Analysis of the variability in the number of viable bacteria after mild heat treatment of food

Effects of Gamma-Ray Irradiation of Bacteria Colonies in Animal Feeds and on Growth and Gut Health of Weaning Piglets

Animal feeds contain a substantial number and diversity of microorganisms, and some of them have pathogenic potential. The objectives of this study were to investigate the effects of different doses of gamma (γ)-ray irradiation on the bacteria count in different types of feed and then to test the effect of γ-ray-irradiation-treated fishmeal on the gut health and growth performance of weaning piglets. In trial 1, three fishmeal samples, two feather meal samples, three meat meal samples, three soybean meal samples, and three vitamin complexes were treated with γ-ray irradiation doses of 0, 3, 6, or 9 kGy. The 6 and 9 kGy doses eliminated most of the bacteria in the feed but also resulted in a loss of vitamin C and B1. In trial 2, 96 weaning piglets were fed one of the following three diets with eight replicates (pens) per group over a 14-day period: (1) the control diet-the basal diet supplemented with 6% fishmeal with a low bacteria count (40 CFU/g) and no E. coli; (2) the fishmeal-contaminated diet (FM-contaminated) diet-the basal diet supplemented with 6% fishmeal with a high bacteria count (91,500 CFU/g) and E. coli contamination; and (3) the irradiated fishmeal (irradiated FM) diet-the basal diet supplemented with γ-ray-irradiation-treated E. coli-contaminated fishmeal. The piglets that received the FM-contaminated diet had significantly lower average daily gain and a greater diarrhea index compared to those fed the control diet, whereas γ-ray irradiation treatment abrogated the negative effect of the E. coli-contaminated fishmeal. Collectively, γ-ray irradiation at a dose of 6-9 kGy was sufficient to eliminate the microorganisms in the feed, thereby benefitting the growth performance and gut health of the weaning piglets.

Assessment on the efficacy of methods 2 to 5 and method 7 set out in Commission Regulation (EU) No 142/2011 to inactivate relevant pathogens when producing processed animal protein of porcine origin intended to feed poultry and aquaculture animals

An assessment was conducted on the level of inactivation of relevant pathogens that could be present in processed animal protein of porcine origin intended to feed poultry and aquaculture animals when methods 2 to 5 and method 7, as detailed in Regulation (EU) No 142/2011, are applied. Five approved scenarios were selected for method 7. Salmonella Senftenberg, Enterococcus faecalis, spores of Clostridium perfringens and parvoviruses were shortlisted as target indicators. Inactivation parameters for these indicators were extracted from extensive literature search and a recent EFSA scientific opinion. An adapted Bigelow model was fitted to retrieved data to estimate the probability that methods 2 to 5, in coincidental and consecutive modes, and the five scenarios of method 7 are able to achieve a 5 log10 and a 3 log10 reduction of bacterial indicators and parvoviruses, respectively. Spores of C. perfringens were the indicator with the lowest probability of achieving the target reduction by methods 2 to 5, in coincidental and consecutive mode, and by the five considered scenarios of method 7. An expert knowledge elicitation was conducted to estimate the certainty of achieving a 5 log10 reduction of spores of C. perfringens considering the results of the model and additional evidence. A 5 log10 reduction of C. perfringens spores was judged: 99-100% certain for methods 2 and 3 in coincidental mode; 98-100% certain for method 7 scenario 3; 80-99% certain for method 5 in coincidental mode; 66-100% certain for method 4 in coincidental mode and for method 7 scenarios 4 and 5; 25-75% certain for method 7 scenario 2; and 0-5% certain for method 7 scenario 1. Higher certainty is expected for methods 2 to 5 in consecutive mode compared to coincidental mode.

Inactivation of indicator microorganisms and biological hazards by standard and/or alternative processing methods in Category 2 and 3 animal by-products and derived products to be used as organic fertilisers and/or soil improvers

The European Commission requested EFSA to assess if different thermal processes achieve a 5 log10 reduction in Enterococcus faecalis or Salmonella Senftenberg (775W) and (if relevant) a 3 log10 reduction in thermoresistant viruses (e.g. Parvovirus) as well as if different chemical processes achieve a 3 log10 reduction of eggs of Ascaris sp., in eight groups of Category 2 and 3 derived products and animal by-products (ABP). These included (1) ash derived from incineration, co-incineration and combustion; (2) glycerine derived from the production of biodiesel and renewable fuels; (3) other materials derived from the production of biodiesel and renewable fuels; (4) hides and skins; (5) wool and hair; (6) feathers and down; (7) pig bristles; and (8) horns, horn products, hooves and hoof products. Data on the presence of viral hazards and on thermal and chemical inactivation of the targeted indicator microorganisms and biological hazards under relevant processing conditions were extracted via extensive literature searches. The evidence was assessed via expert knowledge elicitation. The certainty that the required log10 reductions in the most resistant indicator microorganisms or biological hazards will be achieved for each of the eight groups of materials mentioned above by the thermal and/or chemical processes was (1) 99-100% for the two processes assessed; (2) 98-100% in Category 2 ABP, at least 90-99% in Category 3 ABP; (3) 90-99% in Category 2 ABP; at least 66-90% in Category 3 ABP; (4) 10-66% and 33-66%; (5) 1-33% and 10-50%; (6) 66-90%; (7) 33-66% and 50-95%; (8) 66-95%, respectively. Data generation on the occurrence and reduction of biological hazards by thermal and/or chemical methods in these materials and on the characterisation of the usage pathways of ABP as organic fertilisers/soil improvers is recommended.

The COM-Poisson Process for Stochastic Modeling of Osmotic Inactivation Dynamics of Listeria monocytogenes

Controlling harmful microorganisms, such as Listeria monocytogenes, can require reliable inactivation steps, including those providing conditions (e.g., using high salt content) in which the pathogen could be progressively inactivated. Exposure to osmotic stress could result, however, in variation in the number of survivors, which needs to be carefully considered through appropriate dispersion measures for its impact on intervention practices. Variation in the experimental observations is due to uncertainty and biological variability in the microbial response. The Poisson distribution is suitable for modeling the variation of equi-dispersed count data when the naturally occurring randomness in bacterial numbers it is assumed. However, violation of equi-dispersion is quite often evident, leading to over-dispersion, i.e., non-randomness. This article proposes a statistical modeling approach for describing variation in osmotic inactivation of L. monocytogenes Scott A at different initial cell levels. The change of survivors over inactivation time was described as an exponential function in both the Poisson and in the Conway-Maxwell Poisson (COM-Poisson) processes, with the latter dealing with over-dispersion through a dispersion parameter. This parameter was modeled to describe the occurrence of non-randomness in the population distribution, even the one emerging with the osmotic treatment. The results revealed that the contribution of randomness to the total variance was dominant only on the lower-count survivors, while at higher counts the non-randomness contribution to the variance was shown to increase the total variance above the Poisson distribution. When the inactivation model was compared with random numbers generated in computer simulation, a good concordance between the experimental and the modeled data was obtained in the COM-Poisson process.

Bayesian Generalized Linear Model for Simulating Bacterial Inactivation/Growth Considering Variability and Uncertainty

Conventional regression analysis using the least-squares method has been applied to describe bacterial behavior logarithmically. However, only the normal distribution is used as the error distribution in the least-squares method, and the variability and uncertainty related to bacterial behavior are not considered. In this paper, we propose Bayesian statistical modeling based on a generalized linear model (GLM) that considers variability and uncertainty while fitting the model to colony count data. We investigated the inactivation kinetic data of Bacillus simplex with an initial cell count of 10⁵ and the growth kinetic data of Listeria monocytogenes with an initial cell count of 10⁴. The residual of the GLM was described using a Poisson distribution for the initial cell number and inactivation process and using a negative binomial distribution for the cell number variation during growth. The model parameters could be obtained considering the uncertainty by Bayesian inference. The Bayesian GLM successfully described the results of over 50 replications of bacterial inactivation with average of initial cell numbers of 10¹, 10², and 10³ and growth with average of initial cell numbers of 10^–1, 10⁰, and 10¹. The accuracy of the developed model revealed that more than 90% of the observed cell numbers except for growth with initial cell numbers of 10¹ were within the 95% prediction interval. In addition, parameter uncertainty could be expressed as an arbitrary probability distribution. The analysis procedures can be consistently applied to the simulation process through fitting. The Bayesian inference method based on the GLM clearly explains the variability and uncertainty in bacterial population behavior, which can serve as useful information for risk assessment related to food borne pathogens.

Multilevel modelling as a tool to include variability and uncertainty in quantitative microbiology and risk assessment. Thermal inactivation of Listeria monocytogenes as proof of concept

Variability is inherent in biology and also substantial for microbial populations. In the context of food safety risk assessment, it refers to differences in the response of different bacterial strains (between-strain variability) and different cells (within-strain variability) to the same condition (e.g. inactivation treatment). However, its quantification based on empirical observations and its incorporation in predictive models is a challenge for both experimental design and (statistical) analysis. In this article we propose the use of multilevel models to quantify (different levels of) variability and uncertainty and include them in the predictions. As proof of concept, we analyse the microbial inactivation of Listeria monocytogenes to thermal treatments including different levels of variability (between-strain and within-strain) and uncertainty. The relationship between the microbial count and time was expressed using a (non-linear) Weibullian model. Moreover, we defined stochastic hypotheses to describe the different types of variation at the level of the kinetic parameters, as well as in the observations (microbial counts). The model parameters (kinetic parameters and variances) are estimated using Bayesian statistics. The multilevel approach was compared against an analogous, single-level model. The multilevel methodology shrinks extreme parameter estimates towards the mean according to uncertainty, thus mitigating overfitting. In addition, this approach enables to easily incorporate different levels of variation (between-strain and/or within-strain variability and/or uncertainty) in the predictions. On the other hand, multilevel (Bayesian) models are more complex to define, implement, analyse and communicate than single-level models. Nevertheless, their ability to incorporate different sources of variability in predictions make them very suitable for Quantitative Microbial Risk Assessment.

Flow Cytometry to Assess the Counts and Physiological State of Cronobacter sakazakii Cells after Heat Exposure

Cronobacter sakazakii is an opportunistic pathogen that is associated with outbreaks of neonatal necrotizing enterocolitis, septicaemia, and meningitis. Reconstituted powdered infant formulae is the most common vehicle of infection. The aim of the present study is to gain insight into the physiological states of C. sakazakii cells using flow cytometry to detect the compromised cells, which are viable but non-culturable using plate-based methods, and to evaluate the impact of milk heat treatments on those populations. Dead-cell suspensions as well as heat-treated and non-heat-treated cell suspensions were used. After 60 or 65 °C treatments, the number of compromised cells increased as a result of cells with compromised membranes shifting from the heat-treated suspension. These temperatures were not effective at killing all bacteria but were effective at compromising their membranes. Thus, mild heat treatments are not enough to guarantee the safety of powered infant formulae. Flow cytometry was capable of detecting C. sakazakii’s compromised cells that cannot be detected with classical plate count methods; thus, it could be used as a screening test to decrease the risk derived from the presence of pathogenic viable but non-culturable cells in this food that is intended for newborns’ nutrition.

Antibacterial effect of copper sulfate against multi-drug resistant nosocomial pathogens isolated from clinical samples

Background and Objective:

With the emergence of antibiotic resistance and the hospital acquired infection, the interest for antimicrobial agents has recently increased again in public health. Copper is recommended as a supplementary method of increasing biological safety in the hospital environment. The objective of this study was to determine the antibacterial activity of copper sulfate salts on strains of bacterial pathogens isolated from different clinical pictures in different health establishment in Algeria.

Methods:

A total of 25 different bacterial isolates (16 Enterobacteriaceae, 5 Staphylococci, and 4 Pseudomonas) were tested for susceptibility to copper sulfate using minimum inhibitory concentration (MIC-Cu) and minimum bactericidal concentrations (MBC-Cu) determinations. All isolates were also tested for susceptibility to six antibiotics.

Results:

Antibiotic susceptibility studies revealed that 100% of isolates were resistant to one or more antibiotics. Fifty two percent of isolates were very susceptible to copper sulfate, with MICs ranging from 100 to 200 µg/ml. MBC-Cu = 1600 μg/ml showed the best bactericidal effect against the great majority of studied bacteria (52%). A good bactericidal activities of copper sulfate were recorded against Proteus vulgaris and Staphylococcus aureus (MBC/MIC=1). The Gram-negative bacteria isolates which were copper resistant also showed a high resistance to chloramphenicol (r=0.78) and Trimethoprime (r=0.61). Furthermore, the strains that were no-susceptible to three different antimicrobial classes (Escherichia coli, Staphylococcus saprophyticus) were not resistant to copper sulfate.

Conclusion:

Copper sulfate salts has significant antibacterial activity against multi-drug resistant nosocomial pathogens.

Determining the Age of Spoiled Milk from Dried Films Using Attenuated Reflection Fourier Transform Infrared (ATR FT-IR) Spectroscopy

Milk spoilage is an inevitable occurrence, which generates waste and can result in food poisoning. When milk spoils, the off-flavor and curdling are due to excessive proliferation of various bacteria which causes pH changes. Time, temperature, environment, and previous handling practice all affect the spoilage rate. There is a need for a fast reliable and accurate method that can identify in situ early spoilage of milk. Here we show the ability of attenuated total reflection Fourier transformed infrared spectroscopy (ATR FT-IR) in conjunction with multivariate data analysis to predict the age of milk. We found that dried films vastly increased the absorbance of important biomolecules within milk such as lipids, proteins, and sugars, compared to an unchanged milk sample. This allowed us to note the minor discrepancies that happened in spoilage. Spoilt milk was characterized by bands associated with increased lipids, proteins, and lactic acid and a decrease in carbohydrates. A semi-quantitative prediction model for milk spoilage at room temperature demonstrated ATR FT-IR spectroscopy can predict milk age with a root mean square error of prediction of approximately 14 h. The model showed poor performance in the first 40 h but the predictions improved significantly after this time. The experimental procedure proposed for detecting biomolecules within milk has the potential to improve common practice. Furthermore, the model would be a starting point for newer and improved methods to predict the spoilage date of milk, with potential commercial uses to reduce food waste and costs to the milk industry.

Stochastic modeling of variability in survival behavior of Bacillus simplex spore population during isothermal inactivation at the single cell level using a Monte Carlo simulation

The control of bacterial reduction is important to maintain food safety during thermal processing. The goal of this study was to illustrate and describe variability in bacterial population behavior during thermal processing as a probability distribution based on individual cell heterogeneity regarding heat resistance. Toward this end, we performed a Monte Carlo simulation via computer, and compared and validated the simulated estimations with observed values. Weibullian fitted parameters were estimated from the kinetic survival data of Bacillus simplex during thermal treatment at 94 °C. The variability in reductions of bacterial sporular populations was illustrated using Monte Carlo simulation based on the Weibull distribution of the parameters. In particular, variabilities in viable spore counts and survival probability of the B. simplex spore population were simulated in various replicates. We also experimentally determined the changes in survival probability and distributions of survival spore counts; notably, these were successfully predicted by the Monte Carlo simulation based on the kinetic parameters. The kinetic parameter-based Monte Carlo simulation could thus successfully illustrate bacterial population behavior variability during thermal processing as a probability distribution. The simulation approach may contribute to improving food quality through risk-based processing designs and enhance risk assessment model accuracy.

Tail or artefact? Illustration of the impact that uncertainty of the serial dilution and cell enumeration methods has on microbial inactivation

The estimation of the concentration of microorganisms in a sample is crucial for food microbiology. For instance, it is essential for prevalence studies, challenge tests (growth and/or inactivation studies) or microbial risk assessment. The application of serial dilutions followed by viable counts in Petri dishes is probably the most extended experimental methodology for this purpose. However, this enumeration technique is also a source of uncertainty. In this article, the uncertainty of the serial dilution and viable count methodology related to the sampling error is analyzed, as well as the approximation of the microbial concentration by the number of colonies in a Petri dish. We analyze from a theoretical point of view (statistical analysis) the application of the binomial and Poisson models, demonstrating that the Poisson distribution increases the variance when used to model individual serial dilutions. On the other hand, the binomial model produces unbiased results. Therefore, the Poisson distribution is only applicable when it is a good approximation of the binomial distribution, so the use of the latter is recommended. The relevance of this uncertainty is demonstrated by Monte Carlo simulations of a generic microbial inactivation experiment, where the only source of uncertainty/variability considered is the one generated by serial plating and viable cell enumeration. Due to both the uncertainty of the methodology and the omission of zero-count plates because of the log-transformation, the simulated survival curve can have a tail. Therefore, this phenomenon, which is usually attributed to biological variability, can be to some extent an artefact of the experimental design and/or methodology.

Stochastic simulation for death probability of bacterial population considering variability in individual cell inactivation time and initial number of cells

Decimal reduction time (D-value) based on the first-order survival kinetics model is not sufficient for reliable estimation of the bacterial survivors of inactivation treatment because the model does not consider inactivation curvature. However, even though doubt exists in the calculation of D-value, it is still widely used for risk assessment and sterilisation time estimation. This paper proposes an approach for estimating the time-to-inactivation and death probability of bacterial population that considers individual cell heterogeneity and initial number of cells via computer simulation. In the proposed approach, Weibull and Poisson distributions are respectively used to provide individual cell inactivation time variability and initial number of cells variability. Our simulation results show that the time-to-inactivation significantly depends on kinetics curvature and initial number of cells. For example, with increases in the initial number of cells, the respective variance of the time-to-inactivation of log-linear, concave downward curve, and concave upward curve remains constant, decreases, and increases, respectively. The death probability contour plot was successfully generated via our computer simulation approach without using D-value estimation. Further, the death probability calculated using our stochastic approach was virtually the same as that obtained using inactivation kinetics. We validated the simulation by using literature data for acid inactivation of Salmonella population. The results of this study indicate that inactivation curvature can replace D-value extrapolation to estimate the death probability of bacterial population. Further, our computer simulation facilitates realistic estimation of the time-to-inactivation of bacterial population. The R code used for the above stochastic calculation is outlined.

Performance of a Heating Block System Designed for Studying the Heat Resistance of Bacteria in Foods

Knowledge of bacteria's heat resistance is essential for developing effective thermal treatments. Choosing an appropriate test method is important to accurately determine bacteria's heat resistances. Although being a major factor to influence the thermo-tolerance of bacteria, the heating rate in samples cannot be controlled in water or oil bath methods due to main dependence on sample's thermal properties. A heating block system (HBS) was designed to regulate the heating rates in liquid, semi-solid and solid foods using a temperature controller. Distilled water, apple juice, mashed potato, almond powder and beef were selected to evaluate the HBS's performance by experiment and computer simulation. The results showed that the heating rates of 1, 5 and 10 °C/min with final set-point temperatures and holding times could be easily and precisely achieved in five selected food materials. A good agreement in sample central temperature profiles was obtained under various heating rates between experiment and simulation. The experimental and simulated results showed that the HBS could provide a sufficiently uniform heating environment in food samples. The effect of heating rate on bacterial thermal resistance was evaluated with the HBS. The system may hold potential applications for rapid and accurate assessments of bacteria's thermo-tolerances.

Antibacterial Effect of Copper on Microorganisms Isolated from Bovine Mastitis

The antimicrobial properties of copper have been recognized for several years; applying these properties to the prevention of diseases such as bovine mastitis is a new area of research. The aim of the present study was to evaluate in vitro the antimicrobial activity of copper on bacteria isolated from subclinical and clinical mastitis milk samples from two regions in Chile. A total of 327 microorganisms were recovered between March and September 2013, with different prevalence by sample origin (25 and 75% from the central and southern regions of Chile, respectively). In the central region, Escherichia coli and coagulase negative Staphylococci (CNS) were the most frequently detected in clinical mastitis cases (33%), while in the southern region S. uberis, S. aureus, and CNS were detected with frequencies of 22, 21, and 18%, respectively. Antibiotic susceptibility studies revealed that 34% of isolates were resistant to one or more antibiotics and the resistance profile was different between bacterial species and origins of isolation of the bacteria. The minimum inhibitory concentration of copper (MIC-Cu) was evaluated in all the isolates; results revealed that a concentration as low as 250 ppm copper was able to inhibit the great majority of microorganisms analyzed (65% of isolates). The remaining isolates showed a MIC-Cu between 375 and 700 ppm copper, and no growth was observed at 1000 ppm. A linear relationship was found between the logarithm of viable bacteria number and time of contact with copper. With the application of the same concentration of copper (250 ppm), CNS showed the highest tolerance to copper, followed by S. uberis and S. aureus; the least resistant was E. coli. Based on these in vitro results, copper preparations could represent a good alternative to dipping solutions, aimed at preventing the presence and multiplication of potentially pathogenic microorganisms involved in bovine mastitis disease.

Variability in Cell Response of Cronobacter sakazakii after Mild-Heat Treatments and Its Impact on Food Safety

Cronobacter spp. have been responsible for severe infections in infants associated with consumption of powdered infant formula and follow-up formulae. Despite several risk assessments described in published studies, few approaches have considered the tremendous variability in cell response that small micropopulations or single cells can have in infant formula during storage, preparation or post process/preparation before the feeding of infants. Stochastic approaches can better describe microbial single cell response than deterministic models as we prove in this study. A large variability of lag phase was observed in single cell and micropopulations of ≤50 cells. This variability increased as the heat shock increased and growth temperature decreased. Obviously, variability of growth of individual Cronobacter sakazakii cell is affected by inoculum size, growth temperature and the probability of cells able to grow at the conditions imposed by the experimental conditions should be taken into account, especially when errors in bottle-preparation practices, such as improper holding temperatures, or manipulation, may lead to growth of the pathogen to a critical cell level. The mean probability of illness from initial inoculum size of 1 cell was below 0.2 in all the cases and for inoculum size of 50 cells the mean probability of illness, in most of the cases, was above 0.7.

Effects of Modified Atmosphere Packaging, Food Life Extenders and Temperature on the Shelf Life of Ready-Made Dishes

The combined effect of several microbial control factors including gas barrier of containers, modified atmosphere packaging, food life extenders and storage temperature was discussed in order to determine the possibility for improving the shelf life for hamburger steak and deepfried chicken, representative ready-made dishes sold at convenience stores in Japan. Multiple measures including cold storage were effective in improving the shelf life of ready-made dishes. It was also suggested that storage tests for ready-made dishes should be conducted at 10℃, a practical temperature, to confirm the storable period, as well as at 15℃, an adequate abuse temperature, to confirm the effects of various microbial control factors. In the present study, the test group 4 (nitrogen + barrier containers + pH modifier) performed most favorably at both temperatures, indicating the efficacy of multiple means including "cold storage" in improving the shelf life (extending the consume-by date) of ready-made dishes. All strains isolated from the tested hamburger steak and deep-fried chicken were common food contaminant bacterial species.

Towards lag phase of microbial populations at growth-limiting conditions: The role of the variability in the growth limits of individual cells

The water activity (aw) growth limits of unheated and heat stressed Listeria monocytogenes individual cells were studied. The aw limits varied from 0.940 to 0.997 and 0.951 to 0.997 for unheated and heat stressed cells, respectively. Due to the above variability a decrease in aw results in the presence of a non-growing fraction in the population leading to an additional pseudo-lag in population growth. In this case the total apparent lag of the population is the sum of the physiological lag of the growing cells (time required to adjust to the new environment) and the pseudo-lag. To investigate the effect of aw on the above lag components, the growth kinetics of L. monocytogenes on tryptone soy agar with aw adjusted to values ranging from 0.997 to 0.940 was monitored. The model of B&R was fitted to the data for the estimation of the apparent lag. In order to estimate the physiological lag of the growing fraction of the inoculum, the model was refitted to the growth data using as initial population level the number of cells that were able to grow (estimated from the number of colonies formed on the agar at the end of storage) and excluding the rest data during the lag. The results showed that for the unheated cells the apparent lag was almost identical to the physiological lag for aw values ranging from 0.997 to 0.970, as the majority of the cells in the initial population was able to grow in these conditions. As the aw decreased from 0.970 to 0.940 however, the number of cells in the population which were able to grow, decreased resulting to an increase in the pseudo-lag. The maximum value of pseudo-lag was 13.1h and it was observed at aw=0.940 where 10% of the total inoculated cells were able to grow. For heat stressed populations a pseudo-lag started to increase at higher aw conditions (0.982) compared to unheated cells. In contrast to the apparent lag, a linear relation between physiological lag and aw was observed for both unheated and heat stressed cells.

Heat fixation inactivates viral and bacterial pathogens and is compatible with downstream MALDI mass spectrometry tissue imaging

BACKGROUND

Tissue samples should be fixed and permanently stabilized as soon as possible ex-vivo to avoid variations in proteomic content. Tissues collected from studies involving infectious microorganisms, must face the additional challenge of pathogen inactivation before downstream proteomic analysis can be safely performed. Heat fixation using the Denator Stabilizor System (Gothenburg, Sweden) utilizes conductive heating, under a mild vacuum, to rapidly eliminate enzymatic degradation in tissue samples. Although many studies have reported on the ability of this method to stop proteolytic degradation and other sample changes immediately and permanently, pathogen inactivation has not been studied.

RESULTS

We examined the ability of the heat fixation workflow to inactivate bacterial and viral pathogens and the suitability of this tissue for Matrix Assisted Laser Desorption Ionization mass spectrometry imaging (MALDI-MSI). Mice were infected with viral or bacterial pathogens representing two strains of Venezuelan Equine Encephalitis virus (VEEV) and two strains of Burkholderia. Additionally, a tissue mimetic model was employed using Escherichia, Klebsiella and Acinetobacter isolates. Infected tissue samples harvested from each animal or mimetic model were sectioned in half. One half was heat fixed and the other remained untreated. Lysates from each sample were checked for organism viability by performing plaque (infectivity) assays or plating on nutrient agar for colony forming unit (CFU) calculation. Untreated infected control tissue demonstrated the presence of each viable pathogen by positive plaque or colony formation, whereas heat fixation resulted in complete inactivation of both the viral and bacterial pathogens. MALDI-MSI images produced from heat fixed tissue were reflective of molecular distributions within brain, spleen and lung tissue structures.

CONCLUSIONS

We conclude that heat fixation inactivates viral and bacterial pathogens and is compatible with proteomic analysis by MALDI-MSI. This treatment will enable the use of infected tissue from studies performed in bio-safety level 3 laboratories with VEEV and Burkholderia to be safely used for proteomic, small molecule drug detection, and imaging mass spectrometry analysis.

Survival of Salmonella on chamomile, peppermint, and green tea during storage and subsequent survival or growth following tea brewing

The survival of Salmonella on dried chamomile flowers, peppermint leaves, and green tea leaves stored under different conditions was examined. Survival and growth of Salmonella was also assessed after subsequent brewing using dried inoculated teas. A Salmonella enterica serovar cocktail was inoculated onto different dried tea leaves or flowers to give starting populations of approximately 10 log CFU/g. The inoculum was allowed to dry (at ambient temperature for 24 h) onto the dried leaves or flowers prior to storage under 25 and 35 °C at low (<30% relative humidity [RH]) and high (>90% RH) humidity levels. Under the four storage conditions tested, survival followed the order 25 °C with low RH > 35 °C with low RH > 25 °C with high RH > 35 °C with high RH. Salmonella losses at 25 °C with low RH occurred primarily during drying, after which populations showed little decline over 6 months. In contrast, Salmonella decreased below detection after 45 days at 35 °C and high RH in all teas tested. The thermal resistance of Salmonella was assessed at 55 °C immediately after inoculation of tea leaves or flowers, after drying (24 h) onto tea leaves or flowers, and after 28 days of storage at 25 °C with low RH. All conditions resulted in similar D-values (2.78 ± 0.12, 3.04 ± 0.07, and 2.78 ± 0.56, at 0 h, 24 h, and 28 days, respectively), indicating thermal resistance of Salmonella in brewed tea did not change after desiccation and 28 days of storage. In addition, all brewed teas tested supported the growth of Salmonella. If Salmonella survives after storage, it may also survive and grow after a home brewing process.

Isolation of highly heat-resistant Listeria monocytogenes variants by use of a kinetic modeling-based sampling scheme

Stable high-hydrostatic-pressure (HHP)-resistant Listeria monocytogenes LO28 variants were previously isolated and characterized. These HHP variants were also more resistant to heat. In addition, nonlinear heat inactivation kinetics pointed toward the existence of heat-resistant variants, although these could not be isolated so far. In this study, we used kinetic modeling of inactivation curves of two isolated HHP variants and their wild type, and this revealed that the probability of finding resistant variants should depend on the nature of the inactivation treatment and the time of exposure. At specific heat and HHP conditions, resistant LO28 and EGDe variants were indeed isolated. Resistant LO28 variants were even isolated after a heat inactivation at 72°C in milk, and these variants showed high resistance to standard pasteurization conditions. The increased resistance of part of the isolated LO28 and EGDe variants was due to mutations in their ctsR genes. For the variants whose ctsR genes and upstream regions were not altered, the mechanisms leading to increased resistance remain to be elucidated. This research showed the strength of kinetic modeling in unraveling the causes of nonlinear inactivation and facilitating the isolation of heat-resistant L. monocytogenes variants.