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The pH-dependent lactose metabolism of Lactobacillus delbrueckii subsp. bulgaricus: An integrative view through a mechanistic computational model.

Authors :
Bendig, Tamara
Ulmer, Andreas
Luzia, Laura
Müller, Susanne
Sahle, Sven
Bergmann, Frank T.
Lösch, Maren
Erdemann, Florian
Zeidan, Ahmad A.
Mendoza, Sebastian N.
Teusink, Bas
Takors, Ralf
Kummer, Ursula
Figueiredo, Ana Sofia
Source :
Journal of Biotechnology. Sep2023, Vol. 374, p90-100. 11p.
Publication Year :
2023

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. • Kinetic model that takes cell culture growth into account. • Integration of new experimental data sets. • Potential to predict acidification during batch culture growth. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01681656
Volume :
374
Database :
Academic Search Index
Journal :
Journal of Biotechnology
Publication Type :
Academic Journal
Accession number :
170903216
Full Text :
https://doi.org/10.1016/j.jbiotec.2023.08.001