Protein thermodynamics can be predicted directly from biological growth rates

Insights and challenges of insecticide resistance modelling in malaria vectors: a review

BACKGROUND

Malaria is one of the most devastating tropical diseases, resulting in loss of lives each year, especially in children under the age of 5 years. Malaria burden, related deaths and stall in the progress against malaria transmission is evident, particularly in countries that have moderate or high malaria transmission. Hence, mitigating malaria spread requires information on the distribution of vectors and the drivers of insecticide resistance (IR). However, owing to the impracticality in establishing the critical need for real-world information at every location, modelling provides an informed best guess for such information. Therefore, this review examines the various methodologies used to model spatial, temporal and spatio-temporal patterns of IR within populations of malaria vectors, incorporating pest-biology parameters, adopted ecological principles, and the associated modelling challenges.

METHODS

The review focused on the period ending March 2023 without imposing restrictions on the initial year of publication, and included articles sourced from PubMed, Web of Science, and Scopus. It was also limited to publications that deal with modelling of IR distribution across spatial and temporal dimensions and excluded articles solely focusing on insecticide susceptibility tests or articles not published in English. After rigorous selection, 33 articles met the review's elibility criteria and were subjected to full-text screening.

RESULTS

Results show the popularity of Bayesian geostatistical approaches, and logistic and static models, with limited adoption of dynamic modelling approaches for spatial and temporal IR modelling. Furthermore, our review identifies the availability of surveillance data and scarcity of comprehensive information on the potential drivers of IR as major impediments to developing holistic models of IR evolution.

CONCLUSIONS

The review notes that incorporating pest-biology parameters, and ecological principles into IR models, in tandem with fundamental ecological concepts, potentially offers crucial insights into the evolution of IR. The results extend our knowledge of IR models that provide potentially accurate results, which can be translated into policy recommendations to combat the challenge of IR in malaria control.

Model-driven insights into the effects of temperature on metabolism

Temperature affects cellular processes at different spatiotemporal scales, and identifying the genetic and molecular mechanisms underlying temperature responses paves the way to develop approaches for mitigating the effects of future climate scenarios. A systems view of the effects of temperature on cellular physiology can be obtained by focusing on metabolism since: (i) its functions depend on transcription and translation and (ii) its outcomes support organisms' development, growth, and reproduction. Here we provide a systematic review of modelling efforts directed at investigating temperature effects on properties of single biochemical reactions, system-level traits, metabolic subsystems, and whole-cell metabolism across different prokaryotes and eukaryotes. We compare and contrast computational approaches and theories that facilitate modelling of temperature effects on key properties of enzymes and their consideration in constraint-based as well as kinetic models of metabolism. In addition, we provide a summary of insights from computational approaches, facilitating integration of omics data from temperature-modulated experiments with models of metabolic networks, and review the resulting biotechnological applications. Lastly, we provide a perspective on how different types of metabolic modelling can profit from developments in machine learning and models of different cellular layers to improve model-driven insights into the effects of temperature relevant for biotechnological applications.

The effect of pH on the growth rate of Bacillus cereus sensu lato: Quantifying strain variability and modelling the combined effects of temperature and pH

In this study, the effect of pH, alone or in combination with temperature, on the maximum growth rate (μ_max) of B. cereus sensu lato was investigated. In phase 1, the effect of pH at 30 °C was studied for 16 mesophilic strains and 2 psychrotrophic strains of Bacillus cereus sensu lato. The μ_max vs. pH relationship was found to show a similar pattern for all the strains. Several pH models from literature were evaluated and the best performing 'growth rate vs. pH' model selected. A stochastic model was then developed to predict the maximum specific growth rate of mesophilic B. cereus at 30 °C as a function of pH, the intra-species variability being incorporated via considering the model parameters (e.g. pH_min) randomly distributed. The predicted maximum specific growth rates were acceptably close to independent published data. In phase 2, the combined effects of temperature and pH were studied. Growth rates were also generated at 15, 20 and 40 °C for a selection of strains and the pH model was fitted at each temperature. Interestingly, the results showed that the estimates for the pH_min parameter for mesophilic strains were lower at 20-30 °C than near the optimum temperature (40 °C), suggesting that experiments for the determination of this parameter should be conducted at lower-than-optimum temperatures. New equations were proposed for the relationship between temperature and the minimum pH-values, which were also consistent with the experimental growth boundaries. The parameters defining this equation quantify the minimum temperature for growth observed experimentally, the temperature of maximum enzyme stability and the maximum temperature for growth. Deviations from the Gamma hypothesis (multiplicative effects of environmental factors on the maximum specific growth rate) were observed near the growth limits, especially at 40 °C. To improve model performance, two approaches, one based on a minimum pH-term (doi: https://doi.org/10.3389/fmicb.2019.01510) and one based on an interaction term (doi: http://dx.doi.org/10.1016/S0168-1605(01)00640-7) were evaluated.

Diminished growth and vitality in juvenile Hydractinia echinata under anticipated future temperature and variable nutrient conditions

In a warming climate, rising seawater temperatures and declining primary and secondary production will drastically affect growth and fitness of marine invertebrates in the northern Atlantic Ocean. To study the ecological performance of juvenile hydroids Hydractinia echinata we exposed them to current and predicted water temperatures which reflect the conditions in the inter- and subtidal in combination with changing food availability (high and low) in laboratory experiments. Here we show, that the interplay between temperature stress and diminished nutrition affected growth and vitality of juvenile hydroids more than either factor alone, while high food availability mitigated their stress responses. Our numerical growth model indicated that the growth of juvenile hydroids at temperatures beyond their optimum is a saturation function of energy availability. We demonstrated that the combined effects of environmental stressors should be taken into consideration when evaluating consequences of climate change. Interactive effects of ocean warming, decreasing resource availability and increasing organismal energy demand may have major impacts on biodiversity and ecosystem function.

Temperature adaptation of soil microbial respiration in alpine, boreal and tropical soils: An application of the square root (Ratkowsky) model

Warming is expected to stimulate soil microbial respiration triggering a positive soil carbon-climate feedback loop while a consensus remains elusive regarding the magnitude of this feedback. This is partly due to our limited understanding of the temperature-adaptive response of soil microbial respiration, especially over broad climatic scales. We used the square root (Ratkowsky) model to calculate the minimum temperature for soil microbial respiration (T_min , which describes the temperature adaptation of soil microbial respiration) of 298 soil samples from alpine grasslands on the Tibetan Plateau and forest ecosystems across China with a mean annual temperature (MAT) range from -6°C to +25°C. The instantaneous soil microbial respiration was determined between 4°C and 28°C. The square root model could well fit the temperature effect on soil microbial respiration for each individual soil, with R² higher than 0.98 for all soils. T_min ranged from -8.1°C to -0.1°C and increased linearly with increasing MAT (R²  = 0.68). MAT dominantly regulated T_min variation when accounting simultaneously for multiple other drivers (mean annual precipitation, soil pH and carbon quality); an independent experiment showed that carbon availability had no significant effect on T_min . Using the relationship between T_min and MAT, soil microbial respiration after an increased MAT could be estimated, resulting in a relative increase in respiration with decreasing MAT. Thus, soil microbial respiration responses are adapted to long-term temperature differences in MAT. We suggest that T_min  = -5 + 0.2 × MAT, that is, every 1°C rise in MAT is estimated to increase T_min of respiration by approximately 0.2°C, could be used as a first approximation to incorporate temperature adaptation of soil microbial respiration in model predictions. Our results can be used to predict future changes in the response of soil microbial respiration to temperature over different levels of warming and across broad geographic scales with different MAT.

Short-Term Temperature Response of Leaf Respiration in Different Subtropical Urban Tree Species

Plant leaf respiration is one of the critical components of the carbon cycle in terrestrial ecosystems. To predict changes of carbon emissions from leaves to the atmosphere under a warming climate, it is, therefore, important to understand the thermodynamics of the temperature response of leaf respiration. In this study, we measured the short-term temperature response of leaf respiration from five different urban tree species in a subtropical region of southern China. We applied two models, including an empirical model (the Kavanau model) and a mechanistic model (Macromolecular Rate Theory, MMRT), to investigate the thermodynamic properties in different plant species. Both models are equivalent in fitting measurements of the temperature response of leaf respiration with no significant difference (p = 0.67) in model efficiency, while MMRT provides an easy way to determine the thermodynamic properties, i.e., enthalpy, entropy, and Gibbs free energy of activation, for plant respiration. We found a conserved temperature response in the five studied plant species, showing no difference in thermodynamic properties and the relative temperature sensitivity for different species at low temperatures (<42°C). However, divergent temperature response among species happened at high temperatures over 42°C, showing more than two-fold differences in relative respiration rate compared to that below 42°C, although the causes of the divergent temperature response remain unclear. Notably, the convergent temperature response at low temperatures could provide useful information for land surface models to improve predictions of climate change effects on plant respiration.

Phytoplankton thermal responses adapt in the absence of hard thermodynamic constraints

To better predict how populations and communities respond to climatic temperature variation, it is necessary to understand how the shape of the response of fitness-related rates to temperature evolves (the thermal performance curve). Currently, there is disagreement about the extent to which the evolution of thermal performance curves is constrained. One school of thought has argued for the prevalence of thermodynamic constraints through enzyme kinetics, whereas another argues that adaptation can-at least partly-overcome such constraints. To shed further light on this debate, we perform a phylogenetic meta-analysis of the thermal performance curves of growth rate of phytoplankton-a globally important functional group-controlling for environmental effects (habitat type and thermal regime). We find that thermodynamic constraints have a minor influence on the shape of the curve. In particular, we detect a very weak increase of maximum performance with the temperature at which the curve peaks, suggesting a weak "hotter-is-better" constraint. Also, instead of a constant thermal sensitivity of growth across species, as might be expected from strong constraints, we find that all aspects of the thermal performance curve evolve along the phylogeny. Our results suggest that phytoplankton thermal performance curves adapt to thermal environments largely in the absence of hard thermodynamic constraints.

Modeling and Exploiting Microbial Temperature Response

Temperature is an important parameter in bioprocesses, influencing the structure and functionality of almost every biomolecule, as well as affecting metabolic reaction rates. In industrial biotechnology, the temperature is usually tightly controlled at an optimum value. Smart variation of the temperature to optimize the performance of a bioprocess brings about multiple complex and interconnected metabolic changes and is so far only rarely applied. Mathematical descriptions and models facilitate a reduction in complexity, as well as an understanding, of these interconnections. Starting in the 19th century with the “primal” temperature model of Svante Arrhenius, a variety of models have evolved over time to describe growth and enzymatic reaction rates as functions of temperature. Data-driven empirical approaches, as well as complex mechanistic models based on thermodynamic knowledge of biomolecular behavior at different temperatures, have been developed. Even though underlying biological mechanisms and mathematical models have been well-described, temperature as a control variable is only scarcely applied in bioprocess engineering, and as a conclusion, an exploitation strategy merging both in context has not yet been established. In this review, the most important models for physiological, biochemical, and physical properties governed by temperature are presented and discussed, along with application perspectives. As such, this review provides a toolset for future exploitation perspectives of temperature in bioprocess engineering.

Experimental evolution of phytoplankton fatty acid thermal reaction norms

Temperature effects on the fatty acid (FA) profiles of phytoplankton, major primary producers in the ocean, have been widely studied due to their importance as industrial feedstocks and to their indispensable role as global producers of long-chain, polyunsaturated FA (PUFA), including omega-3 (ω3) FA required by organisms at higher trophic levels. The latter is of global ecological concern for marine food webs, as some evidence suggests an ongoing decline in global marine-derived ω3 FA due to both a global decline in phytoplankton abundance and to a physiological reduction in ω3 production by phytoplankton as temperatures rise. Here, we examined both short-term (physiological) and long-term (evolutionary) responses of FA profiles to temperature by comparing FA thermal reaction norms of the marine diatom Thalassiosira pseudonana after ~500 generations (ca. 2.5 years) of experimental evolution at low (16°C) and high (31°C) temperatures. We showed that thermal reaction norms for some key FA classes evolved rapidly in response to temperature selection, often in ways contrary to our predictions based on prior research. Notably, 31°C-selected populations showed higher PUFA percentages (including ω3 FA) than 16°C-selected populations at the highest assay temperature (31°C, above T. pseudonana's optimum temperature for population growth), suggesting that high-temperature selection led to an evolved ability to sustain high PUFA production at high temperatures. Rapid evolution may therefore mitigate some of the decline in global phytoplankton-derived ω3 FA production predicted by recent studies. Beyond its implications for marine food webs, knowledge of the effects of temperature on fatty acid profiles is of fundamental importance to our understanding of the mechanistic causes and consequences of thermal adaptation.

The Biokinetic Spectrum for Temperature and optimal Darwinian fitness

Darwinian fitness is maximised at a temperature below T_opt, 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 U_mes 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 U_mes 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 U_mes. 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.

Rapid thermal adaptation in a marine diatom reveals constraints and trade-offs

Rapid evolution in response to environmental change will likely be a driving force determining the distribution of species across the biosphere in coming decades. This is especially true of microorganisms, many of which may evolve in step with warming, including phytoplankton, the diverse photosynthetic microbes forming the foundation of most aquatic food webs. Here we tested the capacity of a globally important, model marine diatom Thalassiosira pseudonana, for rapid evolution in response to temperature. Selection at 16 and 31°C for 350 generations led to significant divergence in several temperature response traits, demonstrating local adaptation and the existence of trade-offs associated with adaptation to different temperatures. In contrast, competitive ability for nitrogen (commonly limiting in marine systems), measured after 450 generations of temperature selection, did not diverge in a systematic way between temperatures. This study shows how rapid thermal adaptation affects key temperature and nutrient traits and, thus, a population's long-term physiological, ecological, and biogeographic response to climate change.

Temperature sensitivity of soil microbial activity modeled by the square root equation as a unifying model to differentiate between direct temperature effects and microbial community adaptation

Numerous models have been used to express the temperature sensitivity of microbial growth and activity in soil making it difficult to compare results from different habitats. Q10 still is one of the most common ways to express temperature relationships. However, Q10 is not constant with temperature and will differ depending on the temperature interval used for the calculation. The use of the square root (Ratkowsky) relationship between microbial activity (A) and temperature below optimum temperature, √A = a × (T-T_min ), is proposed as a simple and adequate model that allow for one descriptor, T_min (a theoretical minimum temperature for growth and activity), to estimate correct Q10-values over the entire in situ temperature interval. The square root model can adequately describe both microbial growth and respiration, allowing for an easy determination of T_min . Q10 for any temperature interval can then be calculated by Q10 = [(T + 10 - T_min )/(T-T_min )]² , where T is the lowest temperature in the Q10 comparison. T_min also describes the temperature adaptation of the microbial community. An envelope of T_min covering most natural soil habitats varying between -15°C (cold habitats like Antarctica/Arctic) to 0°C (tropical habitats like rain forests and deserts) is suggested, with an 0.3°C increase in T_min per 1°C increase in mean annual temperature. It is shown that the main difference between common temperature relationships used in global models is differences in the assumed temperature adaptation of the soil microbial community. The use of the square root equation will allow for one descriptor, T_min , determining the temperature response of soil microorganisms, and at the same time allow for comparing temperature sensitivity of microbial activity between habitats, including future projections.

Thermosensitivity of growth is determined by chaperone-mediated proteome reallocation

Maintenance of a properly folded proteome is critical for bacterial survival at notably different growth temperatures. Understanding the molecular basis of thermoadaptation has progressed in two main directions, the sequence and structural basis of protein thermostability and the mechanistic principles of protein quality control assisted by chaperones. Yet we do not fully understand how structural integrity of the entire proteome is maintained under stress and how it affects cellular fitness. To address this challenge, we reconstruct a genome-scale protein-folding network for Escherichia coli and formulate a computational model, FoldME, that provides statistical descriptions of multiscale cellular response consistent with many datasets. FoldME simulations show (i) that the chaperones act as a system when they respond to unfolding stress rather than achieving efficient folding of any single component of the proteome, (ii) how the proteome is globally balanced between chaperones for folding and the complex machinery synthesizing the proteins in response to perturbation, (iii) how this balancing determines growth rate dependence on temperature and is achieved through nonspecific regulation, and (iv) how thermal instability of the individual protein affects the overall functional state of the proteome. Overall, these results expand our view of cellular regulation, from targeted specific control mechanisms to global regulation through a web of nonspecific competing interactions that modulate the optimal reallocation of cellular resources. The methodology developed in this study enables genome-scale integration of environment-dependent protein properties and a proteome-wide study of cellular stress responses.

Temperature Sensitivity as a Microbial Trait Using Parameters from Macromolecular Rate Theory

The activity of soil microbial extracellular enzymes is strongly controlled by temperature, yet the degree to which temperature sensitivity varies by microbe and enzyme type is unclear. Such information would allow soil microbial enzymes to be incorporated in a traits-based framework to improve prediction of ecosystem response to global change. If temperature sensitivity varies for specific soil enzymes, then determining the underlying causes of variation in temperature sensitivity of these enzymes will provide fundamental insights for predicting nutrient dynamics belowground. In this study, we characterized how both microbial taxonomic variation as well as substrate type affects temperature sensitivity. We measured β-glucosidase, leucine aminopeptidase, and phosphatase activities at six temperatures: 4, 11, 25, 35, 45, and 60°C, for seven different soil microbial isolates. To calculate temperature sensitivity, we employed two models, Arrhenius, which predicts an exponential increase in reaction rate with temperature, and Macromolecular Rate Theory (MMRT), which predicts rate to peak and then decline as temperature increases. We found MMRT provided a more accurate fit and allowed for more nuanced interpretation of temperature sensitivity in all of the enzyme × isolate combinations tested. Our results revealed that both the enzyme type and soil isolate type explain variation in parameters associated with temperature sensitivity. Because we found temperature sensitivity to be an inherent and variable property of an enzyme, we argue that it can be incorporated as a microbial functional trait, but only when using the MMRT definition of temperature sensitivity. We show that the Arrhenius metrics of temperature sensitivity are overly sensitive to test conditions, with activation energy changing depending on the temperature range it was calculated within. Thus, we propose the use of the MMRT definition of temperature sensitivity for accurate interpretation of temperature sensitivity of soil microbial enzymes.

Genomic and metagenomic challenges and opportunities for bioleaching: a mini-review

High-throughput genomic technologies are accelerating progress in understanding the diversity of microbial life in many environments. Here we highlight advances in genomics and metagenomics of microorganisms from bioleaching heaps and related acidic mining environments. Bioleaching heaps used for copper recovery provide significant opportunities to study the processes and mechanisms underlying microbial successions and the influence of community composition on ecosystem functioning. Obtaining quantitative and process-level knowledge of these dynamics is pivotal for understanding how microorganisms contribute to the solubilization of copper for industrial recovery. Advances in DNA sequencing technology provide unprecedented opportunities to obtain information about the genomes of bioleaching microorganisms, allowing predictive models of metabolic potential and ecosystem-level interactions to be constructed. These approaches are enabling predictive phenotyping of organisms many of which are recalcitrant to genetic approaches or are unculturable. This mini-review describes current bioleaching genomic and metagenomic projects and addresses the use of genome information to: (i) build metabolic models; (ii) predict microbial interactions; (iii) estimate genetic diversity; and (iv) study microbial evolution. Key challenges and perspectives of bioleaching genomics/metagenomics are addressed.

Increased Biomass Production by Mesophilic Food-Associated Bacteria through Lowering the Growth Temperature from 30°C to 10°C

Five isolates from chilled food and refrigerator inner surfaces and closely related reference strains of the species Escherichia coli, Listeria monocytogenes, Staphylococcus xylosus, Bacillus cereus, Pedobacter nutrimenti, and Pedobacter panaciterrae were tested for the effect of growth temperature (30°C and 10°C) on biomass formation. Growth was monitored via optical density, and biomass formation was measured at the early stationary phase based on the following parameters in complex and defined media: viable cell count, total cell count, cell dry weight, whole-cell protein content, and cell morphology. According to the lack of growth at 1°C, all strains were assigned to the thermal class of mesophiles. Glucose and ammonium consumption related to cell yield were analyzed in defined media. Except for the protein content, temperature had a significant (t test, P < 0.05) effect on all biomass formation parameters for each strain. The results show a significant difference between the isolates and the related reference strains. Isolates achieved an increase in biomass production between 20% and 110% at the 10°C temperature, which is 15 to 25°C lower than their maximum growth rate temperatures. In contrast, reference strains showed a maximum increase of only about 25%, and some reference strains showed no increase or a decrease of approximately 25%. As expected, growth rates for all strains were higher at 30°C than at 10°C, while biomass production for isolates was higher at 10°C than at 30°C. In contrast, the reference strains showed similar growth yields at the two temperatures. This also demonstrates for mesophilic bacterial strains more efficient nutrient assimilation during growth at low temperatures. Until now, this characteristic was attributed only to psychrophilic microorganisms.

IMPORTANCE

For several psychrophilic species, increased biomass formation was described at temperatures lower than optimum growth temperatures, which are defined by the highest growth rate. This work shows increased biomass formation at low growth temperatures for mesophilic isolates. A comparison with closely related reference strains from culture collections showed a significantly smaller increase or no increase in biomass formation. This indicates a loss of specific adaptive mechanisms (e.g., cold adaptation) for mesophiles during long-term cultivation. The increased biomass production for mesophiles under low-temperature conditions opens new avenues for a more efficient biotechnological transformation of nutrients to microbial biomass. These findings may also be important for risk assessment of cooled foods since risk potential is often correlated with the cell numbers present in food samples.

Venturing into new realms? Microorganisms in space

One of the biggest challenges of science is the determination of whether extraterrestrial life exists. Although potential habitable areas might be available for complex life, it is more likely that microbial life could exist in space. Many extremotolerant and extremophilic microbes have been found to be able to withstand numerous, combined environmental factors, such as high or low temperatures and pressures, high-salt conditions, high doses of radiation, desiccation or nutrient limitations. They may even survive the transit from one planet to another. Terrestrial Mars-analogue sites are one focus of researchers, in order to understand the microbial diversity in preparation for upcoming space missions aimed at the detection of life. However, such missions could also pose a risk with respect to contamination of the extraterrestrial environment by accidentally transferred terrestrial microorganisms. Closer to the Earth, the International Space Station is the most enclosed habitat, where humans work and live-and with them numerous microorganisms. It is still unknown how microbes adapt to this environment, possibly even creating a risk for the crew. Information on the microbiology of the ISS will have an impact on the planning and implementation of long-term human spaceflights in order to ensure a safe, stable and balanced microbiome on board.

The Biokinetic Spectrum for Temperature

We identify and describe the distribution of temperature-dependent specific growth rates for life on Earth, which we term the biokinetic spectrum for temperature. The spectrum has the potential to provide for more robust modeling in thermal ecology since any conclusions derived from it will be based on observed data rather than using theoretical assumptions. It may also provide constraints for systems biology model predictions and provide insights in physiology. The spectrum has a Δ-shape with a sharp peak at around 42°C. At higher temperatures up to 60°C there was a gap of attenuated growth rates. We found another peak at 67°C and a steady decline in maximum rates thereafter. By using Bayesian quantile regression to summarise and explore the data we were able to conclude that the gap represented an actual biological transition between mesophiles and thermophiles that we term the Mesophile-Thermophile Gap (MTG). We have not identified any organism that grows above the maximum rate of the spectrum. We used a thermodynamic model to recover the Δ-shape, suggesting that the growth rate limits arise from a trade-off between activity and stability of proteins. The spectrum provides underpinning principles that will find utility in models concerned with the thermal responses of biological processes.

Real versus Artificial Variation in the Thermal Sensitivity of Biological Traits

Whether the thermal sensitivity of an organism's traits follows the simple Boltzmann-Arrhenius model remains a contentious issue that centers around consideration of its operational temperature range and whether the sensitivity corresponds to one or a few underlying rate-limiting enzymes. Resolving this issue is crucial, because mechanistic models for temperature dependence of traits are required to predict the biological effects of climate change. Here, by combining theory with data on 1,085 thermal responses from a wide range of traits and organisms, we show that substantial variation in thermal sensitivity (activation energy) estimates can arise simply because of variation in the range of measured temperatures. Furthermore, when thermal responses deviate systematically from the Boltzmann-Arrhenius model, variation in measured temperature ranges across studies can bias estimated activation energy distributions toward higher mean, median, variance, and skewness. Remarkably, this bias alone can yield activation energies that encompass the range expected from biochemical reactions (from ~0.2 to 1.2 eV), making it difficult to establish whether a single activation energy appropriately captures thermal sensitivity. We provide guidelines and a simple equation for partially correcting for such artifacts. Our results have important implications for understanding the mechanistic basis of thermal responses of biological traits and for accurately modeling effects of variation in thermal sensitivity on responses of individuals, populations, and ecological communities to changing climatic temperatures.

Habitability: A Review

Habitability is a widely used word in the geoscience, planetary science, and astrobiology literature, but what does it mean? In this review on habitability, we define it as the ability of an environment to support the activity of at least one known organism. We adopt a binary definition of "habitability" and a "habitable environment." An environment either can or cannot sustain a given organism. However, environments such as entire planets might be capable of supporting more or less species diversity or biomass compared with that of Earth. A clarity in understanding habitability can be obtained by defining instantaneous habitability as the conditions at any given time in a given environment required to sustain the activity of at least one known organism, and continuous planetary habitability as the capacity of a planetary body to sustain habitable conditions on some areas of its surface or within its interior over geological timescales. We also distinguish between surface liquid water worlds (such as Earth) that can sustain liquid water on their surfaces and interior liquid water worlds, such as icy moons and terrestrial-type rocky planets with liquid water only in their interiors. This distinction is important since, while the former can potentially sustain habitable conditions for oxygenic photosynthesis that leads to the rise of atmospheric oxygen and potentially complex multicellularity and intelligence over geological timescales, the latter are unlikely to. Habitable environments do not need to contain life. Although the decoupling of habitability and the presence of life may be rare on Earth, it may be important for understanding the habitability of other planetary bodies.

Microbial growth parameters obtained from the analysis of time to detection data using a novel rearrangement of the Baranyi-Roberts model

AIMS

To explore the predictions of a novel rearrangement of the Baranyi-Roberts model (BRM) with time to detection data obtained from optical density data of microbial growth.

METHODS AND RESULTS

Growth of Escherichia coli and Salmonella Typhimurium under mild conditions of temperature (25-37°C), salt (0·086, 0·51 and 1·03 mol l(-1)) and pH (6·85-4·5) was examined using optical density. Time to detection (TTD) data were fitted to a model based on a rearrangement of the BRM. Observations showed compatibility with standard viable count studies and produced highly accurate specific growth rates and lag phase durations. At high salt and low pH, however, there was a substantial dependency on the initial inoculum for the observation of visible growth. At 30 and 37°C, with 1·03 mol l(-1) salt, and at pH <5·75, no visible growth was recorded for E. coli at initial inoculum levels below 10(7) CFU ml(-1).

CONCLUSIONS

The rearranged BRM can be used directly with TTD data obtained from optical density measurements.

SIGNIFICANCE AND IMPACT OF THE STUDY

A distinct advantage of the rearranged model is that it allows for a very simple interpretation of easily obtainable data using standard nonlinear regression. The rearranged model gives to TTD data the same modelling capability that the BRM gives to plate count data.