Effect of pH and storage conditions on Listeria monocytogenes growth inoculated into sapote mamey (Pouteria sapota (Jacq) H.E. Moore &amp; Stearn) pulp

Saucedo-Reyes, Daniela; Carrillo-Salazar, José Alfredo; Reyes-Santamaría, María Isabel; Saucedo-Veloz, Crescenciano

doi:10.1016/j.foodcont.2012.05.003

Cited by 8 publications

(7 citation statements)

References 41 publications

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“…However, when pH increases to 4.0 and beyond, the bacteria not only survive for a longer period but also manage to replicate. Similar results were found on the survival of L. monocytogenes on Sapote mamey pulp at various pH levels [ 57 ]. To estimate δ in terms of pH, we fit an exponential model

to bacterial growth data [ 32 ] and found δ 0 =260 220 and δ 1 =−3.4.…”

Section: Mechanistic Dose–response Modelsupporting

confidence: 84%

Advancing risk assessment: mechanistic dose–response modelling ofListeria monocytogenesinfection in human populations

et al. 2018

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The utility of characterizing the effects of strain variation and individual/subgroup susceptibility on dose–response outcomes has motivated the search for new approaches beyond the popular use of the exponential dose–response model for listeriosis. While descriptive models can account for such variation, they have limited power to extrapolate beyond the details of particular outbreaks. By contrast, this study exhibits dose–response relationships from a mechanistic basis, quantifying key biological factors involved in pathogen–host dynamics. An efficient computational algorithm and geometric interpretation of the infection pathway are developed to connect dose–response relationships with the underlying bistable dynamics of the model. Relying on in vitro experiments as well as outbreak data, we estimate plausible parameters for the human context. Despite the presence of uncertainty in such parameters, sensitivity analysis reveals that the host response is most influenced by the pathogen–immune system interaction. In particular, we show how variation in this interaction across a subgroup of the population dictates the shape of dose–response curves. Finally, in terms of future experimentation, our model results provide guidelines and highlight vital aspects of the interplay between immune cells and particular strains of Listeria monocytogenes that should be examined.

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to bacterial growth data [ 32 ] and found δ 0 =260 220 and δ 1 =−3.4.…”

Section: Mechanistic Dose–response Modelsupporting

confidence: 84%

Advancing risk assessment: mechanistic dose–response modelling ofListeria monocytogenesinfection in human populations

et al. 2018

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“…Mamey pulp with no-added preservatives was prepared following the methodology described by Saucedo-Reyes et al (2012). Ripe sapote mamey (Pouteria sapota (Jacq.)…”

Section: Preparation Of Mamey Pulpmentioning

confidence: 99%

Modeling the pressure inactivation of Escherichia coli and Salmonella typhimurium in sapote mamey (Pouteria sapota (Jacq.) H.E. Moore & Stearn) pulp

Saucedo-Reyes

Carrillo-Salazar

Román-Padilla

et al. 2017

Food sci. technol. int.

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High hydrostatic pressure inactivation kinetics of Escherichia coli ATCC 25922 and Salmonella enterica subsp. enterica serovar Typhimurium ATCC 14028 ( S. typhimurium) in a low acid mamey pulp at four pressure levels (300, 350, 400, and 450 MPa), different exposure times (0-8 min), and temperature of 25 ± 2℃ were obtained. Survival curves showed deviations from linearity in the form of a tail (upward concavity). The primary models tested were the Weibull model, the modified Gompertz equation, and the biphasic model. The Weibull model gave the best goodness of fit ( R > 0.956, root mean square error < 0.290) in the modeling and the lowest Akaike information criterion value. Exponential-logistic and exponential decay models, and Bigelow-type and an empirical models for b'( P) and n( P) parameters, respectively, were tested as alternative secondary models. The process validation considered the two- and one-step nonlinear regressions for making predictions of the survival fraction; both regression types provided an adequate goodness of fit and the one-step nonlinear regression clearly reduced fitting errors. The best candidate model according to the Akaike theory information, with better accuracy and more reliable predictions was the Weibull model integrated by the exponential-logistic and exponential decay secondary models as a function of time and pressure (two-step procedure) or incorporated as one equation (one-step procedure). Both mathematical expressions were used to determine the t parameter, where the desired reductions ( 5D) (considering d = 5 ( t) as the criterion of 5 Log reduction (5 D)) in both microorganisms are attainable at 400 MPa for 5.487 ± 0.488 or 5.950 ± 0.329 min, respectively, for the one- or two-step nonlinear procedure.

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“…Saucedo et al. found that L. monocytogenes can grow in Sapote mamey pulp at higher pH levels, but not at a pH of 4.0 or less ( Saucedo-Reyes, Carrillo-Salazar, Reyes-Santamaría, & Saucedo-Veloz, 2012 ). Several studies observed that L. monocytogenes cannot grow at a pH less than 4.0 in different media (e.g.…”

Section: Host Defense and Survival Factors Of L Monocytogementioning

confidence: 99%

“…showed through an in vitro experiment that the decay rate of E. coli bacteria in different media varied between 6.15 and 9.15 at pH 3.0 ( Zhu et al., 2006 ). Since the growth/decay rate of E. coli and L. monocytogenes are similar at the same pH level ( Saucedo-Reyes et al., 2012 , Zhu et al., 2006 ), we consider the range of δ to be [6.15,9.15] (with mean 7.65 and sd 2.21). Lecuit et al.…”

Section: Application Of the Model To Guinea Pigsmentioning

confidence: 99%

Unraveling the dose-response puzzle of L. monocytogenes: A mechanistic approach

Rahman

Munther

Fazil

et al. 2016

Infectious Disease Modelling

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Food-borne disease outbreaks caused by Listeria monocytogenes continue to impose heavy burdens on public health in North America and globally. To explore the threat L. monocytogenes presents to the elderly, pregnant woman and immuno-compromised individuals, many studies have focused on in-host infection mechanisms and risk evaluation in terms of dose-response outcomes. However, the connection of these two foci has received little attention, leaving risk prediction with an insufficient mechanistic basis. Consequently, there is a critical need to quantifiably link in-host infection pathways with the dose-response paradigm. To better understand these relationships, we propose a new mathematical model to describe the gastro-intestinal pathway of L. monocytogenes within the host. The model dynamics are shown to be sensitive to inoculation doses and exhibit bi-stability phenomena. Applying the model to guinea pigs, we show how it provides useful tools to identify key parameters and to inform critical values of these parameters that are pivotal in risk evaluation. Our preliminary analysis shows that the effect of gastro-environmental stress, the role of commensal microbiota and immune cells are critical for successful infection of L. monocytogenes and for dictating the shape of the dose-response curves.

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Effect of pH and storage conditions on Listeria monocytogenes growth inoculated into sapote mamey (Pouteria sapota (Jacq) H.E. Moore & Stearn) pulp

Cited by 8 publications

References 41 publications

Advancing risk assessment: mechanistic dose–response modelling ofListeria monocytogenesinfection in human populations

Advancing risk assessment: mechanistic dose–response modelling ofListeria monocytogenesinfection in human populations

Modeling the pressure inactivation of Escherichia coli and Salmonella typhimurium in sapote mamey (Pouteria sapota (Jacq.) H.E. Moore & Stearn) pulp

Unraveling the dose-response puzzle of L. monocytogenes: A mechanistic approach

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