Pan-genome analysis of <i>Mycobacterium tuberculosis</i> identifies accessory genome sequences deleted in modern Beijing lineage
Bibliographic record
Abstract
Abstract Beijing sub-lineage of Mycobacterium tuberculosis has been reported to have increased transmissibility and drug resistance. This led us to get insights of genomic landscape of modern Beijing sub-lineages in comparison with other lineages of M. tuberculosis utilizing pan-genomics approach. Pangenome analysis was performed using software Spine (v0.2.3), AGEnt (v0.2.3) and ClustAGE (v0.7.6). The average pangenome size was 45,40,849 bp with 4,391 coding sequences (CDS), with a GC content of 65.4%. The size of the core genome was 36,83,161 bp, contained 3,698 CDS and had an average GC content of 65.1%. The average accessory genome size was 6,96,320.9 bp, with 539.4 CDS and GC content of 67.9%. Among the accessory elements complete deletion of CRISPR-associated endoribonuclease cas1 ( Rv2817c ), cas2 ( Rv2816c ), CRISPR type III-a/mtube-associated protein csm6 ( Rv2818c ), CRISPR type III-a/mtube-associated ramp protein csm5 ( Rv2819c ) and partial deletion (61.5%) CRISPR type III-a/mtube-associated ramp protein csm4 ( Rv2820c ) sequences was found specifically in modern Beijing lineages taken in assortment. The sequences were validated using conventional PCR method, which precisely amplified the corresponding targets of sequence elements with 100% sensitivity and specificity. Deletion of accessory CRISPR sequence elements amongst the modern Beijing sub-lineage of M. tuberculosis suggest more defective DNA-repair in these strains which may enhance virulence of the strains. Further, the developed conventional PCR approach for detection of virulent modern Beijing lineage may be of interest to public health and outbreak control organizations for rapid detection of modern Beijing lineage.
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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 | 0.000 | 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) | 0.002 | 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".