Kyoto University microbiome researcher Hiroyuki Ogata says that the recent work2,3 further connects RNA viruses and the carbon pump, which affects the Earth’s biogeochemical cycles and thus its climate. And it sheds light on the diversity, evolution and ecology of RNA viruses, which has not previously been possible through applying the techniques of traditional DNA-based metagenomics. The team found many new lineages at the phylum-level by using “highly sensitive” computational approaches.
It’s possible to assess the ecosystem impact of viruses by inferring auxiliary metabolic genes (AMGs). AMGs hint at the ways RNA viruses manipulate the physiology of their hosts as they seek to maximize production of more virus through the host. As Jian explains, labs have identified a variety of AMGs that are encoded by DNA viruses and, he says, it’s “well-recognized” that AMGs probably play a role in marine ecosystems. It was unknown if AMGs could be found in RNA viruses, which the recent Science paper2 has now established, he says. Jian sees this work as providing “a very important foundational dataset” for exploring questions connected to AMGs. “In my opinion, if more long-sequence or complete marine RNA virus genomes can be obtained in the future, and they can be further connected with specific hosts, it will greatly promote the understanding of the ecological impact of RNA viruses in the oceans.”
To tease out AMGs, the scientists used a variety of tools, such as viral identification software for both DNA and RNA viruses, says Wainaina. The ones for DNA viruses are available on Cyverse, and the protocols for the tools from the Sullivan lab are on protocols.io. One method for RNA viruses is in progress and will be soon available on Cyverse, he says. DNA viral identification tools include VirSorter2, a pipeline for identifying viral sequence from metagenomics data, and the protocol for using this and other tools are also on protocols.io. To identify AMGs from viral sequence that had been identified through VirSorter, the team used use DRAM-v, a software tool from the lab of microbiome researcher Kelly Wrighton at Colorado State University. Her group had created Distilled and Refined Annotation of Metabolism (DRAM), a framework to resolve metabolic information from microbial data. The companion tool DRAM-v is for viruses and can be applied to metagenomic data sets for annotating metagenomics-based assembled genomes, for example through the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, and to contiguous viral sequences identified by VirSorter.
The hunt for AMGs is one instance in which the team needed to determine in each case whether a sequence was likely ‘stolen’ from host cells, says Dominguez-Huerta. RNA viral genomes are less than 40 kilobases long and usually have complicated genomic organization, both in a structural genomics sense related to the physical arrangement of genes along the viral genome and in a functional sense in terms of transcription and translation: there are overlapping genes, frameshifts and more, all of which makes this kind of annotation difficult. And sometimes information in the annotation databases is wrong and indicates that a match is cellular when it is in fact viral. Thus, to find AMGs, “we don’t have a defined clean methodology automated in a pipeline yet,” he says. It remains a time-consuming task. Assigning putative function to the protein sequences encoded by AMGs also involves checking the literature and comparing different annotation sources.
Dominguez-Huerta says he and the team were glad they could assemble AMG functionalities to suggest the range of ways in which RNA viruses manipulate the metabolisms of their hosts—from photosynthesis to central carbon metabolism to vacuolar digestion and RNA repair. This overview let them see how some AMGs are repeated across different viruses across the oceans. Finding AMGs in long-read sequence is what he calls a “fire test” for the lab. To avoid ‘false AMGs’ from unreliable matches, they use BLASTP, the Basic Alignment Search Tool that compares a protein query sequence to a protein database.
“I am fascinated by the ability of viruses to metabolic reprogram not only their hosts but more importantly at the ecosystem level,” says Wainaina. It is probable that the AMGs the team identified “are a central cog in microbial metabolism networks.” Current and future modeling efforts will hopefully provide insights into the ecosystem roles of viruses—both DNA viruses and RNA viruses—and on a global scale both within the ocean ecosystem and beyond.
Host inference is challenging, says Dominguez-Huerta, because, for example, viruses with RNA genomes do not share genetic information with their host genomic DNA the way dsDNA viruses do when they infect bacteria. That means there is no clear signal to be derived from the host genome to help one guess the possible host. But sometimes RNA viruses do integrate into host genomes, and those, likely more accidental, events were sufficient for the scientists to capture some signal to infer hosts. “We also performed statistical co-occurrence analytics using abundances to infer the hosts with certain success,” he says.
Unlike dsDNA viruses, RNA viruses infect mostly eukaryotes, from protists and fungi to invertebrates and fish larvae; only a minority infect bacteria. Overall, the team has been able to capture “a picture of dsDNA viruses infecting prokaryotes and RNA viruses infecting eukaryotes in the oceans, complementing each other in their marine hosts,” says Dominguez-Huerta. The fact that the scientists can infer “that RNA viruses can steal genes from the host,” in the form of AMGs, to then reprogram host metabolism matters not only as scientists complete the picture of how viruses directly tune the activity of hosts during infection, but also in regard to how this influences biogeochemical cycles, he says. “We think that these AMGs are incorporated into the RNA virus genomes from cellular mRNA transcripts by non-homologous recombination,” he says. This gives, in his view, a new picture of RNA viruses, which, despite their small genome sizes, can squeeze in protein-coding genes. Such proteins could be sufficient to boost the production of virus particles per infected cell, perhaps increasing viral fitness in the difficult conditions of the oligotrophic open ocean and letting the viruses better propagate in the environment.
More generally, says Dominguez-Huerta, capturing RNA from ocean samples is difficult, because RNA is physically fragile and degrades rapidly. When digging into metatranscriptomic data, which include the RNA from plankton and RNA from other organisms, less than 1% of this RNA is likely to be viral RNA, he says. Previously, some labs have first purified RNA from samples, enriched it for replicating RNA viruses and then applied a method called dsRNA-seq to recover dsRNA virus sequence and replicate sequences from single-stranded RNA viruses. For future ocean RNA virus projects, he says that the lab is currently working on a wet-lab method to purify RNA virus particles from seawater to solve the challenges of obtaining viral RNA for analysis.
Source: Ecology - nature.com
