Recon3D enables a three-dimensional view of gene variation in human metabolism

Elizabeth Brunk; Swagatika Sahoo; Daniel C. Zielinski; Ali Altunkaya; Andreas Dräger; Nathan Mih; Francesco Gatto; Avlant Nilsson; German Andres Preciat Gonzalez; Maike Kathrin Aurich; Andreas Prlic; Anand Sastry; Anna D. Danielsdottir; Almut Heinken; Alberto Noronha; Peter W. Rose; Stephen K. Burley; Ronan M.T. Fleming; Jens Nielsen; Ines Thiele; Bernhard O. Palsson

doi:https://doi.org/10.1038/nbt.4072

Recon3D enables a three-dimensional view of gene variation in human metabolism

Elizabeth Brunk, Swagatika Sahoo, Daniel C. Zielinski, Ali Altunkaya, Andreas Dräger, Nathan Mih, Francesco Gatto, Avlant Nilsson, German Andres Preciat Gonzalez, Maike Kathrin Aurich, Andreas Prlic, Anand Sastry, Anna D. Danielsdottir, Almut Heinken, Alberto Noronha, Peter W. Rose, Stephen K. Burley, Ronan M.T. Fleming, Jens Nielsen, Ines ThieleBernhard O. Palsson

Rutgers, The State University

Research output: Contribution to journal › Article › peer-review

177 Scopus citations

Abstract

Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. These data provide a unique resource for investigating molecular mechanisms of human metabolism. Recon3D is available at http://vmh.life.

Original language	English (US)
Pages (from-to)	272-281
Number of pages	10
Journal	Nature biotechnology
Volume	36
Issue number	3
DOIs	https://doi.org/10.1038/nbt.4072
State	Published - Mar 1 2018

ASJC Scopus subject areas

Biotechnology
Bioengineering
Applied Microbiology and Biotechnology
Molecular Medicine
Biomedical Engineering

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Brunk, E., Sahoo, S., Zielinski, D. C., Altunkaya, A., Dräger, A., Mih, N., Gatto, F., Nilsson, A., Preciat Gonzalez, G. A., Aurich, M. K., Prlic, A., Sastry, A., Danielsdottir, A. D., Heinken, A., Noronha, A., Rose, P. W., Burley, S. K., Fleming, R. M. T., Nielsen, J., ... Palsson, B. O. (2018). Recon3D enables a three-dimensional view of gene variation in human metabolism. Nature biotechnology, 36(3), 272-281. https://doi.org/10.1038/nbt.4072

Brunk, Elizabeth ; Sahoo, Swagatika ; Zielinski, Daniel C. ; Altunkaya, Ali ; Dräger, Andreas ; Mih, Nathan ; Gatto, Francesco ; Nilsson, Avlant ; Preciat Gonzalez, German Andres ; Aurich, Maike Kathrin ; Prlic, Andreas ; Sastry, Anand ; Danielsdottir, Anna D. ; Heinken, Almut ; Noronha, Alberto ; Rose, Peter W. ; Burley, Stephen K. ; Fleming, Ronan M.T. ; Nielsen, Jens ; Thiele, Ines ; Palsson, Bernhard O. / Recon3D enables a three-dimensional view of gene variation in human metabolism. In: Nature biotechnology. 2018 ; Vol. 36, No. 3. pp. 272-281.

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abstract = "Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. These data provide a unique resource for investigating molecular mechanisms of human metabolism. Recon3D is available at http://vmh.life.",

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Brunk, E, Sahoo, S, Zielinski, DC, Altunkaya, A, Dräger, A, Mih, N, Gatto, F, Nilsson, A, Preciat Gonzalez, GA, Aurich, MK, Prlic, A, Sastry, A, Danielsdottir, AD, Heinken, A, Noronha, A, Rose, PW, Burley, SK, Fleming, RMT, Nielsen, J, Thiele, I & Palsson, BO 2018, 'Recon3D enables a three-dimensional view of gene variation in human metabolism', Nature biotechnology, vol. 36, no. 3, pp. 272-281. https://doi.org/10.1038/nbt.4072

Recon3D enables a three-dimensional view of gene variation in human metabolism. / Brunk, Elizabeth; Sahoo, Swagatika; Zielinski, Daniel C.; Altunkaya, Ali; Dräger, Andreas; Mih, Nathan; Gatto, Francesco; Nilsson, Avlant; Preciat Gonzalez, German Andres; Aurich, Maike Kathrin; Prlic, Andreas; Sastry, Anand; Danielsdottir, Anna D.; Heinken, Almut; Noronha, Alberto; Rose, Peter W.; Burley, Stephen K.; Fleming, Ronan M.T.; Nielsen, Jens; Thiele, Ines; Palsson, Bernhard O.

In: Nature biotechnology, Vol. 36, No. 3, 01.03.2018, p. 272-281.

Research output: Contribution to journal › Article › peer-review

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AU - Mih, Nathan

AU - Gatto, Francesco

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AU - Preciat Gonzalez, German Andres

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AU - Prlic, Andreas

AU - Sastry, Anand

AU - Danielsdottir, Anna D.

AU - Heinken, Almut

AU - Noronha, Alberto

AU - Rose, Peter W.

AU - Burley, Stephen K.

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AU - Thiele, Ines

AU - Palsson, Bernhard O.

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Recon3D enables a three-dimensional view of gene variation in human metabolism

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