Principles of metabolome conservation in animals

Author:

Liska Orsolya123ORCID,Boross Gábor24,Rocabert Charles2567ORCID,Szappanos Balázs128ORCID,Tengölics Roland129ORCID,Papp Balázs1210ORCID

Affiliation:

1. Hungarian Centre of Excellence for Molecular Medicine - Biological Research Centre Metabolic Systems Biology Lab, 6728 Szeged, Hungary

2. National Laboratory of Biotechnology, Synthetic and System Biology Unit, Institute of Biochemistry, Biological Research Centre, Eötvös Loránd Research Network, 6726 Szeged, Hungary

3. Doctoral School of Biology, University of Szeged, 6726 Szeged, Hungary

4. Department of Biology, Stanford University, Stanford, City of Palo Alto, CA 94305-5020

5. Inria, 78150 Rocquencourt, 69100 Villeurbanne, France

6. Organismal and Evolutionary Biology Research Programme, University of Helsinki, 00014 Helsinki, Finland

7. Institute for Computational Cell Biology, Heinrich-Heine Universität, 40225 Düsseldorf, Germany

8. Department of Biotechnology, University of Szeged, 6726 Szeged, Hungary

9. Metabolomics Lab, Core facilities, Biological Research Centre, Eötvös Loránd Research Network, 6726 Szeged, Hungary

10. National Laboratory for Health Security, Biological Research Centre, Eötvös Loránd Research Network, 6726 Szeged, Hungary

Abstract

Metabolite levels shape cellular physiology and disease susceptibility, yet the general principles governing metabolome evolution are largely unknown. Here, we introduce a measure of conservation of individual metabolite levels among related species. By analyzing multispecies tissue metabolome datasets in phylogenetically diverse mammals and fruit flies, we show that conservation varies extensively across metabolites. Three major functional properties, metabolite abundance, essentiality, and association with human diseases predict conservation, highlighting a striking parallel between the evolutionary forces driving metabolome and protein sequence conservation. Metabolic network simulations recapitulated these general patterns and revealed that abundant metabolites are highly conserved due to their strong coupling to key metabolic fluxes in the network. Finally, we show that biomarkers of metabolic diseases can be distinguished from other metabolites simply based on evolutionary conservation, without requiring any prior clinical knowledge. Overall, this study uncovers simple rules that govern metabolic evolution in animals and implies that most tissue metabolome differences between species are permitted, rather than favored by natural selection. More broadly, our work paves the way toward using evolutionary information to identify biomarkers, as well as to detect pathogenic metabolome alterations in individual patients.

Funder

NKFI | National Research, Development and Innovation Office

Magyar Tudományos Akadémia

EC | Horizon 2020 Framework Programme

Emberi Eroforrások Minisztériuma

Tobacco-Related Disease Research Program

Magyarország Kormánya

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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