Quantitative assessment of NCLDV-host interactions predicted by co-occurrence analyses
L. Meng, H. Endo, R. Blanc-Mathieu, S. Chaffron, R. Hernandez-Velazquez, H. Kaneko, H. Ogata
Abstract
Nucleocytoplasmic DNA viruses (NCLDVs) are highly diverse and abundant in marine environments. However, 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 four-fold compared with 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 twelve-fold. Finally, we inferred virophage - NCLDV networks to corroborate that co-occurrence approaches are effective for predicting interacting partners of NCLDVs in marine environments. ImportanceNCLDVs can infect a wide range of eukaryotes although their life cycle is less dependent on hosts compared with 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 approach for metagenomic exploration of the ecology of this diverse group of viruses.
02 /Specification & Classification
Click any tag to browse matching papers- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- A Cophylogenetic Approach for Virus-Host Interaction Prediction
Md Zarzees Uddin Shah Chowdhury, T. M. Murali, Palash Sashittal·bioRxiv·Feb 27, 2026
- Virus-Host Interactions Predictor (VHIP): machine learning approach to resolve microbial virus-host interaction networks
G Eric Bastien, Rachel N. Cable, … Melissa Beth Duhaime·PLoS Computational BiologyPeer-reviewed·Sep 18, 2024
- Phylogenetic proximity drives temporal succession of marine giant viruses in a five-year metagenomic time-series
Sarah M. Laperriere, Benjamin Minch, … Jed A. Fuhrman·ISME CommunicationsPeer-reviewed·Jan 1, 2025
- Contrasting defense strategies of oligotrophs and copiotrophs revealed by single-cell-resolved virus-host pairing of freshwater bacteria
Yusuke Okazaki, Yohei Nishikawa, … Shin‐ichi Nakano·ISME CommunicationsPeer-reviewed·Jan 1, 2025
- A network-based integrated framework for predicting virus-host interactions
Weili Wang, Jie Ren, … Nathan A. Ahlgren·bioRxiv·Aug 19, 2019
- Viral coinfection is shaped by host ecology and virus-virus interactions across diverse microbial taxa and environments
S. L. Diaz-Munoz·bioRxiv·Feb 7, 2016