Biology subjects

Yu, Z.

Publications and source records attributed to Yu, Z..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

The diversity of disease-associated natural human antibody specificities declines dramatically in Alzheimers disease.

Alzheimers disease (AD) is the leading cause of dementia and administration of monoclonal antibodies against A{beta} amyloid are associated with disease modifying effects leading to FDA approval for some antibodies. Naturally-occurring human antibodies (NAbs) are believed to be the front line of defense against a variety of diseases, so we investigated the specificity of NAbs in AD and cognitively normal (NC) individuals using epitomic profiling (EP). We found that the diversity of antibody-specific peptide epitope segments (ES) declines dramatically (26-fold) in the AD compared to NC populations. Many of these differentially expressed ES (DEES) map to amyloid sequences that accumulate in AD, such as A{beta}, tau, -synuclein, TDP43 and TMEM106b. NAbs that target amino terminal A{beta} epitopes are elevated in AD (residues 1-6 and 18-21) and NAbs that target different A{beta} epitopes are elevated in NC (residues 5-10 and 35-41). DEES that map to 2N4R tau are highly cross correlated in the population implying that that the antibodies may be polyspecific or that a set of antibodies are coordinately regulated. We used weighted gene correlation network analysis (WGCNA) to identify co-expressed DEES and UMAP to embed DEES in both AD and NC populations that bind to the same antibody or co-expressed set of antibodies. An average of approximately 25 DEES cluster in each WGCNA group. A major WGCNA cluster associated with AD contains 3 groups of overlapping DEES that assemble into longer linear epitopes. One of these 3 groups contain sequences that map to the amino terminus of A{beta}. DEES elevated in AD may be useful blood biomarkers for AD. The DEES clusters elevated in NC may be associated with protection against misfolded protein amyloid seeding and propagation and maintaining the resilience of neuronal populations.

neuroscience↗

bioRxiv2026

Distillation enables scalable high-fidelity virtual screening across ultra-large chemical libraries

Accurate virtual screening of ultra-large chemical libraries remains challenging. Existing approaches rely on lower-fidelity scoring functions or sampling-based strategies that can limit predictive accuracy and bias the exploration of chemical space. Here, we present FastBindRank, a distillation-based framework that transfers the predictive power of the structure-based model Boltz-2 into an efficient sequence-based surrogate. Trained on [~]1% of the 122-million-compound PubChem library, FastBindRank enables high-fidelity screening at scale. Applied to histone deacetylase 11 (HDAC11), FastBindRank substantially enriched high-confidence binders relative to the background chemical space. The lightweight model captured structural patterns associated with predicted binding, revealing structural determinants of binding. Under a comparable computational budget, FastBindRank achieved a 74-fold increase in hit rate and over a 30-fold increase in discovery yield over direct subset-based screening. Experimental validation confirmed the activity of two novel compounds. These results establish distillation as a practical strategy for scalable, high-fidelity virtual screening of ultra-large chemical libraries.

bioinformatics↗

bioRxiv2026

An engineered IdeS variant with enhanced activity and performance for IgG degradation

IgG-degrading enzymes have emerged as innovative therapeutic agents for treating conditions driven by pathogenic antibodies. Here, we used structure-guided rational design to engineer IdeSM33, a double mutant (K167R/D226E) of the IgG-specific bacterial protease IdeS from Streptococcus pyogenes, with improved catalytic efficiency. Biolayer interferometry revealed a fourfold increase in binding affinity relative to wild-type IdeS (IdeSWT). This enhancement is likely attributable to mutations that strengthen hydrogen bonding at the enzyme-IgG Fc interface. In vitro, IdeSM33 has higher performance than IdeSWT in cleaving serum IgG. In vivo studies in rabbits demonstrated that IdeSM33 effectively depleted circulating IgG and showed better performance at a dose of 0.005 mg/kg than the IdeSWT. Although doses greater than 0.2 mg/kg demonstrated higher plasma concentrations of IdeS and a larger AUClast, they did not show a significant enhancement in the pharmacodynamics of IgG degradation. Importantly, a single dose of IdeSM33 (0.2 mg/kg) potently degraded binding and neutralizing antibodies against AAV9 within 1-2 days and restored hepatic AAV9 transduction in pre-immunized animals. Together, these findings highlight IdeSM33 as a potent and safe engineered enzyme with therapeutic potential for autoimmune disorders, transplant rejection, and overcoming pre-existing humoral immunity in gene therapy.

bioengineering↗

bioRxiv2026

RBMP2 shapes specialized membranes for CO₂ delivery in the pyrenoid condensate

Approximately one-third of global CO2 fixation occurs in the algal pyrenoid, a condensate of the CO2-fixing enzyme Rubisco traversed by membranes that supply it with CO2. In the model alga Chlamydomonas reinhardtii, CO2 is delivered by a specialized central reticulated region of these membranes. Here we define how this region is built and identify RBMP2 as the first factor required for its biogenesis. Loss of RBMP2 prevents reticulated-region formation and impairs pyrenoid-dependent growth. RBMP2 domains perform separable roles in extending membrane tubules toward the pyrenoid center and remodeling them into narrow tubules of the reticulated region. The CO2-releasing carbonic anhydrase CAH3 localizes not only to the reticulated region but also to helical interfaces between tubules and minitubules, which expand in some RBMP2 truncation mutants. Our findings advance the basic understanding of pyrenoid function and establish the pyrenoid as a powerful system for studying membrane remodeling within a phase-separated condensate.

Plant Biology↗

bioRxiv2026

Bioelectric state transitions enable de novo feather bud formation in developing skin

Tissue patterning is integral to development and regeneration, yet the factors that initiate morphogenetic patterning remain to be explored. Here, using embryonic chicken skin as a model, we show that perturbation of calcium signaling induces de novo feather bud formation in regions that normally do not form feather buds. This is achieved through coordinated changes in calcium dynamics, endogenous bioelectric currents, transcriptional regulation of calcium and potassium channel genes, and morphogen signaling. Different combinations of channel perturbations altered the number, distribution, size, and shape of induced feather buds. Live calcium imaging and extracellular electrophysiological recordings revealed homeostatic regulation, in which initially depressed calcium activity is followed by elevated calcium activity. Inward bioelectric currents emerge as de novo feather buds appear. Potassium channel blockade suppressed calcium dynamics, abolished endogenous currents, and inhibited new bud formation. Canonical feather morphogenesis pathways including Shh and {beta}-catenin are induced in these new buds. Our findings support a model in which developmental bioelectricity contributes to regulating the threshold of feather bud formation. These results identify developmental bioelectricity as an unrecognized regulatory layer of tissue patterning that warrants further study. Bullet points- Calcium signaling perturbation induces de novo feather bud formation in apteric skin - Ion channel perturbations regulate the formation, distribution and shape of new buds across a continuum, depending on channel type(s) and perturbation strength. - Elevated calcium activity and inward bioelectric currents accompany feather bud induction - Developmental bioelectricity represents an unrecognized regulatory layer for morphogenesis

Developmental Biology↗

bioRxiv2026

Killer-cell dominance dichotomy governs tumor immune networks and stratifies inflamed cancers

Cancer immunotherapy benefits remain limited, even among "hot" tumors with high killer lymphocyte infiltration. Here, we investigated the population-level architecture of killer cells based on nearly 5,000 pan-cancer scRNA-seq samples, together with orthogonal validation by spectral cytometry and spatial transcriptomics. Unlike the prevailing "hot-cold" paradigm, which assumes coordinated infiltration of multiple cytotoxic lineages, we uncovered a conserved framework wherein terminal cytotoxic immunity in individuals or malignancies diverges into states dominated by either exhausted CD8+ T cells (Tex) or CD56dimCD16hi NK (NK1) cells. Despite the complexity of the tumor microenvironment, Tex-NK1 divergence governs the primary axis of tumor-intrinsic and tumor-extrinsic variance. Distinct from the conventional view that NK cells positively contribute to immunotherapy efficacy, NK1-skewed tumors, although highly cytolytic, are refractory to current immune checkpoint blockade regimens. This killer divergence defines a foundational axis of cancer immunity and provides a resource for prioritizing next-generation targets for NK-directed immunotherapy.

immunology↗

bioRxiv2026

Hearing Lips and Seeing Voices After Fifty Years: A Large-Scale McGurk Illusion Dataset for Audiovisual Speech Research

Efficient face-to-face communication relies on the integration of auditory speech and visual articulatory signals. Over the past five decades, the McGurk illusion has been widely used as an index of audiovisual speech integration. However, substantial variabilities in susceptibility to the illusion across participants and speakers limit its reliability as a stable measure of audiovisual integration ability. Here, we introduce the McGurk illusion dataset (MID), which, to our knowledge, is the largest publicly available McGurk stimulus dataset to date. The MID comprises auditory (N = 400), visual (N = 400), and audiovisual (N = 640) speech stimuli generated from 80 Mandarin speakers and validated through behavioral judgments across 360,900 trials. Using this dataset, we characterized the acoustic and facial articulatory properties of McGurk stimuli, replicated substantial inter-participant and inter-speaker variabilities in illusion susceptibility, and revealed the associations between variations in McGurk illusion rate and the variations in unisensory perception, audiovisual correspondences, and speakers characteristics. Furthermore, the stimulus set enabled systematic comparisons of the reliability of different McGurk illusion-based indices of audiovisual speech integration. Overall, the MID not only provides a standardized resource for investigating audiovisual speech integration and its alterations across populations, but also supports research on speaker normalization, lip-reading, and speech perception.

neuroscience↗

bioRxiv2026

Piezo1 transduces mechanical signals to inhibit osteoclast fusion and coordinate bone homeostasis

Osteoclasts originate from bone marrow-derived macrophages, and their maturation relies on fusion of pre-osteoclasts into mature osteoclasts that maintain bone homeostasis. Previous studies established that mechanical signals regulate osteoblast activity in bone homeostasis, although whether such signals regulate bone homeostasis by acting on osteoclasts remains unclear. Herein, membrane tension decreased during pre-osteoclast fusion, accompanied by reduced Piezo1. This suggests that mechanical stimulation inhibits fusion of monocytes into osteoclasts through Piezo1. Piezo1-knockout monocytes (CTSKCre; Piezo1fl/fl) attenuated the anabolic effect of exercise on bone mass in vivo, whereas shear stress inhibited osteoclast fusion in vitro. Piezo1 activation elevated E-cadherin, which anchors Merlin. This led to hyperactivation of the Yes-associated protein (YAP) signaling pathway, subsequently activating TAX1BP1 and suppressing NF-{kappa}B signaling as well as osteoclast differentiation and maturation. Thus, physical exercise activates a Piezo1-E-cadherin-Merlin-YAP axis that prevents osteoclast fusion, presenting a druggable mechanotransduction pathway for osteoporosis.

cell biology↗

bioRxiv2026

Systems-Scale Structural Modeling Reveals the Germline Architecture of Immunodominance

The adaptive immune system generates diverse antibodies to protect against infection, yet responses often focus on a limited number of antigenic sites, a phenomenon called immunodominance. Using the SARS-CoV-2 receptor-binding domain as a model, this study combines large-scale antibody sequencing, deep mutational scanning, and AlphaFold 3 structural modeling to investigate the basis of immunodominant epitope selection. The results show that germline-encoded antibody features are a primary driver of immunodominance. Specifically, 76% of RBD-targeting antibodies display conserved gene segment usage and/or germline-encoded HCDR3 motifs. Structural analyses identified recurrent germline-encoded residues within these regions that interact with immunodominant epitopes, and mutating these residues eliminated binding. Mutations in SARS-CoV-2 variants frequently disrupt these interactions and are associated with immune escape; other mutations enable germline-mediated recognition and generate new immunodominant epitopes. These findings indicate that innate features, rather than diverse somatic mutations, determine binding specificity for the large majority of the antibody response and underlie antibody immunodominance.

immunology↗

bioRxiv2026

Ultra-efficient High Resolution 3D Reconstruction of Spatial Omics Data with Neural Transcriptomic Field

Biological tissues are inherently three-dimensional (3D) ecosystems where spatial architecture dictates cellular function. While spatial omics technologies have revolutionized molecular profiling, they are largely restricted to isolated two-dimensional (2D) tissue sections. Existing computational methods attempting to reconstruct 3D volumes from sparse slices rely heavily on local slice-to-slice interpolation, struggling to balance high-fidelity reconstruction, noise reduction, and atlas-scale efficiency. Here, we present Neural Transcriptomic Field (NTF), a deep learning framework employing multi-resolution hash-grid encoding and implicit neural representations. Unlike interpolation-based approaches that merely bridge adjacent observations, NTF learns a global, continuous 3D representation of the tissue. By modeling the underlying latent biological patterns, NTF intrinsically decouples true molecular signals from technical artifacts, naturally enabling robust denoising and high-fidelity reconstructions. This global field paradigm shatters traditional scalability limits: NTF achieves up to a 1,000x speedup over existing methods, notably reconstructing a 100-million-cell scale 3D whole-mouse embryo atlas in under 15 minutes. Furthermore, NTF can generate super-resolved volumes from sparse input (e.g., utilizing only 10% of slices) and robustly extrapolating into unseen tissue regions. We demonstrate NTFs versatility across diverse transcriptomic and proteomic datasets, capturing complex spatiotemporal dynamics in Drosophila and mouse embryogenesis, and mapping intra-tumoral functional gradients in human breast cancer. Ultimately, NTF provides an unprecedentedly fast, scalable, and robust computational engine for constructing the next generation of comprehensive 3D tissue atlases.

bioinformatics↗

bioRxiv2026

Hierarchical spatial organization stabilizes algal-fungal living materials and enables sustained carbon fixation

Engineering stable multicellular living materials remains difficult because distinct partners require incompatible local microenvironments, while sustained cooperation depends on integration across multiple spatial scales. Here we show that hierarchical spatial organization stabilizes algal-fungal living materials and enables sustained carbon fixation. Compartmentalized seed-seedcase units create partner compatible local niches for Chlorella vulgaris and Pleurotus ostreatus, while fungal outgrowth bridges neighboring units into an integrated artificial lichen. This transition converts localized coexistence into a mechanically coherent assembly that sustains net CO2 drawdown together with O2 production in closed systems and restores carbon fixation activity after repeated CO2 replenishment. A printable formulation further enables macroscopic architecture with enhanced volumetric carbon-fixation performance. Transcriptomics reveals division of labor between algal carbon fixation and fungal redox and matrix support functions, whereas perturbation assays demonstrate functional robustness. These results establish hierarchical spatial organization as a design principle for stable cooperative living materials. TeaserProgrammable algal-fungal assemblies turn spatial design into durable carbon capture.

bioengineering↗

bioRxiv2026

De novo design of RNA pseudoknots with deep learning

RNA design has been hindered by the limited accuracy of 3D structure prediction. Here, we show that intricate RNA structures can be generated with current deep learning tools through accurate de novo design of pseudoknot secondary structures. In an Eterna competition involving 57 pseudoknots, generative AI methods matched experienced human designers in solving most blind challenges, evaluated by single-nucleotide-resolution chemical mapping, compensatory mutagenesis, and cryogenic electron microscopy. AI-generated molecules with accurate secondary structures formed well-ordered 3D folds stabilized by noncanonical tertiary interactions not modeled during design. Success was guided by an RNet foundation model trained on prior chemical mapping data, suggesting that some difficult RNA design tasks may be tractable without first solving RNA 3D structure prediction.

biophysics↗

bioRxiv2026

In situ molecular architecture of the mammalian sperm nuclear vacuole

Direct identification of macromolecular complexes in their native context remains a major barrier to unbiased biological discovery. This challenge is particularly acute in mammalian sperm nuclei, in which condensed chromatin is interspersed with poorly understood phase-separated compartments termed nuclear vacuoles. Vacuoles are associated with reduced fertilization efficiency, yet their composition remains unclear. Here we combine high-resolution in situ cryo-electron tomography (cryo-ET) with AlphaFold docking to identify vacuole components as proteasomes, the proteasome activator PA200, and ferritin. In situ structures at resolutions up to 3.8 [A] reveal distinct proteasome-PA200 associations and gating states, consistent with a stepwise activation mechanism. Ferritin assemblies exhibit heterogeneous mineralization states and directly contact chromatin. Together, these findings establish the molecular organization of sperm nuclear vacuoles and implicate protein turnover and metal homeostasis in shaping the nuclear landscape, while demonstrating the power of in situ cryo-ET to resolve protein identity and conformational dynamics in native cellular environments.

biochemistry↗

bioRxiv2026

Neuronal secretome from bipolar patient-derived neurons alters network function and contains candidate biomarkers for diagnosis and lithium response

Delayed diagnosis and treatment are a major burden to patients with bipolar disorder. While lithium is the most effective treatment against mania, depressive episodes, and suicide, only 30% of patients respond to it fully. Currently there are no reliable methods to predict lithium responsiveness. To address these challenges, we aimed to identify potential diagnostic and treatment response biomarkers for BD, in addition furthering understanding of BD pathophysiology. Here, we leveraged human induced pluripotent stem cell (hiPSC) derived neurons from lithium responsive (LR), lithium non-responsive (LNR), and healthy age-matched controls (CTL). We found extracellular vesicle (EV) cargos from hiPSC-derived neurons are indicative of disease state and treatment-response. Unbiased proteomic and miRNA profiling identified 10 proteins and 13 miRNAs that were differentially expressed in BD EVs relative to CTL, as well as distinct molecular signatures separating LR ad LNR groups. These differences converged on pathways related to synaptic function, neurotrophic signalling, and cellular stress responses. Additionally, we found the BD neuronal secretome alters activity in non-BD neuronal networks. Chronic treatment of CTL cultures with BD neuron-conditioned media modified the proportion of active neurons and the frequency and amplitude of calcium transients in individual neurons. We demonstrate that neuronal EVs contain molecular signatures of disease state and treatment response in BD and identify the BD secretome as an active regulator of neuronal network homeostasis. This study provides novel insights into the pathophysiology of BD and candidate biomarkers for personalized BD diagnosis and treatment selection.

neuroscience↗

bioRxiv2026

Pathogen-specific host responses define distinct pneumonia endotypes in the human lung

Pneumonia is the leading cause of death from infectious disease worldwide. The diagnosis and treatment of patients with pneumonia lag behind other major conditions, relying on syndromic definitions that lack molecular resolution and ignore underlying endotypes. We sought to test the hypothesis that dynamic pathogen-specific host responses in the alveolar space represent distinct pneumonia endotypes linked to different clinical features and outcomes. We prospectively enrolled a cohort of 690 patients (including immunocompromised patients) with known or suspected pneumonia receiving mechanical ventilation in whom the etiology of pneumonia was determined by gold-standard analysis of distal lung fluid obtained by bronchoalveolar lavage (BAL) combined with clinical adjudication. From these patients, we analyzed 792 BAL fluid samples, including 310 serial samples, using flow cytometry (482 patients) and single-cell RNA-sequencing (170 patients; 263 samples, complemented by 9 healthy controls and 25 post-COVID-19 patients, yielding [~]2.4 million single cells across 28 cell types), and extracted daily clinical data from the electronic health record (>15,000 patient-days). We used machine learning models to identify pathogen-specific host responses in the transcriptome of alveolar immune cells that were associated with changes in alveolar cell abundance and clinical features. Our results suggest that therapeutic strategies for pneumonia should be individualized to specific host-pathogen interactions.

immunology↗

bioRxiv2026

Machine learning cross-platform proteomic imputation enables protein quality scoring and replication of epidemiological associations

High-throughput affinity-based proteomics has advanced biomedical research, yet fundamental, persistent discordance between mainstream platforms (SomaScan and Olink) routinely undermines the replication of findings. This platform-driven non-replication complicates downstream biological validation and biomarker prioritization. Here, we develop a machine learning-based framework for cross-platform protein value imputation to resolve this translational bottleneck. Using paired proteomic data measured by both SomaScan and Olink from 5,325 participants of the Multi-Ethnic Study of Atherosclerosis, we developed models to impute cross-platform measurements and applied them to two independent and demographically distinct cohorts (Cardiovascular Health Study [N=3,171] and UK Biobank [UKB; N=41,405]) for external validation. Our bi-directional model 1) established an imputation performance-based protein fidelity index, validated against gold-standard measurements from Atherosclerosis Risk in Communities study (N=101) and Nurses Health Study (N=54), 2) enabled imputation of platform-exclusive protein measurements, and 3) facilitated calibration of overlapping proteins. We demonstrate the utility of this framework through three applications: 1) fidelity-informed analyses enhanced the replication of biomarker discovery, 2) recovery of SomaScan signals that were previously inaccessible in UKBs original Olink measurements, and 3) improved replication performance for overlapping proteins. Our study offers a translational roadmap that allows researchers to achieve reliable epidemiological replication, target specific assays for future optimization, and prioritize biological signal over platform noise.

bioinformatics↗

bioRxiv2026

PRMT7 restricts CD8+ T cells expansion via the NF-κB pathway.

New therapeutics are needed to enhance cytotoxic T lymphocyte (CTL) expansion and effector function for effective tumor control. Here, we show that T cell specific deletion of Prmt7 using CD4-Cre mice increases CD8+ effector differentiation, cytokine secretion, cytolytic activity, and anti-tumor responses. Prmt7 deficiency transcriptionally reprogrammed CD8+ T cells by activating the NF-{kappa}B pathway, boosting proliferation, and elevating effector molecules such as CD25, CD69, and IFN{gamma}. Mechanistically, PRMT7 associated with RelA and restricted its nuclear translocation. To enable therapeutic translation, we developed a PRMT7-targeting PROTAC degrader (MS54). MS54-treated CTLs exhibited NF-{kappa}B pathway activation similar to Prmt7-deficient CTLs. Adoptive transfer of MS54-treated OT-I CTLs significantly improved tumor control in a syngeneic melanoma model. In human CTLs, MS54 enhanced proliferation, activation markers (CD69, CD137), IFN{gamma} production, and cytotoxicity toward melanoma. Together, these findings identify PRMT7 as a negative regulator of CD8+ T cell immunity and highlight MS54 as a promising strategy to improve adoptive T cell therapy.

molecular biology↗

bioRxiv2026

Extending the MARTINI 3 Coarse-Grained Forcefield to Polypeptoids

Polypeptoids (poly-N-substituted glycines) are synthetic peptidomimetic polymers with their sidechains attached to the backbone amide nitrogen rather than the -carbon in natural peptides. Peptoids display pronounced sequence-dependent conformational flexibility arising from the absence of backbone hydrogen bonding and slow cis/trans {omega}-dihedral isomerization. Despite growing interest in peptoid-based biomaterials, a coarse-grained (CG) model compatible with the modern MARTINI 3 framework is not yet available, limiting mesoscale simulation of peptoid structure and self-assembly. In this work, we develop the first MARTINI 3 compatible peptoid CG forcefield, covering 19 commonly used residue types. Extensive all-atom reference simulations employing parallel bias metadynamics (PBMetaD) were performed to ensure converged sampling of {omega}-dihedral transitions. Bonded parameters were derived from atomistic distribution functions via direct Boltzmann inversion (DBI), while nonbonded interactions were primarily adopted from the standard MARTINI 3 parameter library. The resulting CG model reproduces structural and thermodynamic properties in close agreement with all-atom simulations, while providing up to 57-fold enhanced computational efficiency. To facilitate its adoption by the research community, we have integrated all parameters and workflows to the MARTINI-based martinize2 tool, enabling automated generation of MARTINI 3 peptoid structures and topologies. This work establishes a transferable and computational efficient framework for simulating large-scale peptoid confirmations, assemblies, membrane interactions, and nanostructure formation, and supports the rational design of next-generation sequence-specific functional peptoid-based materials.

biophysics↗