Unifying metabolome and proteome informatics

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Biologists are increasing wishing to understand the complex interactions between the building blocks of genes, metabolites and proteins that control the function of every living organism. The field of systems biology has emerged to overcome the deficiencies of the traditional reductionist approach, which has identified the building blocks themselves and many of the individual interactions but has not been able to deduce how systems of these blocks act and react in unison. The application of systems biology is widespread, as it promises to revolutionise our understanding of healthy processes in plants, animals and humans, as well as how they break down under disease and how this breakdown can be averted.Often the systems biology approach starts with a 'snapshot' of a particular biological sample. Mass spectrometry is a pervasive technique for gaining a snapshot of a sample, and it does this by ionising the sample and then measuring each constituent compound's mass and quantity based on the resulting charge. This is often not enough to separate out the sample fully and therefore a preceding phase of liquid or gas chromatography is used to provide an initial separation. Classes of protein and metabolite require different sample preparation, ionisation and chromatography approaches. These all add different kinds of biases and variation which make it extremely challenging to infer links between compounds, especially if the compounds are from different classes. To make matters worse, many snapshots are needed to capture different 'angles' of the biological process under investigation, and the instrumental conditions themselves are not entirely reproducible over time. All this has led systems biology to become a progressively computational discipline.The academic disciplines for studying global patterns of proteins ('proteomics') and metabolites ('metabolites') have broadly originated from different fields, and therefore there is little synergy between the two. This is also the case for the computational aspect, despite the fact both are applied to mass spectrometry data. Cross-fertilisation of methodology and ideas therefore has the prospect of seeding novel, effective new approaches of analysis. The project team is involved in the development of the prominent mzMatch and ProteoSuite informatics packages for metabolomics and proteomics respectively. They are the most actively developed academic metabolome and proteome informatics packages in the UK. Therefore there is a timely opportunity to lead a concerted effort bringing together the informatics community, methodology and software for metabolomics and proteomics to: (a) Establish a new, powerful unified informatics workflow 'borrowing strength' in methodology advancements across both fields, greater than the sum of its parts and with coherent statistical properties enabling optimal integration into systems biology research; (b) Underpin cross-disciplinary collaborations, new understanding and mobility between metabolomics and proteomics fields; and (c) Support development of joint data exchange and reporting standards for optimal integration of metabolomics and proteomics data. To achieve this, we will first integrate mzMatch into ProteoSuite with unified data exchange and reporting. This will then enable the development of the novel unified informatics pipeline. The key is to use the same underlying statistical methodology for both types of omics, with analysis differing only in biological models utilised, thus underpinning coherent delivery to downstream systems biology modelling. We will also spearhead a programme of community involvement to encourage long-term community participation in the unified informatics approach. This will include an international one-day workshop drawing in leading groups from both metabolome and proteome informatics disciplines for the first time, in order to foster a shared mind-set towards unifying the two fields.