Abstract Viruses of the phylum Nucleocytoviricota are ubiquitous in ocean waters and play important roles in shaping the dynamics of marine ecosystems. In this study, we leveraged the bioGEOTRACES metagenomic dataset collected across the Atlantic and Pacific Oceans to investigate the biogeography of these viruses in marine environments. We identified 330 viral genomes, including 212 in the order Imitervirales and 54 in the order Algavirales. We found that most viruses appeared to be prevalent in shallow waters (<150 m), and that viruses of the Mesomimiviridae (Imitervirales) and Prasinoviridae (Algavirales) are by far the most abundant and diverse groups in our survey. Five mesomimiviruses and one prasinovirus are particularly widespread in oligotrophic waters; annotation of these genomes revealed common stress response systems, photosynthesis-associated genes, and oxidative stress modulation genes that may be key to their broad distribution in the pelagic ocean. We identified a latitudinal pattern in viral diversity in one cruise that traversed the North and South Atlantic Ocean, with viral diversity peaking at high latitudes of the northern hemisphere. Community analyses revealed three distinct Nucleocytoviricota communities across latitudes, categorized by latitudinal distance towards the equator. Our results contribute to the understanding of the biogeography of these viruses in marine systems.
more »
« less
virMine: automated detection of viral sequences from complex metagenomic samples
Metagenomics has enabled sequencing of viral communities from a myriad of different environments. Viral metagenomic studies routinely uncover sequences with no recognizable homology to known coding regions or genomes. Nevertheless, complete viral genomes have been constructed directly from complex community metagenomes, often through tedious manual curation. To address this, we developed the software tool virMine to identify viral genomes from raw reads representative of viral or mixed (viral and bacterial) communities. virMine automates sequence read quality control, assembly, and annotation. Researchers can easily refine their search for a specific study system and/or feature(s) of interest. In contrast to other viral genome detection tools that often rely on the recognition of viral signature sequences, virMine is not restricted by the insufficient representation of viral diversity in public data repositories. Rather, viral genomes are identified through an iterative approach, first omitting non-viral sequences. Thus, both relatives of previously characterized viruses and novel species can be detected, including both eukaryotic viruses and bacteriophages. Here we present virMine and its analysis of synthetic communities as well as metagenomic data sets from three distinctly different environments: the gut microbiota, the urinary microbiota, and freshwater viromes. Several new viral genomes were identified and annotated, thus contributing to our understanding of viral genetic diversity in these three environments.
more »
« less
- Award ID(s):
- 1149387
- PAR ID:
- 10092508
- Date Published:
- Journal Name:
- PeerJ
- Volume:
- 7
- ISSN:
- 2167-8359
- Page Range / eLocation ID:
- e6695
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)Giant viruses are widespread in the biosphere and play important roles in biogeochemical cycling and host genome evolution. Also known as nucleo-cytoplasmic large DNA viruses (NCLDVs), these eukaryotic viruses harbor the largest and most complex viral genomes known. Studies have shown that NCLDVs are frequently abundant in metagenomic datasets, and that sequences derived from these viruses can also be found endogenized in diverse eukaryotic genomes. The accurate detection of sequences derived from NCLDVs is therefore of great importance, but this task is challenging owing to both the high level of sequence divergence between NCLDV families and the extraordinarily high diversity of genes encoded in their genomes, including some encoding for metabolic or translation-related functions that are typically found only in cellular lineages. Here, we present ViralRecall, a bioinformatic tool for the identification of NCLDV signatures in ‘omic data. This tool leverages a library of giant virus orthologous groups (GVOGs) to identify sequences that bear signatures of NCLDVs. We demonstrate that this tool can effectively identify NCLDV sequences with high sensitivity and specificity. Moreover, we show that it can be useful both for removing contaminating sequences in metagenome-assembled viral genomes as well as the identification of eukaryotic genomic loci that derived from NCLDV. ViralRecall is written in Python 3.5 and is freely available on GitHub: https://github.com/faylward/viralrecall.more » « less
-
The diversity of viruses identified from the various niches of the human oral cavity—from saliva to dental plaques to the surface of the tongue—has accelerated in the age of metagenomics. This rapid expansion demonstrates that our understanding of oral viral diversity is incomplete, with only a few studies utilizing passive drool collection in conjunction with metagenomic sequencing methods. For this pilot study, we obtained 14 samples from healthy staff members working at the Duke Lemur Center (Durham, NC, USA) to determine the viral diversity that can be identified in passive drool samples from humans. The complete genomes of 3 anelloviruses, 9 cressdnaviruses, 4 Caudoviricetes large bacteriophages, 29 microviruses, and 19 inoviruses were identified in this study using high-throughput sequencing and viral metagenomic workflows. The results presented here expand our understanding of the vertebrate-infecting and microbe-infecting viral diversity of the human oral virome in North Carolina (USA).more » « less
-
Viruses play crucial roles in the ecology of microbial communities, yet they remain relatively understudied in their native environments. Despite many advancements in high-throughput whole-genome sequencing (WGS), sequence assembly, and annotation of viruses, the reconstruction of full-length viral genomes directly from metagenomic sequencing is possible only for the most abundant phages and requires long-read sequencing technologies. Additionally, the prediction of their cellular hosts remains difficult from conventional metagenomic sequencing alone. To address these gaps in the field and to accelerate the study of viruses directly in their native microbiomes, we developed an end-to-end bioinformatics platform for viral genome reconstruction and host attribution from metagenomic data using proximity-ligation sequencing (i.e., Hi-C). We demonstrate the capabilities of the platform by recovering and characterizing the metavirome of a variety of metagenomes, including a fecal microbiome that has also been sequenced with accurate long reads, allowing for the assessment and benchmarking of the new methods. The platform can accurately extract numerous near-complete viral genomes even from highly fragmented short-read assemblies and can reliably predict their cellular hosts with minimal false positives. To our knowledge, this is the first software for performing these tasks. Being significantly cheaper than long-read sequencing of comparable depth, the incorporation of proximity-ligation sequencing in microbiome research shows promise to greatly accelerate future advancements in the field.more » « less
-
metaviralSPAdes: Assembly of Viruses From Metagenomic Data Abstract Motivation: Although the set of currently known viruses has been steadily expanding, only a tiny fraction of the Earth's virome has been sequenced so far. Shotgun metagenomic sequencing provides an opportunity to reveal novel viruses but faces the computational challenge of identifying viral genomes that are often difficult to detect in metagenomic assemblies. Results: We describe a metaviralSPAdes tool for identifying viral genomes in metagenomic assembly graphs that is based on analyzing variations in the coverage depth between viruses and bacterial chromosomes. We benchmarked metaviralSPAdes on diverse metagenomic datasets, verified our predictions using a set of virus-specific Hidden Markov Models, and demonstrated that it improves on the state-of-the-art viral identification pipelines. Availability: metaviralSPAdes includes viralAssembly, viralVerify, and viralComplete modules that are available as standalone packages: https://github.com/ablab/spades/tree/metaviral_publication, https://github.com/ablab/viralVerify/ and https://github.com/ablab/viralComplete/. Supplementary information: Supplementary data are available at Bioinformatics online.more » « less