Developing a Genotyping Scheme for Mycobacterium abscessus Complex Using Whole Genome Sequencing Data
Bibliographic record
Abstract
Mycobacterium abscessus complex is a rapid growing non-tuberculous mycobacteria (NTM) and a clinically significant pathogen capable of causing varying infections in humans. It is notoriously difficult to treat due to its inducible resistant state to clarithromycin and intrinsic resistant states to other drugs including rifampicin. Typing schemes for bacterial pathogens provide numerous applications including sourcing an outbreak, identifying cross contamination, chain of transmission and surveillance. However, they either lack or are limited for many NTMs including M. abscessus complex. The current publically available scheme on PubMLST has not been updated in several years and was only able to apply a sequence type to less than half of tested isolates. This project was aimed at creating a workflow for the development of a multi-locus sequence typing (MLST) scheme using whole genome data. A total of 104 genomes and 14 loci were used to build the scheme (including 3 type strains of each of the 3 subspecies). All 7 genes from the PubMLST scheme were incorporated namely, argH, cya, gnd, murC, pta, purH, and rpoB and were expanded by 6, 9, 12, 8, 12, 10, and 8 alleles, respectively. Another 7 novel genes were added including hsp65, erm(41), arr, rrs, rrl, gyrA, and gyrB with 9, 14, 20, 7, 25, 24, 22 alleles, respectively with 62 unique sequence types were identified among all isolates. This scheme can also differentiate M. abscessus complex to the subspecies level on the basis of 3 discriminatory genes and includes 6 genes related to antimicrobial resistance. Â Supplementary information available online at:Â http://ojs.lib.umanitoba.ca/index.php/pmuser/article/view/682/699Â
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".