Phage-delivered CRISPR-Cas9 for strain-specific depletion and genomic deletions in the gut microbiome
Bibliographic record
Abstract
Mechanistic insights into the role of the human microbiome in the predisposition to and treatment of disease are limited by the lack of methods to precisely add or remove microbial strains or genes from complex communities. Here, we demonstrate that engineered bacteriophage M13 can be used to deliver DNA to Escherichia coli within the mouse gastrointestinal (GI) tract. Delivery of a programmable exogenous CRISPR-Cas9 system enables the strain-specific depletion of fluorescently marked isogenic strains during competitive colonization and genomic deletions that encompass the target gene in mice colonized with a single strain. Multiple mechanisms allow E. coli to escape targeting, including loss of the CRISPR array or even the entire CRISPR-Cas9 system. These results provide a robust and experimentally tractable platform for microbiome editing, a foundation for the refinement of this approach to increase targeting efficiency, and a proof of concept for the extension to other phage-bacterial pairs of interest.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".