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MEMOTE for standardized genome-scale metabolic model testing

Nature Biotechnology volume 38, pages 272–276 (2020)Cite this article

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A Publisher Correction to this article was published on 19 March 2020

This article has been updated

To the Editor — Reconstructing metabolic reaction networks enables the development of testable hypotheses of an organism’s metabolism under different conditions1. State-of-the-art genome-scale metabolic models (GEMs) can include thousands of metabolites and reactions that are assigned to subcellular locations. Gene–protein–reaction (GPR) rules and annotations using database information can add meta-information to GEMs. GEMs with metadata can be built using standard reconstruction protocols2, and guidelines have been put in place for tracking provenance and enabling interoperability, but a standardized means of quality control for GEMs is lacking3. Here we report a community effort to develop a test suite named MEMOTE (for metabolic model tests) to assess GEM quality.

Incompatible description formats and missing annotations4 limit GEM reuse. Moreover, numerical errors5 and omission of essential cofactors6 in a single biomass objective function can have substantial impact on the predictive performance of a GEM. Failure to make checks for flux cycles and imbalances can render model predictions untrustworthy7.

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Fig. 1: Graphical summary of MEMOTE.
Fig. 2: Quality of manually reconstructed GEMs from collections without quality control or quality assurance.

Data availability

The model collection is available at https://doi.org/10.5281/zenodo.2636858. Individual results and aggregated tables, as well as analysis code, are available at https://doi.org/10.5281/zenodo.2638234.

Code availability

MEMOTE source code is available at https://github.com/opencobra/memote under the Apache license, version 2.0. Supporting documentation is available at https://memote.readthedocs.io/en/latest/. The MEMOTE web interface is hosted at https://memote.io. A detailed list of all tests in MEMOTE is available at https://memote.readthedocs.io/en/latest/autoapi/index.html.

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Acknowledgements

We acknowledge D. Dannaher and A. Lopez for their supporting work on the Angular parts of MEMOTE; resources and support from the DTU Computing Center; J. Cardoso, S. Gudmundsson, K. Jensen and D. Lappa for their feedback on conceptual details; and P. D. Karp and I. Thiele for critically reviewing the manuscript. We thank J. Daniel, T. Kristjánsdóttir, J. Saez-Saez, S. Sulheim, and P. Tubergen for being early adopters of MEMOTE and for providing written testimonials. J.O.V. received the Research Council of Norway grants 244164 (GenoSysFat), 248792 (DigiSal) and 248810 (Digital Life Norway); M.Z. received the Research Council of Norway grant 244164 (GenoSysFat); C.L. received funding from the Innovation Fund Denmark (project “Environmentally Friendly Protein Production (EFPro2)”); C.L., A.K., N. S., M.B., M.A., D.M., P.M, B.J.S., P.V., K.R.P. and M.H. received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 686070 (DD-DeCaF); B.G.O., F.T.B. and A.D. acknowledge funding from the US National Institutes of Health (NIH, grant number 2R01GM070923-13); A.D. was supported by infrastructural funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), Cluster of Excellence EXC 2124 Controlling Microbes to Fight Infections; N.E.L. received funding from NIGMS R35 GM119850, Novo Nordisk Foundation NNF10CC1016517 and the Keck Foundation; A.R. received a Lilly Innovation Fellowship Award; B.G.-J. and J. Nogales received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no 686585 for the project LIAR, and the Spanish Ministry of Economy and Competitivity through the RobDcode grant (BIO2014-59528-JIN); L.M.B. has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 633962 for project P4SB; R.F. received funding from the US Department of Energy, Offices of Advanced Scientific Computing Research and the Biological and Environmental Research as part of the Scientific Discovery Through Advanced Computing program, grant DE-SC0010429; A.M., C.Z., S.L. and J. Nielsen received funding from The Knut and Alice Wallenberg Foundation, Advanced Computing program, grant #DE-SC0010429; S.K.’s work was in part supported by the German Federal Ministry of Education and Research (de.NBI partner project “ModSim” (FKZ: 031L104B)); E.K. and J.A.H.W. were supported by the German Federal Ministry of Education and Research (project “SysToxChip”, FKZ 031A303A); M.K. is supported by the Federal Ministry of Education and Research (BMBF, Germany) within the research network Systems Medicine of the Liver (LiSyM, grant number 031L0054); J.A.P. and G.L.M. acknowledge funding from US National Institutes of Health (T32-LM012416, R01-AT010253, R01-GM108501) and the Wagner Foundation; G.L.M. acknowledges funding from a Grand Challenges Exploration Phase I grant (OPP1211869) from the Bill & Melinda Gates Foundation; H.H. and R.S.M.S. received funding from the Biotechnology and Biological Sciences Research Council MultiMod (BB/N019482/1); H.U.K. and S.Y.L. received funding from the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries (grants NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557) from the Ministry of Science and ICT through the National Research Foundation (NRF) of Korea; H.U.K. received funding from the Bio & Medical Technology Development Program of the NRF, the Ministry of Science and ICT (NRF-2018M3A9H3020459); P.B., B.J.S., Z.K., B.O.P., C.L., M.B., N.S., M.H. and A.F. received funding through Novo Nordisk Foundation through the Center for Biosustainability at the Technical University of Denmark (NNF10CC1016517); D.-Y.L. received funding from the Next-Generation BioGreen 21 Program (SSAC, PJ01334605), Rural Development Administration, Republic of Korea; G.F. was supported by the RobustYeast within ERA net project via SystemsX.ch; V.H. received funding from the ETH Domain and Swiss National Science Foundation; M.P. acknowledges Oxford Brookes University; J.C.X. received support via European Research Council (666053) to W.F. Martin; B.E.E. acknowledges funding through the CSIRO-UQ Synthetic Biology Alliance; C.D. is supported by a Washington Research Foundation Distinguished Investigator Award. I.N. received funding from National Institutes of Health (NIH)/National Institute of General Medical Sciences (NIGMS) (grant P20GM125503).

Author information

Author notes

  1. Beatriz García-Jiménez

    Present address: Centro de Biotecnología y Genómica de Plantas (CBGP, UPM-INIA), Universidad Politécnica de Madrid (UPM) – Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Madrid, Spain

  2. These authors contributed equally: Christian Lieven, Moritz E. Beber.

Authors and Affiliations

  1. Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark

    Christian Lieven, Moritz E. Beber, Parizad Babaei, Jennifer A. Bartell, Adam M. Feist, Markus J. Herrgård, Ali Kaafarani, Sang Yup Lee, Jens Nielsen, Lars Keld Nielsen, Bernhard O. Palsson, Benjamín J. Sánchez & Nikolaus Sonnenschein

  2. Systems Biology Lab, Amsterdam Institute of Molecular and Life Sciences (AIMMS), Vrije Universiteit Amsterdam, Amsterdam, the Netherlands

    Brett G. Olivier & Bas Teusink

  3. BioQUANT/COS, Heidelberg University, Heidelberg, Germany

    Frank T. Bergmann

  4. Ecole Polytechnique Fédérale de Lausanne, Laboratory of Computational Systems Biotechnology, Lausanne, Switzerland

    Meric Ataman, Georgios Fengos & Vassily Hatzimanikatis

  5. iAMB-Institute of Applied Microbiology, ABBt-Aachen Biology and Biotechnology, RWTH Aachen University, Aachen, Germany

    Lars M. Blank & Birgitta E. Ebert

  6. Department of Bioengineering, University of California, La Jolla, CA, USA

    Siddharth Chauhan, Adam M. Feist, Zachary King, Nathan E. Lewis, Jonathan M. Monk & Bernhard O. Palsson

  7. Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario, Canada

    Kevin Correia & Radhakrishnan Mahadevan

  8. Human Systems Biology Laboratory, Instituto Nacional de Medicina Genomica & Coordinación de la Investigación Científica-Red de Apoyo a la Investigación, UNAM, Mexico City, Mexico

    Christian Diener & Osbaldo Resendis-Antonio

  9. Institute for Systems Biology, Seattle, WA, USA

    Christian Diener & Nathan D. Price

  10. Computational Systems Biology of Infection and Antimicrobial-Resistant Pathogens, Institute for Biomedical Informatics (IBMI), Tübingen, Germany

    Andreas Dräger

  11. Department of Computer Science, University of Tübingen, Tübingen, Germany

    Andreas Dräger

  12. German Center for Infection Research (DZIF), partner site Tübingen, Tübingen, Germany

    Andreas Dräger

  13. Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Queensland, Australia

    Birgitta E. Ebert & Lars Keld Nielsen

  14. Argonne National Laboratory, Lemont, IL, USA

    Janaka N. Edirisinghe, José P. Faria, Christopher S. Henry & Filipe Liu

  15. Analytical Biosciences, Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands

    Ronan M. T. Fleming

  16. Department of Systems Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain

    Beatriz García-Jiménez & Juan Nogales

  17. Department of Animal and Aquacultural Sciences, Faculty of Biosciences, Norwegian University of Life Sciences, Oslo, Norway

    Wout van Helvoirt, Jon Olav Vik & Maksim Zakhartsev

  18. Hanze University of Applied Sciences, Groningen, the Netherlands

    Wout van Helvoirt

  19. European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK

    Henning Hermjakob & Rahuman S. Malik Sheriff

  20. Department of Chemical and Biomolecular Engineering (BK21 Plus Program), BioProcess Engineering Research Center, BioInformatics Research Center, Institute for the BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea

    Hyun Uk Kim & Sang Yup Lee

  21. Analysis and Redesign of Biological Networks, Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg, Magdeburg, Germany

    Steffen Klamt

  22. Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany

    Edda Klipp, Matthias König & Judith A. H. Wodke

  23. Department of Agrotechnology and Food Sciences, Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, the Netherlands

    Jasper J. Koehorst & Peter J. Schaap

  24. Bioprocessing Technology Institute, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore

    Meiyappan Lakshmanan & Dong-Yup Lee

  25. School of Chemical Engineering Sungkyunkwan University, Jangan-gu Suwon, Gyeonggi-do, Republic of Korea

    Dong-Yup Lee

  26. Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden

    Sunjae Lee, Adil Mardinoglu, Saeed Shoaie & Cheng Zhang

  27. Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King’s College London, London, UK

    Sunjae Lee, Adil Mardinoglu & Saeed Shoaie

  28. Department of Pediatrics and Novo Nordisk Foundation Center for Biosustainability, University of California, San Diego School of Medicine, La Jolla, CA, USA

    Nathan E. Lewis & Anne Richelle

  29. Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, P.R. China

    Hongwu Ma & Qianqian Yuan

  30. Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany

    Daniel Machado & Kiran R. Patil

  31. Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Canada

    Radhakrishnan Mahadevan

  32. SilicoLife Lda., Braga, Portugal

    Paulo Maia & Paulo Vilaça

  33. Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA

    Gregory L. Medlock & Jason A. Papin

  34. Chalmers University of Technology, Department of Biology and Biological Engineering, Division of Systems and Synthetic Biology, Göteborg, Sweden

    Jens Nielsen, Intawat Nookaew & Benjamín J. Sánchez

  35. Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences (UAMS), Little Rock, AR, USA

    Intawat Nookaew

  36. Oxford Brookes University, Oxford, UK

    Mark Poolman

  37. Centre of Biological Engineering, University of Minho, Braga, Portugal

    Isabel Rocha

  38. Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa (ITQB-NOVA), Oeiras, Portugal

    Isabel Rocha

  39. Institute for Molecular Evolution, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany

    Joana C. Xavier

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Correspondence to Nikolaus Sonnenschein.

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Lieven, C., Beber, M.E., Olivier, B.G. et al. MEMOTE for standardized genome-scale metabolic model testing. Nat Biotechnol 38, 272–276 (2020). https://doi.org/10.1038/s41587-020-0446-y

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