Biology subjects

Wang, T.

Publications and source records attributed to Wang, T..

At least 91 records · Page 5Linked to original sources

bioRxiv2026

BAG2 Condensates Couple Proteostasis to CD8+T Cell Surveillance

Protein aggregation, impaired degradation, and immune activation are central hallmarks of neurodegenerative diseases, yet how these processes are coordinated remains unclear. Here, we identify Immune-Protein Degradation Bodies (I-PDBs), a previously unrecognized class of BAG2-driven, phase-separated organelles that integrate protein quality control with adaptive immunity. IFN{gamma} induce I-PDB formation at the endoplasmic reticulum (ER), where they concentrate immunoproteasome components, MHC-I peptide-loading machinery, and ER-associated chaperones. I-PDBs redirect proteostatic cargo from centrosomal aggregation pathways to spatially restricted degradation sites optimized for antigenic peptide generation, coupling selective substrate clearance to CD8 T cell engagement. Using a cellular model of aggregation-prone tau, we show that I-PDBs capture pathological tau fibrils at ER-microtubule interfaces and process them into potentially antigenic peptides, thus reducing the load of aggregation-prone tau peptides. We term this mechanism the Proteostasis-Associated Immune Relay (PAIR), establishing I-PDBs as critical hubs linking proteostasis to immune surveillance with broad implications for disease. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/719751v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@16fa503org.highwire.dtl.DTLVardef@ba7607org.highwire.dtl.DTLVardef@19ae5bdorg.highwire.dtl.DTLVardef@60fdf7_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIIFN{gamma} drives BAG2-dependent Immune-Protein Degradation Bodies (I-PDBs) C_LIO_LII-PDBs assemble at the endoplasmic reticulum and are enriched in immunoproteasome and MHC-I machinery C_LIO_LII-PDBs shunt misfolded proteins, including pathological tau, away from aggresomes C_LIO_LII-PDBs couple proteostasis to antigen presentation, enhancing CD8 T cell recognition C_LIO_LIThe Proteostasis-Associated Immune Relay (PAIR) defines a pathway linking proteostasis to adaptive immunity C_LI

cell biology↗

bioRxiv2026

Single cell eQTL mapping reveals convergent glial-neuronal risk architecture in Parkinson's disease

Synucleinopathies affect [~]15 million people and are classically divided into neuronal (Parkinsons disease (PD), dementia with Lewy bodies) and glial (multiple system atrophy) disorders. Here we challenge this dichotomy. We functionally fine-map 90 PD GWAS signals across nine cell types in cortex and substantia nigra using disease-context, population-scale single-nucleus eQTL meta-analysis (N = 1,197), bulk brain eQTL analysis (N = 1,182), and Mendelian randomization. A stringent causal framework integrates single-nucleus allelic imbalance (snASE) with orthogonal validation. We identify 125 functional risk genes for 50 loci--nearly doubling supported genes--and assign genes and cell types to over half of GWAS signals. Unexpectedly, 51% of risk genes are regulated in glia, particularly oligodendrocytes and their precursors. Across cell types, risk converges on a shared glial-neuronal vesiculopathy network. These findings uncover a convergent glial-neuronal risk architecture and establish a single-cell atlas for context-aware gene discovery and precision therapeutics for PD.

genetics↗

bioRxiv2026

Modular organization and selective motifs in the insula provide structural priors for efficient learning

The insular cortex (IC) integrates diverse sensory and interoceptive signals to support emotional and cognitive functions, exhibiting topologically functional distinctions. Although long-range pathways of the IC have been extensively mapped, the contribution of intra-IC architecture to network-level information processing remains poorly understood. Here we reconstructed single-cell projectomes of 2,267 IC neurons, generating a comprehensive cellular-resolution map of intra-IC connectivity. Graph-theoretic analyses revealed a hierarchical, topographically organized modular network with a hub-and-spoke organization and selective motif enrichment. Embedding these anatomical priors into recurrent neural network models demonstrated that intrinsic IC topology confers a distinct computational advantage: across multiple cognitive tasks, IC-initialized networks learned faster and exhibited better robustness to perturbations than those initialized with shuffled, randomized, or neighboring somatosensory cortical architectures. Together, these findings identify the IC as a structurally specialized cortical hub whose internal wiring supports efficient learning and provides design principles for brain-inspired networks.

neuroscience↗

bioRxiv2026

Cardiac oxidative stress monitoring enabled by hierarchical mechanical adaptation

Soft bioelectronics have advanced cardiac monitoring through electrophysiological tracking, yet this alone cannot resolve the metabolic pathology essential to surgical decision-making. However, real-time molecular sensing on beating hearts remains unresolved due to deformation-induced sensor failure and stress-induced metabolite artifacts. This challenge is exemplified by ischemia-reperfusion injury (IRI), a major cardiac surgery complication characterized by reactive oxidative species (ROS) bursts, where true pathological ROS signals being confounded by mechanotransduction-induced ROS artifacts. Herein, we propose an enzymatic cardiac oxidative stress biosensor (E-cardiac) with hierarchical mechanical adaptation: macro-scale biofluid-mediated contact, micro-scale fiber reorganization, and nano-scale enzymatic confinement within gold nanoarches dissipate interfacial stress. This produces ultrathin ([~]460 nm), soft (0.79 kPa) E-cardiac with robust electrochemical stability (100% strain), low detection limit (380 nM), rapid adhesion (<3 s), stable biosensing on beating heart, as well as minimal invasive deployment capability. Mechanical analysis and cellular studies confirm mitigated stress-induced ROS and absent PIEZO channel activation. Validated across cardiomyocytes, ex vivo tissues, multi-species ischemia models (mouse, rat, rabbit, pig), rat ischemia-reperfusion injury, and Langendorff hearts simulating graded perfusion deficits, E-cardiac quantitatively differentiates IRI severity (sham < ischemia < reperfusion) as well as detecting the "ECG blind window". The E-cardiac platform provides real-time metabolic feedback for surgical guidance during cardiac procedures, enabling timely intervention before irreversible damage.

bioengineering↗

bioRxiv2026

Pan-cancer circular genomics identifies intratumoral Staphylococcus lugdunensis as a metabolic driver in bladder cancer

Intratumoral microbiota play key roles in cancer but are challenging to profile due to low biomass. We developed CIRCMIP, an enzymatic pipeline that eliminates linear DNA to enrich bacterial genomes, achieving 100-fold higher sensitivity than standard metagenomics. Applied to 312 pan-cancer specimens, CIRCMIP identified Staphylococcus lugdunensis as a signature bacterium enriched in early-stage bladder cancer (BLCA), where its presence predicts poor survival. Integrated modeling and lipidomics revealed that Staphylococcus lugdunensis colonization drives aberrant lipid metabolism with secretion of LPC14:0. Both Staphylococcus lugdunensis and LPC14:0 drive BLCA progression by promoting fatty acid uptake and {beta}-oxidation. Mechanistically, chemical proteomics revealed LPC14:0 as a direct PPAR{delta} ligand, binding via hydrogen bonds with Thr292/Thr289. This activation upregulates fatty acid transporters (CD36, FABP4) and metabolic enzymes (ACOX2), fueling malignant proliferation. Furthermore, CIRCMIP-derived biomarkers show robust diagnostic accuracy, establishing a new research paradigm and revealing the Staphylococcus lugdunensis-LPC14:0-PPAR{delta} axis as a therapeutic target in bladder cancer. HIGHLIGHTO_LICIRCMIP leverages DNA circularity to achieve 100-fold sensitivity in pan-cancer bacteriome profiling. C_LIO_LIStaphylococcus lugdunensis is a bacterial signature in early-stage bladder cancer that predicts poor patient survival. C_LIO_LIBacteria-derived LPC14:0 acts as a direct ligand for PPAR{delta} to drive host malignant metabolic reprogramming. C_LIO_LITargeting the Staphylococcus lugdunensis-LPC14:0-PPAR{delta} axis abrogates malignant progression in bladder cancer. C_LI

cancer biology↗

bioRxiv2026

Molecular Architecture of Cryptococcus Cell Walls Reveals Species-Specific Chitosan-Dependent Remodeling

Cryptococcus neoformans and Cryptococcus gattii are fungal pathogens that cause life-threatening infections, including cryptococcal meningitis. A distinctive feature of the cryptococcal cell wall is the extensive deacetylation of chitin to chitosan, a modification that is essential for virulence but whose structural role in cell-wall organization remains poorly understood. Here, we analyzed the cell walls of wild-type strains of both species and their avirulent chitosan-deficient mutants, which serve as vaccine candidates. Loss of chitosan disrupted cell morphology and altered cell-wall ultrastructure, with more pronounced defects in C. neoformans. Solid-state NMR revealed that aggregated -1,3-glucans form the principal rigid domain of the cell wall in both species and are closely associated with chitin microfibrils, whereas surrounding {beta}-glucans and mannoproteins constitute a more dynamic matrix. Chitosan modulates hydration and flexibility, and its loss increases chitin exposure and triggers species-specific remodeling of the polysaccharide network. In C. neoformans, chitosan depletion increased -1,3-glucan content and reduced {beta}-glucan levels, whereas C. gattii selectively lost one -1,3-glucan subtype while maintaining {beta}-glucan levels. Although capsule production remained intact, chitosan deficiency altered glucuronoxylomannan linkage patterns and mannoprotein composition. These findings reveal how chitosan organizes cryptococcal cell-wall architecture and highlight distinct structural adaptation strategies among pathogenic Cryptococcus species.

biochemistry↗

bioRxiv2026

Transcription Factor Subtype Governs Response and Resistance to DLL3-Directed T-Cell Engagement in Small Cell Lung Cancer

Although small cell lung cancer (SCLC) comprises transcription factor (TF)-defined molecular subtypes (ASCL1, NEUROD1, POU2F3), the extent to which these subtypes predict response to clinically effective therapy in patients--and whether therapy can select for subtype switching--remains unknown. The recent approval of the DLL3xCD3 bispecific T-cell engager tarlatamab represents one of the first meaningful advances in relapsed small cell lung cancer (SCLC) in decades, yet responses remain heterogeneous and resistance is inevitable. Here, we inferred SCLC gene expression from circulating chromatin in prospectively collected patient plasma (46 patients; 167 samples), enabling interrogation of response and acquired resistance to tarlatamab. Parallel development of the first immunocompetent syngeneic mouse model to study tarlatamab response and resistance enabled functional validation. Across species, findings converged on a central principle: TF subtype governs both initial response and acquired resistance. Therapeutic response was significantly associated with ASCL1-subtype tumors, whereas NEUROD1-subtype tumors exhibited inferior responses and POU2F3-subtype tumors were uniformly resistant, consistent with DLL3 being a direct ASCL1 transcriptional target and most highly expressed in ASCL1-positive tumors. Strikingly, one mode of acquired resistance revealed therapeutic selection for a NEUROD1-high state with concomitant DLL3 downregulation. Other resistant tumors exhibited enrichment of regulatory and exhausted T-cell programs, highlighting tarlatamabs dual-targeting mechanism of action. Together, these results reveal that tarlatamab exerts selective pressure against ASCL1-driven lineages, facilitating resistance through loss of an antigen intrinsically linked to that state. These findings underscore the clinical relevance of TF-defined molecular subtypes in human SCLC. More broadly, they highlight the power of integrating longitudinal in vivo plasma transcriptional profiling from patient plasma with functional mouse modeling to uncover clinical and biological mechanisms of response and resistance to cell-surface-targeted therapies.

cancer biology↗

bioRxiv2026

FAM134B isoform 2/RETREG1-2 defines a calnexin-TOLLIP-coupled ER-phagy pathway that restricts Ebola virus glycoprotein and is antagonized by VP40 through macro-autophagy

Selective autophagy of the endoplasmic reticulum (ER-phagy) is critical for ER proteostasis and host defense, yet how ER quality-control pathways interface with ER-phagy to restrict viral glycoproteins remains poorly defined. Previously, the 1st known ER-phagy receptor gene RETREG1 (RETR1)/FAM134B gene was reported to restrict Ebola virus (EBOV) replication in vivo by inhibiting the viral glycoprotein (GP) and viral protein 40 kDa (VP40) expression, but this mechanism remains unknown. Here, we identify the truncated RETR1/FAM134B isoform 2 (RETR1-2), but not its full-length protein RETR1, as an ER-phagy receptor that targets EBOV-GP for degradation. RETR1-2 broadly triggers GP degradation across ebolavirus species but not Marburg virus and inhibits EBOV replication. Mechanistically, RETR1-2 recognizes EBOV-GP via its luminal domain, undergoes GP-induced oligomerization, and directs GP-containing ER membranes to lysosomes through canonical macro-autophagy. Using unbiased mass spectrometry, we identified TOLLIP as the key cytoplasm adaptor for RETR1-2, which also requires cooperation with the ER chaperone calnexin for EBOV-GP degradation. Notably, the PI3P-binding C2 domain of TOLLIP mediates its interaction with RETR1-2, and the EBOV-GP degradation occurs independently of ubiquitination, revealing an unexpected role for TOLLIP in ER-phagy. Furthermore, EBOV-VP40 antagonizes this pathway by selectively targeting RETR1-2 for macroautophagic degradation independently of TOLLIP, thereby restoring GP expression and viral infectivity. Nevertheless, RETR1-2 reciprocally degrades VP40 via a similar mechanism. Together, these findings define a calnexin-TOLLIP-RETR1-2 axis that links ER quality control to ER-phagy-mediated antiviral restriction and uncover a reciprocal host-virus arms race centered on selective macro-autophagy.

microbiology↗

bioRxiv2026

The Urinary Tract Commensal Peptoniphilus spp. Encodes a Novel 17β-Hydroxysteroid Dehydrogenase

Microbial steroid metabolism represents an underappreciated extension of the vertebrate endocrine system, with growing evidence that host-associated microbes contribute to the diversity and bioavailability of sex steroids within human tissues. Emerging studies have linked microbial androgen metabolism to urinary microbiome composition and to resistance to androgen deprivation therapy (ADT) in prostate cancer. While microbial pathways capable of converting steroid precursors such as cortisol to androgens, via the steroid-17,20-desmolase pathway, such as DesG-mediated interconversion of androstenedione to testosterone have been reported, the diversity of enzymes mediating downstream androgen interconversion remains incompletely defined. Here, we investigate the androgen-forming capabilities of anaerobic bacteria from the male genitourinary microbiome, focusing on NADPH-dependent 17{beta}-hydroxysteroid dehydrogenases (17{beta}-HSDHs) that catalyze interconversion of androstenedione and testosterone. We isolated androgen-forming bacterial strains from human male urine and identified a previously uncharacterized 17{beta}-HSDH encoded by Peptoniphilus obesi, demonstrated that this enzyme catalyzes the NADPH-dependent reduction of androstenedione to testosterone and the reverse oxidation reaction. Sequence similarity searches further identified a homologous 17{beta}-HSDH in Anaerococcus, which was synthesized and functionally validated, revealing conserved activity despite low sequence identity to the previously characterized urinary tract enzyme DesG. The enzymes were found to have broad substrate specificity for C19 and C18 17keto- and 17{beta}-hydroxysteroids. Together, these findings expand the known diversity of microbial 17{beta}-HSDHs and identify previously unrecognized androgen-forming activities within the genitourinary microbiome. ImportanceMicrobial steroid-transforming pathways may provide a mechanism by which commensal anaerobes contribute to androgen availability in the genitourinary tract. By identifying novel 17{beta}-hydroxysteroid dehydrogenases from Peptoniphilus and Anaerococcus, genera repeatedly associated with prostate cancer, this study provides mechanistic insight into how microbial steroid metabolism may influence hormone-driven disease.

microbiology↗

bioRxiv2026

SSPSPredictor: A Sequence and Structure based Deep Learning Model for Predicting Phase-Separating Proteins

Liquid-liquid phase separation (LLPS) underlies the formation of biomolecular liquid condensates (also referred to membraneless organelles, MLOs), which are essential for spatially organizing various biochemical processes within cells. Proteins that play a key role in driving condensates formation are termed phase-separating proteins (PSPs). Given experimental identification of PSPs remains labor-intensive and time-consuming, multiple computational tools have been developed based on empirical features or deep learning. In this study, we propose SSPSPredictor, a novel multimodal predictive model for PSPs with folded or intrinsically disordered structures, leveraging the fusion of sequence information from a protein language model ESM-2 and structural insights from a graph neural network GVP. Compared with existing tools, SSPSPredictor achieves balanced performance in identifying endogenous PSPs, predicting relative LLPS propensities, and recognizing key regions that drive LLPS. Moreover, SSPSPredictor exhibits good interpretability in identifying driving regions along protein sequences, although no relevant supervision was provided during training. Further predictive analysis of the human proteome using SSPSPredictor reveals that the proportion of intrinsically disordered proteins (IDPs) undergoing LLPS is significantly higher than that of folded proteins. In addition, pathogenic variants, especially those located in disordered regions, exhibit higher LLPS propensity than other mutations, uncovering a link between LLPS and diseases at the amino acid level.

bioinformatics↗

bioRxiv2026

Folate Receptor α Contributes to Radiation Resistance in Neuroendocrine Prostate Cancer by Regulating Redox Homeostasis

Ionizing radiation can be an effective therapy for prostate cancer. Unfortunately, however, more aggressive prostate cancers such as neuroendocrine prostate cancer (NEPC) are often radiation resistant, which contributes to their high degree of morbidity and mortality. In this study, we used an unbiased approach to identify novel mechanisms that contribute to resistance to radiation and that are associated with neuroendocrine differentiation. Specifically, we compared the expression of cell surface proteins by mass spectrometry in prostate cancer cell lines that had been either untreated or treated with radiation to induce resistance, a process that also promotes neuroendocrine differentiation. Among the proteins identified by this screen, we focused on folate receptor (FR) because of its known biological functions and the fact that it is a validated therapeutic target. Our data reveal that FR has a causal role in enabling prostate cancer cells to resist radiation. Importantly, we also demonstrate that the expression of FR is regulated by HIF-1, which also has a causal role in radiation resistance and neuroendocrine differentiation. Given that the ability of cells to resist damage and death in response to ionizing radiation depends largely on their ability to buffer the substantial increase in reactive oxygen species (ROS) that is generated by radiation, we also demonstrate that the folate-FR axis promotes radiation resistance by sustaining intracellular glutathione levels that buffer this increase in ROS. In summary, the data reported here highlight a novel role for FR in resistance to ionizing radiation that is intimately associated with the hypoxic microenvironment of NEPC and the ability of the folate-FRa axis to maintain redox homeostasis.

cancer biology↗

bioRxiv2026

Seeded aggregation of ANXA11 induces prion-like propagation, TDP-43 co-pathology and nucleocytoplasmic transport defects

Mutations in ANXA11 cause amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), yet the mechanisms linking ANXA11 dysfunction to neurodegeneration remain poorly defined. Recent cryo-EM studies revealed heteromeric ANXA11-TDP-43 filaments in patient brains, suggesting a direct pathological connection between these two ALS-associated proteins. However, whether ANXA11 possesses intrinsic amyloidogenic properties and how its aggregation relates to TDP-43 proteinopathy remain unknown. Here, we demonstrate that ANXA11 undergoes liquid-liquid phase separation and subsequently matures into amyloid fibrils through a liquid-to-solid phase transition. ANXA11 fibrils exhibit prion-like properties, including self-templating seeding activity and intercellular propagation in human iPSC-derived neurons. Strikingly, ANXA11 fibrils induces pathological conversion of TDP-43, including hyperphosphorylation, accumulation in detergent-insoluble fractions, and formation of cytoplasmic aggregates. TurboID proximity-labeling proteomics further revealed aggregation-dependent enrichment of nuclear pore complex and nucleocytoplasmic transport factors in the ANXA11 aggregate-proximal proteome. Consistently, ANXA11 aggregation was associated with nuclear envelope abnormalities, altered nucleoporin distribution, impaired mRNA export, and progressive neuronal toxicity in iPSC-derived neurons. Together, these findings establish ANXA11 as an intrinsically amyloidogenic, phase-transition-competent protein whose seeded assemblies propagate between cells, induce TDP-43 co-pathology, and are linked to nucleocytoplasmic transport defects and neuronal injury, thereby providing a mechanistic framework for ANXA11-associated ALS/FTD pathogenesis. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=188 SRC="FIGDIR/small/713853v1_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@1aaad3org.highwire.dtl.DTLVardef@c51d5eorg.highwire.dtl.DTLVardef@10b2891org.highwire.dtl.DTLVardef@1945575_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIANXA11 undergoes liquid-liquid phase separation and matures into amyloid fibrils through a liquid-to-solid phase transition. C_LIO_LIANXA11 fibrils supports homotypic seeding and propagate within SH-SY5Y cells and iPSC-derived neurons. C_LIO_LIANXA11 fibrils induce TDP-43 pathological conversion, including phosphorylation and accumulation in insoluble aggregates. C_LIO_LIANXA11 aggregation is associated with nuclear pore complex remodeling, impaired mRNA export, and neuronal toxicity. C_LI In BriefANXA11 undergoes phase separation and matures into prion-like amyloid fibrils through a liquid-to-solid transition. These seeded assemblies propagate between cells and human neurons, induce TDP-43 pathological conversion, and are associated with remodeling of nuclear pore complexes, impaired mRNA export, and progressive neuronal toxicity. ANXA11 forms seeded amyloid assemblies that spread between cells, induce TDP-43 pathology, and disrupt nucleocytoplasmic transport.

neuroscience↗

bioRxiv2026

Enhancing non-local interaction modeling for ab initio biomolecular calculations and simulations with ViSNet-PIMA

AI-based molecular dynamics simulation brings ab initio calculations to biomolecules in an efficient way, in which the machine learning force field (MLFF) locates at the central position by accurately predicting the molecular energies and forces. Most existing MLFFs assume localized interatomic interactions, limiting their ability to accurately model non-local interactions, which are crucial in biomolecular dynamics. In this study, we introduce ViSNet-PIMA, which efficiently learns non-local interactions by physics-informed multipole aggregator (PIMA) and accurately encodes molecular geometric information. ViSNet-PIMA outperforms all state-of-the-art MLFFs for energy and force predictions of different kinds of biomolecules and various conformations on MD22 and AIMD-Chig datasets, while adapting the PIMA blocks into other MLFFs further achieves 55.1% performance gains, demonstrating the superiority of ViSNet-PIMA and the universality of the model design. Furthermore, we propose AI2BMD-PIMA to incorporate ViSNet-PIMA into AI2BMD simulation program by introducing "Transfer Learning-Pretraining-Finetuning" scheme and replacing molecular mechanics-based non-local calculations among protein fragments with ViSNet-PIMA, which reduces AI2BMDs energy and force calculation errors by more than 50% for different protein conformations and protein folding and unfolding processes. ViSNet-PIMA advances ab initio calculation for the entire biomolecules, amplifying the application values of AI-based molecular dynamics simulations and property calculations in biochemical research.

bioinformatics↗

bioRxiv2026

Preferential formation of NUP98-KDM5A condensates at specific H3K4me3-rich loci drives leukemogenic gene expression

Chromosomal translocations involving NUP98 generate fusion proteins that alter gene expression programs, yet the fundamental principles governing their gene targeting and condensate behavior remain poorly understood. Using NUP98-KDM5A as a model, we integrate cellular imaging, in vitro reconstitution, and genomic analyses to dissect how chromatin engagement shapes condensate formation. We find that NUP98-KDM5A forms sub-diffraction-limited, gel-like condensates whose assembly is potentiated by binding to H3K4me3. This interaction creates a quantitative targeting mechanism in which, at the native expression level, condensates preferentially form at genomic loci with high local H3K4me3 density. Such local density-dependent recruitment explains selective enrichment at the leukemogenic HOX gene clusters, despite widespread presence of H3K4me3 across the genome. Analysis of single-cell sequencing data from patients further supports a correlation between local H3K4me3 density and transcriptional activation in NUP98-KDM5A-driven leukemia. Together, our findings reveal how activating chromatin marks and condensate-forming proteins synergize to generate specificity within euchromatin, offering a generalizable framework for understanding how chromatin-associated condensates interpret epigenetic landscapes.

cell biology↗

bioRxiv2026

APOE4 Accelerates Menopause-Associated Brain Metabolic Shift and Disrupts Bioenergetic Adaptation

IntroductionDisruption of brain glucose and lipid metabolism contributes to Alzheimers disease (AD) and often emerges before clinical symptoms. Women are at elevated AD risk due to menopause-associated estrogen decline, which impairs mitochondrial function and glucose metabolism. Womens risk of AD is further elevated by the APOE4 allele, the strongest genetic risk factor for late-onset AD. MethodsTo investigate the impact of APOE genotype on the menopausal metabolic transition, brain metabolomic and lipidomic profiling was conducted in humanized female APOE3/3, APOE3/4, and APOE4/4 mice across chronological and endocrinological stages of peri-to postmenopausal transition. ResultsAPOE3/3 mice exhibited dynamic regulation of brain metabolic systems that supported postmenopausal bioenergetic demand. In contrast, APOE3/4 and APOE4/4 mice displayed accelerated and altered metabolic shifts, resulting in postmenopausal amino acid depletion, reduced tricarboxylic acid (TCA) cycle intermediates, lipid accumulation, and alterations in brain lipid composition. A single APOE4 allele was sufficient to impair metabolic adaptation, while APOE4 homozygosity resulted in greater severity of deficits. DiscussionOutcomes of these analyses revealed that APOE4 accelerated menopause-related metabolic decline and compromised bioenergetic adaptation, providing a mechanistic basis for increased AD susceptibility and earlier onset in APOE4-positive women.

neuroscience↗

bioRxiv2026

Single-molecule analysis sheds light on cardiac myosin dysfunction due to hypertrophic cardiomyopathy mutation A57D in ventricular myosin light chain-1 (MLC1v)

Ventricular myosin light chain-1 (MLC1v) is a key structural and function-modulating component of the {beta}-cardiac myosin ({beta}M-II) motor complex. Single-point mutations in MLC1v are linked to severe forms of hypertrophic cardiomyopathy (HCM) and sudden cardiac death (SCD) at a young age. However, the molecular mechanisms underlying the motor dysfunction responsible for HCM phenotype development are not fully understood. Here, we investigated native {beta}M-II motors isolated from septal myectomy sample of an HCM patient, harboring a rare homozygous mutation in MLC1v (A57D). Using a pure population of mutant motors (MUT), and sensitive single-molecule functional analysis approach, we directly assessed the primary functional alterations in {beta}M-II bearing A57D MLC1v mutation. In optical trap single-molecules measurements, the mutant motors displayed increased actomyosin (AM) interaction duration in strongly bound state (ton), corresponding to 3-fold reduced AM detachment rate than wild type myosin (WT). The MUT myosin also generated a shorter powerstroke size ({delta}). Ensemble average analysis of AM interaction events demonstrated that both the first powerstroke ({delta}1) associated with Pi release and the second powerstroke ({delta}2) linked to ADP release were reduced in MUT myosin. Moreover, the increased actomyosin cross-bridge stiffness in the AM.ADP state was observed for MUT compared to WT motors. Consistent with slower AM detachment rate and shorter stroke size, reconstituted human mutant {beta}M-II displayed slower actin filament gliding speed. Alterations in sarcomere-level mechanics included increased Ca2+ sensitivity of force generation and prolonged relaxation time, as predicted by FiberSim modelling. Molecular dynamics simulations indicated that the substitution of alanine by aspartate altered MLC1v interactions with myosin heavy chain (MyHC) and light chain 2 (MLC2v), affecting the curvature and flexibility of the lever arm. Overall, these studies establish the molecular mechanism underlying the primary myosin dysfunction due to A57D MLC1v mutation and further highlight the crucial role of MLC1v-mediated regulation of myosin function. Understanding the precise changes in the mutant myosins biomechanical properties is directly relevant to comprehending the initial triggers for pathological cardiac remodeling in HCM patients and designing tailored therapeutic interventions.

biophysics↗

bioRxiv2026

Gothic Identity as Cultural Practice: Paleogenomic Evidence for Multi - Ethnic Assemblages Under Gothic Material Culture in Late Antique Bulgaria (4th - 6th centuries CE)

We report genome-wide ancient DNA from 38 individuals associated with Gothic-period mortuary contexts at two Bulgarian sites: the Aquae Calidae necropolis ([~]320 - 375 CE; n=23) and the Aul of Khan Omurtag (AKO; [~]350 - 489 CE; n=15). Although linked by closely similar Gothic-associated material culture and east - west Arian burial practices, the two assemblages are genetically distinct. Aquae Calidae individuals are modeled with predominantly Anatolian-related ancestry (50 - 85% in qpAdm), whereas AKO individuals are modeled with predominantly Wielbark/Chernyakhov-related northern ancestry (60 - 78%). Across the full assemblage, no single ancestry model fits all individuals, whose profiles range from nearly unadmixed Chernyakhov-like to predominantly Anatolian-related. DATES analysis places admixture between northern European and southern Balkan/Anatolian-related ancestry components approximately 11 - 13 generations before burial (point estimate [~]50 CE; 95% CI, 85 BCE - 183 CE; Z=5.26), raising the possibility that this mixture predated the earliest documented Gothic - Roman contacts ([~]170 CE). The convergence of dates across alternative southern proxies, together with reduced fit when Balkan and Anatolian sources are pooled into a single southern reference, favors admixture involving a pre-blended Balkan - Anatolian substrate over two temporally distinct southern admixture pulses. This signal was not recovered in the non-Gothic Roman-period Balkan populations tested as controls and is consistent with admixture in a trans-Danubian frontier setting, potentially including Roman Dacia after 106 CE. These findings support models in which Gothic affiliation in the Balkans operated as a cultural-political framework encompassing populations of diverse biological ancestry.

genomics↗

bioRxiv2026

ToxiVerse: A Public Platform for Chemical Toxicity Data Sharing and Customizable Predictive Modeling

Chemical toxicity assessment is critical for drug development and environmental safety. Computational models have emerged as a promising alternative to animal testing and now play a significant role in efficiently evaluating new chemicals. To address the urgent need for providing user-friendly machine learning tools in computational toxicology, we developed ToxiVerse, a public web-based platform. It provides curated toxicity datasets, automatic chemical bioprofiling, and a predictive modeling interface designed for researchers who lack programming expertise. The platform comprises three integrated modules: (i) the Bioprofiler module, which provides chemical descriptors by combining chemical-bioactivity data from PubChem assay with a machine learning-based data gap-filling procedure; (ii) the Database module, which hosts around 50,000 curated unique chemicals covering diverse toxicity endpoints; and (iii) the Cheminformatics module, which allows users to upload their own datasets, use datasets from ToxiVerse, or retrieve existing data from PubChem; perform chemical curation; and automatically generate Quantitative Structure-Activity Relationship (QSAR) models to predict chemicals of interest. ToxiVerse enables researchers to carry out bioprofiling, access curated toxicity datasets, and evaluate chemical toxicity through machine learning-based modeling and prediction. The platform is supported by sample files and a detailed tutorial, and it is freely accessible at www.toxiverse.com. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/708255v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@d92764org.highwire.dtl.DTLVardef@a92f4aorg.highwire.dtl.DTLVardef@15fa39corg.highwire.dtl.DTLVardef@1ee89bc_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗