Here we present MARVEL, a tool for prediction of double-stranded DNA bacteriophage sequences in metagenomic bins. MARVEL uses a random forest machine learning approach. We trained the program on a dataset with 1,247 phage and 1,029 bacterial genomes, and tested it on a dataset with 335 bacterial and 177 phage genomes. We show that three simple genomic features extracted from contig sequences were sufficient to achieve a good performance in separating bacterial from phage sequences: gene density, strand shifts, and fraction of significant hits to a viral protein database. We compared the performance of MARVEL to that of VirSorter and VirFinder, two popular programs for predicting viral sequences. Our results show that all three programs have comparable specificity, but MARVEL achieves much better performance on the recall (sensitivity) measure. This means that MARVEL should be able to identify many more phage sequences in metagenomic bins than heretofore has been possible. In a simple test with real data, containing mostly bacterial sequences, MARVEL classified 58 out of 209 bins as phage genomes; other evidence suggests that 57 of these 58 bins are novel phage sequences. MARVEL is freely available at https://github.com/LaboratorioBioinformatica/MARVEL.

BACKGROUND Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was confirmed in Brazil in February 2020, the first cases were followed by an increase in the number of cases throughout the country, resulting in an important public health crisis that requires fast and coordinated responses. OBJECTIVES The objective of this work is to describe the isolation and propagation properties of SARS-CoV-2 isolates from the first confirmed cases of coronavirus disease 2019 (COVID-19) in Brazil. METHODS After diagnosis in patients that returned from Italy to the São Paulo city in late February by RT-PCR, SARS-CoV-2 isolates were obtained in cell cultures and characterised by full genome sequencing, electron microscopy and in vitro replication properties. FINDINGS The virus isolate was recovered from nasopharyngeal specimen, propagated in Vero cells (E6, CCL-81 and hSLAM), with clear cytopathic effects, and characterised by full genome sequencing, electron microscopy and in vitro replication properties. Virus stocks - viable (titre 2.11 × 10 6 TCID50/mL, titre 1.5 × 10 6 PFUs/mL) and inactivated from isolate SARS.CoV2/SP02.2020.HIAE.Br were prepared and set available to the public health authorities and the scientific community in Brazil and abroad. MAIN CONCLUSION We believe that the protocols for virus growth and studies here described and the distribution initiative may constitute a viable model for other developing countries, not only to help a rapid effective pandemic response, but also to facilitate and support basic scientific research.

Phages have a major impact on microbial populations. In this work, we discuss how predation, transduction, lysogeny, and phage domestication lead to symbio-centric genomic interactions between bacteria and phages, ranging from antagonistic to mutualistic. Furthermore, these interactions influence bacterial diversification and ecotype formation. We then propose an additional consideration in the form of a symbio-centric ecological speciation framework for bacteria. Our framework builds upon classical morphological and molecular taxonomy by also considering bacteria and their phages as a unit of evolutionary selection. This framework acknowledges the considerable effect that phage interaction has on bacterial genomic content, regulation, and evolution, and will advance our understanding of bacterial evolution.

BackgroundAmong viruses, bacteriophages are a group of special interest due to their capacity of infecting bacteria that are important for biotechnology and human health. Composting is a microbial-driven process in which complex organic matter is converted into humus-like substances. In thermophilic composting, the degradation activity is carried out primarily by bacteria and little is known about the presence and role of bacteriophages in this process.ResultsUsing Pseudomonas aeruginosa as host, we isolated three new phages from a composting operation at the Sao Paulo Zoo Park (Brazil). One of the isolated phages is similar to Pseudomonas phage Ab18 and belongs to the Siphoviridae YuA-like viral genus. The other two isolated phages are similar to each other and present genomes sharing low similarity with phage genomes in public databases; we therefore hypothesize that they belong to a new genus in the Podoviridae family. Detailed genomic descriptions and comparisons of the three phages are presented, as well as two new clusters of phage genomes in the Viral Orthologous Clusters database of large DNA viruses. We found sequences encoding homing endonucleases that disrupt a putative ribonucleotide reductase gene and an RNA polymerase subunit 2 gene in two of the phages. These findings provide insights about the evolution of two-subunits RNA polymerases and the possible role of homing endonucleases in this process. Infection tests on 30 different strains of bacteria reveal a narrow host range for the three phages, restricted to P. aeruginosa PA14 and three other P. aeruginosa clinical isolates. Biofilm dissolution assays suggest that these phages could be promising antimicrobial agents against P. aeruginosa PA14 infections. Analyses on composting metagenomic and metatranscriptomic data indicate association between abundance variations in both phage and host populations in the environment.ConclusionThe results about the newly discovered and described phages contribute to the understanding of tailed bacteriophage diversity, evolution, and role in the complex composting environment.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3729-z) contains supplementary material, which is available to authorized users.

Objectives Little is currently known about vaccine effectiveness (VE) for either two doses of Oxford-AstraZeneca (ChAdOx1) viral vector vaccine or CoronaVac inactivated viral vaccine followed by a third dose of mRNA vaccine (Pfizer/BioNTech) among healthcare workers (HCWs). Methods We conducted a retrospective cohort study among HCWs (aged ≥18 years) working in a private healthcare system in Brazil from January to December 2021. VE was defined as 1-IRR (incidence rate ratio), with IRR determined using Poisson models with the occurrence of laboratory-confirmed COVID-19 infection as the outcome, adjusting for age, sex, and job type. We compared those receiving viral vector or inactivated viral primary series (two doses) to those who received an mRNA booster. Results A total of 11,427 HCWs met the inclusion criteria. COVID-19 was confirmed in 31.5% of HCWs receiving two doses of CoronaVac vaccine vs. 0.9% of HCWs receiving two doses of CoronaVac vaccine with mRNA booster (p < 0.001), and 9.8% of HCWs receiving two doses of ChAdOx1 vaccine vs. 1% among HCWs receiving two doses of ChAdOx1 vaccine with mRNA booster (p < 0.001). In the adjusted analyses, the estimated VE was 92.0% for two CoronaVac vaccines plus mRNA booster, and 60.2% for two ChAdOx1 vaccines plus mRNA booster, when compared to those with no mRNA booster. Of 246 samples screened for mutations, 191 (77.6%) were Delta variants. Conclusions While two doses of ChAdOx1 or CoronaVac vaccines prevent COVID-19, the addition of a Pfizer/BioNTech booster provided significantly more protection.

The experimental determination of a bacteriophage host is a laborious procedure. For this reason, there is a pressing need for reliable computational predictions of bacteriophage hosts in phage research in general and in phage therapy in particular. Here, we present a new program called vHULK for phage host prediction based on 9,504 phage genome features. These features take into account alignment significance scores between predicted-protein sequences in the phage genomes and a curated database of viral protein families. The features were fed to a deep neural network, and four distinct models were trained to predict 61 different host genera and 52 host species. In random controlled test sets, the program obtained 99% and 98% accuracy values at the genus and species levels, respectively. On a validation dataset with 2,178 phage genomes, mean accuracies were 82% and 52% at the genus and species levels, respectively. When compared against other phage host prediction programs on the same validation dataset, vHULK achieved substantially better performance, therefore demonstrating that the program is an advance on the state-of-art in phage host prediction. vHULK is freely available at https://github.com/LaboratorioBioinformatica/vHULK.

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Summary Viruses are now recognized as important players in microbial dynamics and biogeochemical cycles in the oceans. Yet, compared with aquatic ecosystems, virus discovery in terrestrial ecosystems has been challenging partly due to the inherent complexity of soils. To expand our understanding of soil viruses and their putative contributions to soil microbial processes, we analysed metagenomes of community‐level virus‐enriched suspensions by tangential flow filtration obtained from two French agricultural soils. We found viral sequences representing a total of 239 viral operational taxonomic units that corresponded to 29.5% of the mapping reads in the metagenomic datasets. The analysis of their genomic sequences revealed novel virocell metabolic potential with implications to virus–host interactions, carbon cycling, plant‐beneficial functions in the rhizosphere, horizontal gene transfer and other relevant microbial strategies applied to survive in soils.