Escherichia coli Thermal Inactivation Relative to Physiological State

2009 ◽  
Vol 72 (2) ◽  
pp. 399-402 ◽  
Author(s):  
D. GLENN BLACK ◽  
FEDERICO HARTE ◽  
P. MICHAEL DAVIDSON
Keyword(s):  
Escherichia Coli ◽  
Goodness Of Fit ◽  
Thermal Inactivation ◽  
Physiological State ◽  
Weibull Model ◽  
Growth Conditions ◽  
Coli Strain ◽  
Microbial Inactivation ◽  
Microbial Cells ◽  
K 12

Studies have explored the use of various nonlinear regression techniques to better describe shoulder and/or tailing effects in survivor curves. Researchers have compiled and developed a number of diverse models for describing microbial inactivation and presented goodness of fit analysis to compare them. However, varying physiological states of microorganisms could affect the measured response in a particular population and add uncertainty to results from predictive models. The objective of this study was to determine if the shape and magnitude of the survivor curve are possibly the result of the physiological state, relative to growth conditions, of microbial cells at the time of heat exposure. Inactivation tests were performed using Escherichia coli strain K-12 in triplicate for three growth conditions: statically grown cells, chemostat-grown cells, and chemostat-grown cells with buffered (pH 6.5) feed media. Chemostat cells were significantly less heat resistant than the static or buffered chemostat cells at 58°C. Regression analysis was performed using the GInaFiT freeware tool for Microsoft Excel. A nonlinear Weibull model, capable of fitting tailing effects, was effective for describing both the static and buffered chemostat cells. The log-linear response best described inactivation of the nonbuffered chemostat cells. Results showed differences in the inactivation response of microbial cells depending on their physiological state. The use of any model should take into consideration the proper use of regression tools for accuracy and include a comprehensive understanding of the growth and inactivation conditions used to generate thermal inactivation data.

Influence of Heat Transfer with Tube Methods on Measured Thermal Inactivation Parameters for Escherichia coli

2007 ◽  
Vol 70 (4) ◽  
pp. 851-859 ◽  
Author(s):  
HYUN-JUNG CHUNG ◽  
SHAOJIN WANG ◽  
JUMING TANG
Keyword(s):  
Heat Transfer ◽  
Escherichia Coli ◽  
Heat Resistance ◽  
Bacterial Strain ◽  
Thermal Inactivation ◽  
Microbial Inactivation ◽  
Outer Diameter ◽  
Survival Curves ◽  
Log Linear ◽  
K 12

The purpose of this study was to investigate the influence of heat transfer on measured thermal inactivation kinetic parameters of bacteria in solid foods when using tube methods. The bacterial strain selected for this study, Escherichia coli K-12, had demonstrated typical first-order inactivation characteristics under isothermal test conditions. Three tubes of different sizes (3, 13, and 20 mm outer diameter) were used in the heat treatments at 57, 60, and 63°C with mashed potato as the test food. A computer model was developed to evaluate the effect of transit heat transfer behavior on microbial inactivation in the test tubes. The results confirmed that the survival curves of E. coli K-12 obtained in 3-mm capillary tubes were log linear at the three tested temperatures. The survival curves observed under nonisothermal conditions in larger tubes were no longer log linear. Slow heat transfer alone could only partially account for the large departures from log-linear behavior. Tests with the same bacterial strain after 5 min of preconditioning at a sublethal temperature of 45°C revealed significantly enhanced heat resistance. Confirmative tests revealed that the increased heat resistance of the test bacterium in the center of the large tubes during the warming-up periods resulted in significantly larger D-values than those obtained with capillary tube methods.

Theil Error Splitting Method for Selecting the “Best Model” in Microbial Inactivation Studies

2009 ◽  
Vol 72 (4) ◽  
pp. 843-848 ◽  
Author(s):  
FEDERICO HARTE ◽  
GLENN BLACK ◽  
P. MICHAEL DAVIDSON
Keyword(s):  
Escherichia Coli ◽  
Random Error ◽  
Error Term ◽  
Goodness Of Fit ◽  
Statistical Tests ◽  
Splitting Method ◽  
Microbial Inactivation ◽  
Time Data ◽  
Error Sources ◽  
K 12

Escherichia coli K-12 was grown under unbuffered, buffered, and starving environmental conditions and then subjected to isothermal inactivation at 58°C for up to 30 min. Survival versus time data were used to evaluate three models reported as suitable for the prediction of microbial inactivation by thermal means. The error splitting method proposed by Theil was used to divide the average squared difference between each observed and predicted datum into three orthogonal error sources: bias, regression, and random error. The method is based on the hypothesis that if the model is accurate, the overall average predicted and observed values should be the same and a plot of observed versus predicted inactivation values should have a slope of 1. The bias fixed error term quantifies the overall average difference between predicted and observed inactivation values. The regression fixed error term quantifies the difference between observed and predicted values near the end of the predictive region, where shoulders and tails may occur. The random error term quantifies the random variability of the predicted versus observed inactivation values. Statistical tests were proposed to determine the significance of each fixed error term and the normality of the random error source. The method was used to discuss the goodness of fit for the three models for Escherichia coli. The best model was the one that minimized total residual error, maximized random error sources (i.e., fixed error terms are not significant), and maximized the coefficient of correlation between observed and predicted inactivation values.

scholarly journals Phenotype inference in an Escherichia coli strain panel

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Marco Galardini ◽  
Alexandra Koumoutsi ◽  
Lucia Herrera-Dominguez ◽  
Juan Antonio Cordero Varela ◽  
Anja Telzerow ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Association Studies ◽  
Growth Conditions ◽  
Coli Strain ◽  
Genome Wide Association Studies ◽  
Loss Of Function ◽  
Promising Alternative ◽  
Genetic Interventions ◽  
K 12 ◽  
The Impact

Understanding how genetic variation contributes to phenotypic differences is a fundamental question in biology. Combining high-throughput gene function assays with mechanistic models of the impact of genetic variants is a promising alternative to genome-wide association studies. Here we have assembled a large panel of 696 Escherichia coli strains, which we have genotyped and measured their phenotypic profile across 214 growth conditions. We integrated variant effect predictors to derive gene-level probabilities of loss of function for every gene across all strains. Finally, we combined these probabilities with information on conditional gene essentiality in the reference K-12 strain to compute the growth defects of each strain. Not only could we reliably predict these defects in up to 38% of tested conditions, but we could also directly identify the causal variants that were validated through complementation assays. Our work demonstrates the power of forward predictive models and the possibility of precision genetic interventions.

Thermal Inactivation of Escherichia coli O157:H7 When Grown Statically or Continuously in a Chemostat

2010 ◽  
Vol 73 (11) ◽  
pp. 2018-2024 ◽  
Author(s):  
D. GLENN BLACK ◽  
X. PHILIP YE ◽  
FEDERICO HARTE ◽  
P. MICHAEL DAVIDSON
Keyword(s):  
Escherichia Coli ◽  
Linear Model ◽  
Thermal Inactivation ◽  
Physiological State ◽  
Weibull Model ◽  
Process Temperature ◽  
Log P ◽  
Model Parameters ◽  
Escherichia Coli O157 ◽  
Log Linear

The objective of this study was to determine if survivor curves for heat-inactivated Escherichia coli O157:H7 were affected by the physiological state of the cells relative to growth conditions and pH of the heating menstruum. A comparison was made between the log-linear model and non–log-linear Weibull approach. Cells were grown statically in aerobic culture tubes or in an aerobic chemostat in tryptic soy broth (pH 7.2). The heating menstruum was unbuffered peptone or phosphate buffer (pH 7.0). Thermal inactivation was carried out at 58, 59, 60, and 61°C, and recovery was on a nonselective medium. Longer inactivation times for statically grown cells indicated potential stress adaptation. This was more prevalent at 58°C. Shape response was also significantly different, with statically grown cells exhibiting decreasing thermal resistance over time and chemostat cells showing the opposite effect. Buffering the heating menstruum to ca. pH 7 resulted in inactivation curves that showed less variability or scatter of data points. Time to specific log reduction values (td) for the Weibull model were conservative relative to the log-linear model depending upon the stage of reduction. The Weibull model offered the most accurate fit of the data in all cases, especially considering the log-linear model is equivalent to the Weibull model with a fixed shape factor of 1. The determination of z-value for the log-linear model showed a strong correlation between log D-value and process temperature. Correlations for the Weibull model parameters (log δand log p) versus process temperature were not statistically significant.

scholarly journals Development of a Genome-Scale Metabolic Model and Phenome Analysis of the Probiotic Escherichia coli Strain Nissle 1917

2021 ◽  
Vol 22 (4) ◽  
pp. 2122
Author(s):  
Dohyeon Kim ◽  
Youngshin Kim ◽  
Sung Ho Yoon
Keyword(s):  
Escherichia Coli ◽  
Metabolic Model ◽  
Growth Conditions ◽  
Coli Strain ◽  
Anaerobic Growth ◽  
System Level ◽  
Genome Comparison ◽  
Phenotype Microarray ◽  
A Genome ◽  
K 12

Escherichia coli Nissle 1917 (EcN) is an intestinal probiotic that is effective for the treatment of intestinal disorders, such as inflammatory bowel disease and ulcerative colitis. EcN is a representative Gram-negative probiotic in biomedical research and is an intensively studied probiotic. However, to date, its genome-wide metabolic network model has not been developed. Here, we developed a comprehensive and highly curated EcN metabolic model, referred to as iDK1463, based on genome comparison and phenome analysis. The model was improved and validated by comparing the simulation results with experimental results from phenotype microarray tests. iDK1463 comprises 1463 genes, 1313 unique metabolites, and 2984 metabolic reactions. Phenome data of EcN were compared with those of Escherichia coli intestinal commensal K-12 MG1655. iDK1463 was simulated to identify the genetic determinants responsible for the observed phenotypic differences between EcN and K-12. Further, the model was simulated for gene essentiality analysis and utilization of nutrient sources under anaerobic growth conditions. These analyses provided insights into the metabolic mechanisms by which EcN colonizes and persists in the gut. iDK1463 will contribute to the system-level understanding of the functional capacity of gut microbes and their interactions with microbiota and human hosts, as well as the development of live microbial therapeutics.

Polarity and the regulation of the ilv gene cluster in Escherichia coli strain K-12

1976 ◽  
Vol 148 (2) ◽  
pp. 111-124 ◽  
Author(s):  
John M. Smith ◽  
David E. Smolin ◽  
H. Edwin Umbarger
Keyword(s):  
Escherichia Coli ◽  
Gene Cluster ◽  
Coli Strain ◽  
K 12

Linkage map of Escherichia coli strain K-12.

1972 ◽  
Vol 36 (4) ◽  
pp. 504-524 ◽  
Author(s):  
A L Taylor ◽  
C D Trotter
Keyword(s):  
Escherichia Coli ◽  
Linkage Map ◽  
Coli Strain ◽  
K 12

scholarly journals Transcriptomic Analysis of Escherichia coli O157:H7 and K-12 Cultures Exposed to Inorganic and Organic Acids in Stationary Phase Reveals Acidulant- and Strain-Specific Acid Tolerance Responses

2010 ◽  
Vol 76 (19) ◽  
pp. 6514-6528 ◽  
Author(s):  
Thea King ◽  
Sacha Lucchini ◽  
Jay C. D. Hinton ◽  
Kari Gobius
Keyword(s):  
Escherichia Coli ◽  
Hydrochloric Acid ◽  
Organic Acids ◽  
Stationary Phase ◽  
Molecular Mechanisms ◽  
Microbial Inactivation ◽  
Specific Response ◽  
Transcriptomic Response ◽  
E Coli ◽  
K 12

ABSTRACT The food-borne pathogen Escherichia coli O157:H7 is commonly exposed to organic acid in processed and preserved foods, allowing adaptation and the development of tolerance to pH levels otherwise lethal. Since little is known about the molecular basis of adaptation of E. coli to organic acids, we studied K-12 MG1655 and O157:H7 Sakai during exposure to acetic, lactic, and hydrochloric acid at pH 5.5. This is the first analysis of the pH-dependent transcriptomic response of stationary-phase E. coli. Thirty-four genes and three intergenic regions were upregulated by both strains during exposure to all acids. This universal acid response included genes involved in oxidative, envelope, and cold stress resistance and iron and manganese uptake, as well as 10 genes of unknown function. Acidulant- and strain-specific responses were also revealed. The acidulant-specific response reflects differences in the modes of microbial inactivation, even between weak organic acids. The two strains exhibited similar responses to lactic and hydrochloric acid, while the response to acetic acid was distinct. Acidulant-dependent differences between the strains involved induction of genes involved in the heat shock response, osmoregulation, inorganic ion and nucleotide transport and metabolism, translation, and energy production. E. coli O157:H7-specific acid-inducible genes were identified, suggesting that the enterohemorrhagic E. coli strain possesses additional molecular mechanisms contributing to acid resistance that are absent in K-12. While E. coli K-12 was most resistant to lactic and hydrochloric acid, O157:H7 may have a greater ability to survive in more complex acidic environments, such as those encountered in the host and during food processing.

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