Generation Times and Modeling of Enterotoxin-Positive and Enterotoxin-Negative Strains of Clostridium perfringens in Laboratory Media and Ground Beef

Labbé, Ronald G.; Huang, Teng

doi:10.4315/0362-028x-58.12.1303

Cited by 61 publications

(28 citation statements)

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“…Information regarding the growth rate of bacteria in the wild is sparse, and so we have used the number of rRNA operons as a (very approximate) guide to the growth rate of species. Remarkably, C.perfringens , the species with the highest S -value (2.65) and 10 rRNA operons, can grow with a generation time under 7 min in specific laboratory conditions (55). In contrast, Mycobacterium species are renowned for their very slow growth: M.tuberculosis and M.leprae have generation times of ∼1 and 14 days, respectively.…”

Section: Discussionmentioning

confidence: 99%

Variation in the strength of selected codon usage bias among bacteria

Sharp

Bailes

Grocock

et al. 2005

Nucleic Acids Research

374

429

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Among bacteria, many species have synonymous codon usage patterns that have been influenced by natural selection for those codons that are translated more accurately and/or efficiently. However, in other species selection appears to have been ineffective. Here, we introduce a population genetics-based model for quantifying the extent to which selection has been effective. The approach is applied to 80 phylogenetically diverse bacterial species for which whole genome sequences are available. The strength of selected codon usage bias, S, is found to vary substantially among species; in 30% of the genomes examined, there was no significant evidence that selection had been effective. Values of S are highly positively correlated with both the number of rRNA operons and the number of tRNA genes. These results are consistent with the hypothesis that species exposed to selection for rapid growth have more rRNA operons, more tRNA genes and more strongly selected codon usage bias. For example, Clostridium perfringens, the species with the highest value of S, can have a generation time as short as 7 min.

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Section: Discussionmentioning

confidence: 99%

Variation in the strength of selected codon usage bias among bacteria

Sharp

Bailes

Grocock

et al. 2005

Nucleic Acids Research

374

429

View full text Add to dashboard Cite

show abstract

“…These results were interpreted as reflecting selection for a co-adapted suite of genomic characteristics required for rapid growth (Sharp et al 2005). For example, C. perfringens has 10 rRNA operons and 96 tRNA genes and can replicate in only 7 min under ideal conditions (Labbe & Huang 1995).…”

Section: Variation In the Strength Of Selected Codon Usage Bias Amongmentioning

confidence: 99%

Forces that influence the evolution of codon bias

Sharp

Emery

Zeng

2010

Phil. Trans. R. Soc. B

317

246

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The frequencies of alternative synonymous codons vary both among species and among genes from the same genome. These patterns have been inferred to reflect the action of natural selection. Here we evaluate this in bacteria. While intragenomic variation in many species is consistent with selection favouring translationally optimal codons, much of the variation among species appears to be due to biased patterns of mutation. The strength of selection on codon usage can be estimated by two different approaches. First, the extent of bias in favour of translationally optimal codons in highly expressed genes, compared to that in genes where selection is weak, reveals the longterm effectiveness of selection. Here we show that the strength of selected codon usage bias is highly correlated with bacterial growth rate, suggesting that selection has favoured translational efficiency. Second, the pattern of bias towards optimal codons at polymorphic sites reveals the ongoing action of selection. Using this approach we obtained results that were completely consistent with the first method; importantly, the frequency spectra of optimal codons at polymorphic sites were similar to those predicted under an equilibrium model. Highly expressed genes in Escherichia coli appear to be under continuing strong selection, whereas selection is very weak in genes expressed at low levels.

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“…For each isothermal growth curve, the entire data set is reported in ComBase. The beef data were published in 3 studies (Foegeding and Busta ; Labbe and Huang ; Juneja and others ), and contain a total of 285 individual data points. The poultry data were published in 2 studies (Mead ; Juneja and others ), and contain 176 individual data points.…”

Section: Methodsmentioning

confidence: 99%

Evaluating the Performance of a New Model for Predicting the Growth of Clostridium perfringens in Cooked, Uncured Meat and Poultry Products under Isothermal, Heating, and Dynamically Cooling Conditions

Huang

2016

Journal of Food Science

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Clostridium perfringens type A is a significant public health threat and its spores may germinate, outgrow, and multiply during cooling of cooked meats. This study applies a new C. perfringens growth model in the USDA Integrated Pathogen Modeling Program-Dynamic Prediction (IPMP Dynamic Prediction) Dynamic Prediction to predict the growth from spores of C. perfringens in cooked uncured meat and poultry products using isothermal, dynamic heating, and cooling data reported in the literature. The residual errors of predictions (observation-prediction) are analyzed, and the root-mean-square error (RMSE) calculated. For isothermal and heating profiles, each data point in growth curves is compared. The mean residual errors (MRE) of predictions range from -0.40 to 0.02 Log colony forming units (CFU)/g, with a RMSE of approximately 0.6 Log CFU/g. For cooling, the end point predictions are conservative in nature, with an MRE of -1.16 Log CFU/g for single-rate cooling and -0.66 Log CFU/g for dual-rate cooling. The RMSE is between 0.6 and 0.7 Log CFU/g. Compared with other models reported in the literature, this model makes more accurate and fail-safe predictions. For cooling, the percentage for accurate and fail-safe predictions is between 97.6% and 100%. Under criterion 1, the percentage of accurate predictions is 47.5% for single-rate cooling and 66.7% for dual-rate cooling, while the fail-dangerous predictions are between 0% and 2.4%. This study demonstrates that IPMP Dynamic Prediction can be used by food processors and regulatory agencies as a tool to predict the growth of C. perfringens in uncured cooked meats and evaluate the safety of cooked or heat-treated uncured meat and poultry products exposed to cooling deviations or to develop customized cooling schedules. This study also demonstrates the need for more accurate data collection during cooling.

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Generation Times and Modeling of Enterotoxin-Positive and Enterotoxin-Negative Strains of Clostridium perfringens in Laboratory Media and Ground Beef

Cited by 61 publications

References 0 publications

Variation in the strength of selected codon usage bias among bacteria

Variation in the strength of selected codon usage bias among bacteria

Forces that influence the evolution of codon bias

Evaluating the Performance of a New Model for Predicting the Growth of Clostridium perfringens in Cooked, Uncured Meat and Poultry Products under Isothermal, Heating, and Dynamically Cooling Conditions

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