Time-series metaproteogenomics of a high-CO2 aquifer reveals active viruses with fluctuating abundances and broad host ranges

Microlife. 2024 May 20:5:uqae011. doi: 10.1093/femsml/uqae011. eCollection 2024.

Abstract

Ecosystems subject to mantle degassing are of particular interest for understanding global biogeochemistry, as their microbiomes are shaped by prolonged exposure to high CO2 and have recently been suggested to be highly active. While the genetic diversity of bacteria and archaea in these deep biosphere systems have been studied extensively, little is known about how viruses impact these microbial communities. Here, we show that the viral community in a high-CO2 cold-water geyser (Wallender Born, Germany) undergoes substantial fluctuations over a period of 12 days, although the corresponding prokaryotic community remains stable, indicating a newly observed "infect to keep in check" strategy that maintains prokaryotic community structure. We characterized the viral community using metagenomics and metaproteomics, revealing 8 654 viral operational taxonomic units (vOTUs). CRISPR spacer-to-protospacer matching linked 278 vOTUs to 32 hosts, with many vOTUs sharing hosts from different families. High levels of viral structural proteins present in the metaproteome (several structurally annotated based on AlphaFold models) indicate active virion production at the time of sampling. Viral genomes expressed many proteins involved in DNA metabolism and manipulation, and encoded for auxiliary metabolic genes, which likely bolster phosphate and sulfur metabolism of their hosts. The active viral community encodes genes to facilitate acquisition and transformation of host nutrients, and appears to consist of many nutrient-demanding members, based on abundant virion proteins. These findings indicate viruses are inextricably linked to the biogeochemical cycling in this high-CO2 environment and substantially contribute to prokaryotic community stability in the deep biosphere hotspots.

Keywords: aquifer; high-CO2; metaproteogenomics; prokaryotic viruses; subsurface; time-series.