ABSTRACT. The main purpose of this research was to analyze the relation of the genetic polymorphisms frequently expressed by antigen-presenting cells, erythrocytes and malaria susceptibility/resistance with the human malaria infection cases. The sample used consisted of 23 Plasmodium vivax (Pv)-and P. falciparum (Pf)-infected patients, and 21 healthy individuals as a control group, from the Baixo Amazonas population in Pará, Brazil. The Asp299Gly polymorphisms in the Toll-like receptor 4 (TLR4), and Gly42Asp, Arg89Cys, Ala100Thr, and T-33C in the Duffy gene (FY) were analyzed by restriction fragment length polymorphism-polymerase chain reaction. The Lys1590Glu and Arg1601Gly polymorphisms in the complement receptor type 1 (CR1) were analyzed by DNA sequencing. According to the results obtained and statistical analysis considering a significance level or α = 0.01, we conclude that the low heterozygote frequency (2.27%) for the Asp299Gly mutation, detected in the TLR4 gene, is not related to the Pv and Pf infections in the patients analyzed. Also, the promoter region GATA-1 analysis of the FY gene in the Pv-infected patients showed that the heterozygote frequency for the T-33C mutation (11.36% of the infected patients and 20.45% of the control patients) is not related to infection resistance. Regarding the CR1 gene, the observed heterozygote frequency (9.09%) for the Arg1601Gly mutation in Pf-infected patients when compared to heterozygote frequency in the control group (18.18%) suggests that there is no correlation with infection resistance.

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.

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.

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.

This study aimed to compare the effects of different levels of cashew nutshell liquid (CNSL) and castor oil (CNSL–castor oil) with growth-promoting antibiotics associated with anticoccidials in broiler chickens challenged with coccidiosis. In this work, 2520 one-day-old male broiler chicks (Cobb) were randomly assigned to 84 pens, containing 30 birds each. The experimental design was completely randomized, with seven treatments: enramycin (8 ppm), virginiamycin (16.5 ppm), and tylosin (55 ppm); different doses of CNSL–castor oil (0.5, 0.75, and 1.00 kg/t); and a control diet (without additives). All treatments received semduramicin + nicarbazin (500 g/t; Aviax® Plus) from 0 to 28 d and monensin sodium (100 ppm; Elanco) from 29 to 35 days of age, when the feed was without antibiotics. The challenge was introduced at 14 days of age by inoculating broiler chickens with sporulated Eimeria tenella, Eimeria acervulina, and Eimeria maxima oocysts via oral gavage. In addition to performance parameters, intestinal contents were collected at 28 and 42 days of age for microbiota analysis by sequencing the 16s rRNA in V3 and V4 regions using the Illumina MiSeq platform. Taxonomy was assigned using the SILVA database (v. 138) with QIIME2 software (v. 2020.11). After one week of challenge, the broilers that received tylosin had a higher body weight gain (BWG) than those in the control group (p < 0.05), while the other treatments presented intermediate values. At 28 d, the BWG was lower for the control, CNSL–Castor oil 0.5 kg/t, enramycin, and virginiamycin treatments than that in the tylosin treatment. The inclusion of CNSL–Castor oil at concentrations of 0.75 and 1 kg/t acted as an intermediate treatment (p < 0.05). For alpha diversity, using the Shannon index, it was possible to observe the effect of age, with substantial diversity at 42 d. The Firmicutes phylum had the highest abundance, with values between 84.33% and 95.16% at 42 d. Tylosin showed better performance indices than other treatments. CNSL–castor oil treatments with concentrations of 0.75 and 1 kg/t showed similar results to those of enramycin and virginiamycin. Furthermore, CNSL–castor oil acted as a modulator of intestinal microbiota, reducing the abundance of pathogenic bacteria.

Antimicrobial resistance is a major threat to public health. Antimicrobial use in animal husbandry is a major concern since it can favor an increase in antimicrobial resistance among farms. Herein, we aim to better understand and characterize the main resistome profiles in microbial communities found in pig farms. Sampling of swine manure was performed in two different timepoints (October 2019 and January 2020) in each of the 14 different swine farms, located in the mesoregion of Western Santa Catarina state in Brazil, a pole of swine product production of worldwide importance. Samples were divided into three groups: farms with the opened regimen and no usage of antimicrobials (F1; n = 10), farms with the closed regimen and usage of antimicrobials (F2; n = 16), and farms with the closed regimen and no usage of antimicrobials (F3; n = 2). The metagenomic evaluation was performed to obtain and identify genetic elements related to antimicrobial resistance using nanopore sequencing. We used ResistoXplorer software to perform composition, alpha and beta diversity, and clustering analysis. In addition, PCR reactions were performed to confirm the presence or absence of seven different beta-lactamase family genes and five phosphoethanolamine transferase gene variants clinically relevant. Our findings based on the identification of resistance genes at the mechanism level showed a prevalence of alteration of the drug target (72.3%) profile, followed by drug inactivation (17.5%) and drug efflux (10.1%). We identified predominantly aminoglycosides (45.3%), tetracyclines (15.9%), and multiclass (11,2%) resistance genes. PCoA analysis indicates differences between F1 and F2 profiles. F2 samples showed increased diversity when compared to the F1 group. In addition, herein we first report the identification of mcr-4 in a slurry sample (C1F1.1) in Santa Catarina State. In general, our findings reinforce that many factors on the practices of animal husbandry are involved in the resistome profile at the mechanism and class levels. Further studies to better understand microbiome and mobilome aspects of these elements are necessary to elucidate transmission pathways between different bacteria and environments.

Epitopes are portions of a protein that are recognized by antibodies. These small amino acid sequences represent a significant breakthrough in a branch of bioinformatics called immunoinformatics. Various software are available for linear B-cell epitope (BCE) prediction such as ABCPred, SVMTrip, EpiDope, and EpitopeVec; a well-known BCE predictor is BepiPred-2.0. However, despite the prediction, there are several essential steps, such as epitope assembly, evaluation, and searching for epitopes in other proteomes. Here, we present EpiBuilder ( https://epibuilder.sourceforge.io ), a user friendly software that assists in epitope assembly, classifying and searching using input results of BepiPred-2.0. EpiBuilder generates several output results from these data and supports a proteome-wide processing approach. In addition, this software provides the following features: Chou & Fasman beta-turn prediction, Emini surface accessibility prediction, Karplus and Schulz flexibility prediction, Kolaskar and Tongaonkar antigenicity, Parker hydrophilicity prediction, N-glycosylation domains, and hydropathy. These information generate a unique topology for each epitope, visually demonstrating its characteristics. The software can search the entire epitope sequence in various FASTA files, and it allows to use BLASTP to identify epitopes that eventually have sequence variations. As an EpiBuilder application, we developed a epitope dataset from the protozoan Trypanosoma brucei gambiense, the gram-positive bacterium Clostridioides difficile, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).