A protocol for the cultivation and monitoring of ileal gut microbiota surrogates.

AIMS: This research aimed to develop and validate a cultivation and monitoring protocol that is suitable for a surrogate microbial community that accounts for the gut microbiota of the ileum of the small intestine. METHODS AND RESULTS: Five bacterial species have been selected as representatives of the ileal gut microbiota and a general anaerobic medium (MS-BHI, as minimally supplemented brain heart infusion) has been constructed and validated against BCCM/LGM recommended and commercial media. Moreover, appropriate selective/differential media have been investigated for monitoring each ileal gut microbiota surrogate. Results showed that MS-BHI was highly efficient in displaying individual and collective behaviour of the ileal gut microbiota species, when compared with other types of media. Likewise, the selective/differential media managed to identify and describe the behaviour of their targeted species. CONCLUSIONS: MS-BHI renders a highly efficient, inexpensive and easy-to-prepare cultivation and enumeration alternative for the surrogate ileal microbiota species. Additionally, the selective/differential media can identify and quantify the bacteria of the surrogate ileal microbial community. SIGNIFICANCE AND IMPACT OF STUDY: The selected gut microbiota species can represent an in vitro ileal community, forming the basis for future studies on small intestinal microbiota. MS-BHI and the proposed monitoring protocol can be used as a standard for gut microbiota studies that utilize conventional microbiological techniques.

Effect of microstructure and initial cell conditions on thermal inactivation kinetics and sublethal injury of Listeria monocytogenes in fish-based food model systems.

The development of more accurate predictive models that describe the microbial kinetics of mild thermal treatments of foods requires knowledge concerning the influence of food microstructure and initial cell conditions on foodborne pathogens' inactivation kinetics. The effect of food microstructure and initial cell conditions on thermal inactivation kinetics and sublethal injury (SI) of Listeria monocytogenes was investigated at 59, 64 and 69°C. Fish-based food model systems with different microstructures, possessing minimal compositional and physicochemical variations, were used. L. monocytogenes growth morphology had no significant influence on thermal inactivation kinetics. A gelled matrix resulted in a lower specific inactivation rate kmax and a higher residual cell population Nres, while the presence of fat droplets resulted in a higherkmaxand did not influenceNres. SI was higher in viscous than in gelled systems and more prominent for cells that were grown inside the matrix. Hence, predictive thermal inactivation models could benefit from the inclusion of factors related to the nature of the food matrix and fat properties. Starting inactivation from cells that were grown inside the matrix, resulted in lower (i.e., fail-safe)kmaxvalues and more uncertainty onNres as compared to starting from cells grown at optimal conditions.

Mechanistic modelling of the inhibitory effect of pH on microbial growth.

Modelling and simulation of microbial dynamics as a function of processing, transportation and storage conditions is a useful tool to improve microbial food safety and quality. The goal of this research is to improve an existing methodology for building mechanistic predictive models based on the environmental conditions. The effect of environmental conditions on microbial dynamics is often described by combining the separate effects in a multiplicative way (gamma concept). This idea was extended further in this work by including the effects of the lag and stationary growth phases on microbial growth rate as independent gamma factors. A mechanistic description of the stationary phase as a function of pH was included, based on a novel class of models that consider product inhibition. Experimental results on Escherichia coli growth dynamics indicated that also the parameters of the product inhibition equations can be modelled with the gamma approach. This work has extended a modelling methodology, resulting in predictive models that are (i) mechanistically inspired, (ii) easily identifiable with a limited work load and (iii) easily extended to additional environmental conditions.

Comparing design of experiments and optimal experimental design techniques for modelling the microbial growth rate under static environmental conditions.

Building secondary models that describe the growth rate as a function of multiple environmental conditions is often very labour intensive and costly. As such, the current research aims to assist in decreasing the required experimental effort by studying the efficacy of both design of experiments (DOE) and optimal experimental designs (OED) techniques. This is the first research in predictive microbiology (i) to make a comparison of these techniques based on the (relative) model prediction uncertainty of the obtained models and (ii) to compare OED criteria for the design of experiments with static (instead of dynamic) environmental conditions. A comparison of the DOE techniques demonstrated that the inscribed central composite design and full factorial design were most suitable. Five conventional and two tailor made OED criteria were tested. The commonly used D-criterion performed best out of the conventional designs and almost equally well as the best of the dedicated criteria. Moreover, the modelling results of the D-criterion were less dependent on the experimental variability and differences in the microbial response than the two selected DOE techniques. Finally, it was proven that solving the optimisation of the D-criterion can be made more efficient by considering the sensitivities of the growth rate relative to its value as Jacobian matrix instead of the sensitivities of the cell density measurements.

Modeling the effect of pH, water activity, and ethanol concentration on biofilm formation of Staphylococcus aureus.

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 aw (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 aw 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 aw 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 R2 of 0.978, 0.991, and 0.947 for pH, EtOH, and aw, 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.

Novel methods to monitor the biodegradation of polylactic acid (PLA) by Amycolatopsis orientalis and Amycolatopsis thailandensis.

Plastics are essential in modern life, but their conventional production is problematic due to environmental pollution and waste management issues. Polylactic acid (PLA) is a widely used bioplastic that is bio-based and biodegradable, making it a key player in the bioeconomy. PLA has been proven to be degradable in various settings, including aqueous, soil, and compost environments. However, monitoring and optimizing PLA biodegradation remains challenging. This study proposes methods to improve the quantification of PLA biodegradation by Amycolatopsis spp. Ultrasound treatments (10 s) significantly improved the enumeration of viable Amycolatopsis cells by breaking the pellets into quantifiable individual cells. A separation technique combining ultrasound (120 s) and 40 µm cell strainers effectively isolated PLA particles from biomass to quantify PLA weight loss. This enabled the monitoring of PLA biofragmentation. Finally, CO2 production was measured according to ISO 14852 to quantify mineralization. Integrating these methods provides an improved quantification for PLA biodegradation along its different stages. In a case study, this led to the construction of a carbon balance where 85.1% of initial carbon content was successfully tracked. The developed techniques for monitoring of PLA biodegradation are essential to design future waste management strategies for biodegradable plastics.

Interference of gastrointestinal barriers with antibiotic susceptibility of foodborne pathogens: an in vitro case study of ciprofloxacin and tetracycline against Salmonella enterica and Listeria monocytogenes.

Minimum inhibitory concentrations (MIC) assays are often questioned for their representativeness. Especially when foodborne pathogens are tested, it is of crucial importance to also consider parameters of the human digestive system. Hence, the current study aimed to assess the inhibitory capacity of two antibiotics, ciprofloxacin and tetracycline, against Salmonella enterica and Listeria monocytogenes, under representative environmental conditions. More specifically, aspects of the harsh environment of the human gastrointestinal tract (GIT) were gradually added to the experimental conditions starting from simple aerobic lab conditions into an in vitro simulation of the GIT. In this way, the effects of parameters including the anoxic environment, physicochemical conditions of the GIT (low gastric pH, digestive enzymes, bile acids) and the gut microbiota were evaluated. The latter was simulated by including a representative consortium of selected gut bacteria species. In this study, the MIC of the two antibiotics against the relevant foodborne pathogens were established, under the previously mentioned environmental conditions. The results of S. enterica highlighted the importance of the anaerobic environment when conducting such studies, since the pathogen thrived under such conditions. Inclusion of physicochemical barriers led to exactly opposite results for S. enterica and L. monocytogenes since the former became more susceptible to ciprofloxacin while the latter showed lower susceptibility towards tetracycline. Finally, the inclusion of gut bacteria had a bactericidal effect against L. monocytogenes even in the absence of antibiotics, while gut bacteria protected S. enterica from the effect of ciprofloxacin.

Macroscopic modeling of the growth and substrate consumption of wild type and genetically modified Pichia pastoris.

Pichia pastoris is a popular yeast platform to generate several industrially relevant products which have applications in a wide range of sectors. The complexities in the processes due to the addition of a foreign gene are not widely explored. Since these complexities can be dependent on the strain characteristics, promoter, and type of protein produced, it is vital to investigate the growth and substrate consumption patterns of the host to facilitate customized process optimization. In this study, the growth rates of P. pastoris GS115 wild type (WT) and genetically modified (GM) strains grown on glycerol and methanol in batch cultivation mode were estimated and the model providing the best representation of the true growth kinetics based on substrate consumption was identified. It was observed that the growth of P. pastoris exhibits Haldane kinetics on glycerol rather than the most commonly used Monod kinetics due to the inability of the latter to describe growth inhibition at high concentrations of glycerol. Whereas, the cardinal parameter model, a newly proposed model for this application, was found to be the best fitting to describe the growth of P. pastoris on methanol due to its ability to describe methanol toxicity. Interestingly, the findings from this study concluded that in both substrates, the genetically engineered strain exhibited a higher growth rate compared to the WT strain. Such an observation has not been established yet in other published works, indicating an opportunity to further optimize the carbon source feeding strategies when the host is grown in fed-batch mode.

Influence of Hurdle Technology on Foodborne Pathogen Survival in the Human Gastrointestinal Tract.

The application of several sublethal stresses in hurdle technology can exert microbial stress resistance, which, in turn, might enable foodborne pathogens to overcome other types of lethal stresses, such as the gastrointestinal barriers. The present study evaluated the survival of Salmonella Typhimurium and Listeria monocytogenes during simulated digestion, following exposure to combinations of water activity (aw), pH and storage temperature stresses. The results revealed that both pathogens survived their passage through the simulated gastrointestinal tract (GIT) with their previous habituation to certain hurdle combinations inducing stress tolerance. More specifically, the habituation to a low temperature or to a high pH resulted in the increased stress tolerance of Salmonella, while for Listeria, the cells appeared stress tolerant after exposure to a high temperature or to a low pH. Nonetheless, both pathogens expressed increased sensitivity after habituation to growth-limiting hurdle combinations. The survival of stress-tolerant pathogenic cells in the human GIT poses major public health issues, since it can lead to host infection. Consequently, further research is required to obtain a deeper understanding of the adaptive stress responses of foodborne bacteria after exposure to combinations of sublethal hurdles to improve the existing food safety systems.

Effect of food structure and buffering capacity on pathogen survival during in vitro digestion.

Even though a plethora of barriers are employed by the human gastrointestinal tract (GIT) to cope with invading pathogens, foodborne diseases are still a common problem. The survival of food pathogens in the GIT is known to depend on food carrier properties. The aim of this study was to investigate the influence of food buffering capacity and food structure on the survival of Salmonella Typhimurium and Listeria monocytogenes during simulated digestion, following contamination of different food model systems that had different combinations of fat and protein content. The results illustrated the strong protective properties of proteins, acting either as a strong buffering agent or as a physical barrier against gastric acidity, for both pathogens. In comparison, fat manifested a lower buffering capacity and weaker protective effects against the two pathogens. Intriguingly, a low fat content was often linked with increased microbial resistance. Nonetheless, both pathogens survived their transit through the simulated GIT in all cases, with S. Typhimurium exhibiting growth during intestinal digestion and L.monocytogenes demonstrating a healthy residual population at the end of the intestinal phase. These results corroborate the need for a deeper understanding regarding the mechanisms with which food affects bacterial survival in the human GIT.

Gut microbiota of the small intestine as an antimicrobial barrier against foodborne pathogens: Impact of diet on the survival of S. Typhimurium and L. monocytogenes during in vitro digestion.

The human gastrointestinal tract employs an assortment of chemical, enzymatic and immune barriers to impede pathogen colonization. An essential component of these barriers is the gut microbiota, which infers protection against ingested pathogens through its colonization resistance mechanisms. Specifically, the gut microbiota of the distal small intestine (ileum) renders a crucial line of defense, given that this location is regarded as an important interaction site. This study aimed to evaluate the impact of the ileal microbiota on the survival of the foodborne pathogens Salmonella enterica serotype Typhimurium and Listeria monocytogenes, utilizing an in vitro digestion model system. Moreover, the effect of diet on the gut microbiota colonization resistance mechanisms was assessed, by comparing a healthy (high fiber/low sugar) and a western diet (low fiber/high sugar). For S. Typhimurium, the results revealed that the digestion of a healthy diet led to a similar inactivation compared to the western diet, with the values of total log reduction being 0.83 and 0.82 log(CFU), respectively; yet the lack of readily accessible nutrients in the healthy diet combined with the acidic shock during gastric digestion caused the induction of stress tolerance to the pathogen. This resulted in increased pathogen survival in the presence of gut microbiota, with S. Typhimurium proliferating during the ileal phase with a maximum specific growth rate of 0.16 1/h. On the contrary, for L. monocytogenes, the healthy diet was associated with a greater inactivation than the western diet (total log reduction values: 3.08 and 1.30 log(CFU), respectively), which appeared strongly influenced by the encounter of the pathogen with the gut microbiota. Regarding the latter, the species Escherichia coli and Bacteroides thetaiotaomicron appeared to be the most prevalent in most cases. Finally, it was also demonstrated that the ileal microbiota colonization resistance mechanisms largely relied on competitive responses. The obtained knowledge of this research can contribute to the development and/or complementation of defensive strategies against pathogen infection, while also underlining the value of in vitro approaches.

Effects of Temperature and pH on Recombinant Thaumatin II Production by Pichia pastoris.

The sweet protein thaumatin is emerging as a promising sugar replacer in the market today, especially in the food and beverage sector. Rising demand for its production necessitates the large-scale extraction of this protein from its natural plant source, which can be limited in terms of raw material availability and production costs. Using a recombinant production technique via a yeast platform, specifically, Pichia pastoris, is more promising to achieve the product economically while maintaining batch-to-batch consistency. However, the bioproduction of recombinant proteins requires the identification of optimal process variables, constituting the maximal yield of the product of interest. These variables have a direct effect on the growth of the host organism and the secretion levels of the recombinant protein. In this study, two important environmental factors, pH, and temperature were assessed by cultivating P. pastoris in shake flasks to understand their influence on growth and the production levels of thaumatin II protein. The results from the pH study indicate that P. pastoris attained a higher viable cell density and secretion of protein at pH 6.0 compared to 5.0 when grown at 30 °C. Furthermore, within the three levels of temperatures investigated when grown at pH 6.0, the protein levels were the highest at 30 °C compared to 20 and 25 °C, whereas 25 °C exhibited the highest viable cell density. Interestingly, the trend observed from the qualitative effects of temperature and pH occurred in all the media that was investigated. These results broaden our understanding of how pH and temperature adjustment during P. pastoris cultivation aid in enhancing the production yields of thaumatin II prior to optimising the fed batch bioreactor operation.

Processing Method for the Quantification of Methanol and Ethanol from Bioreactor Samples Using Gas Chromatography-Flame Ionization Detection.

Methanol, a simple polar solvent, has been widely identified as an attractive carbon source to produce chemicals and fuels in bioprocesses. Specifically, to achieve recombinant protein production from methylotrophic yeasts, such as Pichia pastoris, this organic solvent can be used as a sole carbon source for growth and maintenance as well as an inducer for protein expression. However, if methanol feeding is not controlled well in such a fermentation process, accumulation of the solvent in the growth media will have a detrimental effect on the cells. Hence, monitoring the levels of methanol in these fermentation processes is a crucial step to ensure a healthy culture and maximum protein production. There are various techniques elaborated in the literature for monitoring methanol in cell cultures, but often, they appear to be expensive methods that are less affordable for many laboratories. This is because, in addition to the sophisticated equipment that is required for the analysis, the complexity of the samples retrieved from the bioprocesses necessitates laborious processing steps often involving expensive tools. In this study, a fast, simple, and sensitive method is developed to process biological samples by using the salting-out-assisted liquid-liquid extraction technique to quantify the concentration of methanol and ethanol using gas chromatography. On comparing the combinations of widely available salts and solvents, it was noticed that salting out using potassium carbonate followed by the liquid-liquid extraction of the analyte using ethyl acetate showed the best recovery. Followed by this, a validation test for the developed method was performed, which resulted in good peak resolution, linearity, and limit of detection for the quantitation of methanol and ethanol. By further assessing the tested combination, it was confirmed that its application could be extended to other matrices. Such an approach facilitates the possibility to monitor and control the methanol levels in fermentation and aids in bioprocess optimization.

Enhancing the biodegradation of (bio)plastic through pretreatments: A critical review.

As plastic packaging becomes nearly indispensable in the plastic economy, rigorous efforts have been made to recapture the material value form this waste stream, which is mostly composed of highly resistant plastics. Biodegradation offers an attractive alternative for conventional plastic waste treatment as this approach is environmentally friendly, has low cost and facilitates valorisation. Moreover, there is also an increasing interest in plastic pretreatments waste to enhance biodegradation. This review investigates the pretreatment methods that optimise plastic biodegradation by examining the process's mechanisms and key influencing factors, which can be categorised into: biotic factors, abiotic factors and polymer characteristics. Various types of chemical and physical pretreatments have demonstrated to effectively enhance biodegradation through oxidation and surface changes on the plastics, leading to increased bioconversion rates and biogas production. A critical evaluation of the various categories of pretreatment methods is presented. This evaluation leads to the conclusion that the category of non-thermal physical treatments is most promising, due to the relatively low energy requirements and the absence of a need for chemical additions. Moreover, non-thermal physical treatments have demonstrated application potential at large scale. Based on these conclusions, pretreatments are expected to be an integral part of the biodegradation of plastics within a circular economy approach.

An Accurate Method for Studying Individual Microbial Lag: Experiments and Computations.

Variability in the behavior of microbial foodborne pathogens and spoilers causes difficulties in predicting the safety and quality of food products during their shelf life. Therefore, the quantification of the individual microbial lag phase distribution is of high relevance to the field of quantitative microbial risk assessment. To construct models that predict the effect of changes in environmental conditions on the individual lag, an accurate determination of these distributions is required. Therefore, the current research focuses on the development of an experimental and computational method for accurate determination of individual lag phase distribution. The experimental method is unique in the sense that full liquid volumes are sampled without using dilutions to detect the final population, thereby minimizing experimental errors. Moreover, the method does not aim at the isolation of single cells but at a low number of cells. The fact that several cells can be present in the initial samples instead of having a single cell is considered by the computational method. This method relies on Monte Carlo simulation to predict the individual lag phase distribution for a given set of distribution parameters and maximum likelihood estimation to find the parameters that describe the experimental data best. The method was validated both through simulation and experiments and was found to deliver a desired accuracy.

A Population Balance Model to Describe the Evolution of Sublethal Injury.

The detection and quantification of sublethal injury (SI) of pathogenic microorganisms has become a common procedure when assessing the efficiency of microbial inactivation treatments. However, while a plethora of studies investigates SI in function of time, no suitable modelling procedure for SI data has been proposed thus far. In this study, a new SI model structure was developed that relies on existing microbial inactivation models. This model is based on the description of inactivation kinetics between the subpopulations of healthy, sublethally injured and dead cells. The model was validated by means of case studies on previously published results, modelled by different inactivation models, i.e., (i) log-linear inactivation; (ii) biphasic inactivation; and (iii) log-linear inactivation with tailing. Results were compared to those obtained by the traditional method that relies on calculating SI from independent inactivation models on non-selective and selective media. The log-linear inactivation case study demonstrated that the SI model is equivalent to the use of independent models when there can be no mistake in calculating SI. The biphasic inactivation case study illustrated how the SI model avoids unrealistic calculations of SI that would otherwise occur. The final case study on log-linear inactivation with tailing clarified that the SI model provides a more mechanistic description than the independent models, in this case allowing the reduction of the number of model parameters. As such, this paper provides a comprehensive overview of the potential and applications for the newly presented SI model.

Visible Light as an Antimicrobial Strategy for Inactivation of Pseudomonas fluorescens and Staphylococcus epidermidis Biofilms.

The increase of antimicrobial resistance is challenging the scientific community to find solutions to eradicate bacteria, specifically biofilms. Light-Emitting Diodes (LED) represent an alternative way to tackle this problem in the presence of endogenous or exogenous photosensitizers. This work adds to a growing body of research on photodynamic inactivation using visible light against biofilms. Violet (400 nm), blue (420 nm), green (570 nm), yellow (584 nm) and red (698 nm) LEDs were used against Pseudomonas fluorescens and Staphylococcus epidermidis. Biofilms, grown on a polystyrene surface, were irradiated for 4 h. Different irradiance levels were investigated (2.5%, 25%, 50% and 100% of the maximum irradiance). Surviving cells were quantified and the inactivation kinetic parameters were estimated. Violet light could successfully inactivate P. fluorescens and S. epidermidis (up to 6.80 and 3.69 log10 reduction, respectively), while blue light was effective only against P. fluorescens (100% of maximum irradiance). Green, yellow and red irradiation neither increased nor reduced the biofilm cell density. This is the first research to test five different wavelengths (each with three intensities) in the visible spectrum against Gram-positive and Gram-negative biofilms. It provides a detailed study of the potential of visible light against biofilms of a different Gram-nature.

Bioproduction of the Recombinant Sweet Protein Thaumatin: Current State of the Art and Perspectives.

There is currently a worldwide trend to reduce sugar consumption. This trend is mostly met by the use of artificial non-nutritive sweeteners. However, these sweeteners have also been proven to have adverse health effects such as dizziness, headaches, gastrointestinal issues, and mood changes for aspartame. One of the solutions lies in the commercialization of sweet proteins, which are not associated with adverse health effects. Of these proteins, thaumatin is one of the most studied and most promising alternatives for sugars and artificial sweeteners. Since the natural production of these proteins is often too expensive, biochemical production methods are currently under investigation. With these methods, recombinant DNA technology is used for the production of sweet proteins in a host organism. The most promising host known today is the methylotrophic yeast, Pichia pastoris. This yeast has a tightly regulated methanol-induced promotor, allowing a good control over the recombinant protein production. Great efforts have been undertaken for improving the yields and purities of thaumatin productions, but a further optimization is still desired. This review focuses on (i) the motivation for using and producing sweet proteins, (ii) the properties and history of thaumatin, (iii) the production of recombinant sweet proteins, and (iv) future possibilities for process optimization based on a systems biology approach.

A tutorial on uncertainty propagation techniques for predictive microbiology models: A critical analysis of state-of-the-art techniques.

Building mathematical models in predictive microbiology is a data driven science. As such, the experimental data (and its uncertainty) has an influence on the final predictions and even on the calculation of the model prediction uncertainty. Therefore, the current research studies the influence of both the parameter estimation and uncertainty propagation method on the calculation of the model prediction uncertainty. The study is intended as well as a tutorial to uncertainty propagation techniques for researchers in (predictive) microbiology. To this end, an in silico case study was applied in which the effect of temperature on the microbial growth rate was modelled and used to make simulations for a temperature profile that is characterised by variability. The comparison of the parameter estimation methods demonstrated that the one-step method yields more accurate and precise calculations of the model prediction uncertainty than the two-step method. Four uncertainty propagation methods were assessed. The current work assesses the applicability of these techniques by considering the effect of experimental uncertainty and model input uncertainty. The linear approximation was demonstrated not always to provide reliable results. The Monte Carlo method was computationally very intensive, compared to its competitors. Polynomial chaos expansion was computationally efficient and accurate but is relatively complex to implement. Finally, the sigma point method was preferred as it is (i) computationally efficient, (ii) robust with respect to experimental uncertainty and (iii) easily implemented.

Parameter estimations in predictive microbiology: Statistically sound modelling of the microbial growth rate.

When building models to describe the effect of environmental conditions on the microbial growth rate, parameter estimations can be performed either with a one-step method, i.e., directly on the cell density measurements, or in a two-step method, i.e., via the estimated growth rates. The two-step method is often preferred due to its simplicity. The current research demonstrates that the two-step method is, however, only valid if the correct data transformation is applied and a strict experimental protocol is followed for all experiments. Based on a simulation study and a mathematical derivation, it was demonstrated that the logarithm of the growth rate should be used as a variance stabilizing transformation. Moreover, the one-step method leads to a more accurate estimation of the model parameters and a better approximation of the confidence intervals on the estimated parameters. Therefore, the one-step method is preferred and the two-step method should be avoided.