Darwinian fitness is maximised at a temperature below Topt, but what this temperature is remains unclear. By linking our previous work on the Biokinetic Spectrum for Temperature with a model for temperature-dependent biological growth rate we obtain a plausible value for such a temperature. We find this approach reveals considerable commonalities in how life responds to temperature with implications that follow in evolution, physiology and ecology. We described a data set consisting of 17,021 observations of temperature-dependent population growth rates from 2411 bacterial, archaeal and eukaryal strains. We fitted a thermodynamic model to describe the strains' temperature-dependent growth rate curves that assumed growth was limited by a single rate-limiting enzyme. We defined Umes as an empirical measure of the temperature at which strains grew as fast and also as efficiently as possible. We propose that Darwinian fitness is optimised at Umes by trading-off growth rate and physiological efficiency. Using the full data set we calculated the Biokinetic Spectrum for Temperature (BKST): the distribution of temperature-dependent growth rates for each temperature. We used quantile regression to fit alternative models to the BKST to obtain quantile curves. A quantile is a value that contains a particular proportion of the data. The quantile curves suggested commonalities in temperature-dependencies spanning taxa and ecotype, consistent with the single rate-limiting enzyme concept. We showed that on the log scale, the slopes of the quantile curves were the same as the slopes of the thermodynamic model growth curves at Umes. This was true for Bacteria, Archaea, and Eukarya, and across other conditions (pH, water activity, metabolic type and trophic type). We showed that the quantile curves were the loci of the temperatures and growth rates that optimised Darwinian fitness for each strain at a given temperature-dependence and independently of other conditions. The quantile curves for Archaea and Bacteria shared a number of similarities attributable to the influence of the properties of water on protein folding. Other implications have impact on evolutionary biology, ecology, and physiology. The model predicts the existence of eurythermic strains that grow with about equal efficiency over a broad temperature range. These strains will have higher evolutionary rates with lower mutational costs that are independent of environmental conditions, a factor likely to have been significant during the Precambrian if the early Earth was warmer than today. The model predicts that random mutations are likely to result in shifts along the quantile curves and not across them. It predicts that some psychrophiles will be capable of performing well under climate change, and that selection will favour faster growth rates as the temperature increases. Last, it predicts trade-offs between growth rate and soma production, so that temperature-dependence, and possibly Darwinian fitness, remain constant over a broad temperature range and growth rates.

Life on Earth spans a range of temperatures and exhibits biological growth rates that are temperature dependent. While the observation that growth rates are temperature dependent is well known, we have recently shown that the statistical distribution of specific growth rates for life on Earth is a function of temperature (Corkrey et al., 2016). The maximum rates of growth of all life have a distinct limit, even when grown under optimal conditions, and which vary predictably with temperature. We term this distribution of growth rates the biokinetic spectrum for temperature (BKST). The BKST possibly arises from a trade-off between catalytic activity and stability of enzymes involved in a rate-limiting Master Reaction System (MRS) within the cell. We develop a method to extrapolate quantile curves for the BKST to obtain the posterior probability of the maximum rate of growth of any form of life on Earth. The maximum rate curve conforms to the observed data except below 0 degrees C and above 100 degrees C where the predicted value may be positively biased. The deviation below 0 degrees C may arise from the bulk properties of water, while the degradation of biomolecules may be important above 100 degrees C. The BKST has potential application in astrobiology by providing an estimate of the maximum possible growth rate attainable by terrestrial life and perhaps life elsewhere. We suggest that the area under the maximum growth rate curve and the peak rate may be useful characteristics in considerations of habitability. The BKST can serve as a diagnostic for unusual life, such as second biogenesis or non-terrestrial life. Since the MRS must have been heavily conserved the BKST may contain evolutionary relics. The BKST can serve as a signature summarizing the nature of life in environments beyond Earth, or to characterize species arising from a second biogenesis on Earth.

[This corrects the article DOI: 10.1371/journal.pone.0153343.].

Predictive microbiology is based on the premise that the responses of populations of microorganisms to environmental factors are reproducible and that by characterizing foods in terms of those factors, it is possible, from past observations, to predict the responses of those micro organisms in other analogous environments. This knowledge is summarized in mathematical models to enable prediction of the behavior of microbial populations in foods over time. Predictive microbiology is a powerful tool to aid microbial food safety and quality assurance, both in its own right and to complement hazard analysis and critical control points programs, hurdle technology, and quantitative microbial risk assessment.

Life on Earth is capable of growing from temperatures well below freezing to above the boiling point of water, with some organisms preferring cooler and others hotter conditions. The growth rate of each organism ultimately depends on its intracellular chemical reactions. Here we show that a thermodynamic model based on a single, rate-limiting, enzyme-catalysed reaction accurately describes population growth rates in 230 diverse strains of unicellular and multicellular organisms. Collectively these represent all three domains of life, ranging from psychrophilic to hyperthermophilic, and including the highest temperature so far observed for growth (122 °C). The results provide credible estimates of thermodynamic properties of proteins and obtain, purely from organism intrinsic growth rate data, relationships between parameters previously identified experimentally, thus bridging a gap between biochemistry and whole organism biology. We find that growth rates of both unicellular and multicellular life forms can be described by the same temperature dependence model. The model results provide strong support for a single highly-conserved reaction present in the last universal common ancestor (LUCA). This is remarkable in that it means that the growth rate dependence on temperature of unicellular and multicellular life forms that evolved over geological time spans can be explained by the same model.

Nutrition is well outside my area of expertise although my first degree was in Agriculture in which Animal Physiology and nutrition was an important part of the course. More recently at UTas we have had several research projects the aim of which was to discover microbial sources of polyunsaturated fatty acids. Thraustochytrids were the most promising organisms and an interesting outcome was that these grew in media with no added salt without affecting PUFA production. Several studies have optimised PUFA production by varying media composition, salinity and temperature. Optimum growth rates were at 25e30 oC and continued to a minimum of 5e10 oC, similar to many other marine organisms including bacteria. That is they fit into the thermal category of psychrotropic organisms which merge with mesophiles as temperatures increase. Temperature plays a major role in the rate at which biological populations develop and potentiates the effect of other factors such as oxygen availability, salinity, hydrostatic pressure and pH. In microbiology time scales range from milliseconds for enzyme catalysed reactions to doubling times of ~7 minutes for Clostridium perfringens, to days, weeks or months for psychrophilic bacteria growing optimally, to > 3.5 billion years to reach the current level of evolutionary adaptation. The temperature dependence of biological process rates requires knowledge of microbial ecology (rate of population increase) and physiology (biochemical reaction rates and physiological control in individual cells). The integration of these disciplines into ecophysiological studies supported by omics technologies is necessary to underpin advances in understanding how to inhibit or stimulate microbial growth. At UTas we have studied the ecophysiology of food borne bacteria including pathogens and spoilage organisms for 40 years. The original aim was to produce mathematical models to predict the rate of growth or decline of populations in foods, and this continues but in the last decade we have expanded into other ecosystems. The field of Predictive Microbiology has changed the paradigm of foodmicrobiology from one of testing and retrospective reporting of results to prospective reporting based on the temperature history of a process interpreted by a predictive model. A major outcome of this work was mandating the use of the Refrigeration Index by The Australian Quarantine Inspection Service in the revised Export Control Meat and Meat Products) Order, AQIS 2005(http://www.daffa.gov.au/aqis/export/meat/elmer-3). The models developed and validated to that time were empirical and the current state of the art can be found in Corkrey et.al 2014, the abstract of which is reproduced below: “Life on Earth is capable of growing from temperatureswell below freezing to above the boiling point of water, with some organisms preferring cooler and others hotter conditions. The growth rate of each organism ultimately depends on its intracellular chemical reactions. Here we show that a thermodynamic model based on a single, rate-limiting, enzyme-catalysed reaction accurately describes population growth rates in 230 diverse strains of unicellular and multicellular organisms. Collectively these represent all three domains of life, ranging from psychrophilic to hyperthermophilic, and including the highest temperature so far observed for growth (122 C). The results provide credible estimates of thermodynamic properties of proteins and obtain, purely from organism intrinsic growth rate data, relationships betweenparameterspreviously identifiedexperimentally, thusbridgingagap between biochemistry and whole organism biology. We find that growth rates of both unicellular and multicellular life forms can be described by the same temperature dependence model. The model results provide strong support for a single highly-conserved reaction present in the last universal common ancestor (LUCA). This is remarkable in that itmeans that the growth rate dependence on temperature of unicellular and multicellular life forms that evolved over geological time spans can be explainedby the samemodel”. Progress in integrating applications in food quality, safety and security will be reported in November.

Marine microheterotrophs thraustochytrids are emerging as a potential source for commercial production of polyunsaturated fatty acids (PUFA) that have nutritional and pharmacological values. With prospective demand for PUFAs increasing, biotechnological companies are looking for potential increases in those valuable products. However, high levels of NaCl in the culture media required for optimal thraustochytrid growth and PUFA production poses a significant problem to the biotechnological industry due to corrosion of fermenters calling for a need to reduce the amount of NaCl in the culture media, without imposing penalties on growth and yield of cultured organisms. Earlier, as reported by Shabala et al. (Environ Microbiol 11:1835–1843, 2009), we have shown that thraustochytrids use sodium predominantly for osmotic adjustment purposes and, as such, can be grown in low-salt environment without growth penalties, providing the media osmolality is adjusted. In this study, we verify if that conclusion, made for one specific strain and osmolyte only, is applicable to the larger number of strains and organic osmotica, as well as address the issue of yield quality (e.g., PUFA production in low-saline media). Using mannitol and sucrose for osmotic adjustment of the growth media enabled us to reduce NaCl concentration down to 1 mM; this is 15–100-fold lower than any method proposed so far. At the same time, the yield of essential PUFAs was increased by 15 to 20 %. Taken together, these results suggest that the proposed method can be used in industrial fermenters for commercial PUFA production.

We review early work on the microbial growth curve and the concept of balanced growth followed by commentary on the stringent response and persister cells. There is a voluminous literature on the effect of antibiotics on resistance and persistence and we call for a greater focus in food microbiology on the effect of biocides in the same context. We also raise potential issues in development of resistance arising from "source-sink" dynamics and from horizontal gene transfer. Redox potential is identified as crucial in determining microbial survival or death, and the recently postulated role for reactive oxygen species in signalling also considered."Traditional" predictive microbiology is revisited with emphasis on temperature dependence. We interpret the temperature vs growth rate curve as comprising 11 regions, some well-recognised but others leading to new insights into physiological responses. In particular we are intrigued by a major disruption in the monotonic rate of inactivation at a temperature, slightly below the actual maximum temperature for growth. This non-intuitive behaviour was earlier reported by other research groups and here we propose that it results from a rapid metabolic switch from the relaxed growth state to the stringent survival state.Finally, we envision the future of predictive microbiology in which models morph from empirical to mechanistic underpinned by microbial physiology and bioinformatics to grow into Systems Biology. (C) 2012 Elsevier Ltd. All rights reserved.

BackgroundMathematical models exist that quantify the effect of temperature on poikilotherm growth rate. One family of such models assumes a single rate-limiting 'master reaction' using terms describing the temperature-dependent denaturation of the reaction's enzyme. We consider whether such a model can describe growth in each domain of life.Methodology/principal findingsA new model based on this assumption and using a hierarchical Bayesian approach fits simultaneously 95 data sets for temperature-related growth rates of diverse microorganisms from all three domains of life, Bacteria, Archaea and Eukarya. Remarkably, the model produces credible estimates of fundamental thermodynamic parameters describing protein thermal stability predicted over 20 years ago.Conclusions/significanceThe analysis lends support to the concept of universal thermodynamic limits to microbial growth rate dictated by protein thermal stability that in turn govern biological rates. This suggests that the thermal stability of proteins is a unifying property in the evolution and adaptation of life on earth. The fundamental nature of this conclusion has importance for many fields of study including microbiology, protein chemistry, thermal biology, and ecological theory including, for example, the influence of the vast microbial biomass and activity in the biosphere that is poorly described in current climate models.

Aims: To elucidate the potential use of microelectrode ion flux measurements to evaluate bacterial responses to heat treatment.Methods and Results: Escherichia coli K12 Was used as a test bacterium to determine whether various heat treatments (55-70 degrees C for 15 min) affected net ion flux across E coli cell membranes using the MIFE (TM) system to measure net K+ fluxes. No difference in K+ fluxes was observed before and after heat treatments regardless of the magnitude of the treatment. Applying hyperosmotic stress (3% NaCl w/v) during flux measurement led to a net K+ loss from the heat treated E cote cells below 65 degrees C as Well as from nonheated cells. In contrast, with E. coli cells treated at and above 65 degrees C, hyperosmotic stress disrupted the pattern of K+ flux observed at lower temperatures and resulted in large flux noise with random scatter. This phenomenon Was particularly apparent above 70 degrees C. Although E. cote cells lost the potential to recover and grow at and above 62 degrees C, K+ flux disruption was not clearly observed until 68 degrees C was reached.Conclusions: No changes in net K+ flux from heat stressed E. coli cells were observed directly as a result of thermal treatments. However, regardless of the magnitude of heat treatment above 55 degrees C, loss of viability indicated by enrichment culture correlated with disrupted K+ fluxes when previously heated cells were further challenged by imposing hyperosmotic stress during flux measurement. This two-stage process enabled evaluation of the lethality of heat treated bacterial cells within 2 h and may be an alternative and more rapid method to confirm the lethality of heat treatment.Significance and Impact of the Study: The ability to confirm the lethality of thermal treatments and to specify minimal time/temperature combinations by a nonculture-dependent test offers an alternative system to culture based methods

Aims: To investigate the relative role of the red dry and rough (rdar) and brown dry and rough (bdar) morphotypes on hydrophobicity and ability to attach to abiotic surfaces of poultry-associated Salmonella strains with a focus on S. Sofia.Methods and Results: Cellulose synthase gene null mutants were constructed in five Salmonella strains converting them from rdar to bdar morphotypes. One S. Sofia null mutant displayed reduced hydrophobicity and attachment to Teflon (R) relative to its parent strain. The S. Virchow and S. Infantis null mutants attached less well to glass relative to their parent strains.Conclusions: The rdar or bdar morphotype may influence S. Sofia persistence but did not explain why bdar strains predominate in this serotype.Significance and Impact of the Study: This work provides some insight into why some Salmonella strains survive in poultry environments and may ultimately contribute to their control.

The term ecophysiology suggests that a natural connection exists between microbial ecology and microbial physiology, the former being concerned with the responses of microbial populations to environmental influences, and the latter with activities within individual cells. In this contribution we choose to integrate these as far as possible and also indicate how understanding of both is benefiting from advances in molecular biology and informatics. We consider how microbial dispersal relates to microbial survival, recovery and proliferation, including the significance of random factors (stochasticity) in continuation of bacterial lineages, observing that minor environmental changes, can greatly influence the potential for food-borne disease. Homeostasis and membrane transport are identified as potential targets to control food-borne pathogens and the role of compatible solutes in stress protection is presented. Phenotypic variation in genetically homogeneous populations is highlighted as a major component of the overall microbial survival strategy. The marked influence and potential of predictive microbiology as an aid to food safety management is discussed, as is the need for greater knowledge of the ecophysiology of microbes in the growth/no growth region. The application of fundamental scientific principles, including thermodynamics, chemistry and microbial physiology is advocated as the basis for development of theory underpinning microbial ecophysiology. Advancing microbial food safety continues to require development of rapid, quantitative methods as an early warning system and mechanism to curtail microbial food-borne disease outbreaks. However, advances made by technologists and molecular biologists must be combined with knowledge of ecophysiology: e.g. biological rates will continue to constrain resolution of the recalcitrant problem of reducing the time required for enrichment processes. The discussion presented leads to the conclusion that microbial and molecular methods are appropriate for enumeration and prevalence studies but that predictive model development should continue for the purposes of comparative process control and to support the risk assessment paradigm. We conclude also that contributions of human error or complacency to microbial food-borne illness will continue to thwart the best efforts of microbiologists and technologists to reduce its incidence. Decision-support technologies reporting in real-time appear to have potential to make objective food safety decisions thereby reducing the impact of human indifference to the application of simple, but effective, food hygiene rules.

Herein we describe systems and technologies for the application of predictive models and the development of growth boundary models. The latter are supported by systematic analysis of the literature and are now used in risk assessments including those cold tolerant pathogens in minimally processed foods including dairy products. To promote further application of predictive models in the dairy industry and potential triple bottom line benefits we strongly advocate collaboration and integration of R&D at several levels.

Part 1 Foodborne pathogen surveillance and outbreak investigation: Surveillance for foodborne pathogens in humans Systems for real-time, linked foodborne pathogen surveillance Detection, investigation and control of outbreaks of foodborne disease Attributing the burden of foodborne disease to specific sources of infection Determining the economic costs and global burden of foodborne disease. Part 2 Subtyping of foodborne pathogens: Phenoytypic subtyping Pulsed-field gel electrophoresis and other commonly used molecular methods Emerging bacterial subtyping methods Development, validation and quality assurance of subtyping methods. Part 3 Molecular methods, genomics and other emerging approaches in the surveillance and study of foodborne pathogens: Sample preparation for detection by molecular biological methods A comparison of molecular technologies and genomotyping for tracing and strain characterization of Campylobacter isolates Investigating foodborne pathogens using comparative genomics Protein-based analysis and other new and emerging non-nucleic acid based methods Virulotyping Using ribotyping to trace foodborne aerobic sporeforming bacteria in the factory: a case study Biotracing: a novel concept in food safety integrating microbiology knowledge, complex systems approaches and probabilistic modeling. Part 4 Tracing pathogens in particular food chains: Red meat and game production chains and the abattoir Fish production chains Poultry and egg production chains Dairy production Molluscan shellfish production chains Fruit and vegetable production chains.

Salmonella can adhere to poultry and food contact surfaces and persist to cause diseases. Adhesion of Salmonella Sofia (n = 14), S. Typhimurium (n = 6), S. Infantis (n = 3) and S. Virchow (n = 2) to Teflon®, stainless steel, glass, rubber and polyurethane were assayed using epifluorescence microscopy. Surface free energies of bacteria and materials were calculated using contact angle values and interfacial free energy between isolates and materials determined. Surface roughness of the materials was analysed using atomic force microscopy. S. Sofia isolates adhered in higher numbers (P < 0.05) to all materials compared to other serovars. The mean number of cells of S. Sofia isolates attaching to Teflon® were significantly higher (P < 0.05) compared to all materials except stainless steel (P > 0.05). Mean roughness values ranged from 82.26 nm (Teflon®) to 1.34 nm (glass). Correlations between the apolar component of the surface free energy of materials (γSLW) and bacterial adhesion (R2 = 0.80), and between γSLW and the surface roughness of the materials (R2 = 0.71) were found. Materials more positive in interfacial free energies had the highest number of adhering bacteria. Generalised surface property measurements were found to be useful in characterising Salmonella attachment but the degree of variability in results suggests that other factors, such as flagella or membrane proteins, could also contribute.

A non-invasive ion-selective microelectrode technique was used to elucidate the ionic mechanisms of osmotic adjustment in a marine protist thraustochytrid. Hypoosmotic stress caused significant efflux of Na(+), Cl(-) and K(+) from thraustochytrid cells. Model calculations showed that almost complete osmotic adjustment was achieved within the first 30 min after stress onset. Of these, sodium was the major contributor (more than half of the total osmotic adjustment), with chloride being the second major contributor. The role of K(+) in the process of osmotic adjustment was relatively small. Changes in Ca(2+) and H(+) flux were attributed to intracellular signalling. Ion flux data were confirmed by growth experiments. Thraustochytrium cells showed normal growth patterns even when grown in a sodium-free solution provided the medium osmolality was adjusted by mannitol to one of the seawater. That suggests that the requirement of sodium for thraustochytrid growth cycle is due to its role in cell osmotic adjustment rather than because of the direct Na(+) involvement in cell metabolism. Altogether, these data demonstrate the evidence for turgor regulation in thraustochytrids and suggest that these cells may be grown in the absence of sodium providing that cell turgor is adjusted by some other means.

The commercial preparation of safe foods is widely considered to be best managed by 'pre-requisite programs' in combination with the Hazard Analysis Critical Control Point (HACCP) strategy. Formal risk assessment approaches have latterly been promoted and developed by national governments and international organisations for the purposes of establishing objective and fair rules for international trade in foods and for setting food safety management priorities and consequent regulatory actions. These initiatives are likely to affect the management of microbial food safety in industry. This chapter briefly describes the principles of and approaches to microbial risk assessment (MRA). The terminology of MRA, and its origins, are described and its application to managing the risk of foodborne pathogens and their toxins, including its integration with HACCP, are considered. It is suggested that the application of the tools and techniques of MRA in the food industry can assist in elucidating optimal food safety control options, identifying CCPs and specifying their limits and appropriate corrective actions. Thus, rather than replacing HACCP, MRA will help to optimise the HACCP systems of the food industry and individual food businesses to improve product safety and overall public health. Additionally, MRA can facilitate innovation in the food industry because it provides an agreed method for demonstration of the food safety equivalence of alternative processing technologies and formulations. Currently MRA is a high-level, resource- and time-intensive activity. Increasingly, the approaches of MRA are being applied to narrower food safety decisions, involving the development of 'fit-for-purpose' approaches to MRA. Examples are presented of the use of MRA approaches to support decision making by food businesses.

This paper considers the future of predictive microbiology by exploring the balance that exists between science, applications and expectations. Attention is drawn to the development of predictive microbiology as a sub-discipline of food microbiology and of technologies that are required for its applications, including a recently developed biological indicator. As we move into the era of systems biology, in which physiological and molecular information will be increasingly available for incorporation into models, predictive microbiologists will be faced with new experimental and data handling challenges. Overcoming these hurdles may be assisted by interacting with microbiologists and mathematicians developing models to describe the microbial role in ecosystems other than food. Coupled with a commitment to maintain strategic research, as well as to develop innovative technologies, the future of predictive microbiology looks set to fulfil “great expectations”.