Single-cell-resolved frequency and modes of phage interactions with prokaryoplankton in the tropical surface ocean
Marine planktonic viruses play critical roles in shaping microbial communities and driving global biogeochemical cycles. However, quantitative, microbiome-wide analyses of marine prokaryoplankton-virus interactions in situ and their ecological impacts remain challenging due to the vast diversity of viral genomes and interaction modes and the limitations of existing methodologies. Here, we…
Marine planktonic viruses have a significant impact on microbial communities and global biogeochemical cycles. Researchers have now conducted an in-depth analysis of the interactions between marine prokaryoplankton and viruses in the tropical surface ocean using GORG-Tropics, a global collection of 12,715 single amplified genomes (SAGs) derived from randomly sampled marine prokaryoplankton cells.
The study found that 4.2% of the SAGs contained phage genomic material, with the highest frequency in productive ocean regions. Prokaryoplankton lineages with high metabolic rates, such as Prochlorococcus and Rhodobacterales, had a larger fraction of cells associated with viruses, particularly compared to the less active but highly abundant Pelagibacterales.
Cell-virus associations indicative of lysogeny were more common in Alphaproteobacteria. The genomic diversity of recovered phages spanned order-level taxonomies, suggesting a high degree of diversity and connectivity within wild phage populations. Interestingly, a significant portion of the observed cell-virus associations did not align with the computationally predicted host identity, indicating non-infective interactions.
This research provides substantial evidence of viral infection rates in the prokaryoplankton community across the global surface tropical ocean, also uncovering non-infective phage-cell associations that may contribute to lateral transfer of viral genes and nutrition for marine prokaryoplankton.
Written by urgent.news from bioRxiv's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.