MUSCLE: Multi-platform Unbiased-optimisation of Spectrometry via Closed-Loop Experimentation

MUSCLE：通过闭环实验对光谱测量进行多平台无偏优化

• 批准号: BB/I023755/1
• 负责人: Joshua Knowles
• 金额: $ 3.47万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2012
• 资助国家: 英国
• 起止时间: 2012 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FI023755%2F1
• 关键词: MUSCLE; Multi; platform; Unbiased; optimisation

Mass spectrometry (MS) is an extremely widely used tool in biology that enables us to measure a wide range of chemicals, including metabolites, peptides and proteins. These measurements are critical for helping us to understand how cells and organisms function at a molecular level. Typically, mass spectrometers are coupled to chromatography. So called liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) are extremely common tools in labs in universities and industry. Direct infusion mass spectrometry (DIMS) is also used in some fields due to its measurement rapidity. Regardless of whether a chemist is using LC-MS, GC-MS or DIMS, the development of new analytical methods on a mass spectrometer is extremely time consuming and challenging; e.g., it took one experienced scientist more than a year of effort to develop an optimised LC-MS method for analysing 13 biochemicals (in letters of support). After a method has been published, other scientists will often want to replicate it in their own labs. Yet even this can take considerable time and resources. The primary reason why optimising an MS method is so difficult and time consuming is because the scientist is faced with a very large number of settings for controlling the instrument. Varying all the settings systematically to optimise an analysis is impossible because of the astronomical number of combinations that are possible. So how can we develop these MS methods much more quickly and efficiently? If a solution can be found, labs could develop and implement more MS methods of significantly improved quality, opening up a plethora of novel biological investigations. Also, time savings would translate directly into cost savings, with obvious benefits to universities and industry. Previously we developed computer software that enabled a chemist to optimise automatically their mass spectrometer. We did this for specific LC-MS and GC-MS instruments. Not only was this procedure fully automated, but it greatly improved the analytical method by detecting three times as many biochemicals (revealing new biology), and it only took a few days of automated optimisation to achieve this exciting result. This was published in a leading journal, and read with enthusiasm by the scientific community. Unfortunately, scientists in other labs have not been able to use this software as it was programmed to control only three specific mass spectrometers. Also, it was done in such a manner that reprogramming it for each additional mass spectrometer would be challenging and time consuming. There is now an urgent need for this software to be redeveloped and expanded, so that it can be used to optimise methods on any mass spectrometer in any laboratory. This need, together with the great benefits that would result including considerable time and cost savings, is explained and justified in 12 letters of support that accompany our proposal. These letters are written by scientists in universities, industry and government labs across the world. Our proposal includes two major international companies, GSK and Dionex, as Project Partners. We will develop novel user-friendly software that can control LC-MS, GC-MS and DIMS instruments, which will enable the rapid, robust and fully automated optimisation of MS methods. We will thoroughly test this software on several instruments from several manufacturers. We will also establish this software, and associated 'application control scripts' for controlling a range of mass spectrometers and chromatographs, as a community resource. One way that we will achieve this is by setting up and maintaining a dedicated interactive website for the software. This will include training material (e.g. as a podcast), and the capability for users to upload and share their own application control scripts and to provide feedback. Ultimately this software tool - MUSCLE - promises to facilitate the ever growing use of MS in biology.

质谱（MS）是生物学中使用极为广泛的工具，它使我们能够测量各种化学物质，包括代谢物、肽和蛋白质。这些测量对于帮助我们了解细胞和生物体在分子水平上的功能是至关重要的。通常，质谱仪与色谱联用。所谓的液相色谱-质谱法（LC-MS）和气相色谱-质谱法（GC-MS）是大学和工业实验室中非常常见的工具。直接输注质谱法（DIMS）由于测量速度快，在一些领域也得到了应用。无论化学家是使用LC-MS， GC-MS还是DIMS，在质谱仪上开发新的分析方法都是非常耗时和具有挑战性的；例如，一位经验丰富的科学家花了一年多的时间才开发出一种优化的LC-MS方法来分析13种生化物质（在支持信中）。一种方法发表后，其他科学家通常会想在自己的实验室里复制它。然而，即使这样也需要大量的时间和资源。优化质谱方法如此困难和耗时的主要原因是科学家面临着控制仪器的大量设置。系统地改变所有设置以优化分析是不可能的，因为可能的组合数量是天文数字。那么我们怎样才能更快更有效地开发这些质谱方法呢？如果能找到解决方案，实验室可以开发和实施更多质量显著提高的质谱方法，开辟大量新的生物学研究。此外，时间的节省将直接转化为成本的节省，这对大学和工业有明显的好处。以前，我们开发了计算机软件，使化学家能够自动优化他们的质谱仪。我们对特定的LC-MS和GC-MS仪器这样做。这一过程不仅完全自动化，而且通过检测三倍的生化物质（揭示新的生物学）大大改进了分析方法，而且只花了几天的自动化优化就实现了这一令人兴奋的结果。这篇文章发表在一本重要的杂志上，科学界热情地阅读了它。不幸的是，其他实验室的科学家还不能使用这个软件，因为它被编程为只能控制三个特定的质谱仪。此外，它是以这样一种方式完成的，即为每一个额外的质谱仪重新编程将是具有挑战性和耗时的。现在迫切需要重新开发和扩展该软件，以便它可以用于优化任何实验室的任何质谱仪的方法。这一需求以及由此带来的巨大好处，包括节省大量的时间和成本，在我们的提案附带的12封支持信中得到了解释和证明。这些信件是由世界各地的大学、工业和政府实验室的科学家撰写的。我们的提案包括两家主要的国际公司，GSK和Dionex作为项目合作伙伴。我们将开发新的用户友好软件，可以控制LC-MS， GC-MS和DIMS仪器，这将使MS方法快速，稳健和全自动优化。我们将在几个制造商的几个仪器上彻底测试这个软件。我们还将建立该软件，以及相关的“应用控制脚本”，用于控制一系列质谱仪和色谱仪，作为社区资源。我们实现这一目标的一种方式是为软件建立和维护一个专门的互动网站。这将包括培训材料（例如作为播客），以及用户上传和分享他们自己的应用程序控制脚本并提供反馈的能力。最终，这个软件工具——MUSCLE——有望促进MS在生物学中不断增长的应用。

项目成果

MUSCLE: automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis.

• DOI: 10.1093/bioinformatics/btu740
• 发表时间: 2015-03-15
• 期刊: Bioinformatics (Oxford, England)
• 作者: Bradbury J;Genta-Jouve G;Allwood JW;Dunn WB;Goodacre R;Knowles JD;He S;Viant MR
• 通讯作者: Viant MR