CRISPR-Cas provides limited phage immunity to a prevalent gut bacterium in gnotobiotic mice
Bibliographic record
Abstract
Many bacteria and archaea harbor the adaptive CRISPR-Cas system, which stores small nucleotide fragments from previous invasions of nucleic acids via viruses or plasmids. This molecular archive blocks further invaders carrying identical or similar nucleotide sequences. However, few of these systems have been confirmed experimentally to be active in gut bacteria. Here, we demonstrate experimentally that the type I-C CRISPR-Cas system of the prevalent gut bacterium Eggerthella lenta can specifically target and cleave foreign DNA in vitro by using a plasmid transformation assay. We also show that the CRISPR-Cas system acquires new immunities (spacers) from the genome of a virulent E. lenta phage using traditional phage assays in vitro but also in vivo using gnotobiotic (GB) mice. Both high phage titer and an increased number of spacer acquisition events were observed when E. lenta was exposed to a low multiplicity of infection in vitro, and three phage genes were found to contain protospacer hotspots. Fewer new spacer acquisitions were detected in vivo than in vitro. Longitudinal analysis of phage-bacteria interactions showed sustained coexistence in the gut of GB mice, with phage abundance being approximately one log higher than the bacteria. Our findings show that while the type I-C CRISPR-Cas system is active in vitro and in vivo, a highly virulent phage in vitro was still able to co-exist with its bacterial host in vivo. Taken altogether, our results suggest that the CRISPR-Cas defense system of E. lenta provides only partial immunity in the gut.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".