Large-scale activity analysis of gut prophages reveals significantly active lineages in the human gut
Huang, Y.; Liu, Z.; Hu, J.; Tan, X.; Dai, L.; Ma, Y.
Show abstract
Prophages dominate the human gut virome and their transition from lysogeny to lytic replication profoundly affects gut microbial community structure. However, the global activity landscape of gut prophages remains largely uncharted. Here, we developed a workflow to assess prophage activity across more than 30,000 gut bacterial isolates cultured in vitro under standard conditions. Using this approach, 4,033 prophages, corresponding to a small fraction (7.5%) of the overall prophage reservoir, were detected as active, indicating a high-lysogeny, low-activity landscape. Prophage activity varied markedly across host taxa, with Bacillota exhibiting notably elevated active rates. Active prophages derived from 183 viral families (vFAMs), 56 of which were assigned as significantly active (SA-vFAMs), including: SA-vFAM7, a novel, hyper-prevalent lineage with expanded host range into Tannerellaceae and substantial intra-lineage diversity; and Candidatus Mubacviridae (SA-vFAM1), a newly defined, hankyphage-inclusive, highly active Mu-like transposable phage family infecting Bacteroidales, characterized by conserved MuA-MuB operons and cross-family host range. Together, this work provides a large-scale, activity-integrated atlas of human gut prophages, demonstrating that prophage activity is driven by both host phylogeny and viral lineage identity, and establishing a foundational resource for understanding prophage ecology.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- The genetic diversity and populational specificity of the human gut virome at single nucleotide resolution 97%
- Viromes vs. mixed community metagenomes: choice of method dictates interpretation of viral community ecology 94%
- Phages are important unrecognized players in the ecology of the oral pathogen Porphyromonas gingivalis 94%
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.