Microbial lipidomics

微生物脂质组学

• 批准号: RGPIN-2022-04433
• 负责人: Goodlett, David
• 金额: $ 2.4万
• 依托单位: University of Victoria
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=744217
• 关键词: Microbial; lipidomics

Lipids are essential components of microbial cell membranes, creating an interface between the microbial cell and its environment. Biological activities of lipids are dependent on their structure (Structure Activity Relationship; SAR). Microbes display a vast array of lipid structure modifications that alter the outer membrane charge and fluidity, and enable them to survive exposure to antimicrobials, and osmolality and temperature shifts. Structure is also detrimental to recognition of lipids by the host immune receptors. Some pathogens therefore switch to production of lipid molecules with low inflammatory potential when establishing infection. In order to better define lipid SARs, we will develop methods that allow analysis of lipid structures without need to culture in vitro, which is known to result in changes to structure that impact function. Thus lipid structures that accurately reflect those present in vivo are needed. The goal of this proposal is to develop novel techniques for studying microbial lipids as they exist in their native environments, and to train highly qualified personnel specialized in mass spectrometry (MS) and allied tools for characterization of microbial lipids. We will focus on the following four 5-year objectives that will improve knowledge on SAR of microbial lipids and in doing so train HQP. HQP will be trained in the following specific areas: (1) Increase sensitivity of MS-based microbial lipids analysis. Microfluidics-based separation and concentration techniques will be employed to identify microbial lipids directly from complex biological samples. We will also explore nanoPOTS (nanodroplet processing in one pot for trace samples) to progress towards single cell lipid analysis. (2) Expand our existing library of microbial lipids (BACLIB) by addition of lipids from aquatic, terrestrial and clinical environments. (3) Optimize transmission-mode Matrix Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) for detection of microbial lipids in situ at or near the single cell level. (4) Develop computational models that aid microbial lipid characterization. Artificial intelligence (AI)-based models that will aid microbial lipid structure characterization will be developed. We will also employ in silico models to predict host receptor binding to microbial lipids and use these predictions to create lipid activity profiles. The short-term goals of this proposal are focused on training HQP who will develop technologies that allow microbial lipid structure assignments directly from environmental and clinical specimens without need for culture. These goals are in-line with our long-term objective to understand SAR of microbial lipids - a key to understanding how microbes adapt to distinct environments and how they elicit host response - and to use this knowledge to improve diagnostic specificity and targeted prevention and treatment of microbial maladies from biofilms to infections.

脂质是微生物细胞膜的重要组成部分，在微生物细胞和环境之间建立了一个界面。脂类的生物活性取决于其结构（结构活性关系；SAR）。微生物表现出大量的脂质结构修饰，改变了外膜的电荷和流动性，使它们能够在暴露于抗菌剂、渗透压和温度变化下存活。结构也不利于宿主免疫受体对脂质的识别。因此，一些病原体在建立感染时转而产生具有低炎症潜力的脂质分子。为了更好地定义脂质SARs，我们将开发不需要体外培养就能分析脂质结构的方法，因为体外培养会导致影响功能的结构变化。因此，需要准确反映体内存在的脂质结构。本提案的目标是开发新的技术来研究微生物脂质，因为它们存在于其原生环境中，并培养高素质的专业人员质谱（MS）和相关工具来表征微生物脂质。我们将重点关注以下4个5年目标，这些目标将提高微生物脂质SAR的知识，并在此过程中训练HQP。HQP将在以下特定领域进行培训：(1)提高MS-based微生物脂质分析的敏感性。基于微流体的分离和浓缩技术将用于从复杂的生物样品中直接鉴定微生物脂质。我们还将探索纳米液滴（在一个锅中处理痕量样品），以进行单细胞脂质分析。(2)通过增加来自水生、陆生和临床环境的脂类来扩展我们现有的微生物脂类库（BACLIB）。(3)优化透射模式矩阵辅助激光解吸/电离质谱成像（MALDI-MSI）在单细胞水平或附近原位检测微生物脂质。(4)建立有助于微生物脂质表征的计算模型。将开发有助于微生物脂质结构表征的基于人工智能（AI）的模型。我们还将采用硅模型来预测宿主受体与微生物脂质的结合，并使用这些预测来创建脂质活性谱。本提案的短期目标集中在培训HQP，他们将开发技术，允许直接从环境和临床标本中进行微生物脂质结构分配，而无需培养。这些目标与我们了解微生物脂质的SAR的长期目标是一致的-这是了解微生物如何适应不同环境以及它们如何引发宿主反应的关键-并利用这些知识来提高诊断特异性和有针对性的预防和治疗从生物膜到感染的微生物疾病。