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T A McMeekin

Publications and source records attributed to T A McMeekin.

At least 19 recordsLinked to original sources
PubMed2006

Information systems in food safety management.

Information systems are concerned with data capture, storage, analysis and retrieval. In the context of food safety management they are vital to assist decision making in a short time frame, potentially allowing decisions to be made and practices to be actioned in real time. Databases with information on microorganisms pertinent to the identification of foodborne pathogens, response of microbial populations to the environment and characteristics of foods and processing conditions are the cornerstone of food safety management systems. Such databases find application in: Identifying pathogens in food at the genus or species level using applied systematics in automated ways. Identifying pathogens below the species level by molecular subtyping, an approach successfully applied in epidemiological investigations of foodborne disease and the basis for national surveillance programs. Predictive modelling software, such as the Pathogen Modeling Program and Growth Predictor (that took over the main functions of Food Micromodel) the raw data of which were combined as the genesis of an international web based searchable database (ComBase). Expert systems combining databases on microbial characteristics, food composition and processing information with the resulting "pattern match" indicating problems that may arise from changes in product formulation or processing conditions. Computer software packages to aid the practical application of HACCP and risk assessment and decision trees to bring logical sequences to establishing and modifying food safety management practices. In addition there are many other uses of information systems that benefit food safety more globally, including: Rapid dissemination of information on foodborne disease outbreaks via websites or list servers carrying commentary from many sources, including the press and interest groups, on the reasons for and consequences of foodborne disease incidents. Active surveillance networks allowing rapid dissemination of molecular subtyping information between public health agencies to detect foodborne outbreaks and limit the spread of human disease. Traceability of individual animals or crops from (or before) conception or germination to the consumer as an integral part of food supply chain management. Provision of high quality, online educational packages to food industry personnel otherwise precluded from access to such courses.

Consumer Product Safety↗
PubMed2006

Effect of suspension media on nonthermal inactivation of Escherichia coli.

AIMS: To investigate the influence of suspension media on the survival of Escherichia coli M23 exposed to nonthermal, lethal stresses. METHODS AND RESULTS: Populations of E. coli M23 suspended in minimal medium (MM) or in different nutrient-rich broths were exposed to water activity 0.90 and/or pH 3.5 and inactivation was determined by culture-based enumeration. In response to the osmotic or acid challenges, E. coli M23 displayed enhanced survival in MM rather than in complex broth. That trend was reversed when populations were exposed to low water activity in combination with low pH. Comparison of microbial survival in three complex media indicated that even relatively small differences in composition influenced inactivation. In most media the combination of lethal stresses resulted in a synergism, which enhanced bacterial inactivation; however, an exception (tryptone soya broth) was observed. CONCLUSIONS: The suspension medium strongly influences the inactivation of E. coli M23 by osmotic and/or acid stresses. This should be considered when comparing studies of microbial survival that use different media and when broth-derived data are intended to represent specific environments (e.g. food matrices). SIGNIFICANCE AND IMPACT OF THE STUDY: The specific effects of synthetic media need to be appreciated when studying bacterial inactivation in conditions relevant to food-manufacturing regimes.

Culture Media↗
PubMed2005

Viable count estimates of lag time responses for Salmonella typhimurium M48 subjected to abrupt osmotic shifts.

Generally, relative lag times (RLT; lag time divided by generation time) become extended as conditions become less favourable for growth. Mellefont et al. (2003, 2004) [Mellefont, L.A., McMeekin, T.A., Ross, T., 2003. The effect of abrupt osmotic shifts on the lag phase duration of foodborne bacteria. Int. J. Food Microbiol. 83(3), 281-293; Mellefont, L.A., McMeekin, T.A., Ross, T., 2004. The effect of abrupt osmotic shifts on the lag phase duration of physiologically distinct populations of Salmonella typhimurium. Int. J. Food Microbiol. 92, 111-120] reported that abrupt osmotic shifts of Salmonella typhimurium M48 from optimal to low aw led to unexpectedly small RLTs at low aw. In this study, RLTs resulting from similar osmotic shifts were estimated by viable count (VC) and compared to turbidimetric estimates to test the hypothesis that the 'downturn' in RLT is an artefact of the turbidimetric technique used. No 'downturn' in RLT was observed with VC data and RLTs increased with increasing magnitude of osmotic shift. Anomalous turbidimetric estimates of lag time at low aw were confirmed as the likely source of the 'downturn' in RLT. The abrupt osmotic shifts resulted in a complex pattern of microbial population behaviour. Immediately after transfer from optimal aw to low aw, inactivation of a portion of the population occurred for all the conditions tested. The degree of inactivation became progressively larger with larger shifts in aw. The initial decline in population was followed by a period during which no change in numbers occurred, followed by growth that appeared, in most cases, to be exponential. At the lowest aws tested (< or =0.954), the growth response after the initial decline was at a rate slower than that of exponential phase growth. Due to the use of non-selective media containing pyruvate (to eliminate oxygen radicals), the observed patterns of inactivation, lag and regrowth at most aw conditions are unlikely to result from a temporary loss of culturability, but may represent inactivation of a portion of the population.

Colony Count, Microbial↗
PubMed2004

Temperature step changes: a novel approach to control biofilms of Streptococcus thermophilus in a pilot plant-scale cheese-milk pasteurisation plant.

A pilot plant-scale cheese-milk pasteurisation plant was designed and constructed to study the development of biofilms of Streptococcus thermophilus during pasteurisation of milk, and to investigate methods for preventing this growth from occurring. Under base run conditions, S. thermophilus grew on surfaces in the cool-down sections of the pilot plant, between 50 and 35 degrees C (bulk milk temperature), and could be detected in the product stream after 8-10 h production, reaching levels of 10(6) CFU ml-1 after 16 h. Thermoduric bacteria also grew in the heating sections of the pilot plant, although to a lesser extent, as did non-thermoduric bacteria that originated in the raw milk. The novel application of temperature step changes, implemented periodically to the growth region of S. thermophilus, successfully controlled the development of biofilms of these organisms. The growth of bacteria on the heating side of the pilot plant was also prevented by the implementation of these same step changes. The optimum step change conditions required to achieve a 20-h production run without detectable growth of S. thermophilus comprised a step change to 55 degrees C, applied for 10 min, with a 60-min interval between step changes.

Animals↗
PubMed2004

The effect of abrupt osmotic shifts on the lag phase duration of physiologically distinct populations of Salmonella typhimurium.

Relative lag time (RLT), i.e. lag time divided by generation time, was used to characterise the lag phase response of exponential and stationary phase Salmonella typhimurium subjected to NaCl-mediated hyperosmotic shifts. Abrupt hyperosmotic shifts induced lag phases. The RLT, however, varied with the physiological history of the inoculum and the magnitude of the shift. Turbidimetric data showed that exponential phase cells had larger RLTs (up to approximately 8 units) than stationary phase cells (up to 2-4 units). Inocula containing exponential and stationary phase cells mixed in known proportions gave intermediate results. For viable count data, there was little difference in RLT between exponential and stationary phase cells. The RLT response determined turbidimetrically was reproducible for exponential phase cells, but less so for stationary phase cells. It is suggested that there may be a lower limit for resolution of RLT, in the range 0-2 units, and that this may account for the lack of reproducibility in RLTs of stationary phase cells. It is hypothesised that stationary phase cells have enhanced resistance to osmotic stress and are able to exploit new growth environments at low a(w) more rapidly than exponential phase cells, resulting in shorter lag phases. However, the data indicate that turbidimetry may not accurately describe the lag phase response of exponential phase cells subjected to large osmotic shifts. Viable count data is required to investigate this hypothesis further.

Colony Count, Microbial↗
PubMed2003

The effect of abrupt osmotic shifts on the lag phase duration of foodborne bacteria.

The effects of osmotic environment and inoculum history on lag times were examined. Abrupt osmotic shifts of cultures were found to induce lag phases in a variety of foodborne bacteria. Relative lag times (RLT; the ratio of lag time to generation time) were used to differentiate the effects of the shift from those of the outgrowth environment. In general, osmotic downshifts induced larger RLTs than equivalent upshifts. An observed reduction in RLT at very low a(w), however, was unexpected. For an osmotic downshift, differences were observed in the RLT response of the Gram-negative and -positive strains tested. RLTs were usually extended for Gram-negative organisms as conditions became less favourable for growth. In comparison, RLT remained relatively unaffected for Gram-positive organisms. The observations reported in this study demonstrate that lag time can be understood in terms of the amount of work to be done to adjust to new environmental conditions and the rate at which that work is done, and are consistent with known strategies for osmoregulation employed by the various organisms studied.

Bacteria↗
PubMed2003

Modelling the effects of temperature, water activity, pH and lactic acid concentration on the growth rate of Escherichia coli.

An extended square root-type model describing Escherichia coli growth rate was developed as a function of temperature (7.63-47.43 degrees C), water activity (0.951-0.999, adjusted with NaCl), pH (4.02-8.28) and lactic acid concentration (0-500 mM). The new model, based on 236 growth rate data, combines and extends previously published square root-type models and incorporates terms for upper and lower limiting temperatures, upper and lower limiting pH, minimum inhibitory concentrations of dissociated and undissociated lactic acid and lower limiting water activity. A term to describe upper limiting water activity was developed but could not be fitted to the E. coli data set because of the difficulty of generating data in the super-optimal water activity range (i.e. >0.998). All data used to generate the model are presented. The model provides an excellent description of the experimental data.

Cell Division↗
PubMed2003

Performance evaluation of a model describing the effects of temperature, water activity, pH and lactic acid concentration on the growth of Escherichia coli.

A square root-type model for Escherichia coli growth in response to temperature, water activity, pH and lactic acid was developed by Ross et al. [Int. J. Food Microbiol. (2002).]. Predicted generation times from the model were compared to the literature data using bias and accuracy factors, graphical comparisons and plots of residuals for data obtained from both liquid growth media and foods. The model predicted well for 1025 growth rate estimates reported in the literature after poor quality or unrepresentative data (n=215) was excluded, with a bias factor of 0.92, and an accuracy factor of 1.29. In a detailed comparison to two other predictive modes for E. coli growth, Pathogen Modeling Program (PMP) and Food MicroModel (FMM), the new model generally performed better. The new model consistently gave better predictions than the other models at generation times </=5 h. Inclusion of the lactic acid term in the model is proposed to account for the consistently good performance of the model for comparisons to growth in meat, a parameter that is not explicitly included in the other models considered in the comparisons.

Cell Division↗
PubMed2002

Predictive microbiology: providing a knowledge-based framework for change management.

This contribution considers predictive microbiology in the context of the Food Micro 2002 theme, "Microbial adaptation to changing environments". To provide a reference point, the state of food microbiology knowledge in the mid-1970s is selected and from that time, the impact of social and demographic changes on microbial food safety is traced. A short chronology of the history of predictive microbiology provides context to discuss its relation to and interactions with hazard analysis critical control point (HACCP) and risk assessment. The need to take account of the implications of microbial adaptability and variable population responses is couched in terms of the dichotomy between classical versus quantal microbiology introduced by Bridson and Gould [Lett. Appl. Microbiol. 30 (2000) 95]. The role of population response patterns and models as guides to underlying physiological processes draws attention to the value of predictive models in development of novel methods of food preservation. It also draws attention to the paradox facing today's food industry that is required to balance the "clean, green" aspirations of consumers with the risk, to safety or shelf life, of removing traditional barriers to microbial development. This part of the discussion is dominated by consideration of models and responses that lead to stasis and inactivation of microbial populations. This highlights the consequence of change on predictive modelling where the need is now to develop interface and non-thermal death models to deal with pathogens that have low infective doses for general and/or susceptible populations in the context of minimal preservation treatments. The challenge is to demonstrate the validity of such models and to develop applications of benefit to the food industry and consumers as was achieved with growth models to predict shelf life and the hygienic equivalence of food processing operations.

Bacteria↗
PubMed2002

Predictive microbiology: towards the interface and beyond.

This review considers the concept and history of predictive microbiology and explores aspects of the modelling process including kinetic and probability modelling approaches. The "journey" traces the route from reproducible responses observed under close to optimal conditions for growth, through recognition and description of the increased variability in responses as conditions become progressively less favourable for growth, to defining combinations of factors at which growth ceases (the growth/no growth interface). Death kinetics patterns are presented which form a basis on which to begin the development of nonthermal death models. This will require incorporation of phenotypic, adaptive responses and may be influenced by factors such as the sequence in which environmental constraints are applied. A recurrent theme is that probability (stochastic) approaches are required to complement or replace kinetic models as the growth/no growth interface is approached and microorganisms adopt a survival rather than growth mode. Attention is also drawn to the interfaces of predictive microbiology with microbial physiology, information technology and food safety initiatives such as HACCP and risk assessment.

Bacteria↗
PubMed2001

Sterol and squalene content of a docosahexaenoic-acid-producing thraustochytrid: influence of culture age, temperature, and dissolved oxygen.

Thraustochytrid strain ACEM 6063, rich in omega-3 polyunsaturated fatty acids, was cultured at 15 degrees C and 20 degrees C in high (>40%) and low (<5%) dissolved oxygen (DO), and at 25 degrees C in low-DO media. Samples were taken 4, 2, and 0 days before each culture reached peak biomass (T(-4), T(-2), and T(p), respectively). Twenty sterols, 13 of which were identified, were detected. Predominant were cholest-5-en-3 beta-ol, 24-ethylcholesta-5,22E-dien-3 beta-ol, 24-methylcholesta-5,22E-dien-3 beta-ol, and 2 coeluting sterols, one of which was 24-ethylcholesta-5,7,22-trien-3 beta-ol. These 4 sterols comprised 50% to 90% of total sterols. Cultures grown at high DO had simpler sterol profiles than those grown at low DO. Only the 4 sterols mentioned above were present at more than 3% of total sterols in high-DO cultures. In low-DO cultures, up to 6 additional sterols were present at more than 3% of total sterols. Culture age, temperature, and DO influenced squalene and sterol content. Total sterols (as a proportion of total lipids) decreased with increasing culture age. If organisms such as ACEM 6063 are to be used for commercial production of lipid products for human consumption, both their sterol content and factors influencing sterol production need to be characterized thoroughly.

Journal Article↗
PubMed2001

Differentiation of the effects of lethal pH and water activity: food safety implications.

The influence of a second lethal stress (SLS) was investigated when populations of Escherichia coli M23 OR.H- were exposed to either a low water activity (aw) of 0.90 or a pH of 3.50 after 24 h at 25 degrees C. Regardless of the initial stress, E. coli M23 OR.H- populations initially demonstrated biphasic inactivation kinetics consisting of a rapid first phase of death followed by a slower second phase. When cultures initially exposed to aw 0.90 experienced an SLS of pH 3.50, a second rapid inactivation period was observed before a subpopulation of more resistant cells emerged. This subpopulation was able to persist for approximately 50 h after imposition of the SLS. In contrast, E. coli M23 OR.H- cells first exposed to a pH of 3.50 were inactivated rapidly to levels below the limits of detection upon imposition of an SLS of aw 0.90. It is hypothesized that pH stress constitutes a large energy drain on the cell and subsequently sensitizes it to other environmental constraints requiring expenditure of metabolic energy.

Acetates↗
PubMed2000

Evaluation of extraction methods for recovery of fatty acids from lipid-producing microheterotrophs.

The effect of different extraction techniques on the recovery of fatty acids from freeze-dried biomass of two lipid-producing microheterotrophs was examined. Two procedures were used: the extraction of lipids from biomass followed by transesterification of the fatty acids (extraction-transesterification); and the direct transesterification of biomass to produce fatty acid methyl esters (i.e. without the initial extraction step). Variable factors in the extraction-transesterification experiment were the sequence in which solvents were added to the samples, the relative amount of methanol in the solvent mix, and sonication of biomass while in the solvent mix. Variable factors in the direct transesterification experiment were sample size, and reaction duration. Statistical analysis of data (level of significance P<0.05) showed that: (1) extraction of total fatty acids prior to transesterification was significantly more efficient when solvents were added in the order of increasing polarity; (2) neither sonication nor increasing the proportion of methanol in the extraction solvent significantly affected extraction of fatty acids prior to transesterification; (3) efficiency of direct transesterification of fatty acids increased significantly with reaction time; (4) efficiency of direct transesterification of fatty acids was not significantly affected by sample size; (5) the most efficient method for extraction of fatty acids prior to transesterification yielded significantly less fatty acids than the most effective direct transesterification method. While the study examined only two strains, our results suggest that fatty acid analysis methodology for microheterotrophs under consideration for biotechnological exploitation requires optimisation and validation.

Biomass↗
PubMed2000

Modelling the combined temperature and salt (NaCl) limits for growth of a pathogenic Escherichia coli strain using nonlinear logistic regression.

A broth-based method is used to determine if exponential phase Escherichia coli R31, an STEC, is able to grow within 50 days under various combinations of sub-optimal temperatures and salt concentrations. From these data, the growth limits for combinations of temperature (7.7-37.0 degrees C) and water activity (0.943-0.987; NaCl as humectant) are defined and modelled using a nonlinear logistic regression model. That form of model is able to predict the combinations of salt concentration/water activity and temperature that will prevent the growth of E. coli R31 with selected levels of confidence. The model fitted the data with an approximate concordance rate of 97.3%. The minimum water activity that permitted growth occurred in the range 25-30 degrees C, the temperature range which optimises cell yield. At temperatures below this range the minimum water activity which allowed growth increased with decreasing temperature.

Culture Media↗
PubMed2000

Quantifying the hurdle concept by modelling the bacterial growth/no growth interface.

The hurdle concept described eloquently over many years by Professor Leistner and his colleagues draws attention to the interaction of factors that affect microbial behaviour in foods. Under some circumstances these effects are additive. Under others the implication is that synergistic interactions lead to a combined effect of greater magnitude than the sum of constraints applied individually. Predictive modelling studies on the combined effects of temperature and water activity and temperature and pH suggest that the effect of these combinations on growth rate is independent. Where the effect of the two factors is interactive rather than independent is at the point where growth ceases--the growth/no growth interface. An interesting and consistent observation is that a very sharp cut off occurs between conditions permitting growth and those preventing growth, allowing those combinations of factors to be defined precisely and modelled. Growth/no growth interface models quantify the effects of various hurdles on the probability of growth and define combinations at which the growth rate is zero or the lag time infinite. Increasing the stringency of one or more hurdles at the interface by only a small amount will significantly decrease the probability of an organism growing. Understanding physiological processes occurring near the growth/no growth interface and changes induced by moving from one side of the interface to the other may well provide insights that can be exploited in a new generation of food preservation techniques with minimal impact on product quality.

Bacteria↗
PubMed2000

The microbial composition of three limnologically disparate hypersaline Antarctic lakes.

16S rRNA clone library analysis was used to examine the biodiversity and community structure within the sediments of three hypersaline Antarctic lakes. Compared to sediment of low to moderate salinity Antarctic lakes the species richness of the hypersaline lake sediments was 2-20 times lower. The community of Deep Lake (32% salinity, average sediment temperature -15 degrees C) was made up almost entirely of halophilic Archaea. The sediment communities of two meromictic hypersaline lakes, Organic Lake (20% salinity, -7 degrees C) and Ekho Lake (15% salinity, 15 degrees C) were more complex, containing phylotypes clustering within the Proteobacteria and Cytophagales divisions and with algal chloroplasts. Many phylotypes of these lakes were related to taxa more adapted to marine-like salinity and perhaps derive from bacteria exported into the sediment from the lower salinity surface waters. The Ekho Lake clone library contained several major phylotypes related to the Haloanaerobiales, the growth of which appears to be promoted by the comparatively high in situ temperature of this lake.

Antarctic Regions↗
PubMed2000

Diversity and community structure within anoxic sediment from marine salinity meromictic lakes and a coastal meromictic marine basin, Vestfold Hilds, Eastern Antarctica.

16S rDNA clone library analysis was used to examine the biodiversity and community structure within anoxic sediments of several marine-type salinity meromictic lakes and a coastal marine basin located in the Vestfolds Hills area of Eastern Antarctica. From 69 to 130 (555 total) 16S rDNA clones were analysed from each sediment sample, and restriction fragment length polymorphism (RFLP) and sequence analysis grouped the clones into 202 distinct phylotypes (a clone group with sequence similarity of >0.98). A number of phylotypes and phylotype groups predominated in all libraries, with a group of 10 phylotypes (31% of clones) forming a novel deep branch within the low G+C Gram-positive division. Other abundant phylotypes detected in several different clone libraries grouped with Prochlorococcus cyanobacteria, diatom chloroplasts, delta proteobacteria (Desulfosarcina group, Syntrophus and Geobacterl Pelobacter/Desulphuromonas group), order Chlamydiales (Parachlamydiaceae) and Spirochaetales (wall-less Antarctic spirochaetes). Most archaeal clones detected (3.1% of clones) belonged to a highly diverged group of Euryarchaeota clustering with clones previously detected in rice soil, aquifer sediments and hydrothermal vent material. Little similarity existed between the phylotypes detected in this study and other clone libraries based on marine sediment, suggesting that an enormous prokaryotic diversity occurs within marine and marine-derived sediments.

Antarctic Regions↗