Biology subjects

Zhao, X.

Publications and source records attributed to Zhao, X..

At least 163 records · Page 9Linked to original sources

bioRxiv2025

Au18(L-NIBC)14 targets ASC oligomerization for autoimmune disease treatment

Gold nanoclusters (AuNCs), unlike conventional nanoparticles, possess molecular characteristics besides ultrasmall nano-features. Recently, we and others showed that AuNCs are promising in treatments of various major diseases. However, the AuNCs used were usually mixtures, and the specific target and their relationship with AuNC structures are unclear, which largely restrict their druggability. Multiple sclerosis (MS) is an autoimmune disease (AID) implicating central nervous system (CNS), in which drug discovery is challenging. Here we used Au18(L-N-isobutyryl-L-cysteine)14 (Au18(L-NIBC)14) and Au25(L-NIBC)18, two AuNCs with the same ligand, to report their much different therapeutic effects in experimental autoimmune encephalomyelitis (EAE). We show that, Au18(L-NIBC)14, but not Au25(L-NIBC)18, specifically targets apoptosis-associated speck-like protein containing a CARD (ASC) oligomerization, thus inhibit the activation of ASC-dependent inflammasomes, resulting in comprehensive restoration of cytokine homeostasis in the CNS of EAE mice. Au18(L-NIBC)14 significantly prevents axon demyelination, protects blood-brain barrier, blocks immune cell infiltration into CNS, and completely prevents motor deficits and relieve the early-cognitive impairments of EAE mice. Remarkable efficacies were also observed in animal models of inflammatory bowel disease, psoriasis, systemic lupus erythematosus, indicating a broad prospect in AIDs treatments. Especially, definite molecular structure, specific target, clear mechanism, and exact therapeutic effects imply a good druggability of Au18(L-NIBC)14.

pharmacology and toxicology↗

bioRxiv2025

Manganese suppresses tumor growth through hyper-activating IRE1α

IRE1 and its downstream XBP1 signal is the most conserved unfolded protein response pathway that cells utilize to combat endoplasmic reticulum stress, also known to be utilized by tumor cells to adapt to harsh environment, leading to tumor progression. Several inhibitors against IRE1 have been developed, some of which show promising effect in clinical trial for cancer therapy, but none of them have been used in practice. Considering that hyper-activation of IRE1 induces cell death, we hypothesize that activation of IRE1 could be an alternative way for tumor suppression. Here, we identified divalent manganese ion as a potent activator to IRE1, which interacts with the cytosolic part of IRE1 directly, augmenting the downstream pro-apoptotic pathway but not the pro-survival outcome. Mn2+ limits tumor growth in xenograft model in an IRE1-dependent way. Our finding suggests pharmacological activation of IRE1 as an underestimated but promising way in cancer therapy. HighlightsO_LIMn2+ binds to cytosolic segment of IRE1 and promotes its oligomerization C_LIO_LIMn2+ hyper-activates IRE1 and induces downstream terminal UPR under ER stress C_LIO_LIMn2+ does not elevate XBP1s expression C_LIO_LIMn2+ as an IRE1 activator impairs tumor growth in xenograft model C_LI

cancer biology↗

bioRxiv2025

Two-Phase Coding Strategy by CA1 Pyramidal Neurons: Linking Spatiotemporal Integration to Predictive Behavior

Space and time are fundamental components of memory, yet how the brain encodes these dimensions to guide behavior remains unclear. Using virtual-reality environments, we uncovered a two-phase neural code in hippocampus CA1 that represents time or distance through two functional pyramidal subpopulations, PyrUp and PyrDown. In Phase I, PyrUp activity synchronously increases to mark the initiation of encoding; In Phase II, their activity decays at heterogeneous, neuron-specific rates, creating a gradual divergence in across-population firing rates that scales with elapsed time. Conversely, PyrDown activity initially decreases before gradually rising. The crossover point, where rising PyrDown activity surpasses declining PyrUp activity, precedes predictive licking behavior. Combining optogenetics and computational modeling, we provided circuit-level evidence that PyrUp neurons primarily process locomotion-related inputs regulated by somatostatin-positive interneurons, whereas PyrDown neurons mainly receive reward-related inputs gated by parvalbumin-positive interneurons. These findings advance our understanding of how hippocampal circuits compute spatiotemporal information to inform behavior.

neuroscience↗

bioRxiv2025

RAMA: an Integrative Approach to Identify Hot Spots and Guide the Directed Evolution of High Molecular Weight Enzyme

Directed evolution has revolutionized enzyme engineering but remains challenging for large, multidomain proteins due to their complex dynamics and vast combinatorial sequence space. Traditional NMR spectroscopy, while powerful for identifying functional residues, is limited by the requirement for complete resonance assignments that become intractable in high molecular weight systems. Here, we present a hybrid NMR-computational framework that integrates chemical shift perturbation mapping with AlphaFold3-docked distance constraints, enabling the identification and assignment of ligand-proximal hotspots without the need for full resonance assignment. By analyzing side chain 1H-13C correlation spectra, probabilistic amino acid typing, and structural proximity filtering, we mapped functional hotspots in the [~]90 kDa Pyrococcus furiosus DNA polymerase. Targeted saturation mutagenesis of these sites resulted in variants exhibiting multi-fold increases in catalytic efficiency while sampling less than 0.6% of total residues. The identified hotspots revealed spatially distinct yet cooperative contributions to catalysis, as further supported by combinatorial mutagenesis and kinetic analyses. This hybrid strategy provides a practical pipeline for narrowing mutagenesis targets in large enzymes under catalytic conditions, overcoming the size, assignment, and screening limitations of conventional NMR-guided evolution, offering a powerful route toward efficient biocatalyst optimization by prioritizing high-probability target residues.

molecular biology↗

bioRxiv2025

Automated Discovery of Therapeutic Biomaterial for Renally Impaired Hyperuricemia Patients by Natural Language Processing and Machine Learning

The exponential growth of scientific publications presents opportunities for researchers to identify valuable knowledge, especially in the highly interdisciplinary field --- biomaterials, where exploiting possible connections between unmet clinical needs and materials properties from literatures is crucial. However, with traditional literature reading, it is extremely challenging to marry unmet clinical needs with existing materials reported for different applications or other purposes. Here, to provide a not-renally cleared therapeutics for renally impaired hyperuricemia patients, we designed a multi-tiered framework MatWISE that fuses state-of-the-art natural language processing, semantic relationship mapping, and machine learning to automate the complex process of material discovery from a sea of scientific literatures published until December of 2022, and successfully identified and optimized {delta}-MnO2 into an orally administered, nonabsorbable uric acid (UA) lowering biomaterial. {delta}-MnO2 had superior serum and urine UA-lowering effect in three hyperuricemia mouse models, by comparing with a standard of care drug. {delta}-MnO2 is highly promising to serve as a safe and effective UA-lowering drug for renally impaired hyperuricemia patients. We demonstrated a new research paradigm for biomaterials that combining state-of-the-art machine learning techniques and a handful of experiments to discover a translationally relevant material from the massive existing research, for an unmet clinical need.

biochemistry↗

bioRxiv2025

Tumor hypoxia adaptation depends on FLAD1 mediated mitochondrial metabolic reprogramming

Hypoxia, a hallmark of solid tumors, promotes the malignant progression and is challenging to target. Metabolic reprogramming and the resulting metabolic vulnerabilities provide a promising strategy to target tumor hypoxia. Here we systematically compared the metabolic network differences between hypoxic and non-hypoxic cells, and developed a deep learning model, "DepFormer", to predict the dependent metabolic genes in hypoxic tumor cells. The performance of DepFormer was validated using CRISPR screening dataset. Oxidative phosphorylation was identified as the most significantly hypoxia-dependent metabolic pathway, and FLAD1 was predicted to be one of the key hypoxia-dependent metabolic genes. FLAD1 locus is amplified, and FLAD1 expression is upregulated in various tumor types, especially in hypoxic tumors. FLAD1 depletion compromises tumors adaptation to hypoxia by disrupting mitochondrial complex II activity, leading to an imbalance between succinate and fumarate, and consequent failure to adapt to hypoxia. Subsequently, we identified a drug-like inhibitor of FLAD1, which selectively inhibits the growth of tumor cells under hypoxia. Our findings reveal FLAD1 as an innovative therapeutic target for hypoxic tumors.

cancer biology↗

bioRxiv2025

An exonuclease safeguards cGAS immune signaling by degrading its 2'-5' phosphodiester intermediate

Excessive activation of cyclic GMP-AMP synthase (cGAS) drives inflammatory and autoimmune diseases, but complete inhibition of cGAS signaling can compromise host defence. Here we show that cGAS signaling can be tuned through a previously unrecognized regulatory checkpoint. Bacterial cGAS generates cGAMP through a two-step mechanism involving release and rebinding of a 2'-5'-linked linear dinucleotide intermediate. We identify a CBASS-associated exonuclease (Exo) that selectively degrades this catalytic intermediate, establishing a threshold for cGAS activation while preserving immune function. This thresholding mechanism is conserved across domains of life: Exo suppresses human cGAS activity in vitro and in mammalian cells and attenuates cGAS-driven pathology in vivo. Our findings identify the catalytic intermediate surveillance as a conserved strategy for safeguarding cGAS signaling.

biochemistry↗

bioRxiv2025

Single-cell copy number alteration signature analysis reveals masked patterns and potential biomarkers for cancer

Copy number alteration (CNA) is a major type of cancer genome alteration that drives cancer progression. CNA signature analysis can reveal underlying etiology and provide biomarkers for cancer treatment, and existing CNA signature analyzes are all performed using bulk tissue samples. However CNA usually affect large proportion of genome, and the CNA profile of bulk sample does not reflect the actual CNA profiles of the individual cancer cells of the sample, especially in tumors with high heterogeneity, such as hepatocellular carcinoma (HCC). Furthermore, the evolutionary trajectory of CNA mutational processes still remain elusive. Here we build a method to comprehensively analyze the CNA signatures of HCC from single-cell and bulk sample perspective, revealing patterns and potential noise signals from the usually performed bulk tissue CNA signature analysis. Single-cell signature analysis delineated the evolutionary trajectory of HCC CNA signatures, and different CNA signatures consistently emerge in different HCC evolution stages. Single-cell CNA signatures show robust performance in patient prognosis and drug sensitivity prediction. This work not only reveals specific considerations in analyzing CNA signature derived from bulk tissue but also depicts CNA evolution process and provides potential biomarkers for the prognosis and treatment of HCC patients. HighlightSingle-cell analysis reveals CNA signatures masked in bulk tissue. Single-cell analysis delineates the evolutionary trajectory of CNA signature. Small CNAs occur early and large CNAs happens late in HCC evolution. Single-cell CNA signatures show robust performance in guiding cancer clinical treatment.

genomics↗

bioRxiv2025

Population-scale gene expression analysis reveals the contribution of expression diversity to the modern wheat improvement

Changes in gene expression are crucial for crop breeding, yet population genomics has primarily focused on sequence polymorphisms rather than gene expression diversity. The strategy of using single genome reference for RNA-seq analysis could not handle introgression bias, especially for hexaploidy wheat. Here, we conducted RNA-seq for 328 wheat lines, including representative diverse landraces and elite cultivars from China and the United States, to investigate the role of gene expression variation in shaping agronomic traits. Using pan-genome resources, we identified 20,615 more transcripts than using the Chinese Spring reference genome alone. We constructed a pan-gene atlas regulatory map through eQTL analysis, demonstrating that genes introgressed from wild relatives were under tight genetic control. Genes responding to environmental stress show higher activity after introgressed into the wheat genome, demonstrating how long-term breeding selection impacted the gene expression regulation of targeted introgression. Multi-omics modeling identified 231 high-confidence candidate genes for 34 field agronomic traits and the seedling resistance phenotypes of 8 powdery mildew isolates. More than one fifth of those candidates have no homolog in Chinese Spring reference genome. By utilizing the indexed KN9204 EMS library, 80% candidates showed significant trait difference between wild type and mutant lines. Furthermore, directional shifts in genes of which expression were changed by breeding improvement demonstrated distinct adaptations to local environments. Our study constructed a pan-gene atlas to correct the reference bias of reads mapping in RNA-seq studies and revealed the expression patterns of introgressed genes within the wheat genome and their regulatory mechanisms, which highlighted the impact of breeding selection on gene expression of the worlds most important crop.

plant biology↗

bioRxiv2025

Dynamic Monomer-Dimer Transition in Ligand-induced Apelin Receptor Activation

G-protein-coupled receptors (GPCRs) are significant signal transducers that exist as monomers and in multiple oligomeric forms. However, molecular mechanism driving their dynamic interconversion to regulate intricate signaling in class A GPCRs remains elusive, compounding our understanding of their related pathophysiological functions. Here, we present a set of 12 assemblies of the apelin receptor (APLNR), including dimeric apo state, agonistic small molecule- or nanobody-bound state of monomeric and dimeric APLNR with and without G-proteins, providing a detailed dynamic view of the monomer-dimer transition. High-resolution cryo-EM structures reveal that different ligands induce varying degrees of pre-dissociation of dimers in the absence of G-protein, with G-protein coupling facilitating the transition from dimeric to monomeric receptor. Functional studies further highlight the critical role of cholesterol clusters in stabilizing the APLNR dimers. These insights enhance our understanding of the dynamic regulation of class A GPCRs across different aggregated forms and advance the rational drug design strategies aimed at selectively modulating of APLNR signaling.

molecular biology↗

bioRxiv2025

Role of the ETV5/p38 signaling axis in aggressive thyroid cancer cells

Patients with poorly differentiated thyroid cancer (PDTC) and anaplastic thyroid cancer (ATC) face a much poorer prognosis than those with differentiated thyroid cancers. Around 25% of PDTCs and 35% of ATCs carry the BRAFV600E mutation, which constitutively activates the MAPK pathway, a key driver of cell growth. Although combining BRAF and MEK inhibitors can shrink tumors, resistance often develops. The exact cause of this resistance remains unclear. We previously found that in PDTC and ATC cells the BRAFV600Emutation is strongly linked to the expression of ETV5, a transcription factor downstream of the MAPK pathway. In the current study, we observed a significant association between ETV5 expression and the activation of p38, a central component of the MAPK14 pathway. Upon reduction of ETV5 levels, p38 expression and activation decreased, along with its upstream regulators MKK3/MKK6. This suggests that the MAPK and p38/MAPK14 pathways are interconnected and that p38 has oncogenic properties in these cancers. Using high-throughput screening, we established that combining p38 inhibitors with the BRAF inhibitor dabrafenib showed strong synergy in vitro, including in cells resistant to dabrafenib and trametinib that had acquired a secondary TP53 mutation. We then tested this combination in a genetically engineered mouse model (GEMM) of ATC. Overall, our findings suggest an oncogenic link between the MAPK and p38/MAPK14 pathways and that combining p38 pathway inhibitors with dabrafenib-targeted therapy could improve treatment outcomes for aggressive thyroid cancers. However, more specific and effective p38 inhibitors are required to fully harness this potential.

cancer biology↗

bioRxiv2025

Multi-alignment framework - consider and detect genomic and transcriptomic sequence alignment variability by comparing different techniques

DNA and RNA nucleotide sequences are ubiquitous in all biological cells, serving as both a comprehensive library of capabilities for the cells and as an impressive regulatory system to control cellular function. The multi-alignment framework (MAF) provided in this study offers a user-friendly platform for sequence alignment and quantification. It is adaptable to various research needs and can incorporate different tools and parameters for in-depth analysis, especially in low read rate scenarios. This framework can be used to compare results from different alignment programs and algorithms on the same dataset, allowing for a comprehensive analysis of subtle to significant differences. This concept is demonstrated in a small RNA case study. MAF is specifically designed for the Linux platform, commonly used in bioinformatics. Its script structure streamlines processing steps, saving time when repeating procedures with various data sets. While the focus is on microRNA analysis, the templates provided can be adapted for all transcriptomic and genomic analyses. The template structure allows for flexible integration of pre- and post-processing steps. MicroRNA analysis indicates that STAR and Bowtie2 alignment programs are more effective than BBMap. Combining STAR with the Salmon quantifier, or with some limitations, the Samtools quantification, appears to be the most reliable approach. This method is ideal for scientists who want to thoroughly analyze their alignment results to ensure quality. The detailed microRNA analysis demonstrates the quality of three alignment and two quantification methods, offering guidance on assessing result quality and reducing false positives.

bioinformatics↗

bioRxiv2025

Pneumo-Typer: a high-throughput capsule genotype visualization tool with integrated serotype and sequence type prediction for Streptococcus pneumoniae

BackgroundStreptococcus pneumoniae persists as a leading global pathogen, with current capsule-based vaccines like PCV13 offering limited coverage against its extensive serotype diversity (>100 serotypes). This restricted coverage drives the emergence of non-vaccine serotypes. Moreover, vaccine efficacy is further compromised by immune evasion caused by capsule genotype (CapT) variations within vaccine-covered serotypes, while existing genome-based tools lack robust analytical capabilities for CapT. ResultsWe developed Pneumo-Typer, a CapT visualization tool enabling rapid identification of CapT variations in S. pneumoniae. Application to 17,407 publicly available genomes from the NCBI database revealed widespread CapT variations across vaccine-covered serotypes, providing critical insights for optimizing vaccine formulations. In addition, Pneumo-Typer integrates high-accuracy serotype prediction (98.44% accuracy across 93 serotypes) and multilocus sequence typing (ST), facilitating comprehensive genomic surveillance. Besides, CapT and ST information can assist in serotype determination. Pneumo-Typer enables integrated analysis of serotype-CapT-ST relationships, demonstrating that while most serotypes associate with multiple STs and CapTs, ST and CapT lineages evolve independently. Strikingly, multi-serotype serogroups exhibited pronounced CapT diversity, suggesting evolutionary processes driving serogroup expansion through CapT plasticity. ConclusionsIn summary, Pneumo-Typer is an integrated platform for genomic surveillance of pneumococcal populations. By resolving previously underexplored serotype-CapT-ST linkages, the tool provides a framework for next-generation vaccine design, emphasizing the need for vaccine formulations that address both serotype replacement and CapT-driven immune evasion.

bioinformatics↗

bioRxiv2025

A Semi-Automated MEA Spike sorting (SAMS) method for high throughput assessment of cultured neurons

Neurons derived from human pluripotent stem cells (hPSCs) are valuable models for studying brain development and developing therapies for brain disorders. Evaluating human-derived neurons requires assessing their electrical activity, which can be achieved using multi-electrode arrays (MEAs) for extracellular recordings. Because each electrode channel generally detects activity from multiple neurons, resolving the activity of single neurons requires a process called spike sorting. However, currently available spike sorting methods are not optimized for the analysis of hPSC-derived neurons, and require complex workflows and time-consuming manual intervention. Here, we introduce a Semi-Automated MEA Spike sorting software (SAMS) designed specifically for low-density MEA recordings of cultured neurons. SAMS outperforms commercially available automated spike sorting algorithms in terms of accuracy and greatly reduces computational and human processing time. By providing an accessible, efficient, and integrated platform for spike sorting, SAMS enhances the resolution and utility of MEA in disease modeling and drug development using human-derived neurons. HighlightsO_LISAMS is designed and optimized for high throughput analysis of hPSC-derived neurons. C_LIO_LISAMS is more efficient and accurate compared to recommended spike-sorting software. C_LIO_LISAMS resolves phenotypic differences previously not observed without spike sorting. C_LIO_LISAMS is an open-source software. C_LI

neuroscience↗

bioRxiv2025

ST-FFPE-mIF: Integrating Spatial Transcriptomics and Multiplex Immunofluorescence in Formalin-Fixed Paraffin-Embedded Tissues Using Stereo-seq

Stereo-seq is the state-of-the-art technique, which allows capturing of spatial transcriptomic data at sub-cellular resolution and in large scale of view. Stereo-seq FFPE technique is recently launched with the capability to obtain spatially resolved gene expression in FFPE tissue sections. However, the omic information is limited to transcriptome. To delineate spatial molecular hierarchy from transcriptome to phenome, we present the protocol that implements nine-plex immunofluorescence staining with detection of spatial transcriptomics in one FFPE tissue section (short for ST-FFPE-mIF). This protocol details the modified biochemistry procedure and also provides analytical framework to achieve single-cell resolution through nuclear or membrane staining-based cell segmentation. We demonstrated the application of ST-FFPE-mIF in colorectal cancer sample to illustrate how ST-FFPE-mIF facilitates a robust analysis of spatially resolved multi-omic data at the single-cell level.

biochemistry↗

bioRxiv2025

Multi-scale structure of chromatin condensates rationalizes phase separation and material properties

Biomolecular condensates, compartments that concentrate molecules without surrounding membranes, are integral to numerous cellular processes. The structure and interaction networks of molecules within condensates remain poorly understood. Using cryo-electron tomography and molecular dynamics simulations we elucidated the structure of phase separated chromatin condensates across scales, from individual amino acids to network architecture. We found that internucleosomal DNA linker length controls nucleosome arrangement and histone tail interactions, shaping the structure of individual chromatin molecules both within and outside condensates. This structural modulation determines the balance between intra- and intermolecular interactions, which in turn governs the molecular network, thermodynamic stability, and material properties of chromatin condensates. Mammalian nuclei contain dense clusters of nucleosomes whose non-random organization is mirrored by the reconstituted condensates. Our work explains how the structure of individual chromatin molecules ultimately determines physical properties of chromatin condensates, with implications for cellular chromatin organization.

biophysics↗

bioRxiv2025

ca-circSCN8A promotes HPASMCs ferroptosis via LLPS initiated R-Loop

BACKGROUNDFerroptosis has been implicated in pulmonary hypertension. Chromatin-associated RNAs are linked to ferroptosis. However, their role in pulmonary vascular ferroptosis in PH is unexplored. METHODSBioinformatics, Sanger sequencing, RNase R and others were employed to identify differentially higher expression of ca-circSCN8A. Functional gain and loss assays were employed to unveil the role of ca-circSCN8A in hypoxia-induced redox-dependent ferroptosis in HPASMCs and PH mice model. Interaction between ca-circSCN8A and FUS was detected via RNA immunoprecipitation and pull-down assays. FRAP, CHIRP-qPCR, MDA, GSH and GSSG were conducted to explore the potential molecular mechanism. RESULTSca-circSCN8A was firstly identified and confirmed to be upregulated in PH. Upregulation of ca-circSCN8A can promote hypoxia induced ferroptosis in HPASMCs. Under hypoxic conditions, ca-circSCN8A promoted the lactylation of FUS by recruiting EP300, leading to formation of LLPS of ca-circSCN8A/FUS/EP300. LLPS maintained the stability of the R-Loop formed by ca-circSCN8A and ferroptosis related-gene SLC7A11 promoter that inhibit the transcription of the SLC7A11 gene, further result in the disruption of the redox balance and causes ferroptosis in HPASMCs. CONCLUSIONSca-circSCN8A recruits EP300 to promote the lactylation of FUS, thereby promoting LLPS formation of ca-circSCN8A/EP300/FUS. Further, the LLPS motivates ca-circSCN8A to form R-loop with its non-host SLC7A11 and participating in the regulation of hypoxic induced HPASMCs redox-dependent ferroptosis. This is the first confirmation that circRNAs forming R-loops with non-host genes regulated by LLPS. Our findings indicated that ca-circSCN8A plays an important role in ferroptosis of hypoxic induced HPASMCs and may be a potential target for the treatment of PH.

molecular biology↗

bioRxiv2025

Telomeric SUMO level influences the choices of APB formation pathways and ALT efficiency

Many cancers use an alternative lengthening of telomeres (ALT) pathway for telomere maintenance. ALT telomeric DNA synthesis occurs in ALT telomere-associated PML bodies (APBs). However, the mechanisms by which APBs form are not well understood. Here, we monitored the formation of APBs with time-lapse imaging employing CRISPR knock-in to track the promyelocytic leukemia (PML) protein at endogenous levels. We found APBs form via two pathways: telomeres recruit PML proteins to nucleate PML bodies de novo, or telomeres fuse with preformed PML bodies. Both nucleation and fusion of APBs require interactions between SUMO and SUMO interaction motifs (SIMs). Moreover, APB nucleation is associated with higher levels of SUMOs and SUMO-mediated recruitment of DNA helicase BLM, resulting in more robust telomeric DNA synthesis. Finally, further boosting SUMO levels at telomeres enhances APB nucleation, BLM enrichment, and telomeric DNA synthesis. Thus, high SUMO levels at telomeres promote APB formation via nucleation, resulting in stronger ALT activity.

cell biology↗