Transformation of <i>Gardnerella vaginalis</i> with a <i>Bifidobacterium-Escherichia coli</i> shuttle vector plasmid
Bibliographic record
Abstract
ABSTRACT Gardnerella spp. significantly influence female reproductive health and are indicators of bacterial vaginosis, a common gynecological disorder. Lack of genetic tools for Gardnerella spp. is a hindrance to fully understanding their role in the vaginal microbiome, and no naturally occurring plasmids have yet been identified in these organisms. The aim of this study was to transform Gardnerella vaginalis and characterize transformants carrying Bifidobacterium-E. coli shuttle vector pKO403- lacZ ′-Sp. G. vaginalis ATCC 49145 was selected for protocol development based on its high growth rate, lack of restriction activity, and susceptibility to spectinomycin. Low efficiency (~10 2 cfu/µg of plasmid DNA) but reproducible transformation was achieved. The expression of the spectinomycin resistance gene and the β-galactosidase gene of pKO403- lacZ ′-Sp in G. vaginalis ATCC 49145 resulted in an increase in spectinomycin tolerance from 2 µg/mL (MIC) to >512 µg/mL, and an appreciable increase in β-galactosidase activity compared with the wild type. Plasmid copy number was determined to be ~3 per genome copy. Plasmid was lost rapidly in the absence of spectinomycin selection, with only ~5% of colony-forming units retaining the resistant phenotype after 24 h of growth without selection. These results demonstrate that G. vaginalis can be transformed by electroporation and that pKO403- lacZ ′-Sp can be maintained and its genes expressed in this host, offering a starting point for the development of genetic tools for mechanistic studies of this important member of the vaginal microbiome. IMPORTANCE The healthy human vaginal microbiome is mainly dominated by Lactobacillus spp. An imbalance or shift in this population can lead to a gynecological disorder known as bacterial vaginosis (BV). In BV, there is a reduction in Lactobacillus spp. and an overgrowth of mixed anaerobes and facultative bacteria including Gardnerella spp. The reason for this increase in the Gardnerella population and associated changes in the vaginal microbiota composition is yet not understood, and a lack of genetic tools is one of the major barriers to performing mechanistic research to study the biology of these clinically significant organisms. The first step in developing genetic tools is introducing foreign DNA. In this study, we have developed a protocol for transformation and identified a plasmid that can be maintained in G. vaginalis .
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".