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The metagenomic surveillance of antimicrobial resistance in wastewater has been suggested as a methodological tool to characterize the distribution, status, and trends of antibiotic-resistant bacteria. In this study, a cross-sectional collection of samples of hospital-associated raw and treated wastewater were obtained from February to March 2020. Shotgun metagenomic sequencing and bioinformatic analysis were performed to characterize bacterial abundance and antimicrobial resistance gene analysis. The main bacterial phyla found in all the samples were as follows: Proteobacteria, Bacteroides, Firmicutes, and Actinobacteria. At the species level, ESKAPEE bacteria such as E. coli relative abundance decreased between raw and treated wastewater, but S. aureus, A. baumannii, and P. aeruginosa increased, as did the persistence of K. pneumoniae in both raw and treated wastewater. A total of 172 different ARGs were detected; blaOXA, blaVEB, blaKPC, blaGES, mphE, mef, erm, msrE, AAC(6'), ant(3â³), aadS, lnu, PBP-2, dfrA, vanA-G, tet, and sul were found at the highest abundance and persistence. This study demonstrates the ability of ESKAPEE bacteria to survive tertiary treatment processes of hospital wastewater, as well as the persistence of clinically important antimicrobial resistance genes that are spreading in the environment.
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Background: The axolotl, Ambystoma mexicanum is a unique biological model for complete tissue regeneration. Is a neotenic endangered species and is highly susceptible to environmental stress, including infectious disease. In contrast to other amphibians, the axolotl is particularly vulnerable to certain viral infections. Like other salamanders, the axolotl genome is one of the largest (32 Gb) and the impact of genome size on Ig loci architecture is unknown. To better understand the immune response in axolotl, we aimed to characterize the immunoglobulin loci of A. mexicanum and compare it with other model vertebrates. Methods: The most recently published genome sequence of A. mexicanum (V6) was used for alignment-based annotation and manual curation using previously described axolotl Ig sequences or reference sequences from other vertebrates. Gene models were further curated using A. mexicanum spleen RNA-seq data. Human, Xenopus tropicalis, Danio rerio (zebrafish), and eight tetrapod reference genomes were used for comparison. Results: Canonical A. mexicanum heavy chain (IGH), lambda (IGL), sigma (IGS), and the putative surrogate light chain (SLC) loci were identified. No kappa locus was found. More than half of the IGHV genes and the IGHF gene are pseudogenes and there is no clan I IGHV genes. Although the IGH locus size is proportional to genome size, we found local size restriction in the IGHM gene and the V gene intergenic distances. In addition, there were V genes with abnormally large V-intron sizes, which correlated with loss of gene functionality. Conclusion: The A. mexicanum immunoglobulin loci share the same general genome architecture as most studied tetrapods. Consistent with its large genome, Ig loci are larger; however, local size restrictions indicate evolutionary constraints likely to be imposed by high transcriptional demand of certain Ig genes, as well as the V(D)J recombination over very long genomic distance ranges. The A. mexicanum has undergone an extensive process of Ig gene loss which partially explains a reduced potential repertoire diversity that may contribute to its impaired antibody response.
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Ambystoma mexicanum , Imunoglobulinas , Animais , Ambystoma mexicanum/genética , Genoma , Genômica , Imunoglobulinas/genéticaRESUMO
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Metagenomics research has recently thrived due to DNA sequencing technologies improvement, driving the emergence of new analysis tools and the growth of taxonomic databases. However, there is no all-purpose strategy that can guarantee the best result for a given project and there are several combinations of software, parameters and databases that can be tested. Therefore, we performed an impartial comparison, using statistical measures of classification for eight bioinformatic tools and four taxonomic databases, defining a benchmark framework to evaluate each tool in a standardized context. Using in silico simulated data for 16S rRNA amplicons and whole metagenome shotgun data, we compared the results from different software and database combinations to detect biases related to algorithms or database annotation. Using our benchmark framework, researchers can define cut-off values to evaluate the expected error rate and coverage for their results, regardless the score used by each software. A quick guide to select the best tool, all datasets and scripts to reproduce our results and benchmark any new method are available at https://github.com/Ales-ibt/Metagenomic-benchmark . Finally, we stress out the importance of gold standards, database curation and manual inspection of taxonomic profiling results, for a better and more accurate microbial diversity description.