Biology subjects

Cao, S.

Publications and source records attributed to Cao, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Targeting the Kidneys Osmotic Gradient with AVPR2 Antagonism Limits Inflammation and Fibrosis after Injury

Background: The renal medulla is characterized by a steep osmotic gradient that is essential for urinary concentration but may also influence cellular stress and injury responses. While vasopressin-dependent medullary hyperosmolarity is well established in water homeostasis, its role in shaping kidney injury and repair remains poorly understood. Methods: We pharmacologically reduced vasopressin signaling using the Avpr2 antagonist Tolvaptan and examined the consequences for renal medullary osmolality, tubular stress responses, inflammation, and fibrotic remodeling. Single-nucleus RNA sequencing, bulk transcriptomics, quantitative PCR, and histological analyses were performed in healthy kidneys and following unilateral ischemia-reperfusion injury (IRI) or cisplatin-induced nephropathy. Results: Tolvaptan treatment lowered renal medullary osmolality and suppressed osmotic stress-associated transcriptional programs in medullary collecting duct cells. Following IRI, Tolvaptan-treated mice exhibited attenuated expression of inflammatory and monocyte recruitment genes, reduced macrophage accumulation in the renal medulla, and diminished fibrotic remodeling at later stages. In cisplatin-induced nephropathy, Tolvaptan reduced tubular injury markers and inflammatory activation in the outer stripe of the outer medulla. Conclusions: These findings identify vasopressin-dependent renal medullary hyperosmolarity as a modulator of tubular stress, inflammation, and fibrotic remodeling after kidney injury. Modulation of the medullary osmotic environment influences early injury trajectories and downstream repair responses across distinct models of acute kidney injury.

pathology↗

bioRxiv2026

Cowpea Chlorotic Mottle Virus virus-like particles as DNA or RNA delivery vehicle to fish cells

Cowpea Chlorotic Mottle Virus (CCMV) is an icosahedral plant virus composed of 180 monomeric units of the capsid protein. Virions encapsulate the viral RNA genome, which can be removed from the virion by changing pH conditions, after which the capsid proteins can be reversibly assembled to form empty CCMV virus-like particles (VLPs), or VLPs that have encapsulated either heterologous DNA or RNA. Earlier research has shown that CCMV VLPs are suitable as delivery vehicles for heterologous DNA/RNA molecules into mammalian cells, leading to subsequent expression of their encoded genes. In this study, we evaluated the potential of CCMV VLPs to encapsulate nucleic acids and transfer them to fish cells in vitro, and to zebrafish larvae and juveniles in vivo. VLPs containing pVax-GFP plasmid (3690 bp) were stable for up to 5 weeks in buffer at pH 7.2 and pH 5, whereas VLPs containing GFP-mRNA (1168 nt) were stable for up to 3 weeks, but only when stored in a buffer at pH 4.5. When administered directly to the culture medium, VLPs were readily taken up by fish as well as mammalian cell lines but could not unpack and transfer nucleic acids to the cells. VLPs delivered by transfection however, could transfer nucleic acids to the cells, leading to reporter gene expression. When VLPs were administered directly to the culture medium along with the cell-penetrating peptide dfTAT, only VLPs containing pVax-GFP in pH 7.2 buffer were able to transfer DNA to mammalian but not fish cells. In vivo however, upon intramuscular injection, the same VLPs were able to transfer plasmid DNA to myocytes of zebrafish larvae and juveniles as efficiently as when injecting naked plasmid DNA. Altogether, these findings provide the foundation for future studies on the use of CCMV VLPs as delivery vehicles for DNA or RNA to fish cells.

molecular biology↗

bioRxiv2026

Indole-3-propionic acid nano-prodrugs sustain increased lymphoid exposure and alleviate experimental autoimmune arthritis

Chronic inflammatory diseases, including rheumatoid arthritis (RA), currently require sustained control of inflammation. Although long-acting therapies can reduce dosing frequency, those that rely on systemic immunosuppression may still compromise protective immunity. Microbiota-derived metabolites offer a complementary starting point for immune modulation through naturally occurring host-microbe signals. Indole-3-propionic acid (IPA), a gut microbial tryptophan metabolite naturally present in human circulation, has newly recognized immunoregulatory activity, yet its effects across disease contexts and its potential for therapeutic use remain incompletely defined. Here, we developed polymeric IPA nano-prodrugs (pIPANP) by conjugating IPA to a methacrylamide polymer through ester linkages and formulating the polymer into injectable nanoparticles. Following subcutaneous administration of fluorescently-labeled pIPANP, injection-site fluorescence remained detectable for at least 35 days, with labeled material detected in multiple lymph nodes. LC-MS/MS confirmed higher lymph-node IPA concentrations in mice treated with the pIPANPs compared to free IPA control at every sampled time point over 14 days. In collagen antibody-induced arthritis (CAIA), pIPANPs reduced clinical disease severity and paw swelling under both prophylaxis and therapeutic administration. pIPANP treatment increased the relative representation of CD11cCD103CD11b- cells with a conventional dendritic cell (cDC)1-associated phenotype and reduced costimulatory-marker frequencies in both CD11cCD103 and CD11cCD11b populations, most prominently in hock-draining lymph nodes. These changes were accompanied by increased PD-1 and IFN-{gamma} frequencies among CD4 and CD8 T cells. Fluorescent nanoparticle tracking showed preferential association with several myeloid populations, while single-cell profiling revealed divergent interferon-response signatures across splenic populations. These findings reveal arthritis-associated immunomodulatory activity of polymeric IPA and support its further development as a microbiome-inspired, long-acting approach to inflammatory arthritis.

bioengineering↗

bioRxiv2026

Venetoclax Resistance Creates Canonical Pyroptosis Vulnerability in AML

Venetoclax has transformed acute myeloid leukemia (AML) therapy, yet resistance is almost inevitable. Its diverse, often difficult-to-target drivers frequently converge on monocytic differentiation, a state that survives on MCL1 rather than BCL2. Here, we show that the very cells that escape BCL2 inhibition retain the canonical pyroptosis machinery of normal monocytes. Across 15 bulk and 4 single-cell cohorts, the canonical pyroptosis program was enriched in monocytic AML and monocytic leukemia stem cells, correlated with venetoclax resistance, and associated with inferior survival specifically after venetoclax-based therapy. In 24 cell lines and 142 patient specimens, both DPP8/9 inhibition by Val-boroPro and NLRP3 activation by lipopolysaccharide (LPS) plus nigericin preferentially killed monocytic AML cells through GSDMD-mediated pyroptosis, largely sparing non-monocytic AML and lymphoid leukemias. Venetoclax preferentially depleted primitive AML blasts but enriched a monocytic residuum vulnerable to canonical pyroptosis; combining venetoclax with Val-boroPro achieved deeper ex vivo clearance than either agent alone. In venetoclax-resistant xenografts, Val-boroPro suppressed leukemia progression, and adding venetoclax further reduced leukemia burden and prolonged survival beyond either monotherapy. Thus, venetoclax resistance itself exposes an alternative, druggable cell-death program that can be therapeutically exploited to overcome this resistance.

cancer biology↗

bioRxiv2026

A kinetic-aware approach to infer metabolic variations and flux using transcriptomics and metabolomics data

Assessing metabolic variations and flux quantities enable systematic understandings of metabolic shifts, reprogramming, adaptation and interactions in human diseases. However, omics-based estimation of metabolic flux and its variation remains challenging due to several fundamental limitations: the need for disease and tissue context specific metabolic model; nonlinear enzyme kinetic model that links enzyme and substrate changes to reaction flux; partial, unpaired, and snap-shot measurements across omics modalities; and uncertainty in computational prediction. Here, we present Michaelis-Menten model-based Flux Estimation Analysis (mmFEA), a Monte Carlo framework for estimating condition-specific flux changes by integrating paired or unpaired metabolomics and transcriptomics (or proteomics) data. mmFEA separates each reaction-rate change into enzyme- and substrate-associated components and assess reaction rate using Michaelis-Menten kinetics equation. A baseline metabolite saturation rate is introduced by integrating protein language model predicted kinetic parameters and human baseline level metabolic concentration to enable kinetic-aware integration of unpaired substrate and enzyme level measurements. Distribution of metabolic flux and variations between conditions are further computed using MCMC sampling by treating Michaelis-Menten-derived marginal flux distribution as prior and coherency in flux balance as likelihood. To benchmark mmFEA, we generated an in-house multi-omics data set including transcriptomics, metabolomics, metabolic activity functional assay, and CRISPR screening data using pancreatic cancer cell line system treated by APEX1 inhibitors. We demonstrated that mmFEA could accurately capture experimentally observed metabolic changes and achieved a better performance than all baseline methods. Our analysis revealed the necessity in using both substrate and enzyme modality and kinetic aware model in metabolic flux assessment. Further analysis using independent pancreatic cancer cohorts further validated the robustness of mmFEA, supporting integration of condition-linked unpaired data. Pan-cancer and spatial multi-omic applications demonstrated the use of mmFEA for resolving context-dependent metabolic variation when direct flux measurements are unavailable. Together, mmFEA provides a mechanistically grounded framework for estimating relative metabolic flux changes and their uncertainty from heterogeneous omics data.

systems biology↗

bioRxiv2026

Monothiol glutaredoxin DaGrxB couples iron homeostasis with redox balance to orchestrate development and virulence in the peach shoot blight fungus Diaporthe amygdali

Peach shoot blight (PSB), caused by Diaporthe amygdali, is one of the most devastating fungal diseases affecting peach production worldwide. Glutaredoxins (Grxs) are ubiquitous redox-regulatory proteins involved in antioxidant defense and iron metabolism, yet their functions in phytopathogenic fungi remain largely unknown. Here, we identified four Grxs (DaGrxA-DaGrxD) in D. amygdali. Among them, DaGrxB, a monothiol glutaredoxin, is the sole member essential for vegetative growth, asexual reproduction and virulence. DaGrxB interacts with iron-regulatory transcription factors DaHapX and DaSreA and modulates their activities via iron-dependent nucleocytoplasmic shuttling, coordinating iron acquisition and storage gene expression. During infection, D. amygdali encounters a biphasic iron environment: an inherently iron-limited host environment at early stages (1-2 dpi) followed by host-mediated iron excess (3-4 dpi), and DaGrxB is essential for navigating this transition. Consistently, deletion of either DaHAPX or DaSREA significantly reduced virulence, confirming that iron homeostasis is a critical determinant of D. amygdali virulence. Notably, deletion of DaGRXB disrupts Fe-S cluster biosynthesis, causing mitochondrial Fe2+ accumulation, impaired aconitase activity, and reduced ATP production, which triggers constitutive activation of the GSH-dependent antioxidant system, with elevated GSH/GSSG ratios, increased GR and GST activities, and reduced H2O2 levels. Exogenous GSH and H2O2 depletion both reduced virulence, suggesting that disturbed redox balance directly contributes to attenuated virulence. Additionally, the Trx domain assists the Grx domain in nucleocytoplasmic translocation through intramolecular interactions. Finally, LDH-delivered dsRNA targeting DaGRXB effectively controls PSB. Collectively, these findings reveal how a monothiol glutaredoxin integrates iron homeostasis, redox balance and virulence in a plant pathogen, providing a foundation for RNAi-based disease management.

pathology↗

bioRxiv2026

Spaghettification: How extreme replichore imbalance impacts bacterial replication and morphology

Bacterial chromosomes are typically organized into two similarly sized replichores to synchronize bidirectional replication and fusion within a Tus/ter-defined termination zone. Previous studies have suggested that replichore balance in both Salmonella and E. coli is maintained by selection for efficient and properly coordinated replication termination and chromosome segregation. However, there is a lack of understanding of the causal relationship between replichore asymmetry, cellular fitness, and replication-fork convergence, as well as how the termination machinery behaves when the two replichores differ substantially in length. Here we dissect the impact of replichore asymmetry by engineering 41 isogenic Salmonella inversion mutants spanning progressive imbalances, complemented by duplication-based asymmetries. Our constructed strains show that even cells with severely imbalanced chromosomes, where one replichore is 11-fold longer in size than the other (0.38 Mb vs. 4.48 Mb) are viable. However, relative fitness declined linearly with replichore size difference at approximately -0.17 per Mb. Additionally, highly imbalanced strains exhibited substantial division defects with severe cell elongation and lysis. Replication profiling showed that, even under extreme replichore asymmetry, forks consistently converge at the innermost ter sites of the shorter replichore and that two sequential Tus/ter barriers were sufficient for complete replication fork arrest. Together, these results establish a quantitative rule linking replichore asymmetry to fitness, define the termination position under imbalance, and reveal a dual Tus/ter barrier that safeguards termination when one replichore reaches the terminus region ahead of the other. Collectively these results connect chromosome architecture to replication mechanics and cell-division outcomes.

microbiology↗

bioRxiv2026

DiffGSP: reversing mRNA diffusion to unlock high-fidelity spatial transcriptomics

Spatial transcriptomics enables gene expression profiling within intact tissues while preserving spatial context, providing unprecedented insights into cellular organization and function. However, mRNA diffusion during tissue processing can cause transcripts originating from adjacent cells to be captured at a given spot. This spatial misalignment challenges a fundamental premise of spatial transcriptomics that measured gene expression faithfully corresponds to its spatial origin, thereby compromising spatial fidelity and potentially biasing biological interpretation. Here, we present DiffGSP, a physics-informed framework that integrates Fick's law with graph signal processing to explicitly model diffusion-induced distortions and recover the underlying spatial gene expression landscape. Comprehensive benchmarking across diverse datasets and evaluation metrics demonstrates the consistent ability of DiffGSP to restore spatial gene expression patterns. By computationally reversing diffusion-induced distortions, DiffGSP enables the discovery of fine anatomical structures in the mouse brain, spatially organized gene modules in the kidney, intratumoral heterogeneity in colorectal cancer, and tertiary lymphoid structures in lung adenocarcinoma. Built on a physically interpretable framework and broadly applicable to sequencing-based spatial transcriptomics technologies, DiffGSP improves the fidelity of spatial gene expression reconstruction and enables more reliable biological interpretation.

bioinformatics↗

bioRxiv2026

FusedFCR: A Fused Forward Continuation-Ratio model for marker selection along cell-fate trajectories

Time-course single-cell RNA sequencing (scRNA-seq) data collected across ordered stages provide population-level snapshots of differentiation, disease progression, and aging. Supervised pseudotime methods use observed stage labels to reconstruct continuous progression but generally do not identify marker genes associated with changes from one stage to the next. Unsupervised pseudotime-based marker selection methods infer latent trajectories directly from expression data and identify trajectory-associated genes, but do not explicitly link these associations to the observed stages. We propose FusedFCR, a regularized forward continuation-ratio model that represents cellular progression through a sequence of conditional transitions across ordered stages. FusedFCR combines a lasso penalty for gene selection with a fusion penalty that encourages similar effects across adjacent transitions while allowing transient and direction-changing associations. The resulting transition-specific coefficients support interpretable gene selection and a continuous pseudotime-like projection anchored to the observed developmental stages. In simulations, FusedFCR accurately recovers gene-effect trajectories and improved predictive performance relative to alternative methods. Applied to one mouse and three human datasets (mouse pancreatic beta-cells, human extravillous trophoblast, human induced pluripotent stem cell derived astrocytes, and human endometrial cells during the secretory phase), FusedFCR identifies biologically interpretable genes associated with distinct developmental transitions. Gene set enrichment analysis further reveals stage-specific pathway activity consistent with known developmental biology, while held-out stage-classification accuracy was competitive or superior across both datasets. Together, these results show that FusedFCR complements pseudotemporal ordering by identifying which molecular programs change and when those changes emerge along the developmental trajectory. An accompanying R package is available on GitHub.

bioinformatics↗

bioRxiv2026

A fast 2C-induction method reveals a barrier role of SP2 for totipotency

The acquisition of totipotency in vitro remains a major challenge, limiting our understanding of early embryogenesis and its clinical and translational applications. Here, we reported a robust and rapid chemical reprogramming system that converts mouse embryonic stem cells (mESCs) into totipotent-like cells (TLCs) within 36 hours, with efficiencies exceeding 70%. The induced cells exhibit transcriptomic, epigenomic, and functional features closely resembling 2-cell (2C) stage embryos, as confirmed by scRNA-seq, ATAC-seq, and chimeric embryo analyses. Single-cell trajectory construction revealed a branching reprogramming process that yields both successful totipotent-like and alternative, non-reprogrammed fates. Mechanistically, we identified the transcription factor SP2 as a barrier to totipotency acquisition, promoting lineage-specific gene expression while repressing totipotency networks. Collectively, our study has established a highly efficient in vitro model for totipotency induction and highlighted molecular barriers shaping cell fate decisions, providing a platform to dissect the mechanisms governing the pluripotency-to-totipotency transition.

developmental biology↗

bioRxiv2026

The Vertebrate Genomes Project Phase I: A global reference genome resource

The Vertebrate Genomes Project (VGP) aims to produce complete and near-error-free reference genomes for all [~]70,000 extant vertebrate species1. Organized in four phases, it progressively targets all vertebrate orders, families, genera, and eventually all species. Here we present the completion of VGP Phase I, delivering reference genomes for [~]95% of vertebrate orders, along with additional lineages within those orders, totaling 816 species and 1.6 trillion base pairs of main haplotype sequence. These genomes were assembled and annotated over an 8-year period (2018-2026) of rapid advances in genome sequencing, assembly, and annotation methods2-4, alongside the growth of associated consortium initiatives and international collaborations5-9. They represent some of the highest-quality vertebrate genomes currently available, and most have become the primary reference for their respective species in public databases. Comparative analyses across a subset of 579 species when we reached a threshold of 85% of orders allowed us to reconstruct the genome of the last common ancestor of all vertebrates 500 million years ago, identify diverse modes of sex chromosome evolution, reveal clade-specific three-dimensional genome architecture, discover methylated epigenetic landscapes across vertebrates, and provide a framework for studying gene and pseudogene evolution, immune loci, cancer-associated genes, and other trait-associated loci. Approximately a quarter of this subset are listed as Vulnerable to Critically Endangered by the IUCN Red List of Threatened Species, and have enabled more advanced genomic investigations of extinction risk. VGP Phase I delivers a reference backbone for vertebrate genomics, enabling discoveries that would otherwise remain out of reach across evolution, conservation, and medicine. Talking pointsO_LIThe flagship paper of VGP Phase I C_LIO_LIThe highest quality collection of genomes within the eukaryotic domain of life C_LIO_LIEvolution of genome sequencing technology quality throughout VGP Phase I C_LIO_LIA driver project that has been a model for multiple large-scale, high-quality reference genome projects C_LIO_LIReleases all currently unpublished genomes in Phase I from scientific study embargoes C_LIO_LIMultiple biological discoveries across the vertebrate tree of life C_LI

genomics↗

bioRxiv2026

Novel mouse models for perianal fistulizing Crohns disease reveal therapeutic value of interferon-gamma antagonists

Background and AimsPerianal fistulizing Crohns disease (PFCD) is a challenging complication with poorly understood pathogenesis and limited treatment options, largely due to the lack of clinically relevant animal models. Interferon-gamma (IFN-{gamma}) signaling is hyperactivated in human PFCD. We aimed to establish mouse models recapitulating human PFCD and to evaluate IFN-{gamma} as a new therapeutic target. MethodsPerianal fistulas were established in three mouse models with concurrent Crohns disease-like intestinal inflammation: wild-type (WT) mice with 2,4,6-trinitrobenzenesulfonic acid (TNBS)-induced proctocolitis, Il10-/-mice, and TNF{Delta}69AU/+ mice. A modified MAGNIFI-CD index was developed for longitudinal fistula assessment in mice. Transcriptomic analysis and flow cytometry were conducted on mouse fistula tissue. Re-analysis of single-cell and spatial transcriptomics of human PFCD tissues was performed. Therapeutic benefits of anti-TNF-, upadacitinib, and IFN-{gamma} pathway antagonists were evaluated in the PFCD models. ResultsAll three PFCD models sustained chronic perianal fistula tracts for at least 5 weeks after wire removal. All three models closely recapitulate the pathological and molecular features of PFCD in patients, as confirmed by clinical examination, MRI, histopathology, immunostaining, flow cytometry, and transcriptomics. IFN-{gamma} signaling emerged as a central and conserved pathway across all three mouse models and human PFCD. Targeting of the IFN-{gamma} pathway promptly improved fistula healing with mitigation of IFN-{gamma} signaling, inflammation, and epithelial-to-mesenchymal transition (EMT). Moreover, combining IFN-{gamma} and TNF- blockade demonstrated augmented therapeutic efficacy compared to anti-TNF- monotherapy. ConclusionsThese PFCD mouse models and imaging tools provide first reliable and clinically relevant platforms for mechanistic studies and therapeutic evaluation. IFN-{gamma} signaling represents a potential therapeutic target warranting clinical investigation.

immunology↗

bioRxiv2026

Single-cell spatial transcriptomics and snRNA-seq decoding the organizational principles of functional modules in the mouse amygdala

The amygdala is a functionally heterogeneous nuclear complex comprising multiple subnuclei that orchestrate diverse behaviors, making it essential for survival and reproduction. However, the precise neural mechanisms underlying these heterogeneous functions remain elusive, primarily due to limited knowledge of the amygdalas cellular heterogeneity, developmental origins, spatial organization, and gene expression profiles. Here, we integrate single-cell-resolution spatial transcriptomics with precise anatomical dissection and single-nucleus RNA sequencing to systematically map the subnuclear enrichment patterns of amygdalar cell types. We further demonstrate that developmental origin determines subnuclear positioning and propose a novel functional modular architecture based on cellular composition and gene expression signatures. Furthermore, we reveal that the central amygdala (CEA) exhibits developmental heterogeneity, with Isl1+ neurons in its medial subdivision (CEAm) predominantly originating from hypothalamic progenitors. Our findings establish a spatially resolved cellular and molecular framework for investigating amygdalar functions at cellular type resolution and understanding amygdala-related neuropsychiatric disorders.

neuroscience↗

bioRxiv2026

Wheat MYB transcription factor TaMYB83-7B regulates seed dormancy by influencing the balance between abscisic acid and gibberellin

In wheat, weak seed dormancy (SD) is related to an increased tendency for pre-harvest sprouting (PHS), which reduces yield and quality. However, the molecular mechanism underlying SD remains elusive. Here, we identified a wheat R2R3-MYB transcription factor (TaMYB83-7B) related to SD. Expression analysis showed that TaMYB83-7B was highly expressed in wheat seeds, and was more highly expressed in strong-dormancy varieties than in weak-dormancy varieties. Sequence and association analysis indicated that T/C mutations at -907 bp and -1133 bp in the TaMYB83-7B promoter were significantly associated with wheat SD, with C at both sites related to strong dormancy. Dual-luciferase reporter assays demonstrated that the transcriptional activity of the TaMYB83-7B promoter was significantly higher in strong-dormancy varieties than in weak-dormancy varieties. Further analyses indicated that TaMYB83-7B functions as a transcriptional inhibitor. Germination experiments revealed that overexpression of TaMYB83-7B significantly enhanced SD, while its loss-of-function reduced SD. Finally, TaMYB83-7B was found to regulate SD by influencing the balance between abscisic acid (ABA) and gibberellin (GA) in wheat seeds. Overall, the results of this study enhance our understanding of the complex regulatory mechanism underlying SD, and provide gene targets and molecular markers for the genetic improvement of PHS resistance in wheat.

molecular biology↗

bioRxiv2026

Targeting Protease-activated Receptor 4 (PAR4) Protects Against Acute Kidney Injury (AKI) in Ischemia Reperfusion Injury

Acute kidney injury (AKI) is a serious and common clinical syndrome that currently has no effective treatment. Emerging evidence links coagulation pathways to kidney injury, particularly through coagulation proteases. Protease-activated receptors (PARs) are a family of G-protein coupled receptors (GPCRs) that are activated by proteolytic cleavage of their N termini, exposing a tethered ligand that initiates receptor signaling. PARs have been shown to play a major role in inflammation, vascular regulation, and tissue injury. PARs play key roles in inflammation, vascular regulation, and tissue injury. Previous work from the Hamm laboratory demonstrated that PAR4 contributes to AKI progression, as PAR4 knockout mice were protected in both unilateral ureteral obstruction and ischemia-reperfusion-based models of kidney disease. In this study, we investigated the potential of a PAR4 antagonist, VU6073819, at mitigating AKI progression in an ischemia-reperfusion injury (IRI) mouse model. PAR4 antagonism not only alleviated kidney injury and inflammatory response, but it significantly improved the survival. These findings identify PAR4 as a promising therapeutic target for AKI.

pharmacology and toxicology↗

bioRxiv2026

GYDE: A collaborative drug discovery platform for AI-powered protein design and engineering

As computational tools and machine learning models for protein sciences continue to advance and proliferate, bench scientists face increasing technical challenges adopting these tools for specific applications such as drug discovery. Here we present GYDE (Guide Your Design and Engineering), an open-source, versatile, and web-based collaboration platform designed to make computational analyses of proteins and antibodies easily accessible to bench scientists. GYDE enables the exploration of sequence-structure-function relationships through a tightly integrated visual interface, offering researchers a comprehensive exploration of protein functional determinants either via real assay data or computational tools. GYDEs intuitive interface facilitates seamless access to cutting-edge AI models for protein and antibody structure prediction, design, and downstream analyses. The flexible and easy addition of new tools and models is facilitated by the use of the Slivka compute API. The platform supports saved sessions that enable researchers to easily share their findings with other users, fostering a more collaborative scientific community. GYDE is freely available for protein scientists in academia and industry to build drug discovery analytics platforms customized to their needs.

bioinformatics↗

bioRxiv2026

UBE3C retrofits the proteasome to enforce degradation of ultra-stable folds

Neurodegeneration and proteinopathies arise from mutated or misfolded proteins that form ultra-stable, proteotoxic aggregates that evade proteasomal degradation despite ubiquitylation1-8. These conditions are exacerbated by the deubiquitylase USP14 that can prematurely rescue substrates9-11. To counter these obstacles to effective proteolysis, eukaryotes evolved the highly conserved HECT-type E3 ligase UBE3C--dysregulated in neurodegeneration12,13 and overexpressed in cancers14-17--to reprogram the 26S proteasome toward heightened activity via unknown mechanisms18-25. Here we visualized functional dynamics of the human UBE3C-retrofitted proteasome enforcing degradation of a re-engineered superfolder GFP that normally escapes proteolysis, using time-resolved cryo-electron microscopy. A continuum of non-equilibrium conformations, comprising fourteen proteasome conformers orthogonally combined with four UBE3C states or three USP14 states, reveals a cryptic UBE3C-receptor site in the proteasomal lid and captures key intermediates of ubiquitin-chain elongation and branching at four linkage-specific ubiquitin-binding sites. Remarkably, UBE3C creates an extreme shortcut for ubiquitin shuttling that bypasses USP14, promotes USP14 recycling and allosterically strengthens substrate-unfolding forces of the AAA-ATPase unfoldase to ultimately surmount the unfolding energy barrier of ultra-stable proteins. These findings define the complete functional cycle of the UBE3C-reprogrammed proteasome, illuminating how UBE3C simultaneously controls USP14 and the proteasome to enforce clearance of ultra-stable folds, and establish crucial mechanistic foundations for proteolysis-targeting therapeutic discovery.

biochemistry↗

bioRxiv2026

Geometric-aware and interpretable deep learning for single-cell batch correction via explicit disentanglement and optimal transport

Single-cell RNA sequencing enables high-resolution characterization of cellular heterogeneity, yet integrating datasets from diverse sources remains challenging due to batch effects. Current methods rely on implicit feature disentanglement and and lack geometric constraints, often result in under-correction, over-correction, or compromised biological fidelity. Here, we present iDLC, an interpretable deep learning framework that performs dual-level correction through explicit feature disentanglement and optimal transport-regularized adversarial alignment. iDLC separates biological and technical components within a structured latent space, then leverages high-confidence mutual nearest neighbor pairs to guide geometrically constrained distribution alignment. Systematic evaluation across pancreatic cancer datasets with varying batch effect intensities, multi-source human immune cells, and large-scale cross-species atlases demonstrates that iDLC robustly eliminates complex batch effects while preserving fine-grained cell subtypes, continuous developmental trajectories, and rare populations. The framework scales efficiently to datasets exceeding one million cells and consistently outperforms existing methods in both batch correction and biological conservation metrics. iDLC provides a principled and reliable tool for constructing unified single-cell reference atlases across diverse experimental conditions and biological systems.

bioinformatics↗