Biology subjects

Li, Z.

Publications and source records attributed to Li, Z..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

TLS-Sim: An Open-Source Toolkit for Individualized Transcranial Light Stimulation Modeling with Deep-Learning-Accelerated Simulation

Background: Accurate modeling of photon transport through the heterogeneous tissues of the human head is important for individualized transcranial light stimulation (tLS). However, high-precision Monte Carlo (MC) simulations can be computationally demanding, and existing general-purpose simulation tools do not provide an integrated, brain-oriented workflow. Methods: We developed TLS-Sim, a framework that integrates subject-specific head-model construction, multiple light-source configuration, GPU-accelerated MC photon simulation, visualization, and intracranial dosimetric analysis. Its central feature is a deep-learning-accelerated MC pathway, termed Flux-to-Flux, that estimates a high-photon-count energy-deposition field from a paired low-photon-count simulation. Sparse and full Monte Carlo fields were encoded using a three-dimensional variational autoencoder (VAE), and a three-dimensional velocity network was trained to transform the sparse latent representation toward the corresponding full-simulation representation. Results: We demonstrate the end-to-end toolkit and the Flux-to-Flux (F2F) pathway on a representative individualized head model evaluated across three source configurations. Relative to the sparse simulation, the learned prediction improved agreement with the full Monte Carlo reference by approximately +4 dB in signal-to-noise ratio on average, with correspondingly higher structural similarity and lower mean absolute error. Conclusions: TLS-Sim provides a modular, openly released computational framework for individualized tLS simulation and analysis. The Flux-to-Flux pathway is presented as an implemented capability that reduces the computational burden of high-photon-count simulation while improving spatial agreement with the full MC reference, most strongly at the low-fluence field boundaries where the sparse simulation is noisiest.

bioengineering↗

bioRxiv2026

Reframing enzyme function prediction as conditional generation

Enzymes frequently exhibit promiscuous activity beyond their native roles, providing starting-points for new functions. Finding these promiscuous enzymes, especially for non-native chemical transformations, is challenging but highly valuable, as they promise novel, sustainable solutions for chemistry and biotechnology. However, current machine learning methods are poorly suited to discovering unseen chemistry as they often frame function prediction as closed set classification or a retrieval task. Here, we present Fluxion, a generative deep learning framework that learns enzymatic catalysis by modeling dynamic electron flow trajectories across the enzyme's catalytic residues. By combining both synthetic chemistry and biochemical datasets with protein language model representations, Fluxion generates multi-step electron-flow trajectories analogous to the arrow-pushing representations used to describe enzyme reaction mechanisms. Generation is conditioned on enzyme context, including the enzyme sequence, catalytic residues, substrates, and cofactors. We show that this conditioning allows Fluxion to learn enzyme-dependent regioselectivity across cytochrome P450 enzymes with different sequences shifting the predicted reaction sites for the same substrate. We then demonstrate that Fluxion's embeddings are useful for downstream tasks, such as specificity prediction on two experimental datasets, with and without finetuning. Finally, we show that Fluxion has the potential to transfer synthetic chemical logic to biology; it can generate the observed non-native product from real-world non-native directed evolution screens. Our results establish a proof of concept that generative modeling through mechanistic representations of enzymes can shift enzyme function prediction beyond static database retrieval and closed set classification to function generation. This conceptual framework provides a stepping stone towards an in silico generative method to discover non-native biocatalysts.

biochemistry↗

bioRxiv2026

Restoring the Chondron: Pericellular Matrix Reconstitution Enhances Mechano-Inflammatory Resilience and Modulates Chondrocyte-Neuron Crosstalk

Abstract Chondrocytes in native articular cartilage are enclosed within a collagen VI (COL VI)-rich pericellular matrix (PCM), forming functional units known as chondrons. However, enzymatic isolation disrupts the PCM, and the functional consequences of its loss and restoration remain poorly understood. In this study, primary human chondrocytes were cultured in alginate beads to promote PCM reconstitution and subsequently recovered as reconstituted chondrons. Chondrocytes and reconstituted chondrons were encapsulated in gelatin methacryloyl hydrogels and compared under inflammatory and mechanical stimulation. Alginate preconditioning generated chondron-like units with a distinct COL VI-positive PCM that was retained after transfer to three-dimensional culture. Under inflammatory conditions, reconstituted chondrons exhibited reduced inflammatory, catabolic, neuroinflammatory, and angiogenic responses compared with isolated chondrocytes at both gene and protein levels. Under interleukin-1{beta} stimulation, mechanical loading further increased inflammatory gene expression in chondrocytes in a donor-dependent manner, whereas responses remained comparatively limited in reconstituted chondrons. Conditioned medium from reconstituted chondrons was also associated with lower capsaicin- and potassium chloride-evoked calcium responses in human induced pluripotent stem cell-derived sensory neurons than corresponding chondrocyte-conditioned medium. These findings demonstrate that reconstitution of a COL VI-rich PCM restores a chondron-like pericellular microenvironment that attenuates inflammatory activation and buffers load-associated inflammatory amplification, while exploratory sensory neuron experiments suggest downstream modulation of neuronal responsiveness. PCM restoration may therefore provide a promising strategy for cartilage tissue engineering and regenerative applications.

molecular biology↗

bioRxiv2026

Catalytic and inhibitory architecture of comammox ammonia monooxygenase

Complete ammonia oxidizers (comammox) are widespread nitrifiers that can dominate ammonia oxidation in diverse environments by efficiently converting ammonia to nitrate within a single cell, yet the molecular basis distinguishing their ammonia monooxygenase (AMO) from those of canonical bacterial AMO remains unresolved. Here we report cryo-electron microscopy (cryo-EM) structures of AMO from the comammox Nitrospira inopinata (NiAMO) in inhibitor-free and allylthiourea (ATU)-bound states at 2.47 and 2.68 angstrom, respectively. NiAMO displays distinctive auxiliary-subunit organization, copper-site configuration and hydrophobic-channel architecture. Integrative molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) calculations support a methyl-plastoquinol (methyl-PQH2)-coupled, CuD-centric catalytic model, with CuC potentially facilitating quinone redox cycling. N. inopinata exhibited broad susceptibility to several known nitrification inhibitors, and ATU-bound NiAMO structure localized the inhibitor to the CuC-CuD region, accompanied by constriction of the hydrophobic channel, which is consistent with the competitive role of ATU demonstrated in recovery assays. Multi-omics analyses further revealed an energy-limited stress response to ATU, including induction of urea transport and utilization systems. Collectively, these findings define a methyl-PQ-linked catalytic and inhibitor-responsive architecture of comammox AMO and establish a mechanistic framework for lineage-aware management of nitrification in natural and engineered ecosystems.

biophysics↗

bioRxiv2026

Systematic evaluation of structural connectome thresholding in whole-brain network modelling

Large-scale whole-brain network models rely on structural connectomes to constrain simulated neural dynamics, yet the optimal processing of these anatomical scaffolds is not fully established. Here, we investigate the impact of structural connectome thresholding on whole-brain model performance to advance precision individual modelling. We measure model goodness-of-fit to both static functional connectivity and dynamic functional connectivity across a comprehensive spectrum of network densities, spatial parcellations, and model complexities using neuroimaging datasets of healthy individuals and a clinical cohort of post-stroke patients. We demonstrate that the optimal structural sparsity is highly resolution dependent. In coarse-grained parcellations, proportional thresholding enhances the model's fit to static functional connectivity but relies on denser connectome to maintain dynamic functional fits. Conversely, fine-grained models require stringent connectome thresholding which simultaneously optimizes both static and dynamic functional fits. Taken together, these results indicate that the uncritical use of raw structural connectomes introduces suboptimal dynamical regimes, establishing resolution-tailored thresholding as an indispensable step for constructing precision brain network models.

neuroscience↗

bioRxiv2026

Programmable Self-Assembly of RNA Nanostructures with >100 Unique Components

Sophisticated biomolecular functions often arise from large, precisely organized architectures, motivating efforts to construct increasingly complex structures through programmed nucleic acid self-assembly. Although RNA offers a richer repertoire of structural motifs and biological functions than DNA, RNA nanostructures constructed to date have remained substantially less complex and less scalable than their DNA counterparts, most notably DNA origami and DNA bricks, which rely on large libraries of synthetic single-stranded (ss) DNA strands. Directly adapting these strategies to RNA, however, faces two major barriers: (i) the high cost of producing large libraries of distinct synthetic ssRNA strands, and (ii) the limited stability of ssRNA under conditions commonly used for assembling multicomponent nucleic acid nanostructures. Here we present the double-stranded RNA (dsRNA) bricks approach, which addresses both barriers by adopting principles inspired by natural RNA systems: (i) many distinct RNA components ("bricks") are encoded within a single precursor transcript and released by enzymatic processing, (ii) each brick's predominantly double-stranded nature enhances stability. The resulting dsRNA bricks self-assemble through programmable branched kissing-loop interactions. Using this approach, we constructed complex two- and three-dimensional RNA nanostructures with more than 100 distinct components, representing, to our knowledge, the largest and most compositionally complex RNA nanoarchitectures reported to date. Overall, the dsRNA bricks approach establishes a scalable and robust framework for constructing complex RNA nanostructures with compositional and architectural sophistication approaching that of DNA-based systems, thereby opening new opportunities for programmable RNA materials and RNA-based devices.

synthetic biology↗

bioRxiv2026

A patient-centric therapeutic paradigm uncouples prostate cancer suppression from systemic metabolic collapse

The clinical benefits of cancer therapies are often compromised by the tolerable adverse effects that impair systemic organismal health and may evolve into latent life threats. Here, we identified profound abiraterone-induced but androgen-independent metabolic perturbations in prostate cancer patients and developed Lifehug-9892 to balance tumor therapy with systemic metabolic homeostasis. By integrating population cohorts with high-resolution metabolomics, we demonstrate that abiraterone induces profound systemic lipidomic dysregulation, characterized by the massive, pathological accumulation of desmosterol. Abiraterone inhibits but stabilizes DHCR24, leading to a metabolic trap in patients showing elevated levels of both desmosterol and cholesterol. Desmosterol accumulation is highly lipotoxic, potently triggering endothelial cell senescence and necrosis, macrophage foam cell formation, murine atherosclerosis, and hepatic senescence. To mechanistically uncouple and therapeutically rescue this systemic metabolic collapse, Lifehug-9892 was rationally designed to selectively retain on-target CYP17A1 inhibition while completely sparing DHCR24 function. Lifehug-9892 maintains potent tumor-suppressive activity while fully preserving the desmosterol-cholesterol metabolic axis and preventing systemic cardiovascular and hepatic damage. Our study uncovers a critical mechanistic link between drug-induced metabolic dysregulation and organismal health in cancer patients, providing a biochemical framework for developing patient-centric targeted therapies that preserve host homeostasis.

cancer biology↗

bioRxiv2026

Beyond Imbalance: An Elasticity Framework for the Distance-averaged Force-Velocity Relationship in Vertical Jump

This study aimed to (1) establish the distance-averaged F-V relationship framework and (2) develop elasticity metrics that quantify how F-V relationship variables govern jump height and inform training prescription. Theoretical derivation and experimental validation across 108 F-V relationship models derived from 1578 jumps (countermovement jump and squat jump at three knee angles; 20 well-trained subjects) yielded a standard error of 2.1% and a nearly perfect correlation (r = 0.96, p < 0.001) between measured and predicted jump height. Four elasticity metrics were formulated: force elasticity (F_{e}), the elasticity of jump height to maximal force (F_{0}); velocity elasticity (v_{e}), the elasticity of jump height to maximal velocity (v_{0}); the force-velocity elasticity norm {(\mathrm{F}-\mathrm{V}}_{\mathrm{EN}}=\sqrt{F_{e}^{2}+v_{e}^{2}}), reflecting the overall sensitivity of jump height to changes in F-V relationship variables; and the force-velocity elasticity ratio {(\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=F_{e}{\div v}_{e}), indicating which variable dominates the jump height response. Simulations and experiments revealed that F_{e} bore an inverse relationship to F_{0}, and v_{e} was inversely related to v_{0}, reflecting diminishing marginal returns. At a fixed jump height, simulations showed {\mathrm{F}-\mathrm{V}}_{\mathrm{EN}} and {\mathrm{F}-\mathrm{V}}_{\mathrm{ER}} displayed a U-shaped relationship; a balanced profile ({\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=1) did not always correspond to the lowest {\mathrm{F}-\mathrm{V}}_{\mathrm{EN}}. The distance-averaged F-V elasticity framework offers a physically grounded and quantitative tool for linking F-V relationship variables directly to jump performance, providing a basis for informing individualized training decisions.

biophysics↗

bioRxiv2026

Quantifying sprint force-velocity elasticity: implications for individualized training decisions

This study aimed to (1) develop an elasticity framework for the sprint force-velocity (F-V) relationship and (2) examine how maximal force (F_{0}), maximal velocity (v_{0}), and sprint distance modulate the four derived elasticity metrics, and (3) explore these elasticity metrics' interrelation. After modelling the F-V relationship differential equation, four elasticity metrics were defined as force elasticity (F_{e}), the elasticity of sprint time to F_{0}; velocity elasticity (v_{e}), the elasticity of sprint time to v_{0}; the force-velocity elasticity norm {(\mathrm{F}-\mathrm{V}}_{\mathrm{EN}}=\sqrt{F_{e}^{2}+v_{e}^{2}}), capturing the combined sprint time sensitivity to proportional changes in F_{0} and v_{0}; and the force-velocity elasticity ratio {(\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=F_{e}{\div v}_{e}), indicating which variable dominates the sprint time response. Model simulations showed that F_{e} decreased with rising F_{0} and increased with rising v_{0}, while v_{e} showed the opposite pattern. With increasing sprint distance, F_{e} decreased and v_{e} increased. Given its negligible effect on sprint time, ignoring air resistance yields a conservation law (2F_{e}+v_{e}\equiv 1), indicating that a gain in one elasticity metric necessarily diminishes the other in a fixed proportion. This framework also identifies a valley distance (d_{valley}) at {\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=2, where {\mathrm{F}-\mathrm{V}}_{\mathrm{EN}} is minimized (\sqrt{0.2}) and sprint time is least responsive to changes in F-V relationship variables. Empirical data confirmed that the two theoretical laws still hold approximately when air resistance is considered. By linking changes in F_{0} and v_{0} to sprint time across different distances, the elasticity framework provides a quantitative basis for estimating the theoretical sprint time response to documented changes in F-V relationship variables.

biophysics↗

bioRxiv2026

Structural basis for catalytic and inhibitory divergence between archaeal and bacterial ammonia monooxygenases

Ammonia oxidation initiates nitrification and is closely linked to microbial N2O production. Ammonia monooxygenase (AMO) catalyzes the first and rate-limiting step of nitrification and is widespread across evolutionarily distinct ammonia-oxidizing archaea (AOA) and bacteria (AOB). The ocean is the largest biome for AOA and AOB, which have distinct ecological niches and markedly different sensitivities to nitrification inhibitors. However, the lack of archaeal AMO structures and inhibitor-bound AMO complexes has hindered mechanistic understanding of the architectural, catalytic, and inhibitory divergence between these two enzyme systems. Here, we report high-resolution cryo-electron microscopy (cryo-EM) structures of marine archaeal AMO captured in active and inactivated states within its native membrane environment, together with inhibitor-bound structures of estuarine bacterial AMO. Archaeal AMO forms an unexpected cup-shaped homotrimer composed of eight subunits per protomer and exhibits substantial architectural divergence from bacterial AMO. Integrated structural, biochemical, kinetic, and computational analyses reveal distinct periplasmic architectures, copper-center organization, and hydrophobic channels between archaeal and bacterial AMOs for ammonium acquisition, catalysis and inhibitor response. These findings provide a structural and mechanistic framework for understanding how archaeal and bacterial AMOs have diverged to distinct ammonia-oxidizing strategies and inhibitor susceptibilities across environmentally important ammonia oxidizers.

molecular biology↗

bioRxiv2026

Chimeric Induced Cooperativity Opens the Design Space of Eukaryotic Gene Regulation

Predictive engineering of eukaryotic transcription is limited by the coupling of signal sensing, DNA binding, TF abundance and promoter output. Here we establish chimeric induced cooperativity (CIC), a modular architecture that separates LBD, DBD and AD functions and links them to promoters with tunable basal and maximal output. Module parameters can be recombined to predict new CIC-TF configurations and guide design before construction. Ligand-induced cooperativity reduces basal DNA occupancy while increasing induced occupancy, and effective DBDs combine low OFF-state activity with strong ON-state promoter occupancy rather than binding strength alone. Synthetic promoters independently control occupancy gain and output range. The same framework extends to repression and can be recalibrated with limited measurements in mammalian cells. In yeast, CIC-12 achieved a mean fold induction of 298-fold across 12 orthogonal sensors; an earlier CIC-10 chassis enabled model-guided optimization of an eight-gene vitamin B5 biosynthetic pathway. CIC establishes a programmable, model-guided design space for eukaryotic transcriptional control.

synthetic biology↗

bioRxiv2026

Avs2 drives non-canonical tetrameric assembly of trypsin-like domain for anti-phage defense

Bacteria have evolved diverse anti-phage defense systems, with the antiviral STAND family (Avs) representing one of the most diverse and widespread, encompassing at least 90 distinct families, yet only Avs3, Avs4, Avs5 and Avs7 have been well characterized. Here, we elucidated the molecular mechanism of Avs2-trypsin-MBL system, where phage terminase recognition by Avs2 triggers coupled activation of the protease and nuclease activities of trypsin-MBL. Cryo-EM structure of Avs2-trypsin-terminase and biochemical analysis reveal that the binding of terminase ATPase domain triggers the assembly of Avs2 into tetramer, with two unique ATP molecules bridging ATPase active-site recognition by TPR domain. This tetramerization drives the fused trypsin into an active C4-symmetric assembly, an architecture distinct from the conventional non-defense trypsin. Our study unravels the activation mechanism of Avs2-trypsin-MBL system, expanding our understanding on commonality and diversity of widespread Avs-mediated anti-phage immunity, alongside the structural and functional adaption of trypsin.

microbiology↗

bioRxiv2026

Programmable De Novo Design of Mesoporous Protein Crystal Frameworks

Three-dimensional protein crystals are ordered, porous macroscopic materials with potential applications in catalysis, biosensing, and biomedicine. However, most protein crystals are obtained by empirical screening, providing limited control over the lattice architecture, pore geometry or component composition that determine material function. Here, we present a modular strategy for the programmable design of highly porous, framework-like protein crystals using predefined protein-protein interactions. This strategy yielded over 30 distinct protein crystals, including single-component and multicomponent P213 and I213 lattices that grow to over 100 micrometers in size. Small-angle X-ray scattering and electron microscopy showed close agreement between experimental lattices and computational models. RFdiffusion-guided design generated isomorphous variants with matched lattice parameters, enabling coherent protein crystal alloys, epitaxial core-shell growth and reversible shell assembly. The designed crystals exhibit tunable mesoporous architectures, with limiting apertures of 2-18 nm, and support genetically encoded incorporation of fluorescent protein guests. These results establish a general route to programmable lattice engineering of protein crystals and position them as genetically encoded, compositionally tunable mesoporous materials.

synthetic biology↗

bioRxiv2026

TxNova: recovery of recurrent unannotated intergenic splice loci from existing bulk RNA-seq alignments

Background. Reference catalogs such as GENCODE capture most stably expressed mammalian genes but may not include condition-restricted or low-abundance transcripts. Reads supporting unannotated intergenic splice junctions are generally absent from annotation-restricted gene-count matrices; transcript assemblers may reconstruct a subset as novel models, but those models are typically handled separately from the annotated gene-count universe. TxNova is a lightweight command-line tool that directly indexes these unannotated splices from existing BAM files - without an external assembler, gffcompare, or workflow manager - yielding candidate leads for bench validation rather than standalone discovery claims. Methods. TxNova retains CIGAR N junctions from STAR/HISAT2 BAM files that recur in >= 2 samples and are absent from a comprehensive annotation, clusters them into residual loci, and counts each locus alongside annotated genes in a unified matrix. Structure gates - canonical splice motif, same-strand distance, coverage valley, bridging-junction absence, minimum length - remove likely artifacts to yield structure-pass models. An optional contrast filter retains loci detected in treatment but nearly silent in control. Results. A residual splice is a recurrent, unannotated CIGAR N junction that does not overlap any annotated gene body; intronic and antisense channels are out of scope. Across four published mouse treatment arms (GSE221720, GSE166522, GSE157460, GSE193335), harvest catalogs yielded 464, 657, 789, and 594 loci. On GSE221720, 45% of loci (209/464) shared an exact intron with another series, versus 0.074% for excluded junctions; a coordinate-placement control yielded 0/5,000 matches for length-matched intergenic decoys. Masked-gene recovery reached 87.6% (176/201) overall and 99.4% (176/177) among genes with a leak junction - sensitivity rather than precision estimates. An optional contrast provides a presence/absence screen on interval TPM. Residual models are partial reconstructions requiring cloning, RACE, or targeted proteomics for confirmation. Conclusions. TxNova produces a reproducible intergenic residual-locus catalog from existing BAM files, with four downloadable mouse injury/infection catalogs. Cross-series recurrence and coordinate-based null controls support reproducibility above simple placement backgrounds but do not by themselves establish biological validity. The optional contrast step offers a practical screen for candidate leads warranting experimental validation.

bioinformatics↗

bioRxiv2026

Chili Pepper Flavourants in 'Heat" Oral Nicotine Pouches Marketed as Unflavoured in United States Jurisdictions Restricting Flavoured Tobacco Products

Background: In the United States, several states have restricted sales of flavoured tobacco products, including popular menthol- and mint-flavoured Oral Nicotine Pouches (ONP). In response, tobacco companies introduced "unflavoured" ONP containing odorless synthetic cooling agents. Since these, in turn, have become targets of legislative bans, the tobacco industry may seek out flavourants with other sensory effects to increase the appeal of "unflavoured" ONP. Methods: Online merchants were searched for "unflavored" ONP marketed to consumers in jurisdictions with flavour bans. Sensory effects of aqueous extracts from identified "heat", "spicy" and "unflavoured" ONP were analyzed by Ca2+ microfluorimetry in HEK293 cells expressing the human heat/chili pepper flavourant (capsaicinoid) receptor, hTRPV1. ONP were analyzed for capsaicinoids and sweeteners by Liquid Chromatography/Mass Spectrometry (LC/MS). Results: A new category of "heat" or "spicy" ONP was identified, including products marketed as "unflavoured". Extracts from all these ONP robustly activated TRPV1, with "unflavoured" Lucy Heat the most potent. Chemical analysis demonstrated that Lucy Heat contained the synthetic capsaicinoid nonivamide at high levels (~675 microgram/pouch), while others contained mixtures of capsaicinoids (5-25 microgram/pouch) combined with other characterizing flavours (tropical, fruit). All tested ONP contained sweeteners. Conclusions: The tobacco industry continues to probe regulatory loopholes by claiming that newly introduced capsaicinoid flavourants and sweeteners in ONP do not represent characterizing flavours. This is contradicted by industry and regulatory determinations assigning characterizing flavour properties to these additives. The toxicological health risks of repeated capsaicinoid exposures due to ONP use, in combination with nicotine and other constituents, need to be assessed.

pharmacology and toxicology↗

bioRxiv2026

Subgenome-Level Phylogeny Reveals an Allopolyploid Origin of Chloranthales from Ancestral Monocot and Eudicot Lineages

Angiosperms (flowering plants) represent the most species-rich lineage of land plants, yet deep phylogenetic relationships among their major clades, particularly within mesangiosperms, remain notoriously difficult to resolve. Although hybridization and whole-genome duplication (WGD) are recognized as major evolutionary forces, the contribution of ancient allopolyploidization, which combines hybridization with WGD, to deep-node phylogenetic discordance in mesangiosperms remains poorly understood. Here, we analyzed genomes from seven representative early-diverging angiosperm lineages, each containing no more than one lineage-specific WGD event. Using a comparative phylogenomic framework, we characterized WGD-derived paralogs across five WGD-bearing lineages. In contrast to other polyploid lineages, Chloranthales WGD-derived paralogs rarely formed sister relationships in gene trees. After evaluating alternative explanations, including incomplete lineage sorting, ancient paralogy, and analytical artifacts, we demonstrate that this discordant phylogenetic signal reflects the genomic legacy of an ancient allopolyploidization event. We further resolved the Chloranthales subgenomes by exploiting biased fractionation patterns within conserved syntenic regions. Subgenome-resolved phylogenomic analyses revealed that the dominant Chloranthales subgenome exhibits phylogenetic affinity with eudicots, whereas the recessive subgenome is associated with monocots, indicating a deep reticulate origin involving ancestral lineages related to these major angiosperm clades. Our findings provide subgenome-resolved evidence that ancient allopolyploidization can connect deeply diverged lineages during early angiosperm evolution, highlighting the importance of incorporating reticulate polyploid histories into phylogenomic frameworks for resolving deep evolutionary relationships.

systems biology↗

bioRxiv2026

TRAPPC8 Is an Endogenous Brake on UFMylation That Suppresses Tauopathy

UFMylation, a ubiquitin-like protein modification, drives tau spread through the brain, but what keeps this process in check has remained unclear. We show that TRAPPC8 acts as a natural brake on UFMylation, binding directly to the E1 enzyme UBA5 to dampen pathway activity. In Alzheimer's disease brain tissue, TRAPPC8 is reduced while UFMylation is elevated, suggesting this brake fails as disease progresses. Sustaining UFMylation in human iPSC-derived neurons increased tau aggregation and spread while disrupting lysosomal function and lipid balance. Restoring TRAPPC8-UBA5 binding reversed these defects through the lysosomal protein CLN8, which restored lysosomal function and reduced tau pathology. Notably, expressing just the UBA5-binding region of TRAPPC8 was enough to suppress tau pathology in vivo, marking it as a promising therapeutic target.

neuroscience↗

bioRxiv2026

PC1-guided transcriptomic stratification reveals hepatic transcriptional heterogeneity and defines a myeloid-associated 20-gene signature

Hepatic lipid-associated inflammation contributes to metabolic liver disease and cardiometabolic complications. Treatment-based transcriptomic comparisons can obscure inter-individual heterogeneity when animals exposed to the same experimental condition show divergent molecular responses. In the public hyperlipidemic liver transcriptomic dataset GSE338111, conventional sex-adjusted comparison of Amlexanox versus DMSO identified only 21 differentially expressed genes at FDR < 0.05 and |log2FC| [≥] 1, and submission of this DEG set to Metascape yielded no GO Biological Process enrichment result. We therefore applied treatment-independent, PC1-guided transcriptomic stratification based on the 500 most variable genes. This analysis resolved three PC1-derived groups and enabled derivation of a myeloid-associated 20-gene signature from the G2-versus-G1 contrast. Independent bulk-transcriptomic cohorts supported responsiveness of the signature to dietary challenge and pharmacologic intervention, while single-cell analysis localized its expression predominantly to hepatic myeloid populations. Human cis-eQTL Mendelian randomization and colocalization further identified TAGLN2 as the signature gene with the strongest genetic support for coronary heart disease. Together, these findings show that PC1-guided stratification can improve resolution of heterogeneous hepatic transcriptional responses and provide a cross-cohort molecular signature for subsequent mechanistic and translational evaluation.

genomics↗