Biology subjects

Li, X.

Publications and source records attributed to Li, X..

At least 163 records · Page 9Linked to original sources

bioRxiv2026

A GPX4 phosphorylation switch by FGFR1 guards against ferroptosis

Ferroptosis is driven by lipid peroxidation, yet the mechanisms by which cells rapidly adjust their sensitivity to ferroptosis in response to extracellular cues remain elusive. We identify a direct phosphorylation switch controlling the activity of glutathione peroxidase 4 (GPX4), the core ferroptosis regulator. The receptor tyrosine kinase FGFR1 directly binds and phosphorylates GPX4 at Tyr180/Tyr196 in a kinase-dependent manner, requiring its Tyr730 as a docking site. This phosphorylation enhances GPX4s catalytic activity and suppresses ferroptosis. In cardiac ischemia/reperfusion injury, the FGFR1-GPX4 axis is suppressed, and a selective FGFR1 agonist (FGF-1{Delta}NT) reactivates it to protect against ferroptosis-mediated damage. Critically, a phosphorylation-deficient GPX4 knock-in mouse exhibits hypersensitivity to injury and non-responsive to this agonist, proving that GPX4 phosphorylation is essential. Our findings reveal a rapid mechanism for regulating ferroptosis via GPX4 tyrosine phosphorylation, directly linking receptor tyrosine kinase signaling to ferroptosis, and offering new strategies for treating ischemic-and other ferroptosis-associated diseases.

Cell Biology↗

bioRxiv2026

Seeing the world in a grain of sand: Fine global and local representations in foveal and parafoveal vision

Foveal vision enables primates to perceive small objects with remarkable precision by resolving both fine-global form and fine-local detail. Yet current coarse-to-fine and local-to-global frameworks, derived largely from parafoveal recordings and large-object representations, posit that V1 encodes local detail whereas IT represents global form, leaving the neuronal basis of foveal object representation unresolved. Here we show that fine-global form and fine-local detail are encoded parallelly as early as V1 and preserved across V2, V4 and IT at both foveal (1{degrees}-2{degrees}) and parafoveal (2{degrees}-6{degrees}) retinal eccentricities. Coarse-global features dominate parafoveal vision and higher cortical areas. Response latencies revealed a rapid processing sequence, with 2-6 ms separating coarse-global, fine-local, and fine-global processing within parafoveal V1, V2 and V4. These findings establish a cortical neuronal framework to resolve fine-global form of small objects in foveal vision along primate ventral visual stream, supporting fine-scale perception during reading and fine object recognition. Highlights O_LIFoveal two-photon imaging across V1, V2, V4, and IT C_LIO_LIGlobal and local processing examined across eccentricity C_LIO_LIFine and coarse global representations emerge as early as V1 C_LIO_LIFine global and local representations are preserved from V1 up to IT C_LIO_LITightly timed coarse-to-fine-to-fine processing within each cortex C_LIO_LIFast coarse-global dominates parafoveal and higher cortical areas C_LI

neuroscience↗

bioRxiv2026

Spatial atlas highlights contribution of C. difficile in early-stage colorectal cancer

Background and AimsIntratumoral heterogeneity with respect to both host and microbial components has emerged as an important contributor to colorectal cancer (CRC) biology. Although the overall taxonomy and abundance of the CRC tumor microbiome have become well characterized, much less is known about bacterial niches within the tumor microenvironment (TME). Escherichia coli and Fusobacterium nucleatum are highly prevalent and abundant species linked to CRC. Less abundant organisms, like Clostridioides difficile and Enterocloster aldenensis, are emerging as potentially important CRC-associated bacteria. Additionally, many studies are confounded by preoperative oral antibiotics or the inclusion of late-stage cancers, both of which may alter the gut microbiome. To better understand the spatial relationships between bacteria and CRC, we generated a molecular atlas based on surgically resected tissue specimens collected from a unique cohort of early-stage CRC patients in whom oral antibiotics were not administered preoperatively. MethodsFrom 20 CRC specimens, we performed matched histopathological analysis, fluorescence in situ hybridization (FISH), whole exome sequencing (WES), 16S rRNA amplicon bacterial DNA sequencing, codetection by indexing (CODEX) multiplex immunofluorescence, and spatial transcriptomics of 756 regions among the specimens. We used 16S rRNA amplicon sequencing data to design and experimentally validate custom bacterial probes that were applied to the spatial transcriptomics. Human colonic organoids were used to validate the relationship between Clostridioides difficile toxin B (TcdB) and an E-twenty-six family transcription factor, ELF3. ResultsWe identified eight intratumoral bacterial niches consisting of a variety of bacterial species, and each niche was associated with unique tumor features. We further defined tumor gene expression patterns correlating with individual bacterial species and show that C. difficile has a disproportionate impact on the tumor transcriptome given its relatively low abundance. Specifically, TcdB induces nuclear localization of ELF3, increased cytosolic {beta}-catenin protein, and upregulated WNT signaling. ConclusionOur study integrates multi-omics to identify bacterial species with biological and spatial relevance in CRC regardless of abundance. These findings will enable further studies to define diagnostic and therapeutic targets for bacteria-associated CRC.

Cancer Biology↗

bioRxiv2026

Sequence-to-function modeling uncovers the context-specific grammar of Drosophila chromatin insulation

Chromatin is organized into self-interacting topologically associating domains partitioned by boundary elements that insulate adjacent domains and restrict regulatory interactions. Yet, how sequence context and combinations of factors dictate boundary strength remains incompletely understood. Here we present Domino, a deep learning framework that maps genomic sequences to quantitative insulation scores defined directly from single-nucleosome resolution Drosophila melanogaster Micro-C data. Unlike traditional transcription factor motif scanning, Domino captures broad sequence context to resolve the functional contributions of individual sequence elements. We validate model predictions through experimental perturbations of insulator sequences. Model interpretation yields insulation-associated motifs genome-wide. Across 7,311 embryonic boundaries, Domino reveals a comprehensive insulation grammar defined by just 24 primary motifs that account for 59% of the boundaries, with an average of only two motifs per motif-containing boundary. Beyond known factors, we identify the zinc-finger proteins Trem, CG4854 and CG17385 as previously unreported insulation factors. We uncover distance- and orientation-dependent motif synergy, including a strict orientation preference of the prominent architectural factor M1BP. Finally, Domino traces tissue-specific shifts in the insulator landscape from the embryo to larval and adult brains, nominating new brain-specific insulation motifs. In sum, Domino provides a generalizable framework for decoding the regulatory logic of 3D genome architecture.

genomics↗

bioRxiv2026

Hyperalignment Reveals Shared Information in Macaques' Idiosyncratic Fine-Grained Movie fMRI Patterns

Response hyperalignment (RHA) of fMRI patterns acquired during movie-viewing in 12 rhesus monkeys revealed shared representational spaces despite idiosyncratic functional topographies. RHA greatly improved inter-subject correlation of movie response time-series in occipital, temporal, and prefrontal cortices and afforded highly accurate between-subject decoding of movie time-points and estimation of idiosyncratic functional topographies. These results demonstrate that nonhuman primates share high-dimensional, high-capacity representational spaces encoded in idiosyncratic fine-grained functional topographies.

neuroscience↗

bioRxiv2026

NKG2C+CD27- Defines Human CD8+ Regulatory T Cells

Here we identify NKG2C+CD27- as a novel surface marker unifying multiple previously reported CD8+ regulatory T cell (Treg) populations. This population displays high clonality and divides into CD226- (Treg1) and CD226+ (Treg2) subsets, with Treg2 exhibiting stronger suppressive activities. Up to 35% of CD8+ TEMRA cells are Tregs, whereas approximately 85% of CD8+ Tregs are TEMRA cells, which increase with aging. These findings establish a unified and novel cell surface marker for CD8+ Tregs and their subsets, which resolves prior heterogeneity in the field, and show that CD8+ TEMRA cells are a heterogeneous population that includes T cells with regulatory function. Our findings provide a critical framework for the isolation and in-depth functional characterization of CD8+ Tregs in health, aging, and disease.

immunology↗

bioRxiv2026

DNA-binding specificity recognition from predicted homologous protein-DNA structures

Predicting protein DNA-binding specificity is essential for understanding gene regulation and disease mechanisms. Existing deep learning methods typically infer specificity from a single protein-DNA complex structure, which limits their ability to capture the diverse geometric patterns underlying protein-DNA recognition. Homologous protein-DNA interfaces provide complementary structural evidence and richer geometric features related to interatomic interactions. To address the limited diversity and coverage of experimentally determined complexes, we constructed a large-scale library of predicted homologous protein-DNA complex structures. Building on this resource, we propose HomoDSP, a template-retrieval-based framework for accurate DNA-binding specificity prediction. Benchmark evaluations and validation on newly released JASPAR 2026 samples indicate that HomoDSP outperforms existing methods in both accuracy and generalization, with particularly substantial gains on high-error samples. Moreover, this performance is largely retained when AlphaFold3-predicted complex structures are used as input. Template- and residue-level interpretability analyses suggest that HomoDSP improves prediction by focusing on DNA-affinity residues across multiple homologous templates. Finally, universal Protein Binding Microarrays evaluations on AI-designed DNA-binding proteins show that HomoDSP rescues a baseline failure mode in which the baseline method produces incorrect predictions because of training-set bias. Together, these results support the use of homologous template interfaces as informative structural priors for decoding protein DNA-binding specificity.

bioinformatics↗

bioRxiv2026

scIsoAgent enables autonomous isoform-resolved characterization and sequence-informed interpretation of long-read single-cell transcriptomes

Alternative isoform usage can alter gene function independently of total gene expression, creating a need to resolve transcript isoforms at single-cell resolution. Long-read single-cell RNA sequencing meets this need by linking cellular identity to transcript isoforms and sequence-level features. Realizing its full biological value requires reproducible workflows that connect specialized long-read analysis with biological interpretation. Existing large language model (LLM)-based biomedical agents support general omics analysis, but are not designed for isoform-resolved long-read single-cell workflows. Here, we present scIsoAgent, an autonomous LLM-powered scientific agent for long-read single-cell RNA-seq analysis. scIsoAgent turns heterogeneous long-read single-cell inputs into traceable isoform-resolved workflows, using stage-aware planning and persistent computational context to support both execution and interpretation. Across complementary evaluations, this design improved the continuity from analysis planning to executable, interactive workflows compared with general-purpose LLM baselines. In real-data reanalysis, scIsoAgent recovered major findings from published long-read single-cell resources and extended a representative differential transcript usage event into a sequence-informed functional hypothesis. By linking full-length isoform sequences with model-inferred transcript properties, scIsoAgent connects observed isoform usage with potential sequence-level functional consequences. These results demonstrate that autonomous scientific agents can transform fragmented long-read single-cell analysis into coherent, reproducible workflows for isoform-resolved discovery and biological interpretation.

bioinformatics↗

bioRxiv2026

A glial source of noradrenaline shapes synaptic integration and motor adaptation

Noradrenaline is a major neuromodulator that shapes neural circuit dynamics and behavior. Prevailing models attribute noradrenergic supply exclusively to long-range inputs from distant nuclei. Yet noradrenergic input can be weak in regions that nonetheless show marked noradrenergic modulation, suggesting additional sources. This mismatch is salient in the cerebellum, where noradrenaline influences behavior despite sparse innervation. Here, we identify Bergmann glia, radial cerebellar astrocytes, as a source of noradrenaline. Using two-photon imaging and cell-type-specific genetic manipulations, we show that Bergmann glia can synthesize and release noradrenaline through a calcium-dependent mechanism requiring the vesicular monoamine transporter VMAT2. Glia-derived noradrenaline modulates synaptic integration in Purkinje neurons and is required for motor adaptation. Together, these findings identify a glial pathway that complements the canonical long-range view of noradrenaline supply.

neuroscience↗

bioRxiv2026

Entanglement-governed protein networks enable mechanically adaptive artificial skin for transplantation-scale skin replacement

Artificial skin substitutes that simultaneously achieve mechanical robustness, regenerative bioactivity, and transplantation-scale tissue integration remain challenging to engineer. Here we report a mechanically adaptive bilayer artificial skin based on entanglement-mediated protein networks. By integrating protein chain entanglement, flexible molecular linkers, and photo-triggered intermolecular crosslinking, we establish a hierarchically organized protein matrix with enhanced toughness, structural adaptability, and regenerative compatibility. Spatial biofunctionalization further enables integration of an antibacterial Zn{superscript 2}-coordinated epidermal layer and a regenerative CLP-EGF-functionalized dermal layer within a unified construct. The engineered skin promotes cellular proliferation through PI3K-AKT-mTOR activation, exhibits sustained antibacterial activity, and supports large-area full-thickness skin replacement covering approximately 40% of the dorsal skin surface in mice. The construct further accelerates diabetic wound repair and extracellular matrix remodeling in vivo. These findings establish entanglement-mediated protein engineering as a strategy for mechanically adaptive regenerative biomaterials and provide a platform for transplantation-scale skin regeneration.

bioengineering↗

bioRxiv2026

TAp63-regulated oncogenic long non-coding RNA-8 ( TROLL-8 ) regulates human breast cancer progression through CPT1A-mediated fatty acid oxidation

Metabolic reprogramming is a crucial hallmark of cancer, supporting tumor growth and adaptation to cellular stress. Although fatty acid oxidation (FAO) has emerged as an important regulator in cancer, the mechanisms that control the FAO machinery remain poorly understood. Here, we demonstrate that the TAp63-regulated long non-coding RNA TROLL-8 is a key regulator of FAO in breast cancer. Using metabolomics and protein microarray assays followed by immunoprecipitation-mass spectrometry, we mechanistically demonstrate that TROLL-8 binds the FAO enzyme CPT1A and promotes the formation of a complex with ACSL1 and VDAC1, thereby enabling efficient fatty acid processing. Loss of TROLL-8 destabilizes this complex, leading to impaired FAO, decreased metabolic fitness, and suppression of tumorigenic phenotypes, such as anchorage-independent growth. Notably, higher levels of CPT1A and VDAC1 are associated with worse survival in breast cancer patients. Given the emerging role of CPT1A in therapy resistance, these findings suggest that targeting TROLL-8 could be a promising approach to selectively disrupt the hyperactive FAO machinery in breast cancers and other tumor types that rely on FAO for their progression.

Cancer Biology↗

bioRxiv2026

Circadian clock gates retinal regeneration by orchestrating Cxcl12-dependent immune coordination

The circadian clock orchestrates tissue homeostasis and repair, yet its role in central nervous system (CNS) regeneration remains largely unexplored. Here, we identify the circadian clock as an essential regulator of adult zebrafish retinal regeneration, a CNS model. Retinal injuries induced at distinct circadian times elicit differential Muller glia (MG) reprogramming and progenitor proliferation, both of which exhibit robust diurnal fluctuations. Disrupting circadian rhythms--via constant darkness (DD) or day-night reversal (DL)--suppresses MG reprogramming, MG-derived progenitor cell (MGPC) formation and neuronal regeneration, concomitant with dampened retinal immune responses. Notably, intravitreal immune stimulation restores MGPC numbers in the retina under DD conditions, linking immune activation to circadian-regulated regeneration. Single-cell RNA-seq reveals that DD disrupts MG reprogramming trajectories while inducing unfolded protein response (UPR) and suppressing ATP/protein synthesis. Moreover, clock disruption alters microglia heterogeneity, and cell-cell communication analysis identifies the Cxcl12-Cxcr4 signaling as a key chemotactic axis between MG/endothelial cell and immune populations. Mechanistically, Bmal1b directly binds E-box motifs in the cxcl12a/12b promoters, driving their rhythmic transcription to orchestrate the immune response after injury. Importantly, exogenous Cxcl12a partially restores both immune and regenerative responses in clock-disrupted retinas, establishing the Cxcl12-Cxcr4 axis as a circadian-immune checkpoint for retinal repair. Collectively, our findings reveal a novel paradigm in which the circadian clock gates CNS regeneration through Cxcl12-mediated immune coordination, offering potential therapeutic insights for CNS repair in mammals.

neuroscience↗

bioRxiv2026

Functional orthogonality of WRN inhibitor resistance enables alternating therapy and mutation-tolerant inhibitor design in MSI-H cancers

Werner syndrome helicase (WRN) is a synthetic-lethal vulnerability in microsatellite instability-high (MSI-H)/mismatch repair-deficient (dMMR) cancers1-5, and non-covalent and covalent WRN inhibitors are now entering clinical development6-9. A central unresolved question is whether resistance to one WRN inhibitor class inevitably compromises the target, or instead creates actionable vulnerabilities to an alternate modality. Here we generated ten stable acquired-resistance models across three MSI-H cell lines using the non-covalent inhibitor HRO761 and the covalent inhibitor VVD-214. Whole-exome sequencing, biochemical reconstitution and isogenic knock-in models identified recurrent on-target WRN missense mutations as dominant resistance drivers, but with sharply modality-specific spectra: HRO761 resistance clustered at G729/F730/I852, whereas VVD-214 resistance concentrated at E846. These mutations impaired inhibitor engagement and abolished the canonical WRN inhibitor (WRNi)-induced pharmacodynamic cascade, including WRN reduction, DNA damage response (DDR) activation and G2/M arrest. Crucially, most resistance mutations retained biochemical, cellular and in vivo sensitivity to the alternate inhibitor modality, revealing a functional orthogonality that enabled a 7-day cyclic alternating regimen to delay tumour regrowth in xenografts. We further identified F730L as an engineered cross-resistant bottleneck model and used structure-guided, artificial intelligence (AI)-enabled optimization to generate GBA-007, a proof-of-concept mutation-tolerant WRN inhibitor candidate with promising activity against F730L in vitro and in vivo. Thus, clinically relevant WRN inhibitor classes impose distinct on-target resistance trajectories that can be exploited through schedule design, while cross-resistant bottlenecks can be addressed by rapid mutation-aware inhibitor engineering.

Cancer Biology↗

bioRxiv2026

SPOTTER: Automated Tissue-Barcoding Platform for Spatial Proteomics and Phosphoproteomics

Spatial proteomics aims to characterize proteome in situ with regional resolution, linking molecular states to tissue architecture and microenvironments. While recent advances have expanded our access to spatially resolved proteomics, major barriers in scalability and throughput remain. Building on our prior SPOT (Spatial Proteomics through On-site Tissue-protein-labeling) framework1, we introduce SPOTTER, a customizable robotic platform that enables automated, micron-scale spatial barcoding directly on intact tissue sections. SPOTTER barcodes proteins by labeling tissue proteins in situ to encode spatial origin across the whole tissue section. This strategy enables unbiased whole-tissue proteome mapping and, for the first time, spatial phosphoproteome profiling from intact sections. Coupled with high-resolution LC-MS/MS, SPOTTER achieves deep proteome and phosphoproteome coverage while preserving histological integrity. By replacing labor-intensive laser capture microdissection workflows and low-plex antibody arrays, SPOTTER provides a scalable route to high-plex spatial proteomics, resolving spatially distinct regions within a single experiment.

bioengineering↗

bioRxiv2026

Somatic Genome Diversification and Clonal Evolution of Pathogenic B Cells in Systemic Autoimmunity

Systemic autoimmune rheumatic diseases are characterized by persistent immune activation and clinical heterogeneity, yet the molecular processes sustaining and diversifying pathogenic immune states remain incompletely understood. Here, we investigate somatic genome diversification as a potential driver of immune variation and disease progression. Using Systemic Lupus Erythematosus as a model disease, we generated a subset-resolved map of somatic mutations across B-cell subsets from 35 patients. Double-negative (DN) B cells carried the highest mutational burden, which was associated with disease duration and immunosuppressive therapy, rather than with disease activity. Integration with single-cell transcriptomes linked DN mutations to dysregulated signalling and proteostasis. Notably, DN cells harboured mutations in genes recurrently altered in B-cell lymphomas. Together, these findings identify somatic genome diversification as a feature of pathogenic B-cell subsets and provide a resource for understanding how chronic stimulation and therapeutic pressure shape the clonal evolution of autoimmunity. KEY POINTSO_LIDouble-negative B cells in SLE carry the highest somatic mutational burden among circulating B-cell subsets and show evidence of treatment-associated mutational processes. C_LIO_LIPathogenic variants in DN cells are acquired de novo or through selective expansion of pre-existing variant-bearing clones. C_LIO_LIAcquisition of lymphoma-relevant mutations by DN cells is common, supporting a molecular-level linkage between chronic systemic autoimmunity and B-cell malignancies. C_LIO_LIThe high-depth, subset-resolved map provides a foundational resource for the functional prioritization of variants and the development of targeted sequencing strategies for monitoring pathogenic clones. C_LI

genomics↗

bioRxiv2026

Validation of MHPC512: A Publicly Available Special-Purpose Supercomputer for Molecular Dynamics Simulations of Biomolecular Systems

MHPC512 is a massively parallel, special-purpose supercomputer designed primarily for atomic-level molecular dynamics (MD) simulations of biomolecular systems. It comprises 512 processor units interconnected by a high-speed three-dimensional torus network and employs a custom chip architecture that uses 35-bit fixed-point arithmetic to accelerate computation while controlling precision loss within an acceptable margin. The preprocessor is compatible with GROMACS and AMBER input formats and supports widely used biomolecular force fields (including CHARMM, AMBER, and OPLS/AA), the Neutral Territory method for short-range nonbonded interactions, the k-space Gaussian Split Ewald method for long-range electrostatics, and multiple thermostats, barostats, and integrators. We present a three-tier validation protocol--comparing static energy and virial components, examining ensemble distributions (NVE, NVT, NPT), and evaluating long-time statistical properties--demonstrating that MHPC512 reproduces results consistent with GROMACS and AmberTools. Application examples, including bulk water, dipeptide conformational sampling, folding of fast-folding peptides, membrane-protein systems, lipid self-assembly, and GPCR conformational transitions, further confirm its reliability. MHPC512 has been deployed at multiple supercomputing centers and is publicly accessible, representing a significant advance in high-throughput, large-scale biomolecular MD simulations.

Molecular Biology↗

bioRxiv2026

Controlling metal-carbonate phase, form, and function through de novo protein design

Biomineralization enables living systems to construct hybrid materials by controlling the location, orientation, and polymorph of inorganic crystals with proteins and other biomolecules. Despite decades of study, the molecular principles underlying these processes remain difficult to harness in engineered materials, in part because native biomineralization proteins are often intrinsically disordered, heterogeneous, or insoluble. Here we show that de novo designed protein interfaces can be assembled into reconfigurable two-dimensional arrays which template calcite nanocrystals. By fine-tuning RFdiffusion2 on repeat protein scaffolds, we further enable the design of protein architectures which selectively form aragonite, a metastable polymorph of calcium carbonate, in nucleation conditions that otherwise result in a mixture of phases. Extending beyond inorganics found in biological systems, we show that lattice-matched protein designs template cobalt carbonate formation: a flat helical repeat protein interface promotes unconfined growth, whereas soluble D3 cage assemblies yield more homogenous cobalt carbonate nanocrystals confined to the interior of the cage. These protein-cage cobalt carbonate hybrid materials function as electrocatalysts for alkaline water splitting. Our results demonstrate the potential of deep learning-based methods to unlock the structural and functional activity of protein-mineral composites.

biochemistry↗

bioRxiv2026

Sequence-encoded H2A.Z nucleosome dynamics control DNA unwrapping and SUV420H1 recognition

H2A.Z and canonical H2A adopt nearly identical nucleosomal folds, yet their distinct chromatin functions are not captured by static structural analysis. Using fast magic-angle spinning 1H-detected solid-state NMR, we show that H2A.Z possesses enhanced backbone flexibility in the L1 loop and the 2-L2 region (M2) relative to H2A. Chimeric segment-swapping demonstrates that these dynamic signatures are locally sequence-encoded and functionally transplantable. The inherent mobility of the M2 region promotes nucleosomal DNA-end unwrapping and persists when DNA ends are stabilized by linker histone H1 or opened by SUV420H1, indicating that this mobility is intrinsic rather than a passive consequence of DNA detachment. Chemical shift perturbation mapping and catalytic assays further show that SUV420H1 reads this H2A.Z-specific conformational landscape: the M2 region, together with the H2A.Z DS motif, supports variant-selective methyltransferase activity. These findings establish an axis of sequence-dynamics-accessibility-recognition along which local backbone fluctuations serve as physical determinants of epigenetic enzyme specificity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/731474v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@a50ceforg.highwire.dtl.DTLVardef@1f43af0org.highwire.dtl.DTLVardef@14969b8org.highwire.dtl.DTLVardef@bbbe0d_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗