Developing an in silico model of the scalp keratinocyte lipidome in dandruff

Lead Research Organisation: University of Manchester
Department Name: School of Health Sciences

Abstract

Dandruff is a common condition, affecting 10-50% of the population, irrespective of ethnicity. Although microbial and host-related factors are known to contribute to this multifactorial condition, the underlying molecular mechanism(s) are not yet understood. Dandruff is considered a mild non-inflammatory condition. Data suggest that there is immune involvement, whilst transcriptomics and lipidomics analyses show a level of cutaneous lipid dysregulation with reduced levels of barrier lipids. It is possible that changes in immune cells and their products in dandruff-affected skin might influence the lipidome of epidermal keratinocytes, but this has not yet been explored.
We have shown that dandruff-affected scalp skin has decreased numbers of innate lymphoid and dendritic cells, increased numbers T cells, and increased production of lipid mediators with anti-inflammatory immunosuppressive and anti-pruritic properties. These findings indicate that skin lipid mediators may have a role in moderating the inflammatory stress observed in dandruff-affected skin.
Hypothesis, Aim and Objectives
We will explore the hypothesis that increased immune infiltrate/activation affects keratinocyte function in dandruff, leading to altered production of bioactive lipids that might mitigate the inflammatory environment. We propose to study the lipidome of epidermal keratinocytes following interactions with immune cells in vitro and use the experimental data to create an in silico model of the 'keratinocyte under inflammatory stress'. We will use our in silico model of eicosanoids and further refine it to represent the scalp keratinocyte-immune cell reactions, as found in dandruff. This will create an in silico predictive tool for cell-cell interactions, that could become a predictive tool for skin inflammatory reactions and may replace experimental models used in the early stages of product development.
Training
The student will receive state-of-the-art training in cell culture, lipid extractions, mass spectrometry lipidomics, RNASeq, computational systems biology and bioinformatics. They will also undertake placements in a UK Unilever R&D lab and will develop insight into how science develops into technologies and then into products on the marker, and gain an understanding of patenting and intellectual property. The student will benefit from the supervisors' collaborations with academic, clinical and industrial groups, and get the opportunity to attend national and international meetings and conferences.
Alignment with the BBSRC remit and DTA themes
The project aligns with the BBSRC's strategic priority area of Bioscience for Health and the DTP theme World Class Underpinning Biosciences. The project will explore the interactions occurring between immune cells and epidermal keratinocytes aiming to understand the impact of cutaneous inflammatory and immune reactions on the lipidome of dandruff-affected skin; this will advance 'immunological research at molecular and cellular level'. Understanding the role of lipids in the 'immune responses' involved in dandruff, a condition that affects a large proportion of the population irrespective of ethnicity, will be addressing a 'human health issue'. Using experimental data from mass spectrometry lipidomics we will adapt, refine and validate an advanced computational in silico model of epidermal keratinocyte-immune cell-cell interactions. This aligns with the BBSRC's strategic plan in using 'systems-based approaches'. The application of computational and bioinformatics techniques to high-quality quantitative biological data (mass spectrometry, RNAseq) and in silico model construction and validation (differential equations, Monte Carlo ensemble modelling), support the development of 'digital biology'.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/V509474/1 30/09/2020 31/12/2024
2449792 Studentship BB/V509474/1 30/09/2020 31/12/2024