Universality of thermodynamic constants governing biological growth rates

Host-microbiota-parasite interactions in two wild sparid fish species, Diplodus annularis and Oblada melanura (Teleostei, Sparidae) over a year: a pilot study

BACKGROUND

The microbiota in fish external mucus is mainly known for having a role in homeostasis and protection against pathogens, but recent evidence suggests it is also involved in the host-specificity of some ectoparasites. In this study, we investigated the influence of seasonality and environmental factors on both fish external microbiota and monogenean gill ectoparasites abundance and diversity and assessed the level of covariations between monogenean and bacterial communities across seasons. To do so, we assessed skin and gill microbiota of two sparid species, Oblada melanura and Diplodus annularis, over a year and collected their specific monogenean ectoparasites belonging to the Lamellodiscus genus.

RESULTS

Our results revealed that diversity and structure of skin and gill mucus microbiota were strongly affected by seasonality, mainly by the variations of temperature, with specific fish-associated bacterial taxa for each season. The diversity and abundance of parasites were also influenced by seasonality, with the abundance of some Lamellodiscus species significantly correlated to temperature. Numerous positive and negative correlations between the abundance of given bacterial genera and Lamellodiscus species were observed throughout the year, suggesting their differential interaction across seasons.

CONCLUSIONS

The present study is one of the first to demonstrate the influence of seasonality and related abiotic factors on fish external microbiota over a year. We further identified potential interactions between gill microbiota and parasite occurrence in wild fish populations, improving current knowledge and understanding of the establishment of host-specificity.

Links between host genetics, metabolism, gut microbiome and amoebic gill disease (AGD) in Atlantic salmon

Background

Rapidly spreading parasitic infections like amoebic gill disease (AGD) are increasingly problematic for Atlantic salmon reared in aquaculture facilities and potentially pose a risk to wild fish species in surrounding waters. Currently, it is not known whether susceptibility to AGD differs between wild and farmed salmon. Wild Atlantic salmon populations are declining and this emerging disease could represent an additional threat to their long-term viability. A better understanding of how AGD affects fish health is therefore relevant for the accurate assessment of the associated risk, both to farming and to the well-being of wild populations. In this study, we assessed the impact of natural exposure to AGD on wild, hybrid and farmed post-smolt Atlantic salmon reared in a sea farm together under common garden conditions.

Results

Wild fish showed substantially higher mortality levels (64%) than farmed fish (25%), with intermediate levels for hybrid fish (39%) suggesting that AGD susceptibility has an additive genetic basis. Metabolic rate measures representing physiological performance were similar among the genetic groups but were significantly lower in AGD-symptomatic fish than healthy fish. Gut microbial diversity was significantly lower in infected fish. We observed major shifts in gut microbial community composition in response to AGD infections. In symptomatic fish the relative abundance of key taxa Aliivibrio, Marinomonas and Pseudoalteromonas declined, whereas the abundance of Polaribacter and Vibrio increased compared to healthy fish.

Conclusions

Our results highlight the stress AGD imposes on fish physiology and suggest that low metabolic-rate fish phenotypes may be associated with better infection outcomes. We consider the role increased AGD outbreak events and a warmer future may have in driving secondary bacterial infections and in reducing performance in farmed and wild fish.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42523-022-00203-x.

The Effects of Temperature on Cellular Physiology

Temperature impacts biological systems across all length and timescales. Cells and the enzymes that comprise them respond to temperature fluctuations on short timescales, and temperature can affect protein folding, the molecular composition of cells, and volume expansion. Entire ecosystems exhibit temperature-dependent behaviors, and global warming threatens to disrupt thermal homeostasis in microbes that are important for human and planetary health. Intriguingly, the growth rate of most species follows the Arrhenius law of equilibrium thermodynamics, with an activation energy similar to that of individual enzymes but with maximal growth rates and over temperature ranges that are species specific. In this review, we discuss how the temperature dependence of critical cellular processes, such as the central dogma and membrane fluidity, contributes to the temperature dependence of growth. We conclude with a discussion of adaptation to temperature shifts and the effects of temperature on evolution and on the properties of microbial ecosystems.

Performance of the SSI development function compared with 33 other functions applied to 79 arthropod species' datasets

The development rates of arthropods are temperature-dependent. Studies aiming to predict the dynamics of arachnid, crustacean, and insect populations in nature often require the derivation of development functions representing this phenomenon. A previous study (Quinn, B.K., 2017, J. Therm. Biol. 63, 65-77) identified 33 development functions commonly used in past studies on temperature-dependent development of arthropods, and illustrated that: (1) most of 99 past studies only applied one or few (2-5) development functions to their data without considering others; and (2) most of a subset of 79 studies' data were not fit with the actual best function for them, resulting in sometimes substantial differences in model performance and predictive ability. However, that study did not test the class of development functions based on theoretical enzyme thermodynamics, including the Sharpe-Schoolfield-Ikemoto (SSI) function. Herein, the meta-analyses done in that previous study were redone, after fitting all 79 reanalyzed datasets with the SSI function. Estimates of the intrinsic optimum temperature (T_Φ) for development of each tested species were also derived using the SSI function and compared among taxa. Including the SSI function in analyses did not change the conclusions of the previous study concerning development function usage, choice, and consequences. Notably, the SSI function performed as well as or relatively better than other functions of comparable or lower complexity in terms of R², AIC_C-based rankings, ΔAIC_C values, and prediction errors, which may recommend its more widespread use in future studies. Overall differences in T_Φ were found among arthropod subphyla, as well as between most species pairs. Most T_Φ estimates produced herein were novel, and could be used to make inferences about or comparisons among arthropod taxa in future studies.

Impacts of global warming on marine microbial communities

Global warming in ocean ecosystems alters temperature, acidification, oxygen content, circulation, stratification, and nutrient inputs. Microorganisms play a dominant role in global biogeochemical cycles crucial for a planet's sustainability. Since microbial communities are highly dependent on the temperature factor, fluctuations in the same will lead to adverse effects on the microbial community organization. Throughout the Ocean, increase in evaporation rates causes the surface mixed layer to become shallower. This intensified stratification inhibits vertical transport of nutrient supplies. Such density driven processes will decrease oxygen solubility in surface waters leading to significant decrease of oxygen from future Ocean. Metabolism and diversity of microbes along with ocean biogeochemistry will be at great risk due to global warming and its related effects. As a response to the changes in temperature, alteration in the distribution of phytoplankta communities is observed all over the planet, creating changes in the primary production of the ocean causing massive impact on the biosphere. Marine microbial communities try to adapt to the changing ocean environmental conditions by responding with biogeographic range shifts, community structure modifications, and adaptive evolution. Persistence of this climate change on ocean ecosystems, in future, will pose serious threat to the metabolism and distribution of marine microbes leading to fluctuations in the biogeochemical cycles thereby affecting the overall ecosystem functioning. Genomics plays an important role in marine microbial research by providing tools to study the association between environment and organisms. The ecological and genomic perspectives of marine microbes are being investigated to design effective models to understand their physiology and evolution in a changing ocean. Mesocosm/microcosm experimental studies and field studies are in the need of the hour to evaluate the impact of climate shifts on microbial genesis.

Bacillus cereus in Packaging Material: Molecular and Phenotypical Diversity Revealed

The Bacillus cereus group has been isolated from soils, water, plants and numerous food products. These species can produce a variety of toxins including several enterotoxins [non-hemolytic enterotoxin (Nhe), hemolysin BL (Hbl), cytotoxin K, and enterotoxin FM], the emetic toxin cereulide and insecticidal Bt toxins. This is the first study evaluating the presence of B. cereus in packaging material. Among 75 different isolates, four phylogenetic groups were detected (II, III, IV, and VI), of which the groups III and IV were the most abundant with 46.7 and 41.3%, respectively. One isolate was affiliated to psychrotolerant group VI. Growth experiments showed a mesophilic predominance. Based on PCR analysis, nhe genes were detectable in 100% of the isolates, while hbl genes were only found in 50.7%. The cereulide encoding gene was found in four out of 75 isolates, no isolate carried a crystal toxin gene. In total, thirteen different toxin gene profiles were identified. We showed that a variety of B. cereus group strains can be found in packaging material. Here, this variety lies in the presence of four phylogenetic groups, thirteen toxin gene profiles, and different growth temperatures. The results suggest that packaging material does not contain significant amounts of highly virulent strains, and the low number of cereulide producing strains is in accordance with other results.

Longitudinal sampling of external mucosae in farmed European seabass reveals the impact of water temperature on bacterial dynamics

Fish microbiota are intrinsically linked to health and fitness, but they are highly variable and influenced by both biotic and abiotic factors. Water temperature particularly limits bacterial adhesion and growth, impacting microbial diversity and bacterial infections on the skin and gills. Aquaculture is heavily affected by infectious diseases, especially in warmer months, and industry practices often promote stress and microbial dysbiosis, leading to an increased abundance of potentially pathogenic bacteria. In this regard, fish mucosa health is extremely important because it provides a primary barrier against pathogens. We used 16 rRNA V4 metataxonomics to characterize the skin and gill microbiota of the European seabass, Dicentrarchus labrax, and the surrounding water over 12 months, assessing the impact of water temperature on microbial diversity and function. We show that the microbiota of external mucosae are highly dynamic with consistent longitudinal trends in taxon diversity. Several potentially pathogenic genera (Aliivibrio, Photobacterium, Pseudomonas, and Vibrio) were highly abundant, showing complex interactions with other bacterial genera, some of which with recognized probiotic activity, and were also significantly impacted by changes in temperature. The surrounding water temperature influenced fish microbial composition, structure and function over time (days and months). Additionally, dysbiosis was more frequent in warmer months and during transitions between cold/warm months. We also detected a strong seasonal effect in the fish microbiota, which is likely to result from the compound action of several unmeasured environmental factors (e.g., pH, nutrient availability) beyond temperature. Our results highlight the importance of performing longitudinal studies to assess the impact of environmental factors on fish microbiotas.

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.

Adaptive evolution shapes the present-day distribution of the thermal sensitivity of population growth rate

Developing a thorough understanding of how ectotherm physiology adapts to different thermal environments is of crucial importance, especially in the face of global climate change. A key aspect of an organism's thermal performance curve (TPC)-the relationship between fitness-related trait performance and temperature-is its thermal sensitivity, i.e., the rate at which trait values increase with temperature within its typically experienced thermal range. For a given trait, the distribution of thermal sensitivities across species, often quantified as "activation energy" values, is typically right-skewed. Currently, the mechanisms that generate this distribution are unclear, with considerable debate about the role of thermodynamic constraints versus adaptive evolution. Here, using a phylogenetic comparative approach, we study the evolution of the thermal sensitivity of population growth rate across phytoplankton (Cyanobacteria and eukaryotic microalgae) and prokaryotes (bacteria and archaea), 2 microbial groups that play a major role in the global carbon cycle. We find that thermal sensitivity across these groups is moderately phylogenetically heritable, and that its distribution is shaped by repeated evolutionary convergence throughout its parameter space. More precisely, we detect bursts of adaptive evolution in thermal sensitivity, increasing the amount of overlap among its distributions in different clades. We obtain qualitatively similar results from evolutionary analyses of the thermal sensitivities of 2 physiological rates underlying growth rate: net photosynthesis and respiration of plants. Furthermore, we find that these episodes of evolutionary convergence are consistent with 2 opposing forces: decrease in thermal sensitivity due to environmental fluctuations and increase due to adaptation to stable environments. Overall, our results indicate that adaptation can lead to large and relatively rapid shifts in thermal sensitivity, especially in microbes for which rapid evolution can occur at short timescales. Thus, more attention needs to be paid to elucidating the implications of rapid evolution in organismal thermal sensitivity for ecosystem functioning.

The Inflection Point Hypothesis: The Relationship between the Temperature Dependence of Enzyme-Catalyzed Reaction Rates and Microbial Growth Rates

The temperature dependence of biological rates at different scales (from individual enzymes to isolated organisms to ecosystem processes such as soil respiration and photosynthesis) is the subject of much historical and contemporary research. The precise relationship between the temperature dependence of enzyme rates and those at larger scales is not well understood. We have developed macromolecular rate theory (MMRT) to describe the temperature dependence of biological processes at all scales. Here we formalize the scaling relationship by investigating MMRT both at the molecular scale (constituent enzymes) and for growth of the parent organism. We demonstrate that the inflection point (T_inf) for the temperature dependence of individual metabolic enzymes coincides with the optimal growth temperature for the parent organism, and we rationalize this concordance in terms of the necessity for linearly correlated rates for metabolic enzymes over fluctuating environmental temperatures to maintain homeostasis. Indeed, T_inf is likely to be under strong selection pressure to maintain coordinated rates across environmental temperature ranges. At temperatures at which rates become uncorrelated, we postulate a regulatory catastrophe and organism growth rates precipitously decline at temperatures where this occurs. We show that the curvature in the plots of the natural log of the rate versus temperature for individual enzymes determines the curvature for the metabolic process overall and the curvature for the temperature dependence of the growth of the organism. We have called this "the inflection point hypothesis", and this hypothesis suggests many avenues for future investigation, including avenues for engineering the thermal tolerance of organisms.

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.

Prior Exposure to Dry-Cured Meat Promotes Resistance to Simulated Gastric Fluid in Salmonella Typhimurium

This study assessed if exposure of foodborne Salmonella enterica in Brazilian dry-cured loin (BDL) affects pathogen inactivation in simulated gastric fluid (SGF). The acid tolerance responses of three Salmonella enterica serovars, Typhimurium, Derby and Panama, were assessed by an acid challenge trial at pH 3.0 for 4 h following pre-adaptation to three conditions: neutral pH, acidic pH (4.5) or BDL matrix. The influence of Salmonella exposure temperature and time in the BDL on pathogen gastric fluid resistance was evaluated by the response surface methodology. The Salmonella serovars acquired acid tolerance when exposed to the BDL matrix and their response to acid stress was strain-dependent, with S. Typhimurium being the most tolerant strain. S. Typhimuirum exposed to temperatures >25 °C in the BDL matrix displayed increased resistance to SGF. By using the response surface methodology, it was determined that S. Typhimurium becomes less resistant against SGF if maintained in the BDL matrix at temperatures <7 °C, reinforcing the recommendation to store dry-cured meat under refrigeration in order to minimize consumer risks. The results presented herein point to a novel aspect of hurdle technology that should be taken into account to further understand the risks associated with hurdle-stable meat product, such as dry-cured meats, concerning foodborne pathogen contamination.

Relative Abundance of Ammonia Oxidizing Archaea and Bacteria Influences Soil Nitrification Responses to Temperature

Ammonia oxidizing archaea (AOA) and bacteria (AOB) are thought to contribute differently to soil nitrification, yet the extent to which their relative abundances influence the temperature response of nitrification is poorly understood. Here, we investigated the impact of different AOA to AOB ratios on soil nitrification potential (NP) across a temperature gradient from 4 °C to 40 °C in twenty different organic and inorganic fertilized soils. The temperature responses of different relative abundance of ammonia oxidizers for nitrification were modeled using square rate theory (SQRT) and macromolecular rate theory (MMRT) models. We found that the proportional nitrification rates at different temperatures varied among AOA to AOB ratios. Predicted by both models, an optimum temperature (T_opt) for nitrification in AOA dominated soils was significantly higher than for soils where AOA and AOB abundances are within the same order of magnitude. Moreover, the change in heat capacity (ΔCP‡) associated with the temperature dependence of nitrification was positively correlated with T_opt and significantly varied among the AOA to AOB ratios. The temperature ranges for NP decreased with increasing AOA abundance for both organic and inorganic fertilized soils. These results challenge the widely accepted approach of comparing NP rates in different soils at a fixed temperature. We conclude that a shift in AOA to AOB ratio in soils exhibits distinguished temperature-dependent characteristics that have an important impact on nitrification responses across the temperature gradient. The proposed approach benefits the accurate discernment of the true contribution of fertilized soils to nitrification for improvement of nitrogen management.

Assessing thermodynamic parameter sensitivity for simulating temperature responses of soil nitrification

Soil nitrification responses to temperature have major implications for the global nitrogen cycle. Temperature sensitivity of soil nitrification has been modeled using several mathematical models, yet the extent to which model-generated thermodynamic parameters are accurate and sensitive in describing temperature sensitivity is unclear. In this study, we performed global sensitivity analysis to identify the key thermodynamic parameters that are most influential when simulating the temperature response of the soil nitrification potential (NP) across two different temperature gradients (4-40 °C and 20-45 °C) which are imposed upon sixteen different soils with square root growth (SQRT) and macromolecular rate theory (MMRT) models. We found that two thermodynamic parameters stand out as moderately to highly sensitive, and are uniquely identifiable in each model, regardless of the temperature range. The minimum and maximum measured temperatures seem to have no impact on the list of sensitive parameters but do influence the parameter ranges, especially for the SQRT model. However, parameters that control the minimum temperature and curvature of the NP response curve (Tmin and ΔC‡P) were found to have little to no sensitivity to SQRT and MMRT model outputs, respectively. We show that the parameter sensitivity and range of measured temperatures influence the complementary model's ability to describe the temperature sensitivity of soil nitrification. Our proposed framework enhances the accurate interpretation of existing thermodynamic parameters that explain the temperature sensitivity of soil biochemical processes, and provides methodological recommendations for future temperature sensitivity studies.

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.

Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits

There is currently unprecedented interest in quantifying variation in thermal physiology among organisms, especially in order to understand and predict the biological impacts of climate change. A key parameter in this quantification of thermal physiology is the performance or value of a rate, across individuals or species, at a common temperature (temperature normalisation). An increasingly popular model for fitting thermal performance curves to data-the Sharpe-Schoolfield equation-can yield strongly inflated estimates of temperature-normalised rate values. These deviations occur whenever a key thermodynamic assumption of the model is violated, i.e., when the enzyme governing the performance of the rate is not fully functional at the chosen reference temperature. Using data on 1,758 thermal performance curves across a wide range of species, we identify the conditions that exacerbate this inflation. We then demonstrate that these biases can compromise tests to detect metabolic cold adaptation, which requires comparison of fitness or rate performance of different species or genotypes at some fixed low temperature. Finally, we suggest alternative methods for obtaining unbiased estimates of temperature-normalised rate values for meta-analyses of thermal performance across species in climate change impact studies.

Predictions of response to temperature are contingent on model choice and data quality

The equations used to account for the temperature dependence of biological processes, including growth and metabolic rates, are the foundations of our predictions of how global biogeochemistry and biogeography change in response to global climate change. We review and test the use of 12 equations used to model the temperature dependence of biological processes across the full range of their temperature response, including supra- and suboptimal temperatures. We focus on fitting these equations to thermal response curves for phytoplankton growth but also tested the equations on a variety of traits across a wide diversity of organisms. We found that many of the surveyed equations have comparable abilities to fit data and equally high requirements for data quality (number of test temperatures and range of response captured) but lead to different estimates of cardinal temperatures and of the biological rates at these temperatures. When these rate estimates are used for biogeographic predictions, differences between the estimates of even the best-fitting models can exceed the global biological change predicted for a decade of global warming. As a result, studies of the biological response to global changes in temperature must make careful consideration of model selection and of the quality of the data used for parametrizing these models.

Rethinking Tertiary Models: Relationships between Growth Parameters of Bacillus cereus Strains

The maximum specific growth rates of 12 strains, pair-wise belonging to six groups of Bacillus cereus sensu lato, were fitted against temperature by a reparametrized version of the model of Ratkowsky et al. (1983). This way, the interpretation of the new parameter set was similar to that of the cardinal-values-model of Rosso and Robinson (2001), both models including the minimum, optimum and maximum temperatures for growth as well as a fourth parameter scaling along the dependent variable. The modularity of the reparametrized version of the Ratkowsky model was utilized to show a so-far undetected relationship between this scaling parameter and the cardinal temperatures, which linked even distant (e.g., mesophilic and psychotropic) strains of B. cereus. We propose that the name “tertiary modeling” should be used for investigations like ours, as logically derived from the concepts of “primary” and “secondary” modeling. Such tertiary models may reveal biological relationships between kinetic parameters within a group of strains. It can also be used to create an overarching predictive model for mixed cultures, when different strains grow together but independently of each other.

Temperature-nutrient interactions exacerbate sensitivity to warming in phytoplankton

Temperature and nutrients are fundamental, highly nonlinear drivers of biological processes, but we know little about how they interact to influence growth. This has hampered attempts to model population growth and competition in dynamic environments, which is critical in forecasting species distributions, as well as the diversity and productivity of communities. To address this, we propose a model of population growth that includes a new formulation of the temperature-nutrient interaction and test a novel prediction: that a species' optimum temperature for growth, T_opt , is a saturating function of nutrient concentration. We find strong support for this prediction in experiments with a marine diatom, Thalassiosira pseudonana: T_opt decreases by 3-6 °C at low nitrogen and phosphorus concentrations. This interaction implies that species are more vulnerable to hot, low-nutrient conditions than previous models accounted for. Consequently the interaction dramatically alters species' range limits in the ocean, projected based on current temperature and nitrate levels as well as those forecast for the future. Ranges are smaller not only than projections based on the individual variables, but also than those using a simpler model of temperature-nutrient interactions. Nutrient deprivation is therefore likely to exacerbate environmental warming's effects on communities.

Thermal Performance Curves and the Metabolic Theory of Ecology-A Practical Guide to Models and Experiments for Parasitologists

Climate change will affect host-parasite dynamics in complex ways. The development of forecast models is necessary for proactive disease management, but past studies have frequently reported thermal performance data in idiosyncratic ways that have limited use for parameterizing thermal host-parasite models. Development of improved forecast models will require strong collaborations between experimental parasitologists and disease modelers. The purpose of this article is to facilitate such collaborations by reviewing practical considerations for describing thermal performance curves of parasite and host performance traits, and using them to predict climate change impacts on host-parasite systems. In the first section, we provide an overview of how thermal performance curves can be embedded in life-cycle-based dynamical models of parasitism, and we outline how such models can capture the net effect of multiple nonlinear temperature dependencies affecting the host-parasite dynamics. We also discuss how macroecological generalities based on the metabolic theory of ecology (MTE) can be used to determine a priori parameter estimates for thermal performance curves to derive null models for data-deficient species, but we note that most of the generalities suggested by MTE remain to be tested for parasites. In the second section, we discuss empirical knowledge gaps for the temperature dependence of parasite and host performance traits, and we outline the types of data that need to be collected to inform MTE-based models for data-deficient species. We specifically emphasize the importance of (1) capturing the entire thermal response of performance traits, including lower and upper temperature thresholds, and (2) experimentally or statistically separating out the thermal responses of different performance traits (e.g., development and mortality) rather than only reporting composite measures (e.g., apparent development). Not adhering to these principles can lead to biased climate change impact predictions. In the third section, we provide a practical guide outlining how experimentalists can contribute to fill data gaps by measuring the temperature dependence of host and parasite performance traits in ways that are systematic, statistically rigorous, and consistent with the requirements of life cycle-based host-parasite models. This guide includes recommendations and practical examples illustrating (1) the use of perturbation analyses to determine experimental priorities, (2) experimental design tips for quantifying thermal response curves, and (3) statistical methods for estimating the parameters of thermal performance curves. Our hope is that this article helps researchers to maximize the value and use of future data collections for both empirical and modelling studies investigating the way in which temperature influences parasitism.

Polar Marine Microorganisms and Climate Change

The large diversity of marine microorganisms harboured by oceans plays an important role in planet sustainability by driving globally important biogeochemical cycles; all primary and most secondary production in the oceans is performed by microorganisms. The largest part of the planet is covered by cold environments; consequently, cold-adapted microorganisms have crucial functional roles in globally important environmental processes and biogeochemical cycles cold-adapted extremophiles are a remarkable model to shed light on the molecular basis of survival at low temperature. The indigenous populations of Antarctic and Arctic microorganisms are endowed with genetic and physiological traits that allow them to live and effectively compete at the temperatures prevailing in polar regions. Some genes, e.g. glycosyltransferases and glycosylsynthetases involved in the architecture of the cell wall, may have been acquired/retained during evolution of polar strains or lost in tropical strains. This present work focusses on temperature and its role in shaping microbial adaptations; however, in assessing the impacts of climate changes on microbial diversity and biogeochemical cycles in polar oceans, it should not be forgotten that physiological studies need to include the interaction of temperature with other abiotic and biotic factors.

Role of Proteome Physical Chemistry in Cell Behavior

We review how major cell behaviors, such as bacterial growth laws, are derived from the physical chemistry of the cell’s proteins. On one hand, cell actions depend on the individual biological functionalities of their many genes and proteins. On the other hand, the common physics among proteins can be as important as the unique biology that distinguishes them. For example, bacterial growth rates depend strongly on temperature. This dependence can be explained by the folding stabilities across a cell’s proteome. Such modeling explains how thermophilic and mesophilic organisms differ, and how oxidative damage of highly charged proteins can lead to unfolding and aggregation in aging cells. Cells have characteristic time scales. For example, E. coli can duplicate as fast as 2–3 times per hour. These time scales can be explained by protein dynamics (the rates of synthesis and degradation, folding, and diffusional transport). It rationalizes how bacterial growth is slowed down by added salt. In the same way that the behaviors of inanimate materials can be expressed in terms of the statistical distributions of atoms and molecules, some cell behaviors can be expressed in terms of distributions of protein properties, giving insights into the microscopic basis of growth laws in simple cells.

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.

Aerobically respiring prokaryotic strains exhibit a broader temperature-pH-salinity space for cell division than anaerobically respiring and fermentative strains

Biological processes on the Earth operate within a parameter space that is constrained by physical and chemical extremes. Aerobic respiration can result in adenosine triphosphate yields up to over an order of magnitude higher than those attained anaerobically and, under certain conditions, may enable microbial multiplication over a broader range of extremes than other modes of catabolism. We employed growth data published for 241 prokaryotic strains to compare temperature, pH and salinity values for cell division between aerobically and anaerobically metabolizing taxa. Isolates employing oxygen as the terminal electron acceptor exhibited a considerably more extensive three-dimensional phase space for cell division (90% of the total volume) than taxa using other inorganic substrates or organic compounds as the electron acceptor (15% and 28% of the total volume, respectively), with all groups differing in their growth characteristics. Understanding the mechanistic basis of these differences will require integration of research into microbial ecology, physiology and energetics, with a focus on global-scale processes. Critical knowledge gaps include the combined impacts of diverse stress parameters on Gibbs energy yields and rates of microbial activity, interactions between cellular energetics and adaptations to extremes, and relating laboratory-based data to in situ limits for cell division.

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.

Niche and metabolic principles explain patterns of diversity and distribution: theory and a case study with soil bacterial communities

The causes of biodiversity patterns are controversial and elusive due to complex environmental variation, covarying changes in communities, and lack of baseline and null theories to differentiate straightforward causes from more complex mechanisms. To address these limitations, we developed general diversity theory integrating metabolic principles with niche-based community assembly. We evaluated this theory by investigating patterns in the diversity and distribution of soil bacteria taxa across four orders of magnitude variation in spatial scale on an Antarctic mountainside in low complexity, highly oligotrophic soils. Our theory predicts that lower temperatures should reduce taxon niche widths along environmental gradients due to decreasing growth rates, and the changing niche widths should lead to contrasting α- and β-diversity patterns. In accord with the predictions, α-diversity, niche widths and occupancies decreased while β-diversity increased with increasing elevation and decreasing temperature. The theory also successfully predicts a hump-shaped relationship between α-diversity and pH and a negative relationship between α-diversity and salinity. Thus, a few simple principles explained systematic microbial diversity variation along multiple gradients. Such general theory can be used to disentangle baseline effects from more complex effects of temperature and other variables on biodiversity patterns in a variety of ecosystems and organisms.

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.

Thermal variation, thermal extremes and the physiological performance of individuals

In this review we consider how small-scale temporal and spatial variation in body temperature, and biochemical/physiological variation among individuals, affect the prediction of organisms' performance in nature. For ‘normal’ body temperatures – benign temperatures near the species' mean – thermal biology traditionally uses performance curves to describe how physiological capabilities vary with temperature. However, these curves, which are typically measured under static laboratory conditions, can yield incomplete or inaccurate predictions of how organisms respond to natural patterns of temperature variation. For example, scale transition theory predicts that, in a variable environment, peak average performance is lower and occurs at a lower mean temperature than the peak of statically measured performance. We also demonstrate that temporal variation in performance is minimized near this new ‘optimal’ temperature. These factors add complexity to predictions of the consequences of climate change. We then move beyond the performance curve approach to consider the effects of rare, extreme temperatures. A statistical procedure (the environmental bootstrap) allows for long-term simulations that capture the temporal pattern of extremes (a Poisson interval distribution), which is characterized by clusters of events interspersed with long intervals of benign conditions. The bootstrap can be combined with biophysical models to incorporate temporal, spatial and physiological variation into evolutionary models of thermal tolerance. We conclude with several challenges that must be overcome to more fully develop our understanding of thermal performance in the context of a changing climate by explicitly considering different forms of small-scale variation. These challenges highlight the need to empirically and rigorously test existing theories.

The effects of temperature on aerobic metabolism: towards a mechanistic understanding of the responses of ectotherms to a changing environment

Because of its profound effects on the rates of biological processes such as aerobic metabolism, environmental temperature plays an important role in shaping the distribution and abundance of species. As temperature increases, the rate of metabolism increases and then rapidly declines at higher temperatures – a response that can be described using a thermal performance curve (TPC). Although the shape of the TPC for aerobic metabolism is often attributed to the competing effects of thermodynamics, which can be described using the Arrhenius equation, and the effects of temperature on protein stability, this account represents an over-simplification of the factors acting even at the level of single proteins. In addition, it cannot adequately account for the effects of temperature on complex multistep processes, such as aerobic metabolism, that rely on mechanisms acting across multiple levels of biological organization. The purpose of this review is to explore our current understanding of the factors that shape the TPC for aerobic metabolism in response to acute changes in temperature, and to highlight areas where this understanding is weak or insufficient. Developing a more strongly grounded mechanistic model to account for the shape of the TPC for aerobic metabolism is crucial because these TPCs are the foundation of several recent attempts to predict the responses of species to climate change, including the metabolic theory of ecology and the hypothesis of oxygen and capacity-limited thermal tolerance.

Environmental variation and population responses to global change

Species' responses to environmental changes such as global warming are affected not only by trends in mean conditions, but also by natural and human-induced environmental fluctuations. Methods are needed to predict how such environmental variation affects ecological and evolutionary processes, in order to design effective strategies to conserve biodiversity under global change. Here, we review recent theoretical and empirical studies to assess: (1) how populations respond to changes in environmental variance, and (2) how environmental variance affects population responses to changes in mean conditions. Contrary to frequent claims, empirical studies show that increases in environmental variance can increase as well as decrease long-term population growth rates. Moreover, environmental variance can alter and even reverse the effects of changes in the mean environment, such that even if environmental variance remains constant, omitting it from population models compromises their ability to predict species' responses to changes in mean conditions. Drawing on theory relating these effects of environmental variance to the curvatures of population growth responses to the environment, we outline how species' traits such as phylogenetic history and body mass could be used to predict their responses to global change under future environmental variability.

Microbial resource utilization traits and trade-offs: implications for community structure, functioning, and biogeochemical impacts at present and in the future

Trait-based approaches provide a mechanistic framework to understand and predict the structure and functioning of microbial communities. Resource utilization traits and trade-offs are among key microbial traits that describe population dynamics and competition among microbes. Several important trade-offs have been identified for prokaryotic and eukaryotic microbial taxa that define contrasting ecological strategies and contribute to species coexistence and diversity. The shape, dimensionality, and hierarchy of trade-offs may determine coexistence patterns and need to be better characterized. Laboratory measured resource utilization traits can be used to explain temporal and spatial structure and dynamics of natural microbial communities and predict biogeochemical impacts. Global environmental change can alter microbial community composition through altering resource utilization by different microbes and, consequently, may modify biogeochemical impacts of microbes.

Reduction of the temperature sensitivity of Halomonas hydrothermalis by iron starvation combined with microaerobic conditions

The limits to biological processes on Earth are determined by physicochemical parameters, such as extremes of temperature and low water availability. Research into microbial extremophiles has enhanced our understanding of the biophysical boundaries which define the biosphere. However, there remains a paucity of information on the degree to which rates of microbial multiplication within extreme environments are determined by the availability of specific chemical elements. Here, we show that iron availability and the composition of the gaseous phase (aerobic versus microaerobic) determine the susceptibility of a marine bacterium, Halomonas hydrothermalis, to suboptimal and elevated temperature and salinity by impacting rates of cell division (but not viability). In particular, iron starvation combined with microaerobic conditions (5% [vol/vol] O2, 10% [vol/vol] CO2, reduced pH) reduced sensitivity to temperature across the 13°C range tested. These data demonstrate that nutrient limitation interacts with physicochemical parameters to determine biological permissiveness for extreme environments. The interplay between resource availability and stress tolerance, therefore, may shape the distribution and ecology of microorganisms within Earth's biosphere.

Inferring the temperature dependence of population parameters: the effects of experimental design and inference algorithm

Understanding and quantifying the temperature dependence of population parameters, such as intrinsic growth rate and carrying capacity, is critical for predicting the ecological responses to environmental change. Many studies provide empirical estimates of such temperature dependencies, but a thorough investigation of the methods used to infer them has not been performed yet. We created artificial population time series using a stochastic logistic model parameterized with the Arrhenius equation, so that activation energy drives the temperature dependence of population parameters. We simulated different experimental designs and used different inference methods, varying the likelihood functions and other aspects of the parameter estimation methods. Finally, we applied the best performing inference methods to real data for the species Paramecium caudatum. The relative error of the estimates of activation energy varied between 5% and 30%. The fraction of habitat sampled played the most important role in determining the relative error; sampling at least 1% of the habitat kept it below 50%. We found that methods that simultaneously use all time series data (direct methods) and methods that estimate population parameters separately for each temperature (indirect methods) are complementary. Indirect methods provide a clearer insight into the shape of the functional form describing the temperature dependence of population parameters; direct methods enable a more accurate estimation of the parameters of such functional forms. Using both methods, we found that growth rate and carrying capacity of Paramecium caudatum scale with temperature according to different activation energies. Our study shows how careful choice of experimental design and inference methods can increase the accuracy of the inferred relationships between temperature and population parameters. The comparison of estimation methods provided here can increase the accuracy of model predictions, with important implications in understanding and predicting the effects of temperature on the dynamics of populations.

Thermodynamic theory explains the temperature optima of soil microbial processes and high Q10 values at low temperatures

Our current understanding of the temperature response of biological processes in soil is based on the Arrhenius equation. This predicts an exponential increase in rate as temperature rises, whereas in the laboratory and in the field, there is always a clearly identifiable temperature optimum for all microbial processes. In the laboratory, this has been explained by denaturation of enzymes at higher temperatures, and in the field, the availability of substrates and water is often cited as critical factors. Recently, we have shown that temperature optima for enzymes and microbial growth occur in the absence of denaturation and that this is a consequence of the unusual heat capacity changes associated with enzymes. We have called this macromolecular rate theory - MMRT (Hobbs et al., , ACS Chem. Biol. 8:2388). Here, we apply MMRT to a wide range of literature data on the response of soil microbial processes to temperature with a focus on respiration but also including different soil enzyme activities, nitrogen and methane cycling. Our theory agrees closely with a wide range of experimental data and predicts temperature optima for these microbial processes. MMRT also predicted high relative temperature sensitivity (as assessed by Q10 calculations) at low temperatures and that Q10 declined as temperature increases in agreement with data synthesis from the literature. Declining Q10 and temperature optima in soils are coherently explained by MMRT which is based on thermodynamics and heat capacity changes for enzyme-catalysed rates. MMRT also provides a new perspective, and makes new predictions, regarding the absolute temperature sensitivity of ecosystems - a fundamental component of models for climate change.

Climate sensitivity across marine domains of life: limits to evolutionary adaptation shape species interactions

Organisms in all domains, Archaea, Bacteria, and Eukarya will respond to climate change with differential vulnerabilities resulting in shifts in species distribution, coexistence, and interactions. The identification of unifying principles of organism functioning across all domains would facilitate a cause and effect understanding of such changes and their implications for ecosystem shifts. For example, the functional specialization of all organisms in limited temperature ranges leads us to ask for unifying functional reasons. Organisms also specialize in either anoxic or various oxygen ranges, with animals and plants depending on high oxygen levels. Here, we identify thermal ranges, heat limits of growth, and critically low (hypoxic) oxygen concentrations as proxies of tolerance in a meta-analysis of data available for marine organisms, with special reference to domain-specific limits. For an explanation of the patterns and differences observed, we define and quantify a proxy for organismic complexity across species from all domains. Rising complexity causes heat (and hypoxia) tolerances to decrease from Archaea to Bacteria to uni- and then multicellular Eukarya. Within and across domains, taxon-specific tolerance limits likely reflect ultimate evolutionary limits of its species to acclimatization and adaptation. We hypothesize that rising taxon-specific complexities in structure and function constrain organisms to narrower environmental ranges. Low complexity as in Archaea and some Bacteria provide life options in extreme environments. In the warmest oceans, temperature maxima reach and will surpass the permanent limits to the existence of multicellular animals, plants and unicellular phytoplankter. Smaller, less complex unicellular Eukarya, Bacteria, and Archaea will thus benefit and predominate even more in a future, warmer, and hypoxic ocean.

Extensive gene acquisition in the extremely psychrophilic bacterial species Psychroflexus torquis and the link to sea-ice ecosystem specialism

Sea ice is a highly dynamic and productive environment that includes a diverse array of psychrophilic prokaryotic and eukaryotic taxa distinct from the underlying water column. Because sea ice has only been extensive on Earth since the mid-Eocene, it has been hypothesized that bacteria highly adapted to inhabit sea ice have traits that have been acquired through horizontal gene transfer (HGT). Here we compared the genomes of the psychrophilic bacterium Psychroflexus torquis ATCC 700755^T, associated with both Antarctic and Arctic sea ice, and its closely related nonpsychrophilic sister species, P. gondwanensis ACAM 44^T. Results show that HGT has occurred much more extensively in P. torquis in comparison to P. gondwanensis. Genetic features that can be linked to the psychrophilic and sea ice-specific lifestyle of P. torquis include genes for exopolysaccharide (EPS) and polyunsaturated fatty acid (PUFA) biosynthesis, numerous specific modes of nutrient acquisition, and proteins putatively associated with ice-binding, light-sensing (bacteriophytochromes), and programmed cell death (metacaspases). Proteomic analysis showed that several genes associated with these traits are highly translated, especially those involved with EPS and PUFA production. Because most of the genes relating to the ability of P. torquis to dwell in sea-ice ecosystems occur on genomic islands that are absent in closely related P. gondwanensis, its adaptation to the sea-ice environment appears driven mainly by HGT. The genomic islands are rich in pseudogenes, insertional elements, and addiction modules, suggesting that gene acquisition is being followed by a process of genome reduction potentially indicative of evolving ecosystem specialism.

Pyrosequencing-based characterization of gastrointestinal bacteria of Atlantic salmon (Salmo salar L.) within a commercial mariculture system

AIMS

The relationship of Atlantic salmon gastrointestinal (GI) tract bacteria to environmental factors, in particular water temperature within a commercial mariculture system, was investigated.

METHODS AND RESULTS

Salmon GI tract bacterial communities commercially farmed in south-eastern Tasmania were analysed, over a 13-month period across a standard commercial production farm cycle, using 454 16S rRNA-based pyrosequencing. Faecal bacterial communities were highly dynamic but largely similar between randomly selected fish. In postsmolt, the faecal bacteria population was dominated by Gram-positive fermentative bacteria; however, by midsummer, members of the family Vibrionaceae predominated. As fish progressed towards harvest, a range of different bacterial genera became more prominent corresponding to a decline in Vibrionaceae. The sampled fish were fed two different commercial diet series with slightly different protein, lipid and digestible energy level; however, the effect of these differences was minimal.

CONCLUSIONS

The overall data demonstrated dynamic hind gut communities in salmon that were related to season and fish growth phases but were less influenced by differences in commercial diets used routinely within the farm system studied.

SIGNIFICANCE AND IMPACT OF THE STUDY

This study provides understanding of farmed salmon GI bacterial communities and describes the relative impact of diet, environmental and farm factors.

Protein thermodynamics can be predicted directly from biological growth rates

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.

Change in heat capacity for enzyme catalysis determines temperature dependence of enzyme catalyzed rates

The increase in enzymatic rates with temperature up to an optimum temperature (Topt) is widely attributed to classical Arrhenius behavior, with the decrease in enzymatic rates above Topt ascribed to protein denaturation and/or aggregation. This account persists despite many investigators noting that denaturation is insufficient to explain the decline in enzymatic rates above Topt. Here we show that it is the change in heat capacity associated with enzyme catalysis (ΔC(‡)p) and its effect on the temperature dependence of ΔG(‡) that determines the temperature dependence of enzyme activity. Through mutagenesis, we demonstrate that the Topt of an enzyme is correlated with ΔC(‡)p and that changes to ΔC(‡)p are sufficient to change Topt without affecting the catalytic rate. Furthermore, using X-ray crystallography and molecular dynamics simulations we reveal the molecular details underpinning these changes in ΔC(‡)p. The influence of ΔC(‡)p on enzymatic rates has implications for the temperature dependence of biological rates from enzymes to ecosystems.

Temperature dependence of trophic interactions are driven by asymmetry of species responses and foraging strategy

Environmental temperature has systematic effects on rates of species interactions, primarily through its influence on organismal physiology. We present a mechanistic model for the thermal response of consumer-resource interactions. We focus on how temperature affects species interactions via key traits - body velocity, detection distance, search rate and handling time - that underlie per capita consumption rate. The model is general because it applies to all foraging strategies: active-capture (both consumer and resource body velocity are important), sit-and-wait (resource velocity dominates) and grazing (consumer velocity dominates). The model predicts that temperature influences consumer-resource interactions primarily through its effects on body velocity (either of the consumer, resource or both), which determines how often consumers and resources encounter each other, and that asymmetries in the thermal responses of interacting species can introduce qualitative, not just quantitative, changes in consumer-resource dynamics. We illustrate this by showing how asymmetries in thermal responses determine equilibrium population densities in interacting consumer-resource pairs. We test for the existence of asymmetries in consumer-resource thermal responses by analysing an extensive database on thermal response curves of ecological traits for 309 species spanning 15 orders of magnitude in body size from terrestrial, marine and freshwater habitats. We find that asymmetries in consumer-resource thermal responses are likely to be a common occurrence. Overall, our study reveals the importance of asymmetric thermal responses in consumer-resource dynamics. In particular, we identify three general types of asymmetries: (i) different levels of performance of the response, (ii) different rates of response (e.g. activation energies) and (iii) different peak or optimal temperatures. Such asymmetries should occur more frequently as the climate changes and species' geographical distributions and phenologies are altered, such that previously noninteracting species come into contact. 6. By using characteristics of trophic interactions that are often well known, such as body size, foraging strategy, thermy and environmental temperature, our framework should allow more accurate predictions about the thermal dependence of consumer-resource interactions. Ultimately, integration of our theory into models of food web and ecosystem dynamics should be useful in understanding how natural systems will respond to current and future temperature change.