Viruses are key players regulating microbial ecosystems. Exploration of viral assemblages is now possible thanks to the development of metagenomics, the most powerful tool available for studying viral ecology and discovering new viruses. Unfortunately, several sources of bias lead to the misrepresentation of certain viruses within metagenomics workflows, hindering the shift from merely descriptive studies towards quantitative comparisons of communities. Therefore, benchmark studies on virus enrichment and random amplification protocols are required to better understand the sources of bias. We assessed the bias introduced by viral enrichment on mock assemblages composed of seven DNA viruses, and the bias from random amplification methods on human saliva DNA viromes, using qPCR and deep sequencing, respectively. While iodixanol cushions and 0.45 μm filtration preserved the original composition of nuclease-protected viral genomes, low-force centrifugation and 0.22 μm filtration removed large viruses. Comparison of unamplified and randomly amplified saliva viromes revealed that multiple displacement amplification (MDA) induced stochastic bias from picograms of DNA template. However, the type of bias shifted to systematic using 1 ng, with only a marginal influence by amplification time. Systematic bias consisted of over-amplification of small circular genomes, and under-amplification of those with extreme GC content, a negative bias that was shared with the PCR-based sequence-independent, single-primer amplification (SISPA) method. MDA based on random priming provided by a DNA primase activity slightly outperformed those based on random hexamers and SISPA, which may reflect differences in ability to handle sequences with extreme GC content. SISPA viromes showed uneven coverage profiles, with high coverage peaks in regions with low linguistic sequence complexity. Despite misrepresentation of certain viruses after random amplification, ordination plots based on dissimilarities among contig profiles showed perfect overlapping of related amplified and unamplified saliva viromes and strong separation from unrelated saliva viromes. This result suggests that random amplification bias has a minor impact on beta diversity studies. Benchmark analyses of mock and natural communities of viruses improve understanding and mitigate bias in metagenomics surveys. Bias induced by random amplification methods has only a minor impact on beta diversity studies of human saliva viromes.

Marine viruses play a critical role not only in the global geochemical cycles but also in the biology and evolution of their hosts. Despite their importance, viral diversity remains underexplored mostly due to sampling and cultivation challenges. Direct sequencing approaches such as viromics has provided new insights into the marine viral world. As a complementary approach, we analysed 24 microbial metagenomes (>0.2 μm size range) obtained from six sites in the Mediterranean Sea that vary by depth, season and filter used to retrieve the fraction. Filter-size comparison showed a significant number of viral sequences that were retained on the larger-pore filters and were different from those found in the viral fraction from the same sample, indicating that some important viral information is missing using only assembly from viromes. Besides, we were able to describe 1,323 viral genomic fragments that were more than 10Kb in length, of which 36 represented complete viral genomes including some of them retrieved from a cross-assembly from different metagenomes. Host prediction based on sequence methods revealed new phage groups belonging to marine prokaryotes like SAR11, Cyanobacteria or SAR116. We also identified the first complete virophage from deep seawater and a new endemic clade of the recently discovered Marine group II Euryarchaeota virus. Furthermore, analysis of viral distribution using metagenomes and viromes indicated that most of the new phages were found exclusively in the Mediterranean Sea and some of them, mostly the ones recovered from deep metagenomes, do not recruit in any database probably indicating higher variability and endemicity in Mediterranean bathypelagic waters. Together these data provide the first detailed picture of genomic diversity, spatial and depth variations of viral communities within the Mediterranean Sea using metagenome assembly. These data provided a glimpse of the genetic diversity and variability of viral sequences without introducing the amplification biases produced when studying viromes. Metagenomes contain abundant viral material due to cells retrieved while undergoing viral lysis or as temperate viruses inserted in the chromosome. Using very stringent criteria, we have managed to assemble large viral genomes from Mediterranean metagenomes. This large-scale study using direct assembly from metagenomes, i.e. from the cellular fraction, clearly shows that metagenomes are an important tool to study environmental viral communities containing complementary information, which is missing in viromes, that should be taken into consideration when studying viral genetic diversity. Thus, in this study we have described more than 1,300 viral genomic fragments larger than 10Kb, of which 36 represented complete viral genomes, including the first deep sea virophage, one novel Marine Group II euryarchaeota virus (magrovirus) and others infecting Cyanobacteria, SAR11 or SAR116. All these new viral contigs were obtained from a collection of 24 metagenomes representing a broad range of geographical and ecological biomes from the Mediterranean Sea.

Macrolides are broad-spectrum antibiotics used to treat a range of infections. Resistance to macrolides is often conferred by mobile resistance genes encoding Erm methyltransferases or Mph phosphotransferases. New erm and mph genes keep being discovered in clinical settings but their origins remain unknown, as is the type of macrolide resistance genes that will appear in the future. In this study, we used optimized hidden Markov models to characterize the macrolide resistome. Over 16 terabases of genomic and metagenomic data, representing a large taxonomic diversity (11 030 species) and diverse environments (1944 metagenomic samples), were searched for the presence of erm and mph genes. From this data, we predicted 28 340 macrolide resistance genes encoding 2892 unique protein sequences, which were clustered into 663 gene families (<70 % amino acid identity), of which 619 (94 %) were previously uncharacterized. This included six new resistance gene families, which were located on mobile genetic elements in pathogens. The function of ten predicted new resistance genes were experimentally validated in Escherichia coli using a growth assay. Among the ten tested genes, seven conferred increased resistance to erythromycin, with five genes additionally conferring increased resistance to azithromycin, showing that our models can be used to predict new functional resistance genes. Our analysis also showed that macrolide resistance genes have diverse origins and have transferred horizontally over large phylogenetic distances into human pathogens. This study expands the known macrolide resistome more than ten-fold, provides insights into its evolution, and demonstrates how computational screening can identify new resistance genes before they become a significant clinical problem.

Background: Most proteins have evolved in specific cellular compartments that limit their functions and potential interactions. On the other hand, motifs define amino acid arrangements conserved between protein family members and represent powerful tools for assigning function to protein sequences. The ideal motif would identify all members of a protein family but in practice many motifs identify both family members and unrelated proteins, referred to as True Positive (TP) and False Positive (FP) sequences, respectively. Results: To address the relationship between protein motifs, protein function and cellular localization, we systematically assigned subcellular localization data to motif sequences from the comprehensive PROSITE sequence motif database. Using this data we analyzed relationships between localization and function. We find that TPs and FPs have a strong tendency to localize in different compartments. When multiple localizations are considered, TPs are usually distributed between related cellular compartments. We also identified cases where FPs are concentrated in particular subcellular regions, indicating possible functional or evolutionary relationships with TP sequences of the same motif. Conclusions: Our findings suggest that the systematic examination of subcellular localization has the potential to uncover evolutionary and functional relationships between motif-containing sequences. We believe that this type of analysis complements existing motif annotations and could aid in their interpretation. Our results shed light on the evolution of cellular organelles and potentially establish the basis for new subcellular localization and function prediction algorithms.

Molluscum contagiosum virus (MCV) is the sole member of the Molluscipoxvirus genus and causes a highly prevalent human disease of the skin characterized by the formation of a variable number of lesions that can persist for prolonged periods of time. Two major genotypes, subtype 1 and subtype 2, are recognized, although currently only a single complete genomic sequence corresponding to MCV subtype 1 is available. Using next-generation sequencing techniques, we report the complete genomic sequence of four new MCV isolates, including the first one derived from a subtype 2. Comparisons suggest a relatively distant evolutionary split between both MCV subtypes. Further, our data illustrate concurrent circulation of distinct viruses within a population and reveal the existence of recombination events among them. These results help identify a set of MCV genes with potentially relevant roles in molluscum contagiosum epidemiology and pathogenesis.