Comparison of Seven Techniques for Typing International Epidemic Strains of <i>Clostridium difficile</i> : Restriction Endonuclease Analysis, Pulsed-Field Gel Electrophoresis, PCR-Ribotyping, Multilocus Sequence Typing, Multilocus Variable-Number Tandem-Repeat Analysis, Amplified Fragment Length Polymorphism, and Surface Layer Protein A Gene Sequence Typing
Bibliographic record
Abstract
Using 42 isolates contributed by laboratories in Canada, The Netherlands, the United Kingdom, and the United States, we compared the results of analyses done with seven Clostridium difficile typing techniques: multilocus variable-number tandem-repeat analysis (MLVA), amplified fragment length polymorphism (AFLP), surface layer protein A gene sequence typing (slpAST), PCR-ribotyping, restriction endonuclease analysis (REA), multilocus sequence typing (MLST), and pulsed-field gel electrophoresis (PFGE). We assessed the discriminating ability and typeability of each technique as well as the agreement among techniques in grouping isolates by allele profile A (AP-A) through AP-F, which are defined by toxinotype, the presence of the binary toxin gene, and deletion in the tcdC gene. We found that all isolates were typeable by all techniques and that discrimination index scores for the techniques tested ranged from 0.964 to 0.631 in the following order: MLVA, REA, PFGE, slpAST, PCR-ribotyping, MLST, and AFLP. All the techniques were able to distinguish the current epidemic strain of C. difficile (BI/027/NAP1) from other strains. All of the techniques showed multiple types for AP-A (toxinotype 0, binary toxin negative, and no tcdC gene deletion). REA, slpAST, MLST, and PCR-ribotyping all included AP-B (toxinotype III, binary toxin positive, and an 18-bp deletion in tcdC) in a single group that excluded other APs. PFGE, AFLP, and MLVA grouped two, one, and two different non-AP-B isolates, respectively, with their AP-B isolates. All techniques appear to be capable of detecting outbreak strains, but only REA and MLVA showed sufficient discrimination to distinguish strains from different outbreaks.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".