Biology subjects

Chen, X.

Publications and source records attributed to Chen, X..

At least 109 records · Page 6Linked to original sources

bioRxiv2026

Kaposi's Sarcoma-associated herpesvirus uses a novel protein fold to hijack RNA Polymerase II for viral late gene transcription

Herpesviruses, including the oncogenic human pathogen Kaposis Sarcoma-associated herpesvirus (KSHV), rely on cellular RNA Polymerase II (RNAPII) for expression of their protein-coding genes. Late in the lytic cycle, transcription initiation on a subset of KSHV genes depends on ORF24, a viral transcriptional activator that binds to viral late promoters through structural mimicry of a host transcription factor. Here, we present a structure of the N-terminal domain of ORF24, and show that it adopts a novel fold that facilitates direct binding of the RNAPII C-terminal domain (CTD). We further show that ORF24 is highly sensitive to the phosphorylation state of the RNAPII CTD, allowing for selective binding of the hypophosphorylated form to viral preinitiation complexes. By combining promoter binding and polymerase recruitment into a single protein, KSHV has streamlined essential steps in transcription complex assembly. Our work lays the groundwork for mechanistic dissection of a viral preinitiation complex.

microbiology↗

bioRxiv2026

Chromatin topology control by a muscle-specific ribosomal protein

Three-dimensional genome organization stabilizes cell-type-specific gene expression, yet the tissue-restricted factors that maintain chromatin insulation remain poorly understood. Here, we identify the muscle-specific ribosomal protein Rpl3l as an unexpected nuclear regulator of genome architecture in atrial cardiomyocytes. Rpl3l is enriched in the nucleus and nucleolus, where it binds its own genomic locus and stabilizes a CTCF-anchored chromatin boundary that represses the T-type calcium channel gene Cacna1h. Loss of Rpl3l weakens local chromatin insulation, increases long-range contacts across the Rpl3l-Cacna1h locus, derepresses Cacna1h, and increases susceptibility to atrial fibrillation (AF), which is suppressed by pharmacological inhibition of T-type calcium channels. Furthermore, AF-associated RPL3L variants exhibit impaired nucleolar localization, reduced rRNA binding, and defective repression of CACNA1H in human iPSC-derived atrial cardiomyocytes. Together, these findings reveal a ribosomal protein-chromatin axis linking genome insulation to ion-channel dosage control and cardiac rhythm stability, expanding the repertoire of cell-type-specific genome architecture regulators. HighlightsThe muscle-specific ribosomal protein Rpl3l exhibits unexpected nuclear and nucleolar enrichment. Rpl3l stabilizes a CTCF-anchored chromatin boundary to maintain atrial-specific local genome insulation. Loss of Rpl3l derepresses Cacna1h which encodes a T-type Ca2+ channel and increases atrial fibrillation susceptibility. Atrial fibrillation-associated RPL3L variants impair nucleolar targeting and CACNA1H repression

physiology↗

bioRxiv2026

A human intracranial map of consciousness returning from anesthesia

How consciousness arises from the brain remains a central yet unsolved question. Although substantial effort has been devoted to characterizing the neural correlates of conscious perception during wakefulness, how consciousness re-emerges from unconscious states remains poorly understood. Here, we took advantage of the rare opportunity to record human intracranial local field potentials from propofol-induced general anesthesia through the transition to behavioral engagement and subsequent full wakefulness, capturing both the stable states of unconsciousness and consciousness and the reconstituting neural dynamics that bridge them. Anesthesia cannot be defined by any single electrophysiological signature; rather, it is an organized low-frequency regime characterized by a constellation of coordinated neural phenomena, including aperiodic slow waves, alpha/beta periodicity, global alpha synchronization, and slow-wave-alpha/beta phase-amplitude coupling. Following anesthetic cessation, this regime progressively dissolved as neural excitability and dynamical complexity climbed. The appearance of conscious behavior coincided with a fast and dramatic transformation in high-gamma activity, from stochastic and unpredictable bursts to structured responses that were distributed, task-selective, and event-locked. These findings suggest that the recovery of consciousness is a multiscale reorganization in which distinct neural underpinnings rise and fall. Together, this work charts an electrophysiological map of how conscious cognition is extinguished, reconfigured, and restored in the human brain.

neuroscience↗

bioRxiv2026

Structure of full-length APOBEC3B bound to EBV BORF2 reveals coordinated neutralization of a cancer-associated mutator

The double-domain APOBEC3B (A3B) contains an N-terminal non-catalytic and C-terminal active cytidine deaminase domains (NTD and CTD). A3B restricts viral infection yet is also a major endogenous mutator in human cancer, driving tumor evolution and drug resistance. A previous study showed that the Epstein-Barr virus (EBV) ribonucleotide reductase large subunit BORF2 binds the active site of the A3B CTD and neutralizes the activity of the isolated catalytic domain. However, the three-dimensional organization of full-length A3B (fl-A3B) and the contribution of A3B NTD to BORF2-mediated neutralization have remained unclear. Here, we report a 2.77 [A] cryo-electron microscopy structure of fl-A3B in complex with EBV BORF2. The structure reveals an elongated hetero-octamer comprising two A3B2/BORF22 tetramers linked through alternating canonical and non-canonical BORF2 dimer interfaces. Full-length A3B adopts a defined NTD-CTD arrangement distinct from previously characterized APOBEC3G conformations. The A3B CTD binds BORF2 and occludes access to the catalytic site, while the A3B NTD simultaneously contacts a second BORF2 subunit, stabilizing a previously uncharacterized BORF2 canonical dimer interface required for higher-order assembly. Disruption of either BORF2 dimer interface prevents formation of filamentous A3B-BORF2 assemblies. These findings establish the structural architecture of full-length A3B and reveal how dual-domain engagement by A3B promotes higher-order BORF2 assembly, providing a structural framework for understanding EBV-mediated neutralization of an antiviral and cancer-associated mutator.

Cancer Biology↗

bioRxiv2026

Incorporation of single-neuron projectome-based connectivity motifs enhances the cortex-specific performance of artificial neural networks

The organizational principles of natural neural networks could inspire the new architecture design of artificial neural networks (ANNs). Analysis of single-neuron connectomes of mouse brains revealed distinct profiles of three-node connectivity motifs in various cortical areas and hippocampal formation. A connectome-informed neural network algorithm ("CINA") was developed to incorporate natural connectivity motifs into ANN algorithms represented by recurrent neural network (RNN) and transformer-based large language model (LLM). We found that incorporation of the average profile of cortical motifs improved the RNNs performance in noise-resistant categorization and motor learning benchmark tasks, as compared with RNNs with random connectivity. Notably, incorporating cortex-specific motifs further elevated the RNNs performance in tasks related to the cortical function, and this effect was enhanced by artificially increasing the bias in the motif profile. Similar experimental results were verified on an LLM using Motif-Transformer for natural language question answering and brain-signal decoding tasks. Graph-theoretic analyses showed that incorporating natural motifs drove the emergence of modular and small-world properties in ANNs. Together, we demonstrated not only connectome-inspired optimization of ANN architecture but also functional significance of specific motif profiles in various cortices.

neuroscience↗

bioRxiv2026

Aberrant neuron-OPC synaptic transmission and deficient myelination define sex bias in major depressive disorder

Sex bias is a notable feature of major depressive disorder (MDD), yet its cellular and molecular origins remain unclear. We integrated computational analyses of human patient data with histological and biochemical validation in animal models to uncover female-specific MDD pathways. We identified female-specific mechanisms involving oligodendroglial lineage cells, especially oligodendrocyte precursor cells (OPCs), as key signal receivers with unidirectional preference in interactome networks. The neurexin (NRXN) pathway emerged as the most perturbed in MDD, with greater disruption in females. Subclustering further identified committed OPCs (cOPCs) as a disease-associated oligodendroglial subpopulation characterized by high expression of synaptic genes; cOPCs were also enriched of MDD-related transcriptional signatures revealed by trajectory analysis. High-dimensional weighted gene co-expression network analysis identified GABRG3 as an MDD-specific hub gene in cOPCs. The GABRG3 was also involved in the NRXN synaptic assembly cascade. Using Gabrg3 conditional knockout mice, we validated findings in patients and demonstrated that conditional deletion of Gabrg3 in cOPCs recapitulates MDD-like phenotypes, highlighting impaired neuron-cOPC synaptic communication, abnormal myelination, and depression-like behaviors. Together, our work defines a sex-specific cellular and molecular pathobiology of MDD, bridges clinical discovery with preclinical context, and provides a translatable framework for precision medicine targeting fundamental sex differences.

neuroscience↗

bioRxiv2026

HoloCell: A Generative Foundation Model for Holistic Cellular Modeling

Single-cell multi-omics technologies have recently advanced to enable the profiling of epigenomic, transcriptomic, and proteomic layers within individual cells, offering new opportunities to characterize cellular states as integrated biological systems. However, developing a unified framework that can seamlessly integrate diverse omics modalities and remain robust to heterogeneous modality missingness remains challenging. Existing methods are often designed for specific modalities or modality pairs, relying on dataset-specific training or paired measurements. Here we present HoloCell, to our knowledge the first generative foundation model for joint representation learning and generative modeling across all three major single-cell omics modalities, i.e., epigenomics, transcriptomics, and proteomics. HoloCell contains over 860 million parameters and is pretrained on the Human-Multi-Omics-Corpus, which comprises approximately 468 million single-cell profiles across these three omics layers, corresponding to over 425 billion tokens. HoloCell introduces a a simple yet biologically motivated hierarchical tokenization strategy that encodes cis-regulatory elements, genes, and proteins as structured tokens within a shared modeling framework. We evaluated HoloCell across single-omics representation learning, paired multi-omics integration, unpaired multi-omics alignment, and cross-modal generation via iterative diffusion and remasking, demonstrating its superior performance and flexibility across diverse omics tasks. From a representation perspective, HoloCell provides a unified digital mapping of cellular states across multiple omics layers, capturing cell heterogeneity as an integrated system. From a generation perspective, its iterative diffusion and remasking frame-work permits flexible generation orders beyond fixed left-to-right causality, enabling in silico simulation of multi-omics information flow. Together, these capabilities position HoloCell as a versatile foundation model toward the emerging concept of a virtual cell, offering both systematic characterization and generative simulation of cellular systems within a unified framework.

bioinformatics↗

bioRxiv2026

Combinatorial docking and molecular generation to navigate over 100-billion molecules for prospective ligand discovery

Commercially available make-on-demand libraries now exceed 100 billion compounds, requiring over 50 years to screen on 2,000 CPU cores using conventional docking. We present two complementary approaches to address this challenge. CombiDOCK, a combinatorial docking framework, enables exhaustive screening at the 100-billion scale within 40 days. MINT-Dock, a generative framework, accelerates navigation of this space by integrating CombiDOCK with Monte Carlo Tree Search. Benchmarked on 46 diverse targets, CombiDOCK matched full-molecule docking accuracy, and MINT-Dock achieved a 4,800-fold enrichment over random selection. Compared with prior billion-scale brute-force campaigns against {sigma}2, VMAT2, and VAChT, prospective CombiDOCK screens of the 100-billion-molecule library yielded higher hit rates and more potent ligands, while MINT-Dock achieved comparable outcomes across single- and multi-target objectives with >20-fold computational cost reductions. Docking-predicted poses of the best VAChT-binding compounds were confirmed by cryo-EM structures. These methods provide exhaustive and generative paths for navigating the trillion-molecule frontier of drug discovery.

bioinformatics↗

bioRxiv2026

ANCHOR: haplotype-aware allelic and isoform inference from single-cell long-read RNA sequencing with de novo variant calling

Long-read RNA sequencing enables haplotype- and isoform-resolved allelic analysis of transcriptomes, yet extending this capability to single cells and distinct cell types remains computationally challenging due to sparse coverage, sequencing errors, incomplete variant information, and reference-biased transcript assignment. Here we present ANCHOR, a haplotype-aware framework for single-cell long-read RNA sequencing that performs de novo expressed-variant discovery, molecule-level haplotype assignment and isoform-resolved allelic quantification. ANCHOR combines a signed-graph variant caller, pair hidden Markov modelling and beta-binomial UMI aggregation to infer parental allele counts for genes and splice-resolved isoforms, without requiring a pre-existing phased genotype or deep learning. In human single-cell long-read RNA benchmarks, ANCHOR improved variant-calling performance over tested long-read RNA callers at single-cell and low-to-moderate coverage, and its beta-binomial model reduced depth-driven false positives in allele-specific expression testing. Applied to newly generated single-cell long-read RNA-seq data from reciprocal mouse crosses during gastrulation, ANCHOR resolved cell-type- and isoform-specific parent-of-origin imprinting and identified an antagonistic maternally biased Sgce isoform. ANCHOR provides a general framework for allele-and isoform-resolved analysis of diploid single-cell long-read transcriptomes.

bioinformatics↗

bioRxiv2026

DigiMus: a connectome-informed spiking framework for multi-region mouse neural-behavior modeling

Computational models are increasingly used to relate mouse brain structure, neural activity and behavior, but most models still learn from task data with limited constraints from biological circuit organization. Here we present DigiMus, a connectome-informed spiking framework for multi-region-capable mouse neural-behavior modeling. DigiMus combines leaky integrate-and-fire spiking dynamics with brain-region-specific motif regularization in a trainable sequence-modeling architecture, allowing directed three-node circuit motifs derived from 38,481 reconstructed neuronal morphologies across approximately 50 brain regions to guide recurrent coupling during learning. We evaluate DigiMus on 18 rule-based cognitive tasks spanning sensorimotor mapping and perceptual decision-making, and on three mouse neural decoding datasets involving auditory discrimination, fixed-interval licking and visual decoding. Across synthetic tasks, DigiMus showed stable performance relative to TCN, LSTM and Transformer baselines, with stronger advantages in more complex decision-making settings. In real neural datasets, single-region instantiations of DigiMus produced small, consistent and dataset-dependent improvements over a structure-free sequence baseline, while retaining motif-prior signatures in trained connectivity. Internal state analyses further linked task-dependent state dynamics to behavioral error patterns. These results suggest that connectome-derived structural priors can shape neural sequence models, and establish DigiMus as a modular, connectome-informed workflow for mouse neural-behavior modeling and hypothesis generation, rather than a complete digital reconstruction.

neuroscience↗

bioRxiv2026

Chromosome gigantism and auxin deconjugation underpin gall induction in a horned gall aphid

Insect galls are extended phenotypes built through sustained reprogramming of host development, yet the genomic innovations and effector mechanisms that enable this process remain poorly resolved. Here we generated chromosome-level genomes for the horned gall aphid Schlechtendalia chinensis and its host tree Rhus chinensis, and integrated these resources with morph-resolved salivary proteomics, metabolomics and functional assays. The aphid genome contains an anomalously expanded chromosome 1 spanning 93.61 Mb that carries 33.08% of anchored genes and concentrates 70.47% of genome-wide segmental duplications, together with elevated transposable-element load and multiple tandem gene clusters. We identified a salivary M20-family enzyme, ACY1, that consistent with an auxin-conjugate hydrolase. Loss- and gain-of-function assays show that ACY1 hydrolyzes stored, inactive auxin-amino acid conjugates in host tissue, increasing local active auxin levels. This hormone manipulation reprograms plant cell development to form galls. Our findings demonstrate how concentrated genomic duplication can drive the evolution of an effector that controls host physiology, suggesting a potential principle in the evolution of parasitic traits.

molecular biology↗

bioRxiv2026

Enhanced Target Binding by Leritrelvir Restores Dimerization of Mpro Mutants and Mitigates Drug Resistance

The SARS-CoV-2 main protease (Mpro) has been a major target of antiviral drug development, leading to the development of inhibitors such as nirmatrelvir, the antiviral component of the COVID-19 drug Paxlovid. However, resistance-associated mutations that reduce the efficacy of current Mpro inhibitors, particularly nirmatrelvir, have emerged. Here, we evaluated the inhibitory activity of leritrelvir (RAY1216), an Mpro inhibitor approved in China for COVID-19 monotherapy, against a panel of Mpro variants carrying mutations at 12 resistance-associated residues distributed across four catalytic subsites. Using integrated biochemical, biophysical, structural, and cellular analyses, we demonstrate that leritrelvir retains stronger inhibitory activity against most tested resistant mutants compared with nirmatrelvir. Most of the tested mutations promote Mpro dimer dissociation, with E166V showing a particularly pronounced effect and markedly compromising nirmatrelvir binding. In contrast, thermal shift and size-exclusion chromatography assays demonstrate that leritrelvir binding restores dimerization of these Mpro mutants. Sixteen high-resolution crystal structures reveal that leritrelvir binding re-instates key dimer-interface interactions disrupted by resistance mutations. Mini-replicon assays further confirm leritrelvir to possess enhanced cellular antiviral efficacy compared with nirmatrelvir. Our findings indicate that tighter leritrelvir binding enables more effective inhibition of dissociation-prone Mpro mutants than nirmatrelvir, supporting its use as a more resilient antiviral agent for SARS-CoV-2 treatment.

molecular biology↗

bioRxiv2026

Investigation of In Vivo Silk Scaffold Degradation by Decoupling Tissue Ingrowth Using a GPR-Driven Digital Twin Framework

Pelvic organ prolapse (POP) reconstruction is increasingly performed utilizing knitted silk meshes (KSM), yet tracking in vivo degradation kinetics remains challenging due to complex host tissue integration. This study developed an AI-driven semi-empirical framework utilizing Gaussian Process Regression (GPR) to bridge the kinetic mismatch between in vitro and in vivo environments. KSM scaffolds underwent 32 weeks of accelerated in vitro enzymatic degradation, with morphology (SEM), molecular conformation (FTIR), and mass loss being coupled with mechanical decay to train the GPR model. In vitro results revealed a multi-stage physical disintegration via a topochemical erosion pathway that preserved crystalline {beta}-sheet structures despite macro-scale mass and mechanical loss. When validated in a rat abdominal wall defect model, traditional tracking metrics encountered severe bottlenecks. Heterogeneous dye labeling caused premature fluorescence quenching by Week 16, while extensive tissue ingrowth masked gravimetric and SEM signatures. Intriguingly, a bi-phasic in vivo mechanical trajectory was identified, where initial degradation-led failure was followed by a secondary mechanical recovery driven by biomechanical synergy with neo-muscular tissue. Importantly, despite premature quenching, this work presents the first optical imaging approach to visually mapping the complete chronological breakdown of the scaffolds peripheral boundary layer in vivo, proving that outer functionalized layers eroded prior to internal silk cores. Furthermore, our GPR framework elegantly resolved the perennial technical barrier of tissue-mesh overlapping. By mathematically decoupling intrinsic polymer degradation from confounding tissue ingrowth, the model successfully achieved a first-of-its-kind prediction of the bare scaffolds long-term structural fate in a non-adhered state, providing a robust digital twin methodology for lifetime predictions of degradable biomaterials.

bioengineering↗

bioRxiv2026

Autoinducer-2 functions as both a quorum sensing and metabolic signal in Escherichia coli

Bacteria integrate diverse environmental signals to coordinate behavior, yet the relationship between nutrient sensing and quorum sensing (QS) remains incompletely understood. Autoinducer-2 (AI-2) is unique among QS signals in that its production is tightly linked to central metabolism, raising fundamental questions about the boundary between metabolic and signaling functions. In Escherichia coli, AI-2 coordinates collective behaviors through the lsr operon, whose expression is controlled not only by the AI-2-responsive repressor LsrR but also by the cAMP receptor protein (CRP), placing it at the intersection of carbon sensing and population-level signaling. While inhibition of lsr operon expression by PTS sugars such as glucose was previously established, we demonstrate that non-PTS sugars similarly suppress lsr expression through CRP, further decoupling QS activation from cell density and coupling it to carbon source availability. Systematic analysis of Enterobacteriaceae genomes reveals that CRP binding sites in the lsr promoter region are broadly conserved, indicating that metabolic modulation of AI-2 signaling is an ancestral regulatory feature. Importantly, using a FRET-based biosensor, we show that AI-2 uptake modulates intracellular cAMP levels in a manner resembling non-PTS carbon source transport, suggesting that AI-2 may have originally functioned as a nutrient substrate, with its signaling role emerging subsequently or co-evolving alongside. In support of this hypothesis, we isolated soil- and phyllosphere-associated bacteria capable of utilizing AI-2 as a sole carbon source. Our findings reveal an underappreciated metabolic dimension of AI-2 QS and suggest an evolutionary trajectory in which AI-2 signaling emerged from ancestral carbon utilization pathways. ImportanceQS allows bacteria to coordinate collective behaviors by detecting secreted signaling molecules, yet the evolutionary origins of these systems remain poorly understood. AI-2, one of the most broadly conserved bacterial signals, is derived from central metabolism and processed by machinery in E. coli that strikingly resembles a sugar utilization system. Here, we show that nutrient availability overrides cell density as the primary determinant of AI-2 responsiveness, that this regulatory logic is conserved among Enterobacteriaceae genomes, and that environmental bacteria can grow on AI-2 as a sole carbon source. These findings reframe AI-2 as a signal embedded within, and potentially evolved from, nutrient sensing pathways, with direct implications for understanding how byproducts of cellular metabolism can acquire signaling functions.

microbiology↗

bioRxiv2026

Polynomial Trajectory Compression for Protein Language Model Embeddings

Protein language models (PLMs) generate rich, layer-wise embeddings that capture diverse biological information but are expensive in terms of storage and computation at scale. In this work, we propose a compact surrogate representation for PLM embeddings across transformer layers using low-dimensional PCA projections and cubic polynomial trajectories. This approach enables efficient storage and on-demand reconstruction of these protein-level embeddings at any layer without rerunning the PLM. We evaluate our method on two downstream tasks: protein-protein interaction and subcellular localization using ESM-35M and ESM-3B PLM. We show that the surrogate embeddings achieve high reconstruction fidelity while reducing storage and computational requirements significantly. The new approach also retains downstream task prediction performance compared to original embeddings. Our approach provides a scalable and practical solution for large-scale protein embedding storage and reuse.

bioinformatics↗

bioRxiv2026

Viral Nuclease Inhibitors: Small molecule disruptors of the UL12 alkaline nuclease display broad anti-herpes virus activity

Herpes simplex virus-1 (HSV-1) UL12 gene encodes a well-conserved 5 [->] 3 alkaline exonuclease. UL12 collaborates with the HSV single-strand DNA binding protein ICP8 to mediate recombination-dependent replication of viral DNA and is essential for the production of DNA that can be packaged into infectious virus. The UL12 gene has orthologs in the eight other human herpesviruses, including UL98 in HCMV and SOX in KSHV, which are also essential for virus production. We have developed viral nuclease inhibitors (VNIs) of HSV-1 UL12 that potently block its nuclease activity and display strong antiviral effects in cell culture. These inhibitors are also effective against alkaline nucleases from the {beta}-HHV HCMV (UL98) and the {gamma}-HHV KSHV (SOX), and we have demonstrated antiviral activity against HSV-1 and HCMV in cell culture. In this work, we describe the first crystal structure of an alphaherpesvirus alkaline nuclease (UL12.5), which was used to elucidate structure activity relationships and improve the selectivity of our inhibitors. These VNIs exhibit EC50 and IC50 values in the nanomolar to low micromolar range. Our findings highlight the potential of targeting HHV alkaline nucleases with novel small molecules, paving the way for the development of new therapies that can be broadly antiviral on their own or in combination with nucleoside analogs. Significance StatementHerpesviruses are widespread pathogens that establish lifelong infections and cause serious disease in immunocompromised individuals, neonates and older adults, yet treatment options remain limited. We report the first crystal structure of the HSV-1 alkaline nuclease UL12.5 and use it to design potent small-molecule inhibitors. These inhibitors exhibit antiviral activity against HSV-1 and HCMV, supporting alkaline nuclease as a conserved and druggable target across all herpesvirus subfamilies. The significance is threefold: it confirms alkaline nucleases as having an essential role in viral replication, provides a structural foundation for rational antiviral design and introduces a new class of inhibitors with potential as pan-herpesvirus therapeutics, alone or in combination, to overcome resistance and improve clinical outcomes.

pharmacology and toxicology↗

bioRxiv2026

Single-cell spatial transcriptomics and snRNA-seq decoding the organizational principles of functional modules in the mouse amygdala

The amygdala is a functionally heterogeneous nuclear complex comprising multiple subnuclei that orchestrate diverse behaviors, making it essential for survival and reproduction. However, the precise neural mechanisms underlying these heterogeneous functions remain elusive, primarily due to limited knowledge of the amygdalas cellular heterogeneity, developmental origins, spatial organization, and gene expression profiles. Here, we integrate single-cell-resolution spatial transcriptomics with precise anatomical dissection and single-nucleus RNA sequencing to systematically map the subnuclear enrichment patterns of amygdalar cell types. We further demonstrate that developmental origin determines subnuclear positioning and propose a novel functional modular architecture based on cellular composition and gene expression signatures. Furthermore, we reveal that the central amygdala (CEA) exhibits developmental heterogeneity, with Isl1+ neurons in its medial subdivision (CEAm) predominantly originating from hypothalamic progenitors. Our findings establish a spatially resolved cellular and molecular framework for investigating amygdalar functions at cellular type resolution and understanding amygdala-related neuropsychiatric disorders.

neuroscience↗

bioRxiv2026

Multi-Domain Interplay Controls Full-Length TDP-43 Phase Separation and Condensate Dynamics

TDP-43 (TAR DNA-binding protein 43) is a 414-amino acid protein with a structured N-terminal domain (NTD), two RNA recognition motifs (RRM1 and RRM2), and a long disordered C-terminal low complexity domain (LCD). TDP-43 forms phase-separated condensates as part of its physiological function in RNA processing. However, aberrant TDP-43 condensation, changes in condensate material properties, and subsequent aggregation are linked to the development of neurodegenerative diseases. Using explicit-solvent, near-atomic resolution coarse-grained simulations we demonstrate how the interplay among different domains drives phase separation of the full-length protein.We directly capture how the secondary structure of a conserved helix in the LCD modulates phase separation, and follow the effect of phosphomimicking mutations on the condensation of full-length TDP-43. C-terminal phosphomimicking mutations rewire the interactions of the LCD by increasing solvation locally and enhancing Na+ binding to the LCD. Our simulations and in vitro experiments emphasize the importance of the aromatic residues in the LCD but also of N-terminal residues 1-101 including the NTD for full-length TDP-43 condensation. With a G[o]-type approach we capture not just conformational flexibility but also specific dimer formation through NTD-NTD interactions and how they modulate the phase behavior as well as the dynamic and interfacial properties of full-length TDP-43 condensates.

biophysics↗