Phylogenomic analysis of natural selection pressure in Streptococcus genomes
Bibliographic record
Abstract
BACKGROUND: In comparative analyses of bacterial pathogens, it has been common practice to discriminate between two types of genes: (i) those shared by pathogens and their non-pathogenic relatives (core genes), and (ii) those found exclusively in pathogens (pathogen-specific accessory genes). Rather than attempting to a priori delineate genes into sets more or less relevant to pathogenicity, we took a broad approach to the analysis of Streptococcus species by investigating the strength of natural selection in all clusters of homologous genes. The genus Streptococcus is comprised of a wide variety of both pathogenic and commensal lineages, and we relate our findings to the pre-existing knowledge of Streptococcus virulence factors. RESULTS: Our analysis of 1730 gene clusters revealed 136 cases of positive Darwinian selection, which we suggest is most likely to result from an antagonistic interaction between the host and pathogen at the molecular level. A two-step validation procedure suggests that positive selection was robustly identified in our genomic survey. We found no evidence to support the notion that pathogen specific accessory genes are more likely to be subject to positive selection than core genes. Indeed, we even uncovered a few cases of essential gene evolution by positive selection. Among the gene clusters subject to positive selection, a large fraction (29%) can be connected to virulence. The most striking finding was that a considerable fraction of the positively selected genes are also known to have tissue specific patterns of expression during invasive disease. As current expression data is far from comprehensive, we suggest that this fraction was underestimated. CONCLUSION: Our findings suggest that pathogen specific genes, although a popular focus of research, do not provide a complete picture of the evolutionary dynamics of virulence. The results of this study, and others, support the notion that the products of both core and accessory genes participate in complex networks that comprise the molecular basis of virulence. Future work should seek to understand the evolutionary dynamics of both core and accessory genes as a function of the networks in which they participate.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".