Biology subjects

Liu, J.

Publications and source records attributed to Liu, J..

At least 163 records · Page 9Linked to original sources

bioRxiv2026

FALCON: Closed-Loop Multi-Objective Optimization of Lipid Nanoparticles for Cell-Selective mRNA Delivery

Efficient, cell type-selective delivery of genetic payloads remains a central challenge in the development of gene and cell therapies. Lipid nanoparticles (LNPs) offer a versatile delivery platform, but their optimization is hindered by reliance on brute-force screening methods that are laborious, resource-intensive, and focus on single targets. Here, we present FALCON (Framework for Active Learning-driven Compositional Optimization of Nanoparticles), a closed-loop pipeline that leverages iterative screening, surrogate modeling, and multi-objective optimization to accelerate LNP compositional design. In B cell-targeted validation experiments, FALCON-optimized LNPs achieved a 1.8-fold increase in splenic B cell transfection in vivo compared with reference compositions. When optimized for selectivity, FALCON LNPs displayed an 84-fold improvement in selective transfection of splenic B cells over off-target liver populations and enabled spleen-tropic behavior across factorial panels of varying ionizable and helper lipid chemistries. In vaccine studies, these LNPs induced higher IgG2c antibody titers and a more Th1-biased immune profile. FALCON was also deployed to optimize LNPs for myeloid cell-selective delivery, achieving enhanced in vivo selectivity following systemic administration both across and within spleen and liver compartments. Our results establish FALCON as a useful tool for data-driven design of LNP compositions for precision gene delivery.

bioengineering↗

bioRxiv2026

DesignMaster: A Multi-Conditional Diffusion Framework for Rational PROTAC Design

MotivationProteolysis-targeting chimeras (PROTACs) enable targeted protein degradation through ternary complex formation with E3 ubiquitin ligase. However, the rational design of PROTACs remains highly challenging due to limited structure-activity relationship data and the vast conformational diversity of linkers. Existing computational approaches can be broadly divided into structure-based ternary modelling methods and fragment-based linker generation models. Although these approaches have advanced PROTAC design, they typically neglect key physicochemical constraints and linker-length control during the generation process, causing the generated PROTACs to lack balanced structural properties required for effective ternary complex formation with drug-like characteristics. ResultsTo address these limitations, we propose DesignMaster, a diffusion-based generative framework that explicitly incorporates linker length and physicochemical properties as controllable conditioning signals. DesignMaster employs an E(3)-equivariant graph Transformer with a gated multi-condition fusion module to inject linker length and physicochemical constraints throughout the diffusion process, enabling fine-grained and constraint-aware molecular generation. Experiments on PROTAC-DB 2.0 and 3.0 demonstrate that DesignMaster outperforms state-of-the-art baselines, with a 3.2% improvement in validity and a 34.4% improvement in recovery. The Case study shows DesignMaster achieves a 51.78% reduction in RMSD when predicting the linker of PROTAC BCPyr targeting 6W7O, highlighting its potential for practical structure-guided PROTAC design. AvailabilityThe source code and datasets are available at https://github.com/ABILiLab/DesignMaster.

bioinformatics↗

bioRxiv2026

Improving All-Atom Molecular Dynamics Models for Quantitative Prediction of Nanopore Blockade Current

All-atom molecular dynamics has become an indispensable tool in development of nanopore sensors of biological information. In a typical nanopore experiment, measurements of ionic current flowing through a nanopore report on the chemical structure of biomolecules that pass through the nanopore. Such experiments alone are often insufficient to relate the structure of the biomolecules to the ionic current modulations. The molecular dynamics method can establish such a relationship directly through a brute force simulation under applied electric field. Here, we examine the ability of molecular dynamics force fields to reproduce experimentally measured nanopore blockade currents produced by single-stranded DNA. Our simulations show that none of the "off the shelf" force fields (CHARMM36, AMBER Parmbsc1 and DES-AMBER) is capable of reproducing experimental data with the desired level of accuracy. To improve the accuracy, we examined and refined interactions between ions, protein nanopores and DNA, guided by experiments designed specifically for this purpose. Ultimately, the introduction of surgical corrections to non-bonded interactions within the CHARMM36 force field produced a favorable agreement between simulation and experiment. This refined parameterization, initially developed for nanopore sensing simulations, may have broader applications in computational studies of DNA-protein systems.

biophysics↗

bioRxiv2026

GYS2 Promotes the Progression of Aortic Dissection and Aortic Aneurysm via C5a/NF-κB-Mediated Pro-Inflammatory Macrophage Polarization

BackgroundAortic aneurysm and aortic dissection (AAD) are lethal cardiovascular emergencies characterized by sudden onset and extremely high early mortality. The pro-inflammatory polarization of macrophages is one of the core factors driving the pathogenesis of AAD, but its underlying mechanism remains unclear. This study focuses on the aberrant expression of glycogen synthase 2 (GYS2) in the AAD microenvironment and its role in driving macrophage polarization toward the pro-inflammatory M1 phenotype. MethodsProteomic analysis was conducted to identify protein heterogeneity associated with AAD. Clinical and animal samples were used to evaluate the correlation between GYS2 expression and AAD progression. Whole-body GYS2 knockout mice and adeno-associated virus (AAV)-mediated macrophage-specific gain- and loss-of-function models were utilized to investigate the regulatory role of GYS2 in macrophage polarization and complement activation. Downstream molecular pathways were identified and validated through in vitro stimulation and in vivo exogenous C5a rescue experiments. ResultsGYS2 expression was significantly upregulated in AAD tissues and primarily localized in macrophages. Activation of GYS2 by LiCl or macrophage-specific overexpression of GYS2 exacerbated aortic dilation and extracellular matrix degradation, and increased mortality in AAD mice. Conversely, whole-body GYS2 knockout or macrophage-specific GYS2 knockdown suppressed inflammatory factors, significantly reduced the incidence of AAD, and attenuated vascular injury. Mechanistically, excessive GYS2 in macrophages specifically triggered the complement-coagulation cascade, promoting the generation of the potent anaphylatoxin C5a. C5a further bound to its receptor C5AR1, activating the downstream PLC{beta}3/NF-{kappa}B signaling pathway, thereby inducing M1 macrophage polarization and matrix metalloproteinase-mediated extracellular matrix degradation. In vivo exogenous C5a rescue completely reversed the vascular protective effects conferred by GYS2 deficiency. ConclusionsThis study demonstrates that highly expressed GYS2 regulates the pro-inflammatory polarization of macrophages and extracellular matrix degradation via the complement C5a/PLC{beta}3/NF-{kappa}B signaling axis, which is a key mechanism driving AAD progression. Specific inhibition of macrophage GYS2 can effectively alleviate aortic vascular inflammation and prevent AAD progression, providing a promising novel strategy for the clinical conservative treatment of AAD.

Molecular Biology↗

bioRxiv2026

Ecosystem disservices are underrepresented in literature on annual crop agroecosystems

Maximising ecosystem service (ES) benefits while minimising ecosystem disservices (EDS) is essential for ecological intensification in annual crop systems. Yet ecosystem disservices are often underreported in the scientific literature, potentially biasing how agroecosystem functioning is understood. To test this, we built a predicted network of plausible links between ecosystem service providers (taxa or functional groups that can deliver ecosystem services or disservices), and the ES or EDS they may provide. We then compared this with a realised network based on systematic Scopus searches of annual crop literature. The predicted network contained 47 nodes and 103 links, whereas the realised network contained 33 nodes and 58 links, representing declines of 29.8% in nodes and 43.7% in links. Overall connectivity declined, especially for highly connected nodes, and four of the nine predicted disservice nodes were absent from the literature. ES links were more likely to be documented than EDS links, and EDS links were three times more likely to be absent. Across all links, ES were reported in 6.6 times more papers than EDS. Projected networks, which map indirect connections by linking ES directly to EDS if they share common providers, showed that these bundled interactions were strongly reduced, obscuring multifunctionality and trade-offs. This systematic underrepresentation of EDS, reflecting a cognitive bias, can inflate perceived benefits, distort the evaluation of key taxa and interactions, and create unrealistic expectations about intervention outcomes in biological crop protection. Addressing EDS alongside ES is therefore essential for more balanced assessments of crop-system management and better-informed decisions.

ecology↗

bioRxiv2026

Chromosome gigantism and auxin deconjugation underpin gall induction in a horned gall aphid

Insect galls are extended phenotypes built through sustained reprogramming of host development, yet the genomic innovations and effector mechanisms that enable this process remain poorly resolved. Here we generated chromosome-level genomes for the horned gall aphid Schlechtendalia chinensis and its host tree Rhus chinensis, and integrated these resources with morph-resolved salivary proteomics, metabolomics and functional assays. The aphid genome contains an anomalously expanded chromosome 1 spanning 93.61 Mb that carries 33.08% of anchored genes and concentrates 70.47% of genome-wide segmental duplications, together with elevated transposable-element load and multiple tandem gene clusters. We identified a salivary M20-family enzyme, ACY1, that consistent with an auxin-conjugate hydrolase. Loss- and gain-of-function assays show that ACY1 hydrolyzes stored, inactive auxin-amino acid conjugates in host tissue, increasing local active auxin levels. This hormone manipulation reprograms plant cell development to form galls. Our findings demonstrate how concentrated genomic duplication can drive the evolution of an effector that controls host physiology, suggesting a potential principle in the evolution of parasitic traits.

molecular biology↗

bioRxiv2026

PanKbase Integrated Single-Cell Map: A Comprehensive Atlas of Human Pancreatic Islets

Single-cell RNA sequencing (scRNA-seq) of human pancreatic islet tissue is a powerful tool for investigating type 1 diabetes (T1D). However, individual datasets are limited in size and fragmented across donors, laboratories, and experimental conditions. To address this, we constructed a comprehensive, integrated scRNA-seq atlas of isolated human pancreatic islets by collating publicly available data generated from tissue provided by resources including the Human Pancreas Analysis Program, the Integrated Islet Distribution Program, and Prodo Labs. Systematic quality controls were implemented to select high-quality samples, reads, and cells. During integration, we accounted for important variables such as age, sex, body mass index, origin study, treatments, islet distribution resources, and sequencing chemistry. Our single-cell atlas comprises 191 high-quality samples from 140 donors (59 female, 81 male) across five phenotypic groups: no diabetes (controls, n=69), autoantibody positivity without diabetes (n=12), pre-diabetes (n=11), T1D (n=12), and type 2 diabetes (T2D) (n=36). In total, the atlas contains 448,935 cells, capturing 13 distinct populations, including alpha cells (43.3%) and beta cells (26.8%), as well as groups such as immune cells (0.6%). Publicly available at www.pankbase.org, this atlas provides a platform for hypothesis-driven investigation of diabetes pathophysiology and, given rigorous quality control, is well-suited for downstream machine-learning applications. Article HighlightsO_LICurrent scRNA-seq datasets of pancreatic islet tissue are limited in size and scattered across donors, laboratories, and experimental conditions, underscoring the need for a consolidated resource. C_LIO_LIWe harmonized datasets from multiple sources to build a comprehensive single-cell map of isolated human pancreatic islets. C_LIO_LIOur atlas captures 448,935 cells from 191 high-quality samples across 140 donors and multiple phenotypic groups, identifying 13 distinct cell populations. C_LIO_LIAvailable at www.pankbase.org, the atlas provides a scalable, rigorously curated platform to support hypothesis-driven diabetes research and can enable a broad range of downstream computational applications. C_LI

genomics↗

bioRxiv2026

Working Memory as Programmable Fast Weight Computation

Working memory (WM) stores information after sensory input disappears and later retrieves it in a task-relevant format, but the mechanism unifying storage and retrieval remains unclear. Here we combine neural geometry analyses of macaque dorsolateral prefrontal cortex activity during a visuospatial delayed-match-to-sample task with computational modeling to test whether WM can be implemented as recurrent fast-weight computation. We found that the relational geometry of remembered locations was strongly expressed during sample presentation, degraded during the early delay, and reemerged before requirement in a partially distinct mnemonic subspace. A recurrent fast-weight programmer model, which implements a form of dynamic fast-weight memory closely related to linear Transformer computation, reproduced these latent-to-mnemonic dynamics. Direct inspection and perturbation of the model revealed that neural activity writes stimulus information into rapidly modifiable synaptic states, synaptic dynamics organize this latent memory over time, and recurrent readout queries the evolving state to generate task-relevant activity. These findings provide a unified account of WM storage and retrieval and suggest that biological WM and Transformer family architectures share an algorithmic principle of programmable temporary memory.

neuroscience↗

bioRxiv2026

Self-supervised Internal Learning Enhances Isotropic Resolution for Three-dimensional Fluorescence Microscopy

Three-dimensional fluorescence microscopy often exhibits anisotropic resolution because axial information is poorly sampled and more blurred than lateral information, which complicates quantitative interpretation of fine 3D structures. Although optical remedies and computational restoration have been explored, many approaches require demanding system calibration or rely on accurate PSF models and assumptions that are difficult to satisfy across all samples and modalities. Here we present DeepIso, a self-supervised isotropy restoration framework that couples supervised pretraining with an internal-learning inference stage to estimate degradation directly from the measured volume. Without explicit PSF specification or enforced lateral-axial structural equivalence, DeepIso recovers axial frequency content and improves the continuity of elongated structures while retaining fine features, with superior performance over existing computational approaches in terms of both visual inspection and quantitative metrics. The method is validated on synthetic benchmarks and experimental datasets, demonstrating isotropy enhancement across confocal, light-sheet, and 3D structured illumination microscopy, thereby supporting downstream volumetric analysis including segmentation and tracking.

bioengineering↗

bioRxiv2026

Chaperonin recognition of protein dynamics drives drug resistance

The emergence of drug resistance is typically driven by mutations that alter drug-target affinity, yet the role of host cellular machinery regulating these processes remains unclear. Here, we reveal that the chaperonin GroEL/S promotes drug resistance through recognition of protein dynamics. Using directed evolution of E. coli DHFR under antibiotic stress and varying GroEL/S expression, we identify a well-folded resistance variant whose fitness, despite tight inhibitor binding, is critically potentiated by GroEL/S engagement. X-ray crystallography, NMR, molecular dynamics and kinetic modeling reveal that millisecond-timescale flipping of the M20 loop generates steric accessibility and a kinetic window for chaperonin interaction that forcibly displaces tightly bound inhibitors, thereby overriding thermodynamic equilibrium of inhibitor binding to restore the active enzyme pool and preserve metabolic flux. Our findings not only reveal a novel paradigm of "dynamic recognition" where both conformational kinetics and distribution govern chaperonin recognition but also establish chaperonins as "deligandases" that actively modulate in vivo drug binding, suggesting that chaperone surveillance of the cellular proteome extends beyond quality control to govern native protein function. This mechanism defines a previously unrecognized route for the rapid development of drug resistance, with implications for understanding therapeutics of microbial infections and human malignancies.

biophysics↗

bioRxiv2026

Single-cell gene regulatory network reconstruction and key regulator identification using a dual-channel fusion graph convolutional network

Background and objectiveGene regulatory networks are formed by complex regulatory relationships between transcription factors and their target genes. A systematic understanding of these regulatory relationships is crucial for deciphering the molecular mechanisms that underlie cell state transitions under physiological and pathological conditions. Single-cell expression data can reveal cell-type-specific transcriptional regulation, and computational methods have recently been developed to infer gene regulatory networks from single-cell transcriptomics and prior regulatory knowledge. However, existing methods could not explore the common and specific information in expression correlations and prior regulatory knowledge, which can adversely affect prediction performance. MethodsWe propose a novel method for inferring gene regulatory networks from single-cell RNA sequencing data. The proposed method consists of dual-channel graph neural networks and a weight-shared common graph neural network, enabling effective fusion of prior regulatory knowledge with gene co-expression patterns. Furthermore, we formulate a new computational framework built upon the proposed algorithm, which integrates differential gene expression profiles and regulatory changes to identify key regulators that distinguish different cell states. ResultsExperimental results demonstrate that our method significantly improves the accuracy of regulatory inference across multiple datasets, outperforming other state-of-the-art approaches. Our method also exhibits robustness to noise and missing data. Analysis of two single-cell expression datasets suggests that the proposed framework could help identify key regulators involved in tumor metastasis and drug resistance. ConclusionThese results indicate that the proposed method could advance the understanding of the biological mechanisms underlying diseases by reconstructing single-cell gene regulatory networks and identifying key regulators across different cell states.

bioinformatics↗

bioRxiv2026

Lysosomal lipid metabolism promotes tumor cell invasion through local energetics and membrane lipid remodeling

Metabolic vulnerabilities in cancer have been targeted primarily to suppress tumor growth, but less is known about the metabolic requirements for tumor cell invasion. Here we report that lipid catabolism by cytosolic and lysosomal lipases supports pancreatic cancer cell invasion through both overlapping and distinct functional and metabolic mechanisms. Lysosomal acid lipase (LAL)-dependent lipid droplet catabolism promotes invadopodia formation and stabilization, enabling extracellular matrix degradation. In addition to modulating cellular energetics, lipidomics revealed that lipid droplet catabolism regulates cholesterol and membrane phospholipid levels. Using spatially resolved biosensors and cholesterol imaging, we found that lysosomal lipid catabolism occurs at invadopodia and sustains local ATP and membrane cholesterol. These findings identify spatially organized lipid catabolism as a mechanism that couples local energetics and membrane remodeling during the earliest steps of pancreatic cancer cell invasion.

cell biology↗

bioRxiv2026

Transcription factor CCTF1 plays a decisive role in regulating the proteasome activity during archaeal cell division

Archaea of the order Sulfolobales exhibit a highly ordered cell cycle progression similar to that of eukaryotes. It has been demonstrated that degradation of the cell division protein CdvB by the proteasome controls the progression of cell division. However, how the proteasome itself is regulated during the cell cycle is not fully understood. Recently, the cyclically expressed ArsR family transcription factor CCTF1 (cell cycle transcription factor 1) was shown to represses expression of PAN (proteasome-activating nucleotidase) in Sulfolobus acidocaldarius. Here, using biochemical approaches, comparative transcriptomics and proteomics, we provide further insights into the CCTF1 function and show that it regulates PAN expression in Saccharolobus islandicus by binding to an AT-rich palindromic sequence within the pan promoter. We also reassessed the role of the cyclically expressed protein kinase aCcrK in regulation of proteasome activity and conclude that CCTF1, rather than aCcrK, is the primary factor controlling the proteasome activity. These findings advance our understanding of the proteosome-mediated cell cycle regulation in archaea.

microbiology↗

bioRxiv2026

Deep learning-guided design of hydrolases for crystalline PET depolymerization

Poly(ethylene terephthalate) (PET), a ubiquitous polyester used in packaging and textiles, persists in the environment due to its high crystallinity and stability, contributing substantially to global plastic pollution. Enzymatic depolymerization by PET hydrolase (PETase) offers a chemically precise and environmentally sustainable route to convert PET into its monomeric building blocks, enabling recycling. However, practical implementation remains hindered by the rigid, crystalline architecture of PET, which restricts enzyme access and necessitates energy-intensive pretreatment to enable efficient depolymerization. In addition, most PETases achieve only partial depolymerization with low terephthalic acid (TPA) yields and accumulate inhibitory intermediates, while limited thermostability and slow surface kinetics further restrict efficiency. To overcome these barriers, we report VenusPETase, an engineered variant of KbPETase designed using PET-Flow, a state-of-the-art computational framework for PETase engineering. Compared with KbPETase, VenusPETase exhibits a 3.4-fold increase in hydrolytic activity, up to a 27-fold improvement after heat treatment of protein, and a 12 {degrees}C enhancement in thermostability. VenusPETase exhibits rapid degradation across a wide crystallinity range (8%-50%) at 50 {degrees}C, effectively spanning the entire spectrum of commercial PET products. Moreover, VenusPETase outperformed nine high-performance PETases under their respective optimal conditions and degraded untreated PET substrates across 8%-50% crystallinity, producing TPA as over 95% of the released products with minimal intermediate accumulation. X-ray crystallography and molecular dynamics simulations suggest that dynamic modulation, elevated surface electrostatic potential enhance the interaction of VenusPETase with crystalline PET, thereby lowering the hydrolytic energy barrier and improving catalytic performance. We also demonstrate that untreated, postconsumer-PET from nine different products can all be degraded by VenusPETase. The recovered monomers can be directly repolymerized into virgin-quality PET, demonstrating a closed-loop enzymatic recycling process. In a 100 L bioreactor, VenusPETase completely depolymerizes post-consumer crystalline PET (28% crystallinity) within 24 h under 50 {degrees}C. These results establish VenusPETase as a robust biocatalyst that enables efficient, closed-loop recycling of crystalline PET under mild conditions.

biochemistry↗

bioRxiv2026

EZH1/2 inhibition improves immunotherapy response through MHC Class II de-repression and neutrophil reprogramming

Squamous cell carcinoma of the lung is a difficult-to-treat cancer with high prevalence in the US, and particularly in Kentucky. Here, we sought to test if the EZH1/2 inhibitor valemetostat improves anti-PD1 responses in squamous cell lung cancer models, and to develop ex vivo models to test immunotherapy drug combinations. We found that valemetostat augmented anti-tumor responses to anti-PD1 therapy, led to up-regulation of tumor cell specific Major Histocompatibility Complex Class II (MHC Class II), and drove systemic neutrophil maturation. Likewise, Ezh2 knock-out mice produced neutrophils that were more apoptotic, less migratory, and less able to produce extracellular nets, but had similar ability to kill bacteria as Ezh2-WT neutrophils. To test tumor responses to differing neutrophil populations, we engineered three-dimensional air-liquid interface cultures with tumoroids, lung mesenchymal cells, and T cells, with and without bone marrow containing neutrophils and myeloid progenitors from distinct donors. Bone marrow from tumor-naive or mice with actively growing untreated tumors boosted tumoroid growth, while bone marrow from spontaneously tumor-rejected or mice with tumors treated with valemetostat was anti-tumor. MHC Class II blockade lowered the ability of bone marrow to boost tumor growth, and reduced the ability of valemetostat with anti-PD1 to reduce tumoroid growth. Patient samples revealed a strong negative correlation between EZH2 and MHC Class II, suggesting that targeting EZH2 activity could lead to marked increase in MHC Class II and improve treatment responses in lung squamous cell carcinomas.

cancer biology↗

bioRxiv2026

Visibly Transparent, Near-Infrared Absorbing Nanofluids Enable High-Efficiency and Safe Laser Lithotripsy

Laser lithotripsy (LL) is the gold standard for urinary stone management yet maximizing ablation efficiency while maintaining procedural safety remains clinically challenging. Here, we present a visibly transparent, near-infrared (NIR)-absorbing ITO@SiO2 nanofluid irrigation strategy that significantly enhances LL efficiency without compromising endoscopic visibility. By spectrally matching the absorption profile of ITO@SiO2 with the clinical Holmium:YAG laser wavelength, ablation efficiency improved by >200% in the bench-top spot treatments and >100% in the hydrogel kidney model. Mechanistic investigations revealed that the enhanced optical absorption of the nanofluid modifies bubble dynamics and synergistically amplifies photothermal/microexplosion effects and cavitation damage. Importantly, both in-vitro hydrogel and in-vivo porcine kidney models demonstrated a substantial thermal safety margin (maximum temperatures <35 {degrees}C) and excellent acute biocompatibility, with no evidence of thermal tissue injury. Integrating seamlessly into established clinical workflows without requiring stone pretreatment, this strategy offers a highly translatable, safe, and efficient platform for next-generation endoscopic lithotripsy.

bioengineering↗

bioRxiv2026

Circular RNA aptamers act as superb sub-stoichiometric chaperones to prevent cytosolic TDP-43 condensation

Pathological protein misfolding and aggregation underlie many devastating human diseases, yet strategies to selectively neutralize aggregation-prone protein states without perturbing their normal functions remain limited. Here we identify loosely structured circular RNA (cRNA) aptamers, circT3 and its minimized 116-nt variant circT3-M3, as superb sub-stoichiometric RNA chaperones that suppress pathological assembly of TAR DNA-binding protein 43 (TDP-43), a defining feature of amyotrophic lateral sclerosis and frontotemporal dementia, in vitro and in cells. Rather than acting through simple stoichiometric sequestration, these cRNA aptamers engage TDP-43 transiently and iteratively through functionally and pathologically important residues in the RRM1 domain. Such interaction enables a single cRNA aptamer to promote rapid and multiple RRM1-dependent homomeric assembly, thereby stabilizing TDP-43 in a soluble oligomeric state to outcompete the C-terminal prion-like domain-driven condensation and supersaturation. Together, our findings establish cRNA aptamers as highly efficient subcellular RNA chaperones with exceptionally potent low-dose activity and highlight their promise as next-generation RNA therapeutics for certain protein-aggregation disorders.

molecular biology↗

bioRxiv2026

Glucocorticoid Programming of Erythrocyte Hypoxic Memory Enables Rapid High-Altitude Acclimatization

BackgroundRapid ascent to high altitude causes acute mountain sickness (AMS) and life-threatening pulmonary/cerebral edema, yet no prophylaxis enables immediate acclimatization. Intermittent hypoxia training (IHT) establishes a "hypoxic memory" that accelerates adaptation, to high altitude, but its cellular and molecular basis remains undefined, precluding effective pharmacological strategies. MethodsA human cohort of 18 sea-level inhibitants was equally divided into two groups, one group received IHT prior to ascent to 3,500 meters, the other group did not. Multi-omics profiling of erythrocytes and plasma, along with isotopic glucose tracing, was employed to examine the metabolic effects of IHT upon high altitude acclimatization. Preclinical studies with genetically engineered mice were used to further define the molecular and metabolic basis of IHT-induced hypoxic memory allowing rapid acclimatization to high altitude. ResultsMetabolomics revealed glucocorticoids as previously unrecognized endogenous erythroid hypoxic memory orchestrators induced by IHT that negatively correlated with AMS severity. Lipidomics and isotopic glucose tracing demonstrated that glucocorticoid signaling via the glucocorticoid receptor (GR) coordinately enhanced glucose metabolism and activated sphingosine kinase-1 (SPHK1)-driven sphingosine-1-phosphate (S1P) synthesis, pre-conditioning erythrocyte oxygen unloading and antioxidant capacity. Glucocorticoid supplementation enhanced erythrocyte SPHK1 activation and oxygen delivery, counteracting multi-tissue hypoxia and pulmonary and renal neutrophil infiltration. Conversely, erythrocyte-specific Sphk1 ablation abolished glucocorticoid-induced S1P production causing severe tissue hypoxia and exaggerated pulmonary neutrophil infiltration. ConclusionsWe establish a new function of glucocorticoids in erythrocyte metabolic plasticity to enhance oxygen delivery as a hypoxic memory mechanism for rapid adaptation to high altitude. This previously unrecognized GR-mediated reprograming of glucose and sphingolipid metabolism offers a transformative precision pharmacologic strategy for high altitude preconditioning, high altitude emergencies and hypoxia-driven diseases.

cell biology↗