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Xu, J.

Publications and source records attributed to Xu, J..

At least 73 records · Page 4Linked to original sources

ComplexDesign: sequence-hallucination design of protein binders bridging multiple proteins

MotivationDesigning multichain protein complexes requires coordinating the folding of component proteins with the formation of their interfaces. The existing methods, however, remain limited in their ability to satisfy these requirements simultaneously, especially for trimeric and tetrameric complexes. As an important practical scenario, designing a binder that bridges two target proteins into a ternary complex requires flexibility in the relative arrangement of the two targets, adding an additional challenge to existing design methods. ResultsWe present ComplexDesign, a hallucination-based approach for multichain protein design. ComplexDesign performs structure-prediction-guided sequence optimization to simultaneously fold each protein chain and form inter-chain interactions that bind them together. To provide the flexibility required to appropriately arrange these target proteins, ComplexDesign introduces a specialized masking mechanism that enables exploration of possible relative arrangements rather than being limited to the predefined ones. Across a comprehensive set of benchmarks with various chain lengths, ComplexDesign outperformed existing methods in the unconditional design of dimers, trimers, and tetramers, achieving a high design success rate exceeding 50%, supporting its capability for multichain complex design. Furthermore, in the case of multi-target binder design, ComplexDesign produced high-confidence, self-consistent ternary complexes for 8 out of 10 target pairs. These results establish ComplexDesign as an effective tool for multichain protein design, with particular utility for designing binders that bridge two target proteins. Availability and implementationThe source code of ComplexDesign will be made publicly available upon publication.

bioinformatics↗

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↗

Structure of the mammalian ciliary transition zone microtubule doublet

The ciliary transition zone gates bidirectional protein trafficking to maintain the specialized ciliary proteome using microtubule doublets as a scaffold. While ciliary axonemal doublets are well-characterized, the molecular architecture of the transition zone doublet remains elusive. Here, we report the structure of the mammalian transition zone doublet from bovine tracheal cilia using cryo-electron tomography at 4.7-5.0 [A] resolution. The transition zone doublet is a structurally independent segment defined by an 8 nm-periodic arrangement of unique microtubule-inner proteins (MIPs) and microtubule-associated proteins (MAPs). We identify the calcium-binding protein CAPSL as a lumenal MIP that forms a pseudo-helical spiral and stabilizes microtubules in vitro. Furthermore, a dense MAP network on the A-microtubule surface clashes with intraflagellar transport (IFT) motor binding sites, suggesting anterograde IFT is directed to the B-microtubule for potential regulation by MAP9. Our work provides a structural framework for understanding gated ciliary transport and transition zone-linked human ciliopathies.

Cell Biology↗

TetraFuse: A Synergistic Four-Dimensional Dynamic Fusion Framework for Efficient and Robust Medical Image Classification

Accurate and robust classification of medical pathology images is pivotal for computer-aided diagnosis. However, the deployment of deep learning models in high-throughput clinical screening faces a fundamental challenge: the trade-off between diagnostic accuracy and computational efficiency. Current lightweight architectures, while reducing parameter complexity through grouped convolutions, often lead to cross-channel information isolation and diminished representational capacity. In this paper, we propose TetraFuse, a novel framework that systematically integrates features from four complementary domains: space, channel, statistics, and frequency. TetraFuse introduces a novel Cross-Channel Dynamic Aggregation (CCDA) paradigm that reconstructs global channel topology with negligible computational overhead, resolving the inter-group isolation issue. To balance perceptual fidelity and efficiency, we design a stage-aware local enhancement mechanism: Local Variance-Guided Enhancer (LVGE) is employed to filter out shallow-stage background noise, while High-Frequency Boundary Injection (HFBI) reinforces deep-stage pathological contours, preventing spatial over-smoothing. Experimental results on the COVID-19, ISIC 2018, and Kvasir datasets confirm that TetraFuse outperforms state-of-the-art (SOTA) methods. Notably, TetraFuse-Tiny achieves a transformative 91.53% reduction in FLOPs compared to ResNet50; on the Kvasir dataset, it achieved an accuracy of 0.926 and an AUC of 0.994 with only 0.345G FLOPs. By combining high representational power with minimal computational demand, TetraFuse offers a scalable solution for large-scale medical image analysis, especially in resource-constrained clinical environments.

bioinformatics↗

Spatiotemporal Cascade of AP1/CCA1-TOC1 Module Gates Stem Development

Stem development is crucial in plant vertical architecture and overall crop improvement. The molecular mechanisms underlying the initiation and circadian growth of stem remain still enigmatic. Here, we demonstrate that APETALA1 (AP1) spatially initiates circadian stem growth through a noncell-autonomous role of TIMING OF CAB EXPRESSION1 (TOC1) emanating from the floral meristem to inflorescence meristem in Arabidopsis thaliana. Mechanistically, AP1 interacts with and recruits CIRCADIAN CLOCK-ASSOCIATED1 (CCA1) to associate TOC1. Dynamic formation of the AP1-CCA1 complex is crucial for maintaining the circadian rhythmicity and expression of TOC1. Tissue-specific expression of TOC1 in floral meristems rescues the developmental defects of toc1 mutants at both functional and transcriptional levels. Furthermore, TOC1 directly activates the circadian expression of pectin methylesterase gene family, which is critical for its role in stem development. AP1 homologs regulate circadian stem elongation and plant height in wheat and rice, underscoring the conserved mechanism across flowering plants. Our findings uncovered a spatiotemporal regulatory cascade gating stem development and identified candidate genes for crop improvement.

plant biology↗

(2R,6R)-Hydroxynorketamine elicits rapid antidepressant effects by promoting astrocytic μ-δ opioid receptor heterodimerization

Ketamine produces rapid antidepressant effects but is constrained by psychotomimetic properties and abuse potential. The ketamine metabolite (2R,6R)-hydroxynorketamine (HNK) shows antidepressant-like efficacy without N-methyl-D-aspartate receptor (NMDAR) blockade, yet its upstream targets remain unclear. Here we show that HNK potentiates hippocampal excitatory transmission and reverses stress-induced behavioural deficits through opioid receptor signaling. Pharmacological and genetic analyses reveal a requirement for both {micro}- and {delta}-opioid receptors in astrocytes. Chronic stress reduces {micro}-{delta} receptor heterodimers in the hippocampus, and a single dose of HNK restores their abundance. PAINT-MINFLUX nanoscopy quantifies increased {micro}-{delta} heterodimerization, and molecular dynamics simulations indicate selective binding of HNK to the {micro}-receptor protomer via Asp147 and Tyr148. Mutating these residues abolishes HNK-driven heterodimer formation, downstream signaling and rapid antidepressant-like effects in vivo. Astrocytic {micro}-{delta} opioid receptor heterodimers thus represent a targetable mechanism for next-generation rapid-acting antidepressants.

neuroscience↗

Integrating Histology with Spatial Molecular Programs Using a Multimodal Foundation Model

Histopathological assessment remains central to cancer diagnosis and stratification, yet its mechanistic interpretation remains limited without molecular context. To address this, we developed SQUALL, a multimodal foundation model integrating histology with spatial molecular programs. For pretraining, we assembled histMol, a large-scale corpus of 1.76 billion paired histology-spatial transcriptomics spots/bins across 33 tissues and 12 platforms from 3,446 tissue sections. Following pretraining, SQUALL enables transcriptome-wide virtual biomarker profiling, prognostically relevant spatial niches discovery, and integrative disease progression modeling. Leveraging its multimodal embeddings, SQUALL identifies niches associated with tertiary lymphoid structure (TLS) maturation and ovarian cancer relapse, reconstructs molecular trajectories of breast cancer invasion across 325,112 spots, and uncovers underlying transcriptional programs. Applied to whole-slide images from 898 patients, SQUALL outperforms existing pathology foundation models in outcome prediction while enabling interpretable risk stratification. Together, these results establish spatially aligned multimodal pretraining as a new paradigm for extending molecular insights into pathology images.

bioinformatics↗

Pseudomonas aeruginosa CRISPR-Cas primes a minimal proline-codon toxin to abort anti-CRISPR phages

Pseudomonas aeruginosa typically carries type I-F CRISPR-Cas systems, which are targeted by diverse (pro)phage-encoded anti-CRISPR (Acr) proteins. Here, we show that [~]26% of P. aeruginosa Cas effectors are reprogrammed by a regulatory RNA guide (CreA) to transcriptionally silence a conserved small RNA toxin (CreT) that arrests cell growth upon Cas inactivation. This toxin unprecedentedly employs two consecutive proline codons, thus termed "proline-codon toxin". Combined phylogenetic and genetic analyses unraveled that CreTA has forced P. aeruginosa to reject prophages whose Acrs disrupt Cas-DNA binding, which is essential for CreT repression. We further show that Acr-armed lytic phages designed to overcome CRISPR adaptive immunity can be instead aborted by CreTA-mediated defense in vitro and in a mouse model. Our findings unravel intra-genomic arms races between CreTAs and anti-CRISPR phages, and underscore the necessity of rational engineering of strain-specific therapeutic phages to penetrate the layered CRISPR and TA barriers of multidrug-resistant P. aeruginosa.

microbiology↗

Efficient base editing and development in human embryos without chromosomal alterations

Cas9-based tools enable the introduction of genetic lesions to investigate DNA repair outcomes and edit the genome at disease-relevant loci. DNA double-strand breaks (DSBs) induced by CRISPR/Cas9 result in frequent aneuploidy and large deletions, revealing a repair deficiency in early human embryos and limiting the clinical application of this technology. Here we evaluated the DNA repair outcomes of DNA nicks and mismatches introduced using base editors in human embryos at two targets, PCSK9 and HBG. Editing was efficient and, unlike Cas9-induced DSBs, did not result in either chromosomal abnormalities or large deletions. Small insertions or deletions after base editing were rare, and off-target activity was dependent on the guide RNA. Delivering the base editor as a protein at fertilization or at the pronuclear stage allowed normal development to the blastocyst stage and the derivation of edited stem cell lines. In stark contrast, introduction of the editor as RNA resulted in early embryo arrest. Our results demonstrated that, unlike DSBs, DNA nicks and mismatches are efficiently repaired in human embryos, allowing specific on-target changes without genotoxic consequences.

genetics↗

Carbamylome analysis reveals regulatory roles for lysine carbamylation in β-cell glycolytic and insulin-processing enzymes

In type 1 diabetes (T1D), insulin-producing {beta} cells are destroyed by an autoimmune response driven by pro-inflammatory cytokines, including interferons. {beta}-cell cytokine signaling is mediated in part by post-translational modifications, such as phosphorylation and acetylation. However, the role of other post-translational modifications in {beta}-cell cytokine signaling represents an important knowledge gap. In the context of autoimmune diseases, lysine carbamylation has gained attention for its role in pathogenesis. Here, we investigate the role of carbamylation in T1D. We found that pancreatic islet cells from the T1D model, non-obese diabetic (NOD) mice, exhibit 11% carbamylation-positive cells, whereas non-diabetic CD1 mice have only 5%. Proteomics analysis of the MIN6 insulin-producing cell line treated with a cocktail of three pro-inflammatory cytokines IFN{gamma} + IL-1{beta} + TNF identified 284 carbamylated peptides from 222 proteins impacted by the cytokine treatment. Integration of carbamylation and acetylation provided a deep view of the cytokine-regulated PTMs and potential points of interplay. A functional-enrichment analysis revealed that carbamylation was enriched in pathways related to autoimmune diseases, metabolism, DNA replication, and protein translation. Moreover, functional testing demonstrated that carbamylation inhibits the glycolytic enzyme aldolase A and the insulin-processing enzyme carboxypeptidase E, identifying a possible role for cytokine-induced {beta}-cell dysfunction. In summary, protein carbamylation is elevated in islets from NOD mice, and pro-inflammatory cytokine treatment regulates protein carbamylation in MIN6 cells. These data identify carbamylation as a potential regulatory mechanism for {beta}-cell metabolism and insulin production in the context of islet inflammation.

biochemistry↗

Distinct and shared synergistic effects of high-fat and high-iron diets on liver tumorigenesis and transcriptomic remodeling in mice

Background and AimsThe incidence of hepatocellular carcinoma (HCC) is increasingly driven by metabolic risk factors, including obesity and iron overload. Although high-fat and high-iron diets independently promote hepatocarcinogenesis, their shared and distinct molecular effects remain unclear. We sought to define how dietary fat and iron differentially shape HCC development. ApproachMale C3HeB/FeJ mice were exposed to long-term high-fat (HFD), high-iron (HID), or combined (HFD+HID) diets for 16.5 months. Tumor burden, hepatic iron distribution, mTOR signaling, oxidized phospholipid (OxPL) accumulation, and transcriptomic alterations across normal, adjacent non-tumor, and tumor liver tissues were analyzed using biochemical, histological, and RNA sequencing approaches. ResultsAll diets induced HCC with comparable tumor burden. HID increased iron levels in non-tumor liver tissue but resulted in relative iron depletion within tumors, indicating tumor-specific iron utilization. Tumors from all diet groups showed robust mTOR activation and increased OxPL accumulation, with stronger oxidative stress signatures in HFD and HFD+HID tumors. Transcriptomic analyses revealed conserved oncogenic programs alongside diet-specific signatures, with HFD exerting a dominant effect on metabolic reprogramming and gene dysregulation, whereas HID preferentially enhanced immune and inflammatory signaling. Progressive, monotonic changes in gene expression were observed across disease stages. Cross-species analyses linked diet-induced mouse tumors to immunologically "hot" human HCC subtypes. ConclusionsDietary fat and iron promote HCC through overlapping yet distinct molecular pathways, highlighting metabolic and immune mechanisms as key targets in diet-associated liver cancer.

cancer biology↗

Efficient and accurate near telomere-to-telomere haplotype reconstruction of diploid genomes

Telomere-to-telomere (T2T) and haplotype-resolved assembly are crucial for understanding eukaryotic genomes. For diploid species, this resolution is critical to uncover allelic variations, inheritance patterns, and functional genomic traits. Current scaffolding methods typically employ either sequence-based or graph-based strategies. Sequence-based approaches rely on proximity signals to yield high contiguity, but underutilize assembly graph information, resulting in more structural errors and chromosomal misassignments. Graph-based methods leverage graph topology for higher accuracy but frequently struggle to achieve chromosome-scale contiguity. However, neither strategy alone can overcome its inherent limitations to simultaneously achieve high contiguity and accuracy. To address these challenges, we introduce HapFold, the first hybrid scaffolding framework that synergistically leverages the complementary strengths of both graph-based and sequence-based approaches. By integrating the topological accuracy of assembly graphs with the proximity-guided contiguity of sequence models, HapFold achieves highly accurate, chromosome-scale or near-T2T haplotype reconstructions for diploid genomes. Compared to existing methods, HapFold achieves superior assembly quality while accelerating computation by an order of magnitude. Furthermore, in the haplotype reconstruction of diploid genomes using standard Oxford Nanopore Technologies simplex reads, HapFold enables the reconstruction of a greater number of near-T2T assemblies. Our approach provides a robust and scalable solution for the high-fidelity reconstruction of haplotype-resolved diploid genomes.

bioinformatics↗

Nature-inspired nanodiscs for lesion-targeted delivery reprogram macrophages and attenuate established abdominal aortic aneurysms

Abdominal aortic aneurysm (AAA) is a life-threatening vascular disease characterized by chronic inflammation and immune dysregulation, with lesional macrophages playing a pivotal role in disease progression. However, effective and safe delivery of immune modulators to macrophages at the site of AAA remains a major clinical challenge. To address this unmet need, we report a nature-inspired nanodisc platform based on high-density lipoproteins for targeted delivery to lesional macrophages, further engineered with a multi-component targeting strategy incorporating an aneurysm-homing peptide and phosphatidylserine lipids. Nanodiscs encapsulating an anti-inflammatory protein kinase R-like endoplasmic reticulum kinase (PERK) inhibitor remarkably attenuated progression of established AAA in an elastase-induced mouse model. Using a combination of in vivo biodistribution and immune profiling approaches, we demonstrate that nanodisc-assisted PERK inhibitor delivery selectively reprograms the local immune microenvironment and attenuates pathological inflammation in AAA disease models. Notably, a single administration achieves sustained therapeutic efficacy with favorable safety profiles, effectively limiting the progression of established AAA in a clinically relevant setting. This work presents a new avenue of designer nanomedicines for targeted immunomodulation and maybe broadly applicable for a wide range of vascular and immune-mediated pathologies.

bioengineering↗

Redesign selective protein binders using contrastive decoding

MotivationFixed-backbone sequence design methods such as ProteinMPNN operate on backbone coordinates alone and cannot represent target side-chains at the binding interface. Their decoding algorithm also lacks a mechanism to balance binding affinity and folding stability or to improve selectivity against structurally similar off-targets. These gaps limit the computational design of protein binders with high affinity and specificity. ResultsWe present RedNet, a multiscale graph neural network that encodes side-chain information of the binding target. We further develop a contrastive decoding algorithm, motivated by the thermodynamic decomposition of binding free energy, that addresses two objectives: (1) balancing binding affinity and folding stability, and (2) improving selectivity against structurally similar off-targets. RedNet reaches 43% native sequence recovery on heterodimers, compared with 37% for ProteinMPNN and 33% for ESM-IF. With contrastive decoding, it matches native-sequence co-folding success (68%) on high-confidence AlphaFold3 targets, exceeding ProteinMPNN (59%) and ESM-IF (61%). On a new benchmark of structurally similar on-/off-target pairs, RedNet with contrastive decoding reaches 64.8% energetic selectivity, ahead of PiFold (55.6%), ProteinMPNN (53.7%), and ESM-IF (53.7%). AvailabilitySource code and datasets are released at https://github.com/zw2x/rednet_public. Contactjinbo.xu@gmail.com

bioinformatics↗

Cell Type-informed Characterization of Spatial Niches from Spatial Multimodal and Multi-omics Data

Cell niches play critical roles in tissue organization and orchestrate homeostasis, development, and disease progression. Advances in spatial omics technologies now allow diverse molecular and image-derived data to be jointly captured while preserving spatial context, but deciphering cell niches from such spatial multimodal and multi-omics data remains challenging. Existing computational methods are still limited in their flexibility across variable combinations of spatial modalities and omics data. Here we introduce SpaNECT, a unified and flexible framework designed to accommodate spatial multimodal and multi-omics data for cell niche characterization. SpaNECT further incorporates reference-informed cell-type information to support biologically interpretable niche analysis. Systematic evaluations across diverse tissues, disease conditions, and developmental stages showed that SpaNECT consistently outperformed representative methods in resolving cell niches. In mouse brain spatial multi-omics data, SpaNECT uncovered niche-associated molecular and regulatory programs; in developing chick heart, it tracked cross-stage niche reorganization and progressive remodeling of ventricular-associated cell states during maturation. Overall, SpaNECT establishes a general and robust framework for characterizing cell niches across spatial multimodal and multi-omics data.

bioinformatics↗

A CandiChrome toolkit for multicolor labeling of Candida cells

Here, we develop CandiChrome, a multiplex labeling toolkit for Candida albicans, through combined in vitro and in vivo characterization of fluorescent proteins in a standard strain background. To this end, we screened 13 candidate fluorophores across the visible spectrum and assessed their practical performance based on brightness, stability, and usability. This analysis identified a seven-fluorophore set that achieved the most effective balance of signal strength, robustness, and compatibility. We used this optimized panel to build a modular multicolor platform that enables strain labeling, mixed-population imaging, and competition assays in C. albicans. This platform could resolve up to 21 distinct populations by flow cytometry and microscopy. Importantly, CandiChrome supported the resolution of differentially labeled populations both in vitro and in the murine host, supporting the simultaneous tracking of multiple strains in complex settings. Together, these results establish CandiChrome as a flexible platform for multiplex fungal imaging in a pathogenic species where multicolor tools remain underdeveloped.

microbiology↗

Histone modifications analysis reveals enhancers reprogramming during maternal-to-zygotic transition

Enhancers are important epigenetic regulatory components that coordinate spatiotemporal gene expression and play a crucial role in mammalian development, gene regulation, and illness. During early mammalian embryogenesis, histone modifications including H3K4me1, a canonical enhancer mark, and H3K27ac, which identifies active enhancers, are still poorly understood. This study profiles the genome-wide H3K4me1 and H3K27ac patterns in mouse oocytes and pre-implantation embryos using low-input CUT&RUN (cleavage under targets and release using nuclease) with input as low as 50 cells. Both markers are enriched in distal regions and exhibit distinct sequence preferences and reprogramming dynamics in pre-implantation embryos. H3K27ac, a mark of active enhancers, is reprogrammed at the 2-cell stage, whereas H3K4me1 is remodeled at the 4-cell stage and overlaps with H3K27ac, coinciding with accessible chromatin regions. Interestingly, H3K4me1 and H3K27ac are co-localized in promoter regions, where they are mutually exclusive to H3K4me3. Enhancers are dynamically remodeled during maternal-to-zygotic transition (MZT). there are three enhancer types: active enhancers (H3K4me1/H3K27ac), primed enhancers (H3K4me1), and poised enhancers (H3K4me1/H3K27me3). Active enhancers increase significantly after zygotic genome activation. Further, super-enhancers are present across the genome and are mainly enriched in promoters. The specific motifs enriched by super-enhancers may be associated with the variations of gene expressions at different stages.

developmental biology↗