Resurgence of human respiratory syncytial virus during COVID-19 pandemic in Southern Brazil.

Respiratory Syncytial Virus (RSV) is an important cause of respiratory infection in humans. Severe cases are common in children ≤2 years old, immunocompromised individuals, and the elderly. In 2020, RSV infection reduced in Rio Grande do Sul (RS), southern Brazil; however, in 2021 resurgence of RSV was observed. This study analyzed epidemiological and genetic features of RSV infection cases reported in 2021 in RS. Nasopharyngeal samples collected from individuals with respiratory infection negative for SARS-CoV-2, Influenza A and B viruses were assessed for the presence of RSV by real time RT-qPCR. RSV-A and RSV-B genomic sequencing and phylogenetic reconstructions were performed for genotyping and clade characterization. Among 21,035 respiratory samples analyzed, 2,947 were positive for RSV, 947 of which were hospitalized patients. Positive cases were detected year-round, with the highest number in June-July (winter). Children <1 year comprised 56.28% (n = 533) of the hospitalized patients infected with RSV, whereas 14.46% (n = 137) were individuals >60 years. Of a total of 361 deaths, 14.68% (n = 53) were RSV positive, mostly patients >60 years old (73.58%, n = 39). Chronic kidney disease, cardiopathy, Down syndrome and neurological diseases were associated with RSV infection. RSV-A was identified in 58.5% (n = 117/200) of the patients, and RSV-B in 41.5% (n = 83/200). Of 95 RSV genomes recovered from SARI cases, 66 were RSV-A GA.2.3.5 genotype, while 29 were RSV-B GB.5.0.5a genotype. This study provides epidemiological and molecular data on RSV cases in RS during the COVID-19 pandemic and highlights that investigation of different respiratory viruses is essential for decision-making and disease prevention and control measures.

Introduction, Dispersal, and Predominance of SARS-CoV-2 Delta Variant in Rio Grande do Sul, Brazil: A Retrospective Analysis.

Mutations in the SARS-CoV-2 genome can alter the virus' fitness, leading to the emergence of variants of concern (VOC). In Brazil, the Gamma variant dominated the pandemic in the first half of 2021, and from June onwards, the first cases of Delta infection were documented. Here, we investigate the introduction and dispersal of the Delta variant in the RS state by sequencing 1077 SARS-CoV-2-positive samples from June to October 2021. Of these samples, 34.7% were identified as Gamma and 65.3% as Delta. Notably, 99.2% of Delta sequences were clustered within the 21J lineage, forming a significant Brazilian clade. The estimated clock rate was 5.97 × 10-4 substitutions per site per year. The Delta variant was first reported on 17 June in the Vinhedos Basalto microregion and rapidly spread, accounting for over 70% of cases within nine weeks. Despite this, the number of cases and deaths remained stable, possibly due to vaccination, prior infections, and the continued mandatory mask use. In conclusion, our study provides insights into the Delta variant circulating in the RS state, highlighting the importance of genomic surveillance for monitoring viral evolution, even when the impact of new variants may be less severe in a given region.

Homology Inference Based on a Reconciliation Approach for the Comparative Genomics of Protozoa.

Protozoa parasites are responsible for several diseases in tropical countries, such as malaria, sleeping sickness, Chagas disease, leishmaniasis, amebiasis, and giardiasis, which together threaten millions of people around the world. In addition, most of the classic parasitic diseases due to protozoa are zoonotic. Understanding the biology of these organisms plays a relevant role in combating these diseases. Using homology inference and comparative genomics, this study targeted 3 protozoan species from different Phyla: Cryptosporidium muris (Apicomplexa), Entamoeba invadens (Amoebozoa), and Trypanosoma grayi (Euglenozoa). In this study, we propose a new approach for the identification of homologs, based on the reconciliation of the results of 2 different homology inference software programs. Our results showed that 46.1% (59/128) of the groups inferred by our reconciliation approach could be validated using this methodology. These validated groups are here called homologous Supergroups and were compared with SUPERFAMILY and Pfam Clans.