Experimental bacterial adaptation to the zebrafish gut reveals a primary role for immigration
Bibliographic record
Abstract
All animals live in intimate association with microorganisms that profoundly influence their health and development, yet the traits that allow microorganisms to establish and maintain host associations are not well understood. To date, most investigations aimed at identifying traits required for host association have focused on intrahost niches. Consequently, little is known about the relative contribution of extrahost factors such as environmental growth and survival and immigration into hosts from the external environment, as promoters of host association. To address this, we developed a tractable experimental evolution system that investigates both intra- and extrahost factors contributing to bacterial adaptation to the vertebrate gut. We passaged replicate lines of a zebrafish bacterial isolate, Aeromonas veronii, through populations of germ-free larval zebrafish (Danio rerio), each time using gut-associated Aeromonas populations to inoculate the aquatic environment of the next zebrafish population. We observed rapid increased adaptation to the host in all replicate lines. The initial adaptations present in early-evolved isolates did not increase intrahost fitness but rather enhanced both immigration from the environment and interhost transmission. Only in later-evolved isolates did we find evidence for intrahost-specific adaptations, as demonstrated by comparing their competitive fitness in the host genotype to which they evolved to that in a different genotype. Our results show how selection for bacterial transmission between hosts and their environment can shape bacterial-host association. This work illuminates the nature of selective forces present in host-microbe systems and reveals specific mechanisms of increased host association. Furthermore, our findings demonstrate that the entire host-microbe-environment system must be considered when identifying microbial traits that contribute to host adaptation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".