Computational tools and workflows in metabolomics: An international survey highlights the opportunity for harmonisation through Galaxy

Weber, Ralf; Lawson, Thomas N.; Salek, Reza M.; Ebbels, Timothy M. D.; Glen, Robert C.; Goodacre, Royston; Griffin, Julian L.; Haug, Kenneth; Koulman, Albert; Moreno, Pablo; Ralser, Markus; Steinbeck, Christoph; Dunn, Warwick B.; Viant, Mark R.

doi:10.1007/s11306-016-1147-x

Cited by 74 publications

(60 citation statements)

References 12 publications

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“…This approach paired with high acquisitions speed (>1 Hz) of state of the art instruments results in thousands of spectra per LC-MS/MS run. For a reliable data analysis and reproducible interpretation of the results, bioinformatic workflows including comprehensive databases and statistical significance estimation are crucial (da Silva et al, 2015;Böcker, 2017;Scheubert et al, 2017;Weber et al, 2017) and have been very recently employed for marine metabolomic studies Hartmann et al, 2017;Kujawinski et al, 2017;Longnecker and Kujawinski, 2017). With these new bioinformatic tools and instrumental improvements in sensitivity, acquisition speed and resolution we anticipate that the techniques used for DOM characterization will further shift toward non-targeted analyses using high-resolution LC-MS/MS that provide inventories of molecular structures in complex environmental datasets.…”

Section: Introductionmentioning

confidence: 99%

High-Resolution Liquid Chromatography Tandem Mass Spectrometry Enables Large Scale Molecular Characterization of Dissolved Organic Matter

et al. 2017

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Dissolved organic matter (DOM) is arguably one of the most complex exometabolomes on earth, and is comprised of thousands of compounds, that together contribute more than 600 × 10 15 g carbon. This reservoir is primarily the product of interactions between the upper ocean's microbial food web, yet abiotic processes that occur over millennia have also modified many of its molecules. The compounds within this reservoir play important roles in determining the rate and extent of element exchange between inorganic reservoirs and the marine biosphere, while also mediating microbe-microbe interactions. As such, there has been a widespread effort to characterize DOM using high-resolution analytical methods including nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS). To date, molecular information in DOM has been primarily obtained through calculated molecular formulas from exact mass. This approach has the advantage of being non-targeted, accessing the inherent complexity of DOM. Molecular structures are however still elusive and the most commonly used instruments are costly. More recently, tandem mass spectrometry has been employed to more precisely identify DOM components through comparison to library mass spectra. Here we describe a data acquisition and analysis workflow that expands the repertoire of high-resolution analytical approaches available to access the complexity of DOM molecules that are amenable to electrospray ionization (ESI) MS. We couple liquid chromatographic separation with tandem MS (LC-MS/MS) and a data analysis pipeline, that integrates peak extraction from extracted ion chromatograms (XIC), molecular formula calculation and molecular networking. This provides more precise structural characterization. Although only around 1% of detectable DOM compounds can be annotated through publicly available spectral libraries, community-wide participation in populating and annotating DOM datasets could rapidly increase the annotation rate and should be broadly encouraged. Our analysis also identifies shortcomings of the current Petras et al. LC-MS/MS Analysis of DOMdata analysis workflow that need to be addressed by the community in the future. This work will lay the foundation for an integrative, non-targeted molecular analysis of DOM which, together with next generation sequencing, meta-proteomics and physical data, will pave the way to a more comprehensive understanding of the role of DOM in structuring marine ecosystems.

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Section: Introductionmentioning

confidence: 99%

High-Resolution Liquid Chromatography Tandem Mass Spectrometry Enables Large Scale Molecular Characterization of Dissolved Organic Matter

et al. 2017

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“…These tools, however, usually come with their own software dependencies, resource requirements and scripting languages. As a consequence, configuring and running them is often complicated, especially for researchers who are untrained in computer science [4]. Furthermore, many tools require users to input parameters that can significantly affect results and performance, and reporting of these parameters is not always clear [8].…”

Section: Findings Backgroundmentioning

confidence: 99%

PhenoMeNal: Processing and analysis of Metabolomics data in the Cloud

Peters

Bradbury

Bergmann

et al. 2018

Preprint

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Background: Metabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organism's metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological and many other applied biological domains. Its computationally-intensive nature has driven requirements for open data formats, data repositories and data analysis tools. However, the rapid progress has resulted in a mosaic of independent -and sometimes incompatible -analysis methods that are difficult to connect into a useful and complete data analysis solution. Findings: The PhenoMeNal (Phenome and Metabolome aNalysis) e-infrastructure provides a complete, workflow-oriented, interoperable metabolomics data analysis solution for a modern infrastructure-as-a-service (IaaS) cloud platform. PhenoMeNal seamlessly integrates a wide array of existing open source tools which are tested and packaged as Docker containers through the project's continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardized, automated and published analysis workflows in the user interfaces Galaxy, Jupyter, Luigi and Pachyderm. Conclusions: PhenoMeNal constitutes a keystone solution in cloud infrastructures available for metabolomics. It provides scientists with a ready-to-use, workflow-driven, reproducible and shareable data analysis platform harmonizing the software installation and configuration through user-friendly web interfaces. The deployed cloud environments can be dynamically scaled to enable large-scale analyses which are interfaced through standard data formats, versioned, and have been tested for reproducibility and interoperability. The flexible implementation of PhenoMeNal allows easy adaptation of the infrastructure to other application areas and 'omics research domains.

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“…Comprehensive workflows for preprocessing, statistical analysis, and annotation of data from liquid chromatography - MS (LC-MS), direct infusion MS (DIMS), gas chromatography - MS (GC-MS), and NMR technologies can be created, tailored, run, saved, shared, and publicly referenced with digital object identifiers ( http://workflow4metabolomics.org/referenced_W4M_histories). A recent questionnaire has shown a need to further develop such tools and workflows, as part Galaxy, that are well supported through community-based training, to further improve the standardisation and automation of data processing and analysis 38 .…”

Section: Alignment With Elixir Platformsmentioning

confidence: 99%

The future of metabolomics in ELIXIR

Rijswijk

Beirnaert

Caron³

et al. 2017

F1000Res

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Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the “Future of metabolomics in ELIXIR” was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.

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Computational tools and workflows in metabolomics: An international survey highlights the opportunity for harmonisation through Galaxy

Cited by 74 publications

References 12 publications

High-Resolution Liquid Chromatography Tandem Mass Spectrometry Enables Large Scale Molecular Characterization of Dissolved Organic Matter

High-Resolution Liquid Chromatography Tandem Mass Spectrometry Enables Large Scale Molecular Characterization of Dissolved Organic Matter

PhenoMeNal: Processing and analysis of Metabolomics data in the Cloud

The future of metabolomics in ELIXIR

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