Improved lipid analysis to inform future therapeutic strategies

改进脂质分析以指导未来的治疗策略

• 批准号: 2679337
• 金额: --
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2679337
• 关键词: Improved; lipid; analysis; inform; future

Antimicrobial resistance (AMR) threatens to rival cancer in mortality and financial burden by 2050. Mycobacterial infections are the primary bacterial cause of global morbidity and mortality (2 million deaths annually), costing $12 billion, with lipids implicated in AMR1. Medulloblastoma is the most common malignant child brain tumour, with various phospholipids implicated in tumour metastastasis2. Because lipids are indicative of disease/progression and impact therapeutic strategies/success it is imperative to have sensitive methods of detection and identification directly from biological samples.Surface-sampling MS approaches offer the benefit of direct analysis and imaging; recent advances in instrumentation allow coupling to high resolution (trapping) mass analysers (HRMS), offering high accurate mass analysis3,4, aiding identification. Complementary approaches will be utilised; secondary ion MS (SIMS), ambient pressure (AP) matrix-assisted laser desorption/ionisation (MALDI) and liquid extraction surface analysis (LESA).Lipid analysis is complicated by the formation of (naturally occurring) adducts ([M+H]+, [M+Na]+, [M+K]+), decreasing sensitivity and complicating assignments. Salt additives have been shown to afford improvements in sensitivity, decrease spectral complexity and identification via MALDI and LESA5,6. MALDI matrix enhancement can also improve SIMS (ME-SIMS)7, and hasn't been investigated via OrbiSIMS. This project will deliver sensitive analytical methods for the direct detection and identification of lipids implicated in disease/infection.

到2050年，抗菌素耐药性（AMR）在死亡率和经济负担方面可能与癌症相媲美。分枝杆菌感染是全球发病率和死亡率（每年200万人死亡）的主要细菌原因，耗资120亿美元，其中脂质与AMR 1有关。髓母细胞瘤是最常见的儿童恶性脑肿瘤，各种磷脂参与肿瘤转移2。由于脂质是疾病/进展和影响治疗策略/成功的指示，因此必须有直接从生物样品中检测和鉴定的灵敏方法。表面采样MS方法提供直接分析和成像的好处;仪器的最新进展允许耦合到高分辨率（捕获）质量分析仪（HRMS），提供高精度的质量分析3，4，帮助鉴定。将使用补充方法;二次离子MS（西姆斯）、环境压力（AP）基质辅助激光解吸/电离（MALDI）和液体萃取表面分析（LESA）。脂质分析因（天然存在的）加合物（[M+H]+、[M+Na]+、[M+K]+）的形成而复杂化，从而降低灵敏度并使分配复杂化。盐添加剂已被证明可以提高灵敏度，降低光谱复杂性，并通过MALDI和LESA进行识别5，6。MALDI矩阵增强也可以改善西姆斯（ME-SIMS）7，尚未通过OrbiSIMS进行研究。该项目将提供灵敏的分析方法，用于直接检测和鉴定与疾病/感染有关的脂质。