Biology subjects

Xiao, H.

Publications and source records attributed to Xiao, H..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Multi-omics analysis reveals genetic regulatory mechanismsof muscle traits in wild and domesticated Bactrian camels

Bactrian camels, large domesticated animals adapted to extreme environments, have evolved under natural and artificial selection to suit their living conditions and meet human needs. In arid and semi-arid regions, they provide valuable resources through economically important traits such as meat, milk, and wool production, contributing significantly to both economy and ecology. However, research on gene function, adaptive evolution, and molecular mechanisms underlying complex traits in Bactrian camels remains limited, constraining the full utilization of their breeding potential and conservation efforts.To address this gap, we performed whole-genome resequencing (WGS) on 35 domesticated Bactrian camels from the Chinese Sunite local population and integrated this data with publicly available WGS data from 112 Asian Bactrian camels. Our comprehensive analysis revealed significant genetic differences and genomic features between wild and domesticated Bactrian camels. We further integrated 27 epigenomic (ATAC-seq) and transcriptomic (RNA-seq) datasets from eight biologically important tissues of four Bactrian camels, along with skeletal muscle scRNA-seq and scATAC data. This allowed us to identify tissue-specific genes, regulatory elements, and genes under positive selection.Our integrated analysis identified target genes and their upstream regulatory elements, including potential regulatory transcription factors, with a focus on positively selected regions in Bactrian camel muscle tissue. We constructed regulatory pathways from key SNPs to regulatory elements to genes, and for the first time, identified regulatory elements in major tissues of the Bactrian camel genome. Our results also summarized the single-cell transcriptional landscape of Bactrian camel skeletal muscle, revealing cellular heterogeneity and genetic expression patterns across two developmental stages.This comprehensive regulatory element map provides a valuable resource for genetic and genomic studies in Bactrian camels. It reveals key regulatory networks, important genes, and regulatory elements influencing muscle development, as well as potentially significant functional variants affecting meat production traits. These findings will provide crucial data support for future genetic improvement and breeding efforts in Bactrian camels.

genetics↗

bioRxiv2025

Memorability of Images Positively Influences Associative Memory Retention

Enhancing memory function is essential for daily living and cognitive health, particularly amid population aging and cognitive decline. However, current methods for memory enhancement often require specialized interventions or effortful practice. Here, we present evidence that the intrinsic memorability of images can serve as a simple, scalable, and involuntary strategy for improving associative memory. We studied its effects on associative memory in adults of distinct ages, memory retention in cognitively impaired older adults, and vocabulary learning in foreign language learners. Our results show that highly memorable images significantly enhance the recall of associated words, especially when the cue image and target word are semantically unrelated. Notably, these effects persist for at least one week and are robust across age groups and cognitive status. In a foreign language vocabulary task, pairing words with memorable images led to either improved recall accuracy or reduced learning time. These findings highlight that, in addition to being an intrinsic memory-enhancing property, image memorability also serves as a general facilitator of associative memory, via a method that is easy to adopt, requires minimal conscious effort, and can benefit the general public, particularly learners and cognitive impairment patients in educational and clinical settings.

neuroscience↗

bioRxiv2025

C9orf72/SMCR8 complex maintains microglial homeostasis via RAB8A-ESCRT-mediated lysosomal repair

Microglia are critical regulators of neuroinflammation and neurodegeneration. Haploinsufficiency of C9orf72, the most common genetic cause of ALS and FTD, has been mainly linked to autophagy-lysosomal pathway defects, but its precise role in microglial lysosomal function remains unclear. Here we identify the C9orf72/SMCR8 complex as a key regulator of microglial homeostasis through lysosomal repair. Loss of C9orf72 and SMCR8 in mice causes age-dependent neuroinflammation and microgliosis, with microglia adopting a disease-associated state. In aged CNS tissue, microglia display lysosomal damage, marked by galectin-3 upregulation and its accumulation on lysosomes. To model this process, we applied the lysosomotropic agent LLOMe to microglia, which recapitulated lysosomal damage and revealed defective recruitment of phosphorylated RAB8A and the ESCRT machinery in C9orf72/SMCR8-deficient cells. Notably, mutant microglia accumulate GTP-bound RAB8A, which becomes aberrantly hyperphosphorylated and mislocalized to non-lysosomal vesicles. We further show that the GAP activity of the C9orf72/SMCR8 complex is essential for lysosomal repair. These findings uncover a previously unrecognized role for the C9orf72/SMCR8 complex in coordinating RAB8A-ESCRT-mediated lysosomal repair, thereby safeguarding microglial homeostasis and limiting neuroinflammation.

cell biology↗

bioRxiv2025

Metabolomics-Guided Machine Learning Reveals Diagnostic and Mechanistic Biomarkers in CHB with MASLD

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) often coexists with chronic hepatitis B (CHB), yet early diagnosis remains challenging, particularly in non-obese patients or those with subclinical features. This study aimed to identify metabolic signatures of CHB-related MASLD and construct a predictive model using untargeted metabolomics integrated with machine learning. MethodsSerum metabolomics was performed on 160 subjects (80 CHB + MASLD and 80 healthy controls). Differential metabolites were identified and analyzed using KEGG enrichment and 4 machine learning algorithms (Random Forest, XGBoost, SVM, and LASSO). Metabolite-clinical correlations and diagnostic model performance were evaluated. ResultsA total of 924 differential metabolites were identified, with significant enrichment in pathways related to the TCA cycle, sphingolipid metabolism, and amino acid turnover. Machine learning prioritized six robust and biologically relevant metabolites: L-aspartic acid, succinic acid, caproic acid, sebacic acid, monomenthyl succinate, and glycolaldehyde, which consistently distinguished CHB + MASLD patients from controls (AUC > 0.75). These metabolites reflect key disruptions in mitochondrial function, lipid oxidation, and redox homeostasis. Integrated models combining metabolomics with clinical indices achieved perfect classification (AUC = 1.000). ConclusionCHB-associated MASLD is driven by systemic metabolic remodeling centered on mitochondrial overload, oxidative stress, and impaired amino acid metabolism. The identified metabolites provide mechanistic insights and hold promise for non-invasive MASLD screening in CHB patients. This study underscores the potential of multi-algorithmic metabolomics in advancing early diagnosis and personalized management of complex liver comorbidities.

bioinformatics↗

bioRxiv2025

Desert Hedgehog mediates stem Leydig cell differentiation through Ptch2/Gli1/Sf1 signaling axis

Desert Hedgehog (Dhh) mutations cause Leydig cell dysfunction, yet the mechanisms governing Leydig lineage commitment through Dhh-mediated receptor selectivity, transcriptional effector specificity, and steroidogenic coupling remain elusive. In this study, using CRISPR/Cas9-mediated gene knockout and stem Leydig cells (SLCs) transplantation, we identified a critical Dhh/Patched 2 (Ptch2)/Glioma-associated oncogene homolog 1 (Gli1)/steroidogenic factor 1 (Sf1) signaling axis essential for SLC differentiation in Nile tilapia (Oreochromis niloticus). Dhh deficiency resulted in defective adult Leydig cells and androgen insufficiency. Rescue experiments involving 11-ketotestosterone administration and a Dhh agonist treatment, combined with SLCs transplantation, demonstrated that Dhh regulates SLC differentiation, not survival. In vitro knockout of ptch1 and ptch2 in SLCs revealed that Ptch2 likely acts as the functional receptor for Dhh. This was further supported by in vivo genetic rescue experiments, where ptch2 mutation did not impair testicular development, yet completely rescued the testicular defects in dhh mutants--consistent with Ptch2 acting as an inhibitory receptor whose loss alleviates Dhh pathway suppression. Luciferase assays in Gli-knockout SLCs demonstrated that Gli1 acts as the primary transcriptional effector, and transactivates sf1 expression. Additionally, functional transplantation assays confirmed that Sf1 is indispensable for SLCs differentiation, as Sf1-overexpressing SLCs rescued differentiation, whereas sf1-mutant SLCs failed. Overall, our work delineates the Dhh-Ptch2-Gli1-Sf1 axis and provides fundamental insights into the endocrine regulation of Leydig cell lineage development. HighlightsO_LIDhh regulates the differentiation of SLCs rather than their survival C_LIO_LIPtch2 acts as the functional receptor for Dhh signaling in SLCs C_LIO_LIGli1 is the principal transcriptional activator for Dhh signaling in SLCs C_LIO_LISf1 is the critical downstream effector of Gli1 in SLCs differentiation C_LI

developmental biology↗

bioRxiv2025

Lactate metabolism antagonizes antiviral innate immunity bypromoting VDAC1-lactylation-mediated mtDNA release

Foot-and-mouth disease (FMD) is an acute, highly contagious disease caused by the foot-and-mouth disease virus (FMDV). Due to its zoonotic nature, this disease not only significantly impacts livestock productivity but also poses a serious threat to human health. FMDV exhibits distinct host specificity, mainly infecting cloven-hoofed animals such as cattle, sheep, pigs, and deer, while perissodactyl animals like horses and donkeys show natural resistance. Elucidating the interspecies differences in response to FMDV infection is essential for understanding the pathogenesis of the virus. In this study, we report that FMDV infection in horse epithelial cells induces the production of lactate, which modulates the function of VDAC1 protein through lactylation, facilitating the release of mtDNA from mitochondria into the cytoplasm. This process activates the cGAS-STING signaling pathway, which stimulates interferon-{beta} expression and suppresses FMDV replication. Our findings provide new insights into the mechanism behind horse resistance to FMDV and lay a theoretical foundation for further research concerning the differential pathogenesis of FMDV infection across species.

cell biology↗

bioRxiv2025

Developing a zebrafish xenograft model of diffuse midline glioma

Diffuse midline glioma (DMG) is a highly aggressive brain tumor that predominantly affects children. Conventional treatments such as radiation therapy can control progression for a time, but DMG kills nearly 100 percent of patients. Although murine models have provided critical insights into the biology of DMG and in assessing new therapeutic strategies, they are not suitable for high-throughput screening to identify and profile novel therapies due to technical challenges, ethical considerations and high cost. Zebrafish (Danio rerio) is an established vertebrate model for large-scale drug screening, and zebrafish have demonstrated the ability to replicate the key biological and pathlogical aspects of human malignancies. Here, we developed a novel method for transplanting human DMG cells into large numbers of zebrafish embyros to speed the assessment of anti-tumor drug efficacy in vivo and thereby facilitate the development of novel therapeutics for clinical translation. We transplanted red fluorescent protein (RFP)-labeled, patient-derived DMG cell lines into zebrafish blastulas. Remarkably, many DMG cells migrate into the developing brain and are present in the midline of the brain 24 hours after blastula injection. Tumor cell burden was monitored by measuring RFP fluorescence intensity changes over time. Time-course images of transplanted tumor cell volumes were acquired, and the interactions between transplanted DMG cells and microglial cells were further analyzed using Imaris software. We have developed a simple and rapid transplantation protocol to establish a zebrafish xenograft model of DMG. Our method involves transplanting DMG cells into the blastula stage (1000 cell stage) of zebrafish embryos, which does not require complex surgical techniques. This approach allows for the transplantation of hundreds of embryos per hour, significantly increasing the efficiency of creating DMG zebrafish xenografts that are suitable for high-throughput drug and gene discovery screens.

cancer biology↗

bioRxiv2025

HIV-Induced Sialoglycans on Infected Cells Promote Immune Evasion from Myeloid Cell-Mediated Killing

Sialic acid-containing glycans (sialoglycans) on pathological cells interact with Siglecs, glyco-immune checkpoint receptors expressed on myeloid cells such as monocytes and neutrophils. This interaction suppresses the cytotoxic functions of these immune cells. We show that HIV infection reprograms the glycosylation machinery of infected cells to increase the expression of specific sialoglycan ligands for Siglecs-3, -7, and -9. These ligands engage Siglecs on myeloid cells, impairing their ability to target HIV-infected cells. Selective disruption of these interactions using 10-1074-Sia, an HIV-specific antibody conjugated to sialidase--an enzyme that removes sialic acids--significantly enhances monocyte- and neutrophil-mediated killing of HIV-infected cells in autologous assays. Treatment with 10-1074-Sia in humanized mice infected with HIV reduces viral load and decreases inflammation. These findings reveal a novel immune evasion mechanism exploited by HIV to evade myeloid cell immune surveillance and highlight the potential of targeting sialoglycan-Siglec interactions to improve immune clearance of HIV-infected cells.

immunology↗

bioRxiv2025

Simultaneous profiling of native-state proteomes and transcriptomes of neural cell types using proximity labeling

Deep molecular phenotyping of cells at transcriptomic and proteomic levels is an essential first step to understanding cellular contributions to development, aging, injury, and disease. Since proteome and transcriptome level abundances only modestly correlate with each other, complementary profiling of both is needed. We report a novel method called simultaneous protein and RNA -omics (SPARO) to capture the cell type-specific transcriptome and proteome simultaneously from both in vitro and in vivo experimental model systems. This method leverages the ability of biotin ligase, TurboID, to biotinylate cytosolic proteins including ribosomal and RNA-binding proteins, which allows enrichment of biotinylated proteins for proteomics as well as protein-associated RNA for transcriptomics. We validated this approach first using well-controlled in vitro systems to verify that the proteomes and transcriptomes obtained reflect the ground truth, bulk proteomes and transcriptomes. We also show that the effect of a biological stimulus (e.g., neuroinflammatory activation by lipopolysaccharide) can be faithfully captured. We also applied this approach to obtain native-state proteomes and transcriptomes from two key neural cell types, astrocytes and neurons, thereby validating the in vivo application of SPARO. Next, we used these data to interrogate protein-mRNA concordance and discordance across these cell types, providing insights into groups of molecular processes that exhibit uniform or cell type-specific patterns of mRNA-protein discordance.

neuroscience↗

bioRxiv2025

GEI-17-Mediated SUMOylation of GDI-1 Regulates Apoptotic Cell Clearance

Apoptotic cell clearance represents the final stage of apoptosis, and involves phagosome formation, maturation, and digestion. Here, we found that SUMO modifications participate in apoptotic cell clearance by influencing phagosomal degradation activity in C. elegans. The SUMO E3 ligase, GEI-17, SUMOylates GDP dissociation inhibitor (GDI-1) at K270 to trigger phagosomal degradation. Upon SUMOylation, GDI-1 facilitates release of GDP-bound RAB-1, which is subsequently converted to the GTP-bound form in a manner dependent on GDI displacement factor, PRAF-3. RAB-1 conversion enables binding and translocation of RAB-7 from the endoplasmic reticulum to Golgi to promote phagosome maturation and degradation activity. In the absence of GDI-1 SUMOylation, GDI-1 binds to GDP-RAB-1, sequestering it in the cytoplasm, resulting in impaired phagosomal degradation. Furthermore, we found SUMOylation of GDI1 at a conserved site plays a crucial role in efferocytosis regulation in mammals. This study defines a previously unrecognized mechanism by which SUMOylation drives apoptotic cell clearance.

cell biology↗

bioRxiv2024

OsMORF protein selectively promotes the dual-localized RNA editing factor OsPGL1 binding to its target RNA

Post-transcriptional RNA editing plays a key regulatory role and serves as a genetic information proofreading mechanism. In flowering plants, RNA editing typically involves the removal of amino groups from cytidine to produce uridine in both plastids and mitochondria. In our previous work, we identified OsPGL1 as a rare organelle editing factor that regulates both mitochondrial and chloroplast RNA in rice. This protein mediates RNA editing and is associated with several OsMORFs. We speculated that they may form editing complex to regulate editing events, but we are still unclear about the detailed mechanism between OsMORF proteins and OsPGL1, as well as their roles in target RNA recognition and binding. In this study, we found that three OsMORFs can significantly promote the binding of OsPGL1 to target RNA in vitro. Notably, OsMORF8 can promote OsPGL1 to form a homologous dimer, thereby enhancing RNA binding to a greater extent. The E and DYW motifs do not affect the role of MORF proteins in RNA editing events, ruling out the potential influence of these two special motifs. In addition, we predicted a series of supercomplex structures of OsPGL1, the OsPGL1-RNA ligand complex, the OsPGL1-OsMORF2-OsMORF8-OsMORF9 complex, and the OsPGL1-OsMORF2-OsMORF8-OsMORF9-RNA complex. We determined that the conformational changes and newly added positively charged surface caused by OsMORF on OsPGL1 are the main reasons for MORF to promote the binding of OsPGL1 to RNA. Based on some new discoveries, we have expanded the RNA editing complex model, which greatly enhances our understanding of plant RNA editing complexes. Short summaryPPRs and MORFs are two kinds of RNA editing factors, both can mediate organelle RNA editing, the difference between them is that PPR can directly bind target RNA, MORF does not directly bind RNA, but can independently or assist PPR in performing RNA editing. Function of MORF protein in post-transcriptional processing is not clear, our study verifies the function of MORFs in the process of PPR binding RNA through molecular biology. We also analyzed the interaction network between PPR-MORF-RNA from the perspective of structural biology.

plant biology↗

bioRxiv2024

PMAIP1-Mediated Glucose Metabolism and its Impact on the Tumor Microenvironment in Breast Cancer: Integration of Multi-Omics Analysis and Experimental Validation

BackgroundGlucose metabolism in breast cancer has a potential effect on tumor progression and is related to the immune microenvironment. Thus, this study aimed to develop a glucose metabolism- tumor microenvironment score to provide new perspectives on breast cancer treatment. MethodData were acquired from the Gene Expression Omnibus and UCSC Xena databases, and glucose-metabolism-related genes were acquired from the Gene Set Enrichment Analysis database. Genes with significant prognostic value were identified, and immune infiltration analysis was conducted, and a prognostic model was constructed based on the results of these analyses. The results were validated by in vitro experiments with MCF-7 and MCF-10A cell lines, including expression validation, functional experiments, and bulk sequencing. Single-cell analysis was also conducted to explore the role of specific cell clusters in breast cancer, and Bayes deconvolution was used to further investigate the associations between cell clusters and tumor phenotypes of breast cancer. ResultsFour significant prognostic genes (PMAIP1, PGK1, SIRT7, and SORBS1) were identified, and, through immune infiltration analysis, a combined prognostic model based on glucose metabolism and immune infiltration was established. The model was used to classify clinical subtypes of breast cancer, and PMAIP1 was identified as a potential critical gene related to glucose metabolism in breast cancer. Single-cell analysis and Bayes deconvolution jointly confirmed the protective role of the PMAIP1+ luminal cell cluster.

bioinformatics↗

bioRxiv2024

Real-Time Visualization of Protein Microenvironment Changes with High Spatial Resolution in Live Cells via Site-Specific Incorporation of Rotor-Based Fluorescent Noncanonical Amino Acids

Traditional methods, such as the use of fluorescent protein fusions and environment-sensitive fluorophores, have limitations when studying protein microenvironment changes at the finest spatial resolution. These techniques often rely on bulky proteins or tags restricted to the N- or C-terminus, which can disrupt the natural behavior of the target protein and dramatically limit the ability of their method to investigate noninvasively microenvironment effects. To overcome these challenges, we have developed an innovative strategy to visualize microenvironment changes of protein substructures in real-time by genetically incorporating environment-sensitive noncanonical amino acids (ncAAs) containing rotor-based fluorophores (RBFs) at specific positions within a protein of interest. Through computational redesign of aminoacyl-tRNA synthetase, we successfully incorporated these rotor-based ncAAs into various proteins in mammalian cells. By site-specifically placing these ncAAs in distinct regions of proteins, we detected microenvironmental changes of several different protein domains during events such as aggregation, clustering, aggregation disassembly, and cluster dissociation.

biochemistry↗

bioRxiv2024

WIMOAD: Weighted Integration of Multi-omics data for Alzheimer's Disease (AD) Diagnosis

INTRODUCTIONAlzheimers disease (AD), the most prevalent subtype of dementia, is characterized by a gradual decline in brain cognitive function. Early detection is critical for initiating timely interventions that may delay the severe progression of the disease. Recent advances in next-generation sequencing (NGS) offer promising, non-invasive, and cost-effective strategies for AD screening. However, most current approaches rely on single-omics data, which may fail to capture the complex biological heterogeneity among individuals. METHODSWe introduce WIMOAD, a stacking ensemble and weighted multi-omics integration for AD diagnosis. It leverages paired gene expression and methylation data from ADNI and presents a meta learning framework for multi-cognitive stage classification during AD progression. RESULTS AND DISCUSSIONWIMOAD outperforms existing integration methods in AD diagnosis, effectively capturing complex multi-omics patterns linked to clinical outcomes. Its interpretability also facilitates the detection of novel biomarkers across different omics layers.

bioinformatics↗

bioRxiv2024

RanBALL: An Ensemble Random Projection Model for Identifying Subtypes of B-cell Acute Lymphoblastic Leukemia

As the most common pediatric malignancy, B-cell acute lymphoblastic leukemia (B-ALL) has multiple distinct subtypes characterized by recurrent and sporadic somatic and germline genetic alterations. Identifying B-ALL subtypes can facilitate risk stratification and enable tailored therapeutic design. Existing methods for B-ALL subtyping primarily depend on immunophenotyping, cytogenetic tests and genomic profiling, which would be costly, complicated, and laborious. To overcome these challenges, we present RanBALL (an ensemble Random projection-based model for identifying B-ALL subtypes), an accurate and cost-effective model for B-ALL subtype identification. By leveraging random projection (RP) and ensemble learning, RanBALL can preserve patient-to-patient distances after dimension reduction and yield robustly accurate classification performance for B-ALL subtyping. Benchmarking results based on >1700 B-ALL patients demonstrated that RanBALL achieved remarkable performance (accuracy: 0.93, F1-score: 0.93, and Matthews correlation coefficient: 0.93), significantly outperforming state-of-the-art methods like ALLSorts in terms of all performance metrics. In addition, RanBALL performs better than tSNE in terms of visualizing B-ALL subtype information. We believe RanBALL will facilitate the discovery of B-ALL subtype-specific marker genes and therapeutic targets to have consequential positive impacts on downstream risk stratification and tailored treatment design. To extend its applicability and impacts, a Python-based RanBALL package is available at https://github.com/wan-mlab/RanBALL.

bioinformatics↗

bioRxiv2024

Haplotype-resolved assemblies provide insights into genomic makeup of the oldest grapevine cultivar (Munage) in Xingjiang

AbstractsMunage, an ancient grape variety that has been cultivated for thousands of years in Xinjiang, China, is recognized for its exceptional fruit traits. There are two main types of Munage: white fruit (WM) and red fruit (RM). However, the lack of a high-quality genomic resources has impeded effective breeding and restricted the potential for expanding these varieties to other growing regions. In this study, we assembled haplotype-resolved genome assemblies for WM and RM, alongside integrated whole genome resequencing (WGS) data and transcriptome data to illuminate specific mutations and associated genes in Munake and the genes associated with fruit color traits. Selective analysis between Munage clones and Eurasian grapes suggested that adaptive selection exists in Munage grapes, with genes enriched in processes including cell maturation, plant epidermal cell differentiation, and root epidermal cell differentiation. The study examined the mutations within Munage grapes and found that the genes PMAT2 on chromosome 12 and MYB123 on chromosome 13 are likely responsible for color variation in RM. These findings provide crucial genetic resources for investigating the genetics of the ancient Chinese grape variety, Munage, and will facilitate the genetic improvement in grapevine.

genomics↗

bioRxiv2024

Evaluation of a Deep Learning Based Approach to Computational Label Free Cell Viability Quantification

One of the most common techniques found in a cell biology or tissue engineering lab is the cytotoxicity assay. This can be performed using a variety of different dyes and stains and various protocols to result in a clear indication of dead and live cells within a culture to quantify the viability of a culture and monitor for sudden drops or increases in viability by a drug, material, viral vector, etc introduced into the culture. This assay helps cell biologists determine the health of their culture and what toxicity added substances may add to the culture and whether they are appropriate and safe to use with human cells. However, many of the dyes and stains used for this process are eventually toxic to cells, rendering the cells useless after testing and preventing real time monitoring of the same culture over a period of hours or days. Computation biology is moving cell biology towards novel and innovative techniques such as in silico labeling and dye free labeling using deep learning algorithms. In this work, we investigate whether it is feasible to train a Resnet CNN model to detect morphological changes in human cells that indicate cell death in order to classify cells as live or dead without utilizing a stain or dye. This work also aims to train one CNN model to count all cells regardless of viability status to get a total cell count, and then one CNN model that specifically identifies and counts all of the dead cells for an accurate dead and live cell total by utilizing both pieces of data to determine a general viability percentage for the culture. Additionally, this work explores the use of various image enhancements to understand if this process helps or impedes the deep learning models in their detection of total cells and dead cells.

cell biology↗

bioRxiv2024

Mitochondrial complex III-derived ROS amplify immunometabolic changes in astrocytes and promote dementia pathology

Neurodegenerative disorders alter mitochondrial functions, including the production of reactive oxygen species (ROS). Mitochondrial complex III (CIII) generates ROS implicated in redox signaling, but its triggers, targets, and disease relevance are not clear. Using site-selective suppressors and genetic manipulations together with mitochondrial ROS imaging and multiomic profiling, we found that CIII is the dominant source of ROS production in astrocytes exposed to neuropathology-related stimuli. Astrocytic CIII-ROS production was dependent on nuclear factor-{kappa}B (NF-{kappa}B) and the mitochondrial sodium-calcium exchanger (NCLX) and caused oxidation of select cysteines within immune and metabolism-associated proteins linked to neurological disease. CIII-ROS amplified metabolomic and pathology-associated transcriptional changes in astrocytes, with STAT3 activity as a major mediator, and facilitated neuronal toxicity in a non-cell- autonomous manner. As proof-of-concept, suppression of CIII-ROS in mice decreased dementia-linked tauopathy and neuroimmune cascades and extended lifespan. Our findings establish CIII-ROS as an important immunometabolic signal transducer and tractable therapeutic target in neurodegenerative disease.

neuroscience↗