Considering the complexity of microbial community dynamics in food safety risk assessment

Abstract

The potential for competitive inhibition to limit the growth of microbial pathogens in food raises questions about the external validity of typical predictive microbiology studies and suggests the need to consider microbial community dynamics in food safety risk assessment. Ecological theory indicates, however, that community dynamics are highly complex and may be very sensitive to initial conditions and random variation. Seemingly incongruous empirical results for Escherichia coli O157:H7 in ground beef are shown to be consistent with a simple theoretical model of interspecific competition. A potential means of incorporating community-level microbial dynamics into the food safety risk assessment process is explored.

Introduction

Predictive microbiology has made significant contributions to food safety risk assessment and risk management (McMeekin et al., 1997). Like the results of other experimental studies, however, nagging concerns remain about the external validity of predictive microbiology models for drawing inferences about real world exposures to microbial pathogens in food. Typically, such models have been developed on the basis of monospecific cultures grown in an artificial matrix under static abiotic environmental conditions. Predictive microbiological models typically have failed to account for non-steady-state environmental conditions and diversity in the physiologic status of microorganisms and pretreatment storage conditions (McMeekin et al., 1997). Furthermore, pathogen growth rates and maximum densities are thought to be a function of the total microbial community composition and density in the food due to competition for nutrients, the production of inhibitory substances, and overall density. Thus, the potential for spoilage and other normal food microflora to competitively inhibit the growth of pathogens also raises questions about the validity of monospecific culture experimental results with respect to growth rates, maximum population density (MPD), and other aspects of pathogen population dynamics in naturally contaminated food products. Competitive inhibition of foodborne pathogens has been demonstrated for Salmonella, where the suppression of growth of all microorganisms occurred when the total microbial population density achieved the upper limit characteristic of the growth matrix (Jameson, 1962). This effect has also been reported for Staphylococcus aureus, Listeria monocytogenes, Yersinia enterocolitica, Bacillius cereus, Salmonella infantis, and Carnobacterium spp. Buchanan and Bagi, 1997, Duffes et al., 1999, Grau and Vanderlinde, 1992, Mattila-Sandholm and Skytta, 1991, Nilsson et al., 1999, Ross and McMeekin, 1991. The observed dynamics of mixed microbial populations can be highly complex, however. Buchanan and Bagi (1999) demonstrated, for example, that L. monocytogenes grown in co-culture with Pseudomonas fluorescens can attain maximum population densities that are lower, higher, or the same compared to levels of the pathogen monoculture, depending on the temperature, acidity, and availability of water in the surrounding environment. Such results indicate that fully considering the complexity of microbial community dynamics would require detailed knowledge of the food, its microbial composition and inoculum levels, the factors affecting competitive interactions, and how the food is handled during transportation, storage, distribution, and use.

Undoubtedly, predictive microbiological models based on multi-species trials would present a more realistic picture of microbial community dynamics in food products. As a practical matter, however, an experimental program that evaluates all possible combinations of abiotic and biotic environmental conditions would be prohibitively costly and time-consuming. There are also practical limits on the successful identification and enumeration of target organisms and their competitors given currently available microbiological selective culture methods. Therefore, great care in experimental design will be needed to ensure that the value of information provided by community-level studies warrants the time and resources allocated to them. From an experimental perspective, judicious use of theoretical ecology models has the potential to inform efficient community-level study design by helping to identify important regions in the experimental design space (e.g., the growth/no-growth interface). Furthermore, theoretical modeling can help to construct general explanations for specific observed results. This application of theoretical modeling can be particularly useful when results are unexpected. Therefore—as a practical matter—the insights gained from theoretical ecology may help to avert potentially unproductive disagreements arising from seemingly contradictory empirical results.

One apparent contradiction arises from the intuitive notion that ubiquitous natural spoilage flora (e.g., Pseudomonas species) will inevitably outcompete and eventually exclude comparatively rare pathogens in food products. Responses observed under experimental conditions vary considerably, however (e.g., Buchanan and Bagi, 1999). Further, theoretical ecology indicates that the course of competitive interactions between microorganisms may be substantially altered or even reversed due to variation among strains or environmental conditions or as a consequence of chance events, such as differences in initial concentrations between pathogens and other microflora within the food substrate. This paper first illustrates the consistency of seemingly incongruous results from predictive microbiological experiments with a simple model of interspecific competition, using Escherichia coli O157:H7 in ground beef as an illustrative example. We then explore how community-level microbial dynamics could be incorporated into the food safety risk assessment process.

Predictive microbiology models have been developed for E. coli O157:H7 under a variety of environmental conditions. These models predict the growth and decline of E. coli O157:H7 given environmental parameters including time, temperature, pH, and salinity. One set of equations was developed by Buchanan and Bagi (1994) based on studies of monospecific cultures grown in brain heart infusion broth. This set of equations was later incorporated into the Pathogen Modeling Program (PMP) available from the US Department of Agriculture, Agricultural Research Service (ARS). Based on the ARS data, Marks et al. (1998) calculated the maximum population density (e.g., the observed maximum number of E. coli O157:H7 colony-forming units per gram (cfu/g)) as a function of the theoretical maximum density (TMD) and temperature. Marks et al. (1998) estimated the TMD of E. coli O157:H7 at refrigeration temperatures to be about 10 log (10¹⁰ cfu/g).

Walls and Scott (1996) compared predictions from the PMP with observations of E. coli O157:H7 growth in ground beef with natural flora and concluded that the PMP “offers reasonably good predictions of growth in raw ground beef”. In particular, Walls and Scott (1996) demonstrated growth in ground beef up to approximately 10 log. (Note that the figures in Walls and Scott (1996) present the average levels for the experimental replicates.) How is it possible that the MPD of E. coli O157:H7 co-cultured with the natural ground beef flora could approach the theoretical maximum? Initially, the experimental results for E. coli O157:H7 cultured in raw ground beef appear to contradict those reported for Salmonella, Listeria, and other pathogens co-cultured with natural foodborne microflora. These seemingly paradoxical experimental results are consistent, however, with the complex range of outcomes predicted by a simple model of interspecific competition.