Jiang Boyu, Quinn-Bohmann Nick, Diener Christian, Nathan Vignesh Bose, Han-Hallett Yu, Reddivari Lavanya, Gibbons Sean M, Baloni Priyanka
School of Health Sciences, Purdue University, West Lafayette, Indiana, United States of America.
Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, Indiana, United States of America.
PLoS Comput Biol. 2025 Jul 3;21(7):e1013253. doi: 10.1371/journal.pcbi.1013253. eCollection 2025 Jul.
The colonic epithelium plays a key role in the host-microbiome interactions, allowing uptake of various nutrients and driving important metabolic processes. To unravel detailed metabolic activities in the human colonic epithelium, our present study focuses on the generation of the first cell-type-specific genome-scale metabolic model (GEM) of human colonic epithelial cells, named iColonEpithelium. GEMs are powerful tools for exploring reactions and metabolites at the systems level and predicting the flux distributions at steady state. Our cell-type-specific iColonEpithelium metabolic reconstruction captures genes specifically expressed in the human colonic epithelial cells. iColonEpithelium is also capable of performing metabolic tasks specific to the colonic epithelium. A unique transport reaction compartment has been included to allow for the simulation of metabolic interactions with the gut microbiome. We used iColonEpithelium to identify metabolic signatures associated with inflammatory bowel disease. We used single-cell RNA sequencing data from Crohn's Diseases (CD) and ulcerative colitis (UC) samples to build disease-specific iColonEpithelium metabolic networks in order to predict metabolic signatures of colonocytes in both healthy and disease states. We identified reactions in nucleotide interconversion, fatty acid synthesis and tryptophan metabolism were differentially regulated in CD and UC conditions, relative to healthy control, which were in accordance with experimental results. The iColonEpithelium metabolic network can be used to identify mechanisms at the cellular level, and we show an initial proof-of-concept for how our tool can be leveraged to explore the metabolic interactions between host and gut microbiota.
结肠上皮在宿主-微生物组相互作用中起着关键作用，它允许摄取各种营养物质并推动重要的代谢过程。为了阐明人类结肠上皮中详细的代谢活动，我们目前的研究聚焦于构建首个针对人类结肠上皮细胞的细胞类型特异性基因组规模代谢模型（GEM），命名为iColonEpithelium。GEM是在系统水平探索反应和代谢物以及预测稳态通量分布的强大工具。我们的细胞类型特异性iColonEpithelium代谢重建捕获了在人类结肠上皮细胞中特异性表达的基因。iColonEpithelium还能够执行结肠上皮特有的代谢任务。其中包含一个独特的转运反应区室，以模拟与肠道微生物组的代谢相互作用。我们使用iColonEpithelium来识别与炎症性肠病相关的代谢特征。我们利用来自克罗恩病（CD）和溃疡性结肠炎（UC）样本的单细胞RNA测序数据构建疾病特异性的iColonEpithelium代谢网络，以便预测健康和疾病状态下结肠细胞的代谢特征。我们发现，相对于健康对照，在CD和UC条件下，核苷酸相互转化、脂肪酸合成和色氨酸代谢中的反应受到差异调节，这与实验结果一致。iColonEpithelium代谢网络可用于在细胞水平识别机制，并且我们展示了一个初步的概念验证，说明我们的工具如何能够用于探索宿主与肠道微生物群之间的代谢相互作用。
