BACKGROUND Gram-negative and Gram-positive bacteria produce beta-lactamase as factors to overcome beta-lactam antibiotics, causing their hydrolysis and impaired antimicrobial action. Class A beta-lactamase contains the chromosomal sulfhydryl reagent variable (SHV, point mutation variants of SHV-1), LEN (Klebsiella pneumoniae strain LEN-1), and other K. pneumoniae beta-lactamase (OKP) found mostly in Klebsiella’s phylogroups. The SHV known as extended-spectrum β-lactamase can inactivate most beta-lactam antibiotics. Class A also includes the worrisome plasmid-encoded Klebsiella pneumoniae carbapenemase (KPC-2), a carbapenemase that can inactivate most beta-lactam antibiotics, carbapenems, and some beta-lactamase inhibitors. OBJECTIVES So far, there is no 3D crystal structure for OKP-B, so our goal was to perform structural characterisation and molecular docking studies of this new enzyme. METHODS We applied a homology modelling method to build the OKP-B-6 structure, which was compared with SHV-1 and KPC-2 according to their electrostatic potentials at the active site. Using the DockThor-VS, we performed molecular docking of the SHV-1 inhibitors commercially available as sulbactam, tazobactam, and avibactam against the constructed model of OKP-B-6. FINDINGS From the point of view of enzyme inhibition, our results indicate that OKP-B-6 should be an extended-spectrum beta-lactamase (ESBL) susceptible to the same drugs as SHV-1. MAIN CONCLUSIONS This conclusion advantageously impacts the clinical control of the bacterial pathogens encoding OKP-B in their genome by using any effective, broad-spectrum, and multitarget inhibitor against SHV-containing bacteria.

BACKGROUND During routine Coronavirus disease 2019 (COVID-19) diagnosis, an unusually high viral load was detected by reverse transcription real-time polymerase chain reaction (RT-qPCR) in a nasopharyngeal swab sample collected from a patient with respiratory and neurological symptoms who rapidly succumbed to the disease. Therefore we sought to characterise the infection. OBJECTIVES We aimed to determine and characterise the etiological agent responsible for the poor outcome. METHODS Classical virological methods, such as plaque assay and plaque reduction neutralisation test combined with amplicon-based sequencing, as well as a viral metagenomic approach, were performed to characterise the etiological agents of the infection. FINDINGS Plaque assay revealed two distinct plaque phenotypes, suggesting either the presence of two severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains or a productive coinfection of two different species of virus. Amplicon-based sequencing did not support the presence of any SARS-CoV-2 genetic variants that would explain the high viral load and suggested the presence of a single SARS-CoV-2 strain. Nonetheless, the viral metagenomic analysis revealed that Coronaviridae and Herpesviridae were the predominant virus families within the sample. This finding was confirmed by a plaque reduction neutralisation test and PCR. MAIN CONCLUSIONS We characterised a productive coinfection of SARS-CoV-2 and Herpes simplex virus 1 (HSV-1) in a patient with severe symptoms that succumbed to the disease. Although we cannot establish the causal relationship between the coinfection and the severity of the clinical case, this work serves as a warning for future studies focused on the interplay between SARS-CoV-2 and HSV-1 coinfection and COVID-19 severity.

BACKGROUND Serological evidence of West Nile virus (WNV) infection has been reported in different regions of Brazil from equine and human hosts but the virus had never been isolated in the country. OBJECTIVES We sought to identify the viral etiology of equine encephalitis in Espírito Santo state. METHODS We performed viral culture in C6/36 cells, molecular detection of WNV genome, histopathology and immunohistochemistry from horse cerebral tissue. We also carried out sequencing, phylogenetic analysis and molecular clock. FINDINGS Histopathologic analysis from horse cerebral tissue showed injury related to encephalitis and WNV infection was confirmed by immunohistochemistry. The virus was detected by reverse transcription quantitative polymerase chain reaction (RT-qPCR) from brain tissue and subsequently isolated in C6/36 cells. WNV full-length genome was sequenced showing the isolated strain belongs to lineage 1a. The molecular clock indicated that Brazilian WNV strain share the same common ancestor that were circulating in US during 2002-2005. MAIN CONCLUSIONS Here we report the first isolation of WNV in Brazil from a horse with neurologic disease, which was clustered into lineage 1a with others US WNV strains isolated in beginning of 2000’s decade.

ABSTRACT The soil represents the main source of novel biocatalysts and biomolecules of industrial relevance. We searched for hydrolases in silico in four shotgun metagenomes (4,079,223 sequences) obtained in a 13-year field trial carried out in southern Brazil, under the no-tillage (NT), or conventional tillage (CT) managements, with crop succession (CS, soybean/wheat), or crop rotation (CR, soybean/maize/wheat/lupine/oat). We identified 42,631 hydrolases belonging to five classes by comparing with the KEGG database, and 44,928 sequences by comparing with the NCBI-NR database. The abundance followed the order: lipases > laccases > cellulases > proteases > amylases > pectinases. Statistically significant differences were attributed to the tillage system, with the NT showing about five times more hydrolases than the CT system. The outstanding differences can be attributed to the management of crop residues, left on the soil surface in the NT, and mechanically broken and incorporated into the soil in the CT. Differences between the CS and the CR were slighter, 10% higher for the CS, but not statistically different. Most of the sequences belonged to fungi (Verticillium, and Colletotrichum for lipases and laccases, and Aspergillus for proteases), and to the archaea Sulfolobus acidocaldarius for amylases. Our results indicate that agricultural soils under conservative managements may represent a hotspot for bioprospection of hydrolases.

Abstract Rivers and streams are important reservoirs of freshwater for human consumption. These ecosystems are threatened by increasing urbanization, because raw sewage discharged into them alters their nutrient content and may affect the composition of their microbial community. In the present study, we investigate the taxonomic and functional profile of the microbial community in an urban lotic environment. Samples of running water were collected at two points in the São Pedro stream: an upstream preserved and non-urbanized area, and a polluted urbanized area with discharged sewage. The metagenomic DNA was sequenced by pyrosequencing. Differences were observed in the community composition at the two sites. The non-urbanized area was overrepresented by genera of ubiquitous microbes that act in the maintenance of environments. In contrast, the urbanized metagenome was rich in genera pathogenic to humans. The functional profile indicated that the microbes act on the metabolism of methane, nitrogen and sulfur, especially in the urbanized area. It was also found that virulence/defense (antibiotic resistance and metal resistance) and stress response-related genes were disseminated in the urbanized environment. The structure of the microbial community was altered by uncontrolled anthropic interference, highlighting the selective pressure imposed by high loads of urban sewage discharged into freshwater environments.

An online scheme to assign Stenotrophomonas isolates to genomic groups was developed using the multilocus sequence analysis (MLSA), which is based on the DNA sequencing of selected fragments of the housekeeping genes ATP synthase alpha subunit (atpA), the recombination repair protein (recA), the RNA polymerase alpha subunit (rpoA) and the excision repair beta subunit (uvrB). This MLSA-based scheme was validated using eight of the 10 Stenotrophomonas species that have been previously described. The environmental and nosocomial Stenotrophomonas strains were characterised using MLSA, 16S rRNA sequencing and DNA-DNA hybridisation (DDH) analyses. Strains of the same species were found to have greater than 95% concatenated sequence similarity and specific strains formed cohesive readily recognisable phylogenetic groups. Therefore, MLSA appeared to be an effective alternative methodology to amplified fragment length polymorphism fingerprint and DDH techniques. Strains of Stenotrophomonas can be readily assigned through the open database resource that was developed in the current study (www.steno.lncc.br/).

Bacterial cell division has been studied mainly in model systems such as Escherichia coli and Bacillus subtilis, where it is described as a complex process with the participation of a group of proteins which assemble into a multiprotein complex called the septal ring. Mycoplasmas are cell wall-less bacteria presenting a reduced genome. Thus, it was important to compare their genomes to analyze putative genes involved in cell division processes. The division and cell wall (dcw) cluster, which in E. coli and B. subtilis is composed of 16 and 17 genes, respectively, is represented by only three to four genes in mycoplasmas. Even the most conserved protein, FtsZ, is not present in all mycoplasma genomes analyzed so far. A model for the FtsZ protein from Mycoplasma hyopneumoniae and Mycoplasma synoviae has been constructed. The conserved residues, essential for GTP/GDP binding, are present in FtsZ from both species. A strong conservation of hydrophobic amino acid patterns is observed, and is probably necessary for the structural stability of the protein when active. M. synoviae FtsZ presents an extended amino acid sequence at the C-terminal portion of the protein, which may participate in interactions with other still unknown proteins crucial for the cell division process.

Restriction and Modification (R-M) systems are present in all Mycoplasma species sequenced so far. The presence of these genes poses barriers to gene transfer and could protect the cell against phage infections. The number and types of R-M genes between different Mycoplasma species are variable, which is characteristic of a polymorphism. The majority of the CDSs code for Type III R-M systems and particularly for methyltransferase enzymes, which suggests that functions other than the protection against the invasion of heterologous DNA may exist. A possible function of these enzymes could be the protection against the invasion of other but similar R-M systems. In Mycoplasma hyopneumoniae strain J, three of the putative methyltransferase genes were clustered in a region forming a genomic island. Many R-M CDSs were mapped in the vicinity of transposable elements suggesting an association between these genes and reinforcing the idea of R-M systems as mobile selfish DNA. Also, many R-M genes present repeats within their coding sequences, indicating that their expression is under the control of phase variation mechanisms. Altogether, these data suggest that R-M systems are a remarkable characteristic of Mycoplasma species and are probably involved in the adaptation of these bacteria to different environmental conditions.

Mollicutes are cell wall-less bacteria with a genome characterized by its small size. Chromosomal rearrangements help these organisms evade host immune surveillance and hence cause disease. Our goal was to determine genes shared by Mollicutes genomes using the bidirectional best hit methodology. The twelve studied Mollicutes share 210 genes, most of which (> 60%) fall into the following COG categories: translation, ribosomal structure and biogenesis; DNA replication, recombination and repair; nucleotide transport and metabolism and energy production and conversion. Thirty Mollicute-specific genes were identified, 22 of them previously described as essential genes in Mycoplasma genitalium.

Pattern recognition is an important process for gene localization in genomes. The ribosome binding sites are signals that can help in the identification of a gene. It is difficult to find these signals in the genome through conventional methods because they are highly degenerated. Artificial Neural Networks is the approach used in this work to address this problem.