Shining light on a deep-sea bacterial symbiont population structure with CRISPR
Bibliographic record
Abstract
Many foundation species in chemosynthesis-based ecosystems rely on environmentally acquired symbiotic bacteria for their survival. Hence, understanding the biogeographic distributions of these symbionts at regional scales is key to understanding patterns of connectivity and predicting resilience of their host populations (and thus whole communities). However, such assessments are challenging because they necessitate measuring bacterial genetic diversity at fine resolutions. For this purpose, the recently discovered clustered regularly interspaced short palindromic repeats (CRISPR) constitutes a promising new genetic marker. These DNA sequences harboured by about half of bacteria hold their viral immune memory, and as such, might allow discrimination of different lineages or strains of otherwise indistinguishable bacteria. In this study, we assessed the potential of CRISPR as a hypervariable phylogenetic marker in the context of a population genetic study of an uncultured bacterial species. We used high-throughput CRISPR-based typing along with multi-locus sequence analysis (MLSA) to characterize the regional population structure of the obligate but environmentally acquired symbiont species Candidatus Endoriftia persephone on the Juan de Fuca Ridge. Mixed symbiont populations of Ca. Endoriftia persephone were sampled across individual Ridgeia piscesae hosts from contrasting habitats in order to determine if environmental conditions rather than barriers to connectivity are more important drivers of symbiont diversity. We showed that CRISPR revealed a much higher symbiont genetic diversity than the other housekeeping genes. Several lines of evidence imply this diversity is indicative of environmental strains. Finally, we found with both CRISPR and gene markers that local symbiont populations are strongly differentiated across sites known to be isolated by deep-sea circulation patterns. This research showed the high power of CRISPR to resolve the genetic structure of uncultured bacterial populations and represents a step towards making keystone microbial species an integral part of conservation policies for upcoming mining operations on the seafloor.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".