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This study evaluated the effect of both gaseous and dissolved oxygen (O 2 ) concentration (0 - 21%) on the growth of six heat-resistant moulds (HRMs) (Neosartorya and Byssochlamys spp.) previously isolated from high-acid fruit products. The study was performed in acidified potato dextrose agar (aPDA) with all six HRMs and with B. fulva and N. fischeri in strawberry, apple and orange juice-based media. At ≥ 0.15% O 2 , visible growth of the HRMs occurred within 3-6 days. Complete inhibition on aPDA did not occur even at very low levels of dissolved O 2 (ca. 0.01% O 2 ). With the exception of B. fulva, decrease of the O 2 concentration to ≤0.03% resulted in significantly (p < 0.05) longer times to visible growth. The growth of N. laciniosa, N. fischeri, B. nivea and B. fulva was inhibited for 30 days when they were incubated under strict anaerobic conditions. As in aPDA, B. fulva and N. fischeri grew in the three fruit-based media at O 2 concentrations ≥0.15%. Significantly slower (p < 0.05) growth was observed for N. fischeri in orange juice medium. Strategies to inhibit the growth of HRMs should therefore not be based entirely on establishing low headspace O 2 levels. With this in mind, the effect of low O 2 concentrations (<1%) should be studied in combination with other factors (hurdles) such as antioxidants, organic acids, sugars (a w ), storage temperature and pasteurization intensity, in order to predict the growth inhibition of the HRMs., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

This Research Communication describes the adaptation and testing of an RP-HPLC method, previously tested for the determination of lactoferrin (LF) in whey, for its applicability to determine milk lactoferrin content. Milk samples of various species, namely, ovine, caprine, bovine, donkey and human milk, were tested. The advantage of this RP-HPLC method includes speed and convenience, as it does not include extensive pretreatment or separation steps. A simple pre-treatment step was added in order to remove fat and proteins of the casein family and the samples were tested. The results varied in terms of elution of the LF peak both between the milk of the different species as well as from the initial application on whey. The peak resolution was satisfactory in the cases of ovine, bovine and donkey milk samples while for caprine and human milk an interference with other peaks was observed. Nevertheless, quantification of LF was found possible for all samples. This new application of the modified method will allow the determination of LF in milk samples of the tested species either for everyday analysis or as a useful qualitative screening for presence or absence of LF.

High hydrostatic pressure (HHP) is an interesting hurdle in minimal food processing that aims to synergistically combine different stresses to improve food microbiological safety and stability without compromising quality. For a proper understanding and design of hurdle technology, the cellular impact of the applied stresses on foodborne pathogens should be well-established. To study the mechanism of HHP-mediated cell injury and death, we screened for loss-of-function mutations in E. coli MG1655 that affected HHP sensitivity. More specifically, ca. 6000 random transposon insertion mutants were individually exposed to HHP, after which the phenotype of the most resistant or sensitive mutations was confirmed by de novo gene deletions in the parental strain. We found that disruption of rbsK, rbsR, hdfR and crl decreased HHP resistance, while disruption of sucC and sucD (encoding subunits of the succinyl-CoA synthetase) increased HHP resistance. More detailed study of the tricarboxylic acid cycle enzymes encoded by the sdhCDAB-sucABCD operon surprisingly showed that disruption of the sucA or sucB gene (encoding subunits of the 2-oxoglutarate dehydrogenase complex) notably decreased HHP survival. We also found that the increased HHP resistance of a ΔsucC and ΔsucD mutant was mediated by increased basal RpoS activity levels, although it did not correlate with their heat resistance. Our results reveal that compromising TCA cycle enzymes can profoundly affect HHP resistance in E. coli., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

In this work, the effect of environmental factors on Staphylococcus aureus (ATCC 13150) biofilm formation in tryptic soy broth was investigated under different ranges of pH (3.0-9.5), ethanol concentration (EtOH 0.0-20.0%), and a w (NaCl, 0.866-0.992). Biofilm formation was quantified using the crystal violet staining method and optical density (OD: 590 nm) measurements. Biofilm formation was significantly stronger at pH and a w close to S. aureus optimal growth conditions, while it was high at EtOH around 2.5-3.5%. Data sets from the difference between the OD measurements of the test and control (ΔOD) were fitted to the cardinal parameter model (CPM) and cardinal parameter model with inflection (CPMI) to describe the effect of the environmental factors. The models showed good quality of fit for the experimental data in terms of calculated RMSE, with the latter ranging from 0.276 to 0.455. CPM gave a good quality of fit compared to CPMI for the environmental factors tested. Optimal pH was close to neutral (6.76-6.81) and biofilm formation was possible till pH = 3.81-3.78 for CPM and CPMI, respectively. Optimum EtOH and a w conditions for biofilm formation were in the range of 1.99-2.75 and 0.98-0.97, respectively. Predicted OD values observed using strain 13150 were very closely correlated to the OD values predicted with strain 12600 with R 2 of 0.978, 0.991, and 0.947 for pH, EtOH, and a w , respectively. The cultivable bacterial cells within the biofilm were enumerated using standard plate counting and a linear model was applied to correlate the attached biofilm cells to ΔOD of biofilm formation. It was found that the biofilm formation correlated with S. aureus population growth. At 2.5-3.5% of EtOH the maximum population density was lower than that observed at 0.0% of EtOH. As 2.5-3.5% of EtOH initiated a stronger biofilm formation, biofilm formation seems to be induced by ethanol stress. The development of cardinal parameter models to describe the effect environmental factors of importance to biofilm formation, offers a promising predictive microbiology approach to decrypting the S. aureus population growth and survival ability on food processing surfaces., (Copyright © 2018. Published by Elsevier Ltd.)

The major aims of this study were to assess inter- and intra-species variability of heat resistant moulds (HRMs), Byssochlamys fulva and Byssochlamys nivea, with regards to (i) heat resistance and (ii) effect of heat treatment intensity on subsequent outgrowth. Four-week-old ascospores were suspended in buffered glucose solution (13° Brix, pH 3.5) and heat treated in a thermal cycler adjusted at 85 °C, 90 °C and 93 °C. Two variants of the Weibull model were fitted to the survival data and the following inactivation parameters estimated: b (inactivation rate, min -1 ), n (curve shape) and δ (the time taken for first decimal reduction, min). In addition to the assessment of heat resistance, outgrowth of Byssochlamys sp. from ascospores heated at 70 °C, 75 °C, 80 °C, 85 °C and 90 °C for 10 min and at 93 °C for 30 and 70 s was determined at 22 °C for up to 30 days. The Baranyi and Roberts model was fitted to the growth data to estimate the radial growth rates (μ max , mm.day -1 ) and lag times (λ, days). Inter-species variability and significant differences (p < 0.05) were observed for both inactivation and growth estimated parameters among B. fulva and B. nivea strains. The effect of heat treatment intensity on outgrowth of B. fulva strains was more apparent at the most intense heat treatment evaluated (90 °C/10 min), which was also the condition in which greater dispersion of the estimated kinetic parameters was observed. On the other hand, B. nivea strains were more affected by heating, resulting in greater variability of growth parameters estimated at different heating intensities and in very long lag phases (up to 25 days). The results show that inter- and intra-species variability in the kinetic parameters of Byssochlamys sp. needs to be taken into account for more accurate spoilage prediction. Furthermore, the effect of thermal treatments on subsequent outgrowth from ascospores should be explored in combination with other relevant factors such as °Brix and oxygen to develop thermal processes and storage conditions which can prevent the growth of HRMs and spoilage of heat treated food products., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The discharge of dye-contaminated wastewater into natural waterways presents a substantial risk to human and environmental health, therefore necessitating the treatment and removal of toxic dyes from colored wastewaters before their release into the ecosystem. The aim of this study was to isolate and characterize bacterial strains capable of decolorizing and/or degrading azo dyes commonly applied in textile production (monoazo dye Reactive Orange 16 and diazo dye Reactive Green 19) from activated sludge systems used in the treatment of (textile) wastewater. Following a prescreening of 125 isolates for their decolorization potential five strains were retained for further evaluation of decolorization rate and effects of physicochemical parameters using a microtiter plate method. Of those five strains, one strain belonging to the genus Acinetobacter (ST16.16/164) and another belonging to Klebsiella (ST16.16/034) outperformed the other tested strains. Both strains exhibited strong decolorization ability (>80%) within a wide temperature range (20 °C-40 °C) and retained good decolorization activity at temperatures as low as 10 °C (especially strain ST16.16/034). Among the different pH values tested (pH 4, 7 and 10), highest dye removal for both strains occurred at pH 7, with decolorization efficiency remaining relatively high under alkaline conditions (pH 10), and neither isolates decolorization efficiency was negatively impacted by high salt or high dye concentration. Furthermore, both strains displayed the highest rate of decolorization and were able to completely (ST16.16/034) or partly (ST16.16/164) degrade the azo dyes. Altogether, our results support the use of these bacteria in the treatment of industrial wastewaters containing azo dyes., (Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.)

Contamination of cereal grains as a key global food resource with insects or microorganisms is a persistent concern for the grain industry due to irreversible damage to quality and safety characteristics and economic losses. Atmospheric cold plasma presents an alternative to conventional grain decontamination methods owing to the high antimicrobial potential of reactive species generated during the treatment, but effects against product specific microflora are required to understand how to optimally develop this approach for grains. This work investigated the influence of ACP processing parameters for both cereal grain decontamination and grain quality as important criteria for grain or seed use. A high voltage (HV) (80 kV) dielectric barrier discharge (DBD) closed system was used to assess the potential for control of native microflora and pathogenic bacterial and fungal challenge microorganisms, in tandem with effects on grain functional properties. Response surface modelling of experimental data probed the key factors in relation to microbial control and seed germination promotion. The maximal reductions of barley background microbiota were 2.4 and 2.1 log 10  CFU/g and of wheat - 1.5 and 2.5 log 10  CFU/g for bacteria and fungi, respectively, which required direct treatment for 20 min followed by a 24 h sealed post-treatment retention time. In the case of challenge organisms inoculated on barley grains, the highest resistance was observed for Bacillus atrophaeus endospores, which, regardless of retention time, were maximally reduced by 2.4 log 10  CFU/g after 20 min of direct treatment. The efficacy of the plasma treatment against selected microorganisms decreased in the following order: E. coli > P. verrucosum (spores) > B. atrophaeus (vegetative cells) > B. atrophaeus (endospores). The challenge microorganisms were more susceptible to ACP treatment than naturally present background microbiota. No major effect of short term plasma treatment on the retention of quality parameters was observed. Germination percentage measured after 7 days cultivation was similar for samples treated for up to 5 min, but this was decreased after 20 min of direct treatment. Overall, ACP proved effective for cereal grain decontamination, but it is noted that the diverse native micro-flora may pose greater resistance to the closed, surface decontamination approach than the individual fungal or bacterial challenges, which warrants investigation of grain microbiome responses to ACP., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Textile wastewater contains high concentrations of organic substances derived from diverse dyes and auxiliary chemicals, some of which are non-biodegradable and/or toxic. Therefore, it is essential that textile wastewater is treated and that these substances are removed before being discharged into the environment. A combination of advanced oxidation processes (AOPs) to obtain partial dye degradation followed by a biological treatment has been suggested as a promising method for cost-effective decolorization of wastewater. The aim of this study was to develop and evaluate a combined method of partial Fenton's oxidation and biological treatment using activated sludge for decolorization of azo dyes, which represent an important group of recalcitrant, toxic textile dyes. Using Reactive Violet 5 (RV5) as a model dye, color removal was significantly higher when the combined Fenton treatment/activated sludge method was used, as opposed to separate application of these treatments. More specifically, pretreatment with Fenton's reagent removed 52.9, 83.9 and 91.3 % of color from a 500 mg l -1  RV5 aqueous solution within 60 min when H 2 O 2 concentrations of 1.0, 1.5, and 2.0 mM were used, respectively. Subsequent biological treatment was found to significantly enhance the chemical treatment, with microbial decolorization removing 70.2 % of the remaining RV5 concentration, on average. Molecular analysis of the microbial community within the activated sludge revealed that exposure to RV5 shifted the community composition from diverse towards a highly-specialized community harboring taxa with azo dye degrading activity, including Trichosporon, Aspergillus and Clostridium species., (Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.)

A comprehensive mathematical model of the digestive processes in humans could allow for better design of functional foods which may play a role in stemming the prevalence of food related diseases around the world. This work presents a mathematical model for a nutrient based feedback mechanism controlling gastric emptying, which has been identified in vivo by numerous researchers. The model also takes into account the viscosity of nutrient meals upon gastric secretions and emptying. The results show that modelling the nutrient feedback mechanism as an on/off system, with an initial emptying rate dependent upon the secretion rate (which is a function of the gastric chyme viscosity) provides a good fit to the trends of emptying rate for liquid meals of low and high nutrient content with varying viscosity.

It is assumed that microbial communities involved in the biological treatment of different wastewaters having a different chemical composition harbor different microbial populations which are specifically adapted to the environmental stresses encountered in these systems. Yet, little is known about the composition of these microbial communities. Therefore, the aim of this study was to assess the microbial community composition over two seasons (winter and summer) in activated sludge from well-operating textile wastewater treatment plants (WWTPs) in comparison with municipal WWTPs, and to explain observed differences by environmental variables. 454-pyrosequencing generated 160 archaeal and 1645 bacterial species-level Operational Taxonomic Units (OTUs), with lower observed richness in activated sludge from textile WWTPs compared to municipal WWTPs. The bacterial phyla Planctomycetes, Chloroflexi, Chlorobi, and Acidobacteria were more abundant in activated sludge samples from textile WWTPs, together with archaeal members of Thaumarchaeota. Nonmetric multidimensional scaling analysis of the microbial communities showed that microbial communities from textile and municipal WWTPs were significantly different, with a seasonal effect on archaea. Nitrifying and denitrifying bacteria as well as phosphate-accumulation bacteria were more abundant in municipal WWTPs, while sulfate-reducing bacteria were almost only detected in textile WWTPs. Additionally, microbial communities from textile WWTPs were more dissimilar than those of municipal WWTPs, possibly due to a wider diversity in environmental stresses to which microbial communities in textile WWTPs are subjected to. High salinity, high organic loads, and a higher water temperature were important potential variables driving the microbial community composition in textile WWTPs. This study provides a general view on the composition of microbial communities in activated sludge of textile WWTPs, and may provide novel insights for identifying key players performing important functions in the purification of textile wastewaters., (© 2016 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.)

(13)C-based metabolic flux analysis is an excellent technique to resolve fluxes in the central carbon metabolism but costs can be significant when using specialized tracers. This work presents a framework for cost-effective design of (13)C-tracer experiments, illustrated on two different networks. Linear and non-linear optimal input mixtures are computed for networks for Streptomyces lividans and a carcinoma cell line. If only glucose tracers are considered as labeled substrate for a carcinoma cell line or S. lividans, the best parameter estimation accuracy is obtained by mixtures containing high amounts of 1,2-(13)C2 glucose combined with uniformly labeled glucose. Experimental designs are evaluated based on a linear (D-criterion) and non-linear approach (S-criterion). Both approaches generate almost the same input mixture, however, the linear approach is favored due to its low computational effort. The high amount of 1,2-(13)C2 glucose in the optimal designs coincides with a high experimental cost, which is further enhanced when labeling is introduced in glutamine and aspartate tracers. Multi-objective optimization gives the possibility to assess experimental quality and cost at the same time and can reveal excellent compromise experiments. For example, the combination of 100% 1,2-(13)C2 glucose with 100% position one labeled glutamine and the combination of 100% 1,2-(13)C2 glucose with 100% uniformly labeled glutamine perform equally well for the carcinoma cell line, but the first mixture offers a decrease in cost of $ 120 per ml-scale cell culture experiment. We demonstrated the validity of a multi-objective linear approach to perform optimal experimental designs for the non-linear problem of (13)C-metabolic flux analysis. Tools and a workflow are provided to perform multi-objective design. The effortless calculation of the D-criterion can be exploited to perform high-throughput screening of possible (13)C-tracers, while the illustrated benefit of multi-objective design should stimulate its application within the field of (13)C-based metabolic flux analysis., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Mathematical modeling and the development of predictive dynamic models are of paramount importance for the optimization, state estimation, and control of bioprocesses. This study is dedicated to the identification of a simple model of microalgae growth under substrate limitation, i.e., Droop model, and describes the design and instrumentation of a lab-scale flat-plate photobioreactor, the associated on-line and off-line instrumentation, the collection of experimental data, and the parameter identification procedure. In particular, a dedicated methodology for parameter identification is discussed, including the determination of an initial parameter set using an analytical procedure, the selection of a cost function, the evaluation of confidence intervals as well as direct and cross-validation tests.

Informative experiments are highly valuable for estimating parameters in nonlinear dynamic bioprocesses. Techniques for optimal experiment design ensure the systematic design of such informative experiments. The E-criterion which can be used as objective function in optimal experiment design requires the maximization of the smallest eigenvalue of the Fisher information matrix. However, one problem with the minimal eigenvalue function is that it can be nondifferentiable. In addition, no closed form expression exists for the computation of eigenvalues of a matrix larger than a 4 by 4 one. As eigenvalues are normally computed with iterative methods, state-of-the-art optimal control solvers are not able to exploit automatic differentiation to compute the derivatives with respect to the decision variables. In the current paper a reformulation strategy from the field of convex optimization is suggested to circumvent these difficulties. This reformulation requires the inclusion of a matrix inequality constraint involving positive semidefiniteness. In this paper, this positive semidefiniteness constraint is imposed via Sylverster's criterion. As a result the maximization of the minimum eigenvalue function can be formulated in standard optimal control solvers through the addition of nonlinear constraints. The presented methodology is successfully illustrated with a case study from the field of predictive microbiology., (Copyright © 2015. Published by Elsevier Inc.)

In this study, a low-cost RGB sensor is developed to measure online the microalgae concentration within a photo-bioreactor. Two commercially available devices, i.e., a spectrophotometer for offline measurements and an immersed probe for online measurements, are used for calibration and comparison purposes. Furthermore, the potential of such a sensor for estimating other variables is illustrated with the design of an extended Luenberger observer.

Proteins secreted by Gram-positive bacteria are released into the culture medium with the obvious benefit that they usually retain their native conformation. This property makes these host cells potentially interesting for the production of recombinant proteins, as one can take full profit of established protocols for the purification of active proteins. Several state-of-the-art strategies to increase the yield of the secreted proteins will be discussed, using Streptomyces lividans as an example and compared with approaches used in some other host cells. It will be shown that approaches such as increasing expression and translation levels, choice of secretion pathway and modulation of proteins thereof, avoiding stress responses by changing expression levels of specific (stress) proteins, can be helpful to boost production yield. In addition, the potential of multi-omics approaches as a tool to understand the genetic background and metabolic fluxes in the host cell and to seek for new targets for strain and protein secretion improvement is discussed. It will be shown that S. lividans, along with other Gram-positive host cells, certainly plays a role as a production host for recombinant proteins in an economically viable way. This article is part of a Special Issue entitled: Protein trafficking and secretion in bacteria. Guest Editors: Anastassios Economou and Ross Dalbey., (Copyright © 2014 Elsevier B.V. All rights reserved.)

The metabolic impact exerted on a microorganism due to heterologous protein production is still poorly understood in Streptomyces lividans. In this present paper, based on exometabolomic data, a proposed genome-scale metabolic network model is used to assess this metabolic impact in S. lividans. Constraint-based modeling results obtained in this work revealed that the metabolic impact due to heterologous protein production is widely distributed in the genome of S. lividans, causing both slow substrate assimilation and a shift in active pathways. Exchange fluxes that are critical for model performance have been identified for metabolites of mouse tumor necrosis factor, histidine, valine and lysine, as well as biomass. Our results unravel the interaction of heterologous protein production with intracellular metabolism of S. lividans, thus, a possible basis for further studies in relieving the metabolic burden via metabolic or bioprocess engineering., (Copyright © 2013. Published by Elsevier Inc.)

The impact of alternating influent carbon sources, i.e., glucose and starch, on activated sludge bioflocculation was investigated. To this end, four lab-scale reactors were operated during a long-term experiment. During this period the influent carbon source ratio (glucose/starch) was alternated every 7 or 35 days (i.e., a fast and slow switching frequency). Bioflocculation was monitored throughout the entire experiment using an extensive set of parameters, including macroscopic and microscopic activated sludge characteristics. Sludge hydrophobicity remained high (>80%) throughout the experiment indicating good bioflocculation. However, sludge settleability decreased for all four reactors after a 60 day adaptation period to the applied alternation in influent carbon source. During this adaptation period, floc size decreased due to the release of microcolonies. The subsequent period was characterized by a decrease in settleability, coinciding with a release of primary particles and an increase in floc size. The observed phenomena could be linked with the protein concentration near the floc surface. This fraction mainly consists of hydrolytic enzymes necessary for the degradation of starch and is responsible for a progressive deterioration of the EPS matrix. The results of this specific study indicate to be independent of the influent carbon source ratio or switching frequency., (Copyright © 2013 Elsevier B.V. All rights reserved.)

The optimal design and operation of dynamic bioprocesses gives in practice often rise to optimisation problems with multiple and conflicting objectives. As a result typically not a single optimal solution but a set of Pareto optimal solutions exist. From this set of Pareto optimal solutions, one has to be chosen by the decision maker. Hence, efficient approaches are required for a fast and accurate generation of the Pareto set such that the decision maker can easily and systematically evaluate optimal alternatives. In the current paper the multi-objective optimisation of several dynamic bioprocess examples is performed using the freely available ACADO Multi-Objective Toolkit ( http://www.acadotoolkit.org ). This toolkit integrates efficient multiple objective scalarisation strategies (e.g., Normal Boundary Intersection and (Enhanced) Normalised Normal Constraint) with fast deterministic approaches for dynamic optimisation (e.g., single and multiple shooting). It has been found that the toolkit is able to efficiently and accurately produce the Pareto sets for all bioprocess examples. The resulting Pareto sets are added as supplementary material to this paper.

Anaerobic digestion is widely applied for the recovery of energy from waste activated sludge. Pre-treatment methods are of high interest to increase the biodegradability of the sludge and to enhance the digestion efficiency. This paper studies the application of a microwave pre-treatment. An experimental set-up of two pilot scale semi-continuous digesters was used. During a long term experiment, one of the reactors was fed with untreated sludge, while microwave pre-treated sludge (336 kJ/kg sludge) was introduced in the second one. A solid retention time of 20 days was kept during the experiments. (Organic) dry solids, carbohydrates, proteins and volatile fatty acids were monitored during digestion. It was seen that the microwave pre-treatment resulted in an effective solubilization of the organic matter in the sludge. The changes to the sludge composition resulted in an increase in biogas production by 50%, while the methane concentration in both reactors remained stable., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Streptomyces lividans has shown potential as an expression system for heterologous proteins. Overexpression of proteic factors important for heterologous protein production is a valuable approach to improve yields of such proteins. Comparative transcriptomic analysis revealed that several genes were differentially expressed in strains involved in heterologous protein production. For instance, the gene-encoding phosphoenolpyruvate carboxykinase (pepck) showed a significant twofold change in recombinant S. lividans producing human tumour necrosis factor-alpha (hTNF-α). The effect of pepck overexpression on S. lividans TK24 and its hTNF-α producing recombinant was thus investigated in bench-top fermenters. Results obtained revealed that pepck overexpression resulted into a twofold increase in specific PEPCK activity during growth. This overexpression is correlated with slower growth rate, reduced excretion of pyruvate and less alkalinisation of the growth medium when compared with the control strain. After 26 h of fermentation, hTNF-α yields were enhanced (up to 1.7-fold) in the pepck-overexpressing S. lividans TK24, demonstrating that this metabolic engineering approach is indeed promising for heterologous protein production.

Secondary models, describing the microbial growth rate as a function of temperature, are evaluated with focus on model performance in the suboptimal temperature region. Escherichia coli K12 MG1655 is considered as the case study. A large set of square root of μ(max)(T)-estimates is fitted with (1) the cardinal temperature model with inflection (CTMI, Rosso et al., 1993), (2) the square root model (SQRT, Ratkowsky et al., 1983), and (3) the CTMI adapted to describe the particular behavior of Listeria at suboptimal temperatures (aCTMI, Le Marc et al., 2002). Compared to the CTMI and the SQRT, a more accurate description of the μ(max)(T)-relation is obtained with the aCTMI, certainly at temperatures below 30 °C. Also, the T(min) estimate is more realistic, i.e., ≈6 °C, compared to 8-8.5 °C for the CTMI and SQRT. Use of the aCTMI improved square root of μ(max)(T)-data description which points at the existence of two phases in the suboptimal temperature region of E. coli K12. The alternation of the square root of μ(max)(T) is most likely related to the cold shock response. These results reveal a possible shortcoming of the model structure of commonly used secondary models describing the temperature effect on the microbial growth rate., (Copyright © 2012 Elsevier B.V. All rights reserved.)

It is generally known that intracellular pH (pH(i)) plays a vital role in cell physiology and that pH(i) homeostasis is essential for normal cellular functions. Therefore, it is desirable to know the pH(i) during cell life cycle or under various growth conditions. Different methods to measure pH(i) have been developed and among these methods, the use of pH-sensitive green fluorescent protein (GFP) as a pH(i) indicator is a promising technique. By using this approach, not only can more accurate pH(i) results be obtained but also long-term experiments on pH(i) can be performed. In this study, the wild type Zygosaccharomyces bailii, a notorious food spoilage yeast, was transformed with a plasmid encoding a pH-sensitive GFP (i.e. pHluorin), enabling the pH(i) of the yeast to be determined based on cellular fluorescent signals. After the transformation, growth and pH(i) of the yeast were investigated in four different acidic conditions at 22°C during 26days. From the experimental results, the transformation effectiveness was verified and a good correlation between yeast growth and pH(i) was noticed. Particularly, it was observed that the yeast has an ability to tolerate a significant pH(i) drop during exponential phase and a subsequent pH(i) recovery in stationary phase, which may underlie the exceptional acid resistance of the yeast. This was the first time that a GFP-based approach for pH(i) measurement was applied in Z. bailii and that the pH(i) of the yeast was monitored during such a long period (26days). It can be expected that greater understanding of the physiological properties and mechanisms behind the special acid resistance of the yeast will be obtained from further studies on this new yeast strain., (Copyright © 2012 Elsevier B.V. All rights reserved.)

The biopharmaceutical market has come a long way since 1982, when the first biopharmaceutical product, recombinant human insulin, was launched. Just over 200 biopharma products have already gained approval. The global market for biopharmaceuticals which is currently valued at over US$99 billion has been growing at an impressive compound annual growth rate over the previous years. To produce these biopharmaceuticals and other industrially important heterologous proteins, different prokaryotic and eukaryotic expression systems are used. All expression systems have some advantages as well as some disadvantages that should be considered in selecting which one to use. Choosing the best one requires evaluating the options--from yield to glycosylation, to proper folding, to economics of scale-up. No host cell from which all the proteins can be universally expressed in large quantities has been found so far. Therefore, it is important to provide a variety of host-vector expression systems in order to increase the opportunities to screen for the most suitable expression conditions or host cell. In this overview, we focus on Streptomyces lividans, a Gram-positive bacterium with a proven excellence in secretion capacity, as host for heterologous protein production. We will discuss its advantages and disadvantages, and how with systems biology approaches strains can be developed to better producing cell factories., (Copyright © 2011 Elsevier B.V. All rights reserved.)

In this work, the influence of an ultrasonic pre-treatment on anaerobic digestion of waste activated sludge is studied. Attention is paid to the solubilisation of the main organic (proteins, carbohydrates) and inorganic (heavy metals) sludge components during ultrasonic treatment and the influence of the dry solids content (DS) on the degree of solubilisation. The second part of the paper focuses on the relationship between the applied specific energy of the ultrasonic treatment and methane production. In general, a higher specific energy and a higher DS content are beneficial for the release of organic matter, resulting in an increased methane production. The efficiency of the subsequent anaerobic digestion is similar for both sludge types (2.1 and 3.2% DS). However, at lower DS contents (2.1%), the methane production increase was more significant.

In the past years, we explored the dynamics of Escherichia coli K12 at super-optimal temperatures under static and dynamic temperature conditions (Van Derlinden et al. (2008b, 2009, 2010). Disturbed sigmoid growth curves, i.e., a sequence of growth, inactivation and re-growth, were observed, especially close to the maximum growth temperature. Based on the limited set of experiments (i.e., 2 static temperatures and 2 dynamic temperature profiles), the irregular growth curves were explained by postulating the co-existence of two subpopulations: a more resistant, growing population and a temperature sensitive, inactivating population. In this study, the dynamics of the two subpopulations are studied rigorously at 11 constant temperature levels in the region between 45°C and 46°C, with at least five repetitions per temperature. At all temperatures, the total population follows a sequence of growth, inactivation and re-growth. The sequence of different stages in the growth curves can be explained by the two subpopulations. The first growth phase and the inactivation phase reflect the presence of the sensitive subpopulation. Hereafter, the population's dynamics are dominated by the growth of the resistant subpopulation. Generally, cell counts are characterized by a large variability. The dynamics of the two subpopulations are carefully analyzed using a heterogeneous subpopulation type model to study the relation between the kinetic parameters of the two subpopulations and temperature, and to evaluate if the fraction d of resistant cells varies with temperature. Results indicate that the growth rate of the sensitive subpopulation decreases with increasing temperature within the range of 45-46°C. Furthermore, results point in the direction that the duration of this initial growth phase is approximately constant, i.e., around 2h. Possibly, the stress resistance of the cells decreases after a certain period because the metabolism is fully adapted to exponential growth. Also, the growth rate of the resistant subpopulation decreases with increasing temperature. Due to the extreme variability in the cell density data, derivation of accurate relations was not possible. From the heterogeneous model implementations, given the experimental set-up, both a constant d value and a temperature dependent d value seem plausible., (Copyright © 2010. Published by Elsevier Ltd.)

During the last decade, individual-based modelling (IbM) has proven to be a valuable tool for modelling and studying microbial dynamics. As each individual is considered as an independent entity with its own characteristics, IbM enables the study of microbial dynamics and the inherent variability and heterogeneity. IbM simulations and (single-cell) experimental research form the basis to unravel individual cell characteristics underlying population dynamics. In this study, the IbM framework MICRODIMS, i.e., MICRObial Dynamics Individual-based Model/Simulator, is used to investigate the system dynamics (with respect to the model and the system modelled). First, the impact of the time resolution on the simulation accuracy is discussed. Second, the effect of the inoculum state and size on emerging individual dynamics, such as individual mass, individual age and individual generation time distribution dynamics, is studied. The distributions of individual characteristics are more informative during the lag phase and the transition to the exponential growth phase than during the exponential phase. The first generation time distributions are strongly influenced by the inoculum state. All inocula with a pronounced heterogeneity, except the inocula starting from a uniform distribution, exhibit commonly observed microbial behaviour, like a more spread first generation time distribution compared to following generations and a fast stabilisation of biomass and age distributions., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Microbiological contamination data often is censored because of the presence of non-detects or because measurement outcomes are known only to be smaller than, greater than, or between certain boundary values imposed by the laboratory procedures. Therefore, it is not straightforward to fit distributions that summarize contamination data for use in quantitative microbiological risk assessment, especially when variability and uncertainty are to be characterized separately. In this paper, distributions are fit using Bayesian analysis, and results are compared to results obtained with a methodology based on maximum likelihood estimation and the non-parametric bootstrap method. The Bayesian model is also extended hierarchically to estimate the effects of the individual elements of a covariate such as, for example, on a national level, the food processing company where the analyzed food samples were processed, or, on an international level, the geographical origin of contamination data. Including this extra information allows a risk assessor to differentiate between several scenario's and increase the specificity of the estimate of risk of illness, or compare different scenario's to each other. Furthermore, inference is made on the predictive importance of several different covariates while taking into account uncertainty, allowing to indicate which covariates are influential factors determining contamination., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

The aim of this work is to investigate the effect of acid treatment -before and during heat inactivation- on the heat resistance of Escherichia coli K12 MG1655 cells at lethal temperatures. E. coli cells were grown in Brain Heart Infusion broth until they reached the stationary phase (≈10(9) cfu/mL). Approximately 30 min before thermal inactivation the early stationary phase cells were added in Brain Heart Infusion broth with a specific pH value, achieved with addition of either acetic (50% (v/v)), lactic (50% (v/v)) or hydrochloric acid (30% (v/v)), and inactivation experiments took place at 54 °C and 58 °C. The inactivation dynamics are analysed using the inactivation model of Geeraerd et al. (2000). This enables to define the induced thermotolerance of E. coli as a prolongation of the shoulder and/or a reduction of the inactivation rate. Generally, addition of acids increased the heat resistance of E. coli. The induced resistance depends on the type of acid and on the quantity added, i.e. different levels of acidification lead to a different level of heat resistance. This work provides additional knowledge on the reaction of bacterial cultures to heat after acid treatment -before and during heat treatment- and, therefore, it contributes to an improved understanding of the effect of acid exposure on the bacterial heat resistance., (Copyright © 2010. Published by Elsevier Ltd.)

Growth/no growth (G/NG) studies that include the effect of medium structure have typically been performed for (pathogenic) bacteria and on the basis of gelatin/agar as a gelling agent. In this study, the growth potential of the spoilage yeast Zygosaccharomyces bailii was investigated in two model systems that resemble the macroscopic physicochemical and rheological properties of acidic sauces. In a Carbopol model system, the effect of pH (3.5-4.5), glycerol concentration (17-32%), acetic acid concentration (1.5-2.0%) and medium structure (3 levels) was investigated. In xanthan gum, the behavior of the yeast was studied at different levels of pH (3.5-4.5), NaCl concentration (0.5-13.5%), acetic acid concentration (0-2.0%) and medium structure (2 levels). Rheologically, viscoelastic moduli failed to discriminate between different forms of microbial growth, whereas yield stress data appeared to provide a better indication. In general, G/NG results revealed an unexpected increase of growth probability as a function of medium structure, both at 22 and 30 °C. Whether this behavior is the result of an underlying growth-promoting mechanism could not be explained from a macroscopic point of view (e.g., macrorheology, a(w)), but may be more related to the local microscopic properties of the gels. In a second part of this study, the potential use and information content of optical density measurements for G/NG data collection in structured media were critically evaluated and confronted with their practical relevance to the food industry., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Anaerobic digestion is widely used in waste activated sludge treatment. In this paper, partial least-squares (PLS) is employed to identify the parameters that are determining the biochemical methane potential (BMP) of waste activated sludge. Moreover, a model is developed for the prediction of the BMP. A strong positive correlation is observed between the BMP and volatile fatty acids and carbohydrate concentrations in the sludge. A somewhat weaker correlation with COD is also present. Soluble organics (sCOD, soluble carbohydrates and soluble proteins) were shown not to influence the BMP in the observed region. This finding could be most-valuable in the context of application of sludge pretreatment methods. The obtained model was able to satisfactory predict the BMP.

Anaerobic digestion is generally considered to be an economic and environmentally friendly technology for treating waste activated sludge, but has some limitations, such as the time it takes for the sludge to be digested and also the ineffectiveness of degrading the solids. Various pre-treatment technologies have been suggested to overcome these limitations and to improve the biogas production rate by enhancing the hydrolysis of organic matter. This paper studies the use of peracetic acid for disintegrating sludge as a pre-treatment of anaerobic digestion. It has been proved that this treatment effectively leads to a solubilisation of organic material. A maximum increase in biogas production by 21% is achieved. High dosages of PAA lead to a decrease in biogas production. This is due to the inhibition of the anaerobic micro-organisms by the high VFA-concentrations. The evolution of the various VFAs during digestion is studied and the observed trends support this hypothesis., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Aim: To quantify the influence of trimethylamine-N-oxide (TMAO) on the heat resistance of Escherichia coli K12 MG1655 cells at static temperatures., Methods and Results: Stationary-phase E. coli cells were inactivated at 52, 54 and 58°C. The heat resistance is described as reduction in the inactivation rate, k(max) , and/or an increase in the time for one decimal reduction, D, and/or an increase in the time for the fourth decimal reduction, t(4D) ., Conclusions: Resistance of E. coli changed - increased - at all temperatures under study. Generally, the addition of TMAO to the growth medium protected E. coli cells, leading to an increase in their heat resistance, i.e. reduced k(max) and increased D and t(4D) values are obtained., Significance and Impact of the Study: Additional knowledge on the reaction of E. coli to heat in the presence of the organic osmolyte TMAO at lethal temperatures is provided. This work contributes to an improved understanding of the level of the resistance of bacteria to heat in the presence of osmolytes., (© 2010 The Authors. Letters in Applied Microbiology © 2010 The Society for Applied Microbiology.)

In a previous study on Zygosaccharomyces bailii, three growth/no growth models have been developed, predicting growth probability of the yeast at different conditions typical for acidified foods (Dang, T.D.T., Mertens, L., Vermeulen, A., Geeraerd, A.H., Van Impe, J.F., Debevere, J., Devlieghere, F., 2010. Modeling the growth/no growth boundary of Z. bailii in acidic conditions: A contribution to the alternative method to preserve foods without using chemical preservatives. International Journal of Food Microbiology 137, 1-12). In these broth-based models, the variables were pH, water activity and acetic acid, with acetic acid concentration expressed in volume % on the total culture medium (i.e., broth). To continue the previous study, validation experiments were performed for 15 selected combinations of intrinsic factors to assess the performance of the model at 22°C (60days) in a real food product (ketchup). Although the majority of experimental results were consistent, some remarkable deviations between prediction and validation were observed, e.g., Z. bailii growth occurred in conditions where almost no growth had been predicted. A thorough investigation revealed that the difference between two ways of expressing acetic acid concentration (i.e., on broth basis and on water basis) is rather significant, particularly for media containing high amounts of dry matter. Consequently, the use of broth-based concentrations in the models was not appropriate. Three models with acetic acid concentration expressed on water basis were established and it was observed that predictions by these models well matched the validation results; therefore a "systematic error" in broth-based models was recognized. In practice, quantities of antimicrobial agents are often calculated based on the water content of food products. Hence, to assure reliable predictions and facilitate the application of models (developed from lab media with high dry matter contents), it is important to express antimicrobial agents' concentrations on a common basis-the water content. Reviews over other published growth/no growth models in literature are carried out and expressions of the stress factors' concentrations (on broth basis) found in these models confirm this finding., (Copyright © 2010 Elsevier B.V. All rights reserved.)

Aims: When subjected to dynamic temperatures surpassing the expected maximum growth temperature, Escherichia coli K12 MG1655 shows disturbed growth curves. These irregular population dynamics were explained by considering two subpopulations, i.e. a thermoresistant and a thermosensitive one (Van Derlinden et al. 2010a). In this paper, the influence of the initial cell concentration on the subpopulations' dynamics is evaluated., Methods and Results: Experiments were performed in a bioreactor with the temperature increasing from 42 to 65.2 °C (1 and 4 °C h(-1)) with varying initial cell concentrations [6, 12 and 18 ln(CFU ml(-1))]. When started from the highest cell concentration, the population was characterized by a higher overall maximum growth temperature and a higher inactivation temperature. For all experimental set-ups, resistant cells were still growing at the final temperature of 65.2 °C., Conclusions: The initial cell concentration had no effect on temperature resistance. The increase in temperature resistance of the sensitive subpopulation was because of the change of the physiological state to the stationary phase., Significance and Impact of the Study: A higher initial cell concentration leads to higher heat stress adaptation when cultures reach a maximum cell concentration. The observed growth at a temperature of 65.2 °C is very important for food safety and the temperature treatment of micro-organisms., (© 2010 The Authors. Journal compilation © 2010 The Society for Applied Microbiology.)

In this work, the influence of a low temperature (70-90 degrees C) thermal treatment on anaerobic digestion is studied. Not only the increase in biogas production is investigated, but attention is also paid to the solubilisation of the main organic (proteins, carbohydrates and volatile fatty acids) and inorganic (heavy metals, S and P) sludge constituents during thermal treatment and the breakdown of the organic components during the subsequent anaerobic digestion. Taking into account the effects of the treatment on the sludge composition is of prime importance to evaluate its influence on the subsequent anaerobic digestion and biogas production using predictive models. It was seen that organic and inorganic compounds are efficiently solubilised during thermal treatment. In general, a higher temperature and a longer treatment time are beneficial for the release. The efficiency of the subsequent anaerobic digestion slightly decreased for sludge pre-treated at 70 degrees C. At higher pre-treatment temperatures, the biogas production increased significantly, up to a factor 11 for the 60 min treatment at 90 degrees C., ((c) 2010 Elsevier Ltd. All rights reserved.)

Aims: The objective of this study was to investigate whether bacterial cells could develop resistance (as a part of their adaptation strategy) to high-pressure CO(2) (HPCD) inactivation., Methods and Results: Alternating cycles of exposure to pressurized CO(2) (10.5 MPa, 35 degrees C, 400 min(-1), 70% working volume ratio during 10 min) and re-growth of the surviving subpopulation were used to investigate possible increases in the resistance of Escherichia coli and Listeria monocytogenes to HPCD. The results show an increased resistance of both pathogens tested after seven cycles of inactivation. Increase in the resistance after 15 cycles resulted in a difference of 2.4 log CFU ml(-1) in log N(0)/N(i) when parental (N(0)) and treated cultures (N(i)) of E. coli and L. monocytogenes were compared., Conclusions: Current findings indicate the ability of micro-organisms to adapt to HPCD preservation technology., Significance and Impact of the Study: The occurrence of HPCD-resistant micro-organisms could pose a new hazard to the safety and stability of HPCD-processed foods.

In this study, the relationship between (irreversible) membrane permeabilization and loss of viability in Escherichia coli, Listeria monocytogenes and Saccharomyces cerevisiae cells subjected to high pressure carbon dioxide (HPCD) treatment at different process conditions including temperature (35-45 degrees C), pressure (10.5-21.0 MPa) and treatment time (0-60 min) was examined. Loss of membrane integrity was measured as increased uptake of the fluorescent dye propidium iodide (PI) with spectrofluorometry, while cell inactivation was determined by viable cell count. Uptake of PI by all three strains indicated that membrane damage is involved in the mechanism of HPCD inactivation of vegetative cells. The extent of membrane permeabilization and cellular death increased with the severity of the HPCD treatment. The resistance of the three tested organisms to HPCD treatment changed as a function of treatment time, leading to significant tailing in the survival curves, and was dependent on pressure and temperature. The results in this study also indicated a HPCD-induced damage on nucleic acids during cell inactivation. Transmission electron microscopy showed that HPCD treatment had a profound effect on the intracellular organization of the micro-organisms and influenced the permeability of the bacterial cells by introducing pores in the cell wall., (2009 Elsevier Ltd. All rights reserved.)

Optimal experiment design for parameter estimation (OED/PE) has become a popular tool for efficient and accurate estimation of kinetic model parameters. When the kinetic model under study encloses multiple parameters, different optimization strategies can be constructed. The most straightforward approach is to estimate all parameters simultaneously from one optimal experiment (single OED/PE strategy). However, due to the complexity of the optimization problem or the stringent limitations on the system's dynamics, the experimental information can be limited and parameter estimation convergence problems can arise. As an alternative, we propose to reduce the optimization problem to a series of two-parameter estimation problems, i.e., an optimal experiment is designed for a combination of two parameters while presuming the other parameters known. Two different approaches can be followed: (i) all two-parameter optimal experiments are designed based on identical initial parameter estimates and parameters are estimated simultaneously from all resulting experimental data (global OED/PE strategy), and (ii) optimal experiments are calculated and implemented sequentially whereby the parameter values are updated intermediately (sequential OED/PE strategy). This work exploits OED/PE for the identification of the Cardinal Temperature Model with Inflection (CTMI) (Rosso et al., 1993). This kinetic model describes the effect of temperature on the microbial growth rate and encloses four parameters. The three OED/PE strategies are considered and the impact of the OED/PE design strategy on the accuracy of the CTMI parameter estimation is evaluated. Based on a simulation study, it is observed that the parameter values derived from the sequential approach deviate more from the true parameters than the single and global strategy estimates. The single and global OED/PE strategies are further compared based on experimental data obtained from design implementation in a bioreactor. Comparable estimates are obtained, but global OED/PE estimates are, in general, more accurate and reliable., (Copyright (c) 2010 Elsevier Ltd. All rights reserved.)

A framework using maximum likelihood estimation (MLE) is used to fit a probability distribution to a set of qualitative (e.g., absence in 25 g), semi-quantitative (e.g., presence in 25 g and absence in 1g) and/or quantitative test results (e.g., 10 CFU/g). Uncertainty about the parameters of the variability distribution is characterized through a non-parametric bootstrapping method. The resulting distribution function can be used as an input for a second order Monte Carlo simulation in quantitative risk assessment. As an illustration, the method is applied to two sets of in silico generated data. It is demonstrated that correct interpretation of data results in an accurate representation of the contamination level distribution. Subsequently, two case studies are analyzed, namely (i) quantitative analyses of Campylobacter spp. in food samples with nondetects, and (ii) combined quantitative, qualitative, semiquantitative analyses and nondetects of Listeria monocytogenes in smoked fish samples. The first of these case studies is also used to illustrate what the influence is of the limit of quantification, measurement error, and the number of samples included in the data set. Application of these techniques offers a way for meta-analysis of the many relevant yet diverse data sets that are available in literature and (inter)national reports of surveillance or baseline surveys, therefore increases the information input of a risk assessment and, by consequence, the correctness of the outcome of the risk assessment., ((c) 2010 Elsevier B.V. All rights reserved.)

Several studies have shown that food structure causes slower growth rates and narrower growth boundaries of bacteria compared to laboratory media. In predictive microbiology, both a(w) or corresponding solute concentration (mainly NaCl) have been used as a growth influencing factor for kinetic models or growth/no growth interface models. The majority of these models have been based on data generated in liquid broth media with NaCl as the predominant a(w) influencing solute. However, in complex food systems, other a(w) influencing components might be present, next to NaCl. In this study, the growth rate of Salmonella typhimurium was studied in the growth region and the growth/no growth response was tested in Tryptic Soy Broth at 20 degrees C at varying gelatin concentration (0, 10, 50 g L(-1) gelatin), pH (3.25-5.5) and water activity (a(w)) (0.929-0.996). From the viewpoint of water activity, the results suggest that NaCl is the main a(w) affecting compound. However, gelatin seemed to have an effect on medium a(w) too. Moreover, there is also an interaction effect between NaCl and gelatin. From the microbial viewpoint, the results confirmed that the a(w) decreasing effect of gelatin is less harmful to cells than the effect of Na(+) ions. The unexpected shift of the growth/no growth interface to more severe conditions when going from a liquid medium to a medium with 10 g L(-1) gelatin is more pronounced when formulating the models in terms of a(w) than in terms of NaCl concentrations. At 50 g L(-1) gelatin, the model factored with NaCl concentration shifts to milder conditions (concordant to literature results) while the model with a(w) indicates a further shift to more severe conditions, which is due to the water activity lowering effect of gelatin and the interaction between gelatin and NaCl. The results suggest that solute concentration should be used instead of a(w), both for kinetic models in the growth region and for growth/no growth interface models, if the transferability of models to solid foods is to be increased.

Aims: Non-sigmoid growth curves of Escherichia coli obtained at constant temperatures near the maximum growth temperature (T(max)) were previously explained by the coexistence of two subpopulations, i.e. a stress-sensitive and a stress-resistant subpopulation. Mathematical simulations with a heterogeneous model support this hypothesis for static experiments at 45 degrees C. In this article, the behaviour of E. coli, when subjected to a linearly increasing temperature crossing T(max), is studied., Methods and Results: Subpopulation dynamics are studied by culturing E. coli K12 MG1655 in brain heart infusion broth in a bioreactor. The slowly increasing temperature (degrees C h(-1)) starting from 42 degrees C results in growth up to 60 degrees C, a temperature significantly higher than the known T(max). Given some additional presumptions, mathematical simulations with the heterogeneous model can describe the dynamic experiments rather well., Conclusions: This study further confirms the existence of a stress-resistant subpopulation and reveals the unexpected growth of E. coli at temperatures significantly higher than T(max)., Significance and Impact of the Study: The growth of the small stress-resistant subpopulation at unexpectedly high temperatures asks for a revision of currently applied models in food safety and food quality strategies.

The aim of the study was to develop mathematical models describing growth/no growth (G/NG) boundaries of the highly resistant food spoilage yeast-Zygosaccharomyces bailii-in different environmental conditions, taking acidified sauces as the target product. By applying these models, the stability of products with characteristics within the investigated pH, a(w) and acetic acid ranges can be evaluated. Besides, the well-defined no growth regions can be used in the development of guidelines regarding formulation of new shelf-stable foods without using chemical preservatives, which would facilitate the innovation of additive-free products. Experiments were performed at different temperatures and periods (22 degrees C for 45 and 60days, 30 degrees C for 45days) in 150 modified Sabouraud media characterized by high amount of sugars (glucose and fructose, 15% (w/v)), acetic acid (0.0-2.5% (v/v), 6 levels), pH (3.0-5.0, 5 levels) and a(w) (0.93-0.97, 5 levels). These time and temperature combinations were chosen as they are commonly applied for shelf-stable foods. The media were inoculated with ca. 4.5 log CFU/ml and yeast growth was monitored daily using optical density measurements. Every condition was examined in 20 replicates in order to yield accurate growth probabilities. Three separate ordinary logistic regression models were developed for different tested temperatures and incubation time. The total acetic acid concentration was considered as variable for all models. In general, when one intrinsic inhibitory factor became more stringent, the G/NG boundary shifted to less stressful conditions of the other two factors, resulting in enlarged no growth zones. Abrupt changes of growth probability often occurred around the transition zones (between growth and no growth regions), which indicates that minor variations in environmental conditions near the G/NG boundaries can cause a significant impact on the growth probability. When comparing growth after 45days between the two tested temperatures, an unexpected phenomenon was observed: the no growth region at 30 degrees C was larger than the one at 22 degrees C, though it is known that 30 degrees C is the optimal growth temperature for Z. bailii. These results show that lowering temperature does not always lead to a reduced growth of the yeast (i.e. more stable foods) and storing shelf-stable products at the higher temperature (30 degrees C) is not always the worst case. In addition, at 22 degrees C, there was no significant difference in no growth zones between the two incubation periods (45 and 60days), implying that the no growth zones remain unchanged if the experimental time is sufficiently long., (Copyright 2009 Elsevier B.V. All rights reserved.)

Aims: Previous work showed that the exponential phase of Escherichia coli K12 MG1655, grown in Brain Heart Infusion broth at temperatures close to its maximum growth temperature, is disturbed. Based on plate count data, microscopic images and literature, the existence of a heat-resistant subpopulation was hypothesized. Here, this hypothesis is mathematically explored via a heterogeneous model., Methods and Results: A heat-sensitive and a heat-resistant subpopulation are considered. A large fraction of the population is inactivated, while the remaining smaller fraction is able to resist (or adapt to) the inimical temperature and grows. A heterogeneous model that encloses a growth model (resistant population) and an inactivation model (sensitive population) is used to describe the global population dynamics. Most experimental data can be predicted when taking parameter uncertainty via Monte Carlo simulation into account., Conclusions: The heterogeneous model accurately describes disturbed growth curves at superoptimal temperatures, except for high initial cell densities., Significance and Impact of the Study: This study strengthens the hypothesis of the existence of a (small) heat-resistant subpopulation in typical inoculum cultures of E. coli K12 MG1655.

This research is an extension of previous work reported in Gysemans et al. [Gysemans, K.P.M., Bernaerts, K., Geeraerd, A.H., Vermeulen, A., Debevere, J., Devlieghere, F., Van Impe, J.F., 2007. Exploring the performance of logistic regression model types on growth/no growth data of Listeria monocytogenes. International Journal of Food Microbiology 114, 316-331.] in which the growth/no growth interface of Listeria monocytogenes was modelled as a function of water activity (a(w)), pH and undissociated acetic acid percentage (UAc). The major difference with the previous work is that in the present research the influence of the cell density (N) is also considered during the modelling process. New experimental data were therefore collected as a function of a wide range of cell densities up until the level of the individual cell. Prior to the development of model that incorporates N, the expected inadequacy of the high cell density growth/no growth model developed in Gysemans et al. (2007) on the new cell density dependent data was illustrated. Inadequacy of the model at lower cell densities was expected since the data showed a significant reduction of the growth probability as N decreased. For the development of a model that incorporates the effect of N, a square-root type logistic regression model was proposed and evaluated. The model predicts a strong influence of the cell density with an increase in the growth probability if the cell count increased. The onset of this increase is dependent on the intrinsic factors of the medium (pH, a(w), and acetic acid concentration). The model also suggests that it is unlikely that a larger population has a higher chance to start growing just because the chance on a strong cell is higher in a larger population. It seems that the bacteria influence each other's growth.

Aims: To evaluate a novel secondary model structure (Int J Food Microbiol 2008; 128: 67) that describes the effect of medium structure on the maximum specific growth rate (mu(max)) of Salmonella Typhimurium on the growth of S. Typhimurium, Listeria innocua, Lactococcus lactis and Listeria monocytogenes., Methods and Results: In the present study, the novel secondary model is validated for S. Typhimurium in more realistic media, namely, pasteurized milk and a cheese mimicking medium. The predictions were accurate. Next, the secondary model structure was evaluated in a two step and a global regression procedure on literature data. On the one hand, the growth of two other micro-organisms, namely L. innocua and L. lactis, in monoculture for varying gelatine concentrations was tested and on the other hand the growth rate of L. monocytogenes was fitted in a broth of which the viscosity was altered with polyvinylpyrrolidone. The model was able to describe the effect of increasing gelatine concentration or viscosity accurately., Conclusions: The proposed secondary model structure is able to describe the effect of gelatine concentration on the mu(max) of the micro-organisms tested in this study., Significance and Impact of the Study: In predictive microbiology, much attention has been paid to the effect of food structure on the mu(max) of bacteria. However, to the authors' knowledge, a lack of secondary models still exists to describe this effect. Although the proposed model is empirical, the model parameters have clear biological meaning. The predictive power of the model to describe the effect of food structure is clearly illustrated.

Processed ready-to-eat (RTE) foods with a prolonged shelf-life under refrigeration are at risk products for listeriosis. This manuscript provides an overview of prevalence data (n=1974) and challenge tests (n=299) related to Listeria monocytogenes for three categories of RTE food i) mayonnaise-based deli-salads (1187 presence/absence tests and 182 challenge tests), ii) cooked meat products (639 presence/absence tests and 92 challenge tests), and iii) smoked fish (90 presence/absence tests and 25 challenge tests), based on data records obtained from various food business operators in Belgium in the frame of the validation and verification of their HACCP plans over the period 2005-2007. Overall, the prevalence of L. monocytogenes in these RTE foods in the present study was lower compared to former studies in Belgium. For mayonnaise-based deli-salads, in 80 out of 1187 samples (6.7%) the pathogen was detected in 25 g. L. monocytogenes positive samples were often associated with smoked fish deli-salads. Cooked meat products showed a 1.1% (n=639) prevalence of the pathogen. For both food categories, numbers per gram never exceeded 100 CFU. L. monocytogenes was detected in 27.8% (25/90) smoked fish samples, while 4/25 positive samples failed to comply to the 100 CFU/g limit set out in EU Regulation 2073/2005. Challenge testing showed growth potential in 18/182 (9.9%) deli-salads and 61/92 (66%) cooked meat products. Nevertheless, both for deli-salads and cooked meat products, appropriate product formulation and storage conditions based upon hurdle technology could guarantee no growth of L. monocytogenes throughout the shelf-life as specified by the food business operator. Challenge testing of smoked fish showed growth of L. monocytogenes in 12/25 samples stored for 3-4 weeks at 4 degrees C. Of 45 (non-inoculated) smoked fish samples (13 of which were initially positive in 25 g) which were subjected to shelf-life testing, numbers exceeded 100 CFU/g in only one sample after storage until the end of shelf-life. Predictive models, dedicated to and validated for a particular food category, taking into account the inhibitory effect of various factors in hurdle technology, provided predictions of growth potential of L. monocytogenes corresponding to observed growth in challenge testing. Based on the combined prevalence data and growth potential, mayonnaise-based deli-salads and cooked meat products can be classified as intermediate risk foods, smoked fish as a high risk food.

Aims: The aim of this study was to extract information on cell number and colony volume dynamics of Salmonella Typhimurium colonies., Methods and Results: Both cell number and colony volume of Salmonella Typhimurium in gelatin were monitored during the exponential and the stationary phase with varying pH and water activity, by plate counts and microscopic image analysis respectively. The exponential growth rates of cell numbers and colony volumes were correlated. The exponential growth rate of cell numbers was estimated based on this correlation and a secondary model that describes the effect of pH and water activity on the growth rate of the colony volumes. During the stationary phase, the cell number was constant, while colony volume increased, thus indicating the formation of a dead fraction. Models were developed to describe the living and dead population., Conclusions: By comparing colony volumes and cell numbers, the formation of dead fraction can be noticed from the beginning of the stationary phase, which indicates that the stationary phase is a dynamic - including both cell death and cell growth - rather than a static phase., Significance and Impact of the Study: This study was the first to investigate the proportion of living and dead bacteria within a stationary colony quantitatively.

High pressure carbon dioxide (HPCD) treatment is currently considered as an attractive non-thermal process for preserving food. Industrial application of this technique requires, among others, systematic (quantitative) data on the inactivation of food relevant pathogenic and spoilage microorganisms, and in-depth information on the effect that the composition and the properties of a food matrix have on the inactivation efficacy. The first objective of this study, therefore, is to evaluate and compare the HPCD susceptibility of several food pathogens and spoilage microorganisms under the same treatment conditions. In the second part, the influence of different food components (NaCl, oil, starch, whey protein and emulsifier) and food properties (pH, fluid viscosity and water activity) on the inactivation efficacy of HPCD was determined. For the first aim, a range of Gram-negative and Gram-positive bacteria, yeasts and spores were treated with pressurized CO(2) at 10.5 MPa and 35 degrees C during 20 min. Bacterial susceptibility towards HPCD treatments followed the sequence Gram-negative approximately Gram-positive>yeasts>spores and appeared to be related to the acid resistance of the organisms. To study the effect of different food compounds on HPCD inactivation, the reduction degree of Pseudomonas fluorescens was determined in media with and without these components at 10.5 MPa and 35 degrees C after 5 or 20 min, depending on the tested component. NaCl and the emulsifiers Tween 80 and sucrose stearate enhanced bacterial reduction, while oil reduced the bactericidal efficacy of HPCD. Starch and whey proteins did not influence inactivation. Finally, the influence of pH, fluid viscosity and water activity was investigated by determining the reduction of P. fluorescens at 10.5 MPa and 35 degrees C in suspensions from which the pH, viscosity and water activity were adjusted with respectively NaOH or HCl, gelatin or polyethylene glycol, and sucrose, NaCl or glycerol. Treatment time depended on the studied food property with 5 min for the pH experiments, while other experiments lasted 20 min. The results indicated that P. fluorescens cells became more sensitive to HPCD treatments at low pH and viscosity. Not water activity but the kind of soluble solute used to lower water activity influenced inactivation. High NaCl-concentrations lead to total inactivation, while sucrose and glycerol strongly protected the cells against inactivation.

In this study dynamic microbial inactivation experiments are exploited for performing parameter identification of a non-linear microbial model. For that purpose microbial inactivation data are produced and a differential equation exhibiting a shoulder and a loglinear phase is employed. The derived parameter estimates from this method were used to perform predictions on an independent experimental set at fluctuating temperature. Joint confidence regions and asymptotic confidence intervals of the estimated parameters were compared with previous studies originating from parameter identification under isothermal conditions. The developed approach can provide more reliable estimates for realistic conditions compared to the usual or standard two step approach.

Prediction of the microbial growth rate as a response to changing temperatures is an important aspect in the control of food safety and food spoilage. Accurate model predictions of the microbial evolution ask for correct model structures and reliable parameter values with good statistical quality. Given the widely accepted validity of the Cardinal Temperature Model with Inflection (CTMI) [Rosso, L., Lobry, J. R., Bajard, S. and Flandrois, J. P., 1995. Convenient model to describe the combined effects of temperature and pH on microbial growth, Applied and Environmental Microbiology, 61: 610-616], this paper focuses on the accurate estimation of its four parameters (T(min), T(opt), T(max) and micro(opt)) by applying the technique of optimal experiment design for parameter estimation (OED/PE). This secondary model describes the influence of temperature on the microbial specific growth rate from the minimum to the maximum temperature for growth. Dynamic temperature profiles are optimized within two temperature regions ([15 degrees C, 43 degrees C] and [15 degrees C, 45 degrees C]), focusing on the minimization of the parameter estimation (co)variance (D-optimal design). The optimal temperature profiles are implemented in a computer controlled bioreactor, and the CTMI parameters are identified from the resulting experimental data. Approximately equal CTMI parameter values were derived irrespective of the temperature region, except for T(max). The latter could only be estimated accurately from the optimal experiments within [15 degrees C, 45 degrees C]. This observation underlines the importance of selecting the upper temperature constraint for OED/PE as close as possible to the true T(max). Cardinal temperature estimates resulting from designs within [15 degrees C, 45 degrees C] correspond with values found in literature, are characterized by a small uncertainty error and yield a good result during validation. As compared to estimates from non-optimized dynamic experiments, more reliable CTMI parameter values were obtained from the optimal experiments within [15 degrees C, 45 degrees C].