Biology subjects

Hou, L.

Publications and source records attributed to Hou, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Salt Stress Shifts Isatis indigotica to Prioritize Defense over Goitrin Biosynthesis

Soil salinization threatens the cultivation quality of Isatis indigotica, a medicinal plant whose root bioactivity depends on the glucosinolate-derived compound (R,S)-goitrin. Although moderate abiotic stress is widely assumed to stimulate secondary metabolite accumulation, the temporal dynamics of goitrin biosynthesis under salt stress remain poorly understood. This study quantified goitrin content across four NaCl concentrations (100 - 400 mmol/L) and four time points (2, 6, 12, and 24 h). Time-series transcriptome sequencing was performed under 100 mmol/L NaCl. Contrary to prevailing assumptions, goitrin content declined progressively from 2 to 12 h before partially recovering at 24 h, indicating that salt stress transiently suppresses goitrin accumulation rather than promoting it. Transcriptomic analysis identified 7 glucosinolate biosynthesis genes whose expression positively correlated with goitrin content (p < 0.05), and 6 salt stress-responsive genes negatively correlated with goitrin content (p < 0.05). These opposing patterns suggest that stress defense is transiently prioritized over biosynthesis, with partial metabolic recovery as plants adapt. These findings reveal a defense-biosynthesis trade-off mechanism in I. indigotica roots and provide a transcriptomic framework for understanding how abiotic stress reshapes secondary metabolism in medicinal plants.

plant biology↗

bioRxiv2026

MOD-scTWAS: Leveraging gene co-expression for single-cell transcriptome-wide association studies

Transcriptome-wide association studies (TWAS) provide an effective framework for identifying genes associated with complex traits. Population-scale single-cell transcriptomic data enable genetically regulated expression (GReX) prediction and TWAS analyses at cell-type resolution, but the predictive performance of existing single-cell TWAS methods remains limited. Here, we develop MOD-scTWAS, a module-based method that jointly models GReX for genes within co-expression modules to borrow information across genes. Starting from a generative model for single-cell gene expression, MOD-scTWAS accounts for the heteroscedasticity and cross-gene correlation of individual-level pseudobulk expression in joint GReX prediction. In cross-validation analyses of the OneK1K dataset, MOD-scTWAS achieved higher mean GReX prediction accuracy than scTWAS across all 14 cell types and increased the number of imputable genes. When applied to TWAS analyses of UK Biobank quantitative hematological traits, MOD-scTWAS identified more significant cell type-gene-trait associations than scTWAS. These results demonstrate the potential of leveraging gene co-expression through joint modeling to improve cell-type-specific GReX prediction and TWAS discovery.

genetics↗

bioRxiv2026

Context-dependent regulatory networks connect Alzheimer's disease genetics to microglial inflammatory responses

Inflammation is central to Alzheimer's disease (AD) pathogenesis. Microglia, the resident innate immune cells of the brain, exhibit diverse inflammatory states and are enriched for AD-associated genetic variants within active cis-regulatory elements (CREs). However, the interplay among genetic variants, transcription factor (TF)-CRE-gene programs, and microglial responses across inflammatory and disease contexts remain poorly understood. Here, we develop context-dependent epigenomic networks (cEpiNets), integrating bulk and single-nucleus assay for transposase-accessible chromatin using sequencing (ATAC-seq) to reconstruct regulatory programs across inflammatory, genetic perturbation, and disease contexts. Leveraging TF footprinting and graph embedding, cEpiNets identifies shared and context-specific programs and predicts regulatory circuits in unseen biological contexts. In a SORL1-marked inflammatory microglial state that expands during AD progression, cEpiNets annotates AD risk variants at the SORL1 locus and identifies variants associated with cellular state abundance across donors. Cross-context analysis further identifies ZBTB14, whose inflammation-associated program connects AD risk variant-harboring CREs to target genes and widespread TF remodeling in AD. Donor-level ZBTB14 footprint activity is negatively associated with AD pathology, while combined IFN{gamma}/TNF stimulation represses ZBTB14 and activates a subset of inferred targets. Collectively, cEpiNets bridges genetic variation, regulatory programs, and disease-associated cellular phenotypes to facilitate mechanistic interpretation of complex disease genetics.

bioinformatics↗

bioRxiv2026

IL27 exerts a powerful effect on systolic overload-induced cardiac inflammation, fibrosis, and heart failure development

BACKGROUNDInterleukin-27 (IL-27) is a heterodimeric cytokine that serves as a bifunctional rheostat rather than an inherently pro- or anti-inflammatory signaling protein. However, the specific role of IL-27 in regulating systolic overload-induced cardiac inflammation and heart failure (HF) pathogenesis remains unknown. METHODSWe investigated the effects of genetic IL-27 receptor deficiency (IL-27R knockout), pharmacological IL-27 blockade, and recombinant IL-27 administration on transverse aortic constriction (TAC)-induced HF in mice. RESULTSCardiac IL-27 expression was significantly elevated in both murine and human HF tissues. The global genetic ablation of the IL-27 receptor (IL-27R) significantly suppressed TAC-induced cardiac inflammation, fibrosis, hypertrophy, HF progression, and mortality. Corroborating these protective effects, transcriptomic analysis (RNA-seq) revealed that IL-27R deficiency drastically suppressed pathways driving immune responses and antigen presentation, alongside the significant downregulation of networks governing systemic inflammation, pathogen infection, and extracellular matrix remodeling. Furthermore, pharmacological neutralization of IL-27 effectively attenuated TAC-induced left ventricular dysfunction, chamber dilation, myocardial hypertrophy, fibrosis, and leukocyte infiltration. Conversely, the administration of recombinant mouse IL-27 exacerbated the TAC-induced cardiac accumulation of multiple immune cell subsets, resulting in worsened cardiac fibrosis, cardiomyocyte hypertrophy, and overall HF progression. CONCLUSIONSOur findings demonstrate that IL-27 acts as a critical pathogenic driver of cardiac inflammation and HF development by modulating both cardiac immune cells (predominantly T cells) and non-immune cells, highlighting the IL-27 signaling axis as a promising therapeutic target.

physiology↗

bioRxiv2026

Genetic drivers of protein changes over time: Findings, considerations, and approaches in TOPMed cohorts and UK Biobank

Age is a major risk factor for many diseases, but the biological processes driving aging are heterogeneous across individuals. Efforts to untangle differences between chronological and biological age have focused on identifying age-associated markers, such as omics clocks. Many omics features, including proteins, are strongly associated with age, and genetics contribute to variance in these measures. However, few studies have identified genetic drivers of interindividual variability in omics changes over time. Using longitudinal proteomics data (Olink 3k) from the Multi-Ethnic Study of Atherosclerosis (MESA), we calculated a protein slope for each individual (n=2,007) and protein (n=2,737) across 3 visits spanning 14-18 years, then conducted a genome-wide analysis for each slope, both with and without adjusting for baseline protein level. Subsets in UK Biobank (UKB; n=948) and CARDIA (n=1,328) with longitudinal proteomics data were used for replication. We considered additional methods for modeling of protein change and variability, including linear mixed models, SNP-by-age interactions, and variance quantitative trait loci. Without baseline adjustment, only 19 proteins (20 credible sets) had a slope pQTL in MESA, with poor replication in UKB and CARDIA. With baseline adjustment, 607 proteins (698 credivle sets) had a slope pQTL and over 70% replicated in CARDIA and/or UKB; such baseline adjusted models may, however, be subject to collider bias. Longitudinal and cross-sectional interaction models identified fewer than 14 pQTLs, suggesting they were generally underpowered; but 73% of proteins with a variance pQTL also had a slope pQTL. By examining effect direction concordance, replication rate, directed acyclic graphs, and signal overlap with other models we demonstrate that many baseline-adjusted slope pQTLs may be arising due to model misspecification or regression to the mean. Overall, our results highlight considerations for modeling strategies of change phenotypes and build on understanding of potential genetic mechanisms influencing interindividual proteome changes over time.

genetics↗

bioRxiv2026

Genos-m: a foundation model for human-associated microbial genomes

Human-associated microbial genomes encode extensive strain-level diversity and niche-specific gene repertoires that are critical to host health. However, these complex sequence features remain difficult to capture using general-purpose DNA foundation models, highlighting the need for dedicated representation learning tailored to the human microbiome. Here, we introduce Genos-m, an open-source foundation model for human-associated microbial genome representation. Genos-m was pretrained on approximately 1.2 trillion nucleotide tokens from a curated microbial genome corpus, including human-associated prokaryotic isolates, high-quality metagenome-assembled genomes (MAGs) and bacteriophages, supplemented with GTDB species-level representative genomes to broaden prokaryotic taxonomic breadth. The model uses a sparsely activated Mixture-of-Experts (MoE) Transformer architecture, with 4.7 billion total parameters, approximately 330 million activated parameters per forward pass and a maximum context length of one million base pairs. We evaluated frozen Genos-m representations across short-sequence and gene-level tasks, biosynthetic gene cluster (BGC)-based regional sequence tasks, whole-genome strain phenotype prediction, and zero-shot transfer on prokaryote-related RNAfitness assays. Across these benchmarks, Genos-m consistently ranked among the leading comparison models, with the best performance in five of eight gene-fitness regression tasks and in BGC type classification. Using sparse autoencoders, we identified sparse features in Genos-m hidden activations that aligned with annotated ORFs, intergenic regions, and tRNA and rRNA loci. In downstream applications, Genos-m-derived genome-informed species representations in-corporated into a human microbiome self-supervised learning model improved colorectal cancer (CRC)-control classification over conventional species-abundance random forest models. Genos-m also generated stable sample-level embeddings from as few as 10,000 metagenomic reads, retaining gut microbial community structure that distinguished geographic origin and aligned with enterotypes defined from full-depth taxonomic profiles. Together, these results support Genos-m as a reusable representation model for microbial genomes and metagenomes, with conclusions bounded by the reported datasets, task definitions and evaluation protocols. Genos-m model weights, inference code, and usage documentation are publicly available on GitHub (https://github.com/BGI-HangzhouAI/Genos-m) and Hugging-Face (https://huggingface.co/BGI-HangzhouAI/Genos-m).

bioinformatics↗

bioRxiv2026

Thermal Nano-Engineering of Ginger Extracellular Vesicles for Targeted Oral Therapy of Colitis

Plant-derived extracellular vesicles (PEVs) are promising candidates for oral drug delivery, yet their clinical translation is hindered by limited targeting precision and inconsistent systemic absorption. While surface engineering can enhance tissue accumulation, strategies that preserve biocompatibility and enable scalable production remain limited. Here, we introduce a simple thermal processing approach, boiling, to structurally reconfigure ginger EVs into functionally enhanced, thermally reassembled nanoparticles (B-GEVs). The surface architecture of B-GEVs is enriched with key vesicle trafficking regulators, including V-type proton ATPase subunit G, ARF1, and {beta}-adaptin-like protein. This specific composition drives their tissue-specific accumulation in the intestine and liver and potentiates clathrin-dependent cellular uptake in intestinal cells by 8.57-fold. Beyond superior intrinsic anti-inflammatory activity through NLRP3 inflammasome suppression, B-GEVs function as an efficient oral delivery platform. When loaded with TNF- siRNA, they enable a synergistic therapy that simultaneously modulates upstream inflammation and silences key downstream mediators, showing potent efficacy in colitis. Our findings position boiling as a natural strategy for enhancing the bioactivity and targeted oral delivery potential of ginger-derived EVs.

bioengineering↗

bioRxiv2026

Vicious circle of amyloid and leptomeningeal macrophages evokes vascular dysfunction in CAA

The subarachnoid space contains leptomeningeal arteries and resident immune cells known as subarachnoid macrophages (SAMs). In Alzheimers disease (AD) and related cerebral amyloid angiopathy, amyloid-{beta} (A{beta}) frequently accumulates around the leptomeningeal arteries. Nevertheless, the local immune responses and their functional consequences remain poorly understood. Using longitudinal intravital imaging in a mouse model of AD, we tracked A{beta} deposition and identified a distinct SAM population that migrates to and phagocytoses these arterial A{beta} deposits. SAM recruitment correlated with vascular remodeling, including smooth muscle loss, aneurysm formation, and reduced cerebral perfusion. Transcriptomic profiling revealed a distinct SAM population in AD with upregulated CD39 expression. Pharmacological inhibition of CD39 attenuated arterial A{beta} deposition, identifying SAMs as a potential therapeutic target in AD.

neuroscience↗

bioRxiv2026

Task-Dependent Effects of Channel Density on Multivariate Pattern Analysis and Spatial Representational Similarity Analysis: Evidence from Three EEG Datasets

Despite the widespread use of EEG decoding and representational similarity analysis (RSA), the extent of the impact of electrode density on these multivariate approaches has not been systematically evaluated, particularly across different cognitive domains. Here, we systematically compared four electrode configurations (19, 32, 64, and 128 channels) across three EEG datasets encompassing visual perception, visual search, and emotional processing. All datasets were recorded at 128 channels and subsequently reduced to 64, 32, and 19 channels via electrode subset selection based on the international 10-20 system. Time-resolved decoding and spatial RSA were computed for each configuration with paired statistical evaluation. Decoding sensitivity demonstrated clear task dependence: in the color-harmony paradigm, performance improved markedly with higher densities, consistent with spatially distributed perceptual representations, whereas decoding in the icon-search and dot-probe tasks remained stable across densities, indicating diminishing returns of additional electrodes although all configuration yielded robust decoding accuracies that above chance level. RSA results were comparatively robust, with relative representational similarity structures largely preserved even for 16 channel counts. These findings demonstrate that low-density setups can be sufficient, offering practical guidance for EEG channel selection and supporting the use of low-density EEG in real-world applications, including wearable systems, mobile EEG recordings, and clinical or rehabilitation settings.

neuroscience↗

bioRxiv2025

Eosinophil-derived COX-2 protects against experimental colitis through the PGE2-IL-22 axis

Inflammatory bowel disease (IBD) is driven by a breakdown in immune regulation and epithelial barrier function, yet the contribution of eosinophils to this process has remained poorly defined and controversial. While eosinophils infiltrate the intestinal mucosa during both flares and remission, their role in shaping disease outcomes is unclear. Our RNA-seq analyses of colonic eosinophils isolated from dextran sulfate sodium (DSS)-treated mice revealed a significant upregulation of cyclooxygenase (Cox)-2 (gene name, Ptgs2). Eosinophil-specific deletion of Cox-2 (Ptgs2fl/fleoCre+/-) reduced IL-22 production and exacerbated DSS- and trinitrobenzene sulfonic acid (TNBS)-induced colitis, characterized by greater weight loss, higher disease activity, colon shortening, and epithelial injury. Administration of recombinant IL-22 reversed these phenotypes. Mechanistically, eosinophil-derived COX-2 enhanced IL-22 production by type 3 Innate lymphoid cells (ILC3s) through prostaglandin E2 (PGE2) signaling. Consistently, Ptgs2fl/fleoCre+/-mice exhibited reduced colonic PGE2 levels, while PGE2 analog treatment restored IL-22 production and mucosal protection. Our findings identify eosinophil-derived COX-2 and PGE2 as a critical regulator of IL-22 production during colitis, uncovering a previously unrecognized eosinophil-ILC3 crosstalk that safeguards the intestinal barrier and represents a promising therapeutic target in IBD. Significance StatementThe role of eosinophils in inflammatory bowel disease (IBD) has remained unresolved. We identify eosinophil-derived COX-2 as the main source of prostaglandin E2 (PGE2) in colitis, which drives IL-22 production by ILC3s to maintain epithelial protection. This discovery defines a protective eosinophil/PGE2/IL-22 circuit and reveals a therapeutic target to strengthen barrier defense in IBD.

immunology↗

bioRxiv2025

EEG-based analyses reveal different temporal processing patterns in aesthetic evaluation

BackgroundExisting studies estimate harmony values using the color harmony model, but how these values are reflected in distinct neural stages (early automatic vs. late evaluative) and shape subjective preferences remains unexamined. MethodsTo fill this gap, we recorded behavioral and event-related potential data (N=30 adults, age: 29.20{+/-}2.38 years old) to examine whether the predictions of color harmony theory regarding harmonious vs. disharmonious color combinations align with neural activity from a color perception paradigm. ResultsBehavioral results showed that two-color combinations received higher aesthetic pleasantness ratings than three-color combinations, while the ratings for color harmony were relatively smaller than for disharmony. Univariate ERP analysis revealed that P1 amplitude for harmonious color was significantly higher than for disharmonious color, particularly when three colors were present. In contrast, the amplitude and latency of P2 were significantly impacted by the number of colors. Additionally, multivariate pattern analysis further demonstrated that neural activity reliably differentiated between harmonious vs. disharmonious color combinations and two-color vs. three-color combinations during both P1 and P2 time window. ConclusionsThese findings indicate that harmonious versus disharmonious color combinations subtly influenced early visual processing, while the number of colors used in the design had a stronger influence on aesthetic judgments.

neuroscience↗

bioRxiv2025

Patterns of Microbial Succession and Niche Differentiation Across Depth and Age in a Landfill Have Implications for Management Strategies

Despite microorganisms being primarily responsible for landfill material decomposition, limited characterization has been performed across both landfill depth and age. Here, we investigated the microbial communities and physicochemical parameters in two active and two closed landfill wells from surface to bottom, as well as fill dirt and leachate at a sanitary landfill near Madison, Wisconsin, USA. Amplicon community sequencing fungi, bacteria and archaea revealed distinct microbial community structures across landfill sites. The observed patterns of microbial community succession by depth and age mirror the known phases of the landfill life cycle. Younger surface samples were dominated by aerobic fungi, which transitioned to fermentative bacteria and methanogenic archaea in older, deeper, layers. Simultaneously, high species richness was preserved across landfill ages, while reduced evenness at specific depths support spatial niche differentiation. In conjunction with the lack of trends found for physicochemical parameters by depth, this supports niche differentiation driven by the highly heterogenous waste inputs. This study provides the first comprehensive vertical profile of bacterial, fungal, and archaeal communities across landfill depths and ages, highlighting the influence of these parameters on physicochemical factors and microbial distribution within landfills. These results have implications for improving landfill management, including renewable gas energy production, minimizing emissions, and increasing degradation rates.

microbiology↗

bioRxiv2025

SpatialZoomer: multi-scale feature analysis of spatial transcriptomics

Single-cell resolution spatial transcriptomics (ST) provides a great opportunity to explore the complex cellular contents in different tissues. In this study, we introduce SpatialZoomer, a spectral graph-based method that applies a set of low-pass filters to efficiently extract spatial molecular features from ST data at multiple resolutions or scales, including the single cell scale, the niche scale with dozens of closely interacting cells, and the domain scale with spatially-organized cell contents. The corresponding "critical" scales can be automatically identified by partitioning a cross-scale similarity map. Results show that SpatialZoomer can identify disease-progression signals at specific scales in Alzheimers Disease, and spatial context dependent cell subtypes in tumor microenvironment. The extracted multi-scale features also uncovered spatially heterogeneous niches in cancer. SpatialZoomer also takes advantage of high computational efficiency and low hardware requirements.

bioinformatics↗

bioRxiv2025

Spatiotemporal lineage mapping of tumor immune escape with eTRACER

The plasticity-first hypothesis posits that phenotypic plasticity emerges first in novel environments, followed by (epi)genetic changes that stabilize adaptive phenotypes. Whether tumor evolution follows this model, and how non-genetic mechanisms sustain long-term therapeutic resistance, remain unclear. Here, we develop eTRACER, an endogenously targeted, high-resolution and spatially-resolved CRISPR-Cas9 lineage-tracing system, to study tumor adaptation during longitudinal CD8+ T cell-mediated immunotherapy. Integrated clonal and single-cell transcriptomic analyses show that tumor immune evasion is governed by clonal state composition rather than clonal identity, arguing against selection from pre-existing genetic heterogeneity. Spatiotemporal lineage tracing reveals highly reversible state transitions prior to therapy, followed by consolidated epithelial-mesenchymal transition (EMT) during therapy. Single-cell multiomics identifies AP-1 as a key regulator of EMT stabilization and its inhibition enhances tumor sensitivity to immune killing. Together, these findings show that tumor plasticity precedes stable immune evasion, revealing an AP-1-centered mechanism underlying plasticity-first tumor evolution.

cancer biology↗

bioRxiv2025

Dissecting Tissue Architecture and Function through Mapping of Cellular Communication Networks

Spatial transcriptome provides critical insights for inferring cell-cell communications. Based on the heuristic that physically adjacent cells are more likely to communicate with each other, we develop a computational framework that Infers the Cell-Cell Communication network (IC3) and subsequently identifies communication hotspots with rigorous error control. We demonstrate in simulations and real datasets that our method outperforms existing methods in accuracy and especially improves sensitivity to identify communications involving rare cell types. Applying IC3 in a mouse brain dataset, we recovered how cells communicate with each other to form a local structure that regulates the balance of the blood-brain barrier. These findings highlight that our method is effective in revealing tissue architecture and function from cellular communication networks.

bioinformatics↗

bioRxiv2025

Predicting Spatial Transcriptomics from H&E Image by Pretrained Contrastive Alignment Learning

The intricate molecular landscape within tissues holds crucial information about cellular behavior and disease progression, yet capturing this complexity at a spatial level remains challenging. While Spatial transcriptomics (ST) offers valuable insights into gene expression patterns within their native tissue context, its widespread adoption is hindered by high costs and limited gene detection capabilities. Here we introduce CarHE (Contrastive Alignment of gene expRession for hematoxylin and eosin image), a method that overcomes these limitations by accurately predicting high-dimensional ST data (over 10,000 genes) solely from readily available H&E (Hematoxylin and Eosin) stained images. This novel pre-trained architecture employs contrastive learning through two mechanisms: cell-type-based transcriptomics information transfer and image-based histology information transfer. These mechanisms precisely align image features with spatial single-cell gene expressions, achieving prediction accuracies exceeding 0.7 (up to 1.7 folds compared to second best) across diverse tissue types and species. CarHEs superior performance extends to identifying subtle pathological features such as tertiary lymphoid structures in various cancers, including breast cancer, lung cancer, melanoma and ccRCC (clear cell renal cell carcinoma), and reconstructing 3D spatial transcriptomics from images alone, offering a cost-effective and robust alternative for large-scale spatial transcriptomics. We further validated CarHEs effectiveness by predicting DFS (Disease-Free Survival) from >1,600 lung cancer patients HE images, achieving a significantly higher AUC (Area Under the Receiver Operating Characteristic Curve) of 0.73 compared to state-of-the-art alternatives (0.58-0.64).

bioinformatics↗

bioRxiv2025

Structural Basis for Cas9-Directed Spacer Acquisition in Type II-A CRISPR-Cas Systems

CRISPR-Cas systems confer prokaryotic adaptive immunity by integrating foreign DNA (prespacers) into host arrays. Type II-A systems employ Cas9 for protospacer adjacent motif (PAM) recognition and coordinate with Csn2 and the Cas1-Cas2 integrase during spacer acquisition, yet their structural basis remains unresolved. Here, we report cryo-EM structures of the Enterococcus faecalis Cas9-Csn2-Cas1-Cas2 supercomplex in apo and DNA-bound states. The apo-state structure (Cas92-Csn28-Cas18-Cas24) adopts a resting conformation, with Cas9 locked in a nuclease-inactive state and Cas1-Cas2 sterically blocked from prespacer loading. Upon DNA engagement, Cas9 undergoes a conformational transition, forming a prespacer catching complex that threads the DNA through Csn2s central channel. This architecture enables Cas9 to interrogate the PAM sequence while sliding along the DNA, with Cas9 and Csn2 jointly define a 30-bp DNA segment which matches the prespacer length. Subsequent dissociation of Cas9 triggers a structural reconfiguration of the Csn2-Cas1-Cas2 assembly. The PAM-proximal DNA becomes accessible, and Cas1-Cas2 relocates to bind to the exposed DNA, enabling further prespacer processing and directional integration. These findings reveal how Cas9 collaborates with Csn2 and Cas1-Cas2 to couple PAM recognition with prespacer selection, resolving the dynamic structural transitions that ensure fidelity during type II-A CRISPR adaptation.

molecular biology↗

bioRxiv2025

DAPL1 deficiency impairs autophagy in retinal pigment epithelium to drive age-dependent retinal pathologies

Age-related retinopathy, primarily comprising age-related macular degeneration (AMD), is a major cause of irreversible blindness in the elderly population worldwide. Although its precise mechanisms remain incompletely understood, autophagy deficiency in retinal pigment epithelium (RPE) cells has been associated with AMD in patients; however, the regulatory pathways involved are not fully elucidated. In this study, we report that deficiency in the Dapl1 gene inhibits RPE cell autophagy and leads to age-dependent retinal pathologies in mice. Specifically, 18-month-old Dapl1-/- mice manifest age-related retinal dysfunction and structural abnormities, including increased retinal stress, photoreceptor/RPE cell damage, lipid aggregates and microglial activation. Furthermore, we demonstrate that autophagy is impaired in the RPE cells of Dapl1-/- mice, while overexpression of DAPL1 in RPE cells enhances autophagy activity. Mechanistically, we elucidate that DAPL1 suppresses the expression of E2F1 and c-MYC, which consequently downregulates mTOR and upregulates ATG16 and Beclin1 expression via DAPK1 in RPE cells, thereby promoting autophagy. Taken together, our findings demonstrate that DAPL1 acts as a novel regulator of autophagy in RPE cells, and its deficiency increases susceptibility to age-dependent retinal pathologies in mice.

molecular biology↗