Quantitative Assessment of Nucleocytoplasmic Large DNA Virus and Host Interactions Predicted by Co-occurrence Analyses

Abstract

Nucleocytoplasmic large DNA viruses (NCLDVs) are highly diverse and abundant in marine environments. However, the knowledge of their hosts is limited because only a few NCLDVs have been isolated so far. Taking advantage of the recent large-scale marine metagenomics census, in silico host prediction approaches are expected to fill the gap and further expand our knowledge of virus-host relationships for unknown NCLDVs. In this study, we built co-occurrence networks of NCLDVs and eukaryotic taxa to predict virus-host interactions using Tara Oceans sequencing data. Using the positive likelihood ratio to assess the performance of host prediction for NCLDVs, we benchmarked several co-occurrence approaches and demonstrated an increase in the odds ratio of predicting true positive relationships 4-fold compared to random host predictions. To further refine host predictions from high-dimensional co-occurrence networks, we developed a phylogeny-informed filtering method, Taxon Interaction Mapper, and showed it further improved the prediction performance by 12-fold. Finally, we inferred virophage-NCLDV networks to corroborate that co-occurrence approaches are effective for predicting interacting partners of NCLDVs in marine environments. IMPORTANCE NCLDVs can infect a wide range of eukaryotes, although their life cycle is less dependent on hosts compared to other viruses. However, our understanding of NCLDV-host systems is highly limited because few of these viruses have been isolated so far. Co-occurrence information has been assumed to be useful to predict virus-host interactions. In this study, we quantitatively show the effectiveness of co-occurrence inference for NCLDV host prediction. We also improve the prediction performance with a phylogeny-guided method, which leads to a concise list of candidate host lineages for three NCLDV families. Our results underpin the usage of co-occurrence approaches for the metagenomic exploration of the ecology of this diverse group of viruses.

Tight association between microbial eukaryote and giant virus communities in the Arctic Ocean

“…Additionally, viruses have been proposed as a key factor influencing the protist communities as they can impose top–down controls on their specific host populations (Nagasaki et al 1994; Brussaard et al 1996). Recent studies using Mantel statistics or co‐occurrence network analysis indicated that Imitervirales are tightly associated with a variety of protist lineages at a global level (Endo et al 2020; Meng et al 2021), although only little of them have been isolated (Mihara et al 2018). Our 18S rDNA barcoding revealed that chlorophytes and haptophytes, both of which are known host lineages of Imitervirales , were major protists in the small‐size fraction.…”

“…Our 18S rDNA barcoding revealed that chlorophytes and haptophytes, both of which are known host lineages of Imitervirales, were major protists in the small-size fraction. Although the dominating clades in the large-sized eukaryotic communities such as dinoflagellates, ciliophora, and diatoms have not yet been reported as host lineages, these groups were predicted to be the most closely linked host group for Imitervirales from a global scale network analysis (Meng et al 2021). To date, some diatoms are known to be infected by smaller ssDNA and ssRNA viruses (Toyoda et al 2012), and a dinoflagellate Heterocapsa circularisquama can be infected by ssRNA viruses and viruses of Asfarviridae, another clade of NCLDV (undefined Nagasaki et al 2006).…”

“…Using a cooccurrence network analysis is another approach to dissect associations between microorganisms based on similarities in their emerging patterns. An improved tool named FlashWeave (Tackmann et al 2019) yields more reliable relationships than simple correlation-based methods by removing the indirect association, thus has been used to evaluate the interactions between viruses and their hosts (e.g., Imitervirales and microeukaryotes) (Meng et al 2021;Prodinger et al 2022). Therefore, interactions between viruses and microeukaryotes can be inferred from both variations of overall communities and those of individual taxonomic units.…”

Morphological and Genomic Features of the New Klosneuvirinae Isolate Fadolivirus IHUMI-VV54

“…However, even though these metagenomes assembled viral genomes were of estimated high completeness and low contamination, their hosts and the capacity of each virus to have multiple hosts often remain elusive. Co-occurrence study in Tara Oceans tried to identify probable hosts but their analyses identified families of virus with their probable host in Eukaryotes such as the dominance of Mimiviridae in relation with Alveolata, Opisthokonta, Rhizaria, and Stramenopiles (Meng et al, 2021). Further, based on detection of horizontal gene transfer events in members of the Klosneuvirinae have been suggested to infect Anthoathecata, fungi, arthropods, and various protists including slime molds (Schulz et al, 2020).…”

Endogenous giant viruses contribute to intraspecies genomic variability in the model green alga Chlamydomonas reinhardtii

“…Giant viruses often encode complex functional repertoires in their genomes that include tRNA synthetases, rhodopsins, cytoskeletal components, histones, and proteins involved in glycolysis, the TCA cycle, and other aspects of central carbon metabolism (Aylward et al .). Recent studies have shown that giant viruses are widespread in the environment and infect a wide range of eukaryotic hosts, including green algae (Schulz et al ., 2020; Moniruzzaman et al ., 2020a; Endo et al ., 2020; Meng et al ., 2021). The complex genomes of giant viruses coupled with their collectively broad host range and ability to endogenize into the genomes of their hosts provides compelling evidence that they may be important vectors of gene transfer in eukaryotes.…”