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

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.

Mass spectrometry (MS) is an essential tool in 21st century biology for measuring metabolites, peptides, proteins and other chemicals. However, the development of analytical methods using LC-MS, GC-MS or direct infusion mass spectrometry (DIMS) is extremely time consuming and thus expensive; e.g. it can take more than a year of intensive effort by a skilled chemist to develop a method (see letters). Transferring existing methods between instruments also places a considerable burden on the analyst. This bottleneck significantly impedes our ability to establish new bioanalytical methods, e.g. for understanding molecular mechanisms underpinning health. Previously we developed a closed-loop strategy for the automated optimisation of metabolomics analyses on three platforms: Leco GC-ToF-MS and GCxGC-ToF-MS, and Waters LC-ToF-MS. This approach considerably increased the quality of analysis (3-fold increase in metabolites detected) within only a few days of optimisation. Unsurprisingly, this created significant interest in the research community, both in academia and industry (see letters). Unfortunately, our original software implementation was time consuming to program, and specific to each of just three platforms and software. Furthermore, reprogramming the software for any additional MS platform would be difficult and time intensive. This has seriously impacted the deployability of our software. Here we will develop and implement a multi-platform, user-friendly software tool for the robust, objective and automated optimisation of both targeted and non-targeted MS analyses. We will validate the software on several LC-MS, GC-MS and DIMS instrument configurations, from several manufacturers. Also we will establish the software and associated application control scripts as a community resource, enabling widespread dissemination and uptake. Ultimately this promises to expedite the development of new MS methods leading to an advance of our knowledge in the biosciences.

Who will benefit from this research? As discussed in the Academic Beneficiaries section, the twelve letters of support for our proposal provide extensive evidence of how this software will benefit scientists that utilise mass spectrometry-based approaches in: (1) academic laboratories: metabolomics and proteomics researchers; academics developing targeted analyses of metabolites, peptides or proteins in biology; more widely by analytical chemists developing and implementing MS-based approaches in other matrices, including foods, biofuels, environmental samples etc.; (2) industry, specifically end-users who wish to apply the software to improve the quality of their analyses, or expedite the development of new analytical methods, for example AstraZeneca (collaborator) and GSK (Project Partner); (3) industry, specifically the manufacturers of mass spectrometers and chromatography instrumentation, for example Dionex (Project Partner), Thermo Fisher Scientific and Advion Biosciences (both collaborators). This sector of industry will benefit via the enhanced ability of their customers to use and develop complex analytical methods; (4) governmental end-users, similar to point 2, by improving their ability to more easily develop optimised mass spectrometry methods, for example the US Department of Agriculture and the US Environmental Protection Agency (both collaborators). In addition, the release of an effective software package for the automated optimisation of MS instruments is likely to attract attention to the potential of such automated optimisation approaches in the biosciences more generally. This could help to drive development of better optimisation algorithms, benefiting computer scientists and future end-users alike. How will they benefit from this research? There will be several direct benefits to the bioanalytical chemist. Whether they are developing novel analytical methods, implementing previously published analytical methods in a new laboratory, or transferring analytical methods across instruments within their own laboratory, this process will become: (1) easier, (2) much more rapid, (3) considerably less expensive, and importantly, (4) of improved quality of analysis. In turn, this will facilitate the analyst to (5) attempt method development and optimisation that they could not previously consider, leading to (6) discovery of new biological (or biomedical or environmental) information. It is not at all surprisingly that the pharmaceutical industries are also excited by this proposed project, as time and therefore cost savings could be immense. This in turn impacts positively on that sector, indirectly leading to an improvement in the nation's wealth. In cases where this automated approach is used in biomedical applications, the improved quality of analytical methods will lead to the discovery of new knowledge about health and disease, including in the area of medical diagnostics. Ultimately this has the potential to impact positively on the nation's health. The direct benefits to analytical chemists will start to be realised as soon as the software is completed and distributed, i.e., starting immediately after the 1-year project. As we plan to continue the support of MUSCLE as a tool for the scientific community, benefits will continue into the future. In terms of improvements to the nation's health and wealth, these could also start to be realised within 1-3 years of completion of the grant, dependent upon the rate of uptake of MUSCLE into the relevant communities. Mechanisms for dissemination to scientists and to the general public are described in our Pathways to Impact document.