Open source pipelines for integrated metabolomics analysis by NMR and mass spectrometry

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Research in the Life Sciences is now commonly performed using high-tech instrumentation, producing very large amounts of data about a system of interest. These techniques are collectively called 'omics (e.g. including genomics, proteomics and metabolomics) - and in different ways can measure how genes are switched on or off, how the proteins encoded by those genes behave in a cell or tissue of interest, or how the metabolites (biochemical molecules in cells) change in abundance, as the system behaves normally or is put under stress by disease, dysfunction or the introduction of toxic substances. The metabolites studied can include molecules that provide energy or structure to cells (e.g. fats, sugars etc), the structural building blocks of DNA and proteins (e.g. nucleotides, amino acids) and essential co-factors to biological processes (e.g. vitamins). In fundamental research, and in clinical situations, the presence of a particular metabolite at an unusual abundance can be an indicator (a biomarker) of a particular state - such as a disease. Indeed, metabolomics research is applied in studies on cancer, infectious disease, heart disease, diabetes and many others. One of the greatest challenges in metabolomics research is that the analysis of the data is very difficult. Multiple different processing steps are needed to get from the raw data as delivered by the instrument - primarily nuclear magnetic resonance (NMR) spectroscopy or mass spectrometry (MS), to the final results the researcher is interested in, i.e. quantitative and statistically significant differences in particular metabolites between samples. There are multiple software packages (both commercial and free) that can perform individual steps within a complete pipeline, but there is very little good software that makes it easy to perform a full analysis. In this project, we will build such software for data generated from NMR or MS, using a software framework called Galaxy. Galaxy has been designed to construct a web interface on top of other software packages, enabling different (previously disconnected) packages to be joined together into an easy to use pipeline. The joining together of modules needs data files in a standardized format as the input and output of each step, so we will also work within international organizations to help agree on a universally applied standard format to be used in our pipeline and by other software developers working in metabolomics. Our pipeline will make it much easier for scientists to analyse their data and, in particular, to compare or integrate data coming from both complementary techniques (NMR and MS) to get a more complete picture of the system being studied. This will facilitate many more researchers - who currently lack detailed knowledge in metabolomics - to embrace and exploit this powerful technology. Lastly, we will make it easier for scientists to put their data into public databases when they publish their research, enabling other scientists to verify their findings and in some cases re-analyse their data in their own labs.