Genomic Science Program
U.S. Department of Energy | Office of Science | Biological and Environmental Research Program

Multiomics Pipelines and Approaches to Characterize Viral Impacts on Environmental Microbiomes

Authors:

Simon Roux1*(sroux@lbl.gov), Clement Coclet1, Maureen Berg1, Devaki Bhaya2, Amanda N. Shelton2, Shi Wang3, Patrick O. Sorensen3, Ulas Karaoz3, Eoin L. Brodie3,4, Emiley A. Eloe-Fadrosh1

Institutions:

1DOE Joint Genome Institute; 2Carnegie Institution for Science; 3Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory; 4University of California–Berkeley

Goals

The overarching goals of this project are to establish an analytical and experimental framework for comprehensive characterization of viral-driven alteration of microbial metabolisms in soil. The specific results presented here focus on the development of new tools and resources to help researchers “see” the viral signal in their data, and the benefit of pairing metagenomics and metatranscriptomics approaches to better characterize the potential impacts of viruses in microbiomes.

Abstract

Metagenomics has emerged as a powerful approach to explore environmental viral diversity and identify the potential impacts of viruses in microbiomes, including in complex ecosystems such as soil. As the throughput, quality, and range of omics data expand, new methods and tools are needed to help researchers leverage the growing viromics toolkit and more thoroughly characterize uncultivated viruses beyond genome diversity. Here, researchers first outline how datasets including paired metagenomes and metatranscriptomes can help investigate viral activity in microbiomes. Specifically, in both longitudinal sampling of a mountainous soil and diurnal sampling of a Yellowstone hot spring microbial mat, only a limited fraction (~20 to 50%) of viruses identified via metagenomics were typically detected as transcriptionally active, and sample ordination based on metatransciptomic coverage provided a much stronger sample clustering consistent with ecological parameters compared to similar ordinations based on metagenomic coverage. This indicates that viral dynamics and potential impacts on a microbiome can be better understood by considering transcriptional activity in addition to detection in a metagenome. Next, the group presents Multi-choice Viromics Pipeline (MVP), an integrated workflow designed to enable researchers to run standard viromics analysis of metagenomes and/or metatranscriptomes in only a few easy steps. Integrating state-of-the-art tools, MVP enables nonexpert users to seamlessly process a set of metagenomes into heatmaps and ordinations based on viral signal, immediately providing a window into the viral diversity present in these data. MVP also automates a number of tasks, such as correcting quality estimation of provirus predictions, and provides summary statistics throughout the workflow to inform users on the overall viral content of their sample. Ultimately, the development of new viromics approaches such as community-wide analysis of viral diversity through paired metagenomics and metatranscriptomics, along with the expansion of the viromics toolkit with both new tools and integrated user-friendly pipelines, will pave the way toward widespread adoption of these analyses and robust consideration of the role(s) of viruses in all microbiome studies.

References

Camargo, A. P., et al. 2023. “Identification of Mobile Genetic Elements with geNomad,” Nature Biotechnology DOI:10.1038/s41587-023-01953-y.

Coclet, C., et al. 2023. “Virus Diversity and Activity is Driven by Snowmelt and Host Dynamics in a High-Altitude Watershed Soil Ecosystem,” Microbiome 11. DOI:10.1186/s40168-023-01666-z.

Roux, S., et al. 2023. “iPHoP: An Integrated Machine Learning Framework to Maximize Host Prediction for Metagenome-Derived Viruses of Archaea and Bacteria,” PLoS Biology 21(4). DOI:10.1371/journal.pbio.3002083.

Funding Information

This work was supported by the U.S. DOE, Office of Science, BER program, Early Career Research Program awarded under UC-DOE Prime Contract DE-AC02-05CH11231.