Chemical and Biomolecular Engineering, University of Delaware, Newark, DE, United States of America.
PLoS One. 2018 Nov 9;13(11):e0207072. doi: 10.1371/journal.pone.0207072. eCollection 2018.
Knowledge of the spatial and temporal dynamics of the gut microbiome is essential to understanding the state of human health, as over a hundred diseases have been correlated with changes in microbial populations. Unfortunately, due to the complexity of the microbiome and the limitations of in vivo and in vitro experiments, studying spatial and temporal dynamics of gut bacteria in a biological setting is extremely challenging. Thus, in silico experiments present an excellent alternative for studying such systems. In consideration of these issues, we have developed a user-friendly agent-based model, GutLogo, that captures the spatial and temporal development of four representative bacterial genera populations in the ileum. We demonstrate the utility of this model by simulating population responses to perturbations in flow rate, nutrition, and probiotics. While our model predicts distinct changes in population levels due to these perturbations, most of the simulations suggest that the gut populations will return to their original steady states once the disturbance is removed. We hope that, in the future, the GutLogo model is utilized and customized by interested parties, as GutLogo can serve as a basic modeling framework for simulating a variety of physiological scenarios and can be extended to capture additional complexities of interest.
了解肠道微生物组的时空动态对于理解人类健康状况至关重要，因为已有超过 100 种疾病与微生物种群的变化相关。不幸的是，由于微生物组的复杂性以及体内和体外实验的局限性，在生物环境中研究肠道细菌的时空动态极具挑战性。因此，计算实验为研究此类系统提供了极好的替代方法。考虑到这些问题，我们开发了一个用户友好的基于代理的模型 GutLogo，该模型可以捕获回肠中四种代表性细菌属群体的时空发展。我们通过模拟对流速、营养和益生菌的扰动对种群反应来演示该模型的实用性。虽然我们的模型预测由于这些扰动会导致种群水平发生明显变化，但大多数模拟表明，一旦干扰消除，肠道种群将恢复到其原始稳定状态。我们希望将来有兴趣的各方能够利用和定制 GutLogo 模型，因为 GutLogo 可以作为模拟各种生理场景的基本建模框架，并可以扩展以捕获其他感兴趣的复杂性。
