DNA-Sequence Based Typing of the Cronobacter Genus Using MLST, CRISPR-cas Array and Capsular Profiling
Bibliographic record
Abstract
The Cronobacter genus is composed of 7 species, within which a number of pathovars have been described. The most notable infections by Cronobacter spp. are of infants through the consumption of contaminated infant formula. The description of the genus has greatly improved in recent years through DNA sequencing techniques, and this has led to a robust means of identification. However some species are highly clonal and this limits the ability to discriminate between unrelated strains by some methods of genotyping. This article updates the application of three genotyping methods across the Cronobacter genus. The three genotyping methods were multilocus sequence typing (MLST), capsular profiling of the K-antigen and colanic acid (CA) biosynthesis regions, and CRISPR-cas array profiling. A total of 1654 MLST profiled and 286 whole genome sequenced strains, available by open access at the PubMLST Cronobacter database, were used this analysis. The predominance of C. sakazakii and C. malonaticus in clinical infections was confirmed. The majority of clinical strains being in the C. sakazakii clonal complexes (CC) 1 & 4, sequence types (ST) 8 & 12 and C. malonaticus ST7. The capsular profile K2:CA2, previously proposed as being strongly associated with C. sakazakii and C. malonaticus isolates from severe neonatal infections, was also found in C. turicensis, C. dublinensis and C. universalis. The majority of CRISPR-cas types across the genus was the I-E (Ecoli) type. Some strains of C. dublinensis and C. muytjensii encoded the I-F (Ypseudo) type, and others lacked the cas gene loci. The significance of the expanding profiling will be of benefit to researchers as well as governmental and industrial risk assessors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".