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\begin{document}

\title{Dynamic community-level metabolic modeling for fermentation kinetics and
metabolic interactions of the yogurt starter culture based on
metagenomic analysis}



\author[1]{Sizhe Qiu}%
\author[1]{Hong Zeng}%
\author[1]{Zhijie Yang}%
\author[2]{Wei-Lian Hung}%
\author[1]{Bei Wang}%
\author[3]{Aidong Yang}%
\affil[1]{Beijing Technology and Business University School of Food and Health}%
\affil[2]{National Center of Technology Innovation for Dairy}%
\affil[3]{University of Oxford Department of Engineering Science}%


\vspace{-1em}



  
  \date{May 26, 2024}


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\begin{abstract}
Genome-scale metabolic models (GSMMs) and flux balance analysis (FBA)
have been extensively used to model and design bacterial fermentation.
However, FBA-based metabolic models designed for simulating the dynamics
of co-culture with quantitative accuracy are still uncommon, which is
particularly true for lactic acid bacteria (LAB) used for yogurt
fermentation. To investigate metabolic interactions in yogurt starter
culture of \emph{Streptococcus thermophilus} (ST) and
\emph{Lactobacillus delbrueckii subsp. bulgaricus} (LB), this study
built a dynamic community-level GSMM based on metagenomic analysis. We
first assessed the accuracy of the model by comparing predicted
bacterial growth, consumption of lactose and production of lactic acid
with reference experimental data, and then used it to predict the impact
of different initial ST:LB inoculation ratios (gDW/gDW) on
acidification. The dynamic simulation demonstrated the mutual dependence
of ST and LB during the yogurt fermentation process. The modeling
pipeline presented in this work provided a basis for the computer-aided
process design and control of the production of fermented dairy
products, contributing to the development of precision fermentation in
the food industry.%
\end{abstract}%



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