Department of Biology and Biological Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden.
Department of Biology and Biological Engineering, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden.
Proc Natl Acad Sci U S A. 2021 Jul 27;118(30). doi: 10.1073/pnas.2102344118.
Genome-scale metabolic models (GEMs) are used extensively for analysis of mechanisms underlying human diseases and metabolic malfunctions. However, the lack of comprehensive and high-quality GEMs for model organisms restricts translational utilization of omics data accumulating from the use of various disease models. Here we present a unified platform of GEMs that covers five major model animals, including Mouse1 (), Rat1 (), Zebrafish1 (), Fruitfly1 (), and Worm1 (). These GEMs represent the most comprehensive coverage of the metabolic network by considering both orthology-based pathways and species-specific reactions. All GEMs can be interactively queried via the accompanying web portal Metabolic Atlas. Specifically, through integrative analysis of Mouse1 with RNA-sequencing data from brain tissues of transgenic mice we identified a coordinated up-regulation of lysosomal GM2 ganglioside and peptide degradation pathways which appears to be a signature metabolic alteration in Alzheimer's disease (AD) mouse models with a phenotype of amyloid precursor protein overexpression. This metabolic shift was further validated with proteomics data from transgenic mice and cerebrospinal fluid samples from human patients. The elevated lysosomal enzymes thus hold potential to be used as a biomarker for early diagnosis of AD. Taken together, we foresee that this evolving open-source platform will serve as an important resource to facilitate the development of systems medicines and translational biomedical applications.
基因组规模代谢模型(GEMs)广泛用于分析人类疾病和代谢功能障碍的潜在机制。然而,缺乏全面且高质量的模型生物 GEMs 限制了从使用各种疾病模型积累的组学数据的转化应用。在这里,我们提出了一个统一的 GEM 平台,涵盖了五种主要的模式动物,包括 Mouse1 (), Rat1 (), Zebrafish1 (), Fruitfly1 (), 和 Worm1 (). 这些 GEMs 通过考虑基于同源性的途径和物种特异性反应,代表了代谢网络的最全面覆盖。所有 GEMs 都可以通过附带的代谢图谱网络门户进行交互式查询。具体来说,通过将 Mouse1 与转基因组小鼠脑组织的 RNA-seq 数据进行整合分析,我们鉴定出溶酶体 GM2 神经节苷脂和肽降解途径的协调上调,这似乎是具有淀粉样前体蛋白过表达表型的阿尔茨海默病(AD)小鼠模型的特征代谢改变。这一代谢变化进一步通过转基因组小鼠的蛋白质组学数据和人类患者的脑脊液样本得到了验证。因此,升高的溶酶体酶具有作为 AD 早期诊断的生物标志物的潜力。总之,我们预计这个不断发展的开源平台将成为促进系统药物和转化生物医学应用发展的重要资源。