Large-Scale Comparative Genomics Meta-Analysis of <i>Campylobacter jejuni</i> Isolates Reveals Low Level of Genome Plasticity
Bibliographic record
Abstract
We have used comparative genomic hybridization (CGH) on a full-genome Campylobacter jejuni microarray to examine genome-wide gene conservation patterns among 51 strains isolated from food and clinical sources. These data have been integrated with data from three previous C. jejuni CGH studies to perform a meta-analysis that included 97 strains from the four separate data sets. Although many genes were found to be divergent across multiple strains (n = 350), many genes (n = 249) were uniquely variable in single strains. Thus, the strains in each data set comprise strains with a unique genetic diversity not found in the strains in the other data sets. Despite the large increase in the collective number of variable C. jejuni genes (n = 599) found in the meta-analysis data set, nearly half of these (n = 276) mapped to previously defined variable loci, and it therefore appears that large regions of the C. jejuni genome are genetically stable. A detailed analysis of the microarray data revealed that divergent genes could be differentiated on the basis of the amplitudes of their differential microarray signals. Of 599 variable genes, 122 could be classified as highly divergent on the basis of CGH data. Nearly all highly divergent genes (117 of 122) had divergent neighbors and showed high levels of intraspecies variability. The approach outlined here has enabled us to distinguish global trends of gene conservation in C. jejuni and has enabled us to define this group of genes as a robust set of variable markers that can become the cornerstone of a new generation of genotyping methods that use genome-wide C. jejuni gene variability data.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".