Resolution of glycogen and glycogen-degrading activities reveals correlates of <i>Lactobacillus crispatus</i> dominance in a cohort of young African women
Bibliographic record
Abstract
Abstract Background A healthy vaginal microbiome is dominated by Lactobacillus species that produce lactic acid, lowering vaginal pH and limiting colonization by pathogens. Lactobacillus dominance (LD) is established during puberty, but many women, especially those of Black race, lose LD during their reproductive years. Glycogen is thought to be a key host nutrient that supports vaginal lactobacilli and their fermentative lactic acid production, but mechanisms of glycogen utilization by Lactobacillus species are incompletely understood. By partitioning glycogen and glycogen-derived maltodextrin, as well as the activity of glycogen-degrading pullulanase enzymes, this work refines understanding of vaginal glycogen catabolism and identifies correlates of LD. Results Vaginal swab samples were collected from a cohort of young women with limited sexual experience in Thika, Kenya (N=17, ages 17–20). Metagenomic profiling of the vaginal microbiome revealed that most samples exhibited LD, particularly dominant Lactobacillus crispatus . Amylopullulanase activity, cleavage of glycogen α-1,4 and α-1,6 linkages by individual/multifunctional enzymes, showed a significant positive correlation with glycogen-derived maltodextrin, but no relationship with L. crispatus dominance. Pullulanase activity, which specifically targets glycogen α-1,6 linkages, was 3-fold higher in L. crispatus- dominated samples and significantly correlated with D-lactic acid levels. Metagenomics and targeted PCR revealed that 36% of L. crispatus -dominated metagenomes from our African cohort lacked a functional L. crispatus pullulanase ( pulA ) gene, a 3-fold higher frequency of gene loss than that seen in metagenomes from European and North American women. Our findings suggest pulA gene loss or inactivation may correspond with reductions in L. crispatus abundance, pullulanase activity and lactic acid levels compared to samples dominated by pulA -competent L. crispatus . Conclusions Our results indicate that although amylase activity drives the accumulation of glycogen catabolites in vaginal fluid, pullulanase appears to specifically contribute to maximal D-lactic acid production by L. crispatus . However, this is only possible when a functional pulA gene is present, which was not the case in a substantial proportion of young African women with dominant L. crispatus . Scaling this analysis to a larger cohort will address whether genomic and enzymatic indicators of L. crispatus pullulanase activity are predictive of sustained LD and vaginal health.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".