Impact of Topical Antibiotics on Skin Microbiome in Acne Patients

Thesis Abstract

Common dermatological treatments for acne rely on topical antibiotics, yet the long-term impact of these agents on the cutaneous microbiome and its relation to therapeutic outcomes remains incompletely understood. This study investigates how topical antibiotics alter skin microbial communities in individuals with acne vulgaris and how these changes relate to clinical response and potential adverse effects. The aim is to determine the extent, trajectory, and ecological consequences of microbiome disruption caused by standard topical regimens, and to identify microbiome-associated predictors of treatment success or relapse. Specifically, the objectives are to (1) characterize baseline skin microbiome composition in acne patients; (2) quantify temporal microbiome alterations following commonly prescribed topical antibiotics (e.g., clindamycin, erythromycin) over a 12-week treatment window and a 6-month follow-up; (3) examine associations between microbial shifts (alpha and beta diversity, differential taxa abundance) and clinical outcomes (lesion counts, severity scores, patient-reported tolerability); (4) evaluate the emergence and transmission potential of antibiotic resistance determinants within the skin ecosystem; and (5) explore whether patient-level factors (age, sex, skin phototype, comedonal disease burden) modulate microbiome responses and treatment efficacy. The study uses a longitudinal prospective design with a multi-site dermatology cohort comprising 240 participants aged 16–35 years with mild-to-moderate acne. Participants are assigned to standard-of-care topical antibiotic regimens, with a parallel non-antibiotic moisturizer control arm to disentangle vehicle effects. Skin swab samples are collected from standardized facial sites at baseline, weeks 2, 4, 8, 12, and at 6 months post-initiation. Microbial profiling employs 16S rRNA gene sequencing for bacterial community structure and shotgun metagenomics for functional potential, coupled with quantitative PCR for targeted resistance genes (ermA, ermC, tetK). Clinical data include LESION counts, Global Acne Grading Scale, tolerability indices, and adverse event records. Data analysis proceeds in several layers descriptive statistics for baseline characteristics; mixed-effects models to assess longitudinal microbiome dynamics in relation to time, treatment, and interactions with host factors; differential abundance analysis using DESeq2 to identify taxa responsive to antibiotic exposure; diversity metrics (Shannon, Simpson, Bray-Curtis) to evaluate alpha and beta diversity over time; and multivariate regression to link microbial features with clinical outcomes. Additionally, machine learning approaches (random forest and support vector machines) will be employed to identify microbial signatures predictive of treatment response and relapse risk. A functional analysis of metagenomic data will map antibiotic resistance gene abundance and potential mobile genetic elements, informing ecological risk assessment. Theoretical framing draws on the Niche Theory and Ecological Community Resilience to interpret microbial succession, as well as the precautionary principle in antimicrobial stewardship to contextualize potential long-term trade-offs. Expected findings include measurable shifts in skin microbiome composition characterized by reductions in commensal Propionibacterium (Cutibacterium) acnes subpopulations alongside expansions of opportunistic taxa in response to antibiotic exposure, with partial recovery or persistent perturbation during follow-up. The study anticipates correlations between disrupted microbial networks and slower clinical improvement or higher relapse rates, and a detectable increase in specific antibiotic resistance determinants in treated cohorts. The contribution to knowledge lies in providing robust, longitudinal, microbiome-centric evidence on the ecological consequences of topical antibiotics in acne management, informing evidence-based guidelines for prudent antibiotic use, alternative therapies, and potential microbiome-targeted interventions. The main conclusion is that while topical antibiotics achieve short-term clinical benefit, they exert measurable and potentially lasting perturbations on the facial skin microbiome, with implications for resistance dynamics and relapse; recommendations include iterative monitoring of microbial community structure in future management protocols, prioritization of non-antibiotic adjuncts, and development of microbiome-sparing regimens guided by ecological insights.