Bacteriophages Playing Nice: Lysogenic bacteriophage replication stable in the human gut microbiota
Bibliographic record
Abstract
1.1. Abstract The human gut is a dense microbial community, of which bacteria and bacteriophages are the majority. Bacteriophages, viruses of bacteria, exist stably, without major fluctuations in the gut of healthy individuals. This stability appears to be due to an absence of ‘kill-the-winner’ dynamics, and the existence of ‘piggy-back-the-winner’ dynamics, where lysogenic replication rather than lytic replication occurs. Revisiting the deep-viral sequencing data of a healthy individual studied over 2.4 years, we were able to improve our understanding of how these dynamics occur in healthy individuals. We assembled prophages from bacterial metagenomic data and show that these prophages were continually switching from lysogenic to lytic replication. Prophages were the source of a stable extracellular phage population continually present in low abundance, in comparison to the lytic-phage population, where taxonomic diversity diverged over 2.4 years. The switch to lytic replication, or prophage induction, appears to occur mostly through spontaneous prophage induction. The observed phage dynamics of regular spontaneous induction are ecologically important as they allow prophages to maintain their ability to replicate, avoiding degradation and their loss from the gut microbiota. 1.2. Significance Statement It has been eight years since Minot and colleagues published their landmark longitudinal study of phages in the gut. In the years following, the bioinformatic field improved in great strides, including the methods of bacterial-genome assembly, phage-identification, and prophage detection. We leveraged the unprecedented deep sequencing of phages in this dataset by adding bacterial assembly and prophage detection analyzes. We show clearly for the first time that ‘piggy-back-the-winner’ dynamics are maintained in the gut through spontaneous prophage induction, and not widespread triggered prophage induction. These dynamics play an important ecological role by creating a stable subpopulation of phages, which could help explain how phages are maintained over the 2.4 years timeframe that this individual was studied.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".