| Congresso Brasileiro de Microbiologia 2023 | Resumo: 798-1 | ||||
Resumo:The COVID-19 pandemic has raised significant concerns about global respiratory health. Beyond its primary effects, there is growing evidence indicating that COVID-19 may influence the distribution of other respiratory tract infections, encompassing fungal, bacterial, and viral etiologies. Although research has begun to shed light on the interactions between SARS-CoV-2 and the human respiratory microbiota, comprehensive investigations at regional and national levels, particularly in Rio Grande do Sul state, are still scarce. The present study aims to explore the interactions between COVID-19 and the respiratory tract microbiota in the context of patients from the Rio Grande do Sul state. A total of 23 nasal swab samples, collected from both COVID-19 positive patients and negative controls during 2021 and 2022, were subjected to metagenomic analyses. The first group, consisting of 18 samples obtained from patients with mild respiratory syndrome at the Instituto de Ciências Básicas de Saúde da Universidade Federal do Rio Grande do Sul (ICBS/UFRGS), and the second group, comprising 5 samples from patients with severe acute respiratory syndrome at the Laboratório Central de Saúde Pública do Estado do Rio Grande do Sul (LACEN), were included in the study. DNA extraction was performed using the phenol-chloroform method for the first group, whilst the ZymoBIOMICS DNA Miniprep kit was used for the second. To ensure quality, all samples were quantified using the Qubit dsDNA HS Assay kit and analyzed using the Bioanalyzer High Sensitivity DNA Analysis system prior to being subjected to Illumina sequencing (IPEC, Paraná). Post-sequencing, low-quality reads were removed using fastp (v0.23.2), and sequences mapped to the human reference genome (hg37dec_v0.1) were subtracted by Bowtie 2 (v2.5.1) and samtools (v1.12). Read quality was evaluated pre and post-processing using FastQC (v0.11.9) and MultiQC (v1.13). The mOTUs3 software (v3.1.0) was used for taxonomic classification, followed by read count normalization using the DESeq2 package (v1.38.3) in R (v4.2.2). Principal Component Analysis (PCA) was employed to explore the distribution of the taxonomic groups based on the obtained data. Sequencing yielded substantial read depth, with 24 to 45 million reads per library and over 90% of reads with Phred scores greater than 30 in all samples. The PCA analysis revealed distinctive clusters along the second component, accounting for 21% of the variance. Notably, the second group demonstrated lower variation between its samples, whilst the first group exhibited dispersion along PC1, contributing to 27% of the variance. In terms of predominant Operational Taxonomic Units (OTUs), Streptococcus sp., Corynebacterium accolens, Actinomyces sp. and Rothia mucilaginosa were observed. Particularly, in the negative samples of the second group, Stenotrophomonas maltophilia, an opportunistic and nosocomial pathogen, was found. Moving forward, further bioinformatics analyses will be conducted to a larger sample size; including the taxonomic profiling of fungi and viruses, alpha and beta diversity and antimicrobial resistance molecular markers analyses. These findings are of utmost significance in understanding the complex interactions between COVID-19 and the respiratory tract microbiota, as well as management of secondary respiratory infections that it incurs. Palavras-chave: metagenome, microbiota, COVID-19, respiratory infections Agência de fomento:Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS) | |||||