Development of an Efficient Extraction Methodology to Analyse Potential Inflammatory Biomarkers from Sebum.

Proteins, such as cytokines and chemokines, are present in varying concentrations in a range of biofluids, with an important signalling role in maintaining homeostasis. Commercial tapes have been employed to non-invasively collect these potential biomarkers in sebum from the skin surface to examine their concentrations in conditions including acne, atopic dermatitis, and pressure ulcers. However, the identification of robust biomarker candidates is limited by the low abundance of specific proteins extracted by current methodologies. Therefore, this study was designed to develop an optimized extraction method for potential inflammatory biomarkers in sebum collected with Sebutapes. Commercial tapes (Sebutapes) coated with synthetic sebum were used to systematically evaluate the effects of chemical and mechanical stimuli on extraction efficiency. Varying concentrations of high- and low-abundance biomarkers (IL-1α, IL-6, IL-8, INF-γ, TNF-α, and IL-1RA) were used to spike the synthetic sebum samples. Methodological variables included different surfactants, mechanical stimuli, and buffer volume. Extraction efficiency was estimated using immunoassay kits from the extracted buffer. The results revealed that the use of a surfactant, i.e., β-dodecyl maltoside, in addition to the mechanical stimuli, namely, sonication and centrifugation, resulted in an increased recovery of cytokines, ranging from 80% for high-abundant cytokines, such as IL-1α and IL-1RA, and up to 50% for low-abundance cytokines, including TNF-α, IL-6 and IL-8. Compared to previous methods, the new extraction protocol resulted in between a 1.5-2.0-fold increase in extraction efficiency. The study revealed that there was a high degree of variability in the extraction efficiency of different cytokines. However, improved efficiency was achieved across all cytokines with selective surfactants and mechanical stimuli. The optimised protocol will provide means to detect low levels of potential biomarkers from skin surface, enabling the evaluation of local changes in pro- and anti-inflammatory cytokines present in different skin conditions.

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