Journal Article

Modeling tissue‐relevant Caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels

Schroeder, Frank, Nanda, Shivani, Li, Xuhang, Yilmaz, Lutfu Safak, Fox, Bennett, Walhout, Albertha JM

2020

Overview

Metabolism is a highly compartmentalized process that provides building blocks for biomass generation during development, homeostasis, and wound healing, and energy to support cellular and organismal processes. In metazoans, different cells and tissues specialize in different aspects of metabolism. However, studying the compartmentalization of metabolism in different cell types in a whole animal and for a particular stage of life is difficult. Here, we present MEtabolic models Reconciled with Gene Expression (MERGE), a computational pipeline that we used to predict tissue‐relevant metabolic function at the network, pathway, reaction, and metabolite levels based on single‐cell RNA‐sequencing (scRNA‐seq) data from the nematode Caenorhabditis elegans . Our analysis recapitulated known tissue functions in C. elegans , captured metabolic properties that are shared with similar tissues in human, and provided predictions for novel metabolic functions. MERGE is versatile and applicable to other systems. We envision this work as a starting point for the development of metabolic network models for individual cells as scRNA‐seq continues to provide higher‐resolution gene expression data. Synopsis Monitoring tissue‐ and cell‐type specific metabolic activities by metabolomics remains challenging. MERGE is a computational pipeline that can convert tissue‐level RNA‐seq data from Caenorhabditis elegans into predicted tissue flux potentials that indicate metabolic function. Network‐level flux distributions are successfully fitted to categorized gene expression data for seven tissues in L2 stage animals. Tissue metabolic networks are defined using these integrated flux distributions as the basis. Flux potentials of individual reactions are quantitatively predicted for each tissue. Predicted tissue‐level flux potentials recapitulate known tissue metabolic functions in C. elegans and match key functions to mammalian tissues. Graphical Abstract Monitoring tissue‐ and cell‐type specific metabolic activities by metabolomics remains challenging. MERGE is a computational pipeline that can convert tissue‐level RNA‐seq data from Caenorhabditis elegans into predicted tissue flux potentials that indicate metabolic function.

• Publisher: Nature Publishing Group UK,EMBO Press,John Wiley and Sons Inc,Springer Nature
• Subject: Algorithms / Animals / Biosynthesis / Caenorhabditis elegans / Caenorhabditis elegans - genetics / Caenorhabditis elegans - metabolism / Caenorhabditis elegans Proteins - genetics / Caenorhabditis elegans Proteins - metabolism / Cell culture / Computational Biology / Computer applications / Computer Simulation / data integration / Datasets / EMBO10 / EMBO21 / EMBO22 / Fatty acids / Gene expression / Gene Expression Regulation - genetics / Gene Regulatory Networks / Gene sequencing / Genomes / Gonads - metabolism / Homeostasis / Intestinal Mucosa - metabolism / metabolic network / Metabolic networks / Metabolic Networks and Pathways / Metabolism / Metabolites / Nematodes / Neuroglia - metabolism / Organ Specificity - genetics / Organ Specificity - physiology / Ribonucleic acid / RNA / RNA-Seq / Single-Cell Analysis / single‐cell RNA‐seq / Subcutaneous Tissue - metabolism / tissue metabolism / Tissues / Transcriptome - genetics / Wound healing