Deep Phenotyping of Volatile Organic Compound Biomarkers with cIMS-ToF-MS coupled with a SICRIT ion source.

使用 cIMS-ToF-MS 结合 SICRIT 离子源对挥发性有机化合物生物标志物进行深度表型分析。

• 批准号: MR/X011941/1
• 负责人: Salman Siddiqui
• 金额: $ 86.48万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FX011941%2F1
• 关键词: Deep; Phenotyping; Volatile; Organic; Compound

The air that we breath out contains thousands of chemicals, called volatile organic compounds (VOCs). The information contained within these chemicals has great potential to help diagnose diseases such as asthma, cancer or even types of infection, as exemplified by several studies that have shown that sniffer dogs (whose noses detect different combinations of these chemicals) can diagnose certain diseases. In addition, VOC emitted in the space above culture and tissue samples acquired from patients, have shown great potential to identify different types of bacterial infection - for example in cystic fibrosis and tuberculosis. VOC in human breath and in the space above tissue samples, also tell us more broadly about the metabolism of bacteria and cells providing important insights when coupled with other metabolomic technologies to help us understand the mechanisms of disease. One of the challenges in the field of VOC analysis is that to develop accurate markers for disease diagnosis, monitoring, and to understand mechanism, we need to be able to identify VOC precisely by confirming their identity and structure using specialist equipment to detect them. Furthermore, for VOC to be useful as diagnostic tests, we need to detect them on devices that can ultimately be taken to a patient setting like a GP surgery or outpatient clinic. Finally, most of the current technologies used to discover new VOC in human breath and tissue samples are off-line and don't provide real time measurements, with results taking several hours to process and being highly analyst dependant.Our consortium based at Imperial College, London, is evaluating a new way to identify VOCs precisely (both their identity and structure), using a technique called cyclic ion mobility coupled with mass spectrometry (cIMS- ToF-MS). Whilst Ion mobility (IM) approaches have been around for over a decade to detect VOC, the proposal here is to use a new form of Ion mobility that is much more powerful at separating VOC species and can analyse the VOC in a much more precise way. The technique that we are using has already been used successfully in other fields - for example, to characterise impurity in complex mixtures such as petrochemicals, to look at how proteins fold and unfold and to deeply characterise drug metabolites that might cause toxicity to humans - to name just a few examples. The technology platform that we are deploying will enable real time (during breathing) analysis and accurate characterisation of VOC, which is critical to developing biomarkers that can ultimately be translated for the benefit of patients to smaller and portable IMS devices in relevant care settings. We will use the cIMS-ToF-MS technology to identify and characterise new VOC biomarkers in lung diseases such as asthma and chronic obstructive pulmonary disease (COPD), cystic fibrosis, rare lung diseases and cancers - across the breadth and depth of selected studies that are ongoing and planned within the Faculty of Medicine at Imperial College, London. Our consortium includes experts in the field of metabolomics including the National Phenome Centre at Imperial College, leading industry partners in the field of breath VOC detection e.g. Owlstone Medical and multiple academic partners in the UK and abroad. We hope to use the technology platform to ultimately bring rapid (within seconds), point of care (GP practice, hospital) breath based biomarkers to the clinic for the benefit of patients with a broad range of diseases.

我们呼出的空气中含有数千种化学物质，称为挥发性有机化合物（VOC）。这些化学物质中包含的信息具有很大的潜力，可以帮助诊断哮喘，癌症甚至是感染类型等疾病，几项研究表明嗅探犬（其鼻子检测这些化学物质的不同组合）可以诊断某些疾病。此外，在培养物和从患者获得的组织样本上方的空间中释放的VOC已经显示出识别不同类型的细菌感染的巨大潜力-例如在囊性纤维化和结核病中。人体呼吸中和组织样本上方空间中的VOC也更广泛地告诉我们细菌和细胞的代谢，与其他代谢组学技术相结合，帮助我们了解疾病的机制。VOC分析领域的挑战之一是，为了开发用于疾病诊断、监测和了解机制的准确标记物，我们需要能够通过使用专业设备检测它们来确认它们的身份和结构，从而精确地识别VOC。此外，对于VOC作为诊断测试有用，我们需要在最终可以用于患者设置的设备上检测它们，如GP手术或门诊诊所。最后，目前用于发现人体呼吸和组织样本中新VOC的大多数技术都是离线的，并且不提供真实的时间测量，结果需要几个小时来处理，并且高度依赖于分析师。我们位于伦敦帝国理工学院的联盟正在评估一种精确识别VOC的新方法（它们的身份和结构两者），使用称为循环离子迁移率与质谱联用（cIMS-ToF-MS）的技术。虽然离子迁移率（IM）方法已经存在了十多年来检测VOC，但这里的建议是使用一种新形式的离子迁移率，这种离子迁移率在分离VOC物质方面更强大，并且可以以更精确的方式分析VOC。我们正在使用的技术已经成功地应用于其他领域，例如，在石油化工等复杂混合物中检测杂质，观察蛋白质如何折叠和展开，以及深入检测可能对人类造成毒性的药物代谢物。我们正在部署的技术平台将实现VOC的真实的时间（呼吸期间）分析和准确表征，这对于开发生物标志物至关重要，这些生物标志物最终可以转化为相关护理环境中更小、便携式的IMS设备，以造福患者。我们将使用cIMS-ToF-MS技术来识别和鉴定肺部疾病中的新VOC生物标志物，如哮喘和慢性阻塞性肺疾病（COPD），囊性纤维化，罕见肺部疾病和癌症-在伦敦帝国理工学院正在进行和计划的选定研究的广度和深度。我们的联盟包括代谢组学领域的专家，包括帝国理工学院的国家表型组中心，呼吸VOC检测领域的领先行业合作伙伴，如Owlstone Medical以及英国和国外的多个学术合作伙伴。我们希望利用该技术平台，最终将快速（在几秒钟内）、基于呼吸的床旁（全科医生实践、医院）生物标志物带到临床，造福于患有各种疾病的患者。