Impact of Genomics on Clarifying the Evolutionary Relationships amongst Mycobacteria: Identification of Molecular Signatures Specific for the Tuberculosis-Complex of Bacteria with Potential Applications for Novel Diagnostics and Therapeutics
Bibliographic record
Abstract
has created an urgent need for new antituberculosis drugs acting via novel mechanisms. Phylogenomic and comparative genomic analyses reviewed here reveal that the TB causing bacteria comprise a small group of organisms differing from all other mycobacteria in numerous regards. Comprehensive analyses of protein sequences from mycobacterial genomes have identified 63 conserved signature inserts and deletions (indels) (CSIs) in important proteins that are distinctive characteristics of the TB-complex of bacteria. The identified CSIs provide potential means for development of novel diagnostics as well as therapeutics for the TB-complex of bacteria based on four key observations: (i) The CSIs exhibit a high degree of exclusivity towards the TB-complex of bacteria; (ii) Earlier work on CSIs provide evidence that they play important/essential functions in the organisms for which they exhibit specificity; (iii) CSIs are located in surface-exposed loops of the proteins implicated in mediating novel interactions; (iv) Homologs of the CSIs containing proteins, or the CSIs in such homologs, are generally not found in humans. Based on these characteristics, it is hypothesized that the high-throughput virtual screening for compounds binding specifically to the CSIs (or CSI containing regions) and thereby inhibiting the cellular functions of the CSIs could lead to the discovery of a novel class of drugs specifically targeting the TB-complex of organisms.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".