Genetic Determinants and Polymorphisms Specific for Human-Adapted Serovars of <i>Salmonella enterica</i> That Cause Enteric Fever
Bibliographic record
Abstract
Salmonella enterica serovars Typhi, Paratyphi A, and Sendai are human-adapted pathogens that cause typhoid (enteric) fever. The acute prevalence in some global regions and the disease severity of typhoidal Salmonella have necessitated the development of rapid and specific detection tests. Most of the methodologies currently used to detect serovar Typhi do not identify serovars Paratyphi A or Sendai. To assist in this aim, comparative sequence analyses were performed at the loci of core bacterial genetic determinants and Salmonella pathogenicity island 2 genes encoded by clinically significant S. enterica serovars. Genetic polymorphisms specific for serovar Typhi (at trpS), as well as polymorphisms unique to human-adapted typhoidal serovars (at sseC and sseF), were observed. Furthermore, entire coding sequences unique to human-adapted typhoidal Salmonella strains (i.e., serovar-specific genetic loci rather than polymorphisms) were observed in publicly available comparative genomic DNA microarray data sets. These polymorphisms and loci were developed into real-time PCR, standard PCR, and liquid microsphere suspension array-based molecular protocols and tested for with a panel of clinical and reference subspecies I S. enterica strains. A proportion of the nontyphoidal Salmonella strains hybridized with the allele-specific oligonucleotide probes for sseC and sseF; but the trpS allele was unique to serovar Typhi (with a singular serovar Paratyphi B strain as an exception), and the coding sequences STY4220 and STY4221 were unique among serovars Typhi, Paratyphi A, and Sendai. These determinants provided phylogenetic data on the genetic relatedness of serovars Typhi, Paratyphi A, and Sendai; and the protocols developed might allow the rapid identification of these Salmonella serovars that cause enteric fever.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".