Biology subjects

Pawar, S.

Publications and source records attributed to Pawar, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Development of an HK-fbp1-based vaccine platform against Cryptococcus neoformans

Cryptococcal meningitis remains a leading cause of death among HIV/AIDS patients, and no antifungal vaccine is available in clinical use. We previously showed that mice immunized with a heat-killed preparation of Cryptococcus neoformans (Cn) fbp1{Delta} mutant (HK-fbp1) are protected against cryptococcosis and other invasive mycoses, suggesting that HK-fbp1 is an intriguing vaccine candidate for further study. Recent studies have reported that heat-killed wild type H99 (HK-H99) can also offer some protection in other vaccination models. Here we set out to decipher the differential protective capacity of HK-fbp1 versus HK-H99 across multiple conditions. We observed that HK-fbp1 confers superior protection in both prophylactic and therapeutic intranasal immunization settings than HK-H99, which was associated with greater activation of pulmonary CD4+ T cells and stronger airway IFN-{gamma} production. In addition, HK-fbp1 preparations were highly stable, retaining full protective efficacy even after 5 years of frozen storage. Mice intranasally immunized with two-dose HK-fbp1 were protected against challenge by up to 106 H99 cells, a 100-fold increase over the commonly used lethal inoculum. Addition of a CpG adjuvant ODN to HK-fbp1 (HK-bp1/ODN) led to a 5-fold reduction of the intranasal vaccine inoculum required for protection, and its single-dose intramuscular vaccination induced protection persisted for at least 3 months post vaccination. Together, these findings highlight the robust protective capacity and formulation versatility of HK-fbp1, supporting its further development as a stable, dose-sparing antifungal vaccine candidate.

microbiology↗

bioRxiv2026

Combined celecoxib and NDGA induces a non-canonical, autophagy-independent redox cell death via p62/KEAP1 in colorectal cancer

Colorectal cancer (CRC) exhibits substantial intratumoral heterogeneity, with differences in oncogenic driver mutations and apoptotic competence contributing to therapeutic resistance. Here, we investigated whether combined celecoxib and NDGA treatment (C+N) induces redox-mediated cell death via the p62/KEAP1 axis, offering a therapeutic approach that can overcome genetic diversity in CRC. We used two genetically distinct CRC cell lines, HCT116 and HT29, harbouring KRAS and BRAF mutations respectively, with differing p53 status, as models of tumor heterogeneity. C+N exhibited profound cytotoxicity in both cell lines, independent of COX-2/5-LOX expression and apoptotic competence. Additionally, C+N induced marked oxidative stress with mitochondrial ROS, lipid peroxidation, and labile ferrous iron accumulation, visualized as distinct JC-1 green mitochondrial puncta and FerroOrange red iron puncta in both cell lines. The antioxidant NAC reversed C+N-induced death, but inhibitors of apoptosis, autophagy, necroptosis, or ferroptosis did not, indicating a mechanism distinct from these pathways. Mechanistically, the combination induced p62 Ser349 phosphorylation, promoting KEAP1 degradation and NRF2 stabilization independently of ULK1-mediated autophagy; however, NRF2 stabilization was uncoupled from HO-1 induction. Our work reveals that C+N induces a ULK1/autophagy-independent, redox-mediated cell death mechanism that circumvents apoptotic competence, highlighting redox disruption as a genotype-independent therapeutic strategy to overcome CRC heterogeneity.

cancer biology↗

bioRxiv2026

Ecological and evolutionary drivers of thermal performance curves across the tree of life

Biological rates typically follow a unimodal thermal performance curve (TPC), yet the ecological and evolutionary drivers shaping TPC variation remain poorly understood. We compiled an extensive thermal response database covering 896 TPCs for 416 species and 60 traits, spanning microbes to multicellular organisms. Our analyses reveal three key insights. First, environmental seasonality strongly structures TPCs: species in stable environments exhibit narrower thermal ranges and greater asymmetry, with environmental temperature outperforming latitude as a predictor. Second, trait type and organismal complexity modulate thermal sensitivity: emergent traits have narrower ranges than physiological traits, and complex organisms display reduced heat tolerance. Third, prokaryotes and eukaryotes differ fundamentally: while prokaryotes shift thermal limits symmetrically, eukaryotes show constrained upper limits relative to cold tolerance. These findings highlight how environmental stability, trait organization, and evolutionary history shape species thermal niches, providing crucial insights into vulnerability and adaptation under climate change.

ecology↗

bioRxiv2026

Fibroadipogenic Progenitor Cells Contribute to Tongue Skeletal Muscle Hypertrophy in Beckwith-Wiedemann Syndrome

Beckwith-Wiedemann syndrome (BWS) is a pediatric imprinting disorder characterized by tissue overgrowth, most commonly macroglossia, which can result in airway and feeding complications. Although dysregulated growth is a defining feature of BWS, the cellular interactions that drive organ-specific overgrowth remain poorly understood. We previously demonstrated that BWS macroglossia arises through distinct cell-intrinsic and cell-extrinsic mechanisms depending on molecular subtype. Here, we identify fibroadipogenic progenitor cells (FAPs) as modulators of myogenic differentiation and fusion in the human BWS tongue. BWS-derived FAPs were not increased in abundance in situ and did not exhibit hyperproliferation in vitro. Instead, FAPs from one BWS subtype promoted enhanced differentiation and fusion of normal human myoblasts. Secretome profiling revealed enrichment of CATHEPSIN L and TRANSFERRIN in conditioned media from these FAP populations, and functional perturbation of these factors supported their role in regulating myogenesis. These findings define a non-cell-autonomous mechanism of muscle overgrowth and implicate mesenchymal-myogenic signaling as a context-dependent driver of tissue expansion in an imprinting disorder.

cell biology↗

bioRxiv2026

Lipid Flippase Mediated Membrane Asymmetry Governs Extracellular Vesicles Biogenesis and Host Interactions in Cryptococcus neoformans

Cryptococcus neoformans is the leading cause of fungal meningitis in immunocompromised patients. Alveolar macrophages are the first line of defense against Cryptococcus infection. Our previous study showed that deletion of Cdc50, the regulatory subunit of P4-ATPase (lipid flippase) complex, results in increased phagocytosis and macrophage killing, and avirulence in animal models. However, how fungal flippase dysfunction modulates Cryptococcus-macrophage interaction remains unknown. Here we identify Cdc50 as a central determinant of membrane lipid homeostasis, extracellular vesicle (EV) biogenesis and macrophage responses in C. neoformans. Our whole cell lipidomic analysis revealed that loss of Cdc50 disrupted membrane lipid homeostasis leading to phospholipid enrichment in cdc50{Delta} mutant, and a reduction in fatty acid production accompanied by pronounced ultrastructural defects in membrane architecture. Loss of Cdc50 also induced a hyper-vesiculating phenotype, with cdc50{Delta} producing significantly more extracellular vesicles (EVs) than wild type H99 cells. Lipidomic profiling of cdc50{Delta} EVs revealed enrichment of phospholipids, including phosphatidylserine (PS), indicating active lipid sorting during vesicle biogenesis. Functional analysis showed that EVs from the wildtype H99 suppress phagocytosis whereas cdc50{Delta} EVs enhance phagocytosis, indicating a differential macrophage priming. Despite increased PS externalization in cdc50{Delta} cells and EVs, macrophage recognition and uptake occur independent of PS-mediated efferocytosis pathways, including PS receptor MertK. Following macrophage uptake, cdc50{Delta} were intrinsically vulnerable to macrophage killing due to rapid phagosome acidification. Together, we demonstrate that Cdc50 dependent lipid homeostasis regulates EV production, lipid composition, membrane architecture and drives the intracellular fate of C. neoformans. IMPORTANCECryptococcus neoformans is the leading cause of fungal meningitis in immunocompromised individuals. Understanding how this pathogen evades host immune mediated clearance is essential for developing new treatment strategies. Here, we demonstrated that Cdc50, the regulatory subunit of fungal lipid flippase complex, regulates membrane lipid homeostasis that governs extracellular vesicles (EV) biogenesis and macrophage immune responses. Loss of Cdc50 drives global membrane lipid remodeling, hyper-production of phospholipid enriched EVs that enhance macrophage phagocytosis, while the wild-type EV reduce macrophage phagocytosis. Contrary to the prevailing assumption that phosphatidylserine (PS) externalization on the fungal surfaces mimics the mammalian "eat-me signal", we show fungal PS does not engage canonical PS receptor MertK, revealing a fundamental difference between fungal and mammalian PS biology. Furthermore, cdc50{Delta} cells are unable to resist phagosomal acidification, rendering them susceptible to macrophage killing. These findings establish how phospholipid homeostasis contributes to early host-pathogen interactions and serves as a compelling antifungal target in cryptococcosis.

microbiology↗

bioRxiv2026

A SuperSelective primer-based real-time PCR Platform for hypersensitive detection of azole heteroresistance in Cryptococcus neoformans

Cryptococcus neoformans is the leading cause of fungal meningitis with limited treatment options, making early and accurate diagnosis critical for improved patient outcome. Current diagnostic methods for cryptococcosis rely largely on capsule antigen detection and fungal culture, which are time-consuming and unable to identify mutation-driven antifungal heteroresistance. In this study, we have developed a SuperSelective primer-based PCR (SSP-PCR) platform for the rapid and specific detection of azole resistance-associated single-nucleotide polymorphisms (SNPs). We demonstrate that SSP-PCR reliably detected a single copy mutant allele in the presence of excess wild-type (WT) DNA, with sensitivity reaching a 1:104 mutant-to-WT ratio. Incorporating molecular beacon (MB) probes with our SSP-PCR platform further enhanced amplification specificity, enabling selective detection of the ERG11 Y145F (A434T) mutation that is known to cause high azole resistance. Using genomic DNA from in vitro cultures and mouse lung tissues infected with either WT strain H99 strain or a fluconazole-hyper-resistant mrl1 clinical isolate that carries the ERG11(A434T) mutation, or both strains, we successfully detected the A434T mutant allele in both settings. Moreover, our SSP-PCR simultaneously identified ERG11(A434T) and the multi-azole resistance-associated ERG11(G1885A) mutant alleles in a single-tube duplex reaction. Collectively, the SSP-PCR platform provides a robust and ultrasensitive molecular approach for the detection of azole resistance and heteroresistance in C. neoformans, with strong potential for high-throughput clinical screening applications. ImportanceInvasive fungal infections are a growing public health threat, causing over 1.5 million deaths annually, with cryptococcal meningitis accounting for over 15% HIV/AIDS related mortality. The problem is aggravated by limited treatment options and emerging of drug resistance. Long-term use of fungistatic azoles like fluconazole promotes the emergence of azole heteroresistance, contributing to clinical treatment failure. Current diagnostic assays often fail to detect resistance-associated mutations within heterogeneous fungal populations, limiting their clinical utility. In this study, we developed a SuperSelective primer-based PCR (SSP-PCR) platform for the rapid and ultrasensitive detection of azole resistance associated single-nucleotide polymorphisms (SNPs) in Cryptococcus neoformans. By integrating molecular beacon probes, this assay achieves high specificity and enables simultaneously detection of multiple SNP mutations in a single reaction. Our SSP-PCR platform offers a powerful molecular approach for identifying azole resistance and heteroresistance, with strong potential to improve diagnostic precision and guide antifungal therapy in clinical settings.

microbiology↗

bioRxiv2026

Structural Complementarity Maximizes Feasibility and Stability in Microbial Community Coalescence

Microbial communities frequently coalesce through dispersal, disturbance, or deliberate transplantation, yet the dynamical consequences of such coalescence remain poorly understood. Here, we show that coalescence can function as a structural design mechanism to enhance microbial community robustness. Using a mechanistic consumer-resource model in which the balance between competition and metabolic cooperation is explicitly tunable, we quantify how interaction structure shapes both feasibility, namely the environmental domain supporting coexistence, and dynamical stability. Cooperation-dominated communities exhibit greater but more variable feasibility and intrinsic stability than competition-dominated communities. Strikingly, coalescing communities with maximally distinct interaction structures consistently maximizes both feasibility and stability by reducing alignment among interaction vectors and strengthening effective self-regulation in the resulting assemblage. Heterogeneous coalescence balances reduced facilitation, moderated interspecific effects, and stronger self-regulation. These results identify structural complementarity as a general principle for assembling robust microbial ecosystems and provide a theoretical foundation for microbiome engineering strategies that enhance persistence and functional stability.

ecology↗

bioRxiv2025

A Novel Method to Simultaneously Estimate Bacterial Respiration and Growth from Oxygen Dynamics

Bacterial growth and respiration are fundamental metabolic processes that affect how energy is used and impact carbon sequestration at the ecosystem scale. However, these traits are usually quantified independently, growth is quantified with endpoint biomass measurements while respiration is quantified by monitoring oxygen or carbon dioxide. Because the two physiological traits are collected at different temporal and volumetric scales (hours-to-days for growth versus minutes-to-hours for respiration), reconciling them is challenging and often introduces scale-mismatch bias, obscuring causal links between metabolism and environmental drivers. In this study, we develop a novel method for quantifying the rates of bacterial growth and respiration concurrently from a single dissolved oxygen time series. Our approach introduces a model that couples exponential biomass growth with biomass-specific respiration, enabling the simultaneous inference of both rates in real time. We applied our high throughput method to 15 bacterial strains isolated from natural environments. Our approach yielded growth estimates in close agreement with measurements based on popular methods using optical density or flow cytometry (R2 > 0.9) with no evidence of taxon-specific bias. We also tested our approach in quantifying the effects of temperature on respiration, growth and carbon use-efficiency in Pseudomonas sp. Our method yielded typical unimodal thermal response curves for growth and respiration where rates were highest at moderate temperatures, while carbon-use efficiency increased from cooler temperatures, peaked around the thermal optimum ([~]30-35 {degrees}C), and declined at high temperature. By quantifying respiration and growth simultaneously and in high throughput, our approach effectively enables measurement of microbial metabolic strategies and adaptations to stress. It offers a non-invasive and scalable tool for high throughput phenotyping and studies of environmental perturbations, enabling a new class of trait-based microbial ecology that links cellular physiology to broader ecosystem function.

microbiology↗

bioRxiv2025

Multi Omics Driven Polypharmacology for Osteoarthritis Joint Regeneration

Osteoarthritis (OA) is a common degenerative condition of major joints with no effective cure. Yograj Guggulu (YG) is a well-established polyherbal formulation in Indian traditional medicine for the management of joint disorders. However, its mode of action remains unclear. We integrated multi omics network analysis with a rat model to investigate the effects of oral administration of YG on osteoarthritic joints. YG administration significantly alleviated pain and improved joint function. Imaging and histological analyses reveal that YG protects against structural degeneration in the joint with OA. Proteomic and metabolomic profiling, along with network analysis, uncovered that multiple components of YG alter protein expression in key pathways related to inflammation and cartilage degradation, thus validating the observed clinical effects. The efficacy of YG seems to be the result of the synergistic action of its diverse constituents. Our findings support the use of YG as a multitarget therapy for OA and encourage efforts for the potential repurposing of its active components.

systems biology↗

bioRxiv2025

Mannoprotein Cig1 Contributes to the Immunogenicity of a Heat-Killed F-box Protein Fbp1 Cryptococcus neoformans Vaccine Model

Currently, no fungal vaccine exists for clinical use while fungal infections are responsible for over 1.5 million deaths every year. Our previous studies identified a Cryptococcus neoformans mutant strain fbp1{Delta} as a potential vaccine candidate. This mutant strain contains a deletion of the F-box protein Fbp1, a key subunit of the SCF E3 ligase complex necessary for ubiquitin-mediated proteolysis. Vaccination with heat-killed fbp1{Delta} (HK-fbp1) can elicit protection against C. neoformans parental strain and its sibling species C. gattii in an interferon gamma (IFN-{gamma}) dependent Type 1 immune response. However, we have yet to decipher the immunogenic factor(s) expressed by the fbp1{Delta} mutant that are responsible for the induction of the protective immune response. In this study, we have identified that capsule plays an important role in HK-fbp1 vaccine mediated protection, as acapsular HK-fbp1 cells showed diminished protection against wild type challenge. Additionally, our studies have shown that Cytokine Inducing Glycoprotein 1 (Cig1), a GPI anchored mannoprotein, is regulated by Fbp1 and contributes to the immunogenicity of HK-fbp1. Deletion of Cig1 in the fbp1{Delta} background resulted in decreased recruitment of anti-fungal effector T cells and diminished production of protective inflammatory cytokines by the host. Furthermore, loss of Cig1 in the fbp1{Delta} mutant resulted in reduced protection in vaccination survival studies at lower vaccine inoculum doses compared to HK-fbp1. In aggregate, these findings demonstrate Cig1 is an antigen contributing to the immunogenicity of HK-fbp1 that may be utilized to further optimize the HK-fbp1 fungal vaccine as a tool in the arsenal against invasive fungal infections.

microbiology↗

bioRxiv2025

A General Framework for Predicting the Temperature-Dependence of Microbial Interactions

Despite its global importance, our ability to predict the impacts of temperature change on the community dynamics of heterotrophic microbes remains limited. Here, we develop a metabolic trait-based mathematical framework to predict the temperature dependence of pairwise interactions among heterotrophic microbial consumers, accounting for their resource environment and community composition. Applying this framework leads to two general predictions. First, microbial species interactions are typically more thermally sensitive than the underlying metabolic traits. Second, temperature systematically reshapes intra- and interspecific interactions: their variance peaks at intermediate temperatures, while mean interaction strengths increase with warming more rapidly than interspecific interaction strengths. We show that these features of temperature-dependent interactions have far-reaching implications for the temperature responses of community coexistence, diversity, and stability. Our framework provides a mechanistic foundation for predicting how temperature affects the dynamics of heterotrophic microbial communities across diverse biological and environmental contexts. SignificanceCommunities of heterotrophic microbes, including bacteria, archaea, protists, and fungi, play a fundamental role in human health, bioprocessing, and global biogeochemical cycles. Predicting their responses to environmental change is a major challenge, with a key missing link being the effects of temperature on species interactions that ultimately shape community dynamics. By integrating metabolic constraints into consumer-resource theory, we derive general predictions about how interactions among heterotrophic microbial species respond to temperature changes. We show that interactions are more sensitive to warming than individual metabolic traits and undergo systematic temperature-dependent changes that alter community-level coexistence, diversity, and stability. These results hold across diverse environmental contexts and heterotrophic systems, providing a foundation for predicting how microbial community dynamics respond to environmental temperature, from biotechnological applications to natural ecosystems.

ecology↗

bioRxiv2025

Accuracy of the Lotka-Volterra Model fails in strongly coupled microbial consumer-resource systems

The generalized Lotka-Volterra (GLV) model is a cornerstone in theoretical ecology for modeling the dynamics emerging from pairwise species interactions within complex ecological communities. The GLV is also increasingly being used to infer species interactions and predict dynamics from empirical data on microbial communities in particular. However, despite its widespread use, the accuracy of the GLVs pairwise interaction structure in capturing the unseen dynamics of microbial consumer-resource interactions--arising from resource competition and metabolite exchanges--remains unclear. Here, we rigorously quantify how well the GLV can represent the dynamics of a general mathematical model that encapsulates key consumer-resource processes in microbial communities. We find that the GLV significantly misrepresents the feasibility, stability, and reactivity of microbial communities above a threshold, biologically feasible level of consumer-resource coupling because it omits higher-order nonlinear interactions. We show that the probability of the GLV making inaccurate predictions can be quantified by a simple, empirically accessible measure of timescale separation between consumers and resources. These insights advance understanding of the temporal dynamics in resource-mediated microbial interactions and provide a method to gauge the GLVs reliability under various empirical and theoretical scenarios.

ecology↗

bioRxiv2025

MIReVTD, a Minimum Information Standard for Reporting Vector Trait Data

Vector-borne diseases pose a persistent and increasing challenge to human, animal, and agricultural systems globally. Mathematical modeling frameworks incorporating vector trait responses are powerful tools to assess risk and predict vector-borne disease impacts. Developing these frameworks and the reliability of their predictions hinge on the availability of experimentally derived vector trait data for model parameterization and inference of the biological mechanisms underpinning transmission. Trait experiments have generated data for many known and potential vector species, but the terminology used across studies is inconsistent, and accompanying publications may share data with insufficient detail for reuse or synthesis. The lack of data standardization can lead to information loss and prohibits analytical comprehensiveness. Here, we present MIReVTD, a Minimum Information standard for Reporting Vector Trait Data. Our reporting checklist balances completeness and labor- intensiveness with the goal of making these important experimental data easier to find and reuse, without onerous effort for scientists generating the data. To illustrate the standard, we provide an example reproducing results from an Aedes aegypti mosquito study.

ecology↗

bioRxiv2024

The Association Between Prevotella copri and Advanced Fibrosis in the Progression of Metabolic Dysfunction-Associated Steatotic Liver Disease

Metabolic dysfunction-associated steatotic liver disease (MASLD), driven by obesity and metabolic syndrome, is increasingly prevalent and a significant contributor to liver fibrosis, cirrhosis, and liver-related mortality. Emerging research implicates the gut microbiome as a critical player in MASLD progression, yet specific microbial drivers remain poorly understood. Here, we explore the role of Prevotella copri (P. copri) in MASLD progression through both human patient cohorts and a mouse model of diet-induced obesity. Using 16S rRNA sequencing, we identified elevated P. copri abundance in MASLD patients with advanced fibrosis, linked with significant shifts in microbial diversity and bacterial network connectivity. To investigate causality, experimental colonization of P. copri in mice on a high-fat diet worsened MASLD progression, with P. copri-colonized mice showing significant increases in hepatic steatosis, liver triglyceride accumulation, and body weight, independent of caloric intake. At the molecular level, P. copri colonization downregulated key lipid metabolism genes, such as Carnitine Palmitoyltransferase 1, Diacylglycerol Acyltransferase, and Adipose Triglyceride Lipase, and impaired tight intestinal junction integrity through the downregulation of cluadins, occludin, and zonula occludens-1. Collectively, our findings position P. copri as a possible driver of MASLD progression by promoting hepatic steatosis through lipid and triglyceride accumulation and fibrosis through decreased tight junction integrity. These insights suggest a promising therapeutic avenue to target specific microbial signatures like P. copri to curb MASLD progression and mitigate the associated risk of advanced fibrosis.

microbiology↗

bioRxiv2024

Microbial Differences Accurately Identifies Global SERT KO Phenotype in Mice

Altered serotonin signaling is a well-established contributor to depression, with the serotonin transporter gene (SERT) playing a critical role in regulating serotonin reuptake. Mice lacking SERT (SERT -/-) serve as a robust model for depression, exhibiting significant depressive-like behaviors compared to littermate wild-type (SERT +/+) controls. In this study, we aimed to determine the relationship between gut microbiota composition and depressive behaviors in SERT -/- mice. Behavioral assays, including the Forced Swim Test (FST) and Tail Suspension Test (TST), confirmed that SERT -/- mice exhibited significantly increased immobility times compared to SERT +/+ mice (FST: p = 0.004; TST: p = 0.080), consistent with a depressive phenotype. Utilizing littermate controls, shotgun metagenomic sequencing of fecal samples revealed significant differences in alpha diversity between the two groups of mice, as measured by the Shannon entropy index (p = 0.05). Additionally, our bacterial co-occurrence network analysis uncovered distinct structural differences in microbial interactions between SERT -/- and SERT +/+ mice (p = 0.001), suggesting shifts in microbiome stability and functionality between the groups. We created a microbial depression score utilizing the top five bacteria taxa that were differentially abundant between SERT -/- and SERT +/+ mice: Clostridium sp. MD294, Acetatifactor MGBC165152, Desulfovibrio MGBC129232, Oscillibacter MGBC161747, and Schaedlerella MGBC000001. This microbial depression score correlated strongly with immobility times in the FST (r = 0.705, p < 0.0006) and TST (r = 0.401, p < 0.09). A random forest classifier based on these taxa accurately distinguished SERT -/- from SERT +/+ mice (accuracy = 0.82). These findings suggest that gut microbial species composition is highly associated with depressive-like behaviors in SERT -/- mice, likely via alterations in serotonin signaling pathways, and may offer potential targets for microbiome-based interventions in depression.

microbiology↗

bioRxiv2024

Changes in flexibility but not in compactness underlie the thermal adaptation of prokaryotic adenylate kinases

Understanding the structural changes that enable enzymes to remain active in extreme thermal conditions is of broad scientific interest for both fundamental and applied biological research. Three key mechanisms that underlie the thermal adaptation of enzymes are modifications in structural flexibility, compactness, and the contacts formed among amino acids. However, most previous studies on these topics have been limited to small sample sizes or a narrow taxonomic focus, and the importance of these factors to thermal adaptation remains poorly understood. In this study, we combined molecular dynamics simulations and phylogenetic comparative analyses to thoroughly analyse the structural factors underlying thermal adaptation in adenylate kinase--a key enzyme involved in cellular energy balance and homeostasis--across 70 prokaryotic species. We detect systematic increases in the flexibility of the enzyme with temperature, both across and within species. In contrast, structural compactness appears to be almost completely independent of temperature. Finally, we uncover a remarkable diversity in the number and types of amino acid contacts observed in different adenylate kinases that cannot be explained solely by temperature. Our results suggest that there are multiple paths toward the adaptation of prokaryotic adenylate kinases to extreme thermal environments and that these paths are generally accessible through changes in flexibility. Lay summaryThe structure of a given enzyme can vary considerably among species, reflecting local environmental conditions to an extent. To this day, we do not have a clear picture of the impacts of the thermal environment on enzyme structure. To fill this gap, we performed a structural comparison of the enzyme adenylate kinase (ADK) from 70 species of bacteria and archaea. We find that rises in temperature tend to increase the flexibility of the enzyme. However, at any given temperature, ADKs from cold environments tend to be more flexible than those from hot environments. In contrast, the compactness of the enzyme did not vary consistently with temperature. Finally, we found that the pattern of amino acid contacts can vary dramatically across ADKs of different species, in a manner that cannot be predicted by temperature alone. Overall, our study shows that there are multiple ways to evolve an enzyme structure that can tolerate extreme temperatures, with a key constraint being maintaining sufficient flexibility at temperatures typically experienced by each species.

evolutionary biology↗

bioRxiv2024

The Role of Metabolic Strategies in Determining Microbial Community Diversity along Temperature Gradients

By conservative estimates, microbes make up about 17% of the worlds biomass and are essential for most ecosystem functions. However, the mechanisms driving the variation in microbial species diversity in response to both natural and anthropogenic temperature gradients remain unclear. In this study, we integrate ecological metabolic theory with a community assembly model to predict that microbial community diversity generally follows a unimodal pattern with temperature. The position and magnitude of peak diversity are determined by interaction-driven species sorting acting on variations in the temperature dependence of carbon use efficiency (CUE) and generalist-specialist tradeoff. Specifically, trait sorting across temperatures favours communities with high mean and low variance in species-level CUEs. We provide empirical evidence supporting our qualitative predictions of the unimodal temperature-diversity pattern along the global geological temperature gradient, which peaks at about 10-15 {degrees}C. Our findings indicate that the response of diversity as well as CUE to temperature of microbial communities can be predicted from relatively feasible life-history trait measurements, paving the way for interlinking microbial community diversity and carbon cycling along spatial and temporal thermal gradients.

ecology↗

bioRxiv2024

Divergence of discrete- versus continuous-time calculations of the temperature dependence of maximum population growth rate in a disease vector

O_LIThe temperature dependence of maximal population growth rate (rm) is key to predicting how organisms respond and adapt to natural and anthropogenic changes in climate. For organisms with complex life histories, discrete-time matrix projection models (MPMs) can be used to calculate temperature-dependent rm because they directly capture variation in empirically-observed life-history trait values as well as the time delays inherent in those traits. C_LIO_LIHowever, MPM calculations can be laborious and do not capture the continuous nature of time. Temperature-dependent rm calculated from more complex approaches based on delay-differential equation and integral projection models are more accurate but are notoriously difficult to parameterise. Ordinary differential equation-based models (ODEMs) offer a relatively tractable alternative of intermediate complexity but it is largely unknown whether ODEM-based calculations and MPMs broadly agree when the effects of time delays and altered juvenile survival trajectories on temperature-dependent rm are introduced by environmental variation. C_LIO_LIHere we investigate differences in the predicted temperature dependence of rm obtained from an ODE-based model with those calculated from MPMs using high-resolution temperature- and resource dependent life-history trait data for the globally-distributed disease vector, Aedes aegypti. C_LIO_LIWe show that the level of agreement between discrete- and continuous-time representations of temperature-dependent rm can vary with resource availability, and is extremely sensitive to how juvenile survival is characterised. This finding suggests that analytic rm models can consistently provide comparable rm predictions to standard methods except for under severe resource constraints. C_LIO_LIOur study also suggests that all formulations of the intrinsic growth rate of a population may not be equally accurate for all types of organisms in all situations. Furthermore, this studys findings raise questions relating to whether existing mathematical models can be used to predict and understand population-level effects of environmental change. C_LI

ecology↗