Mechanistic modeling of the dynamics of phage attack during milk acidification in the cheese-making process

Bacteriophage attacks represent a major threat in the dairy industry. Here, an unstructured mechanistic model predicting the dynamics of milk acidification in case of phage attack was developed and experimentally validated. Multiple acidification experiments were run with different combinations of initial phage titers and bacterial concentrations and the resulting pH dynamics were recorded. The model could successfully predict the success or failure of milk acidification. Using the model, important biological parameters were deduced from simple, low-cost acidification measurements. These parameters included bacteria’s maximum growth and lysis rates, phages’ burst size, etc. Sensitivity analysis helped identify biologically relevant aspects of phage-host interactions. Growth and lysis kinetics were shown to have the most important impacts. This knowledge can be used to develop easy routine strategies to fight phage attack in the dairy industry. The model can be used to raise awareness amongst cheese makers on the importance of cleaning to avoid food and material waste. • Prediction of success/failure of milk acidification in the presence of phage. • Development and experimental validation of a dynamic mechanistic model. • Identification of key interactions to enhance phage attack interventions.

Authors

Institutions

Publication Details

Journal
Journal of Food Engineering
Published
2024-10-10
DOI
https://doi.org/10.1016/j.jfoodeng.2024.112329
Primary Topic
Bacteriophages and microbial interactions
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mechanistic modeling of the dynamics of phage attack during milk acidification in the cheese-making process

Ahmad A. Zeidan, Ioan-Cristian Trelea, Michèle Bou Habib, Jannik Vindeloev et al.
Journal of Food Engineering
Bacteriophages and microbial interactions
article

Mechanistic modeling of the dynamics of phage attack during milk acidification in the cheese-making process

Ahmad A. Zeidan, Ioan-Cristian Trelea, Michèle Bou Habib, Jannik Vindeloev, Benjamín J. Sánchez, Emmanuel Bernuau, Dominique Swennen
article en

Abstract

Bacteriophage attacks represent a major threat in the dairy industry. Here, an unstructured mechanistic model predicting the dynamics of milk acidification in case of phage attack was developed and experimentally validated. Multiple acidification experiments were run with different combinations of initial phage titers and bacterial concentrations and the resulting pH dynamics were recorded. The model could successfully predict the success or failure of milk acidification. Using the model, important biological parameters were deduced from simple, low-cost acidification measurements. These parameters included bacteria’s maximum growth and lysis rates, phages’ burst size, etc. Sensitivity analysis helped identify biologically relevant aspects of phage-host interactions. Growth and lysis kinetics were shown to have the most important impacts. This knowledge can be used to develop easy routine strategies to fight phage attack in the dairy industry. The model can be used to raise awareness amongst cheese makers on the importance of cleaning to avoid food and material waste. • Prediction of success/failure of milk acidification in the presence of phage. • Development and experimental validation of a dynamic mechanistic model. • Identification of key interactions to enhance phage attack interventions.

Journal of Food EngineeringVol. 387
ParisTech (FR), AgroParisTech (FR), Université Paris-Saclay (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Novo Holdings (Denmark) (DK), Paris-Saclay Food and Bioproduct Engineering Research Unit (FR)
European Commission, Horizon 2020 Framework Programme, H2020 Marie Skłodowska-Curie Actions, HORIZON EUROPE Marie Sklodowska-Curie Actions
Zero hunger
Openalex Percentile: Top 83%
Bacteriophages and microbial interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.