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: Bacteriophages, the viruses infecting bacteria, are biological entities that can control their host populations. The ecological relevance of phages for microbial systems has been widely explored in aquatic environments, but the current understanding of the role of phages in terrestrial ecosystems remains limited. Here, our objective was to quantify the extent to which phages drive the assembly and functioning of soil bacterial communities. We performed a reciprocal transplant experiment using natural and sterilized soil incubated with different combinations of two soil microbial communities, challenged against native and non-native phage suspensions as well as against a cocktail of phage isolates. We tested three different community assembly scenarios by adding phages: (a) during soil colonization, (b) after colonization, and (c) in natural soil communities. One month after inoculation with phage suspensions, bacterial communities were assessed by 16S rRNA amplicon gene sequencing. Results: By comparing the treatments inoculated with active versus autoclaved phages, our results show that changes in phage pressure have the potential to impact soil bacterial community composition and diversity. We also found a positive effect of active phages on the soil ammonium concentration in a few treatments, which indicates that increased phage pressure may also be important for soil functions. Conclusions: Overall, the present work contributes to expand the current knowledge about soil phages and provide some empirical evidence supporting their relevance for soil bacterial community assembly and functioning.

This study focused on the effects of organic and inorganic amendments and straw retention on the microbial biomass (MB) and taxonomic groups of bacteria in sugarcane-cultivated soils in a greenhouse mesocosm experiment monitored for gas emissions and chemical factors. The experiment consisted of combinations of synthetic nitrogen (N), vinasse (V; a liquid waste from ethanol production), and sugarcane-straw blankets. Increases in CO2-C and N2O-N emissions were identified shortly after the addition of both N and V to the soils, thus increasing MB nitrogen (MB-N) and decreasing MB carbon (MB-C) in the N+V-amended soils and altering soil chemical factors that were correlated with the MB. Across 57 soil metagenomic datasets, Actinobacteria (31.5%), Planctomycetes (12.3%), Deltaproteobacteria (12.3%), Alphaproteobacteria (12.0%) and Betaproteobacteria (11.1%) were the most dominant bacterial groups during the experiment. Differences in relative abundance of metagenomic sequences were mainly revealed for Acidobacteria, Actinobacteria, Gammaproteobacteria and Verrucomicrobia with regard to N+V fertilization and straw retention. Differential abundances in bacterial groups were confirmed using 16S rRNA gene-targeted phylum-specific primers for real-time PCR analysis in all soil samples, whose results were in accordance with sequence data, except for Gammaproteobacteria. Actinobacteria were more responsive to straw retention with Rubrobacterales, Bifidobacteriales and Actinomycetales related to the chemical factors of N+V-amended soils. Acidobacteria subgroup 7 and Opitutae, a verrucomicrobial class, were related to the chemical factors of soils without straw retention as a surface blanket. Taken together, the results showed that MB-C and MB-N responded to changes in soil chemical factors and CO2-C and N2O-N emissions, especially for N+V-amended soils. The results also indicated that several taxonomic groups of bacteria, such as Acidobacteria, Actinobacteria and Verrucomicrobia, and their subgroups acted as early-warning indicators of N+V amendments and straw retention in sugarcane-cultivated soils, which can alter the soil chemical factors.