Search bioRxiv⌕ Search

Biology subjects

Sun, L.

Publications and source records attributed to Sun, L..

At least 55 records · Page 3Linked to original sources

CMS: Achieving Uniform and High-Quality Sequencing across Challenging Non-canonical Genomic Regions

High-throughput sequencing is essential in modern biological research, yet low-complexity sequences remain challenging as they form structurally complex, non-canonical (non-B) DNA conformations that impede sequencing enzyme read-through. This leads to a long-standing trade-off: maximizing coverage introduces false positives (FP), while stringent filtering causes coverage loss and false negatives (FN). To address this, we developed CMS (Cross Mountains and Seas) on GeneMind sequencing platforms by optimizing its chemistry and enzymatic systems to traverse these secondary structures with high fidelity. Benchmarking across whole-genome (WGS) and whole-exome (WES) sequencing demonstrates that CMS addresses the trade-off by simultaneously enhancing both coverage uniformity and accuracy, notably achieving an approximately 100-fold reduction in low-coverage bins for WGS and a 70% reduction in FN insertions/deletions (INDELs) within complex non-B regions. Specifically, a synthetic G-quadruplex (G4) motif sequencing experiment demonstrates that CMS maintains a 1:1 strand ratio, effectively handling G4-induced biases where benchmarked platforms exhibit extensive depletion. These findings establish CMS as a reliable technology for the precise characterization of structural-challenging but functional-essential genome regions.

genomics↗

An autonomous LLM agent platform for computational binder design and conjugation-aware prioritization of antibody drug conjugates

Large language model (LLM) agents have automated tool use in chemistry, but orchestrating multi-step computational biology workflows--spanning structure prediction, protein design, and covalent conjugation--remains manually intensive. Here we present Open Intelligence Hub (OIH), an autonomous LLM-agent platform that dynamically plans and executes 32 containerised tools for protein binder design and antibody-drug conjugate (ADC) prioritization. OIH introduces tier-based decision routing, ipSAE-guided interface filtering, and failure-to-knowledge distillation from 265 curated cases. Across five oncology targets, the agent correctly classified all five evaluated targets and required human correction for hotspot selection in only one case, producing binders ranked by ipSAE (Nectin-4 ipTM = 0.87, HER2 ipTM = 0.85). A controlled ablation suggests that the agents PPI-informed routing yields improved downstream ipTM and ipSAE scores than epitope-guided alternatives. The LLM-agnostic architecture enables deployment with local or commercial models without pipeline changes. All results are computational predictions awaiting experimental validation.

bioinformatics↗

Protein inverse folding through joint modeling of surface and backbone geometry

Inverse protein folding aims to generate amino acid sequences compatible with a given protein structure. While recent deep learning methods have achieved strong performance by conditioning on residue-level backbone geometry, backbone-only representations insufficiently constrain surface-exposed residues and thus incompletely capture the structural determinants of sequence identity. Here we propose Surleton, a structure-aware inverse folding framework that jointly models backbone geometry and protein surface organization. By integrating complementary surface geometric information, Surleton refines the conditional sequence distribution and improves the balance of sequence modeling across buried and exposed residues. On the CATH4.2 and SCOPe benchmarks, Surleton consistently outperforms backbone-only baselines in sequence recovery, sequence similarity, and predictive confidence, with especially strong improvements on surface-exposed residues. Together, these findings indicate that protein surface geometry serves as a complementary source of structural constraint and that surface-aware modeling may provide a promising direction for improving inverse protein folding.

bioinformatics↗

Spikes meet Spins: Quantum-Native Neural Decoding for Ultra_Low-Latency Brain-Computer Interfaces

Brain - computer interfaces (BCIs) require rapid and accurate decoding of neural activity, yet conventional computing architectures face growing latency as neural recording scales. We demonstrate a quantum computing - enabled neural decoding approach using a physical 1000-qubit coherent photonic Ising machine, in which inference is performed through hardware energy relaxation rather than numerical computation. By mapping sparse neural spike patterns onto Ising Hamiltonians, our hardware-native Quantum Semi-Restricted Boltzmann Machine achieves up to 96.2% accuracy across public in vivo datasets spanning multiple species and modalities. We report hardware-verified median latencies of 0.075 ms-- a tenfold speedup over GPUs--with complexity-invariant scaling. These results establish quantum computing as a viable pathway toward ultra-low-latency neural decoding for future BCI systems.

neuroscience↗

Learning latent conformational landscapes encoded in cryo-EM

A protein populates a landscape of structural states, abundant snapshots of which are sampled in every cryo-EM experiment. Current analysis averages these snapshots into single density maps or partitions them into discrete classes, discarding the continuous dynamics encoded in the data. Continuous latent-space methods offer a promising alternative, yet whether their learned representations are physically grounded remains unresolved. Here, we realize cryo-EM as structural landscape microscopy, in which latent density directly reflects the probabilistic distribution of molecular states. A central question is whether such a landscape reflects physical reality. For integrin v{beta}8, the learned landscape shows strong agreement with independently derived molecular dynamics simulations, supporting its physical plausibility. We then apply the landscape to structural states that conventional cryo-EM cannot resolve. For LIS1-mediated dynein activation, the landscape reveals a spectrum of states from dominant conformations to low-population intermediates defined by distinct binding modes, including a previously unresolved state. For the KCTD5/CUL3NTD/G{beta}{gamma} complex, the landscape resolves continuous conformational pathways directly from experimental data. Probability-guided particle selection further improves reconstruction quality.

molecular biology↗

Uncovering zebrafish embryonic proteome dynamics across 16 time points during the first 24 hours of development

Defining how proteins change over developmental time is amenable to studies deciphering regulatory genetic networks in vertebrate development, biology, and pharmacology. In an approach toward such quantitative studies of dynamic network behavior, we produced an atlas using the mass spectrometry-based method to investigate protein expression changes across 16 time points from the zygote to the early pharyngula stage zebrafish embryos. We systematically summarize 8 clusters for interrogating changes in protein expression associated with the development of zebrafish embryos. Specifically, we identified a class of zinc finger-related transcription factors primarily located on the long arm of chromosome 4, which are highly expressed during zygotic genome activation. Furthermore, we highlight the power of this analysis to assign developmental stage-specific expression information to chromosomes and tissues. Time-resolved analyses reveal significant discordance between differential transcript and protein expression, whereas no time lag is observed for proteins involved in stable and fundamental biological processes, such as metabolism (e.g., Ppt2a and Gatm), cytoskeletal organization (e.g., Col18a1), and the translation machinery (e.g., Eif4enif1). This atlas offers high-resolution and in-depth molecular insights into zebrafish development, providing a resource for developmental biologists to generate hypotheses for functional analysis of proteins during early vertebrate embryogenesis. HighlightsO_LIA global protein expression database with high time resolution is created for zebrafish embryos. C_LIO_LIDistinct patterns of protein expression correlate with biological processes. C_LIO_LITranscription factors have a burst of expression from the gastrulation stage. C_LIO_LIDevelopmental stage-specific protein expressions were assigned to chromosomes and tissues. C_LIO_LIHigh-resolution embryonic transcriptome and proteome datasets were compared and connected. C_LI

developmental biology↗

Hierarchical Anchoring Gating Dictates Specific H4K16 Acetylation by the Human MSL Complex

Histone acetylation is a versatile post-translational modification essential for diverse biological processes. While nearly all histone acetyltransferases (HATs) act promiscuously on multiple lysine residues, the human male-specific lethal (MSL) acetyltransferase complex mediates strictly site-specific acetylation of histone H4 at lysine 16 (H4K16ac), with its underlying mechanism remaining enigmatic. Here, we leveraged chemical protein synthesis to engineer a semisynthetic nucleosome probe that traps the MSL complex in a catalytically engaged state and determined its 3.12 [A] cryo-electron microscopy (cryo-EM) structure, which reveals a hierarchical anchoring-gating mechanism responsible for stringent H4K16 selectivity. The MSL complex adopts a dual-anchoring mode to bind nucleosomal DNA at superhelix location (SHL) 1.5 and the H2A-H2B acidic patch. Three spatially coordinated gating elements (the MSL1 anchor helix, KAT8 gating helix, and KAT8 gating hairpin) then conformationally constrain the H4 N-terminal tail, funneling H4K16 side chain exclusively into the active site while sterically occluding flanking lysines. Targeted mutations disrupting these interfaces impair H4K16ac in vitro and in cells, with concomitant defects in chromatin accessibility and transcription. Beyond the monomeric 1:1 complex, cryo-EM analysis identifies a 2:2 MSL-nucleosome assembly, wherein MSL3 dimerization mediates inter-nucleosomal contacts linked to genome-wide H4K16ac patterning. Collectively, our work delineates a residue-to-domain framework in which a chromatin acetylation writer hardwires specific catalysis into nucleosome engagement and scales this precision to higher-order chromatin architecture, providing a mechanistic foothold for understanding aberrant MSL-encoded chromatin programs in diseases.

biochemistry↗

Somatic mutation in human cerebellum illustrates neuron type-specific patterns of age-related mutation

Human neurodegenerative disorders are characterized by exquisite specificity for neuronal types, but the basis of this is unknown. Here, we show that cerebellar granule neurons (GN)--the most abundant neuronal type in the human brain--accumulate somatic mutations in patterns highly distinct from cerebral cortical neurons, and more closely resembling oligodendroglia and other dividing cells. We find shared mutational signatures between normal aging GNs and medulloblastoma subtypes, suggesting the GN lineage as a tumor cell of origin. Whole-genome sequence of multiple single GNs from the same donor allowed analysis of specific times of neurogenesis, revealing a rich lineage tree that includes GNs that become postmitotic 2 years or more after birth, yet migrating postnatally to populate both the cerebellar vermis and the distant cerebellar hemisphere. Our results show that neuronal type-specific somatic mutation patterns enlighten normal development, cancer origins and potentially the cell type-specificity of neurodegeneration.

neuroscience↗

A human gut-BBB-brain microphysiological model for studying neurodegenerative diseases

The gut-brain axis has emerged as a crucial factor in neurodegeneration, with growing evidence linking gut dysbiosis and metabolic dysfunction to Alzheimers disease (AD) progression. Unfortunately, the lack of human-relevant in vitro models limits our ability to effectively explore the mechanism of this axis. To address this gap, we have developed a human induced pluripotent stem cell (iPSC)-derived gut-blood-brain barrier (BBB)-brain microphysiological system that enables systematic investigation of gut-brain interaction in the context of AD under controlled conditions. Our findings reveal that the interaction between gut and brain organoids can promote the maturation of brain organoids, making them more similar to their physiological characteristics in vivo. Additionally, co-culture gut and brain organoids better recapitulates the pathological features of AD. We also discovered that gut organoids of AD can trigger neurodegenerative disease manifestations in healthy brain organoids. In summary, our microphysiological system provides a novel and versatile in vitro platform for studying the interaction between the gut and brain in neurodegenerative diseases.

neuroscience↗

HDAC11 Regulates RNA Splicing via De-Fatty Acylation of SF3B2

Histone deacetylase 11 (HDAC11) is a lysine de-fatty acylase whose cellular substrates and mechanisms remain incompletely defined. Here, using metabolic labeling, mass spectrometry, click chemistry, and standard molecular biology, we show that SF3B2 is modified by lysine myristoylation at K10 and that HDAC11 efficiently removes this modification in cells, establishing SF3B2 as a direct enzymatic substrate. A de-myristoylation mimetic mutant (SF3B2 K10R) exhibits altered pre-mRNA binding activity in a context-dependent manner. In HCC cells, loss of SF3B2 lysine myristoylation enhances SF3B2 association with androgen receptor (AR) splice variant loci and promotes alternative splicing towards the AR-v7 variant. Consistently, HDAC11 overexpression increases, and HDAC11 knockdown decreases, the AR-v7/AR-FL splice isoform ratio in HCC cells in a manner requiring HDAC11 catalytic activity and recapitulated by SF3B2 K10R. In contrast, modulation of HDAC11 does not alter AR splicing in prostate cancer cells, indicating cell type specific regulation. Together, these findings establish lysine myristoylation as a reversible regulatory modification on a spliceosomal component and reveal HDAC11-catalyzed de-myristoylation of SF3B2 as a mechanism that can tune alternative splicing in liver cancer cells. In BriefClements et al. utilize metabolic labelling, mass spectrometry, click chemistry, and protein and RNA biochemistry to establish that a histone deacetylase enzyme, HDAC11, can influence RNA splicing through de-fatty acylation of the RNA splicing factor SF3B2. De-fatty acylation of SF3B2 at K10 by HDAC11 modulates SF3B2s pre-mRNA binding to AR splice variant loci, thereby driving alternative splicing of the AR-v7 variant in a cell type dependent manner. This work provides direct mechanistic evidence linking an HDAC to RNA splicing, identifies a reversible lipid modification on SF3B2, and expands current understanding of post-translational regulation of spliceosomal proteins and HDAC11 de-fatty acylation substrates. HighlightsO_LIHDAC11 de-fatty-acylates SF3B2 at K10, revealing a previously unrecognized modification on SF3B2. C_LIO_LISF3B2 de-fatty acylation enhances alternative splice-site binding in liver cancer cells. C_LIO_LIHDAC11 regulates RNA splicing through enzymatic de-fatty acylation of a spliceosomal protein. C_LI

molecular biology↗

Recalibrating Nanoparticle Protein Corona Analysis for Accurate Biological Identity and Soluble Plasma Proteome Profiling

The nanoparticle (NP) protein corona is considered the biological identity that determines NP fate, safety, targeting, and therapeutic effectiveness in biofluids. Nonetheless, standard corona isolation workflows assume the recovered protein signature originates primarily from plasma proteins adsorbed directly onto the NP surface, while largely overlooking co-isolation of endogenous nanoscale biological structures such as extracellular vesicles (EVs). This oversight can distort the apparent "biological identity" of the NP. Here, we show that EVs are a major hidden contributor to the perceived protein corona composition in human plasma. Using highly monodispersed polystyrene NPs (50-1000 nm) and superparamagnetic beads, we compared corona formation in standard human plasma and plasma depleted of an EV- enriched sedimentable fraction by ultracentrifugation at 100,000 x g for 2 h, with the recovered vesicles subsequently characterized by MACSPlex immunoaffinity analysis. Mass spectrometry revealed that EV depletion reduced the number of proteins identified on polystyrene NPs by 60-75% and on magnetic beads by 45-50%, demonstrating a substantial fraction of the conventionally assigned corona proteome arises from EV- associated carryover. EV depletion also restructured the apparent abundance hierarchy, increasing the relative prominence of soluble plasma proteins such as albumin and shifting dominant signals away from intracellular cytoskeletal component proteins that are characteristic of EV carryover towards genuine soluble plasma proteins and complement factors. These results highlight that standard corona workflows can inadvertently co-isolate a vast array of EV-associated material and thereby yield inaccurate assignments of protein origin. Distinguishing proteins adsorbed from the soluble phase from EV-surface and intravesicular material is essential for accurate interpretation of NP-biofluid interactions, biomarker discovery, and therapeutic targeting because molecular compartment determines both analytical meaning and drug accessibility. Significance StatementThe nanoparticle (NP) "protein corona" defines how engineered nanomaterials interact with living systems, influencing therapeutic safety, efficacy, and diagnostic utility. Conventionally, corona isolation workflows assume that recovered proteins were adsorbed directly from the fluid phase. This study reveals a major, previously overlooked source of analytical distortion: standard separation techniques routinely co-isolate endogenous extracellular vesicles (EVs), drastically distorting the perceived biological identity of NPs. Depletion of an EV-enriched sedimentable fraction by ultracentrifugation reduced identified corona proteins by up to 75% and restructures the apparent proteomic hierarchy. Distinguishing true soluble adsorbates from vesicular carryover is essential for accurately predicting NP behavior in vivo and prevents false positives in nano- diagnostics, establishing a critical new standard for high-fidelity biomarker discovery and nanomedicine.

bioengineering↗

Inhibition of Endocannabinoid Degradation in Astrocytes Reprograms Glial Reactivity and Prevents Seizure Sequelae

BackgroundTemporal lobe epilepsy (TLE) is the most common form of focal epilepsy and is characterized by a pathological cascade of excitotoxicity that leads to neuroinflammation, progressive neuronal loss, and subsequent cognitive decline. Despite its prevalence, effective disease-modifying therapies remain lacking. Previous studies have demonstrated that the endocannabinoid system contributes to epileptic activity. In particular, inactivation of monoacylglycerol lipase (MAGL), the key rate-limiting enzyme responsible for the degradation of the endocannabinoid 2-arachidonoylglycerol (2-AG), an endogenous lipid mediator with anti-inflammatory and neuroprotective properties, suppresses seizures and reduces neuroinflammation. However, the cellular and molecular mechanisms underlying these protective effects remain unclear. MethodsTo dissect the cellular mechanisms underlying MAGL-mediated neuroprotection, we employed a kainic acid (KA)-induced status epilepticus model in mice with global, astrocyte-specific (aKO), and neuron-specific (nKO) deletion of mgll. We combined single-nucleus RNA sequencing (snRNA-seq) to map the transcriptomic landscape of glial responses with pharmacological interventions to validate key signaling pathways, as well as behavioral assays to assess functional recovery. ResultsWe demonstrated that astrocyte-specific, but not neuron-specific, mgll deletion was sufficient to attenuate seizure susceptibility and hippocampal neurodegeneration, thereby recapitulating the protective phenotype observed in global knockouts. Transcriptomic profiling revealed that astrocytic MAGL deficiency fundamentally reshaped the glial response to injury by preventing the transition to pro-inflammatory reactive astrocyte states and suppressing the activation of disease-associated microglia (DAM). Mechanistically, we identified a signaling pathway in which the neuroprotective effects of MAGL inhibition depend on cannabinoid receptor 1 (CB1) activation and are mediated by downstream peroxisome proliferator-activated receptor {gamma} (PPAR-{gamma}) signaling. Either genetic deletion of CB1 or pharmacological blockade of PPAR-{gamma} abolished the protective effects. Furthermore, aKO mice exhibited reduced neuronal loss, preserved synaptic structural integrity and protection against post-seizure cognitive deficits. ConclusionThese findings reveal astrocytic MAGL as a crucial regulatory node in the epileptic brain and demonstrated that enhancing 2-AG signaling in astrocytes orchestrates neuroprotection via CB1-PPAR-{gamma} signaling pathways, thereby attenuating neuroinflammation, preserving synaptic function, and preventing the cognitive comorbidities associated with epilepsy.

neuroscience↗

Decades of dreams coming true: capillary zone electrophoresis-mass spectrometry for reproducible multi-level proteomics

Capillary zone electrophoresis (CZE)-mass spectrometry (MS) has been proposed as a powerful analytical tool for bottom-up, top-down, and native proteomics (multi-level proteomics) decades ago to analyze complex biological samples at the levels of peptides (bottom-up), proteoforms (top-down), and complexoforms (native). However, its broad adoption has been impeded by the limited robustness and reproducibility. Here, we present multi-level proteomics data from nearly 170 CZE-MS runs ([~]170 hours of instrument time), demonstrating qualitatively (i.e., the number of identified peptides and proteoforms, the number of detected complexoforms, and their migration time) and quantitatively (i.e., peptide, proteoform, and complexoform intensity) reproducible measurement of complex samples with varying levels of complexity, i.e., Escherichia coli cells, HeLa cells, and human plasma. CZE-MS-based native proteomics enabled the detection of hundreds of complexoforms up to 800 kDa from the complex systems via consuming only nanograms of protein material. The results indicate that CZE-MS is sensitive and reproducible enough for broad adoption for multi-level proteomics-based biomedical research.

systems biology↗

An Advanced Humanized Systemic Lupus Erythematosus Model Enables Parallel Profiling of B Cell-Targeted Therapies

B cell-targeted therapies represent a transformative frontier for systemic lupus erythematosus (SLE) intervention, yet clinical recommendation of specific treatment is hampered by the challenge to perform head-to-head comparisons of efficacy-toxicity trade-offs and tissue-specific impacts in patients. To address this gap, an advanced Toll-like receptor 7 (TLR7) agonist-induced SLE model is developed in a NCG-M (NOD-Prkdcem26Cd52Il2rgem26Cd22Rosa26em1Cin(hCSF2&IL3&KITLG)/Gpt) human immune system (HIS) mice. This model enables parallel evaluation of multiple B cell-directed therapies within a controlled cohort study. It recapitulates core SLE pathologies--including immune effector cell augmentation, autoantibody production and glomerulonephritis--within 2 months, demonstrating greater severity and clinical fidelity than conventional pristane-induced systems. Validated through replication of clinical responses to rituximab and belimumab, the platform directly compares two emerging modalities: universal chimeric antigen receptor-T cells (UCAR-T) elicits delayed but profound B-cell reset correlating with superior reduction in renal pathology and autoantibodies, while T cell engagers (TCEs) mediate rapid yet partial B-cell depletion and transient efficacy. UCAR-T concurrently induces greater acute inflammatory responses, aligning with its distinct toxicity profile. By resolving therapy-specific effects on human immune dynamics and symptom control, this study empowers context-specific therapeutic selection for SLE, advancing tailored management strategies.

immunology↗

Global Proteomic Analysis of Colorectal Cancers Stratified by Microsatellite Instability Subtype Reveals Protein Differences

Lynch syndrome, historically known as hereditary nonpolyposis colorectal cancer, is caused by germline mutations in the DNA mismatch repair (MMR) genes, MLH1, MSH2 (EPCAM), MSH6, and PMS2. While the genetic changes associated with Lynch Syndrome have previously been characterized, there have not been studies of the associated proteomic alterations, in part because of the limited availability of primary samples and the absence of in vitro model systems. In this study, the first large-scale tissue proteomic assessment of Lynch Syndrome samples as well as three other subtypes of colorectal cancer was completed with specimens from the Ohio Colorectal Cancer Prevention Initiative. The cohort contained three groups of microsatellite unstable (MSI-high) CRC patients (Lynch syndrome, double somatic MMR mutation, and MLH1 hypermethylation) and a group of microsatellite stable (MSS) CRC patients. A total of 122 tumor and complimentary normal mucosa samples from 61 patients were evaluated using label-free bottom-up proteomic analysis. Hierarchical clustering analysis of the global proteome showed that the MSS group was significantly different than the three MSI-high groups. Of the 1,084 proteins found to be dysregulated across all four colorectal cancer subtypes, there were age at diagnosis associated shifts in proteins correlated with tumor proliferation and immune regulation for the Lynch syndrome and Double Somatic samples. The proteins TPD52, GMDS, and DSP showed increased protein abundance correlated with older age at diagnosis. In addition, the Lynch syndrome samples showed substantial sex-based differences in immune and inflammatory pathways, for example, downregulation of ZG16, DIS3, and WDR43. This study fills a critical gap as the first proteomic characterization of Lynch syndrome samples to date. Data are available via ProteomeXchange with identifier PXD073693. TeaserThis is the first study of the global proteomic differences between Lynch Syndrome and other forms of colorectal cancer.

cancer biology↗

Dysregulated RNA G-quadruplex binding proteins reveal shifted stress responses in Alzheimer's Disease

Single-cell sequencing has reshaped the research paradigm of Alzheimers Disease (AD) by revealing the heterogeneous transcriptional states of brain cells. Large single-cell cohort datasets, such as ROSMAP and SEA-AD, provide valuable atlases but primarily focus on RNA expression and chromatin accessibility, often overlooking the roles of RNA secondary structures. Although RNA G-quadruplexes (rG4s) are increasingly recognized as regulators of neurodegeneration, their interacting RNA-binding proteins (RBPs) remain poorly understood. We analyzed multiple independent scRNA-seq datasets to investigate rG4-associated biological functions across AD-relevant cell types and transcriptional states. We discovered that rG4-binding RBPs (RG4BPs) directly regulate essential glial cell functions, which are frequently impaired in AD. At the transcriptional state level, distinct sets of dysregulated RG4BPs correspond to the impaired state-specific biological features of astrocytes and microglia during AD progression, including a shift from an acute protective state to a chronic stress-associated state. This progressive state transition is accompanied by glial exhaustion and accumulated rG4s, which ultimately compromise glial support functions. We report several RG4BPs that are known regulators, including CIRBP, HSP90AA1, VIM, and PICALM, whose altered expression is associated with either pathological activation or severe functional impairment. These dysregulated RG4BPs provide a lens to examine the mechanism of rG4 accumulation in AD and position RG4BPs as novel targets for understanding and potentially intervening in AD progression.

neuroscience↗

A Beneficial Endornavirus Enhances the Fitness of Phytopathogenic Fungus Rhizotonia solani

Although viruses are primarily characterized as pathogenic agents, certain viruses confer advantages to their hosts. The extent to which a virus can improve host biological performance, however, remains a fascinating topic in virology. An endornavirus, Rhizoctonia solani endornavirus IM (RsEV-IM), was identified as prevalent in Rhizoctonia solani isolates obtained from potato plants. Comparative analysis with a virus-free isogenic strain demonstrated that RsEV-IM infection enhances mycelial growth, sclerotium formation, stress tolerance, and fungal virulence across multiple plant species. Inoculation tests involving numerous R. solani strains confirmed that only RsEV-IM-infected strains exhibited high pathogenicity, independent of other mycovirus infections. Additionally, its secreted protein fraction of RsEV-IM-infected fungus contained elevated levels of various proteins, including those involved in cell wall degradation. This fraction not only facilitated R. solani infection but also suppressed the growth of other fungi and bacteria. These findings position RsEV-IM as a beneficial virus that widely enhances its hosts biological fitness. From both pathological and ecological perspectives, these observations are significant, as they reveal that a mycovirus can serve as a key virulence determinant in fungal populations and potentially shape microbial community dynamics in natural environments. ImportanceFungal pathogenicity and ecological traits have long been thought to be primarily governed by endogenous genetic factors. However, this study reveals a mutualistic relationship between an endornavirus (RsEV-IM) and Rhizoctonia solani, demonstrating that viral infection enhances fungal virulence and ecological fitness. RsEV-IM stimulates fungal growth and the secretion of cell wall-degrading enzymes, resulting in a severe disease phenotype. Ecologically, RsEV-IM-infected fungi potentially gain a competitive advantage over soil microbiota. These findings present a key example of a virus acting as an essential extrachromosomal determinant of fungal pathogenicity and ecosystem interactions. Our results advance the understanding of fungal virulence mechanisms and underscore the broader significance of beneficial virus-fungus associations in agriculture and microbial ecology.

microbiology↗

Therapeutic interleukin-2 rewires skeletal-immune circuits to reverse postmenopausal bone loss

Postmenopausal osteoporosis results from excessive osteoclast activity, but the immune circuits that limit osteoclastogenesis in the bone marrow remain poorly understood. Here, we tested a clinically accessible immunotherapy low-dose interleukin-2 (IL-2) as a therapeutic intervention in mice with established ovariectomy-induced bone loss, integrating microcomputed tomography imaging, single-cell transcriptomics, genetic perturbation, and human monocyte-osteoclast assays. Therapeutic administration of IL-2 reversed trabecular bone loss, expanded CXCR3 regulatory T cells in bone marrow, and promoted IL-10- and CGRP-producing ILC2s that were required for protection. IL-2 also acted directly on the osteoclast lineage, suppressing mouse and human osteoclastogenesis through activation of a STAT1-IRF1-dependent IFN program in RANKL-stimulated monocytes. Together, these data define an IL-2-responsive skeletal-immune network that can be therapeutically engaged to suppress osteoclastogenesis, which opens new avenues for cytokine-based immunotherapies in postmenopausal osteoporosis and related bone disorders.

immunology↗