Predicting metabolic preferences through transcriptomics: a data-driven approach to align metabolic signatures with gene expression profiles

Biochemistry and Biophysics Reports, vol. 44, pp. 102302

Abstract

Complex organisms such as mammals have a sophisticated metabolic network to meet energy demand under varying conditions. This network, which includes the exchange of metabolites between organs, is absent in ex vivo model systems like cell culture or isolated organ perfusion. These systems therefore require external management of metabolic substrates; since failure to meet the specific metabolic requirements will lead to cellular stress, non-physiological behaviour and in turn limited translatability, it should be ensured that model systems exhibit ex vivo metabolism that recapitulates in vivo processes. To better support but also assess tissue and cell metabolism under ex vivo conditions, it is thus crucial to be knowledgeable of their specific in vivo metabolic preferences. As in vivo organ- and cell-specific metabolic preferences are only partially characterised, a surrogate marker of metabolism is required that can easily be measured in both in vivo and ex vivo isolated organ or cell culture systems. In an attempt to identify surrogate predictive markers of metabolism that could be easily measured in ex vivo model systems, we investigated the extent to which organ-specific metabolite consumption and production patterns (referred to as “metabolic signatures”) from available arteriovenous flux data align with organ-specific metabolic gene expression patterns. Whilst different tissues displayed distinctive patterns in the consumption and production of metabolites, these did not directly correspond to expression of known metabolic genes. These findings are indicative of the complexity of mammalian metabolism. • Different organs display distinctive metabolite consumption and production patterns. • Knowledge of metabolic preferences is key to support and assess ex vivo models. • Organs' metabolic gene expression do not align with their arteriovenous flux data. • Metabolic gene expression patterns cannot be used to predict metabolic preference. • Control of metabolic flux depends on a complex interplay of many different factors.

Authors 7

1. Lente J. S. Lerink Aachen Department of Surgery & Transplant Centre

   Leiden University · Leiden University Medical Center · John Radcliffe Hospital · University of Oxford

   Affiliation as printed

   Department of Surgery & Transplant Centre, Leiden University Medical Centre, Albinusdreef 2, 2333 ZA, Leiden, the Netherlands

   Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom

2. Marleen J de Winter Aachen Department of Surgery & Transplant Centre

   Leiden University · Leiden University Medical Center

   Affiliation as printed

   Department of Surgery & Transplant Centre, Leiden University Medical Centre, Albinusdreef 2, 2333 ZA, Leiden, the Netherlands

3. Jaap Adriaan Bakker

   Amsterdam UMC Location University of Amsterdam · Amsterdam University Medical Centers

   Affiliation as printed

   Laboratory Genetic Metabolic Diseases, Amsterdam University Medical Centre, Location AMC, Meibergdreef 9, 1105 AZ, Amsterdam, the Netherlands

4. Ian P.J. Alwayn Aachen Department of Surgery & Transplant Centre

   Leiden University · Leiden University Medical Center

   Affiliation as printed

   Department of Surgery & Transplant Centre, Leiden University Medical Centre, Albinusdreef 2, 2333 ZA, Leiden, the Netherlands

5. Rutger J. Ploeg Aachen Department of Surgery & Transplant Centre

   Leiden University · Leiden University Medical Center · John Radcliffe Hospital · University of Oxford · NIHR Oxford Biomedical Research Centre · Oxford University Hospitals NHS Trust

   Affiliation as printed

   Department of Surgery & Transplant Centre, Leiden University Medical Centre, Albinusdreef 2, 2333 ZA, Leiden, the Netherlands

   NIHR Oxford Biomedical Research Centre, Oxford University Hospitals Trust, John Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom

   Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom

6. John F. Mulvey

   John Radcliffe Hospital · University of Oxford

   Affiliation as printed

   Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom

7. Jan H.N. Lindeman corresponding Aachen Department of Surgery & Transplant Centre

   Leiden University · Leiden University Medical Center · John Radcliffe Hospital · University of Oxford

   Affiliation as printed

   Department of Surgery & Transplant Centre, Leiden University Medical Centre, Albinusdreef 2, 2333 ZA, Leiden, the Netherlands

   Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom