Ibrahim Maziya, Raman Karthik
Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, IIT Madras, India.
Centre for Integrative Biology and Systems mEdicine (IBSE), IIT Madras, India.
Comput Struct Biotechnol J. 2021 Nov 9;19:6039-6049. doi: 10.1016/j.csbj.2021.11.009. eCollection 2021.
Microbial communities that metabolise pentose and hexose sugars are useful in producing high-value chemicals, resulting in the effective conversion of raw materials to the product, a reduction in the production cost, and increased yield. Here, we present a computational analysis approach called CAMP (Co-culture/Community Analyses for Metabolite Production) that simulates and identifies appropriate communities to produce a metabolite of interest. To demonstrate this approach, we focus on the optimal production of lactate from various Lactic Acid Bacteria. We used genome-scale metabolic models (GSMMs) belonging to , and species from the Virtual Metabolic Human (VMH; https://vmh.life/) resource and well-curated GSMMs of WCSF1 and JCM 1112. We analysed 1176 two-species communities using a constraint-based modelling method for steady-state flux-balance analysis of communities. Flux variability analysis was used to detect the maximum lactate flux in the communities. Using glucose or xylose as substrates separately or in combination resulted in either parasitism, amensalism, or mutualism being the dominant interaction behaviour in the communities. Interaction behaviour between members of the community was deduced based on variations in the predicted growth rates of monocultures and co-cultures. Acetaldehyde, ethanol, acetate, among other metabolites, were found to be cross-fed between community members. WCSF1 was found to be a member of communities with high lactate yields. community optimisation strategies to predict reaction knock-outs for improving lactate flux were implemented. Reaction knock-outs of acetate kinase, phosphate acetyltransferase, and fumarate reductase in the communities were found to enhance lactate production.
能够代谢戊糖和己糖的微生物群落对于生产高价值化学品很有用，可实现原材料到产品的有效转化，降低生产成本并提高产量。在此，我们提出一种名为CAMP（用于代谢物生产的共培养/群落分析）的计算分析方法，该方法可模拟并识别出合适的群落以生产目标代谢物。为证明此方法，我们聚焦于从各种乳酸菌中最优生产乳酸。我们使用了来自虚拟代谢人类（VMH；https://vmh.life/）资源的属于、和物种的基因组规模代谢模型（GSMMs）以及精心构建的WCSF1和JCM 1112的GSMMs。我们使用基于约束的建模方法对群落进行稳态通量平衡分析，分析了1176个双物种群落。通量变异性分析用于检测群落中最大的乳酸通量。单独或组合使用葡萄糖或木糖作为底物会导致寄生、偏害共生或互利共生成为群落中的主要相互作用行为。基于单培养和共培养预测生长速率的变化推断群落成员之间的相互作用行为。发现乙醛、乙醇、乙酸等代谢物在群落成员之间交叉供应。发现WCSF1是乳酸产量高的群落的成员之一。实施了群落优化策略以预测反应敲除以提高乳酸通量。发现群落中乙酸激酶、磷酸乙酰转移酶和富马酸还原酶的反应敲除可提高乳酸产量。
