Biology subjects

Huang, J.

Publications and source records attributed to Huang, J..

At least 109 records · Page 6Linked to original sources

bioRxiv2026

Oxidation-Driven mtDNA B-Z Transition Activates ZBP1 to Mediate Acetaminophen Hepatotoxicity

Acetaminophen (APAP) overdose induces mitochondrial damage in hepatocytes, leading to secondary toxicity that resists to N-acetylcysteine (NAC) treatment and culminates in hepatocyte death and acute liver failure (ALF)1. The underlying mechanisms remain poorly understood, often necessitating liver transplantation2. Here, we identify oxidative modification-driven B-to-Z transitions in mtDNA as the central pathological driver of APAP-induced ALF. Upon APAP exposure, oxidized mtDNA fragments leak into the cytosol, activating ZBP1 signaling via its Z domain. Genetic inhibition of ZBP1 mitigates liver damage and improves survival. Using synthetic 12-bp dGdC duplexes, we demonstrate that 8-oxoG substitution, even under physiological salt concentrations, is sufficient to induce Z-DNA formation, enabling specific ZBP1 binding through its Z domain. The 8-oxoG repair enzyme OGG13, activated by TH107854, removes 8-oxoG modifications and reverses Z-DNA to B-DNA conformation. In mice with lethal APAP toxicity, delayed NAC treatment results in 50% mortality. In contrast, TH10785 monotherapy increases survival to 90%, while its combination with NAC achieves 100% survival. These results define the oxidized mt Z-DNA-ZBP1 axis as a critical driver of APAP hepatotoxicity, providing fundamental insights into DNA conformational dynamics and therapeutic opportunities in drug-induced liver failure.

cell biology↗

bioRxiv2026

Antibody-Dependent Heterotypic Syncytia Drive COVID-19 Inflammation and Disease Progression

Severe COVID-19 is characterized by profound immune dysregulation and excessive inflammation. Aberrant myeloid responses drive hyperinflammation, yet the precise mechanisms remain elusive. Here, we demonstrate that certain spike antibodies promote the formation of heterotypic syncytia between monocytes/macrophages and virus-infected pneumocytes, leading to excessive inflammatory cytokine release. This antibody-dependent syncytium formation requires Fc{gamma}RI (CD64) and ADAM10, as well as the assembly of the six-helix bundle by the spike S2 subunit. Notably, these syncytia exhibit a stronger proinflammatory signature compared to virus-infected epithelial cells. In vivo, sub-neutralizing antibody concentrations amplified inflammation and exacerbated disease in SARS-CoV-2-infected mice without increasing viral burden. Furthermore, scRNA-seq of postmortem lung tissues from COVID-19 patients implicated the monocyte/macrophage-derived syncytia as a key cellular source of inflammatory cytokines. Together, these findings define a novel mechanism of antibody-dependent enhancement of inflammation that helps explain the hyperinflammatory responses in severe COVID-19 and suggest new therapeutic opportunities targeting this pathway.

immunology↗

bioRxiv2026

Compositional decoding of neural activity enhances generalization in handwriting BCIs

Recent brain-computer interfaces (BCIs) have achieved state-of-the-art performance in decoding behavior from neural activity. These models are typically trained on a con-strained set of behaviors, which limits their ability to generalize to real-world settings where behavior is variable, complex, and context-dependent. However, many complex behaviors can be decomposed into a set of reusable behavioral motifs, indicating a compositional organization. Here, we analyze human intracortical neural activity underlying attempted handwriting and find signatures of neural compositionality at a finer resolution than individual letters. We further introduce a compositional temporal decoding model, MOtif-based Temporal Inference Framework (MOTIF), that jointly predicts the fine-scale behavioral motifs (e.g., strokes, phonemes) and the longer-timescale behavior class (e.g., characters, words). We show that the compositional structure leveraged by MOTIF enables improved generalization in few-shot learning. Our results demonstrate that explicitly incorporating compositionality into neural decoders can enhance generalization and sample efficiency, while providing a principled approach to designing more scalable, robust, and interpretable BCIs.

neuroscience↗

bioRxiv2026

Rapid and Quantitative Phage Susceptibility Test by Ramanome

Antimicrobial resistance poses an escalating global threat, renewing interest in bacteriophage therapy as a precision alternative to antibiotics. However, clinical translation remains hindered by the lack of rapid and quantitative phage susceptibility testing (PST) platforms capable of evaluating host range, infection potency, and effective multiplicity of infection (MOI). Here we present RPST, a ramanome-based phenotypic platform that captures infection-induced remodeling of bacterial macromolecular composition to unify these diagnostic requirements within a single workflow. RPST integrates four Raman biomarkers into a Composite Infection Index (CII), enabling rapid and lysis-independent discrimination between susceptible and resistant bacterial populations within [~]1 hour, with 96.0% categorical concordance (24/25) to plaque assays. As a continuous population-level metric, CII quantifies the proportion of infected cells, allowing quantitative ranking of phage potency against shared hosts. By resolving CII trajectories across the MOI and time, RPST further determines the minimal effective MOI, which is the lowest phage-to-bacterium ratio sustaining self-propagating infection, thereby defining the lower boundary for therapeutic feasibility. Together, these capabilities transform PST from static compatibility assays into a dynamic and quantitative framework that bridges in vitro infectivity assessment and infection dynamics relevant to phage therapy. Impact StatementBased on the rapid emergence of antimicrobial resistance, this study introduces RPST, a novel ramanome-based phage susceptibility testing platform. RPST detects phage-induced biochemical remodeling in bacteria within [~]1 hour, achieving 96.0% concordance with gold-standard plaque assays. By integrating four Raman biomarkers into a Composite Infection Index, it not only distinguishes susceptible from resistant strains but also quantifies phage potency and determines the minimal effective multiplicity of infection required for self-sustaining infection. This transformative approach moves beyond binary diagnostics to offer a dynamic, quantitative framework for precision phage therapy, significantly accelerating therapeutic decision-making and enhancing our ability to combat resistant infections.

microbiology↗

bioRxiv2026

Structural basis for the broad recognition specificity of an Arabidopsis immune receptor

Plant nucleotide-binding leucine-rich repeat (NLR) immune receptors typically confer resistance through recognition of specific pathogen effectors. The Arabidopsis NLR WRR4A defies this paradigm by recognizing multiple sequence-divergent effectors from Albugo candida, conferring resistance to multiple pathogen races. Despite minimal sequence similarity, these effectors share a conserved N-terminal ferredoxin-like fold. Through cryo-EM structure determination of two WRR4A resistosomes bound to sequence-distinct effectors, combined with AlphaFold modelling, we reveal a shape-based recognition mechanism: WRR4A engages structurally conserved backbone features of the effectors in a mostly side chain-independent manner, enabling recognition of diverse effectors with similar three-dimensional architectures. These insights guided successful engineering of WRR4A to acquire novel recognition specificity. In addition, analysis of the monomeric WRR4A resting state reveals a distinct domain architecture characteristic of C-JID-containing TIR-NLRs and informs their activation mechanism. This work provides insights into NLR-mediated broad-spectrum recognition and the potential for structure-informed engineering of improved crop resistance.

plant biology↗

bioRxiv2026

eScreen: a deep learning framework for functionally decoding the regulatory genome at single-nucleotide resolution

The human genome is densely populated with cis-regulatory elements (CREs), yet deciphering their functional regulatory syntax and combinational logic remains a fundamental challenge. Here, we integrate 379 genome-scale CRISPR screen experiments, encompassing 21 million perturbations across 23 cell types, to construct a compendium of 41,239 high-confidence functional CREs from 530,527 candidates. Leveraging this resource, we develop eScreen, a deep learning model built on the StripedHyena2 architecture to functionally decode the regulatory genome at single-nucleotide resolution. eScreen achieves three primary functions: (1) predicts genome-wide cell-type-specific CRE functional activity with high accuracy, outperforming existing models; (2) provides mechanistic interpretation of regulatory syntax at single-nucleotide resolution; (3) dissects the functional organization of enhancer clusters through in silico perturbation analysis. We perform multiple independent CRISPR knockout, CRISPR interference (CRISPRi), and base editing screens to validate these functions of eScreen both at scale and on individual cases. Furthermore, we provide an interactive web server (https://escreen.huanglabxmu.com/) for the community to access the integrated CRISPR screen resources and eScreen functions. Collectively, our work establishes a highly precise and convenient tool to decode the causal effects of the regulatory genome.

genomics↗

bioRxiv2026

MOSAIC: A Structured Multi-level Framework for Probabilistic and Interpretable Cell-type Annotation

Accurate cell-type annotation is a foundational task in single-cell RNA sequencing analysis, yet remains fundamentally challenged by cellular heterogeneity, gradual lineage transitions, and technical noise. As single-cell atlases expand in scale and resolution, most existing annotation approaches operate at a single analytical level and encode cell identity as fixed categorical labels, limiting their ability to represent uncertainty, mixed biological states, and population-level structure. Here we introduce MOSAIC (Multi-level prObabilistic and Structured Adaptive IdentifiCation), a structured multi-level annotation framework that integrates cell-level marker evidence with cluster-level population context within a unified probabilistic system. Rather than treating annotation as an independent per-cell prediction task, MOSAIC formulates cell-type assignment as a coordinated multi-level inference process, in which probabilistic evidence at the single-cell level is aggregated, constrained, and refined by population context. MOSAIC integrates direction-aware marker scoring with dual-layer probabilistic representation and adaptive cross-level refinement, enabling uncertainty to be quantified and propagated across biological scales. This design yields coherent annotations that preserve fine-grained single-cell variation while maintaining population-level consistency, and allows ambiguous or transitional states to be represented explicitly rather than collapsed into hard labels. Across six diverse tissues and under controlled dropout perturbations, MOSAIC consistently matches or outperforms representative marker-based, reference-based, and machine-learning annotation methods. Beyond accuracy, MOSAIC provides structured uncertainty estimates and coherent population-level structure, enabling the identification of stable intermediate cell states that arise from gradual lineage transitions rather than technical noise. Together, MOSAIC advances cell-type annotation from a single-level classification task to a structured multi-level inference problem, and establishes a general, interpretable, and uncertainty-aware computational framework for large-scale single-cell analysis.

bioinformatics↗

bioRxiv2026

IR-B deficiency and fatty acid dysregulation accelerate prostate cancer progression via PI3K/AKT signaling

The insulin receptor (IR) is markedly overexpressed in both human and mouse prostate cancer, with a significant elevation in the IR-A/IR-B ratio across patient tissues, cell lines, and Hi-Myc mouse prostates. To elucidate the role of IR-B in prostate tumorigenesis, we generated a prostate-specific IR-B knockout (KO) mouse model using Pbsn-Cre-driven recombination. Prostate-restricted loss of IR-B was confirmed at the transcript level and did not affect other tissues. Crossing these mice with Hi-Myc transgenics revealed that IR-B deficiency promotes accelerated progression to invasive adenocarcinoma, characterized by enhanced cellular proliferation and atypical histopathology. Transcriptomic and metabolomic profiling of dorsolateral prostate lobes demonstrated activation of PI3K/AKT and mTOR signaling, along with upregulation of IRS1/2/4 and IGF2. Metabolite analyses indicated elevated fatty acid levels and enhanced lipolysis pathways, implicating metabolic reprogramming in tumor progression. Notably, glucose and lipid metabolism genes, including GLUT1, GLUT12, FASN, and GPR120, were upregulated, accompanied by an increased BCL2/BAX ratio, suggesting apoptosis inhibition. Functional studies further revealed opposing roles of dietary fatty acids: {omega}-3 polyunsaturated fatty acids (EPA, DHA) suppressed prostate cancer cell survival, proliferation, and PI3K/AKT signaling while promoting apoptosis, whereas {omega}-6 fatty acid (arachidonic acid) exerted pro-tumorigenic, anti-apoptotic effects. Collectively, these findings identify IR-B loss as a driver of metabolic and signaling reprogramming that accelerates prostate tumorigenesis, while highlighting {omega}-3 fatty acids as potential modulators counteracting IR-B-deficient prostate cancer progression.

cancer biology↗

bioRxiv2026

Native Mass Spectrometry-Based Proteomics Reveals the Mechanism of Hemophore Release by Pathogenic Corynebacterium diphtheriae

Iron is an essential micronutrient for nearly all forms of life, including pathogenic microbes that must acquire it from their host during infection. At the host-pathogen interface, humans restrict microbial access to iron through nutritional immunity, which many pathogens overcome by secreting hemophores that scavenge extracellular heme (iron protoporphyrin IX). However, identifying hemophores and other ligand-binding proteins in complex proteomes remains challenging using conventional peptide-based bottom-up mass spectrometry (MS). Here, we introduce ProteoMIX (Proteome Analysis by Mixing), a function-based native top-down proteomics workflow that combines slow-mixing mode native MS with charge reduction to identify ligand-binding proteins directly from complex mixtures. Applying ProteoMIX to the Corynebacterium diphtheriae exoproteome identified ChtA30-314, an abundant soluble hemophore generated by proteolytic processing of the surface-exposed ChtA heme receptor. Using native top-down MS sequencing, cell fractionation, and gene deletion, we show that the protease DIP2069 releases ChtA30-314 by removing ChtAs transmembrane helix, producing a soluble proteoform that delivers heme to support microbial growth. In contrast, the related paralog ChtC is not processed, enabling C. diphtheriae to generate localization-specific heme-binding proteoforms from related gene products. Extending this approach to Staphylococcus aureus, ProteoMIX also revealed soluble IsdA hemophores that coexist with surface-anchored variants, demonstrating the generality of the method and suggesting that protease-mediated hemophore release may operate across gram-positive pathogens.

microbiology↗

bioRxiv2026

Polymer-lipid hybrid nanoparticle enhances mRNA delivery and T cell-mediated immunity

mRNA vaccines have transformed prophylactic immunization against infectious diseases as well as therapeutic interventions for cancer. However, their effectiveness against emerging viral variants and a range of malignancies continues to be hindered by suboptimal induction of T cell-mediated immunity. To overcome this limitation, here we developed a polymer-lipid hybrid nanoparticle (PLNP) platform engineered to improve mRNA delivery to antigen-presenting cells (APCs) and to potentiate T cell responses. Relative to conventional mRNA lipid nanoparticle (LNP) vaccines, mRNA PLNP vaccines demonstrated markedly improved lymph node targeting, APC activation, Th1-biased pro-inflammatory cytokine response, and antigen-specific T cell expansion while retaining robust humoral immunity. Remarkably, mRNA-PLNP vaccines generated approximately 50% more antigen-specific CD8+ T cells than mRNA-LNP vaccines across multiple antigens, including SARS-CoV-2 spike, influenza hemagglutinin, and ovalbumin. In prophylactic applications, mRNA PLNP vaccine provided complete protection against SARS-CoV-2 variants. As a therapeutic approach in a melanoma model, mRNA PLNP vaccination resulted in enhanced tumor control and significantly prolonged survival compared to LNP-based formulations. Collectively, these results establish PLNP as a versatile and broadly applicable platform for augmenting mRNA vaccine efficacy through improved mRNA delivery and T cell priming, offering promising implications for infection prevention and cancer immunotherapy.

immunology↗

bioRxiv2026

BRD8 Disruption Unlocks Retrotransposon-Driven Tumor-Intrinsic Immunogenicity via Redistribution of Histone Acetylation in Liver Cancer

Overall response rate for immune checkpoint blockade (ICB) therapy remains limited in advanced hepatocellular carcinoma (HCC). Epigenetic perturbation has been shown to enhance tumor-intrinsic immunogenicity and thus reverse resistance to immunotherapy in multiple cancer types. Here, through domain-focused CRISPR/Cas9 genetic screens targeting chromatin regulators, we identified the bromodomain-containing protein 8 (BRD8) as a novel epigenetic factor that functions to suppress tumor-intrinsic immunity through BRD8/EP400 chromatin remodeling complex in HCC. Depletion of BRD8 potently induces anti-tumor immune responses and sensitizes tumors to ICB therapy in mouse tumor models. Mechanistically, BRD8 knockout leads to partial redistribution of H3K27ac to repetitive elements, activating double-stranded RNA (dsRNA) accumulation and subsequent type I interferon (IFN) response, leading to tumor rejection via remodeling the tumor microenvironment. The first-in-class selective chemical probe DN02 targeting the bromodomain of BRD8 also exhibits immunomodulatory and anti-tumor effects. In line with these findings, low BRD8 expression correlated with enriched interferon signatures, elevated immune cell infiltration, and prolonged survival in HCC patients. Together, this study reveals BRD8 as a selective epigenetic vulnerability for promoting tumor immunogenicity, and its bromodomain as a druggable target to overcome immunotherapy resistance in liver cancer patients. SignificanceThe induction of viral mimicry by epigenetic interference could trigger tumor-intrinsic immune response and enhance immunotherapy efficacy. Here, through domain-focused CRISPR/Cas9 screening, we identify BRD8 complex as a regulator involved in the suppression of repetitive elements by controlling H3K27ac distribution and propose BRD8 as a novel target to enhance anti-tumor immunity.

cancer biology↗

bioRxiv2026

Magnetically activatable insect viral vectors promote anticancer immunity through spatially confined gene disruption

Precise control of genome editing activity in vivo remains a major barrier to the clinical translation of CRISPR-based therapeutics, as current approaches cannot reliably restrict editing activity to target tissues 1,2,3. Here we show that a magnetically gated baculoviral CRISPR platform enables spatial control of genome editing activity 4. By coupling magnetic activation of viral transduction at target sites with complement-mediated inactivation of circulating vectors, this system functionally confines genome editing activity to defined spatial contexts, effectively decoupling editing activity from biodistribution. We further show that spatially confined genome editing can be coupled with endogenous antiviral sensing to drive coordinated immune modulation within tumours. In a syngeneic murine tumour model, local administration combined with magnetic activation restricts genome editing to tumours without detectable editing in major organs, remodels dendritic cell and CD8{square} T cell states, suppresses tumour growth, and extends survival. Together, these findings establish a generalizable strategy for spatial control of genome editing and localized immunomodulation in cancer.

bioengineering↗

bioRxiv2026

Selective class IIa HDAC inhibition reverses diastolic dysfunction in cardiometabolic HFpEF

Heart failure with preserved ejection fraction (HFpEF) is a highly prevalent cardiometabolic syndrome with yet no effective therapies. Here, we report that selectively class IIa histone deacetylases (HDACs) but no other classes of HDACs are enzymatically activated in hearts from HFpEF patients and cardiometabolic HFpEF animal models. Cell type-specific and enzymatic activity-specific genetic loss-of-function models of the cardiomyocyte-enriched class IIa HDAC family member HDAC4 and the pharmacological class IIa HDAC-selective inhibitor TMP195 prevent and reverse diastolic dysfunction and exercise intolerance in cardiometabolic HFpEF in vivo. In contrast to pan-HDAC inhibition no adverse effects are observed. Despite its well-known non-enzymatic role as transcriptional repressor, we found that specifically enzymatic activation of HDAC4 has little direct effects on cardiomyocyte-intrinsic gene expression. Instead, non-epigenetic actions lead to endothelial activation via altered cardiocrine signaling. We discovered that selective enzymatic class IIa HDAC inhibition is a new therapeutic concept to combat cardiac HFpEF.

molecular biology↗

bioRxiv2026

Microglia Piezo1 aggravates cerebral ischemia and reperfusion injury by chemotactic recruitment of T lymphocytes

Cerebral ischemia reperfusion injury (CIRI) is a complex pathophysiological process involving multiple mechanisms. Piezo1, a stretch-activated ion channel, has recently emerged as a potential regulator of cellular responses to ischemic conditions. However, its role in specific cells during ischemic events is not well elucidated. Here, we showed that after experimentally induced CIRI, Piezo1 channel was highly expressed in peri-infarct area, where is upregulated and activated mainly in microglia. Behavioral tests, and infarct volume measurements demonstrated that conditional Piezo1 deficient in microglia markedly ameliorated the neurological deficits and reduced the infarct volumes. Flow cytometry and immunofluorescence staining showed decreased peripheral immune cells, especially T lymphocytes infiltration into the brain in microglia Piezo1 deficient mice after stroke. Multiplex chemokine immunoassay and T cell migration assays screened that Piezo1 deficient microglia blocked the CXC chemokine ligand 10 (CXCL10) release from astrocyte, which lead to the inhibited T cell recruitment in transwell co-cultured system. Furthermore, RNA-Sequencing analysis showed that defective Piezo1 in microglia lead to its polarization towards an anti-inflammatory phenotype in response to cerebral ischemia and reduced the secretion of tumor necrosis factor- (TNF-) and interferon-{gamma} (IFN-{gamma}). Collectively, Piezo1 deficiency inhibited the secretion of TNF- and IFN-{gamma} in microglia. The reduction of these inflammatory cytokines further blocked the CXCL10 release from astrocyte, and ultimately ameliorated the infiltration of peripheral T lymphocytes after stroke. Our results therefore highlight the critical role of Piezo1 in microglia-orchestrated neuroinflammation and suggest a potential means for reducing stroke-induced neurological injury.

neuroscience↗

bioRxiv2026

Discovery of potent oligopeptides for various metabolic diseases using deep learning

Artificial intelligence (AI)-based methods are increasingly critical in peptide drug discovery, but their applications are limited in a narrow scope such as antimicrobial peptides. For indications where peptide therapy inherently excels, such as metabolism, endocrinology, and tissue regeneration, AI-based pipeline for therapeutic peptide discovery is long awaited but still unmet. Here, we propose a deep learning-based pipeline, Deepeptide, capable of identifying therapeutic oligopeptides for various metabolism-related indications. Leveraging the intrinsical relationship of disease indication -- biological processes -- molecular functions, Deepeptide discovers oligopeptides with indication-ameliorating-related molecular functions as lead candidates for indication of interest. Deepeptide was applied in five representative indications of metabolism, endocrinology, and tissue regeneration: angiogenesis, lipid metabolism, osteogenesis, glucose metabolism, and anti-angiogenesis. Overall, 62% of the identified oligopeptide candidates demonstrated significant bioactivity in vitro, with most of them showing comparable potency to the first-line drugs. Notably, the heptapeptide AP7 exhibited angiogenic potency comparable to VEGF in excisional wound splinting mouse model by promoting cell migration rather than proliferation, and hexapeptide TP6 showed significant dual-efficacy against hyperlipidemia and obesity in high-fat diet mice by inhibiting lipid synthesis and regulating gut microbiota. These findings highlight the potential and generalizability of Deepeptide in therapeutic oligopeptide discovery for metabolic diseases.

bioinformatics↗

bioRxiv2025

Timing matters: exon skipping therapy is most effective when initiated early in a mouse model of Duchenne muscular dystrophy

Exon skipping is a leading therapeutic approach for Duchenne muscular dystrophy (DMD), a progressive muscle wasting disorder caused by pathogenic variants in the DMD gene that typically disrupt the translation reading frame. This approach aims to modulate DMD pre-mRNA splicing to re-frame the transcript and generate an internally deleted but partially functional quasi-dystrophin protein. Four exon skipping drugs have received FDA accelerated approval, although their clinical efficacy is very limited. To investigate how treatment timing influences exon skipping outcomes, dystrophin-deficient mdx mice were injected with peptide-phosphorodiamidate morpholino oligonucleotide (PPMO) exon skipping conjugates beginning at either the adult (12-week) or aged (75-week) stages, and tibialis anterior muscles harvested for biochemical and transcriptomic analyses. Mean Dmd exon 23 skipping was 79% in adults and 44% in aged PPMO-treated mdx mice, whereas dystrophin protein restoration was 35% and 8%, respectively. Histopathological improvements were only evident in the adult-treated mice. PPMO-treatment in adult mdx mice induced a broad transcriptomic shift towards a wild-type signature, whereas treatment in aged mice resulted in negligible gene expression changes, indicating that late intervention is ineffective at reversing disease-associated pathologies despite low-level dystrophin restoration. Dystrophin transcript imbalance was corrected only in adult-treated mdx mice. Increased expression of the dystrophin-repressing microRNA miR-31-5p, which was more strongly upregulated in aged mdx muscle, provides a potential mechanistic explanation. In conclusion, PPMO-mediated exon skipping is substantially more effective when initiated in adult rather than aged dystrophic muscle, supporting early therapeutic intervention in DMD-affected individuals.

neuroscience↗

bioRxiv2025

Spatially resolved translational dysregulation in Grin2a+/- mouse model of schizophrenia

Loss-of-function (LoF) mutations of GRIN2A, encoding the GluN2A subunit of N-methyl-D-aspartate receptor (NMDAR), confer a high risk for schizophrenia (SCZ)1-3, yet how they affect diverse brain cell types remains poorly understood. Here, we combined subcellular-resolution spatial omics technologies, STARmap4 and RIBOmap5, to jointly resolve single-cell transcriptomes and translatomes for 3,447 genes in the brains of Grin2a+/- mice and their wild-type littermates across 538,188 cells. Translational dysregulation was markedly more prominent than transcriptional changes in neurons. Across neuronal subtypes, a set of genes including Camk2a, Arc, Egr1, Egr3, Chmp2b, and Pja2 exhibited translational reduction in a Grin2a gene dose-dependent fashion, suggesting a connection between NMDAR hypofunction and reduced protein synthesis of downstream synaptic plasticity effectors. In interneurons (particularly parvalbumin interneurons), a strong reduction of Gad2 translation implies loss of inhibitory function in cortical microcircuits, which has long been hypothesized for SCZ pathophysiology. Non-neuronal cell types including astrocytes, oligodendrocytes, and vascular cells also exhibited region-specific translational changes in neurotransmitter transport, lipid synthesis, myelination, and stress response pathways, some of which co-varied with regional neuron state. Together, our study reveals brain-wide translation dysregulation as a critical mechanism underlying SCZ pathophysiology.

neuroscience↗

bioRxiv2025

Dynamic domain interactions encode possible CheA autophosphorylation mechanisms revealed by coarse-grained simulations

Autophosphorylation of CheA is key to initiation of the phosphorylation cascade that eventually controls the direction of downstream flagellar motors for chemotaxis signaling in motile bacteria. The phospho-transfer reaction, from ATP bound in the P4 catalytic domain to a specific His residue in the P1 substrate domain in CheA, can be significantly accelerated within core signaling unit complexes containing chemoreceptors, CheA and CheW. Previous studies have proposed that CheA autophosphorylation activity is regulated by changing the dynamics of P4 and/or altering its interactions with P1 in response to signals transmitted from chemoreceptors. However, the positions of CheA P1 and P2 domains in the core signaling unit are not well-characterized because they form only transient interactions with other domains. Though previous studies have identified possible domain-domain interaction surfaces, especially for P1 and P4, a bottom-up analysis of these interactions has not been performed. Here, we employed extensive molecular simulations to analyze interactions among CheA domains using a hybrid resolution (HyRes) protein model designed for dynamic protein structures and interactions. The results revealed multiple major modes of dynamic P1/P4 interactions. In particular, P1 was found to bind dynamically near the preferential binding surfaces on P4 even in the ATP free state. ATP binding to P4 reduces the motion of P1 binding and promotes a trans- productive-like mode that brings His48 in close contact with the bound ATP for possible autophosphorylation. The predicted non-productive and productive P1/P4 interaction modes appear highly consistent with existing NMR, mutagenesis, and chemical modification data. Together, these findings provide a more complete picture of the dynamics of domain-domain interactions of CheA and new insights into the possible regulation mechanism of its autophosphorylation.

biophysics↗