Abstract：
The human gut microbiota relies on complex carbohydrates (glycans) for energy and growth, primarily dietary fiber and host-derived mucins. We introduce a mathematical model of a glycan generalist and a mucin specialist in a two-compartment chemostat model of the human colon. Our objective is to characterize the influence of dietary fiber and mucin supply on the abundance of mucin-degrading species within the gut ecosystem. Current mathematical gut reactor models that include the enzymatic degradation of glycans do not differentiate between glycan types and their degraders. The model we present distinguishes between a generalist that can degrade both dietary fiber and mucin, and a specialist species that can only degrade mucin. The integrity of the colonic mucus barrier is essential for overall human health and well-being, with the mucin specialist Akkermanisa muciniphila being associated with a healthy mucus layer. Competition, particularly between the specialist and generalists like Bacteroides thetaiotaomicron, may lead to mucus layer erosion, especially during periods of dietary fiber deprivation. Our model treats the colon as a gut reactor system, dividing it into two compartments that represent the lumen and the mucus of the gut, resulting in a complex system of ordinary differential equations with a large and uncertain parameter space. To understand the influence of model parameters on long-term behavior, we employ a random forest classifier, a supervised machine learning method. Additionally, a variance-based sensitivity analysis is utilized to determine the sensitivity of steady-state values to changes in model parameter inputs. By constructing this model, we can investigate the underlying mechanisms that control gut microbiota composition and function, free from confounding factors.
摘要：
人类肠道微生物群依赖于复杂的碳水化合物（聚糖）来提供能量和生长，主要是膳食纤维和宿主来源的粘蛋白。我们在人结肠的两室恒化器模型中介绍了聚糖通才和粘蛋白专家的数学模型。我们的目标是表征膳食纤维和粘蛋白供应对肠道生态系统中粘蛋白降解物种丰度的影响。包括聚糖的酶促降解的当前数学肠反应器模型不区分聚糖类型及其降解物。我们提出的模型区分了可以降解膳食纤维和粘蛋白的通才，和一种只能降解粘蛋白的特殊物种。结肠粘液屏障的完整性对人类整体健康和福祉至关重要，粘蛋白专家Akkermanisa粘蛋白与健康的粘液层有关。Competition,特别是在专家和通才之间，可能导致粘液层侵蚀，尤其是在膳食纤维匮乏时期。我们的模型将结肠视为肠道反应器系统，将它分成两个代表肠道内腔和粘液的隔室，导致具有大且不确定的参数空间的常微分方程的复杂系统。要了解模型参数对长期行为的影响，我们使用一个随机森林分类器，有监督的机器学习方法。此外,基于方差的灵敏度分析用于确定稳态值对模型参数输入变化的灵敏度。通过构建这个模型，我们可以研究控制肠道菌群组成和功能的潜在机制，没有混杂因素。
