Practical media formulations for rapid growth of <i>Lactobacillus iners</i> and other vaginal bacteria
Bibliographic record
Abstract
Abstract Vaginal microbiome composition is closely tied to host health. A microbiome dominated by specific anaerobes (e.g., Gardnerella vaginalis ) is termed bacterial vaginosis (BV) and is associated with negative health outcomes, while colonization by Lactobacillus species is thought to protect against BV. However, the role of the species Lactobacillus iners in vaginal health is controversial, with evidence that some strains may not protect against BV while others do. To better characterize L. iners strains, their interactions with vaginal bacteria and human cells need to be investigated in vitro , but this has been impeded by the lack of liquid media for rapid L. iners growth. We have developed three liquid media formulations for L. iners growth: Serrador’s Lactobacilli-adapted Iscove’s Medium (SLIM) which leads to robust L. iners growth, a vaginally adapted version of SLIM (SLIM-V) and a chemically defined medium (SLIM-CD). SLIM and SLIM-V lead to dramatically improved L. iners growth compared to previously published formulations and support growth of other vaginal bacteria, including L. crispatus, L. jensenii, L. gasseri and G. vaginalis . SLIM-CD leads to slower growth but could prove useful for characterizing L. iners nutrient requirements or metabolite production. A modified version of SLIM-V supports growth of human cervical epithelial cells and provides a base for future co-culture work. Here, we present the formulations of SLIM, SLIM-V and SLIM-CD, and compare the growth of bacterial strains and human cells in the media.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".