Establishing an <i>ex vivo</i> porcine skin model to investigate the effects of broad-spectrum antiseptic on viable skin microbial communities
Bibliographic record
Abstract
ABSTRACT Incomplete antiseptic efficacy against potentially pathogenic microbial taxa places some patients at disproportionate risk for developing a surgical site infection. Laboratory models capable of interrogating the effects of antiseptics on the skin and its complex microbial communities are desperately needed to improve and better tailor antiseptic formulations. This work aims to establish an ex vivo porcine skin model to explore the impact of topical antiseptics on complex skin microbial communities and superficial skin lipids. Microbiome samples were treated with propidium monoazide to selectively evaluate DNA from viable microorganisms. Bacterial abundances were assessed via viability-qPCR and quantitative culture. Viable community populations were evaluated with 16S rRNA gene sequencing. Epidermal biopsies were collected at multiple time points for lipidomic assessment via LC/MS. The ex vivo environment promoted shifts in porcine skin lipid composition and microbial communities over the experiment’s duration. Compared to water-treated control skin, skin treated with the antiseptic chlorhexidine gluconate had significantly lower culturable counts and bioburden as determined by viability-qPCR. Compared to water-treated skin, viable microbial communities on CHG-treated skin displayed greater relative abundance of several gut-associated and Gram-negative bacterial taxa, including SMB53 , Turicibacter , Pseudomonas , and Proteus . Collectively, these findings highlight the utility of an ex vivo porcine skin system for interrogating the impacts of antimicrobial disruption on complex microbial ecosystems, and ultimately, for the future testing and development of improved antiseptic formulations. IMPORTANCE Broad-spectrum antiseptics are widely used to prevent surgical site infection and as wound cleansing agents. The impacts of such agents on beneficial microbes in the skin microbiome are understudied. Here, we describe an ex vivo skin model to test the impacts of antiseptics or other topical agents on the healthy skin microbiome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".