Predictive microbiology theory and application: Is it all about rates?

doi:10.1016/j.foodcont.2012.06.001

Food Control

Volume 29, Issue 2, February 2013, Pages 290-299

https://doi.org/10.1016/j.foodcont.2012.06.001 Get rights and content

Abstract

We review early work on the microbial growth curve and the concept of balanced growth followed by commentary on the stringent response and persister cells. There is a voluminous literature on the effect of antibiotics on resistance and persistence and we call for a greater focus in food microbiology on the effect of biocides in the same context. We also raise potential issues in development of resistance arising from “source–sink” dynamics and from horizontal gene transfer. Redox potential is identified as crucial in determining microbial survival or death, and the recently postulated role for reactive oxygen species in signalling also considered.

“Traditional” predictive microbiology is revisited with emphasis on temperature dependence. We interpret the temperature vs growth rate curve as comprising 11 regions, some well-recognised but others leading to new insights into physiological responses. In particular we are intrigued by a major disruption in the monotonic rate of inactivation at a temperature, slightly below the actual maximum temperature for growth. This non-intuitive behaviour was earlier reported by other research groups and here we propose that it results from a rapid metabolic switch from the relaxed growth state to the stringent survival state.

Finally, we envision the future of predictive microbiology in which models morph from empirical to mechanistic underpinned by microbial physiology and bioinformatics to grow into Systems Biology.

Introduction

This paper is based on a presentation of the same title given at 7ICPMF in September 2011 (McMeekin, Olley, Ratkowsky, & Ross, 2011). In the presentation we discussed rates and time scales in microbiology, early studies on microbial growth rate curves and the concept of balanced growth. This was followed by consideration of the stringent response and persister cells, topics which are underrepresented in the food microbiology literature. Attention was then focused on modelling studies with emphasis on temperature dependence models. Finally, we asked if the quantitative information embedded in predictive models could be effectively integrated with microbial physiology and “omics” technologies.

In answer to the question posed in the presentation title, “… is it all about rates?” we were confident to respond positively when the question addressed the use of predictive models to estimate the safety and shelf-life of foods. However, our response was equivocal when the question was framed in the context of integrating predictive models with microbial physiology studies and the data deluge emanating from “omics” studies. Here we extend the scope of the 7ICPMF presentation by incorporating recent literature (much of it published since September 2011) in an attempt to provide a definitive response to the objective of successful integration of traditional and futuristic predictive modelling.

Section snippets

Rates: all pervasive and all persuasive?

Time scales in microbiology range from milliseconds for enzyme catalysed reactions (Stockbridge, Lewis, Yuan, & Wolfenden, 2010) to doubling times of 7 min for Clostridium perfringens to days, weeks or months for psychrophiles growing under optimal conditions to more than 3.5 billion years for life to reach the current level of adaptive evolution. The last time frame has been achieved only as a result of the sub-second rates of enzyme catalysed reactions. For example the enzyme catalysed

The stringent response – paradigm lost in food microbiology

Even major changes in the physiology of the cell can occur in seconds. A good example is the transition from the relaxed response state to that of the stringent response and the converse switch which occur in 20–30 s (Cashel, 1975). This is equivalent to the half lives of guanosine tetraphosphate (ppGpp) and guanosine pentaphosphate (ppGppp), the alarmones that give an unequivocal clue to cells to switch from one state to the other (Lund & Kjeldgaard, 1972). Thus, in a few seconds the purpose

Persister cells – “stealth bombers” in the microbial survival armoury?

Cells with slow or zero growth rates confer a very distinct competitive advantage on microbial populations that, as a result of minimal metabolism, are extremely difficult to inactivate. The term, “bacterial persistence,” was introduced by Bigger (1944) who reported the inability of ampicillin to “sterilize” cultures of Staphylococcus aureus. Several studies prior to 1944 in which “super-survivors” were described were noted by Kolter (1999). Research on persistence continues apace with

Greater focus on biocides in food microbiology?

The number of publications on the role of the SR and persister cells in surviving antibiotic challenges greatly outnumbers those concerned with detailed mechanisms of survival of cells when challenged with biocides. The possible effect of four antimicrobial substances widely used in the food industry was addressed by EFSA (2008) which wrote that “despite a long history of use, there are currently no published data to conclude that the application of chlorine dioxide, acidified sodium chlorite,

Redox potential – an arbiter of growth or death and associated rates

Above we were concerned with microbial survival and presented several examples of widely contrasting time scales and rates from rapid physiological responses to eons of evolutionary time. One of the major events during evolution was the microbial driven switch from anaerobiosis to the highly oxygenated world that we currently inhabit. But, while aerobic metabolism was essential for development of more complex life forms there was also a downside because of the generation of reactive oxygen

Quantifying rates in predictive microbiology

To this point the discussion has been concentrated on aspects of microbial physiology that affect growth and inactivation rates and rates of recovery from the effects of environmental insults. From this point we will move to consider predictive models more closely in sections 8 Modelling the effects of temperature on growth, 9 The elements of a growth rate versus temperature plot for the full biokinetic temperature range, 10 Moving towards a mechanistic model. Finally we will attempt to

Modelling the effects of temperature on growth

As noted above, temperature has often been the primary factor to measure in predictive microbiology because it is the factor likely to fluctuate to the greatest extent as product moves through the supply chain. The major “competitors” for interpreting the effects of temperature on microbial ecology in foods are Arrhenius-type and Bělehradék-type models. Whilst the goodness-of-fit of these models have been compared in many studies, differences are often minimal. The conclusion is that both

The elements of a growth rate versus temperature plot for the full biokinetic temperature range

The response of growth rate to temperature plotted as the square root of growth rate versus temperature is shown in Fig. 1. This has the advantage of homogenising the variance and providing a linear response in the sub-optimal region. It also emphasises the juxtaposition of T_min and MINt and of T_max and MAXt.

Moving towards a mechanistic model

Ratkowsky, Olley, and Ross (2005) reported on the similarity of temperature dependence of bacterial growth and the stability of globular proteins using a kinetic model incorporating thermodynamic terms for protein denaturation. The underlying concept relied on a term for the positive change in heat capacity during protein unfolding.

The thermodynamic model was developed using 35 data sets for psychrophilic, psychrotropic, mesophilic and thermophilic bacteria resulting in biologically meaningful

Bioinformatics – the highway to predictive Systems Biology?

To date predictive microbiology has been concerned with predicting the rates of biological processes, particularly microbial growth and inactivation, almost exclusively using empirical models. More recently we have seen development of mechanistic models, such as the thermodynamically based temperature dependence model proposed by Corkrey et al. (2012). We have also experienced the “stampede” into ‘omics-based technologies by which enormous amounts of data are accumulated potentially allowing

Conclusions

In the presentation given at 7ICPMF in September 2011 we were unable to conclude unequivocally that successful integration of traditional and futuristic predictive modelling was possible. Now, after an extensive additional literature search, including many papers published subsequent to 7ICPMF we are more confident that this goal is achievable.

The first reference cited in this paper, Stockbridge et al. (2010), provided an estimate of time required for evolution of enzymes. So, having started

Acknowledgement

Tom McMeekin thanks the Organising Committee of 7ICPMF for their kind invitation to attend the conference and their generosity and hospitality. The authors are indebted to Vasilis Valdramidis for his sound advice and considerable patience during preparation of this manuscript. The authors also thank Professor Stanley Brul, University of Amersterdam, for bringing to our attention the role of the stringent response to explain phenomenological reports of non-intuitive behaviour in bacterial growth

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It is therefore important to provide decision-makers with quantitative tools that predict these tails accurately. Another improvement was obtained by highlighting (and integrating in the model) the relationship between experimental (that will be noted MINt as in McMeekin et al., 2013) and fitted (Tmin) minimum temperatures. To our knowledge, this is the first time a quantitative relationship between these two parameters is proposed.
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Predictive microbiology theory and application: Is it all about rates?

Abstract

Introduction

Section snippets

Rates: all pervasive and all persuasive?

The stringent response – paradigm lost in food microbiology

Persister cells – “stealth bombers” in the microbial survival armoury?

Greater focus on biocides in food microbiology?

Redox potential – an arbiter of growth or death and associated rates

Quantifying rates in predictive microbiology

Modelling the effects of temperature on growth

The elements of a growth rate versus temperature plot for the full biokinetic temperature range

Moving towards a mechanistic model

Bioinformatics – the highway to predictive Systems Biology?

Conclusions

Acknowledgement

Trends in Genetics

International Journal of Food Microbiology

Lancet

Biophysical Journal

Trends in Food Science & Technology

Biophysical Journal

International Journal of Food Microbiology

Food Microbiology

Journal of Biological Chemistry

International Journal of Food Microbiology

FEBS Letters

International Journal of Food Microbiology

International Journal of Food Microbiology

International Journal of Food Microbiology

FEMS Microbiology Letters

Journal of Theoretical Biology

Modeling the effect of pH, acidulant and temperature on the growth rate of Yersinia enterocolitica

Journal of Applied Bacteriology

Inhibition of pyruvate kinase M2 by reactive oxygen species contributes to cellular antioxidant responses

Science

Principles that govern folding of protein chains

Science

Bacterial persistence as a phenotypic switch

Science

Antioxidant strategies to tolerate antibiotics

Science

Growth of Clostridium perfringens in cooked chili during cooling

Applied and Environmental Microbiology

Comment: the viable but non-culturable phenomenon explained?

Microbiology

Synchronization of cell division

Bacteriological Reviews

Unprecedented levels of horizontal gene transfer among spatially co-occurring Shewanella bacteria from the Baltic Sea

ISME Journal

Regulation of bacterial ppGpp and pppGpp

Annual Review of Microbiology

Haplotype diversity in “source-sink” dynamics of Escherichia coli urovirulence

Journal of Molecular Evolution

Very slow growth of Escherichia coli

Journal of Bacteriology

Bacterial glutathione: a sacrificial defense against chlorine compounds

Journal of Bacteriology

The origins and meaning of the Schaechter-Maaløe-Kjeldgaard experiments

Journal of General Microbiology

Universality of thermodynamic constants governing biological growth rates

PloS One

Heat stress adaptation of Escherichia coli under dynamic conditions: effect of inoculum size*

Letters in Applied Microbiology

Illuminating the landscape of host-pathogen interactions with the bacterium Listeria monocytogenes

Proceedings of the National Academy of Sciences of the United States of America

Bacterial biofilms: a common cause of persistent infections

Science

We are what we eat: food safety and proteomics

Journal of Proteome Research

Resistance and adaptation to food antimicrobials, sanitizers, and other process controls

Food Technology

Systematic variation in the temperature dependence of physiological and ecological traits

Proceedings of the National Academy of Sciences

Experimental evidence that source genetic variation drives pathogen emergence

Proceedings of the Royal Society B-Biological Sciences

Chemistry and biology of reactive oxygen species in signaling or stress responses

Nature Chemical Biology

Assessment of the possible effect of the four antimicrobial treatment substances on the emergence of antimicrobial resistance

The EFSA Journal