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.

中文翻译：

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在网络、途径、反应和代谢物水平上对组织相关的秀丽隐杆线虫代谢进行建模


新陈代谢是一个高度分隔的过程，为发育、体内平衡和伤口愈合过程中的生物质产生提供构建模块，并为支持细胞和有机体过程提供能量。在后生动物中，不同的细胞和组织专门从事不同方面的代谢。然而，研究整个动物不同细胞类型和生命特定阶段的代谢区​​划是很困难的。在这里，我们提出了与基因表达相协调的代谢模型（MERGE），这是一个计算管道，我们使用它基于单细胞 RNA 测序（scRNA-seq）来预测网络、途径、反应和代谢物水平上的组织相关代谢功能。 ）来自线虫秀丽隐杆线虫的数据。我们的分析概括了线虫已知的组织功能，捕获了与人类类似组织共有的代谢特性，并为新的代谢功能提供了预测。 MERGE 用途广泛，适用于其他系统。我们设想这项工作作为开发单个细胞代谢网络模型的起点，因为 scRNA-seq 继续提供更高分辨率的基因表达数据。