Modelling of bacterial growth with shifts in temperature using automated methods with Listeria monocytogenes and Pseudomonas aeruginosa as examples

Salih, Magdi; Mytilinaios, Ioannis; Schofield, H.K.; Lambert, R. H.

doi:10.1016/j.ijfoodmicro.2012.01.011

Cited by 8 publications

(3 citation statements)

References 17 publications

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“…It is common to include a temperature-dependent model complemented with the growth model for temperature-dependent growth model. There are many studies on microbial growth with the temperature-dependent model (Zwietering et al 1994;Daughtry et al 1997;Bovill et al 2000;Fujikawa et al 2004;Corradini et al 2005;Dominguez and Schaffner 2007;Juneja et al 2007Juneja et al , 2009Gospavic et al 2008;Salih et al 2012). Other alternative may include salinity, pH, temperature, and nutrient concentration into the model (Hosseininoosheri et al 2016).…”

Section: Biosurfactant-producing Bacteria Growth Modelmentioning

confidence: 99%

Microbial enhanced oil recovery: interfacial tension and biosurfactant-bacteria growth

Putra¹,

Hakiki

2019

J Petrol Explor Prod Technol

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Microbial enhanced oil recovery (MEOR) is a method that utilises bacteria or bioproducts to increase oil recovery at the tertiary stage. Clostridium sp. produces biosurfactant that alters rock-fluid properties and increases oil detachment. The interaction between bacteria and surfactant is interesting relation to study. We revisit and develop models for biosurfactantproducing bacteria's growth and the interfacial tension (IFT) response. The biosurfactant-producing bacteria growth model (BBG model) mimics the predator-prey interaction and the IFT response model derived from analogy. Both models form an integrated model called coupled-simultaneous model. We deliver the suitability of these models to experimental datasets by conducting parameter estimation. The decreased number of parameter in BBG model is with the help of rate estimation model. It estimates the bacteria growth rate and biosurfactant production rate. This research introduces a graphical method to narrow parameters initial guess in the IFT model. The method comes with a proposed index to compare surfactant performance called as surfactant performance index (SPI). The paper exposes the logic of each parameter, physics behind the models, and addresses the mathematical artefacts. The significant findings are valuable to anticipate bacterial performance for MEOR.

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Section: Biosurfactant-producing Bacteria Growth Modelmentioning

confidence: 99%

Microbial enhanced oil recovery: interfacial tension and biosurfactant-bacteria growth

Putra¹,

Hakiki

2019

J Petrol Explor Prod Technol

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“…Salih et al . () used microtiter plates to study the effects of temperature shifts on Listeria monocytogenes and P. aeruginosa , and concluded that for temperature shifts within small ranges, growth rates respond quickly to new environments without induction of lag times. Antolinos et al .…”

Section: Introductionmentioning

confidence: 99%

Modeling Growth of Pseudomonas Aeruginosa Single Cells with Temperature Shifts

Wang

Dong

Liu

et al. 2016

Journal of Food Safety

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In this article, a single-cell growth and imaging system was used to study how the growth of single cells of Pseudomonas aeruginosa was affected by temperature shifts. An individual-based modeling was conducted to predict the growth of bacterial single cells. We found that shifts to lower temperatures lengthened the division times of P. aeruginosa single cells, whereas shifts to higher temperature caused a rapid shortening of the division times. The coefficient of variation of the division time decreased as the magnitude of the temperature shifts increased which suggested that the variability of the growth of single P. aeruginosa cells was increased with bigger temperature shifts. Furthermore, the individual-based modeling proposed in this study turned out to be a useful way for predicting the stochastic growth of single bacterial cells under nonconstant temperature conditions. PRACTICAL APPLICATIONSIt was deduced that studying the microbial dynamics at the single cell level, which take into account the growth viability and uncertainty of bacterial single cells, could help to establish a more reliable set of microbe-influenced food shelf life and food safety criteria.

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“…To (120). However, it is generally accepted that the optimal growth temperature for P. aeruginosa is closer to the temperature of the human body, 39°C (122). Additionally, as P. aeruginosa has the ability to infect humans, all essential cellular proteins must have the ability to function at 37°C.…”

Section: Discussionmentioning

confidence: 99%

Moonlighting and Mimicry: Identification and Functional Characterization of a SAM-dependent Methyltransferase Responsible for Methylation of EF-Tu in Pseudomonas Aeruginosa

Owings

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Phosphorylcholine (ChoP) is a charged molecule that, in humans, is the major recognition component of platelet activating factor (PAF) by its cognate receptor, platelet activating factor receptor (PAFR). ChoP-like molecules have been detected on the surfaces of numerous respiratory pathogens where they confer persistence related phenotypes mediated through an increase in adhesion. Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen which is often associated with nosocomial pneumonia. Previously, in P. aeruginosa a ChoP-like modification was detected using ChoP-specific antibodies on surface exposed elongation factor-Tu (EF-Tu), a normally cytoplasmic protein involved in protein chain elongation. Here we identify a gene, eftM, which is required for the modification of EF-Tu. To our surprise, mass spectrometry analysis of modified EF-Tu revealed the modification was not ChoP but rather trimethyl-lysine at amino acid residue 5. This trimethyl-lysine acts as a structural mimic of ChoP and confers similar phenotypes to P. aeruginosa as ChoP does to other respiratory pathogens. Bioinformatic analysis of EftM showed amino acid sequence similarity to Sadenosylmethionine (SAM)-dependent methyltransferases. We confirmed biochemically that EftM is able to bind SAM and used it to directly methylate lysine 5 of EF-Tu both in vivo and in vitro. Mass spectrometry analysis of products from these reactions confirmed that EF-Tu is trimethylated at lysine 5. In vivo, P. aeruginosa methylates EF-Tu only at temperatures closer to ambient, 25°C, and not at body temperature, 37°C. We show that this temperature-dependent methylation phenotype is not due to differences in transcription of eftM. The methyltransferase activity of the laboratory P. aeruginosa strain PAO1 EftM is slightly higher at 25°C compared to 37°C, while the rate of

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Modelling of bacterial growth with shifts in temperature using automated methods with Listeria monocytogenes and Pseudomonas aeruginosa as examples

Cited by 8 publications

References 17 publications

Microbial enhanced oil recovery: interfacial tension and biosurfactant-bacteria growth

Microbial enhanced oil recovery: interfacial tension and biosurfactant-bacteria growth

Modeling Growth of Pseudomonas Aeruginosa Single Cells with Temperature Shifts

Moonlighting and Mimicry: Identification and Functional Characterization of a SAM-dependent Methyltransferase Responsible for Methylation of EF-Tu in Pseudomonas Aeruginosa

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