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At least 919 records · Page 51

Short- and long-term responses of photosynthetic capacity to temperature in four boreal tree species in a free-air warming and rainfall manipulation experiment

Abstract High latitude forests cope with considerable variation in moisture and temperature at multiple temporal scales. To assess how their photosynthetic physiology responds to short- and long-term temperature variation, we measured photosynthetic capacity for four tree species growing in an open-air experiment in the boreal-temperate ecotone `Boreal Forest Warming at an Ecotone in Danger' (B4WarmED). The experiment factorially manipulated temperature above- and below-ground (ambient, +3.2 °C) and summer rainfall (ambient, 40% removal). We measured A/Ci curves at 18, 25 and 32 °C for individuals of two boreal (Pinus banksiana Lamb., Betula papyrifera Marsh.) and two temperate species (Pinus strobus L., Acer rubrum L.) experiencing the long-term warming and/or reduced-rainfall conditions induced by our experimental treatments. We calculated the apparent photosynthetic capacity descriptors VCmax,Ci and Jmax,Ci and their ratio for each measurement temperate. We hypothesized that (i) VCmax,Ci and Jmax,Ci would be down-regulated in plants experiencing longer term (e.g., weeks to months) warming and reduced rainfall (i.e., have lower values at a given measurement temperature), as is sometimes found in the literature, and that (ii) plants growing at warmer temperatures or from warmer ranges would show greater sensitivity (steeper slope) to short-term (minutes to hours) temperature variation. Neither hypothesis was supported as a general trend across the four species, as there was not a significant main effect (across species) of either warming or rainfall reduction on VCmax,Ci and Jmax,Ci. All species markedly increased VCmax,Ci and Jmax,Ci (and decreased their ratio) with short-term increases in temperature (i.e., contrasting values at 18, 25 and 32 °C), and those responses were independent of long-term treatments and did not differ among species. The Jmax,Ci:VCmax,Ci ratio was, however, significantly lower across species in warmed and reduced rainfall treatments. Collectively, these results suggest that boreal trees possess considerable short-term plasticity that may allow homeostasis of VCmax,Ci and Jmax,Ci to a longer term temperature treatment. Our results also caution against extrapolating results obtained under controlled and markedly contrasting temperature treatments to responses of photosynthetic parameters to more modest temperature changes expected in the near-term with climate warming in field conditions.

Forestry↗

Changes in carbon and nitrogen metabolism during seawater-induced mortality of Picea sitchensis trees

Abstract Increasing seawater exposure is causing mortality of coastal forests, yet the physiological response associated with seawater-induced tree mortality, particularly in non-halophytes, is poorly understood. We investigated the shifts in carbon and nitrogen (N) metabolism of mature Sitka-spruce trees that were dying after an ecosystem-scale manipulation of tidal seawater exposure. Soil porewater salinity and foliar ion concentrations increased after seawater exposure and were strongly correlated with the percentage of live foliated crown (PLFC; e.g., crown ‘greenness’, a measure of progression to death). Co-occurring with decreasing PLFC was decreasing photosynthetic capacity, N-investment into photosynthesis, N-resorption efficiency and non-structural carbohydrate (soluble sugars and starch) concentrations, with the starch reserves depleted to near zero when PLFC dropped below 5%. Combined with declining PLFC, these changes subsequently decreased total carbon gain and thus exacerbated the carbon starvation process. This study suggests that an impairment in carbon and N metabolism during the mortality process after seawater exposure is associated with the process of carbon starvation, and provides critical knowledge necessary to predict sea-level rise impacts on coastal forests.

Li, Weibin↗

New insights into the role of constitutive bacterial rhizobiome and phenolic compounds in two Pinus spp. with contrasting susceptibility to pine pitch canker

Abstract The rhizobiome is being increasingly acknowledged as a key player in plant health and breeding strategies. The pine pitch canker (PPC), caused by the fungus Fusarium circinatum, affects pine species with varying susceptibility degrees. Our aims were to explore the bacterial rhizobiome of a susceptible (Pinus radiata) and a resistant (Pinus pinea) species together with other physiological traits, and to analyze shifts upon F. circinatum inoculation. Pinus seedlings were stem inoculated with F. circinatum spores and needle gas exchange and antioxidant-related parameters were analyzed in non-inoculated and inoculated plants. Rhizobiome structure was evaluated through 16S rRNA gene massive parallel sequencing. Species (non-inoculated plants) harbored distinct rhizobiomes (<40% similarity), where P. pinea displayed a rhizobiome with increased abundance of taxa described in suppressive soils, displaying plant growth promoting (PGP) traits and/or anti-fungal activity. Plants of this species also displayed higher levels of phenolic compounds. F. circinatum induced slight changes in the rhizobiome of both species and a negative impact in photosynthetic-related parameters in P. radiata. We concluded that the rhizobiome of each pine species is distinct and higher abundance of bacterial taxa associated to disease protection was registered for the PPC-resistant species. Furthermore, differences in the rhizobiome are paralleled by a distinct content in phenolic compounds, which are also linked to plants’ resistance against PPC. This study unveils a species-specific rhizobiome and provides insights to exploit the rhizobiome for plant selection in nurseries and for rhizobiome-based plant-growth-promoting strategies, boosting environmentally friendly disease control strategies.

Leitão, Frederico↗

Disentangling the drivers of non-stationarity in tree growth

Tree-ring chronologies are an invaluable data source that provides insight into the ecology and physiology of forests across broad spatial and temporal scales. Furthermore, these data have a foundation in paleoclimatic research and have been used for decades to reconstruct climate, fire and other disturbances for several centuries to millennia into the past. Contemporary ecological studies have also used growth data to examine the responses of trees to environmental variability or biotic and abiotic stressors.

59 BASIC BIOLOGICAL SCIENCES↗

PSInet: a new global water potential network

Abstract Given the pressing challenges posed by climate change, it is crucial to develop a deeper understanding of the impacts of escalating drought and heat stress on terrestrial ecosystems and the vital services they offer. Soil and plant water potential play a pivotal role in governing the dynamics of water within ecosystems and exert direct control over plant function and mortality risk during periods of ecological stress. However, existing observations of water potential suffer from significant limitations, including their sporadic and discontinuous nature, inconsistent representation of relevant spatio-temporal scales and numerous methodological challenges. These limitations hinder the comprehensive and synthetic research needed to enhance our conceptual understanding and predictive models of plant function and survival under limited moisture availability. In this article, we present PSInet (PSI—for the Greek letter Ψ used to denote water potential), a novel collaborative network of researchers and data, designed to bridge the current critical information gap in water potential data. The primary objectives of PSInet are as follows. (i) Establishing the first openly accessible global database for time series of plant and soil water potential measurements, while providing important linkages with other relevant observation networks. (ii) Fostering an inclusive and diverse collaborative environment for all scientists studying water potential in various stages of their careers. (iii) Standardizing methodologies, processing and interpretation of water potential data through the engagement of a global community of scientists, facilitated by the dissemination of standardized protocols, best practices and early career training opportunities. (iv) Facilitating the use of the PSInet database for synthesizing knowledge and addressing prominent gaps in our understanding of plants’ physiological responses to various environmental stressors. The PSInet initiative is integral to meeting the fundamental research challenge of discerning which plant species will thrive and which will be vulnerable in a world undergoing rapid warming and increasing aridification.

Forestry↗

The effect of relative humidity and temperature on the response of stomatal conductance to vapor pressure deficit in tropical trees

Understanding how leaf gas exchange responds to changes in vapor pressure deficit (VPD) is key to predicting tropical forest resilience to climate change. Stomata regulate leaf water and CO2 diffusion, and respond to changes in temperature and relative humidity (RH), two drivers of VPD. At high temperatures, the cuticular pathway may also become significant and participate in the overall leaf conductance. Here, we measured gas exchange under light and dark conditions to investigate the stomatal and cuticular responses to temperature and RH on detached branches in five tropical tree species. Leaf conductance in the dark, when stomata are essentially closed, was not markedly impacted by temperature and RH, suggesting a minimal response of the cuticular pathway to these conditions. We compared six steady-state conductance models incorporating different effects of photosynthesis and evaporative demand on stomatal control. All models performed well (residual standard deviation, σ, < 0.025 mol m-2 s-1), but the best-fitting model (σ = 0.017 mol m-2 s-1) used a nonlinear relationship between photosynthesis and stomatal conductance and incorporated RH rather than vapor pressure difference. All models overestimated the steady-state conductance at high RH. Furthermore, leaf conductance immediately increased after a decrease in RH (wrong-way response), but not after an increase in leaf temperature. This suggests that the mechanisms underlying stomatal response to VPD need further investigation. The non-linear coupling between photosynthetic rate and stomatal conductance indicates a sharper physiological response than previously acknowledged.

Lamour, Julien↗

Evaluation of Protein Extraction Methods for Metaproteomic Analyses of Root-Associated Microbes

Metaproteomics is a powerful tool for the characterization of metabolism, physiology, and functional interactions in microbial communities, including plant-associated microbiota. However, the metaproteomic methods that have been used to study plant-associated microbiota are very laborious and require large amounts of plant tissue, hindering wider application of these methods. We optimized and evaluated different protein extraction methods for metaproteomics of plant-associated microbiota in two different plant species (Arabidopsis and maize). Our main goal was to identify a method that would work with low amounts of input material (40 to 70 mg) and that would maximize the number of identified microbial proteins. We tested eight protocols, each comprising a different combination of physical lysis method, extraction buffer, and cell-enrichment method on roots from plants grown with synthetic microbial communities. We assessed the performance of the extraction protocols by liquid chromatography-tandem mass spectrometry–based metaproteomics and found that the optimal extraction method differed between the two species. For Arabidopsis roots, protein extraction by beating whole roots with small beads provided the greatest number of identified microbial proteins and improved the identification of proteins from gram-positive bacteria. For maize, vortexing root pieces in the presence of large glass beads yielded the greatest number of microbial proteins identified. Based on these data, we recommend the use of these two methods for metaproteomics with Arabidopsis and maize. Furthermore, detailed descriptions of the eight tested protocols will enable future optimization of protein extraction for metaproteomics in other dicot and monocot plants.

59 BASIC BIOLOGICAL SCIENCES↗

Nitrogen fixation and resorption efficiency differences among twelve upland and lowland switchgrass cultivars

In nitrogen (N)-limited terrestrial ecosystems, plants employ various strategies to acquire and conserve N, including translocation of N in perennial tissues and stimulation of N fixation in roots and soils. Switchgrass (Panicum virgatum L.) is a genotypically and phenotypically diverse perennial grass with two distinct ecotypes (lowland and upland) and numerous genotypes. It grows well in low-N soils, likely because of its ability to translocate N and to associate with N-fixing microbes, but little is known about variation in these traits among cultivars or even ecotypes. We measured N translocation, N fixation potential in roots and soils, soil net N mineralization, soil net nitrification, and biomass yields in 12 switchgrass cultivars grown in a replicated block experiment in southwestern Michigan, USA. Lowland cultivars had higher yields, rates of N translocation, soil net N mineralization, and N fixation potentials on washed, non-sterile roots, while upland cultivars exhibited higher N fixation potentials in root-free soil. N resorption efficiencies averaged 53±5 [SE] % for lowland versus 29±3% for upland cultivars. Additionally, there were significant among-cultivar differences for all response variables except mineralization and nitrification, with differences likely explained by cultivar-specific physiologies and microbial communities. Here, the ideal cultivar for biofuels is one that can maintain high yields with minimal fertilizer addition and there appear to be several cultivars that meet these criteria. In addition, results suggest substantial N cycle differences among cultivars that might be exploited by breeders to create new or improved high-yielding, N-conserving switchgrass lines.

59 BASIC BIOLOGICAL SCIENCES↗

Statistical Uncertainty of Inhalation Dose Coefficients: Impact of Particle Deposition in ICRP 66 Human Respiratory Tract Model

Inhaled radioactive materials can pose a long-term health concern, as the material can be incorporated into the body’s metabolic pathways and remain in organs and tissues for extended durations. During the retention period, the radioactive material may localize in a source organ and irradiate adjacent target organs and tissues. Distribution of these materials changes over time, requiring biokinetic modeling to evaluate their movement through various tissues and organs. The evolving distribution depends on multiple inputs characterizing the inhaled material, such as particle size and size distribution, particle density, aspect ratio, specific radionuclide, the chemical form, and solubility. In addition, biological parameters such as breathing rate, breathing type (nasal or nasal/oral), respiratory system morphometry, tidal volume, functional residual capacity, and anatomical dead space all influence material transport. These aerosol properties and physiological characteristics of the respiratory tract jointly define a range of initial conditions that influence the time-dependent distribution of radioactive material. To evaluate both uncertainty in the initial conditions of inhalation exposure and the final output (committed effective dose) from biokinetic models, a Python-based software tool, Radiological Exposure Dose Calculator (REDCAL), was developed to propagate uncertainty within the human respiratory tract model. Focusing on deposition fraction uncertainty, the primary objective was to characterize the initial activity distribution across respiratory regions as a function of anticipated particle sizes and distributions. The impact of the deposition fraction uncertainty was propagated to committed effective dose coefficients for selected radionuclides in a companion publication. For each particle size, a lognormal distribution, characterized by its geometric mean as defined within ICRP Publication 66, serves as the basis for introducing uncertainty into the physical processes governing deposition in various lung regions. Finally, this study addresses the deposition process and examines how uncertainty in deposition mechanisms affects activity distribution in the airways, ultimately presenting the expected range and standard deviation of deposited activity as a function of particle size.

International Commission on Radiological Protectio↗

Sulfurospirillum diekertiae sp. nov., a tetrachloroethene-respiring bacterium isolated from contaminated soil

Two anaerobic, tetrachloroethene- (PCE-) respiring bacterial isolates, designated strain ACS DCE T and strain ACS TCE , were characterized using a polyphasic approach. Cells were Gram-stain-negative, motile, non-spore-forming and shared a vibrioid- to spirillum-shaped morphology. Optimum growth occurred at 30°C and 0.1–0.4% salinity. The pH range for growth was pH 5.5–7.5, with an optimum at pH 7.2. Hydrogen, formate, pyruvate and lactate as electron donors supported respiratory reductive dechlorination of PCE to cis-1,2-dichloroethene (cDCE) in strain ACS DCE T and of PCE to trichloroethene (TCE) in strain ACS TCE . Both strains were able to grow with pyruvate under microaerobic conditions. Nitrate, elemental sulphur, and thiosulphate were alternative electron acceptors. Autotrophic growth was not observed and acetate served as carbon source for both strains. The major cellular fatty acids were C 16:1 ω7c, C 16:0 , C 14:0 and C 18:1 ω7c. Both genomes feature a circular plasmid. Strains ACS DCE T and ACS TCE were previously assigned to the candidate species 'Sulfurospirillum acididehalogenans'. Here, based on key genomic features and pairwise comparisons of whole-genome sequences, including average nucleotide identity, digital DNA–DNA hybridization and average amino acid identity, strains ACS DCE T and ACS TCE , 'Ca. Sulfurospirillum diekertiae' strains SL2-1 and SL2-2, and the unclassified Sulfurospirillum sp. strain SPD-1 are grouped into one distinct species separate from previously described Sulfurospirillum species. Compared to Sulfurospirillum multivorans and Sulfurospirillum halorespirans, which dechlorinate PCE to cDCE without substantial TCE accumulation, these five strains produce TCE or cDCE as the end product. In addition, some cellular fatty acids (e.g., C 16:0 3OH, C 17:0 iso 3OH, C 17:0 2OH) were detected in strains ACS DCE T and ACS TCE but not in other Sulfurospirillum species. On the basis of phylogenetic, physiological and phenotypic characteristics, 'Ca. Sulfurospirillum acididehalogenans' and 'Ca. Sulfurospirillum diekertiae' are proposed to be merged into one novel species within the genus Sulfurospirillum, for which the name Sulfurospirillum diekertiae sp. nov. is proposed. Finally, the type strain is ACS DCE T (=JCM 33349 T = KCTC 15819 T =CGMCC 1.5292 T ).

59 BASIC BIOLOGICAL SCIENCES↗

Siderophores and secondary metabolites produced by Ganoderma adspersum

Ganoderma adspersum is a white-rot wood-degrading basidiomycete of ecological, biotechnological and medicinal interest. In addition to its role in lignin degradation, it produces bioactive metabolites with reported antimicrobial and antioxidant activities. However, the mechanisms of iron acquisition, including siderophore-mediated pathways, remain poorly characterized in Ganoderma species. Improved understanding of these systems is essential to elucidate their contributions to fungal physiology, secondary metabolism and ecological adaptation. In this study, the genome of G. adspersum was sequenced for the first time and screened for genes that may be involved in the production of secondary metabolites. A gene cluster was identified as potentially involved in iron uptake. In particular, genes related to non-ribosomal peptide synthetases were detected next to a gene encoding a monooxygenase and indicated a potential hydroxamate-family siderophore. Liquid chromatography (LC)-ES-MS analysis of secondary metabolites secreted by G. adspersum into the growth medium under iron-limiting conditions revealed a group of previously undescribed siderophores. Genome and MS/MS analysis suggested that these structures might be related to the coprinoferrin family of siderophores. Aside from siderophores, the genome and LC-MS analysis revealed G. adspersum to be a prolific producer of a variety of triterpenoids and sesquiterpenoids, in agreement with previous findings. This is the first description of the genome sequence of G. adspersum and its siderophores.

Reyes, Carolina [Laboratory for Cellulose and Wood↗

Large-scale Genetic Characterization of a Model Sulfate-Reducing Bacterium

ABSTRACTSulfate-reducing bacteria (SRB) are obligate anaerobes that can couple their growth to the reduction of sulfate. Despite the importance of SRB to global nutrient cycles and their damage to the petroleum industry, our molecular understanding of their physiology remains limited. To systematically provide new insights into SRB biology, we generated a randomly barcoded transposon mutant library in the model SRB Desulfovibrio vulgaris Hildenborough (DvH) and used this genome-wide resource to assay the importance of its genes under a range of metabolic and stress conditions. In addition to defining the essential gene set of DvH, we identified a conditional phenotype for 1,137 non-essential genes. Through examination of these conditional phenotypes, we were able to make a number of novel insights into our molecular understanding of DvH, including how this bacterium synthesizes vitamins. For example, we identified DVU0867 as an atypical L-aspartate decarboxylase required for the synthesis of pantothenic acid, provided the first experimental evidence that biotin synthesis in DvH occurs via a specialized acyl carrier protein and without methyl esters, and demonstrated that the uncharacterized dehydrogenase DVU0826:DVU0827 is necessary for the synthesis of pyridoxal phosphate. In addition, we used the mutant fitness data to identify genes involved in the assimilation of diverse nitrogen sources, and gained insights into the mechanism of inhibition of chlorate and molybdate. Our large-scale fitness dataset and RB-TnSeq mutant library are community-wide resources that can be used to generate further testable hypotheses into the gene functions of this environmentally and industrially important group of bacteria.

Trotter, Valentine V↗

Evaluating the limitations of Bayesian metabolic control analysis

AbstractBayesian Metabolic Control Analysis (BMCA) has emerged as a promising framework for inferring metabolic control coefficients in data-limited scenarios by integrating Bayesian inference with linlog rate laws. However, its predictive accuracy and limitations remain underexplored. This study systematically evaluates BMCA’s ability to infer elasticity values, flux control coefficients (FCCs), and concentration control coefficients (CCCs) under varying data availability conditions using three synthetic metabolic network models. Our findings highlight the strengths and weaknesses of BMCA, guiding its application in metabolic engineering and emphasizing the need for methodological refinements.Author summaryUnderstanding how enzymes control metabolic pathways is crucial for optimizing biomanufacturing and synthetic biology applications. Bayesian Metabolic Control Analysis (BMCA) is a promising computational method that integrates Bayesian inference with metabolic control analysis to estimate key control parameters, even in cases with limited experimental data. However, the accuracy and limitations of BMCA remain unclear. In this study, we systematically evaluate BMCA using three synthetic metabolic networks to determine how different types of physiological data impact its predictive performance. We find that BMCA requires flux and enzyme concentration data for accurate predictions, while external metabolite concentrations contribute little. Additionally, BMCA fails to predict elasticity values beyond a magnitude of 1.5 and reliably infer allosteric regulation, even when strong regulatory interactions exist. In addition, BMCA does not accurately rank metabolic control points, which may limit its utility in identifying key enzymes in engineered pathways. Our work provides practical insights into when and how BMCA can be applied, guiding future research in metabolic modeling and control analysis.

Shin, Janis (ORCID:0000000216572455)↗

Engineering Crassulacean Acid Metabolism in C 3 and C 4 Plants

Carbon dioxide (CO 2 ) is a major greenhouse gas contributing to changing climatic conditions, which is a grand challenge affecting the security of food, energy, and environment. Photosynthesis plays the central role in plant-based CO 2 reduction. Additionally, plants performing CAM (crassulacean acid metabolism) photosynthesis have a much higher water use efficiency than those performing C 3 or C 4 photosynthesis. Therefore, there is a great potential for engineering CAM in C 3 or C 4 crops to enhance food/biomass production and carbon sequestration on arid, semiarid, abandoned, or marginal lands. Recent progresses in CAM plant genomics and evolution research, along with new advances in plant biotechnology, have provided a solid foundation for bioengineering to convert C 3 /C 4 plants into CAM plants. Here, we first discuss the potential strategies for CAM engineering based on our current understanding of CAM evolution. Then we describe the technical approaches for engineering CAM in C 3 and C 4 plants, with a focus on an iterative four-step pipeline: (1) designing gene modules, (2) building the gene modules and transforming them into target plants, (3) testing the engineered plants through an integration of molecular biology, biochemistry, metabolism, and physiological approaches, and (4) learning to inform the next round of CAM engineering. Finally, we discuss the challenges and future opportunities for fully realizing the potential of CAM engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Streamlined spatial and environmental expression signatures characterize the minimalist duckweed Wolffia australiana

Single-cell genomics permits a new resolution in the examination of molecular and cellular dynamics, allowing global, parallel assessments of cell types and cellular behaviors through development and in response to environmental circumstances, such as interaction with water and the light–dark cycle of the Earth. Here, we leverage the smallest, and possibly most structurally reduced, plant, the semiaquaticWolffia australiana, to understand dynamics of cell expression in these contexts at the whole-plant level. We examined single-cell-resolution RNA-sequencing data and foundWolffiacells divide into four principal clusters representing the above- and below-water-situated parenchyma and epidermis. Although these tissues share transcriptomic similarity with model plants, they display distinct adaptations thatWolffiahas made for the aquatic environment. Within this broad classification, discrete subspecializations are evident, with select cells showing unique transcriptomic signatures associated with developmental maturation and specialized physiologies. Assessing this simplified biological system temporally at two key time-of-day (TOD) transitions, we identify additional TOD-responsive genes previously overlooked in whole-plant transcriptomic approaches and demonstrate that the core circadian clock machinery and its downstream responses can vary in cell-specific manners, even in this simplified system. Distinctions between cell types and their responses to submergence and/or TOD are driven by expression changes of unexpectedly few genes, characterizingWolffiaas a highly streamlined organism with the majority of genes dedicated to fundamental cellular processes.Wolffiaprovides a unique opportunity to apply reductionist biology to elucidate signaling functions at the organismal level, for which this work provides a powerful resource.

Biochemistry & Molecular Biology↗

Structured interactions drive abrupt transitions in the spatial organization of microbial communities

Bacteria possess diverse mechanisms to regulate their motility in response to environmental and physiological signals, enabling them to navigate complex habitats and adapt their behavior. Some of these mechanisms are species specific and enable cells to modulate their movement based on the ecological identity of neighboring species. Here, we introduce a model in which bacteria interact via local signals that either enhance or suppress the motility of neighboring cells depending on species type. Through large-scale simulations and a coarse-grained stochastic model, we demonstrate the emergence of a sharp transition driven by nucleation processes: increasing the density of motility-suppressing interactions drives the system from a fully mixed, motile phase to a state characterized by large, stationary bacterial clusters. Remarkably, in systems with a large number of interacting species, this transition can be triggered solely by altering the structure of the motility-regulation interaction matrix while maintaining species and interaction densities constant. In particular, we find that heterogeneous and modular interactions promote the transition more readily than homogeneous random ones. These findings add a dimension to the theory of motility-induced phase separation and contribute to the ongoing effort to understand microbial interactions, suggesting that structured, nonrandom ones may be key to reproducing commonly observed spatial patterns in microbial communities.

bacterial communities↗

Probabilistic measures for biological adaptation and resilience

This paper introduces an approach to quantifying ecological resilience in biological systems, particularly focusing on noisy systems responding to episodic disturbances with sudden adaptations. Incorporating concepts from nonequilibrium statistical mechanics, we propose a measure termed “ecological resilience through adaptation,” specifically tailored to noisy, forced systems that undergo physiological adaptation in the face of stressful environmental changes. Randomness plays a key role, accounting for model uncertainty and the inherent variability in the dynamical response among components of biological systems. Our measure of resilience is rooted in the probabilistic description of states within these systems and is defined in terms of the dynamics of the ensemble average of a model-specific observable quantifying success or well-being. Our approach utilizes stochastic linear response theory to compute how the expected success of a system, originally in statistical equilibrium, dynamically changes in response to a environmental perturbation and a subsequent adaptation. Importantly, the resulting mathematical derivations allow for the estimation of resilience in terms of ensemble averages of simulated or experimental data. Finally, through a simple but clear conceptual example, we illustrate how our resilience measure can be interpreted and compared to other existing frameworks in the literature. The methodology is general but inspired by applications in plant systems, with the potential for broader application to complex biological processes.

60 APPLIED LIFE SCIENCES↗

Capacitive response of biological membranes

We present a minimal model to analyze the capacitive response of a biological membrane subjected to a step voltage via blocking electrodes. Through a perturbative analysis of the underlying electrolyte transport equations, we show that the leading-order relaxation of the transmembrane potential is governed by a capacitive timescale, τ_{C}=λ_{D}L/D(2+Γδ^{M}/L/4+Γδ^{M}/λ_{D}), where λ_{D} is the Debye screening length, L is the electrolyte width, Γ is the ratio of the permittivity of the electrolyte to the membrane, δ^{M} is the membrane thickness, and D is the ionic diffusivity. This timescale is considerably shorter than the traditional RC timescale λ_{D}L/D for a bare electrolyte due to the membrane's low permittivity and finite thickness. Beyond the linear regime, however, salt diffusion in the bulk electrolyte drives a secondary, nonlinear relaxation process of the transmembrane potential over a longer timescale τ_{L}=L^{2}/4π^{2}D. A simple equivalent-circuit model accurately captures the linear behavior, and the perturbation expansion remains applicable across the entire range of observed physiological transmembrane potentials. Together, these findings underscore the importance of the faster capacitive timescale and nonlinear effects on the bulk diffusion timescale in determining transmembrane potential dynamics for a range of biological systems.

Farhadi, Jafar↗