Calculation of the Non-Isothermal Inactivation Patterns of Microbes Having Sigmoidal Isothermal Semi-Logarithmic Survival Curves

Persistence of poliovirus types 2 and 3 in waste-impacted water and sediment

Eradication of poliovirus (PV) is a global public health priority, and as clinical cases decrease, the role of environmental surveillance becomes more important. Persistence of PV and the environmental factors that influence it (such as temperature and sample type) are an important part of understanding and interpreting positive environmental surveillance samples. The objective of this study was to evaluate the persistence of poliovirus type 2 (PV2) and type 3 (PV3) in wastewater and sediment. Microcosms containing either 1) influent wastewater or 2) influent wastewater with a sediment matrix were seeded with either PV2 or PV3, and stored for up to 126 days at three temperatures (4°C, room temperature [RT], and 30°C). Active PV in the liquid of (1), and the sediment and liquid portions of (2) were sampled and quantified at up to 10 time points via plaque assay and RT-qPCR. A suite of 17 models were tested for best fit to characterize decay of PV2 and PV3 over time and determine the time points at which >90% (T90) and >99% (T99) reduction was reached. Linear models assessed the influence of experimental factors (matrix, temperature, virus type and method of detection) on the predicted T90 and T99 values. Results showed that when T90 was the dependent variable, virus type, matrix, and temperature significantly affected decay, and there was a clear interaction between the sediment matrix and temperature. When T99 was the dependent variable, only temperature and matrix type significantly influenced the decay metric. This study characterizes the persistence of both active and molecular PV2 and PV3 in relevant environmental conditions, and demonstrates that temperature and sediment both play important roles in PV viability. As eradication nears and clinical cases decrease, environmental surveillance and knowledge of PV persistence will play a key role in understanding the silent circulation in endemic countries.

Modeling the persistence of viruses in untreated groundwater

Several factors can affect virus behavior and persistence in water sources. Historically linear models have been used to describe persistence over time; however, these models do not consider all of the factors that can affect inactivation kinetics or the observed patterns of decay. Meanwhile, applying the appropriate persistence model is critical for ensuring that decision makers are minimizing human health risk in the event of contamination and exposure to contaminated groundwater. Therefore, to address uncertainty in predictions of decay or virus concentrations over time, this study fit seventeen different linear and nonlinear mathematical models to persistence data from a previously conducted sampling study on drinking water wells throughout the United States. The models were fit using Maximum Likelihood Estimation and the best fitting models were determined by the Bayesian Information Criterion. The purpose of the study was to identify the best model for estimating decay of viruses in groundwater and to determine if model uncertainty contributes to erroneous predictions of viral contamination when only conventional models are considered. For the datasets analyzed in this study, the Juneja and Marks models and the exponential damped model were more representative of the persistence of viruses in groundwater than the traditionally used linear models. The results from this study were then evaluated with classification trees in order to identify more relevant modeling methodology for future research. The classification trees aid in narrowing the scope of appropriate persistence models based on characteristics of the experimental conditions and water sampled.

Modelling the survival of Listeria monocytogenes strains in soft lactic cheese following acid and salt stress exposures

This study evaluated the survival responses of Listeria monocytogenes strains (individually and mixed) in a soft lactic cheese following acid and salt stress exposures. The Weibull and log-linear with tail models were used to predict the survival responses of the pathogen in the cheese stored at 4°C for 15 days. Both models showed a good prediction accuracy for stressed L. monocytogenes cells (Af = 1·00) and higher prediction errors (Af = 1·12-1·14) for nonstressed cells. The inactivation rates (δ (d) and k_max (d^-1 )) were significantly lower (P < 0·05) for cells subjected to stress exposure indicating the enhanced tolerance to food stress. However, while enhanced tolerance appeared to be the main effect of stress pre-exposure, in one susceptible strain (69), stress exposure led to higher rates of inactivation. When introduced into the food as mixed strains, one strain out-lived others and remained as the sole survivor. Such strains that perhaps have a predilection for the food environment can provide more cautious estimates of kinetic parameters for predicting L. monocytogenes responses in foods especially if their stress-hardened tolerant cells are used. SIGNIFICANCE AND IMPACT OF THE STUDY: The ability to predict the growth and survival of Listeria monocytogenes in contaminated RTE foods is essential for listeriosis risk assessment. The results of this study provided valuable information on the kinetic parameters of survival of some L. monocytogenes strains found within the South African food environment. In addition to showing differences in the survival responses among strains, the study also showed the importance of the pre-contamination state of the cells in influencing survival kinetics.

Enzymatic origin and various curvatures of metabolic scaling in microbes

The famous and controversial power law is a basal metabolic scaling model mainly derived from the “surface rule” or a fractal transport network. However, this law neglects biological mechanisms in the important active state. Here, we hypothesized that the relative metabolic rate and growth rate of actively growing microbes are driven by the changeable rate of their rate-limiting enzymes and concluded that natural logarithmic microbial metabolism (lnλ) and growth (or biomass) (lnM) are both dependent on limiting resources, and then developed novel models with interdependence between lnλ and lnM. We tested the models using the data obtained from the literature. We explain how and why the scaling is usually curved with the difference between microbial metabolic and growth (or biomass’s) half-saturation constants (K_M, K_λ) in the active state and agree that the linear relationship of the power law is a particular case under the given condition: K_M = K_λ, which means that the enzyme dynamics may drive active and basal metabolic scaling relationships. Our interdependent model is more general than the power law, which is important for integrating the ecology and biochemical processes.

Modeling the inactivation of Salmonella Typhimurium, Listeria monocytogenes, and Salmonella Enteritidis on poultry products exposed to pulsed UV light

Pulsed UV light inactivation of Salmonella Typhimurium on unpackaged and vacuum-packaged chicken breast, Listeria monocytogenes on unpackaged and vacuum-packaged chicken frankfurters, and Salmonella Enteritidis on shell eggs was explained by log-linear and Weibull models using inactivation data from previous studies. This study demonstrated that the survival curves of Salmonella Typhimurium and L. monocytogenes were nonlinear exhibiting concavity. The Weibull model was more successful than the log-linear model in estimating the inactivations for all poultry products evaluated, except for Salmonella Enteritidis on shell eggs, for which the survival curve was sigmoidal rather than concave, and the use of the Weibull model resulted in slightly better fit than the log-linear model. The analyses for the goodness of fit and performance of the Weibull model produced root mean square errors of 0.059 to 0.824, percent root mean square errors of 3.105 to 21.182, determination coefficients of 0.747 to 0.989, slopes of 0.842 to 1.042, bias factor values of 0.505 to 1.309, and accuracy factor values of 1.263 to 6.874. Overall, this study suggests that the survival curves of pathogens on poultry products exposed to pulsed UV light are nonlinear and that the Weibull model may generally be a useful tool to describe the inactivation patterns for pathogenic microorganisms affiliated with poultry products.

Influence of pH, type of acid and recovery media on the thermal inactivation of Listeria innocua

Acidification of foods with organic acids, either by fermentation or by intentional addition, is an important and common mechanism for controlling foodborne pathogens in a diversity of food products. The objective of this work was to study thermal inactivation of Listeria innocua, an acid tolerant microorganism, at 52.5, 60.0 and 65.0 degrees C, at different pH values (4.5, 6.0 and 7.5), using three types of acid (lactic, acetic and hydrochloric) and three different plating media (Tryptic Soy Agar with 0.6% yeast extract-TSAYE; TSAYE plus 5% NaCl-TSAYE+5%NaCl; and Palcam Agar with selective supplement-Palcam Agar), according to a 3(4) factorial experimental design. Survival data experimentally obtained were fitted with a Gompertz-inspired model and kinetic parameters (shoulder, maximum inactivation rate-k(max), and tail) were estimated for all conditions considered. The influence of temperature, pH, type of acid and enumeration media on kinetic parameters was assessed. Results showed that, with the exception of the type of acid, all the remaining factors and their combinations significantly affected the shoulder period and k(max). In relation to tail, temperature and recovery media were the affectable factors. It was concluded that the survival of this bacteria is higher when combining low temperature with neutral pH, and when TSAYE is the enumeration medium. Bigelow-inspired models were successfully developed and describe accurately the temperature and pH effects on the kinetic parameters.

Thermal inactivation kinetics of Lactococcus lactis subsp. lactis bacteriophage pll98-22

Survival curves of Lactococcus lactis subsp. lactis bacteriophage pll98 inactivated by heat were obtained at seven temperature values (50-80 degrees C) in M17 broth and skim milk. Deviations from first-order kinetics in both media were observed as sigmoidal shapes in the survival curves of pll98. An empirical model with four parameters was used to define the thermal inactivation. Number of parameters of the model was reduced from four to two in order to increase the robustness of the model. The reduced model produced comparable fits to the full model. Both the survival data and the calculations done using the reduced model (time necessary to reduce the number of phage pll98 six- or seven- log10) indicated that skim milk is a more protective medium than M17 broth within the assayed temperature range.

Linear and non-linear kinetics in the synthesis and degradation of acrylamide in foods and model systems

Isothermal acrylamide formation in foods and asparagine-glucose model systems has ubiquitous features. On a time scale of about 60 min, at temperatures in the approximate range of 120-160 degrees C, the acrylamide concentration-time curve has a characteristic sigmoid shape whose asymptotic level and steepness increases with temperature while the time that corresponds to the inflection point decreases. In the approximate range of 160-200 degrees C, the curve has a clear peak, whose onset, height, width and degree of asymmetry depend on the system's composition and temperature. The synthesis-degradation of acrylamide in model systems has been recently described by traditional kinetic models. They account for the intermediate stages of the process and the fate of reactants involved at different levels of scrutiny. The resulting models have 2-6 rate constants, accounting for both the generation and elimination of the acrylamide. Their temperature dependence has been assumed to obey the Arrhenius equation, i.e., each step in the reaction was considered as having a fixed energy of activation. A proposed alternative is constructing the concentration curve by superimposing a Fermian decay term on a logistic growth function. The resulting model, which is not unique, has five parameters: a hypothetical uninterrupted generation-level, two steepness parameters; of the concentration climbs and fall and two time characteristics; of the acrylamide synthesis and elimination. According to this model, peak concentration is observed only when the two time constants are comparable. The peak's shape and height are determined by the gap between the two time constants and the relative magnitudes of the two "rate" parameters. The concept can be extended to create models of non-isothermal acrylamide formation. The basic assumption, which is yet to be verified experimentally, is that the momentary rate of the acrylamide synthesis or degradation is the isothermal rate at the momentary temperature, at a time that corresponds to its momentary concentration. The theoretical capabilities of a model of this kind are demonstrated with computer simulations. If the described model is correct, then by controlling temperature history, it is possible to reduce the acrylamide while still accomplishing much of the desirable effects of a heat process.

Calculating microbial survival parameters and predicting survival curves from non-isothermal inactivation data

Irrespective of whether the isothermal semi-logarithmic survival curves of heat inactivated microbial cells or spores are linear or nonlinear, it is theoretically possible to numerically calculate their survival parameters from inactivation data obtained under non-isothermal conditions. A method to do the calculation, when the temperature history ('profile') is expressed algebraically, is demonstrated with simulated survival curves. It has been tested with the published survival data of Salmonella, whose nonlinear semi-logarithmic isothermal survival curves can be described by a power law model. The reported survival ratios of Salmonella, determined during non-isothermal heat treatments in a broth and in ground chicken breast, were used to estimate its isothermal survival parameters in the two media and their temperature dependence. These, in turn, were used to predict the cells' survival curves under different temperature 'profiles.' There was a good agreement between the predicted and the reported experimental survival curves in the broth case and reasonable agreement in the ground chicken breasts, where the database was considerably smaller The development of a mathematical method to calculate survival parameters from non-isothermal inactivation data will eliminate the need to determine these parameters under isothermal conditions, which can only be approximated and are technically difficult to perform. In many cases, the proposed method will also enable the determination of the survival parameters in the actual food or medium of interest, which may contain particles, or is too viscous to be heated and cooled effectively using the currently available experimental procedures. In principle, the described mathematical method can also be used to assess organisms' survival parameters in nonthermal inactivation processes, such as exposure to a dissipating chemical agent or the application of ultra high-pressure.

Generating microbial survival curves during thermal processing in real time

AIMS

To develop a method to calculate and record theoretical microbial survival curves during thermal processing of foods and pharmaceutical products simultaneously with the changing temperature. Moreover, to demonstrate that the method can be used to calculate nonisothermal survival curves, with widely available software such as Microsoft Excel.

METHODS AND RESULTS

It has been assumed that the targeted organism's isothermal survival curves are not log linear and hence, the inactivation rate in nonisothermal processes is a function of the momentary temperature and the corresponding survival ratio. This could be expressed by a difference equation, which is an approximation to the continuous rate model. The concept was tested with the isothermal survival parameters of Clostridium botulinum and Bacillus sporothermodurans spores, and Salmonella enteritidis cells, using different kinds of survival models and under temperature profiles resembling those of commercial processes. As expected, there was an excellent agreement between the curves produced by solving the differential equation of the continuous model and by the incremental method, which has been posted on the web as freeware.

CONCLUSIONS

It is possible to calculate nonisothermal survival curves, in real time, with an algorithm that can be written in the language of general purpose software, to follow the inactivation of one or more targeted organisms simultaneously and to simulate microbial survival patterns under existing or planned industrial thermal processes.

SIGNIFICANCE AND IMPACT OF THE STUDY

Replacement of the traditional 'F0-value', which requires the log linearity of the organism's isothermal survival curves, by the more realistic theoretical survival ratio estimate as a measure of the thermal process efficacy.