Mechanistically Inspired Kinetic Approach to Describe Interactions During Co‐Culture Growth of Carnobacterium maltaromaticum and Listeria monocytogenes

DALLAGNOL, ANDREA M.; SCHVEZOV, CARLOS E.; VIGNOLO, GRACIELA M.; PEDROZO, HECTOR A.; PUCCIARELLI, AMADA B.

JOURNAL OF FOOD SCIENCE

WILEY-BLACKWELL PUBLISHING, INC

Lugar: Londres; Año: 2019 vol. 84 p. 2592 - 2602

0022-1147

Lactic acid bacteria and Listeria monocytogenes are psychotropic organisms that can grow and compete in foodsuch as lightly preserved fishery products. Predictive microbiology is nowadays one of the leading tools to assess the behaviorof bacteria in food and to predict food spoilage. Mathematical models can be used to predict the growth, inactivation orgrowth probability of bacteria. Currently, the efforts in microbial modeling are oriented towards extrapolation of resultsbeyond experiments in order to predict the growth of interacting microorganisms and develop new food preservationprocesses. In the present work, a model combining both heterogeneous population and quasi-chemical approaches todescribe the different phases of the bacterial growth curve is presented. The model was applied to both monoculture andco-culture cases of lactic acid bacteria, Carnobacterium maltaromaticum H-17, and two Listeria monocytogenes strains in a rawfish extract. It is a highlight that our model includes novel inhibition reactions due to the accumulation of metabolites,and a general equation to take into account the effect of chemical compounds during the lag or physiological adaptationphase of the cells. Our results show that the proposed model can accurately describe the experimental data when thecurve shape is a sigmoid, and when it presents a maximum. Besides, the parameters have biological interpretability sincethe model is mechanistically inspired.