<i>In Vitro</i> Culture of Previously Uncultured Oral Bacterial Phylotypes
Bibliographic record
Abstract
Around a third of oral bacteria cannot be grown using conventional bacteriological culture media. Community profiling targeting 16S rRNA and shotgun metagenomics methods have proved valuable in revealing the complexity of the oral bacterial community. Studies investigating the role of oral bacteria in health and disease require phenotypic characterizations that are possible only with live cultures. The aim of this study was to develop novel culture media and use an in vitro biofilm model to culture previously uncultured oral bacteria. Subgingival plaque samples collected from subjects with periodontitis were cultured on complex mucin-containing agar plates supplemented with proteose peptone (PPA), beef extract (BEA), or Gelysate (GA) as well as on fastidious anaerobe agar plus 5% horse blood (FAA). In vitro biofilms inoculated with the subgingival plaque samples and proteose peptone broth (PPB) as the growth medium were established using the Calgary biofilm device. Specific PCR primers were designed and validated for the previously uncultivated oral taxa Bacteroidetes bacteria HOT 365 and HOT 281, Lachnospiraceae bacteria HOT 100 and HOT 500, and Clostridiales bacterium HOT 093. All agar media were able to support the growth of 10 reference strains of oral bacteria. One previously uncultivated phylotype, Actinomyces sp. HOT 525, was cultivated on FAA. Of 93 previously uncultivated phylotypes found in the inocula, 26 were detected in in vitro-cultivated biofilms. Lachnospiraceae bacterium HOT 500 was successfully cultured from biofilm material harvested from PPA plates in coculture with Parvimonas micra or Veillonella dispar/parvula after colony hybridization-directed enrichment. The establishment of in vitro biofilms from oral inocula enables the cultivation of previously uncultured oral bacteria and provides source material for isolation in coculture.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".