Analysis and comparison of the pan-genomic properties of sixteen well-characterized bacterial genera
Bibliographic record
Abstract
BACKGROUND: The increasing availability of whole genome sequences allows the gene or protein content of different organisms to be compared, leading to burgeoning interest in the relatively new subfield of pan-genomics. However, while several studies have analyzed protein content relationships in specific groups of bacteria, there has yet to be a study that provides a general characterization of protein content relationships in a broad range of bacteria. RESULTS: A variation on reciprocal BLAST hits was used to infer relationships among proteins in several groups of bacteria, and data regarding protein conservation and uniqueness in different bacterial genera are reported in terms of "core proteomes", "unique proteomes", and "singlets". We also analyzed the relationship between protein content similarity and the percent identity of the 16S rRNA gene in pairs of bacterial isolates from the same genus, and found that the strength of this relationship varied substantially depending on the genus, perhaps reflecting different rates of genome evolution and/or horizontal gene transfer. Finally, core proteomes and unique proteomes were used to study the proteomic cohesiveness of several bacterial species, revealing that some bacterial species had little cohesiveness in their protein content, with some having fewer proteins unique to that species than randomly-chosen sets of isolates from the same genus. CONCLUSIONS: The results described in this study aid our understanding of protein content relationships in different bacterial groups, allowing us to make further inferences regarding genome-environment relationships, genome evolution, and the soundness of existing taxonomic classifications.
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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 | 0.000 | 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".