Biology subjects

Chen, M.

Publications and source records attributed to Chen, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

ACAN regulates VSMC mitochondrial homeostasis through the YAP1/TAZ pathway and contributes to the onset and progression of aortic dissection

Objective: Aortic dissection (AD) is a serious, life-threatening cardiovascular crisis. While vascular proteoglycans normally buffer hemodynamic stress, their aberrant accumulation in the AD aorta predisposes to rupture. Aggrecan (ACAN) is among the most frequently elevated proteoglycans in this setting, yet its pathogenic relationship to AD remains undefined. This study aimed to investigate the role of ACAN in AD and identify potential therapeutic targets. Approach and Results: We employed human tissues, animal models, and cell cultures. Western blotting and immunohistochemistry (IHC) were performed on aortic samples from AD patients and controls to assess contractile markers, MMPs, ACAN, and SOX9. In vivo, AD was induced in mice using {beta}-aminoisobutyric acid (BAPN) and Ang II, with AAV-mediated ACAN knockdown in VSMCs. Histological staining confirmed model validity and enabled assessment of AD incidence, mortality, and protein expression changes. In vitro, human aortic vascular smooth muscle cells (HAVSMCs) were stimulated with Ang II, and SOX9 and ACAN were silenced via siRNA to evaluate the functional impact of ACAN downregulation. In human AD aortas, elevated ACAN and its upstream transcription factor SOX9 drove VSMC phenotypic switching and ECM degradation. In mice, ACAN knockdown corrected AD-induced medial structural disruption, elastin fragmentation, and collagen deposition, markedly reducing incidence and mortality while curbing excessive mitochondrial fission and rescuing functional integrity. ACAN silencing attenuated Ang II-induced mitochondrial damage in HAVSMCs via the RNA-seq-identified YAP1/TAZ pathway, and Verteporfin restored homeostasis. Conclusion: ACAN is aberrantly expressed in AD and murine aortas. ACAN downregulation delays disease progression by preserving mitochondrial homeostasis and function via the YAP1/TAZ pathway.

pharmacology and toxicology↗

bioRxiv2026

A self-limiting, TREM2-dependent anabolic program confers microglial resilience in Alzheimer's disease

Microglia are key drivers of Alzheimer's disease (AD), and TREM2, one of the strongest genetic risk factors, enables the disease-associated microglia (DAM) state required for plaque engagement. How TREM2 sustains this protection, and why it falters as disease advances, remain unclear. Using proteomics, single-cell transcriptomics, and in vivo metabolic labeling, we show that plaque-associated microglia mount a TREM2-dependent anabolic program coupling nascent protein synthesis to mitochondrial biogenesis. This program, not the DAM signature, marks phagocytically competent microglia; its loss is associated with proteostatic overload and mitochondrial dysfunction. Unexpectedly, this anabolic program is self-limiting, peaking at low amyloid burden and declining as burden rises. This decline is conserved in humans: across 523 donors, anabolic capacity tracks TREM2 but falls at advanced Braak stage even as DAM signature keeps rising. Thus, anabolic capacity, rather than activation state, marks microglial resilience in AD, and sustained stimulation of phagocytosis by anti-amyloid antibodies risks biosynthetic exhaustion and self-limiting efficacy.

neuroscience↗

bioRxiv2026

An INSR-BECN1-KIAA0825 complex prevents hepatocytic insulin receptor secretion via extracellular vesicles against monogenic diabetes

Monogenic diabetes from insulin receptor (INSR) mutations is a rare genetic disorder causing early-onset, profound insulin resistance. However, the pathogenic mechanisms by which INSR mutations disrupt receptor trafficking, cell-surface stability, and signaling are unresolved, and consequently, current treatment remains largely symptomatic and prognosis is not optimal. Here we discover that INSR, the autophagy protein BECN1, and KIAA0825, encoded by a diabetic-risk gene of previously unknown function, form a complex to regulate INSR transport, membrane presentation, and functionality in hepatocytes. Loss of hepatic BECN1 or KIAA0825, or expression of monogenic diabetes-causing mutations in INSR, disrupts the INSR-BECN1-KIAA0825 complex and mis-routes INSR to extracellular vesicles for secretion from hepatocytes, leading to impaired hepatocytic INSR cell-surface presentation and defects in hepatic insulin sensitivity, glycogen storage and exercise capacity. These findings identify new regulators and mechanisms governing INSR sorting, trafficking and signaling, uncover a non-canonical, non-degradative role for BECN1, and reveal the cellular fate of pathogenic INSR mutants underlying monogenic diabetes.

cell biology↗

bioRxiv2026

An Oxidative Stress-Associated Seven-Gene Prognostic Signature in Lung Adenocarcinoma: Integrative Transcriptomic Analysis Across Public Cohorts

Lung adenocarcinoma is molecularly heterogeneous, and oxidative-stress programs can support either tumor restraint or tumor adaptation depending on cellular context. This study integrated public lung adenocarcinoma transcriptomic cohorts to identify oxidative-stress-associated expression features and evaluate their prognostic relevance. Expression profiles from The Cancer Genome Atlas, Genotype-Tissue Expression project, and GEO series GSE31210, GSE40791, and GSE30219 were analyzed. Differential expression, weighted gene co-expression network analysis, functional enrichment, univariable Cox regression, and least absolute shrinkage and selection operator Cox modeling were combined to derive a risk signature. Immune-cell enrichment, gene set enrichment analysis, gene set variation analysis, and pan-cancer analyses were used for biological characterization. A total of 1,305 genes differed between tumor and control samples, including 498 upregulated and 807 downregulated genes. Intersection of differentially expressed genes, the oxidative-stress-associated co-expression module, and the oxidative-stress gene set yielded 44 genes enriched in responses to reactive oxygen species and hydrogen peroxide, antioxidant and peroxidase activities, focal adhesion, Rap1 signaling, and PI3K-Akt signaling. A seven-gene signature comprising FBLN5, HBB, FYN, HGF, TFAP2A, PLIN5, and F2RL1 stratified the 523-sample training cohort and the 207-sample internal validation cohort into groups with different overall survival. Time-dependent areas under the receiver operating characteristic curve at 1, 3, and 5 years were 0.677, 0.622, and 0.649 in training and 0.613, 0.691, and 0.706 in internal validation. In the 85-case GSE30219 external cohort, corresponding values were 0.588, 0.661, and 0.631; survival separation followed the expected direction but did not reach statistical significance (log-rank P = 0.100). Seventeen immune-cell signatures differed between risk groups, while high-risk tumors were enriched for cell-cycle, DNA-replication, mismatch-repair, glycolytic, E2F, G2M-checkpoint, MYC-target, and mTORC1-related programs. The signature therefore captures reproducible oxidative-stress-associated transcriptional variation with moderate prognostic discrimination. Its clinical utility requires prospective evaluation, complete clinical adjustment, and experimental validation.

cancer biology↗

bioRxiv2026

Natural and planted forests differ in the mechanisms regulating productivity and stability

Forest productivity and stability underpin ecosystem functioning and services, yet whether the drivers and mechanisms regulating these properties differ between natural and planted forests at large spatial scales remains unclear. Using data from 2,389 forest plots across China and a novel analytical framework, we systematically compared productivity and stability between natural and planted forests and identified their dominant drivers and underlying mechanisms across 38 biotic, structural, climatic, and edaphic variables. We found that natural forests were 14% more productive and 34% more stable than planted forests, although these differences varied across ecoregions and stand development stages. Productivity in natural forests was primarily driven by functional diversity and functional traits, supporting the niche complementarity and mass-ratio hypotheses, whereas nitrogen availability emerged as the dominant regulator of productivity in planted forests. Likewise, stability shifted from diversity-related regulation in natural forests to stronger abiotic control in planted forests, while functional diversity remained a key stabilizing mechanism in both forest types, supporting the insurance hypothesis. We also found that planted forests were more sensitive to hydroclimatic variability, indicating greater vulnerability to drought. Our findings reveal a fundamental shift in the mechanisms regulating forest productivity and stability from diversity-mediated control in natural forests to stronger abiotic regulation in planted forests, highlighting the importance of integrating biodiversity conservation and nitrogen management to sustain forest productivity and stability under future climate change.

ecology↗

bioRxiv2026

AutoScreen: AI Co-Scientist System for Target Discovery in Functional Genomics

Target discovery in functional genomics remains largely manual and time-consuming, lacking systematic tools for efficient and reproducible gene-level hypothesis generation. We introduce AutoScreen, an AI co-scientist system supporting target discovery through both Pre-screen Design, which constructs perturbation libraries de novo from free-text research descriptions, and Post-screen Analysis, which re-ranks experimental screen hits by integrating statistical scores with biological context. AutoScreen leverages the complementary strengths of multiple specialist agents that perform deep research into multi-modal evidence, information restructuring, parallel searches across >26 biomedical databases, evidence synthesis, and target review to provide transparent, explainable gene prioritization with pipeline provenance. Across 320 genome-scale CRISPR screens as expert-curated benchmarks, AutoScreen achieved a ~19% increase in validated-hit recovery among its top 100 predictions, relative to the strongest agent baseline, and required a 1.2-fold smaller library to recover the same number of hits at the top-500 reference point. AutoScreen reached mean average precision more than two orders-of-magnitude above random baseline. Further, we validated AutoScreen in cancer immune-evasion case studies focusing on natural killer (NK) and T-cell therapeutics. AutoScreen recovered NK-resistance genes that were initially lower-ranked in a leukemia screen, moving MUC1, PDPN, and LRRC15 from raw ranks of 118, 81, 1384 to 5, 44, 659, respectively. In follow-up tumor killing assay with primary human NK cells, individual perturbation validated all three hits successfully. Next, in prospective benchmarking across two cytotoxic T-cell-killing screens, AutoScreen recovered 77.1% of ground-truth hits called by the consensus of two gold-standard analysis pipelines (FDR<0.1), achieving 8% improvement over the strongest general-purpose LLM agent baseline. Finally, we re-analyzed >500 public datasets to construct the AutoScreen Resource Hub, a growing knowledge base of pre-computed, annotated reports for CRISPR screens, RNA-seq differential expression, and gene-level UK Biobank genome-wide association studies. This agentic AI approach enables real-time genomics benchmark construction that are continuously updated, expanded, for evaluating frontier AI co-scientists. Overall, AutoScreen enables AI-powered target discovery to be more auditable, scalable, extensible, and reproducible.

bioengineering↗

bioRxiv2026

A SUN1-ApoD feedback loop promotes cellular aging via microtubule-nuclear mechanotransduction

Alterations in nuclear envelope proteins such as SUN1 and prelamin A are known hallmarks of cellular aging, but how they cause aging phenotypes beyond the expressing cells is unknown. With a tissue culture version of parabiosis, we found that aged fibroblasts secrete an activity that induces aging-related polarity defects in young fibroblasts. Secretomics identified the factor as apolipoprotein D (ApoD), a circulating protein whose levels are known to rise with age. ApoD increased SUN1 levels and disrupted polarity in fibroblasts via SUN1-promoted coupling of microtubules to the nucleus. In turn, elevated SUN1 enhanced ApoD expression and secretion, forming a feedback loop that promotes acquisition of aged phenotypes. In mice, ApoD induced aging-related phenotypes in muscle. Elevated ApoD expression required coupling between SUN1, its outer nuclear membrane binding partner nesprin-2, and microtubules. Broader analysis revealed that this pathway regulates hundreds of genes. These findings define microtubule-nuclear coupling as a direct mechanotransduction pathway controlling gene expression and promoting aging-associated phenotypes.

cell biology↗

bioRxiv2026

Sequential assembly in vivo of the bacteriophage P22 genome translocation channel

Bacteriophage P22 ejects four internal proteins into infected cells to assemble a channel for genome translocation across the cell envelope. However, how these proteins cooperate to build the trans-envelope channel remains enigmatic. Using in situ single-particle cryogenic electron microscopy, we determined near-atomic in vivo structures of P22 infection intermediates, revealing how the tail hub protein gp10 templates the sequential assembly of three internal proteins gp7*, gp20 and gp16 into a ~50-nm trans-envelope channel that extends from the virion into the host cytoplasm. Functional analyses explain why phage DNA can be detected in supernatant fluids during infection by channel-defective mutants. Our structures also provide a mechanistic basis for the long-standing observation that a P22 virion lacking gp16 can be complemented, extra-cytoplasmically, by a co-infecting virion lacking gp20, thereby allowing the genome in the gp16-deficient particle to enter the host cytoplasm.

microbiology↗

bioRxiv2026

EukaUTR: a foundation model for functional modelling and design of eukaryotic 3' UTRs

Eukaryotic mRNA 3' UTRs encode regulatory information that shapes post-transcriptional control, RNA fate and gene expression. However, a 3' UTR-specific foundation model that spans broad eukaryotic sequence diversity while supporting both functional prediction and sequence design is lacking. Here we present EukaUTR, a 3' UTR-specific foundation model trained on a large-scale eukaryotic 3' UTR sequence corpus spanning diverse evolutionary lineages. Across 13 prediction tasks spanning post-transcriptional regulation, RNA fate and expression output, EukaUTR models matched or exceeded the strongest external baselines on nearly all tasks, with relative improvements of up to 27.45%. EukaUTR also generated de novo 3' UTRs with natural-like sequence and regulatory properties. EukaUTR-Guide further derived stability-associated signals from small sequence sets to guide editing towards enhanced predicted stability. Together, EukaUTR provides a sequence-to-function-to-design framework for transferable 3' UTR modelling and design.

bioinformatics↗

bioRxiv2026

Subtyping active-site inhibitor binding mode to Abl kinase using super-resolution nanopore tweezers.

Accurate determination of kinase inhibitor binding modes could provide essential information for understanding resistance mechanisms and accelerating drug discovery. While conventional structural methods such as X-ray crystallography, cryo-EM and NMR provide high-resolution information but are low-throughput and capture largely static snapshots of dynamic protein-ligand interactions Here, we introduce a single-molecule nanopore tweezer platform that functionally subtypes ATP-competitive Abl kinase inhibitors by resolving distinct ionic current signatures of Abl-inhibitor complexes. This approach distinguishes Type I, Type IIA, and Type IIB inhibitors without structural determination. We further show how clinically relevant Abl variants (T315I and E255V) reshape inhibitor engagement and binding modes. By combining baseline probability features with wavelet-based time-frequency descriptors, ensemble machine-learning models achieved 97.5% classification accuracy across seven kinase inhibitor binding modes at sub-angstrom resolution and enabled deconvolution of mixed-inhibitor samples at nanomolar concentrations. These results establish nanopore tweezers as a label-free, super-resolution platform for profiling kinase conformational states and inhibitor binding modes, complementing structural approaches and supporting precision oncology.

biophysics↗

bioRxiv2026

Single-Molecule Nanopore Profiling of p53-TAD Conformational Dynamics, Interactions, and Inhibition

Investigating the conformational dynamics of intrinsically disordered proteins (IDPs) is essential to understanding how their structural heterogeneity underlies function and how their dysregulation contributes to diseases. Here, we utilized an MspA nanopore-based approach for studying the conformational dynamics and interactions of IDPs at the single-molecule level. The platform was demonstrated using the intrinsically disordered transactivation domain of tumor suppressor p53 (p53-TAD), one of the important proteins in cancer biology. We showed that MspA can stably capture p53-TAD and resolve up to six distinct current states with frequent interconversions, revealing a rich conformational landscape. The nanopore also detected the effect of a cancer-associated double mutational variant, N29K/N30D. Combining experiments with steered molecular dynamics simulations, we showed that the mutant sampled compact conformational states more frequently than wild type, consistent with previous NMR studies. Importantly, the MspA platform enabled direct monitoring of E3 ligase MDM2 binding to p53-TAD and resolved how this interaction is inhibited by anti-cancer compound epigallocatechin gallate (EGCG). Notably, EGCG stabilizes one of the six states sampled by p53-TAD, providing a mechanistic explanation for its inhibitory effect. Together, these findings demonstrate the promise of the nanopore platform for label-free monitoring of IDP conformational dynamics, modulation, binding and inhibition at single-molecule resolution.

biophysics↗

bioRxiv2026

Avs2 drives non-canonical tetrameric assembly of trypsin-like domain for anti-phage defense

Bacteria have evolved diverse anti-phage defense systems, with the antiviral STAND family (Avs) representing one of the most diverse and widespread, encompassing at least 90 distinct families, yet only Avs3, Avs4, Avs5 and Avs7 have been well characterized. Here, we elucidated the molecular mechanism of Avs2-trypsin-MBL system, where phage terminase recognition by Avs2 triggers coupled activation of the protease and nuclease activities of trypsin-MBL. Cryo-EM structure of Avs2-trypsin-terminase and biochemical analysis reveal that the binding of terminase ATPase domain triggers the assembly of Avs2 into tetramer, with two unique ATP molecules bridging ATPase active-site recognition by TPR domain. This tetramerization drives the fused trypsin into an active C4-symmetric assembly, an architecture distinct from the conventional non-defense trypsin. Our study unravels the activation mechanism of Avs2-trypsin-MBL system, expanding our understanding on commonality and diversity of widespread Avs-mediated anti-phage immunity, alongside the structural and functional adaption of trypsin.

microbiology↗

bioRxiv2026

An inflammation-associated five-gene expression signature stratifies survival and immune states in lung adenocarcinoma: an integrative public-cohort analysis

Background: Inflammation and the tumor immune microenvironment contribute to lung adenocarcinoma (LUAD) progression, but the relationship among inflammation-linked transcriptional heterogeneity, patient survival, and immune-state variation remains incompletely defined. Objective: We aimed to identify inflammation-associated LUAD subtypes, derive a parsimonious survival-stratification signature, and characterize its immune and pathway context across public transcriptomic cohorts. Methods: Expression profiles and clinical data were obtained from TCGA-LUAD, GTEx normal lung, and GEO datasets GSE11969, GSE30219, GSE31210, and GSE40791. A curated set of 596 inflammation-related genes was used for consensus clustering. Differential-expression analysis, functional enrichment, univariate Cox regression, and LASSO-Cox modeling were integrated to construct a gene-expression risk score. The prognostic dataset comprised 730 cases and was randomly divided into training (n=502) and internal-validation (n=228) sets; 85 GSE30219 cases formed an external-validation cohort. Immune-cell enrichment, gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and pan-cancer analyses were used for biological contextualization. Results: The LUAD-versus-control comparison identified 1,305 differentially expressed genes, including 498 upregulated and 807 downregulated genes. Consensus clustering resolved two inflammation-associated subtypes and 67 subtype-associated genes, of which 64 were higher and 3 were lower in Cluster 1 relative to Cluster 2. Thirty-three genes overlapped between the tumor-control and subtype contrasts. LASSO-Cox regression selected CHRDL1, FDCSP, CXCL13, CYP4B1, and S100P. The 1-, 3-, and 5-year areas under the time-dependent receiver operating characteristic curve were 0.6625, 0.6581, and 0.6658 in the training set; 0.7422, 0.6537, and 0.6761 in internal validation; and 0.6560, 0.6387, and 0.6753 in external validation. Risk groups differed across multiple T-cell, B-cell, natural-killer-cell, myeloid, dendritic-cell, macrophage, and granulocyte signatures. Positive GSEA signals included cell cycle (normalized enrichment score [NES]=2.67; adjusted P=1.42 x 10-), DNA replication (NES=2.52; adjusted P=2.52 x 10-), and mismatch repair (NES=2.20; adjusted P=1.77 x 10-). Conclusions: The five-gene expression score separated LUAD survival groups and captured coordinated proliferative and immune transcriptional states. Its moderate discrimination supports further biological and clinical validation rather than immediate clinical application.

bioinformatics↗

bioRxiv2026

CodonMamba: a foundation model for programmable mRNA coding sequence design

Although mRNA codon language models provide a generalizable framework for biological sequence design, effective CDS design requires both a learned sequence design space that captures biological constraints and context-configurable design preferences. Here we present CodonMamba, a codon language model framework for mRNA prediction and programmable CDS design. Pretrained on large-scale coding-sequence corpora, CodonMamba achieved state-of-the-art performance across a comprehensive benchmark of 12 mRNA prediction tasks, ranking first on 10 of 12 tasks. Furthermore, CodonMamba establishes a programmable CDS design framework, transforming codon optimization from a process dependent on preferences embedded during model training into an inference-time steerable generation framework. By introducing user-specified codon usage priors during generation, CodonMamba enables inference-time steering toward host- or application-specific codon preferences without retraining. In design experiments, CodonMamba enabled coordinated optimization over multiple design-relevant sequence properties and demonstrated programmable cross-host CDS retargeting through inference-time prior switching, while preserving most model-derived codon choices. Together, these results establish CodonMamba as a programmable foundation model framework for CDS design, enabling context-specific mRNA sequence engineering and highlighting a promising direction for precise mRNA design using foundation models.

bioinformatics↗

bioRxiv2026

Precise Functional Localization of the Foveolar Representation in Anesthetized Macaque Visual Cortex

The foveola-the central ~1{degrees} of the visual field-supports the highest-acuity spatial vision, yet localizing its cortical representation is technically demanding, particularly under anesthesia where gaze cannot be behaviorally controlled. Here we describe a hierarchical, meridian-based 7T BOLD fMRI strategy for sub-degree localization of the foveolar representation in anesthetized macaques. Drifting grating bars presented at three successively finer scales (4.5{degrees}, 1.5{degrees}, 0.5{degrees}) independently refined the vertical and horizontal meridian representations, each identified by a characteristic activation signature: bilateral convergence at the V1/V2 border for the vertical meridian, and simultaneous dorsal and ventral V2/V3 activation at the fundus of the calcarine sulcus for the horizontal. Their functional intersection defined candidate foveolar coordinates, which were refined using 0.2{degrees} spot stimuli. Surface-based rendering resolved discrete foveolar loci at the lateral end of the V1/V2, V2/V3, V3/V4 and V4/TEO borders, together delimiting the previously described 'foveolar core'. Pooling these with awake data, we place the loci in a common stereotaxic frame, yielding a first anatomical atlas of the core. Intrinsic-signal optical imaging further shows that this territory lacks the ocular-dominance and orientation columns of surrounding cortex. The approach provides a reproducible framework for locating and targeting foveolar cortex in anesthetized primates.

neuroscience↗

bioRxiv2026

Global transmission architecture of VIM carbapenemases reveals host-specific dissemination strategies

Carbapenemase-producing Gram-negative bacteria carrying Verona integron-encoded metallo-{beta}-lactamase (VIM) pose a persistent global threat, yet the mechanisms driving their worldwide dissemination remain poorly resolved. We analysed 5,617 blaVIM-positive genomes collected from 73 countries or regions across six continents between 1999 and 2025 to reconstruct the global epidemiology and transmission architecture of VIM carbapenemases. Forty VIM variants were identified across 16 bacterial genera, revealing marked host preferences and temporal shifts. VIM-2 dominated global circulation, whereas VIM-1 and VIM-4 remained prominent among Enterobacterales. Strikingly, VIM spread followed distinct host-specific evolutionary strategies. In Pseudomonas aeruginosa, dissemination was largely clone-driven, with high-risk lineages ST111 and ST235 supporting long-term persistence through lineage expansion and stable inheritance. By contrast, Enterobacterales were dominated by horizontal transmission through broad-host-range IncHI2A, IncA, and IncC plasmids, although only a limited subset of plasmid-VIM combinations achieved intercontinental spread. Among 2,828 loci with sufficient flanking sequence, 96.2% were embedded within integrative genetic elements, frequently nested with insertion sequences and phage-related elements, revealing a multilayered mobile-element network underlying VIM persistence. Structural analyses showed a highly conserved metallo-{beta}-lactamase scaffold but recurrent diversification near substrate-interacting residues, particularly positions 224 and 228. Shared genetic clusters between human-associated and environmental isolates further suggested cross-niche circulation. Together, these findings establish a hierarchical, host-dependent framework for global VIM dissemination, integrating clonal expansion, plasmid transfer, and nested mobile genetic elements. ImportanceBy analysing 5,617 blaVIM-positive genomes worldwide, this study reveals a host-dependent transmission architecture of VIM carbapenemases. In P. aeruginosa, VIM dissemination is mainly driven by expansion of successful high-risk clones, particularly ST111 and ST235, whereas in Enterobacterales it is primarily mediated by broad-host-range plasmids enabling cross-species transfer. Global VIM spread is not driven by a single dominant pathway but by a limited number of successful clone-plasmid-mobile element combinations, while most genetic backgrounds remain regionally restricted. These findings define a hierarchical transmission model of VIM evolution and provide insights for genomic surveillance and targeted control of metallo-{beta}-lactamase-mediated antimicrobial resistance.

microbiology↗

bioRxiv2026

An aminoglycoside antibiotic drives RNA phase separation

AbstractAminoglycoside antibiotics bind RNA with high affinity through networks of amine and hydroxyl contacts, yet whether this multivalent binding can drive macroscopic RNA phase transitions has never been tested. Here we show that neomycin B (neoB), an FDA-approved aminoglycoside, induces concentration-dependent phase separation of poly(A), poly(U), and total E. coli RNA. Condensate size and density are tunable by pH and ionic strength, which modulate neoB protonation and screening of interdroplet repulsion independently. Comparison with spermine shows that neoB produces more stable condensates despite spermine carrying at least as much effective charge at physiological pH. Fucitol, a hydroxyl-rich polyol lacking amines, fails to condense RNA, showing that cationic amine groups are required and cannot be replaced by hydroxyl groups. Molecular dynamics simulations attribute the greater condensation efficiency of neoB to additional hydrogen bonds donated by its hydroxyl groups. These results reveal that the chemical complexity of aminoglycosides, evolved for tight RNA recognition, also drives a macroscopic RNA phase transition. RNA condensation may contribute to aminoglycoside bactericidal activity and cellular toxicity.

biochemistry↗

bioRxiv2026

Structural basis for the selective inhibition of the PI3KC3-C2 complex by Rubicon in endolysosome maturation and mitophagy

Rubicon is a negative regulator of autophagy and the endolysosomal network (ELN) and an antagonist of the class III phosphatidylinositol 3-kinase complex II (PI3KC3-C2). Inhibition of Rubicon is considered a potential means to therapeutically upregulate autophagy and the ELN to treat Parkinsons disease and other conditions characterized by autophagic and ELN dysfunction. Rubicon is specific for the UVRAG-containing PI3KC3-C2 over the purely autophagic ATG14- containing PI3KC3-C1 complex. Here, we determined the high-resolution cryo-electron microscopy structure of PI3KC3-C2 in complex with the PI3KC3-binding domain (PIKBD) of Rubicon and compared it to cryo-EM structures of unbound PI3KC3-C2 and PI3KC3-C1. Rubicon binds directly to PI3KC3-C2 only via the BARA domain of the BECN1 subunit, which is common to both C1 and C2. The selectivity of Rubicon for the PI3KC3-C2 complex over the PI3KC3-C1 complex is attributed to a conformation of the BECN1BARA domain induced by UVRAG, rather than to direct contact with UVRAG or direct antagonism by the ATG14 subunit of PI3KC3-C1. Targeted disruption of the Rubicon:PI3K3-C2 structural interface by site-directed mutations enhances mitophagic activity in human epithelial cells to levels comparable to those observed in Rubicon knockout (KO) cells. Similarly, disruption of the interaction in Rubicon-overexpressing hippocampal neurons restored lysosomal flux to wild-type levels. These data show that suppressing the function of PI3K3- C2 can fully account for the negative regulatory effects of Rubicon in the autophagy and ELN pathways. Significance StatementEndolysosome maturation and autophagosome-lysosome fusion require the production of phosphatidylinositol 3-phosphate (PI(3)P) by the class III phosphatidylinositol 3-kinase complex II (PI3KC3-C2). Rubicon is a key negative regulator of endolysosomes and autophagy that suppresses PI3KC3-C2 activity. Here, we reveal in atomistic detail how Rubicon selectively recognizes PI3KC3-C2. Disrupting the Rubicon-PI3KC3-C2 interaction restores mitophagy and enhances lysosomal activity to the same extent as Rubicon gene deletion, establishing that PI3KC3-C2 inhibition fully accounts for the biological regulatory effects of Rubicon in the autophagy and lysosome pathways.

biochemistry↗