Genomic surveillance and vaccine response to the dominant SARS-CoV-2 XBB lineage in Rio Grande do Sul.

The COVID-19 pandemic has been marked by novel viral variants, posing challenges to global public health. Recombination, a viral evolution mechanism, is implicated in SARS-CoV-2's ongoing evolution. The XBB recombinant lineage, known for evading antibody-mediated immunity, exhibits higher transmissibility without increased disease severity. We investigated the prevalence and genomic features of XBB in SARS-CoV-2-positive cases in Rio Grande do Sul (RS), Brazil. We sequenced 357 samples from epidemiological weeks (EW) 47/2022 to 17/2023, and included 389 publicly available sequences. Clinical and epidemiological data were obtained from DATASUS, e-SUS, and SIVEP GRIPE (data recording systems of the Brazilian Ministry of Health). Of these, 143 were classified as XBB and 586 were other Omicron lineages. In March 2023 (EW 10), XBB became dominant, accounting for 83.3% of cases. 97.7% of XBB-infected patients successfully recovered from the infection, with a low mortality rate (2.3%). Even after receiving three vaccine doses and having been previously infected, 59.5% of the patients experienced reinfection with XBB. However, for 54% of the individuals, the interval between their XBB infection and the last vaccine dose exceeded one year, potentially leading to a decline in antibody levels. In addition, we identified 90 mutations in RS circulating XBB, spread throughout the genome, notably in the Spike protein region associated with immune resistance. This study provides insights into the dynamics and impact of a recombinant variant becoming predominant for the first time in the state. Continued surveillance of SARS-CoV-2 genomic evolution is crucial for effective public health management.

Pipeline validation for the identification of antimicrobial-resistant genes in carbapenem-resistant Klebsiella pneumoniae.

Antimicrobial-resistant Klebsiella pneumoniae is a global threat to healthcare and an important cause of nosocomial infections. Antimicrobial resistance causes prolonged treatment periods, high mortality rates, and economic impacts. Whole Genome Sequencing (WGS) has been used in laboratory diagnosis, but there is limited evidence about pipeline validation to parse generated data. Thus, the present study aimed to validate a bioinformatics pipeline for the identification of antimicrobial resistance genes from carbapenem-resistant K. pneumoniae WGS. Sequences were obtained from a publicly available database, trimmed, de novo assembled, mapped to the K. pneumoniae reference genome, and annotated. Contigs were submitted to different tools for bacterial (Kraken2 and SpeciesFinder) and antimicrobial resistance gene identification (ResFinder and ABRicate). We analyzed 201 K. pneumoniae genomes. In the bacterial identification by Kraken2, all samples were correctly identified, and in SpeciesFinder, 92.54% were correctly identified as K. pneumoniae, 6.96% erroneously as Pseudomonas aeruginosa, and 0.5% erroneously as Citrobacter freundii. ResFinder found a greater number of antimicrobial resistance genes than ABRicate; however, many were identified more than once in the same sample. All tools presented 100% repeatability and reproducibility and > 75% performance in other metrics. Kraken2 was more assertive in recognizing bacterial species, and SpeciesFinder may need improvements.