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Biology subjects

Luo, O. J.

Publications and source records attributed to Luo, O. J..

6 recordsLinked to original sources

Integrated Multiomics Reveals Intergenerational Brain Sensory System Remodeling Induced by Parental Intermittent Fasting

Intermittent fasting (IF) is increasingly recognized as a potent modulator of metabolic health, but its effects on brain function across generations remain poorly understood. Here, we show that parental IF, administered to both mothers and fathers before mating, is associated with coordinated molecular remodeling in the cerebral cortex of fathers and their offspring, with shared molecular signatures identified between these generations and a pronounced enrichment of sensory-associated pathways. Using whole-genome bisulfite sequencing, transcriptomic profiling, and proteomic analysis, we found that IF elicited widespread cortical epigenetic remodeling in fathers, accompanied by transcriptional and protein-level changes enriched for olfactory, taste, synaptic, and neurometabolic pathways. Strikingly, related molecular signatures were detected in F1 offspring that had never been directly exposed to fasting, consistent with intergenerational transmission of IF-associated cortical remodeling. Offspring responses were sex dependent, with female and male progeny exhibiting distinct patterns of DNA methylation, gene expression, and protein abundance. Integrated multiomic analyses identified conserved candidate networks involved in sensory perception, glutamatergic signaling, synaptic organization, intracellular trafficking, cytoskeletal regulation, and stress-response pathways. Together, these findings identify sensory-associated cortical remodeling as a prominent molecular feature associated with parental IF and reveal persistent, sex-dependent molecular alterations in the offspring brain.

genomics↗

DECIPHER integrates disentangled representation learning and prototype-based cell-type deconvolution across molecular modalities

The growing availability of single-cell resources creates new opportunities to extract cell-type-resolved information from the vast body of existing bulk omics data through cell-type deconvolution. Conventional deconvolution methods often rely on linear mixture models or specific probabilistic assumptions and can be sensitive to batch effects, whereas many deep-learning approaches are modality-specific or lack a unified end-to-end learning framework. Here, we developed DECIPHER, an end-to-end representation-learning framework for cell-type deconvolution that can be applied across multiple molecular modalities. DECIPHER learns a domain-constant representation (Zc) for deconvolution and a domain-specific representation (Zs) to model domain-associated variation. By integrating nonlinear representation learning with differentiable non-negative least-squares optimization, DECIPHER estimates cell-type proportions from Zc. Across simulated datasets, experimentally generated bulk-cell mixtures, real-world datasets, and multiple molecular modalities, DECIPHER showed robust and competitive cell-type deconvolution performance. Beyond cell-type proportion estimation, the learned Zc supported chronological age prediction across independent cohorts and prognostic stratification in lung adenocarcinoma, demonstrating that DECIPHER can transform high-dimensional bulk omics data into low-dimensional, biologically informative representations. DECIPHER thus broadens the utility of existing bulk omics resources for biological discovery and clinical research.

bioinformatics↗

NAD+ - and EVA1-C-dependent reversal of neurological deficits is mediated by differential alternative RNA splicing in tauopathic animal models

Aberrant alternative splicing (ASEs) is an aging hallmark to Alzheimers Disease (AD). Although NAD+ and related metabolites can slow down AD, NAD+ on ASEs in AD remain unclear. Mouse transcriptomic data revealed NR-induced ASEs, focusing on the Eva1-C locus. AI-based algorithms predicted EVA1-C protein structures and protein-protein interactions. AD postmortem brain samples and tauopathy models including transgenic mice and worm was used for validation. NAD+ abundance/metabolic status modulates ASEs and the expression of EVA1-C isoforms, which in turn regulate the interaction with BAG-1 and HSP70 proteins. Importantly, EVA1-C is dramatically reduced in 20 Braak 5/6 AD patients compared to cognitive normal humans in different brain regions. NAD+ metabolism modulates abundance of specific mRNA isoforms, and that ASEs influence disease progression in model tauopathies and potentially AD. These results could facilitate future development of NAD+-based splice-switching therapeutics for AD. TeaserUnveiling the Link Between NAD+ Metabolism and Alzheimers Disease: Discovering the Role of Alternative RNA Splicing in Disease Progression and Potential Therapeutic Targets

neuroscience↗

MIST: an interpretable and flexible deep learning framework for single-T cell transcriptome and receptor analysis

Joint analysis of transcriptomic and T cell receptor (TCR) features at single-cell resolution provides a powerful approach for in-depth T cell immune function research. Here, we introduce a deep learning framework for single-T cell transcriptome and receptor analysis, MIST (Multi-Insight for T cell). MIST features three latent spaces: gene expression, TCR, and a joint latent space. Through analyses of antigen- specific T cells and T cells related to lung cancer immunotherapy, we demonstrate MISTs interpretability and flexibility. MIST easily and accurately resolves cell function and antigen-specificity by vectorizing and integrating transcriptome and TCR data of T cells. In addition, using MIST, we identified the heterogeneity of CXCL13+ subsets in lung cancer infiltrating CD8+ T cells and their association with immunotherapy, providing additional insights into the functional transition of CXCL13+ T cells related to anti-PD-1 therapy that were not reported in the original study. MIST is available at https://github.com/aapupu/MIST.

bioinformatics↗

SARS-CoV-2 variant B.1.1.7 caused HLA-A2+ CD8+ T cell epitope mutations for impaired cellular immune response

The rapid spreading of the newly emerged SARS-CoV-2 variant, B.1.1.7, highlighted the requirements to better understand adaptive immune responses to this virus. Since CD8+ T cell responses play an important role in disease resolution and modulation in COVID-19 patients, it is essential to address whether these newly emerged mutations would result in altered immune responses. Here we evaluated the immune properties of the HLA-A2 restricted CD8+ T cell epitopes containing mutations from B.1.1.7, and furthermore performed a comprehensive analysis of the SARS-CoV-2 specific CD8+ T cell responses from COVID-19 convalescent patients and SARS-CoV-2 vaccinees recognizing the ancestral Wuhan strain compared to B.1.1.7. First, most of the predicted CD8+ T cell epitopes showed proper binding with HLA-A2, while epitopes from B.1.1.7 had lower binding capability than those from the ancestral strain. In addition, these peptides could effectively induced the activation and cytotoxicity of CD8+ T cells. Our results further showed that at least two site mutations in B.1.1.7 resulted in a decrease in CD8+ T cell activation and a possible immune evasion, namely A1708D mutation in ORF1ab1707-1716 and I2230T mutation in ORF1ab2230-2238. Our current analysis provides information that contributes to the understanding of SARS-CoV-2-specific CD8+ T cell responses elicited by infection of mutated strains or vaccination. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=172 SRC="FIGDIR/small/437363v2_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@b9f2cdorg.highwire.dtl.DTLVardef@1f39e3dorg.highwire.dtl.DTLVardef@119c313org.highwire.dtl.DTLVardef@565388_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

CD8+ T cell epitope variations suggest a potential antigen presentation deficiency for spike protein of SARS-CoV-2

COVID-19 is caused by a newly identified coronavirus, SARS-CoV-2, and has become a pandemic around the world. The illustration of the immune responses against SARS-CoV-2 is urgently needed for understanding the pathogenesis of the disease and its vaccine development. CD8+ T cells are critical for virus clearance and induce long lasting protection in the host. Here we identified specific HLA-A2 restricted T cell epitopes in the spike protein of SARS-CoV-2. Seven epitope peptides (n-Sp1, 2, 6, 7, 11, 13, 14) were confirmed to bind with HLA-A2 and potentially be presented by antigen presenting cells to induce host immune responses. Tetramers containing these peptides could interact with specific CD8+ T cells from convalescent COVID-19 patients, and one dominant epitope (n-Sp1) was defined. In addition, these epitopes could activate and generate epitope-specific T cells in vitro, and those activated T cells showed cytotoxicity to target cells. Meanwhile, all these epitopes exhibited high frequency of variations. Among them, n-Sp1 epitope variation 5L>F significantly decreased the proportion of specific T cell activation; n-Sp1 epitope 8L>V variant showed significantly reduced binding to HLA-A2 and decreased the proportion of n-Sp1-specific CD8+ T cell, which potentially contributes to the immune escape of SAR-CoV-2.

immunology↗