Abstract：
The fermentation process of milk to yoghurt using Lactobacillus delbrueckii subsp. bulgaricus in co-culture with Streptococcus thermophilus is hallmarked by the breakdown of lactose to organic acids such as lactate. This leads to a substantial decrease in pH - both in the medium, as well as cytosolic. The latter impairs metabolic activities due to the pH-dependence of enzymes, which compromises microbial growth. To quantitatively elucidate the impact of the acidification on metabolism of L. bulgaricus in an integrated way, we have developed a proton-dependent computational model of lactose metabolism and casein degradation based on experimental data. The model accounts for the influence of pH on enzyme activities as well as cellular growth and proliferation of the bacterial population. We used a machine learning approach to quantify the cell volume throughout fermentation. Simulation results show a decrease in metabolic flux with acidification of the cytosol. Additionally, the validated model predicts a similar metabolic behaviour within a wide range of non-limiting substrate concentrations. This computational model provides a deeper understanding of the intricate relationships between metabolic activity and acidification and paves the way for further optimization of yoghurt production under industrial settings.
摘要：
使用德氏乳杆菌亚种将牛奶发酵为酸奶的过程。保加利亚与嗜热链球菌共培养的特点是乳糖分解为有机酸，例如乳酸。这导致pH值的大幅下降-无论是在培养基中，以及细胞溶质。后者由于酶的pH依赖性而损害了代谢活动，这损害了微生物的生长。为了定量阐明酸化对保加利亚乳杆菌代谢的影响，基于实验数据，我们建立了一个依赖质子的乳糖代谢和酪蛋白降解的计算模型。该模型解释了pH对酶活性以及细菌种群的细胞生长和增殖的影响。我们使用机器学习方法来量化整个发酵过程中的细胞体积。模拟结果表明，随着胞质溶胶的酸化，代谢通量降低。此外,经验证的模型预测在广泛的非限制性底物浓度范围内具有相似的代谢行为.该计算模型可以更深入地了解代谢活动与酸化之间的复杂关系，并为在工业环境下进一步优化酸奶生产铺平了道路。
