bacteria have evolved resistance to these antibiotics mainly due the production of enzymes known as beta-lactamases. Hospital sewage is an important source of dispersion of multidrug-resistant bacteria in rivers and oceans. In this work, we used next-generation DNA sequencing to explore the diversity and dissemination of serine beta-lactamases in two hospital sewage from Rio de Janeiro, Brazil (South Zone, SZ and North Zone, NZ), presenting different profiles, and to compare them with public environmental data available. Also, we propose a Hidden-Markov-Model approach to screen potential serine beta-lactamases genes (in public environments samples and generated hospital sewage data), exploring its evolutionary relationships. Due to the high variability in beta-lactamases, we used a position-specific scoring matrix search method (RPS-BLAST) against conserved domain database profiles (CDD, Pfam, and COG) followed by visual inspection to detect conserved motifs, to increase the reliability of the results and remove possible false positives. We were able to identify novel beta-lactamases from Brazilian hospital sewage and to estimate relative abundance of its types. The highest relative abundance found in SZ was the Class A (50%), while Class D is predominant in NZ (55%). CfxA (65%) and ACC (47%) types were the most abundant genes detected in SZ, while in NZ the most frequent were OXA-10 (32%), CfxA (28%), ACC (21%), CEPA (20%), and FOX (19%). Phylogenetic analysis revealed beta-lactamases from Brazilian hospital sewage grouped in the same clade and close to sequences belonging to Firmicutes and Bacteroidetes groups, but distant from potential beta-lactamases screened from public environmental data, that grouped closer to beta-lactamases of Proteobacteria. Our results demonstrated that HMM-based approach identified homologs of serine beta-lactamases, indicating the specificity and high sensitivity of this approach in large datasets, contributing for the identification and classification of a large number of homologous genes, comprising possible new ones. Phylogenetic analysis revealed the potential reservoir of beta-lactam resistance genes in the environment, contributing to understanding the evolution and dissemination of these genes.