The western mesoregion of the state of Santa Catarina (SC), Southern Brazil, was heavily affected as a whole by the COVID-19 pandemic in early 2021. This study aimed to evaluate the dynamics of the SARS-CoV-2 virus spreading patterns in the SC state from March 2020 to April 2021 using genomic surveillance. During this period, there were 23 distinct variants, including Beta and Gamma, among which the Gamma and related lineages were predominant in the second pandemic wave within SC. A regionalization of P.1-like-II in the Western SC region was observed, concomitant to the increase in cases, mortality, and the case fatality rate (CFR) index. This is the first evidence of the regionalization of the SARS-CoV-2 transmission in SC and it highlights the importance of tracking the variants, dispersion, and impact of SARS-CoV-2 on the public health systems.

: Genomic and proteomic advances in extremophile microorganism studies are increasingly demonstrating their ability to produce a variety of enzymes capable of converting biomass into bioenergy. Such microorganisms are found in environments with nutritional restrictions, anaerobic environments, high salinity, varying pH conditions and extreme natural environments such as hydrothermal vents, soda lakes, and Antarctic sediments. Because extremophile microorganisms and their enzymes are found in widely disparate locations, they generate new possibilities and opportunities to explore biotechnological prospecting, including biofuels (biogas, hydrogen and ethanol) with an aim toward using multi-omics tools that shed light on biotechnological breakthroughs.

Clostridioides difficile BI/NAP1/ribotype 027 is an epidemic hypervirulent strain found worldwide, including in Latin America. We examined the genomes and exoproteomes of two multilocus sequence type (MLST) clade 2 C. difficile strains considered hypervirulent: ICC-45 (ribotype SLO231/UK[CE]821), isolated in Brazil, and NAP1/027/ST01 (LIBA5756), isolated during a 2010 outbreak in Costa Rica. C. difficile isolates were cultured and extracellular proteins were analyzed using high-performance liquid chromatography-tandem mass spectrometry. Genomic analysis revealed that these isolates shared most of the gene composition. Only 83 and 290 NAP1/027 genes were considered singletons in ICC-45 and NAP1/027, respectively. Exoproteome analysis revealed 197 proteins, of which 192 were similar in both strains. Only five proteins were exclusive to the ICC-45 strain. These proteins were involved with catalytic and binding functions and indirectly interacted with proteins related to pathogenicity. Most proteins, including TcdA, TcdB, flagellin subunit, and cell surface protein, were overrepresented in the ICC-45 strain; 14 proteins, including mature S-layer protein, were present in higher proportions in LIBA5756. Data are available via ProteomeXchange with identifier PXD026218. These data show close similarity between the genome and proteins in the supernatant of two strains with hypervirulent features isolated in Latin America and underscore the importance of epidemiological surveillance of the transmission and emergence of new strains.

COVID-19 has assumed significant and lasting proportions worldwide. Following initial cases in the Western mesoregion, the State of Santa Catarina (SC), southern Brazil, was heavily affected as a whole by the pandemic in early 2021. This study aimed to evaluate the dynamics of the SARS-CoV-2 virus spreading patterns in the SC state through March 2020 to April 2021 using genomic surveillance. During this period, 23 distinct variants, including two VOCs (Beta and Gamma) were identified, among which, the Gamma and related lineages were predominant in the second pandemic wave within SC. However, a regionalization of P.1-like-II in the Western region was observed, concomitant to the increase in cases, mortality, and case fatality rate (CFR) index. This is the first evidence of the regionalization of the SARS-CoV-2 transmission in the and highlight the importance of tracking variants, dispersion and their impact of SARS-CoV-2 on the public health system in Brazilian states.

Assignment of gene function has been a crucial, laborious, and time-consuming step in genomics. Due to a variety of sequencing platforms that generates increasing amounts of data, manual annotation is no longer feasible. Thus, the need for an integrated, automated pipeline allowing the use of experimental data towards validation of in silico prediction of gene function is of utmost relevance. Here, we present a computational workflow named AnnotaPipeline that integrates distinct software and data types on a proteogenomic approach to annotate and validate predicted features in genomic sequences. Based on FASTA (i) nucleotide or (ii) protein sequences or (iii) structural annotation files (GFF3), users can input FASTQ RNA-seq data, MS/MS data from mzXML or similar formats, as the pipeline uses both transcriptomic and proteomic information to corroborate annotations and validate gene prediction, providing transcription and expression evidence for functional annotation. Reannotation of the available Arabidopsis thaliana, Caenorhabditis elegans, Candida albicans, Trypanosoma cruzi, and Trypanosoma rangeli genomes was performed using the AnnotaPipeline, resulting in a higher proportion of annotated proteins and a reduced proportion of hypothetical proteins when compared to the annotations publicly available for these organisms. AnnotaPipeline is a Unix-based pipeline developed using Python and is available at: https://github.com/bioinformatics-ufsc/AnnotaPipeline.