Development of molecular approaches for the identification and characterization of oral treponeme bacteria
Bibliographic record
Abstract
Elevated populations of oral treponeme bacteria are associated with periodontal\n\ndiseases. Furthermore, genetic analyses of oral bacterial populations using 16S rRNAbased\n\napproaches have previously shown that deeply-infected periodontal pockets\n\ncontain a large diversity of oral treponeme species (or species level phylotypes).\n\nHowever, the diversity of treponeme populations present within ‘healthy’ dental\n\nplaque has been relatively poorly investigated. In this thesis, I used a 16S rRNA-based\n\nmolecular approach to analyze the diversity of treponeme ‘species’ within human\n\nsubjects with chronic periodontitis, versus periodontally-healthy controls. I found that\n\nsimilar levels of oral treponeme phylotype diversity were present in both subject\n\ngroups, but there were notable significant differences in the composition of treponeme\n\nphylotypes present. Within both groups, oral phylogroup 1 treponemes had the highest\n\nlevels of phylotype diversity; phylogroup 2 treponemes had similar levels of diversity;\n\nwhilst phylogroup 6 treponemes were more abundant and exhibited greater phylotype\n\ndiversity in the healthy group. As has been previously found, T. denticola was\n\nassociated with periodontal disease.\n\nOver the past few decades, numerous T. denticola strains have been isolated from\n\npatients with periodontal diseases. However, their genetic diversity has never been\n\nsystematically analyzed. Here I describe the formulation of a multilocus sequence\n\nanalysis (MLSA) scheme for the characterization of T. denticola isolates. The\n\nsequences of seven conserved genes (flaA, recA, pyrH, ppnK, dnaN, era and radC)\n\nwere determined within 16 diverse reference strains and clinical isolates of T.\n\ndenticola from China, Japan, Canada, the Netherlands and the USA. Results showed\n\nthat all 16 T. denticola strains were monophyletic, and formed at least 5 well-defined\n\nclades, with OTK, ATCC 700768 and ATCC 700771 being the most diverse strains.\n\nNo geographical relationships could be established, but several strains isolated from\n\ndifferent continents appear to be very closely related. Whilst the use of the\n\nconcatenated seven-gene sequence dataset (6,769nt) had the highest straindiscriminatory\n\npower, the concatenated sequence of the recA, pyrH and flaA genes\n\n(3,150 nt) also had excellent strain-discriminatory abilities.\n\nThe recently-discovered oral phylogroup II treponeme, T. putidum shares many\n\nbiological similarities with T. denticola. Here, I used a small-scale MLSA-type\n\napproach based on the recA and pyrH genes to systematically characterize five T.\n\nputidum isolates. Results revealed that these T. putidum strains clustered together with\n\nT. denticola ATCC 700768, and were well-separated from other T. denticola strains. T.\n\nputidum cell morphology was investigated using electron microscopy and fluorescence\n\nin situ hybridization (FISH) techniques. In addition, oral phylogroup II treponeme\n\npopulations present in a clinical sample of subgingival plaque were analyzed by\n\nsurveying the diversity of pyrH genotypes present. A diverse population of T.\n\ndenticola strains was revealed.\n\nIn conclusion, the MLSA approach developed in this study was shown to be a very\n\nuseful tool for the identification and characterization of oral treponeme isolates\n\nbelonging to phylogroup II (e.g. T. denticola, T. putidum). In future studies, this\n\npowerful molecular approach may be further developed for the analysis of other oral\n\ntreponeme phylogroups, or for the analysis of spirochete populations within related\n\nanimal infections.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".