Biology subjects

Zhao, J.

Publications and source records attributed to Zhao, J..

At least 127 records · Page 7Linked to original sources

bioRxiv2025

Single-cell transcriptomic dynamics exposes hidden survival trajectory under antibiotic treatment

Heterogeneity plays a major role in bacterial resistance to antibiotic treatment while the mechanism at single-cell level is largely unknown. Here, we employed a robust integration of bulk and bacterial single-cell RNA-seq (scRNA-seq) to uncover how individual cells of Acinetobacter baumannii reorganise the heterogenous transcriptome in response to antibiotic. Using polymyxin as a representative, bulk RNA-seq showed canonical envelope- and efflux-centred responses but obscured underlying heterogeneity. Single-cell profiling resolved these averages into discrete subpopulations whose abundances shifted with concentration and time. Specifically, in early time an envelope-stress programme predominated survival at the low concentration, whereas an outer-membrane repair/efflux programme dominated survival at the high concentration. These patterns revealed structured and time-resolved heterogeneity, highlighting an ingenious bacterial stress responsive strategy. Through trajectory inference, we further revealed a concentration-dependent bifurcation of cell fates: low-concentration treated cells detoured through a transient stress state and rejoined growth, whereas high-concentration treated survivors diverted into a slow-growing, tolerant branch. Perturbing marker genes from these programmes altered fitness eventually and rapidly increased permeability, depolarisation and reactive-oxygen burden, linking state to survival capability. Collectively, we map a dynamic, concentration-structured landscape of antibiotic responses at the single-cell level, revealing diverse survival trajectories that are obscured in conventional population-averaged analyses. Our developed single-cell based framework revealed tolerant bacterial cells with rewiring of the transcriptional landscape, causing emergence of antibiotic resistance. Importantly, these findings urge precision antimicrobial therapy in patients to minimise emergence of antibiotic resistance.

microbiology↗

bioRxiv2025

Spatial Flavonoid Accumulation in Soybean Pericycle Restricts Phytophthora sojae Invasion

Root immunity relies on coordinated defenses across distinct tissues, yet the underlying cellular mechanisms remain unclear. Here, we integrated single-cell transcriptomics, spatial metabolomics, and genetic manipulation to dissect soybean (Glycine max) interactions with Phytophthora sojae. In resistant Williams82 (Wm82) roots, P. sojae hyphae were excluded from the stele, exhibiting negative tropism toward the pericycle. scRNA-seq revealed that this resistance is mediated by infection-induced pericycle cells expressing high levels of flavonoid biosynthetic genes, including GmCHS7 and GmCHI4A. CRISPR-Cas9 knockout of these genes compromised resistance, whereas overexpression enhanced immunity in susceptible cultivars. Metabolomic and spatial metabolic analyses identified naringenin, a flavonoid phytoalexin, as a key antimicrobial compound that specifically accumulates in pericycle-adjacent tissues of Wm82 during infection. Naringenin directly inhibited hyphal growth in vitro and enhanced resistance when applied exogenously. These findings uncover a spatially targeted immune strategy where pericycle-localized activation of flavonoid synthesis forms a chemical barrier to safeguard vascular integrity, highlighting pericycle-centered metabolic immunity as a target for engineering durable resistance.

plant biology↗

bioRxiv2025

Emergence of Individualized Functional Topography in the Neonatal Brain

The early postnatal period represents a critical phase for establishing the brains fundamental architecture. However, how individualized functional topography emerges and shapes long-term cognition remains unknown. Using multimodal neuroimaging data from 419 neonates, we map personalized functional topographies in the first weeks of life and reveal their association with 18-month neurocognitive outcomes. Unique and stable functional topographies are already present at birth, with interindividual variability organized along a conserved sensorimotor-to-association hierarchy. These individualized maps encode early brain maturity and robustly predict cognitive, language, and motor outcomes at 18-month of age, with predictive features concentrated at network boundaries. This functional refinement is structurally anchored by concurrent maturation in cortical myelination and sulcal depth. Preterm birth results in distinctive topographic alterations characterized by accelerated maturation of association networks. Our work establishes a foundation for precision models of early brain development and elucidates its significance for long-term neurocognitive outcomes.

neuroscience↗

bioRxiv2025

Convergent and divergent spatial topographies of individualized brain functional networks and their developmental origins

The human brain is intrinsically organized into canonical functional networks with distinct spatial topographies. While precision functional mapping delineates individualized topographies of single networks, the spatial coordination among networks and its developmental origin remains largely unknown. Here, we propose functional topography covariance analysis (FOCA), a novel framework that quantifies convergent and divergent spatial alignments across individualized functional networks and further delineates their internetwork relationships, neurobiological basis, ontogenetic layouts, and cognitive outcomes. Across two well-established task-free functional MRI (fMRI) datasets encompassing both conventional and densely sampled scans, FOCA consistently revealed self-clustered hierarchies in the coordination of functional topographies, closely aligned with existing functional gradients and characterized by convergent couplings within primary systems and divergent couplings in higher-order systems. Such pattern was well predicted by fundamental neurobiological attributes, especially aerobic glycolysis. In a large public neonatal cohort, FOCA matrix exhibited adult-inverted hierarchical couplings and marked changes in auditory and action-mode networks, primarily driven by prominent redistributions of negative couplings. Moreover, neonatal FOCA profiles in the primary visual system significantly predicted neurodevelopmental outcomes at 18 months. Finally, compared with conventional functional connectivity (FC), FOCA proved more robust to global signals and more sensitive to the maturation of negative couplings. These findings highlight the critical role of negative connectivity in brain functional reorganization and advance our understanding of the cooperative and competitive relationships among functional systems and their developmental origins.

neuroscience↗

bioRxiv2025

Immature C. elegans motor neurons control early embryo behavior via both synaptic and non-synaptic GABA release

Pre-natal brain activity has long lasting effects on subsequent neurodevelopment. It is unclear if early brain activity is dominated by cell intrinsic, synaptic, or non-synaptic mechanisms. We address this question by analyzing C. elegans embryo behavior in snf-11 mutants, which lack a plasma membrane GABA re-uptake pump (orthologous to GAT1). At 510-570 minutes post-fertilization, embryo motion was transiently and potently inhibited in snf-11 GAT1 mutants, which precedes formation of most nerve ring synapses. This transient motion inhibition requires GABA synthesis in DD motor neurons and UNC-49 GABAA receptors in body muscles. When motion inhibition occurs, DD neurons have not yet completed neurite outgrowth. Genetic analysis suggests that motion inhibition was mediated by both synaptic and tonic GABA release from DD motor neurons. These results suggest that DD neurons control embryo behavior prior to completing their developmental maturation. Significance StatementLittle is known about how prenatal circuits control embryo behavior. We show that the motion of early C. elegans embryos is transiently inhibited by immature GABAergic motor neurons that have not yet completed neurite outgrowth. GABAs inhibitory effect on early embryo behavior occurs before most synapses have formed in the worms central neuropil. For this early behavior, we find that synaptic GABA release plays a minor role while non-synaptic mechanisms predominate. Our results suggest that non-synaptic forms of GABA transmission play a significant role in prenatal circuits.

neuroscience↗

bioRxiv2025

FERAL: A Video-Understanding System for Direct Video-to-Behavior Mapping

Quantifying animal behavior often requires segmenting continuous actions into discrete, interpretable states, yet most automated pipelines infer actions from keypoint dynamics and are limited by keypoint tracking quality. Here we present FERAL (Feature Extraction for Recognition of Animal Locomotion), a supervised video-understanding toolkit that maps raw video directly to frame-level behavioral labels, bypassing the keypoint-extraction and pose-classification stages of conventional pipelines. Across benchmarks, FERAL matches or exceeds state-of-the-art pose- and video-based baselines. On the CalMS21 mouse social-interaction benchmark, it exceeds Googles VideoPrism using only a quarter of the training data. FERAL generalizes across species (apes, zebras, mice, ants, flies, and nematodes), recording conditions, and levels of organization, from single animals to social interactions and colony-scale collective behavior. Released as a user-friendly, open-source package, it integrates with existing analysis pipelines. By enabling scalable, species-agnostic behavioral quantification directly from raw video, FERAL broadens the experimental paradigms available for studying animal behavior.

animal behavior and cognition↗

bioRxiv2025

YAP1 Depletion Enhances TAZ and its Complexation with TEAD4 and AP-1 Heterodimer C-JUN/FOSB to Promote Gastric Cancer Progression and Metastases

BackgroundDysregulation of the Hippo signaling pathway, characterized by aberrant activation of the transcriptional coactivators YAP1 and TAZ, drives tumour progression, immunosuppression and metastasis. Hippo pathway components are emerging therapeutic targets in several solid tumours, however, the expression profiles of Hippo coactivators YAP1, TAZ and their transcriptional factors TEAD1-4 in gastric cancer peritoneal metastases (GCPMs) and their therapeutic value are unknown. ObjectiveTo determine expression status of YAP1, TAZ and TEAD1-4 in GCPMs; and to evaluate whether dual targeting of YAP1 and TAZ provides superior antitumour activity compared with inhibition of either coactivator alone. DesignExpression of YAP1, TAZ and TEAD1-4 was examined in GCPMs by single-cell RNA sequencing and co-immunofluorescent staining. Functional studies using genetic knockout and antisense oligonucleotide (ASO) inhibition of YAP1 or TAZ were performed to assess antineoplastic effects in vitro and in vivo. Co-immunoprecipitation and luciferase reporter assays were used to characterize YAP1/TAZ interactions with TEADs and AP-1 components (JUN and FOSB) and to quantify transcriptional activity. Antitumour efficacy was validated in patient-derived xenograft (PDX) and KP-Luc2 syngeneic models. ResultsYAP1, TAZ, and TEADs1- 4 were highly coexpressed in GCPMs and correlated with poor survival. YAP1 inhibition alone elicited compensatory upregulation of TAZ, while combined inhibition of both coactivators maximally repressed cell proliferation and invasion in vitro, and tumor growth in vivo. Increased TAZ complexation with TEAD4 and AP-1 (c-JUN and FOSB) heterodimer was observed following YAP1 knockdown or pharmacological ASO inhibition. Dual inhibition of YAP1 and TAZ was required to maximally suppress YAP1/TAZ expression and reduce their nuclear accumulation, transactivation of TEAD, and activation of downstream genes. ConclusionsThese findings show that combined YAP1 and TAZ inhibition holds promise for the treatment of GCPMs, a highly lethal disease with an urgent need for novel treatment options. WHAT IS ALREADY KNOWN ON THIS TOPICO_LIGastric cancer with peritoneal metastasis (GCPM), occurring in > 45% of gastric cancer (GC) patients, is a highly lethal malignancy with limited therapeutic options. C_LIO_LIThe Hippo pathway mediator Yes-associated protein 1 (YAP1) is intimately involved in chemoresistance, cancer stemness properties, and the epithelial-to-mesenchymal transition in gastric and other cancers. C_LIO_LIWhile YAP1 represents a promising therapeutic target, clinical trial of YAP1 antisense oligonucleotides has been disappointing. C_LI WHAT THIS STUDY ADDSO_LIHippo coactivators YAP1, TAZ and their main transcription factors TEAD1-4 are markedly upregulated in GCPMs and associated with poor prognosis. C_LIO_LIAntisense targeting of YAP1 results in compensatory upregulation of its paralog TAZ. C_LIO_LIUpon YAP1 depletion, TAZ forms transcriptional complexes with TEAD4 and the AP-1 heterodimer (JUN and FOSB). C_LIO_LIDual targeting of YAP1 and TAZ, by oligonucleotides, achieves maximal suppression of tumour growth in vitro and in vivo. C_LI HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICYO_LIThese findings provide a strong mechanistic rationale for co-targeting YAP1 and TAZ as a therapeutic approach in metastatic gastric cancer. C_LIO_LIDual Hippo coactivator inhibition could inform the design of future clinical trials aimed at improving outcomes for patients with GCPMs. C_LI

cancer biology↗

bioRxiv2025

Integrated Bioinformatics analysis and Metabolomic Responses in finding novel therapeutic approach to treat viral myocarditis

BackgroundMyocarditis is one of the most common health problems in young people. Despite imaging techniques and endomyocardial biopsies advancing, there is still inadequate for myocarditis characterization. Some studies have shown that myocarditis is closely associated with mitochondrial dysfunction. Therefore, this study was aimed to identify mitochondrial-related biomarkers and gene regulatory networks in myocarditis and potential therapeutic targets. MethodsWe downloaded GSE95368 dataset from GEO to get myocarditis gene expression profiles, then used EdgeR and AI algorithm for bioinformatics analysis of DEGs functions. Established CVB3-induced mouse myocarditis model via intraperitoneal injection, and assessed energy metabolism differences using targeted metabolomics. CVB3 stimulus induced myocarditis in H9C2 cells. We assessed mitochondrial dysfunction (ATP, MMP) with commercial kits, MAPK8 release via ELISA, and MAPK8, p-PI3K, p-AKT levels by western blot. Furthermore, a total of 8 patients primarily diagnosed with myocarditis were enrolled, and levels of MAPK8 and CK in serum were detected. SP600125, an inhibitor of MAPK8, was administrated to CVB3-infected mice to study its potential protective effect in viral myocarditis. ResultsWe obtained 77 DEGs enriched in myocarditis. Analysis yielded 11 modules, MEpurple module genes linked to myocarditis progression were identified via WGCNA. MAPK8, NAMPT and ALB are associated with mitochondrial function. CVB3-infected mice showed cardiac inflammation and high MAPK8 expression in serum or heart tissues.The target metabolism results indicated altered central carbon metabolism distinguished CVB3 group from control, with higher D-Glucose-1-phosphate and D-Glucose-6-phosphate and lower L-Cystine, dCMP, IMP and Xylulose-5-phosphate levels. CVB3 treatment caused mitochondrial dysfunction in H9C2 cells (decreased ATP, MMP), and increased MAPK expression. Western blot showed MAPK8 consolidated the levels of p-PI3K and p-AKT. CK activity was notably higher in myocarditis patients than healthy individuals. MAPK8 levels in myocarditis patients serum also exceeded those in healthy individuals. Pearson analysis indicated that MAPK8 and CK may contribute to myocarditis progression via distinct mechanisms. In CVB3-infected mouse model with SP600125 treatment, cardiac inflammation and MAPK8, p-PI3k, p-AKT expression were reduced, confirming MAPK8s crucial role in viral myocarditis. ConclusionOur study identified MAPK8 as a key biomarker of myocarditis, and it may be a potential therapeutic target for myocarditis.

pathology↗

bioRxiv2025

Morphological Identification of Ticks in district Swabi, Mardan, and Charsadda

Ticks are ectoparasitic arthropods that play a significant role in transmitting pathogens to humans and animals. This study aimed to address the research gap in understanding the morphological diversity and distribution of tick species in Swabi, Mardan, and Charsadda districts of Pakistan, where tick-borne diseases are prevalent but poorly documented. The primary objectives were to identify tick species, document their morphological characteristics, and map their distribution patterns across different habitats. Field surveys were conducted over nine months, collecting tick specimens from forests, grasslands, and residential areas. Specimens were preserved and analyzed using stereo-zoom microscopy and taxonomic keys for accurate classification. Key findings revealed a diverse tick fauna, including hard ticks (Ixodidae), with variations in body size, colour patterns, capitulum shape, and scutum features. Some species were widely distributed across all three districts, while others exhibited localized patterns. The study provides the first comprehensive morphological identification of tick species in these regions, highlighting their potential role in disease transmission. The implications of this research are significant for public health and disease control. The data can inform targeted interventions, enhance disease surveillance programs, and support the development of preventive measures to mitigate tick-borne diseases. By contributing to tick taxonomy and epidemiology, this study lays the groundwork for protecting public health in the study regions and beyond. This study addresses the lack of data on tick diversity in high-prevalence regions of Pakistan, providing critical insights for disease control and public health strategies. Limited information exists on the morphological diversity and distribution of tick species in Swabi, Mardan, and Charsadda districts. To identify tick species, document morphological characteristics, and map their distribution patterns in the study areas. Field surveys, specimen collection, stereo-zoom microscopy, and taxonomic classification were employed over nine months. Diverse tick fauna was identified, including hard ticks, with variations in morphology and distribution. Some species were widespread, while others were localized, highlighting potential disease transmission risks. The findings support targeted interventions, disease surveillance, and preventive measures, contributing to public health protection and tick-borne disease control in the region.

zoology↗

bioRxiv2025

ProAffinity++

Proteins are essential biological macromolecules that play a crucial role in living organisms. Protein-protein interactions, which govern various biological processes such as signal transduction, cell metabolism, and cell growth, are key aspect of protein function. The strength of these interactions, characterized by protein-protein binding affinity({Delta}G), is a critical thermodynamic property of protein complexes. Accurate prediction of protein-protein binding affinity is meaningful for understanding the mechanisms of biological systems and improving the speed of binding affinity determination. However, current methods are limited in their accuracy and are primarily designed for binary complexes. To address these limitations, we propose ProAffinity++, an end-to-end algorithm that predicts binding affinities using a combined representation of sequence and structure. The core idea of ProAffinity++ is to model the binding regions of protein complexes and utilize graph neural networks to capture the local microenvironment of residues. Our experimental evaluations demonstrate that ProAffinity++ outperforms state-of-the-art methods in predicting protein-protein binding affinities. Moreover, it exhibits remarkable performance in challenging scenarios, such as antigen-antibody interactions and missense mutation problems, where existing methods have limitations.

bioinformatics↗

bioRxiv2025

Inhibition of CGRP receptor ameliorates AD pathology by reprogramming lipid metabolism through HDAC11/LXRβ/ABCA1 signaling

The Calcitonin gene-related peptide (CGRP) receptor has gained attention in Alzheimers Disease (AD) research due to its involvement in regulating neuroinflammation. However, its role and mechanism in AD pathology remain unclear. Here, we demonstrate that CALCRL, a core component of the CGRP receptor, is upregulated in the hippocampus of AD dementia patients and 5xFAD mice. Knockout of the CGRP receptor ligand Calca or pharmacological blockade using Rimegepant (Rim), reduces soluble A{beta}1-42 oligomer-induced neuronal death and glial inflammation. Rim treatment also rescues neurobehavioral impairments, neurodegeneration, and lipid metabolism dysfunction in 5xFAD mice. Mechanistically, these effects are mediated through HDAC11 inhibition, which enhances LXR{beta} acetylation and ABCA1 expression, promoting the reprogramming of neuronal lipid metabolism. Importantly, this CALCRL/HDAC11/LXR{beta}/ABCA1 axis is conserved across both humans and mice. Our findings uncover a novel mechanism underlying AD pathogenesis and highlight the therapeutic potential of targeting CGRP signaling in AD. HIGHLIGHTSInhibition of CGRP receptor ameliorates disease pathology in models of AD HDAC11 mediates CGRP receptor function in AD HDAC11 is a pivotal regulator in lipid metabolism by LXR{beta}/ABCA1 signaling The HDAC11/LXR{beta}/ABCA1 axis is conserved in AD humans and mice

neuroscience↗

bioRxiv2025

Adaptive Multimodal Temporal Transformer for Bio Signal Driven Stroke Rehabilitation Prognosis

Stroke rehabilitation requires continuous, individualized assessment of recovery progress to optimize treatment planning. Existing prognosis models often rely on static, single-timepoint predictions and lack adaptive fusion of multi-modal bio-signals, limiting their clinical interpretability and utility. To address these challenges, we propose AMTT-Net, an adaptive multimodal temporal transformer for dynamic stroke rehabilitation prognosis. AMTT-Net integrates wearable biosensor data, video keypoints, and clinical records through an attention-based Adaptive Fusion Module and Trajectory-Aware Prediction Heads to jointly predict continuous recovery trajectories and responder likelihoods under different rehabilitation modalities. Evaluations on the StrokeBalance-Sim dataset demonstrate that AMTT-Net achieves superior performance in both trajectory regression and responder classification tasks, while providing interpretable, patient-specific insights to support personalized rehabilitation strategies.

bioengineering↗

bioRxiv2025

Targeting the host factor HGS-viral membrane protein interaction in coronavirus infection

While current antivirals primarily target viral proteins, host-directed strategies remain underexplored. Here, we performed a genome-wide CRISPRi screening to identify the host protein, Hepatocyte Growth Factor-Regulated Tyrosine Kinase Substrate (HGS), as essential for the pan-coronaviruses infection both in vitro and in vivo. Mechanistically, HGS directly interacts with the viral membrane (M) protein, facilitating its trafficking to the ER-Golgi intermediate compartment (ERGIC) for virion assembly. Conversely, HGS deficiency caused M retention in the ER, blocking assembly. Leveraging this interaction, we designed M-derived peptides and screened over 5,000 FDA-approved drugs, identifying riboflavin tetrabutyrate (RTB). Both the peptides and RTB bind HGS and disrupt its interaction with the M protein, leading to M retention in the ER and subsequent blockade of virion assembly. These agents demonstrated broad anti-pan-coronavirus activity in vitro and in vivo. Collectively, our findings establish HGS as a druggable host target and identify RTB as a promising broad-spectrum antiviral candidate.

microbiology↗

bioRxiv2025

scGPD: single-cell informed gene panel design for targeted spatial transcriptomics

In targeted spatial transcriptomics technologies, a key challenge is to select an informative gene panel that captures the complexity of cellular and spatial heterogeneity within tissues. Many existing methods use prior knowledge or heuristic selection rules, such as selecting highly variable genes, which overlook gene-gene correlations and may consequently result in suboptimal coverage. To address the limitations of the existing methods, we introduce scGPD, a deep learning-based framework for gene panel design that leverages single-cell RNA-seq data to identify compact, nonredundant sets of genes for spatial profiling. scGPD uses a gene-gene correlation-aware gating mechanism to extract informative features from data, encouraging diversity among selected genes and eliminating redundancy. Across diverse single-cell datasets, scGPD outperforms existing gene panel design methods in recovering transcriptome-wide expression using a limited number of genes. When applied to spatial transcriptomics data, it achieves superior cell type classification accuracy, demonstrating strong generalization across modalities. The gene panels selected by scGPD further exhibit well-defined spatial expression patterns, highlighting their robustness and relevance for spatial analysis. The scGPD framework is flexible and can be adapted to multiple use cases, enabling the prioritization of genes relevant to specific diseases or phenotypes. Together, these results demonstrate that scGPD provides a robust and adaptable solution to design efficient gene panels for spatial transcriptomics, with broad applicability to tissue mapping and disease characterization.

bioinformatics↗

bioRxiv2025

Accurate and efficient phylogenetic inference through end-to-end deep learning

Accurate phylogenetic inference is crucial for understanding evolutionary relationships among species. Deep learning technique has been introduced for phylogenetic inference; however, the existing deep learning-based approaches either suffer from limited accuracy as they split inference into several disjoint stages, or exhibit low efficiency and hardly apply to the cases with over 20 species. Here we present an accurate and efficient approach to phylogenetic inference. Our approach, called NeuralNJ, employs an end-to-end framework that directly constructs phylogenetic trees from the input taxa, thus effectively avoiding the inaccuracy incurred by the split inference stages. The key innovation of NeuralNJ lies in its learnable neighbor joining mechanism, which iteratively joins neighbors guided by learned priority scores and thereby achieves accurate tree reconstruction. The inference accuracy is further enhanced through incorporating reinforcement learning-based tree search. Using both simulated and empirical data as representatives, we demonstrate that NeuralNJ can effectively infer phylogenetic tree with improved computational efficiency and reconstruction accuracy. The study paves the way to accurate and efficient phylogenetic inference for hundreds of taxa in complex evolutionary scenarios.

bioinformatics↗

bioRxiv2025

A New Aneurysm Rupture-Prone Marfan Mouse Model with FBN1Q2467X Nonsense Mutation Reveals Adventitial Inflammation

Marfan syndrome (MFS) is a genetic disorder caused by mutations in fibrillin-1(FBN1), which encodes FBN1, a key structural component of the extracellular matrix. Mutations in FBN1 influence the severity of aortic disease and therapeutic responses, with aortic aneurysm being the leading cause of mortality in patients with MFS. To investigate the mechanisms driving aneurysm progression, we generated a mouse model (Fbn1Q2469X/+) carrying the FBN1Q2467X nonsense mutation identified in MFS patients. This mutation results in FBN1 deficiency. Although Fbn1Q2469X/+ mice appear normal, showing only mild, nonprogressive dilation of the aortic root and ascending aorta with minor reductions in blood pressure, homozygous Fbn1Q2469X/Q2469X mice develop spontaneous thoracic aortic aneurysms (TAA) that progress to rupture between 10 and 25 days of age, with 100% penetrance. Histopathology shows progressive vessel wall degeneration characterized by disorganized vascular smooth muscle cells, collagen loss, and elastic fiber fragmentation from early to late stages. RNA-seq analysis identifies inflammation as the dominant process in late-stage aneurysms. Immunofluorescence assay reveals inflammatory cells prominently localized to the adventitia near rupture sites, linking adventitial inflammation to aneurysm progression. This genetically modified Fbn1Q2469X/Q2469X mouse model consistently develops progressive aortic aneurysms and provides a reliable, cost-effective platform to investigate the molecular mechanisms of aneurysm progression and to evaluate therapeutic strategies in aneurysm diseases, including Marfan syndrome and related disorders.

genetics↗

bioRxiv2025

Dual Modes of Gene Regulation by CDK12

The process of transcription is driven forward by the activity of kinases including CDK7, CDK9 and CDK12. Accordingly, acute inhibition of any of these kinases results in profound downregulation of gene expression. Here, we discover that loss or inhibition of CDK12 also significantly upregulates a set of coding and non-coding loci, whose activation could contribute to the anti-proliferative effects of CDK12 inhibitors. Mechanistically, CDK12 inhibition impairs transcription elongation, leading to increased RNA polymerase II termination or arrest in long genes. However, short genes such as MYC and enhancer RNAs are highly transcribed in the absence of CDK12 activity. Indeed, in HER2+ breast cancer, a malignancy where CDK12 is co-amplified with HER2 and its expression correlates with disease status, CDK12 inhibition markedly elevates MYC expression to induce lethality. The dual effects of CDK12 inhibition elucidated herein clarify its role in transcriptional control and have significant translational implications.

cancer biology↗

bioRxiv2025

Loss of the tumor suppressor PTEN activates cell-intrinsic interferon signaling to drive immune resistance

Loss of the tumor suppressor PTEN is strongly associated with a lack of response to immune checkpoint blockade therapies in cancer patients, but the underlying mechanisms are not fully understood. We have developed a transformation model where knocking out PTEN in human mammary epithelial cells drives dependence on the p110{beta} subunit of PI3K and, notably, elicits a robust induction of endogenous retroviral elements (ERVs) and activation of the interferon signaling. This constitutive cell-intrinsic interferon response, hallmarked by hyperactivated STAT1, is also observed in human tumors with a PTEN-low status. We further find that PTEN deficiency renders cancer cells resistant to the cytotoxic effects of immune cells and interferon-{gamma}. Notably, PTEN loss also results in a dependency on an activated DNA damage response pathway, leading to an exquisite vulnerability to CDK12 inhibition. Our study suggests an interferon adaptation model in which tumors driven by PTEN deficiency inherently activate the interferon response, enabling them to adapt to interferon cytotoxicity and gain resistance to immunotherapies.

cancer biology↗