Table 1_Optimisation of cutaneous microbiota sampling methodology.xlsx

Introduction

The cutaneous microbiome plays an essential role in guarding against invasive pathogens and maintaining healthy skin homeostasis. Several studies have demonstrated the importance of a healthy skin microbiome through its alteration in several diseases. Differing skin characteristics across the body (temperature, pH, humidity) create distinct ecological niches inhabited by diverse microbial communities. The study of cutaneous microbiota is further complicated by numerous variables at all stages of investigation, including study design, skin sampling method, sample storage, sample processing, sequencing, and data analysis. Utilisation of standardised approaches is critical for reproducibility and comparison between skin microbiome studies. However, there is a notable lack of standardisation of sampling methodologies in the literature. Studies have employed differing sampling strategies and conditions which may affect microbiota characterisation.

Methods

Antecubital fossa was sampled from sixteen individuals using sterile dry cotton swabs or eSwabs. Sterile phosphate buffered saline, or 0.9% sterile saline were used as moistening solutions. Samples were then either stored at room temperature for 30 minutes or stored at -80°C for at least 24 hours before processing. Cutaneous microbiome was identified using 16S sequencing.

Results

Comparative analysis determined whether the type of swab (cotton/eSwab), moistening solution (saline solution/phosphate buffered saline), duration of swabbing (30 sec/1 min), and sample storage temperature (room temperature/-80°C) affect sampling and identification of skin microbial communities. Comparison of the total DNA yield extracted using different conditions showed that while moistening solution, duration of swabbing, and storage conditions did not affect the total DNA amount, using eSwabs yielded higher biomass.

Discussion

Sampling approaches are critical for the success of sequencing. The conditions investigated in this study did not influence microbiome profiling allowing consistent sampling of the microbiota. However, data clustering was affected more by individual subject than by the conditions investigated, suggesting the importance of recognizing inter-individual variability as an important factor in real-life skin microbiome studies.