Biology subjects

Wang, J.

Publications and source records attributed to Wang, J..

At least 793 records · Page 44Linked to original sources

bioRxiv2025

Bimodality in pan-cancer proteomics reveals new opportunities for biomarker discovery

Bimodal protein expression, characterized by the distribution of protein expression with two modes, is linked to phenotypic variation across various biological systems. Whereas previous studies focused on RNA expression data, we developed a bimodality model tailored for proteomics to enhance the identification of cancer-associated biomarkers and targets, facilitating precision oncology. We analyzed proteomics data from various cancer types and identified 2401 tumor-associated bimodal proteins. These proteins were evaluated for pathway enrichment, revealing significant associations with critical cancer pathways, such as metabolism of non-essential amino acids, interaction between the extracellular matrix and its receptors on the cell surface, and central carbon metabolism in cancer. Utilizing an AI-enhanced knowledge graph, we further delineated common patterns among pan-cancer tumor-associated bimodal proteins. A case study on the bimodal expression of TROP2 in colon adenocarcinoma highlighted upregulation of MYC and WNT/{beta}-catenin signaling pathways and down-regulation of inflammatory and interferon-related pathways in the TROP2-high group. The biological difference between TROP2-high and TROP2-low groups underscored its significance in determining cancer heterogeneity and differences in cancer vulnerability, which can inform treatment decisions. Our findings show the value of proteomics in uncovering novel biomarkers and advancing precision medicine, setting a precedent for further multi-omics integration and clinical validation.

bioinformatics↗

bioRxiv2025

Identification of a neural basis for energy expenditure in the arcuate hypothalamus

Given the evolutionary instinct for caloric intake and the tendency for weight rebound after discontinuing dietary interventions or medications, increasing energy expenditure emerges as an alternative obesity treatment. However, neural regulation of energy expenditure remains poorly understood. Here, we report that a hypothalamic neuronal subtype, characterized by Crabp1 expression, establishes connections with multiple hypothalamic nuclei to regulate energy expenditure in mice. Inactivation of Crabp1 neurons reduces physical activity, body temperature, and adaptive thermogenesis, leading to an obese phenotype. Conversely, activation of these neurons increases energy expenditure and mitigates diet-induced obesity. Structural and functional analyses reveal that Crabp1 neurons promote energy metabolism through a "one-to-many" projection pattern. While Crabp1 neurons are rapidly activated by cold exposure and physical activity, prolonged light exposure abrogates their firing and may mediate light-induced metabolic disorder. Together, we reveal a neural basis that integrate various physiological and environmental stimuli to control energy expenditure and body weight.

neuroscience↗

bioRxiv2025

Proteome-wide computational analyses reveal links between protein condensate formation and RNA biology

Biomolecular condensates mediate dynamic compartmentalization of cellular processes. The multivalent interactions that underlie biomolecular condensation are often promoted by intrinsically disordered regions (IDRs) within proteins. While the role of IDRs in biomolecular condensates is well appreciated, predicting whether an IDR forms condensates in cells remains challenging. Here, we developed a machine learning model to predict condensation behavior of IDRs, analyzing 215 IDRs from fusion oncoproteins in HEK293T cells. Our study identified distinct sequence-derived physicochemical features associated with condensation. Leveraging these data, our model predicts that [~]12% of the [~]13,000 IDRs in the human proteome are likely to form cellular condensates. Proteins with condensate-forming IDRs are enriched in functions involving RNA-related processes and membrane-less organelles (MLOs), highlighting their role in MLO assembly and function. Our model, available via the SAK3.0 web server (https://sak.stjude.org), provides a powerful resource for studying IDR-driven phase separation across proteomes, offering insights into biomolecular condensates and their biological roles.

bioinformatics↗

bioRxiv2025

Unlocking hidden flaws in PPV and ACC: A step towards more reliable identification of protein complex

As classic evaluation indexes, clustering-wise predictive positive value (PPV) and accuracy (ACC) have been widely used for the detection of protein complexes ([1]). However, we identified a critical error in their calculation, which can lead to inaccurate evaluation results under most conditions. Here, we elaborate on the problem of the original indexes and propose revised indexes PPVM (PPV Modified) and ACCM, which correct the identified error. Experiments demonstrate that revised indexes achieve higher reliability. Based on the new indexes, we reevaluated three state-of-the-art computational methods for protein complex detection on five benchmarks to provide a revised baseline to facilitate comparison of performance for algorithms developed later. The code and data involved in the experimental section of this paper can be found in https://github.com/hyx-1/PPV_M-and-ACC_M.

bioinformatics↗

bioRxiv2025

Structural insights into the ubiquitin independent MIDN-proteasome pathway

The protein midnolin (MIDN) augments proteasome activity in lymphocytes, where it is predominantly expressed in adult mice. MIDN binds both to proteasomes and to substrates, but the mechanism by which MIDN facilitates substrate degradation in a ubiquitin-independent manner is unknown. Here, we present cryo-electron microscopy structures of the substrate-engaged, MIDN-bound human proteasome in two conformational states. MIDN induces proteasome conformations similarly to ubiquitinated substrates by using its ubiquitin-like domain to bind to the deubiquitinase RPN11. By simultaneously binding to RPN1 with its C-terminal -helix, MIDN positions its substrate-carrying Catch domain above the proteasome channel through which substrates are translocated before degradation. Our findings suggest that both ubiquitin-like domain and C-terminal -helix must bind to the proteasome for MIDN to stimulate proteasome activity.

biophysics↗

bioRxiv2025

Aedes aegypti aminopeptidase N3 is a functional binding receptor of Bacillus thuringiensis subsp. israelensis Cry4Ba toxin

Bacillus thuringiensis is widely employed for biological control. It can effectively suppress populations of various mosquito species, including Aedes aegypti. However, the precise mechanism underlying the action of cry toxin secreted by Bacillus thuringiensis on Ae. aegypti remains elusive. In this study, we investigated one of the binding receptors of cry toxin, aminopeptidase N. Through comprehensive bioinformatics analysis involving whole-genome screening, genetic mapping, structural characterization, phylogenetic analysis, and spatiotemporal expression profiling, we identified twenty-nine homologs of Ae. aegypti aminopeptidase N. Further, we successfully expressed GST-APN3 protein in E. coli and demonstrated through ligand blot and ELISA assays that APN3 exhibits high affinity binding to Cry4Ba toxin (Kd = 20.53 nM). To elucidate the functional role of APN3 as a receptor mediating Cry4Ba activity in Ae. aegypti midgut cells (some of which express this gene at high levels), CRISPR/Cas9 technology was employed to knock out APN3. Our bioassay results revealed that APN3 knockout mosquito larvae had 2.9 to 4.1-fold higher resistance against Cry4Ba, indicating its crucial involvement as an active receptor mediating Cry4Ba activity. Overall, this study provides a foundation for elucidating the specific larvicidal mechanisms of Bt against mosquito populations.

molecular biology↗

bioRxiv2025

Uncovering synaptic and cellular nanoarchitecture of brain tissue via seamless in situ trimming and milling for cryo-electron tomography

Cell-cell communication underlies all emergent properties of the brain, including cognition, learning and memory. The physical basis for these communications is the synapse, a multi-component structure requiring coordinated interactions between diverse cell types. However, many aspects of three-dimensional (3D) synaptic organization remain poorly understood. Here, we developed an approach, seamless in situ trimming and milling (SISTM), to reliably fabricate sufficiently thin lamellae for mapping of the 3D nanoarchitecture of synapses in mouse, monkey and human brain tissue under near-native conditions via cryo-electron tomography (cryo-ET). We validated SISTM in a mouse model of Huntingtons disease, demonstrating distinct 3D alterations to synaptic vesicles and mitochondria. By successfully applying SISTM to macaque brain, we described the 3D architecture of a tripartite synapse within the cortex. Subtomogram averaging (STA) enabled spatial mapping of astrocyte-neuron contacts within the tripartite synapse, revealing neurexin-neuroligin complexes as potential constituents that tether the two cell types. Finally, we showed that the defining features of synaptic nanoarchitecture were conserved across species and evident in human brain tissue obtained postmortem. Combining SISTM with cryo-ET and STA is a starting point for a new understanding of brain organization, disease-induced structural alterations and the development of rational, structure-guided therapeutics.

cell biology↗

bioRxiv2025

De novo Genome Assembly and Annotation of Manouria impressa

The Manouria impressa (Impressed tortoise) is a unique fungivore species with restricted distribution in Southeast Asia, recognized for its evolutionary importance and conservation priority. Here, we present the first de novo genome assembly of an impressed tortoise sampled from Yunnan, China. Using PacBio HiFi long-read sequencing and Hi-C proximity ligation technologies, we generated a 2.29 Gb assembly comprising 81 scaffolds with a contig N50 of 78.37 Mb, a scaffold N50 of 148.31 Mb, and a BUSCO completeness score of 98.3%. This high-quality genome assembly provides a critical resource for exploring the genetic basis of evolutionary adaptations and informing conservation genomics to support the management of this vulnerable species.

genomics↗

bioRxiv2025

REEP6 deficiency impairs ER and Golgi morphologies and causes retinal degeneration by attenuating the expression of phototransduction proteins

REEP6 is a member of the REEP family proteins belonging to the YIP superfamily. REEP proteins were membrane proteins involved in regulating membrane curvature. Mutations in REEP6 are associated with retinitis pigmentosa (RP). Mice lacking REEP6 were generated to model human RP. Reep6 mutant mice exhibit progressive retinal degeneration, which is attributed to abnormal trafficking of PDE6 and the absent expression of guanylate cyclases (GCs), due to ER dysfunction. However, the phenotype regarding the failed expression of GCs is questionable. Here, we generated an independent Reep6 knockout mouse model. Our Reep6-deficient mouse line showed progressive retinal degeneration as previously reported. Nevertheless, unlike the previous report, our Reep6 mutant mice had normal trafficking of PDE6. GCs were not absent from the mutant mice, but their expression decreased by approximately one third. Other membrane phototransduction proteins, such as rhodopsin and rhodopsin kinase (GRK1) were also reduced. Attenuated expression of membrane proteins might stem from abnormal ER and Golgi function, as in vitro expression of REEP6 altered the expression of the ER marker and Golgi morphologies. Additionally, RNA-seq revealed that deletion of Reep6 caused reduced expression of multiple phototransduction proteins at the transcription level and activated the inflammation pathway. Thus, retinal degeneration associated with REEP6 mutations is the consequence of reduced expression of phototransduction proteins mediated by ER and Golgi dysfunction and ensuing retinal inflammation.

pathology↗

bioRxiv2025

Identification of Rapaglutin E as An Isoform-specific Inhibitor of Glucose Transporter 1

Natural products rapamycin and FK506 are macrocyclic compounds with therapeutic benefits whose unique scaffold inspired the generation and exploration of the hybrid macrocycle rapafucins. From this library, a potent inhibitor of the facilitative glucose transporter (GLUT), rapaglutin A (RgA) was previously identified. RgA is a pan-GLUT inhibitor of Class I isoforms GLUT1, GLUT3, and GLUT4. Herein, we report the discovery of rapaglutin E (RgE). Unlike RgA, RgE is highly specific for GLUT1. Further characterization revealed that RgE and RgA likely bound to distinct sites on GLUT1 despite their shared FKBP-binding domain, suggesting that the distinct effector domains of RgE and RgA play key roles in recognition of GLUTs. TOC GRAPHIC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=168 SRC="FIGDIR/small/641094v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@d69b12org.highwire.dtl.DTLVardef@15ee120org.highwire.dtl.DTLVardef@e2495org.highwire.dtl.DTLVardef@83e270_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2025

Deviant functional connectivity patterns in the EEG and their potential use for dyslexia screening

Developmental dyslexia (DD) is a common learning disorder with potential neural origins. While EEG-based brain activation measures combined with machine learning have shown promise for DD screening, these approaches often lack validation on independent participants, which is a crucial step for practical application. This study developed an EEG-based screening approach and investigated the neural correlates of DD in Chinese children. EEG signals were recorded from 130 children (82 with DD, 48 typically developing) aged betweeen 7 and 11 during resting-state and working memory tasks. The EEG data were preprocessed into clean segments to compute functional connectivity (FC) matrices across four frequency bands (delta, theta, alpha, beta). The segments were split into two independent samples, ensuring independence at the participant level: Sample 1, used for training and five-fold cross validation of the convolutional neural networks, and Sample 2, used for cross-sample validation with the trained model. The beta-band FC index in the eyes-open condition achieved the highest within-sample classification accuracy (98%) and cross-sample accuracy (70%, p < .001). Discriminative FC patterns revealed that children with DD exhibited reduced temporal-parietal and central connectivity but increased frontal-central connectivity, likely reflecting compensatory mechanisms. Within the DD group, stronger FCs showed significant negative correlations with Chinese word reading accuracy and fluency. These findings suggest that EEG-based FC measures can effectively distinguish DD and reveal neural markers associated with impaired reading performance. This approach shows promise for noninvasive screening and deeper insight into the neural basis of DD, particularly in non-alphabetic language systems.

neuroscience↗

bioRxiv2025

Application of machine learning to discriminate photoreceptor cell species in xenotransplanted chimeric retinas

Photoreceptor transplantation is being studied to improve visual function in retinal diseases causing blindness, such as age-related macular degeneration, hereditary eye diseases, and traumatic retinopathy, among others. Preclinical studies often involve the delivery of exogenous human photoreceptor cells into the retinas of animal models. In such experiments, a key readout is the differential frequency of donor cell somatic integration versus artificial labeling secondary to material transfer of cytosolic or nuclear labels from donor to recipient cells. For this analysis, the ability to recognize photoreceptor nuclei as being of donor (human) versus animal is key, but purely immunohistology discrimination can be challenging because of antigenic species overlap or intercellular antigen transfer. To address this challenge, we sought to develop and validate a computational technique to discriminate between photoreceptor cells of different animal species based on machine learning of nuclear morphology. Here, we aimed to evaluate the feasibility of using computer-assisted detection of separate nuclei and employing random forest classification to automate the species differentiation, among DAPI-stained photoreceptors after xeno-transplantation of human photoreceptors into the retinas of mice and pigs. Our models were trained on single-species samples and validated with mixed-species samples. We then transplanted human embryonic stem cell-derived retinal organoid cells into rodent and pig retinal degeneration models. The random forest model accurately determined cell identity post-xenotransplantation, validated by histological assessment using an anti-human nuclear antibody. Our results support the potential efficacy of employing machine learning image analysis and classification techniques that may promote experimental rigor, minimize observer bias, and enable high throughput semi-automated workflows for transplantation outcomes analysis. The methodological framework reported here may enable a more nuanced and precise analysis of the behavior of transplanted photoreceptors for the purposes of human retinal regeneration.

neuroscience↗

bioRxiv2025

Inhibiting B-cell-mediated Immunosuppression to Enhance the Immunotherapy Efficacy in Hepatocellular Carcinoma

BackgroundImmunotherapy is efficacious in hepatocellular carcinoma (HCC), but the benefits are limited to a minority of patients. Most HCC patients show resistance to immune checkpoint blockade (ICB). Agonists of the stimulator of interferon genes (STING), potent immune stimulators, showed limited effectiveness. Using preclinical models, we studied the mechanisms of resistance to ICB and STING agonism. MethodsMurine HCA-1 and RIL-175 HCCs were orthotopically grown in mice with underlying liver fibrosis, to mimic the presentation of human HCC. Established tumors were treated with a STING agonist (BMS-986301) or anti-PD1 ICB, and mice were followed to evaluate safety and efficacy, as well as the mechanisms of treatment resistance by RNA sequencing, flow cytometry, and immunofluorescence, B-cell depletion and T-cell immunoglobulin and mucin domain 1 (TIM-1) ICB. ResultsUnbiased analyses of transcriptomic data from murine HCC tissues from ICB-treated mice showed an increased abundance of intratumoral CD8+ T cells and B cells. STING agonism alone showed efficacy in the ICB-responsive RIL-175 HCC model but more limited efficacy in the ICB-resistant HCA-1 model. STING agonism increased circulating IL-10 and intratumoral infiltration by B-cells, including TIM-1+ B cells, and promoted the formation of tertiary lymphoid structure (TLS)-like structures, especially in the peritumoral areas. Strikingly, adding B cell depletion to ICB or STING agonism treatment significantly increased survival. Interestingly, unlike ICB, STING agonism also had a pronounced anti-metastatic activity. In addition, the combination of STING agonism and TIM-1 blockade augmented B cell differentiation and antigen presentation in vitro and improved the anti-tumor effects in murine HCC in vivo. This approach decreased the number of TIM-1+ B cells in the tumor and shifted B cells to higher expression of CD86 and MHC class II, enhancing the antigen presentation capability and further boosting the antitumor efficacy of CD8+ cytotoxic T cells. ConclusionOur findings demonstrate that B cells are associated with ICB- and STING-mediated therapy resistance, and that depleting B-cells or targeting TIM-1 enhances both innate and acquired therapeutic efficacy in HCC.

cancer biology↗

bioRxiv2025

DEK::NUP214 acts as an XPO1-dependent transcriptional activator of essential leukemia genes

The t(6;9)(p22.3;q34.1) translocation/DEK::NUP214 fusion protein defines a distinct subgroup of younger AML patients classified as a separate disease entity by the World Health Organization. DEK is a nuclear factor with multifunctional roles, including gene regulation, while its fusion partner, NUP214, plays a pivotal role in nuclear export by interacting with transport receptors such as XPO1. However, the precise mechanism by which DEK::NUP214 drives leukemia remains unclear. A comprehensive multi-omics comparison of 57 AML primary samples (including whole genome sequencing, targeted sequencing, transcriptomics, and drug screening with > 500 compounds) revealed that t(6;9) cases display a selective response to XPO1 inhibitors (Selinexor & Eltanexor) and a distinct transcriptomic signature characterized by the overexpression of FOXC1 and HOX genes that are key leukemia mediators. CUT&RUN experiments demonstrated the direct binding of DEK::NUP214 to the promoters of FOXC1 and HOXA/B clusters. Strikingly, the expression of these genes and the binding of DEK::NUP214 to their regulatory regions were selectively reduced upon XPO1 inhibition in t(6;9) cells. Altogether, these results identified a novel function of DEK::NUP214 as an XPO1-dependent transcriptional activator of key leukemia drivers and provide a rationale to explore the use of XPO1 inhibitors in this patient population.

cancer biology↗

bioRxiv2025

Spatial transcriptomics elucidates the central role of cerebral vasculatures in the progression of Japanese encephalitis

The cellular and molecular mechanisms underlying the neuropathology of Japanese encephalitis virus (JEV) remain obscure. Herein, we designed Stereo-seq chips to simultaneously capture the in situ transcriptomes of both the host and JEV, constructing a comprehensive spatiotemporal pathological landscape for Japanese encephalitis (JE). This study reveals the central role of the vascular system in JE pathogenesis, particularly the meninges, which displayed the strongest signal of inflammation and cell death in the JEV-infected brain. The activation of the Ackr1+ endothelial cells, disruption of the blood-brain barrier, the migration of JEV-infected monocytes, secretion of immune factors by the infected cells, and the occurrence of pyroptosis and necroptosis form a positive feedback loop, resulting in an increasing influx of immune cells and tissue damage. JEV infection leads to neurological impairments, which may be attributed to the interaction between viral proteins and host cellular factors such as Stat1, Stat3, Nfkb1, and Sp1. As the vascular system serves as a central receiver and amplifier of inflammatory signals, regulating inflammation within the vascular system is essential in mitigating JE progression.

immunology↗

bioRxiv2025

The Th1/Th17 axis regulates chimeric antigen receptor (CAR) T cell therapy toxicities

CAR-T therapy has led to significant improvements in patient survival. However, a subset of patients experience high-grade toxicities, including cytokine release syndrome (CRS) and immune cell-associated hematologic toxicity (ICAHT). We utilized IL-2R knockout mice to model cytokine toxicities with elevated levels of IL6, IFN{gamma}, and TNF and increased M1-like macrophages. Onset of CRS was accompanied by a reduction in peripheral blood neutrophils due to disruption of bone marrow neutrophil homeostasis characterized by an increase in apoptotic neutrophils and a decrease in proliferative and mature neutrophils. Both non-tumor-bearing and E-ALL tumor-bearing mice recapitulated the co-occurrence of CRS and neutropenia. IFN{gamma}-blockade alleviated CRS and neutropenia without affecting CAR-T efficacy. Mechanistically, a Th1-Th17 imbalance was observed to drive co-occurrence of CRS and neutropenia in an IFN{gamma}-dependent manner leading to decreased IL-17A and G-CSF, neutrophil production, and neutrophil survival. In patients, we observed an increase in the IFN{gamma}-to-IL-17A ratio in the peripheral blood during high-grade CRS and neutropenia. We have uncovered a biological basis for ICAHT and provide support for the use of IFN{gamma}-blockade to reduce CRS and neutropenia. Statement of SignificanceDespite clinical success of CAR-T therapy, patients develop toxicities such as cytokine release syndrome and neutropenia, whose co-occurrence impacts their survival and quality-of-life. We recapitulate these toxicities in mice to discover their co-occurrence is driven by Th1-Th17 imbalance following CAR-T administration, which can be prevented via IFN{gamma} blockade.

cancer biology↗

bioRxiv2025

Re: Concerns Regarding the Validation of ZYS-1 as a Bona Fide ADAR1 Inhibitor

Wang et al. in Nature Cancer report ZYS-1 as an ADAR1 inhibitor and present biochemical and cellular evidence to support ZYS-1s direct interaction with and inhibition of ADAR1, including enzymatic assays, surface plasmon resonance (SPR), drug affinity responsive target stability (DARTS), and cellular thermal shift assays (CETSA). We raise critical methodological concerns regarding the validation of ZYS-1 as a bona fide ADAR1 inhibitor. Our primary concern relates to the misuse of an adenosine deaminase (ADA) activity assay kit for ADAR1 enzymatic activity characterization. Using established biochemical assays with direct inosine quantification, we evaluated ZYS-1s inhibitory activity against ADAR1 using physiologically relevant RNA substrates. The compound showed no inhibitory activity at concentrations up to 1 mM. We demonstrate that the ADA assay kit used by Wang et al. does not reflect ADAR1-specific activity, and ZYS-1 is unable to inhibit ADAR1 in well-validated biochemical assays. We urge for further validation using ADAR1-specific assays to establish ZYS-1 as a genuine ADAR1 inhibitor.

pharmacology and toxicology↗

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↗