Biology subjects

Tang, Z.

Publications and source records attributed to Tang, Z..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

MolSpecFlow: Mass-Constrained Hybrid Flow Matching for Joint Molecular-Spectral Analysis

Identifying the "dark matter" of the chemical universe requires bridging the fundamental gap between molecules and mass spectra. Existing approaches struggle to accurately map between these distinct data formats, often yielding results that are either chemically implausible or inconsistent with the physical evidence. We introduce MolSpecFlow, a unified foundation model pretrained on 100 million molecules and 42 million spectra, which leverages a hybrid flow matching framework to orchestrate optimal transport paths for spectral peaks and discrete probability flows for molecular tokens. Furthermore, to guarantee the physicochemical validity of the generated structures, we incorporate explicit rule-based constraints into the generative process, utilizing a token-level mass control mechanism that strictly enforces alignment with the precursor molecular weight. MolSpecFlow establishes a new state-of-the-art on the MassSpecGym benchmark, surpassing diffusion and retrieval baselines in de novo generation (Top-1 accuracy +35%), spectral simulation, and molecular retrieval, demonstrating the power of physics-grounded unified modeling.

bioinformatics↗

bioRxiv2026

Optimizing broadly neutralizing antibodies via all-atom interaction modeling and pre-trained language models

Antibody optimization is a fundamental challenge, and the identification of antibody-antigen interactions is crucial in the optimization process. However, current methods cannot accurately predict antibody-antigen interactions, providing limited functional guidance to improve the time-consuming and costly traditional optimization techniques. Here, we present InterAb and InterAb-Opt, a unified computational framework that integrates all-atom modeling with antibody language models to predict antibody-antigen interactions and enable antibody optimization. Leveraging the proposed all-atom modeling approach, AtomInter, and pre-trained antibody language models, InterAb outperforms existing methods in predicting antibody specificity and antibody-antigen binding affinity. InterAb successfully identified influenza A virus-binding antibodies from an antibody library and accurately detected high-affinity antibodies in the AIntibody competition. Empowered by the robust functional insights from InterAb, InterAb-Opt was developed to optimize broadly neutralizing antibodies. For R1-32 antibody, biolayer interferometry results reveal that 85%, 80%, 90%, and 67.5% of the 40 InterAb-Opt-optimized antibodies exhibit enhanced binding affinities to wild-type SARS-CoV-2, Lambda, BQ.1.1, and EG.5.1, respectively, with a maximum improvement of up to 96-fold. For the newly emerging BA.2.86 and KP.3, 55% and 52.5% of the optimized antibodies notably transition from non-binding to binding. Neutralization assays demonstrated that the optimized antibodies exhibited enhanced neutralization activity across multiple targets, highlighting the capability of InterAb-Opt in engineering broadly neutralizing antibodies. This technology enables precise analysis of antibody-antigen interactions and optimization of broadly neutralizing antibodies, holding promise for addressing challenges in immune evasion and vaccine design.

bioinformatics↗

bioRxiv2026

Human-Perception-Aligned Machine Learning for Indoor-Outdoor Classification

Daylight is vital for eye, brain, and overall health, yet misperceptions of what constitutes true outdoor daylight exposure can lead to poor behavioural choices and weaken public health recommendations. We developed InNOut, a perception-aligned machine learning model trained on 73,879 minutes of multispectral light data to classify environments as indoor or outdoor, and benchmarked against public (n = 383) and expert (n = 17) judgments across 183 scenes. InNOut achieved excellent performance (AUC = 0.92 [95% CI, 0.92-0.93], sensitivity 73.9%, specificity 94.5%), closely aligning with expert (83.5%) and public (80.8%) judgments. Clear outdoor and indoor scenes were reliably classified, whereas ambiguous settings (e.g., windowed rooms, vehicles) were often judged indoor by participants but outdoor by the model, consistent with their spectral light profiles. InNOut bridges perception and measurement, offering a scalable means to map light environments and inform digital interventions in medicine and public health.

physiology↗

bioRxiv2026

Leveraging Human Pangenome for Improved Somatic Variant Detection

Somatic variant detection is technically challenging due to low variant allele fractions, the confounding presence of germline variation, and reference bias. Linear references such as GRCh38 miss sample-specific variation, causing misalignments and incorrect variant calls. Although telomere-to-telomere donor-specific assemblies (DSAs) accurately represent individual genomes, their application is limited by cost and technical barriers. Alternatively, the graph-based human pangenome provides a scalable framework to improve read alignment and perform genome inference. Here, we benchmarked somatic variant detection using GRCh38, graph-based pangenomes, and pangenome-inferred DSAs with a HapMap mixture dataset and the COLO829 melanoma cell line. Pangenome-guided alignment improves read mapping and somatic variant calling accuracy. Furthermore, personalized pangenomes partially reconstruct donor-specific genomic content, improving accuracy, reducing germline contamination, and enabling detection of events in loci absent or poorly represented in GRCh38. These findings demonstrate that graph-based and personalized pangenomes are effective strategies for enhancing somatic variant detection compared with GRCh38.

genomics↗

bioRxiv2025

A foundational model for joint sequence-function multi-species modeling at scale for long-range genomic prediction

Genomic prediction and design require models that integrate local sequence features with long-range regulatory dependencies spanning hundreds of kilobases to megabases. Existing approaches have made substantial progress along complementary axes: supervised sequence-to-function models achieve high accuracy for specific assays and organisms, self-supervised genomic foundation models learn transferable representations from large-scale sequence data, and conditional generative models enable principled sequence design guided by functional objectives. However, these strengths are typically realized in isolation--across distinct model classes, architectures, and training regimes--limiting the ability to combine long-context, base-resolution prediction, functional modeling, and controllable generation within a single efficient framework that generalizes across organisms and modalities. Here we introduce Nucleotide Transformer v3 (NTv3), a multi-species foundation model that unifies representation learning, functional-track and genome-annotation prediction, and controllable sequence generation within a common backbone. NTv3 uses a U-Net-like architecture to enable single-base tokenization and efficient modeling of contexts up to 1 Mb. We pre-train NTv3 on 9 trillion base pairs from OpenGenome2 using base-resolution masked language modeling, followed by post-training with a joint objective that integrates continued self-supervision with supervised learning on [~]16,000 functional tracks and annotation labels from 24 animal and plant species. After post-training, NTv3 achieves state-of-the-art accuracy for functional-track prediction and genome annotation across species, outperforming leading sequence-to-function and foundation-model baselines on established benchmarks and on the new NO_SCPLOWTVC_SCPLOW 3 BO_SCPLOWENCHMARKC_SCPLOW, a controlled downstream fine-tuning suite in a standardized 32 kb input / base-resolution output setting. We further show that NTv3 consolidates a shared regulatory grammar across tasks, enabling coherent long-range genome-to-function inference and variant-associated remodeling. Finally, we fine-tune NTv3 into a controllable generative model via masked diffusion language modeling and use it to design enhancer sequences with specified activity levels and promoter selectivity. We validate these designs experimentally, showing that generated enhancers recapitulate the intended activity stratification and achieve the desired promoter-specific activation in cellulo. We release the NTv3 model family together with code and practical cookbooks for long-context training, multispecies post-training, fine-tuning, interpretation, and sequence design.

genomics↗

bioRxiv2025

scProtoTransformer: Scalable Reference Mapping Across Molecules, Cells and Donors

The rapid accumulation of single-cell data has made it possible to comprehensively characterize biological systems at molecular, cellular, and donor levels. However, scalable reference mapping across different resolutions remains a major challenge in current research. Here, we propose scProtoTransformer, a prototype-based Transformer architecture designed to achieve scalable reference mapping across molecular, cell, and donor levels. scProtoTransformer introduces a knowledge-guided prototype tokenizer that projects gene expression into biologically interpretable pathway prototypes, effectively reducing numerical batch effects while preserving biological semantic patterns. Furthermore, by leveraging knowledge distilled from the foundation model and a dynamic supervised fine-tuning strategy, scProtoTransformer achieves robust biological representations with reduced pre-training requirements. Benchmark experiments across molecular, cell, and donor-level reference mapping demonstrate that scProtoTransformer delivers competitive or even superior performance compared with state-of-the-art approaches, while providing interpretability through biologically prototypes. Together, these results establish scProtoTransformer as a unified framework for scalable reference mapping, laying the foundation for systematic understanding from genes to individuals.

bioinformatics↗

bioRxiv2025

Design principles underlying nearly-homeostatic biological networks

A nearly-homeostatic system like body temperature maintenance keeps the steady state system output like internal body temperature within a narrow range, regardless of different persistent levels of environmental perturbations like external temperatures. Nearly-homeostatic systems can be implemented to guarantee performance of a therapeutic device in different patient contexts. Exploration of different near-homeostasis-supporting architectures to satisfy different design requirements is necessary, but methods for doing so in a fast and comprehensive manner remain elusive. We have identified two constrained optimization approaches to find near-homeostasis supporting architectures 10 to 100 times faster than brute-force search. Once such architectures are found, characterizing the underlying mechanisms of near-homeostasis is hindered by the very cumbersome and limited nature of traditional statistical analysis approaches. We have developed two levels of "inverse homeostasis plots", and used them to identify two novel near-homeostasis mechanisms that tolerate much higher undesired basal expression and much higher undesired first order degradation rates than previously characterized near-homeostasis mechanisms. TeaserA comprehensive toolset was developed for much faster discovery and much more comprehensive analysis of near-homeostasis-supporting architectures.

systems biology↗

bioRxiv2025

Pan-cancer analysis reveals that tumor microbiomes generate specific epitopes through transcriptional reprogramming

The therapeutic promise of tumor microbial peptides faces a critical safety paradox: tumors and peritumor tissues harbor compositionally similar microbiomes, yet safe immunotherapy demands tumor-specific targeting. We performed comprehensive transcriptomic analysis of microbial communities from 1,868 tumor and peritumor samples across 11 cancer types. Although 88.5% of microbial species are present in both tissue types, tumor and peritumor tissues exhibit profound transcriptional divergence: only 34.1% of microbial genes are expressed in both tissue types, and merely 18.2% of predicted HLA-binding peptides overlap. This transcriptional divergence represents microbial transcriptional reprogramming (MTR) in tumor tissues, through which microbes activate distinct genomic regions while adapting to tumor microenvironmental pressures, thereby generating tumor-specific peptide repertoires. Using Microbial Transcriptional Reprogramming Index (MiTRI) to quantify MTR, we found that higher MiTRI values correlate with expanded immunogenic peptide repertoires. Mass spectrometry-based immunopeptidomics confirmed that 25% of naturally presented microbial peptides originate from MTR regions. Crucially, in microsatellite-stable colorectal cancer, neo-adjuvant therapy responders exhibited significantly higher MiTRI values. T cell receptors (TCRs) recognized MTR-derived epitopes at 2.10-fold higher rates than genome-wide epitopes, accounting for 79.1% of clonally expanded TCRs. These findings establish MTR as the principle that ensures the tumor-specificity and safety of micorbiome-directed immunotherapy.

cancer biology↗

bioRxiv2025

Targeted α-Synuclein mRNA Degradation by PMO-Based RNA-Degrading Chimeras

-Synucleinopathies are devastating neurodegenerative diseases characterized by pathological accumulation of a neuronal protein, -synuclein (Syn). Lowering soluble Syn levels is a promising therapeutic strategy to limit aggregation and neurotoxicity, but directly targeting this protein is hindered by its intrinsically disordered structure and other factors, such as its conformational heterogeneity and intracellular drug delivery barriers. Consequently, increasing attention has been directed toward targeting the SNCA transcript, which encodes Syn. Here, we developed phosphorodiamidate morpholino oligonucleotide (PMO)-based RNA-degrading chimeras (RDCs) that selectively bind the 5' untranslated region of SNCA mRNA and recruit RNase L for targeted RNA degradation. Through the systematic evaluation of 10 RDCs, we identified and optimized 4-D1, which effectively reduced SNCA mRNA and Syn protein expression in HEK293T cells in an RNase L-dependent manner. 4-D1 lowered SNCA transcript and Syn protein levels in both primary cortical neurons from humanized SNCA mice and in human induced pluripotent stem cell-derived cortical neurons. This reduction prevented prion-like seeding induced by patient-derived Syn fibrils and protected neurons from fibril-induced cytotoxicity. Finally, in vivo studies confirmed the efficacy of 4-D1 in reducing Syn mRNA expression in humanized SNCA mice. These findings indicate that PMO-based RDCs may represent a promising therapeutic modality for -synucleinopathies. Significance StatementAbnormal aggregation of the neuronal protein -synuclein is central to Parkinsons disease and related disorders, yet therapeutic candidates that directly target this protein have yet to demonstrate efficacy. in clinical trials. We developed a new strategy that lowers -synuclein production at the RNA level using phosphorodiamidate morpholino oligonucleotide (PMO)-based RNA-degrading chimeras (RDCs). These molecules recruit a natural RNA-degrading enzyme to selectively destroy the RNA transcript encoding -synuclein. Our lead RDC reduced -synuclein levels in cultured cells, humanized mouse and human neurons, blocked -synuclein pathological aggregation, and protected neurons from toxicity. This study establishes RDCs as a promising therapeutic platform for Parkinsons disease and other neurodegenerative diseases driven by -synuclein.

biochemistry↗

bioRxiv2025

Highly Adaptive Conductive Polymer Electronics Enhance Neural Data and Learning Accuracy

Human skin, the bodys largest organ, plays a vital role in sensing and transmitting neuronal, mechanical, and biochemical signals, making it an essential non-invasive interface for health monitoring, rehabilitation, and human-machine interaction. However, aging-related changes, including thinning, increased wrinkling, dryness, and altered collagen structure, significantly impact electrical impedance, conductance, and contact stability, challenging the fidelity and consistency of bioelectronic signal acquisition. Here, we address this gap by developing "AdapSkin," an age-adaptive, skin-mimicking, bio-adhesive, and stretchable polymeric electronic skin interface that seamlessly conforms to diverse skin properties, enabling high-fidelity and high-density electrophysiological recording. The soft electrodes of AdapSkin are composed of an aqueously processed, homogeneously mixed organic nanocomposite with a conductive polymer percolation network, forming a gel-like interface that reduces modulus and enhances skin-electrode contact. The materials platform achieves extraordinary softness and electrical stretchability of up to 1200% through a double-network composite structure. AdapSkin significantly minimizes age-induced variations in interfacial impedance and signal-to-noise ratio (SNR), improving signal consistency for neuromuscular assessment, prosthetic control, and rehabilitation applications. Scalable fabrication enables the creation of large-area electrode arrays, which reduces motion artifacts, improves sEMG mapping reliability, and ensures long-term signal stability across various age groups. Machine learning analysis further demonstrates AdapSkins superior accuracy in gesture classification for elderly users, highlighting its potential to enhance prosthetic control, assistive robotics, and rehabilitation for individuals with sarcopenia and neuromuscular decline. By improving signal quality and adaptability in aging populations, AdapSkin advances fair bioelectronic interfaces, fostering more equitable and effective healthcare technologies for age-related conditions.

bioengineering↗

bioRxiv2025

Brain-derived neurotrophic factor supports pericyte and vascular homeostasis in the aging brain

Microvascular circulation in the brain is often impaired in connection with the loss of pericytes in old age. The neurotrophic factor BDNF also decreases in the aging brain. We hypothesized that BDNF regulates the homeostasis of cerebral pericytes and microvasculature. We used differently aged C57BL/6J mice, and C57BL6 mice with conditional knockout of Bdnf gene. Collagen IV-positive microvessels and PDGFR{beta}-positive pericytes in the brain were counted after immunological staining. Pericytes were also quantified by Western blot of PDGFR{beta} and CD13 in isolated cerebral microvessels. The level of BDNF and TrkB phosphorylation was determined in brain homogenates. To demonstrate the direct effect of BDNF on pericytes, TrkB and pericytes were co-stained in brain tissue, single-cell sequencing and transcriptomic analysis were used to identify and characterize Ntrk2-expressing pericytes, and TrkB was also detected in the pericyte cell line by Western blot. Cultured pericytes were further treated with recombinant BDNF in the presence and absence of an Akt inhibitor and examined for PDGFR{beta} expression. The length and branching of microvessels and pericytes decreased in conjunction with the reduction in mature BDNF and TrkB phosphorylation in aging brains. Deficiency of BDNF in neurons or astrocytes was sufficient to reduce cerebral microvessels, PDGFR{beta} and CD13 concentrations and Akt and Erk1/2 phosphorylation in isolated blood vessels. A subset of pericytes in the brain and cultured pericytes expressed TrkB. BDNF treatment increased PDGFR{beta} expression along with Akt and Erk1/2 phosphorylation in cultured cells. The effect of BDNF on PDGFR{beta} expression was abolished by treatment with Akt inhibitor. Therefore, BDNF induces the expression of PDGFR{beta} and CD13 by activating Akt signaling in pericytes, promoting the homeostasis of pericytes and microvasculature in the aging brain. Our study identified a BDNF-mediated mechanism that regulates microvascular integrity in the aged brain.

neuroscience↗

bioRxiv2025

A Pangenomic Method for Establishing a Somatic Variant Detection Resource in HapMap Mixtures

Somatic mosaicism is essential in human biology and disease, yet robust benchmarks are scarce. The SMaHT Consortium mixed six HapMap cell lines to create artificial somatic variants spanning 0.25% to 16.5% variant allele fractions. We developed a technology-agnostic method that builds pangenome graphs from individual assemblies to create unified benchmarking sets: > 6M single-nucleotide variants, 1.8M small insertions/deletions, 49K structural variations, and 10K mobile element insertions across autosomes, X, and mitochondrial chromosomes. We validated the variants using ultra-deep simulated reads and developed a binomial-based model to estimate coverage requirements for variant detection. Evaluating multiple callers showed CHM13 alignment improves structural variant detection and offers advantages in difficult-to-map regions compared to GRCh38. Systematic characterization showed regions with low detection rate are enriched in centromeres, satellite sequences, tandem repeats, and falsely duplicated genes. This accurate, versatile resource enables systematic evaluation of somatic variant detection technologies.

genomics↗

bioRxiv2025

Single-nucleus transcriptomics reveal disrupted pathways in the prefrontal cortex of Scn2a-deficient mice

Truncating variants in SCN2A, which encodes the NaV1.2 sodium channel critical for action potential initiation and propagation, are associated with autism spectrum disorder (ASD) and epilepsy. To investigate SCN2A deficiency-related phenotypes, we developed a preclinical mouse model with under 50% NaV1.2 expression, exhibiting neuronal hyperexcitability and social deficits. However, the neuronal populations and molecular alterations underlying these phenotypes at single-cell resolution have not been investigated. In this study, we conducted single-nucleus RNA sequencing (snRNA-seq) of wild-type (WT), homozygous Scn2a-deficient (HOM) mice, and HOM mice with Scn2a restoration (HOM-FlpO) to examine the effects of Scn2a level on gene expression in the medial prefrontal cortex (mPFC), a critical brain region related to ASD development. Differential expression analysis in GABAergic and glutamatergic neurons between genotypes revealed gene expression enriched in neurotransmitter activity regulation and synapse organization. Lastly, snRNA-seq results in HOM-FlpO identified genes that were rescued after Scn2a restoration. These results reveal that reduced Scn2a expression disrupts RNA transcriptomes in multiple neuronal subtypes, providing insight into cell type-specific mechanisms underlying SCN2A-related disorders.

neuroscience↗

bioRxiv2025

Binding of inhibitory checkpoints to CD18 in cis hinders anti-cancer immune responses

SIRP is an inhibitory receptor on macrophages that limits phagocytosis and anti-tumor activity of macrophages by "trans" interacting with CD47 on tumor cells. Herein, we found that a large component of SIRPs inhibitory function occurred independently of CD47-binding and phosphatase signaling. This function resulted from a direct interaction between SIRP and CD18 ({beta}2 integrin) in "cis" at the surface of macrophages, involving SIRP amino acids distinct from those implicated in the SIRP-CD47 interaction. The cis interaction prevented activation of CD18, which is necessary for phagocytosis. Combined blockade of SIRP-CD18 and SIRP-CD47 was essential for maximizing phagocytosis and suppression of tumor growth in vivo. Similar cis interactions between CD18 and other inhibitory checkpoints, including PD-1, were also observed. Thus, in addition to mediating effects when engaged by ligands in trans, inhibitory checkpoints suppress immune cell activation through a mechanism targeting CD18 in cis. This dual mode of action should be considered when developing blockers of inhibitory checkpoints for immunotherapy. One-Sentence SummaryIn addition to being engaged in "trans" by ligands on tumor cells, inhibitory receptors, such as SIRP and PD-1, hinder anti-cancer immune responses by "cis" interacting with {beta}2 integrin CD18.

immunology↗

bioRxiv2025

The U1 snRNP protein U1C and Helix H of U1 snRNA are critical for small molecule splicing modulator function

Risdiplam and branaplam represent two classes of small-molecule splicing modulators that promote U1 snRNP recognition of weak non-canonical GA/GU-containing 5 splice sites (ss). We demonstrated that branaplam enhanced recognition of these 5 ss by reconstituted U1 snRNP in vitro, and that this effect depended on the ZnF domain of U1C and Helix H of U1 snRNA, but not U1A or U1-70K. In cells, depletion of U1C generally reduced compound-induced exon inclusion for most cassette exons. Interestingly, a subset of cassette exons became responsive to compound only upon U1C knockdown, supporting a model in which U1C stabilizes specific conformations at the 5 ss/U1 snRNA interface in a context-dependent manner that can either facilitate or hinder compound binding. Surprisingly, risdiplam shows no effect on weak 5 ss recognition in vitro, suggesting additional cellular factors are required for its activity.

biochemistry↗

bioRxiv2025

Hypobaric hypoxia drives citrate cycle reprogramming to suppress tumor progression

High altitude residents present lower tumor incidence and mortality than plain residents, suggesting that hypobaric hypoxia displays protective effect against tumor development. The results of our studies showed that hypobaric hypoxia exposure significantly suppressed tumor progression in subcutaneous bearing and lung metastasis tumor models. With single-cell transcriptome analysis, we identified HIF-1 pathway was significantly downregulated in tumor tissues with high altitude hypoxia, leading to decreased glycolysis and angiogenesis and improved antitumor immune response. Mechanistically, systemic hypoxia rewired citric acid cycle, with enhanced CS and IDH2 expression and reduced OGDH and SUCLG2 expression, to induce -ketoglutarate accumulation and succinate decline in tumor microenvironment, further mediating HIF-1 pathway inhibition. Moreover, hypobaric hypoxia treatment significantly improved the antitumor effects of adjuvant therapies (including chemotherapy, anti-angiogenic therapy and immunotherapy). Our findings reveal the role and mechanism of hypobaric hypoxia for tumor regression and yield new insights into tumor therapy.

cancer biology↗

bioRxiv2025

Retinal pigment epithelium-derived PD-L1 reprograms microglial cells and protects against retinal degeneration in mouse models of experimental AMD and genetic retinitis pigmentosa

Retinal degeneration is a leading cause of blindness and a significant health burden during aging worldwide. Because of its complex pathogenic mechanisms, however, effective interventions applicable to multiple retinal degenerations remain limited. Excessive microglia-mediated inflammation is a common pathological feature of different retinal degenerative diseases, and inhibiting these overactive inflammatory responses by reprogramming microglia may provide a therapeutic strategy with broad-spectrum potential. Here, we uncover a novel retinal pigment epithelium (RPE) homeostatic signal, PD-L1, that drives the reprogramming of activated microglial toward a retinal-protective phenotype. Using multiple analyses, including gene expression profiling bioinformatics, adeno-associated virus-mediated RPE-specific gene overexpression, pharmacological, and genetic manipulations, we show that RPE cells upregulate the expression of PD-L1 to modulate microglia for protection against retinal degeneration in an experimental dry AMD mouse model. Bioinformatics enrichment analysis of the high-expression gene signatures of subretinal microglia in AMD patients, combined with pharmacological blocking of NF-{kappa}B activity or using Nlrp3 knockout mice, show that PD-L1/PD-1 signaling suppresses NF-{kappa}B activation in microglia, thereby inhibiting NLRP3 inflammasome priming and attenuating microglia-mediated excessive inflammation. Furthermore, the overexpression of PD-L1 by the AAV8 virus exerts similar microglial reprogramming and retinal protective effects to alleviate retinal degeneration in a preclinical model of retinitis pigmentosa. These findings reveal that RPE-derived PD-L1 suppresses inflammatory reprogramming of subretinal microglia and mitigates retinal degeneration, highlighting a promising proof of concept for PD-L1 as a potential therapeutic target for the broad treatment of retinal degenerative diseases.

genetics↗

bioRxiv2025

Chemerin-CMKLR1 mediated OGD/R induced Mitochondrial Dysfunction, Oxidative Stress, and Autophagy differentially in Microglia and Neurons

IntroductionIschemia-reperfusion (I/R) injury exacerbates tissue damage upon reperfusion after ischemia. The impact of chemerin and its receptor, chemokine-like receptor 1 (CMKLR1) on I/R injury remains poorly understood. We hypothesized that chemerin-CMKLR1 differentially regulates signaling in microglia and neuronal cells oxygen-glucose deprivation/reoxygenation (OGD/R), influencing mitochondrial function, oxidative stress, and autophagy. MethodsUsing BV2 microglia and Neuro-2a (N2a) neuronal cells, we examined OGD/R-induced changes in autophagy associated proteins, chemerin and CMKLR1 expression. We investigated the functional consequences of CMKLR1 overexpression and chemerin treatment on oxidative stress, apoptosis, autophagy, and mitochondrial dynamics in BV2 microglia and N2a neuronal cells. ResultsOGD/R downregulated CMKLR1 while upregulating autophagy in both BV2 microglia and N2a cells; While chemerin expression decreased in BV2 microglia but increased in N2a cells following OGD/R. Treatment with chemerin dose-dependently reduced oxidative stress and apoptosis while enhancing mitochondrial fusion, suppressing fission, and promoting autophagy and mitochondrial function in both cell types under OGD/R. CMKLR1 overexpression exacerbated mitochondrial respiratory dysfunction, mitochondrial fusion, fission, and elevated autophagy (LC3II/LC3I and Pink1 levels), with cell-type-specific differences observed in Parkin and P62 regulation. ConclusionOur study demonstrates cell-type-specific regulation of chemerin-CMKLR1 signaling in I/R injury, and distinct mitophagy activation mechanisms in microglia and neurons. These findings suggest cell-type specific modulation of chemerin-CMKLR1 as a potential therapeutic target in preserving mitochondrial homeostasis, modulating autophagy, mitophagy and reducing oxidative stress, apoptosis in both microglia and neurons for mitigating I/R injury.

neuroscience↗