Characterization of <i>Chlamydia trachomatis omp1</i> Genotypes Detected in Eye Swab Samples from Remote Australian Communities
Bibliographic record
Abstract
Chlamydia trachomatis conjunctival samples collected over a 6-month period from individuals with clinical signs of trachoma and located in remote communities in the Australian Northern Territory were differentially characterized according to serovar and variants. The rationale was to gain an understanding of the epidemiology of an apparent increased prevalence of acute trachoma in areas thought to be less conducive to this disease. Characterization was performed through sequencing of a region of the omp1 gene spanning the four variable domains and encoding the major outer membrane protein. Nucleotide and deduced amino acid sequences were genotyped by using a BLAST similarity search and were examined by phylogenetic analyses to illustrate evolutionary relationships between the clinical and GenBank reference strains. The predominant genotype identified corresponded to that of serovar C (87.1%), followed by the genotype corresponding to serovar Ba (12.9%). All nucleotide and amino acid sequences exhibited minor levels of variation with respect to GenBank reference sequences. The omp1 nucleotide sequences of the clinical samples best aligned with those of the conjunctival C. trachomatis reference strains C/TW-3/OT and Ba/Apache-2. All clinical samples (of serovar C) exhibited four or five nucleotide changes compared with C/TW-3/OT, while all serovar Ba samples had one or two nucleotide differences from Ba/Apache-2. Phylogenetic analyses revealed close relationships between these Northern Territory chlamydial samples and the respective reference strains, although the high proportion of sequence variants suggests an evolutionarily distinct C. trachomatis population causing eye infections in Australia. Given that such genotypic information has gone unreported, these findings provide knowledge and a foundation for trachoma-associated C. trachomatis variants circulating in the Northern Territory.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".