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

开发头皮屑中头皮角质形成细胞脂质组的计算机模型

• 批准号: 2449792
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2449792
• 关键词: Developing; silico; model; scalp; keratinocyte

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 ObjectivesWe 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. TrainingThe 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 themesThe 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'.

头皮屑是一种常见的情况，影响10-50%的人口，无论种族如何。虽然已知微生物和宿主相关因素有助于这种多因素疾病，但潜在的分子机制尚不清楚。头皮屑被认为是一种轻微的非炎症性疾病。数据表明存在免疫参与，而转录组学和脂质组学分析显示，皮肤脂质失调水平与屏障脂质水平降低有关。在受头皮屑影响的皮肤中，免疫细胞及其产物的变化可能会影响表皮角质形成细胞的脂质组，但这一点尚未得到探讨。我们已经证明，受头皮屑影响的头皮皮肤先天淋巴细胞和树突状细胞数量减少，T细胞数量增加，具有抗炎、免疫抑制和抗瘙痒特性的脂质介质的产生增加。这些发现表明，皮肤脂质介质可能在减缓头皮屑影响皮肤的炎症应激中起作用。假设，目的和目的我们将探讨免疫渗透/激活增加影响头皮屑中角质细胞功能的假设，导致生物活性脂质的产生改变，从而可能减轻炎症环境。我们建议在体外研究与免疫细胞相互作用后表皮角质形成细胞的脂质组，并利用实验数据创建“炎症应激下角质形成细胞”的计算机模型。我们将使用我们的类二十烷酸硅模型，并进一步完善它来代表头皮角化细胞-免疫细胞反应，如在头皮屑中发现的。这将创造一个细胞-细胞相互作用的计算机预测工具，它可能成为皮肤炎症反应的预测工具，并可能取代产品开发早期阶段使用的实验模型。该学生将接受细胞培养、脂质提取、质谱脂质组学、RNASeq、计算系统生物学和生物信息学方面的最先进培训。他们还将在英国联合利华的研发实验室实习，并将深入了解科学如何发展成为技术，然后进入市场上的产品，并了解专利和知识产权。学生将受益于导师与学术、临床和工业团体的合作，并有机会参加国内和国际会议。该项目与BBSRC的战略优先领域“生物科学促进健康”和DTP的主题“世界一流的基础生物科学”相一致。该项目将探索免疫细胞和表皮角质形成细胞之间发生的相互作用，旨在了解皮肤炎症和免疫反应对头皮屑影响皮肤脂质组的影响；这将推进“分子和细胞水平上的免疫学研究”。头皮屑是一种不分种族影响很大一部分人口的疾病，了解脂质在头皮屑相关的“免疫反应”中的作用，将解决一个“人类健康问题”。利用质谱脂质组学的实验数据，我们将适应、完善和验证表皮角质形成细胞-免疫细胞-细胞相互作用的先进计算机计算机模型。这与BBSRC使用“基于系统的方法”的战略计划是一致的。将计算和生物信息学技术应用于高质量的定量生物数据（质谱分析、RNAseq）和计算机模型构建和验证（微分方程、蒙特卡罗集成建模），支持“数字生物学”的发展。