Reaction and diffusion thermodynamics explain optimal temperatures of biochemical reactions

Analysis of subcellular energy metabolism in five Lacertidae lizards across varied environmental conditions

Aerobic respiration is the main energy source for most eukaryotes, and efficient mitochondrial energy transfer greatly influences organismal fitness. To survive environmental changes, cells have evolved to adjust their biochemistry. Thus, measuring energy metabolism at the subcellular level can enhance our understanding of individual performance, population dynamics, and species distribution ranges. We investigated three important metabolic traits at the subcellular level in five lacertid lizard species sampled from different elevations, from sea level up to 2000 m. We examined hemoglobin concentration, two markers of oxidative stress (catalase activity and carbonyl concentration) and maximum rate of metabolic respiration at the subcellular level (potential metabolic activity at the electron transport system). The traits were analysed in laboratory acclimated adult male lizards to investigate the adaptive metabolic responses to the variable environmental conditions at the local sampling sites. Potential metabolic activity at the cellular level was measured at four temperatures - 28 °C, 30 °C, 32 °C and 34 °C - covering the range of preferred body temperatures of the species studied. Hemoglobin content, carbonyl concentration and potential metabolic activity did not differ significantly among species. Interspecific differences were found in the catalase activity, Potential metabolic activity increased with temperature in parallel in all five species. The highest response of the metabolic rate with temperature (Q10) and Arrhenius activation energy (Ea) was recorded in the high-mountain species Iberolacerta monticola.

No universal mathematical model for thermal performance curves across traits and taxonomic groups

In ectotherms, the performance of physiological, ecological and life-history traits universally increases with temperature to a maximum before decreasing again. Identifying the most appropriate thermal performance model for a specific trait type has broad applications, from metabolic modelling at the cellular level to forecasting the effects of climate change on population, ecosystem and disease transmission dynamics. To date, numerous mathematical models have been designed, but a thorough comparison among them is lacking. In particular, we do not know if certain models consistently outperform others and how factors such as sampling resolution and trait or organismal identity influence model performance. To fill this knowledge gap, we compile 2,739 thermal performance datasets from diverse traits and taxa, to which we fit a comprehensive set of 83 existing mathematical models. We detect remarkable variation in model performance that is not primarily driven by sampling resolution, trait type, or taxonomic information. Our results reveal a surprising lack of well-defined scenarios in which certain models are more appropriate than others. To aid researchers in selecting the appropriate set of models for any given dataset or research objective, we derive a classification of the 83 models based on the average similarity of their fits.

Thermal effects and ephaptic entrainment in Hodgkin-Huxley model

The brain is understood as an intricate biological system composed of numerous elements. It is susceptible to various physical and chemical influences, including temperature. The literature extensively explores the conditions that influence synapses in the context of cellular communication. However, the understanding of how the brain's global physical conditions can modulate ephaptic communication remains limited due to the poorly understood nature of ephapticity. This study proposes an adaptation of the Hodgkin and Huxley (HH) model to investigate the effects of ephaptic entrainment in response to thermal changes (HH-E). The analysis focuses on two distinct neuronal regimes: subthreshold and suprathreshold. In the subthreshold regime, circular statistics are used to demonstrate the dependence of phase differences with temperature. In the suprathreshold regime, the Inter-Spike Interval are employed to estimate phase preferences and changes in the spiking pattern. Temperature influences the model's ephaptic interactions and can modify its preferences for spiking frequency, with the direction of this change depending on specific model conditions and the temperature range under consideration. Furthermore, temperature enhance the anti-phase differences relationship between spikes and the external ephaptic signal. In the suprathreshold regime, ephaptic entrainment is also influenced by temperature, especially at low frequencies. This study reveals the susceptibility of ephaptic entrainment to temperature variations in both subthreshold and suprathreshold regimes and discusses the importance of ephaptic communication in the contexts where temperature may plays a significant role in neural physiology, such as inflammatory processes, fever, and epileptic seizures.

A flexible model for thermal performance curves

Temperature responses of many biological traits-including population growth, survival, and development-are described by thermal performance curves (TPCs) with phenomenological models like the Briere function or mechanistic models related to chemical kinetics. Existing TPC models are either simple but inflexible in shape, or flexible yet difficult to interpret in biological terms. Here we present flexTPC: a model that is parameterized exclusively in terms of biologically interpretable quantities, including the thermal minimum, optimum, and maximum, and the maximum trait value. FlexTPC can describe unimodal temperature responses of any skewness and thermal breadth, enabling direct comparisons across populations, traits, or taxa with a single model. We apply flexTPC to various microbial and entomological datasets, compare results with the Briere model, and find that flexTPC often has better predictive performance. The interpretability of flexTPC makes it ideal for modeling how thermal responses change with ecological stressors or evolve over time.

Atmospheric CO2 in the megacity Hangzhou, China: Urban-suburban differences, sources and impact factors

Limited observation sites and insufficient monitoring of atmospheric CO2 in urban areas restrict our comprehension of urban-suburban disparities. This research endeavored to shed light on the urban-suburban differences of atmospheric CO2 in levels, diurnal and seasonal variations as well as the potential sources and impact factors in the megacity of Hangzhou, China, where the economically most developed region in China is. The observations derived from the existing Hangzhou Atmospheric Composition Monitoring Center Station (HZ) and Lin'an Regional Atmospheric Background Station (LAN) and the newly established high-altitude Daming Mountain Atmospheric Observation Station (DMS), were utilized. From November 2020 to October 2021, the annual averages of HZ, LAN and DMS were 446.52 ± 17.01 ppm, 441.56 ± 15.42 ppm, and 422.02 ± 10.67 ppm. The difference in atmospheric CO2 mole fraction between HZ and LAN was lower compared to the urban-suburban differences observed in other major cities in China, such as Shanghai, Nanjing, and Beijing. Simultaneous CO2 enhancements were observed at HZ and LAN, when using DMS observations as background references. The seasonal variations of CO2 at LAN and DMS exhibited a high negative correlation with the normalized difference vegetation index (NDVI) values, indicating the strong regulatory of vegetation canopy. The variations in boundary layer height had a larger influence on the low-altitude HZ and LAN stations than DMS. Compared to HZ and LAN, the atmospheric CO2 at DMS was influenced by emissions and transmissions over a wider range. The potential source area of DMS in autumn covered most areas of the urban agglomeration in eastern China. DMS measurements could provide a reliable representation of the background level of CO2 emissions in the Yangtze River Delta and a broader region. Conventional understanding of regional CO2 level in the Yangtze River Delta through LAN measurements may overestimate background concentration by approximately 10.92 ppm.

Hotter is not (always) better: Embracing unimodal scaling of biological rates with temperature

Rate-temperature scaling relationships have fascinated biologists for nearly two centuries and are increasingly important in our era of global climate change. These relationships are hypothesized to originate from the temperature-dependent kinetics of rate-limiting biochemical reactions of metabolism. Several prominent theories have formalized this hypothesis using the Arrhenius model, which characterizes a monotonic temperature dependence using an activation energy E. However, the ubiquitous unimodal nature of biological temperature responses presents important theoretical, methodological, and conceptual challenges that restrict the promise for insight, prediction, and progress. Here we review the development of key hypotheses and methods for the temperature-scaling of biological rates. Using simulations, we examine the constraints of monotonic models, illustrating their sensitivity to data nuances such as temperature range and noise, and their tendency to yield variable and underestimated E, with critical consequences for climate change predictions. We also evaluate the behaviour of two prominent unimodal models when applied to incomplete and noisy datasets. We conclude with recommendations for resolving these challenges in future research, and advocate for a shift to unimodal models that better characterize the full range of biological temperature responses.

Warm Cells, Hot Mitochondria: Achievements and Problems of Ultralocal Thermometry

Temperature is a crucial regulator of the rate and direction of biochemical reactions and cell processes. The recent data indicating the presence of local thermal gradients associated with the sites of high-rate thermogenesis, on the one hand, demonstrate the possibility for the existence of "thermal signaling" in a cell and, on the other, are criticized on the basis of thermodynamic calculations and models. Here, we review the main thermometric techniques and sensors developed for the determination of temperature inside living cells and diverse intracellular compartments. A comparative analysis is conducted of the results obtained using these methods for the cytosol, nucleus, endo-/sarcoplasmic reticulum, and mitochondria, as well as their biological consistency. Special attention is given to the limitations, possible sources of errors and ambiguities of the sensor's responses. The issue of biological temperature limits in cells and organelles is considered. It is concluded that the elaboration of experimental protocols for ultralocal temperature measurements that take into account both the characteristics of biological systems, as well as the properties and limitations of each type of sensor is of critical importance for the generation of reliable results and further progress in this field.

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.

Metabolomic rearrangement controls the intrinsic microbial response to temperature changes

Temperature is one of the key determinants of microbial behavior and survival, whose impact is typically studied under heat- or cold-shock conditions that elicit specific regulation to combat lethal stress. At intermediate temperatures, cellular growth rate varies according to the Arrhenius law of thermodynamics without stress responses, a behavior whose origins have not yet been elucidated. Using single-cell microscopy during temperature perturbations, we show that bacteria exhibit a highly conserved, gradual response to temperature upshifts with a time scale of ~1.5 doublings at the higher temperature, regardless of initial/final temperature or nutrient source. We find that this behavior is coupled to a temperature memory, which we rule out as being neither transcriptional, translational, nor membrane dependent. Instead, we demonstrate that an autocatalytic enzyme network incorporating temperature-sensitive Michaelis-Menten kinetics recapitulates all temperature-shift dynamics through metabolome rearrangement, which encodes a temperature memory and successfully predicts alterations in the upshift response observed under simple-sugar, low-nutrient conditions, and in fungi. This model also provides a mechanistic framework for both Arrhenius-dependent growth and the classical Monod Equation through temperature-dependent metabolite flux.

Energetic costs increase with faster heating in an aquatic ectotherm

The thermal sensitivity of metabolism is widely studied due to its perceived importance for organismal fitness and resilience to future climate change. Almost all such studies estimate metabolism at a variety of constant temperatures, with very little work exploring how metabolism varies during temperature change. However, temperature in nature is rarely static, so our existing understanding from experiments may not reflect how temperature influences metabolism in natural systems. Using closed-chamber respirometry, we estimated the aerobic metabolic rate of an aquatic ectotherm, the Atlantic ditch shrimp Palaemonetes varians, under varying thermal conditions. We continuously measured oxygen consumption of shrimp during heating, cooling and constant temperatures, starting trials at a range of acclimation temperatures and exposing shrimp to a variety of rates of temperature change. In a broad sense, cumulative oxygen consumption estimated from static temperature exposures corresponded to estimates derived from ramping experiments. However, further analyses showed that oxygen consumption increases for both faster heating and faster cooling, with rapid heating driving higher metabolic rates than if shrimp were warmed slowly. These results suggest a systematic influence of heating rate on the thermal sensitivity of metabolism. With influential concepts such as the metabolic theory of ecology founded in data from constant temperature experiments, our results encourage further exploration of how variable temperature impacts organism energetics, and to test the generality of our findings across species. This is especially important given climate forecasts of heat waves that are characterised by both increased temperatures and faster rates of change.

Optical, Structural, and Magnetic Hyperthermia Properties of Yttrium Iron Garnet Synthesized by Hybrid Microwave-Assisted Hydrothermal and Sol-Gel Auto Combustion Routes

Magnetic hyperthermia is an emerging technique used for the treatment of tumors, where the infected cells will be deactivated using the heat generated from magnetic particles. This study discusses the viability of yttrium iron garnet (YIG) in magnetic hyperthermia treatment. YIG is synthesized using hybrid microwave-assisted hydrothermal and sol-gel auto combustion techniques. The formation of the garnet phase is confirmed using powder X-ray diffraction studies. Further, the morphology and grain size of the material are analyzed and estimated with the help of field emission scanning electron microscopy. Transmittance and optical band gap are obtained using UV-visible spectroscopy. Raman scattering of the material is discussed to understand the phase and vibrational modes. The functional groups of garnet are studied using Fourier transform infrared spectroscopy. Further, the effect of the synthesizing routes on the characteristics of the materials is discussed. A relatively higher magnetic saturation value is observed in the hysteresis loop at room temperature of YIG samples, which is synthesized by a sol-gel auto combustion technique, and it confirms the ferromagnetic behavior. The colloidal stability and surface charge of the prepared YIG are evaluated by a zeta potential measurement. In addition, magnetic induction heating studies are carried out for both prepared samples. The specific absorption rates of 1 mg/mL concentration are 237 and 214 W/g at 35.33 kA/m and 316 kHz field of sol-gel auto combustion and hydrothermal methods, respectively. Due to their higher saturation magnetization of 26.39 emu/g, the sol-gel auto combustion method produced effective YIG and demonstrated superior heating efficiency than the hydrothermally prepared sample. The prepared YIG are biocompatible, and their hyperthermia properties may be explored in various biomedical applications.

Interactive effects of temperature and bisphenol A on phytoplankton growth and community structure

Environmental contamination of bisphenol A (BPA) is a widespread and multifaceted issue with vast ecological, social and economic consequences. Thus, understanding how local environmental conditions, such as temperature, interact with BPA to affect populations and community dynamics remain important areas of research. Here, we conduct laboratory experiments aimed at understanding how environmental gradients of both temperature and BPA concentration influence freshwater phytoplankton population growth and community structure. We exposed phytoplankton assemblages comprised of three common species of green algae (Chlorella vulgaris, Ankistrodesmus braunii and Scenedesmus quadricauda) as well as isolates of each individual species to three BPA concentrations (0, 2, 13 mg/L BPA) and three temperatures (18, 23, 27°C) monitoring population growth and community structure (via biovolume). We observed antagonistic interactions between BPA and warmer temperatures, such that when warmer temperatures decreased growth (observed with A. braunii), high concentrations of BPA elevated growth at these warm temperatures; however, when warmer temperatures increased growth (C. vulgaris, S. quadricauda), high BPA concentrations diminished these gains. Although BPA exposure inhibited the growth of most C. vulgaris populations, growth was not reduced in A. braunii or S. quadricauda populations exposed to 2 mg/L BPA. Phytoplankton assemblage evenness (Pielou evenness index) decreased as BPA concentration increased and was consistently lowest under 27°C. Community composition was similar in assemblages cultured under 0 and 2 mg/L BPA under 18 and 23°C but was most similar between assemblages cultured under 2 and 13 mg/L BPA under 27°C. These results indicate that local environmental temperatures can mediate the consequences of BPA for freshwater phytoplankton growth rates and community structure and that BPA can diminish potential gains of increased growth rate for warm-adapted phytoplankton species at high environmental temperatures.

Impact of temperature on optical sensing in biology based on investigation of SARS-CoV-2

In this paper, we present an investigation of the influence of the temperature on the sensing of biological samples. We used biofunctionalized microsphere-based fiber-optic sensor to detect immunoglobulin G attached to the sensor head at temperatures relevant in biological research: 5°C, 25°C, and 55°C. The construction of the sensor allowed us to perform measurements in the small amount of solution. The results of our experiment confirm substantial changes in the measured reflected optical power, indicating the need to control the temperature during such measurements. The sensitivity of the sensor used in this research is 8.82 nW/°C. Coefficient R was also calculated and it equals 0.998, which shows good fit between theoretical linear fit and obtained measured data.

Time- and temperature-dependent dynamics of prothoracicotropic hormone and ecdysone sensitivity co-regulate pupal diapause in the green-veined white butterfly Pieris napi

Diapause, a general shutdown of developmental pathways, is a vital adaptation allowing insects to adjust their life cycle to adverse environmental conditions such as winter. Diapause in the pupal stage is regulated by the major developmental hormones prothoracicotropic hormone (PTTH) and ecdysone. Termination of pupal diapause in the butterfly Pieris napi depends on low temperatures; therefore, we study the temperature-dependence of PTTH secretion and ecdysone sensitivity dynamics throughout diapause, with a focus on diapause termination. While PTTH is present throughout diapause in the cell bodies of two pairs of neurosecretory cells in the brain, it is absent in the axons, and the PTTH concentration in the haemolymph is significantly lower during diapause than during post diapause development, indicating that the PTTH signaling is reduced during diapause. The sensitivity of pupae to ecdysone injections is dependent on diapause stage. While pupae are sensitive to ecdysone during early diapause initiation, they gradually lose this sensitivity and become insensitive to non-lethal concentrations of ecdysone about 30 days into diapause. At low temperatures, reflecting natural overwintering conditions, diapause termination propensity after ecdysone injection is precocious compared to controls. In stark contrast, at high temperatures reflecting late summer and early autumn conditions, sensitivity to ecdysone does not return. Thus, here we show that PTTH secretion is reduced during diapause, and additionally, that the low ecdysone sensitivity of early diapause maintenance is lost during termination in a temperature dependent manner. The link between ecdysone sensitivity and low-temperature dependence reveals a putative mechanism of how diapause termination operates in insects that is in line with adaptive expectations for diapause.

A general theory for temperature dependence in biology

At present, there is no simple, first principles-based, and general model for quantitatively describing the full range of observed biological temperature responses. Here we derive a general theory for temperature dependence in biology based on Eyring-Evans-Polanyi's theory for chemical reaction rates. Assuming only that the conformational entropy of molecules changes with temperature, we derive a theory for the temperature dependence of enzyme reaction rates which takes the form of an exponential function modified by a power law and that describes the characteristic asymmetric curved temperature response. Based on a few additional principles, our model can be used to predict the temperature response above the enzyme level, thus spanning quantum to classical scales. Our theory provides an analytical description for the shape of temperature response curves and demonstrates its generality by showing the convergence of all temperature dependence responses onto universal relationships-a universal data collapse-under appropriate normalization and by identifying a general optimal temperature, around 25 ^∘C, characterizing all temperature response curves. The model provides a good fit to empirical data for a wide variety of biological rates, times, and steady-state quantities, from molecular to ecological scales and across multiple taxonomic groups (from viruses to mammals). This theory provides a simple framework to understand and predict the impact of temperature on biological quantities based on the first principles of thermodynamics, bridging quantum to classical scales.

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.

Lipase nanogel catalyzed synthesis of vitamin E succinate in non-aqueous phase

BACKGROUND

In order to improve the stability of vitamin E and broaden its scope of application, an effective solution is to convert vitamin E into its derivatives. This work developed a new Candida rugosa lipase (CRL) nanogel based on modification of ionic liquid with vinyl functional groups. This novel CRL nanogel was used in the preparation process of vitamin E succinate based on the principle of non-aqueous enzymology. At the same time, various factors including enzyme concentration, substrate molar ratio, reaction temperature and reaction time, that affect the yield of vitamin E succinate were optimized and analyzed.

RESULTS

Different solvents with various hydrophobicity parameters (LogP values) from -1.3 to 3.5 were studied, it was found that dimethyl sulfoxide (DMSO) had the lowest LogP value among organic solvents but vitamin E succinate had the highest yield in DMSO. Furthermore, the effect of different operating conditions, such as molar ratios of substrate, enzyme concentration, reaction temperature and reaction time was studied. Under the optimal process conditions (enzyme concentration 6 mg mL^-1 , substrate molar ratio 4:1, reaction temperature 55 °C and reaction time 15 h), the product yield was 62.58 ± 1.16%. CRL and CRL nanogel were characterized using Fourier-transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM). It was shown that CRL nanogel influenced the catalytic behavior of lipase significantly by changing the structure and surface properties of CRL.

CONCLUSION

Novel lipase nanogel was an excellent biocatalyst for enzymatic synthesis of vitamin E succinate. © 2020 Society of Chemical Industry.

Kinetics of proteolysis in stored Mongolian cheese at ice-temperatures and split-split-plot analysis of storage factors affecting cheese quality

Mongolian cheese is non-fermented cheese, which easily deteriorates during storage because of hydrolysis. The freezing points of sucrose and sucrose-free cheese were measured -5.16 °C and -4.29 °C, respectively. Ice-storage temperatures of -2 °C and -4 °C were used and 0 °C was used as reference temperature. In this study, the changes of proteolytic indexes (PI) and total viable counts (TVC) of cheese at different ice-temperatures during storage were studied. The PIs of all treatments increased over storage time, which conformed to the Arrhenius first-order kinetic model. The shelf lives of sucrose and sucrose-free cheese were predicted. In addition, -4 °C effectively suppressed the increases in TVC and PIs. The split-split-plot design was applied in comparing the effects of cheese type, the storage time and storage temperature on PI. Storage time was the most important factor followed by cheese type and storage temperature.

Flexibility of enzymatic transitions as a hallmark of optimized enzyme steady-state kinetics and thermodynamics

We investigate the relations between the enzyme kinetic flexibility, the rate of entropy production, and the Shannon information entropy in a steady-state enzyme reaction. All these quantities are maximized with respect to enzyme rate constants. We show that the steady-state, which is characterized by the most flexible enzymatic transitions between the enzyme conformational states, coincides with the global maxima of the Shannon information entropy and the rate of entropy production. This steady-state of an enzyme is referred to as globally optimal. This theoretical approach is then used for the analysis of the kinetic and the thermodynamic performance of the enzyme triose-phosphate isomerase. The analysis reveals that there exist well-defined maxima of the kinetic flexibility, the rate of entropy production, and the Shannon information entropy with respect to any arbitrarily chosen rate constant of the enzyme and that these maxima, calculated from the measured kinetic rate constants for the triose-phosphate isomerase are lower, however of the same order of magnitude, as the maxima of the globally optimal state of the enzyme. This suggests that the triose-phosphate isomerase could be a well, but not fully evolved enzyme, as it was previously claimed. Herein presented theoretical investigations also provide clear evidence that the flexibility of enzymatic transitions between the enzyme conformational states is a requirement for the maximal Shannon information entropy and the maximal rate of entropy production.

Pitfalls in Monitoring Mitochondrial Temperature Using Charged Thermosensitive Fluorophores

Mitochondria are the source of internal heat which influences all cellular processes. Hence, monitoring mitochondrial temperature provides a unique insight into cell physiology. Using a thermosensitive fluorescent probe MitoThermo Yellow (MTY), we have shown recently that mitochondria within human cells are maintained at close to 50 °C when active, increasing their temperature locally by about 10 °C. Initially reported in the HEK293 cell line, we confirmed this finding in the HeLa cell line. Delving deeper, using MTY and MTX (MitoThermo X), a modified version of MTY, we unraveled some caveats related to the nature of these charged fluorophores. While enabling the assessment of mitochondrial temperature in HEK and HeLa cell lines, the reactivity of MTY to membrane potential variations in human primary skin fibroblasts precluded local temperature monitoring in these cells. Chemical modification of MTY into MTX did not result in a temperature probe unresponsive to membrane potential variations that could be universally used in any cell type to determine mitochondrial temperature. Thus, the cell-type dependence of MTY in measuring mitochondrial temperature, which is likely due to the variable binding of this dye to specific internal mitochondrial components, should imply cautiousness while using these nanothermometers for mitochondrial temperature analysis.

Standardizing luminescence nanothermometry for biomedical applications

Luminescence nanothermometry enables accurate, remote, and all-optically-based thermal sensing. Notwithstanding its fast development, there are serious obstacles hindering reproducibility and reliable quantitative assessment of nanothermometers, which impede the intentional design, optimization and use of these sensors. These issues include ambiguities or absence of established universal rules for quantitative evaluation, incorrect assumptions about the mechanisms behind the thermal response of the sensors as well as the dependence of the nanothermometers readout on external conditions and host materials themselves. In this perspective article, we discuss these problems and propose a series of standardization guidelines to be followed. This critical discourse constitutes the first required step towards the ubiquitous acceptance, by the scientific community, of luminescence thermometry as a reliable tool for remote temperature determination in numerous practical biomedical implementations.

The effect of temperature on sulfur and oxygen isotope fractionation by sulfate reducing bacteria (Desulfococcus multivorans)

Temperature influences microbiological growth and catabolic rates. Between 15 and 35 °C the growth rate and cell specific sulfate reduction rate of the sulfate reducing bacterium Desulfococcus multivorans increased with temperature. Sulfur isotope fractionation during sulfate reduction decreased with increasing temperature from 27.2 ‰ at 15 °C to 18.8 ‰ at 35 °C which is consistent with a decreasing reversibility of the metabolic pathway as the catabolic rate increases. Oxygen isotope fractionation, in contrast, decreased between 15 and 25 °C and then increased again between 25 and 35 °C, suggesting increasing reversibility in the first steps of the sulfate reducing pathway at higher temperatures. This points to a decoupling in the reversibility of sulfate reduction between the steps from the uptake of sulfate into the cell to the formation of sulfite, relative to the whole pathway from sulfate to sulfide. This observation is consistent with observations of increasing sulfur isotope fractionation when sulfate reducing bacteria are living near their upper temperature limit. The oxygen isotope decoupling may be a first signal of changing physiology as the bacteria cope with higher temperatures.

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.

Maximum Entropy Production Theorem for Transitions between Enzyme Functional States and Its Applications

Transitions between enzyme functional states are often connected to conformational changes involving electron or proton transport and directional movements of a group of atoms. These microscopic fluxes, resulting in entropy production, are driven by non-equilibrium concentrations of substrates and products. Maximal entropy production exists for any chosen transition, but such a maximal transitional entropy production (MTEP) requirement does not ensure an increase of total entropy production, nor an increase in catalytic performance. We examine when total entropy production increases, together with an increase in the performance of an enzyme or bioenergetic system. The applications of the MTEP theorem for transitions between functional states are described for the triosephosphate isomerase, ATP synthase, for β-lactamases, and for the photochemical cycle of bacteriorhodopsin. The rate-limiting steps can be easily identified as those which are the most efficient in dissipating free-energy gradients and in performing catalysis. The last step in the catalytic cycle is usually associated with the highest free-energy dissipation involving proton nanocurents. This recovery rate-limiting step can be optimized for higher efficiency by using corresponding MTEP requirements. We conclude that biological evolution, leading to increased optimal catalytic efficiency, also accelerated the thermodynamic evolution, the synergistic relationship we named the evolution-coupling hypothesis.

Entropy Generation Rate Minimization for Methanol Synthesis via a CO2 Hydrogenation Reactor

The methanol synthesis via CO2 hydrogenation (MSCH) reaction is a useful CO2 utilization strategy, and this synthesis path has also been widely applied commercially for many years. In this work the performance of a MSCH reactor with the minimum entropy generation rate (EGR) as the objective function is optimized by using finite time thermodynamic and optimal control theory. The exterior wall temperature (EWR) is taken as the control variable, and the fixed methanol yield and conservation equations are taken as the constraints in the optimization problem. Compared with the reference reactor with a constant EWR, the total EGR of the optimal reactor decreases by 20.5%, and the EGR caused by the heat transfer decreases by 68.8%. In the optimal reactor, the total EGRs mainly distribute in the first 30% reactor length, and the EGRs caused by the chemical reaction accounts for more than 84% of the total EGRs. The selectivity of CH3OH can be enhanced by increasing the inlet molar flow rate of CO, and the CO2 conversion rate can be enhanced by removing H2O from the reaction system. The results obtained herein are in favor of optimal designs of practical tubular MSCH reactors.

Entropy Density Acceleration and Minimum Dissipation Principle: Correlation with Heat and Matter Transfer in Glucose Catabolism

The heat and matter transfer during glucose catabolism in living systems and their relation with entropy production are a challenging subject of the classical thermodynamics applied to biology. In this respect, an analogy between mechanics and thermodynamics has been performed via the definition of the entropy density acceleration expressed by the time derivative of the rate of entropy density and related to heat and matter transfer in minimum living systems. Cells are regarded as open thermodynamic systems that exchange heat and matter resulting from irreversible processes with the intercellular environment. Prigogine's minimum energy dissipation principle is reformulated using the notion of entropy density acceleration applied to glucose catabolism. It is shown that, for out-of-equilibrium states, the calculated entropy density acceleration for a single cell is finite and negative and approaches as a function of time a zero value at global thermodynamic equilibrium for heat and matter transfer independently of the cell type and the metabolic pathway. These results could be important for a deeper understanding of entropy generation and its correlation with heat transfer in cell biology with special regard to glucose catabolism representing the prototype of irreversible reactions and a crucial metabolic pathway in stem cells and cancer stem cells.