Genotyping of Mycobacterium avium complex organisms using multispacer sequence typing
Bibliographic record
Abstract
Mycobacterium avium complex (MAC) currently comprises eight species of environmental and animal-associated, slowly-growing mycobacteria: Mycobacterium avium, Mycobacterium intracellulare, Mycobacterium chimaera, Mycobacterium colombiense, Mycobacterium arosiense , Mycobacterium bouchedurhonense, Mycobacterium marseillense and Mycobacterium timonense. In humans, MAC organisms are responsible for opportunistic infections whose unique epidemiology remains poorly understood, in part due to the lack of a genotyping method applicable to all eight MAC species. In this study we developed multispacer sequence typing (MST), a sequencing-based method, for the genotyping of MAC organisms. An alignment of the genome sequence of M. avium subsp. hominissuis strain 104 and M. avium subsp. paratuberculosis strain K-10 revealed 621 intergenic spacers <1000 bp. From these, 16 spacers were selected that ranged from 300 to 800 bp and contained a number of variable bases, <50 within each of the 16 spacers. Four spacers were successfully PCR-amplified and sequenced in 11 reference strains. Combining the sequence of these four spacers in 106 MAC organisms, including 83 M. avium, 11 M. intracellulare , six M. chimaera, two M. colombiense and one each of M. arosiense, M. bouchedurhonense, M. marseillense and M. timonense, yielded a total of 45 spacer types, with an index of discrimination of 0.94. Each spacer type was specific for a species and certain spacer types were specific for subspecies of M. avium. MST is a new method for genotyping of organisms belonging to any one of the eight MAC species tested in this study.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".