Biology subjects

li, L.

Publications and source records attributed to li, L..

4 recordsLinked to original sources

bioRxiv2026

Cross Study Regulator Activity Analysis Reveals Convergent Programs in alpha Synuclein PFF Models of Parkinson Disease

Alpha-synuclein preformed fibril (PFF) models reproduce features of Parkinson disease (PD), but differences in brain region, cell composition, and experimental design complicate comparisons across studies. We reconstructed study-specific regulatory networks using ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks) and inferred transcription factor (TF) and transcription cofactor activity using VIPER (Virtual Inference of Protein-activity by Enriched Regulon analysis). Five transcriptomic comparisons from four mouse PFF datasets were analyzed, with human PD single-nucleus RNA-sequencing data used to assess cross-species agreement. In the dopamine-neuron-enriched dataset GSE252967, PFF exposure was associated with increased activity of stress- and inflammation-related TFs, including JUND and RELA, and decreased activity of dopaminergic-identity regulators, including NR4A2, LMX1B, FOXA1, FOXA2, PITX3, and EN1. Several regulators were connected to Th in the inferred network. The substantia nigra bulk dataset GSE296779 showed reduced activity of ATF4- and XBP1-associated protein homeostasis and unfolded protein response programs, supported by regulon-weighted gene-set enrichment. Supporting mouse comparisons showed limited overlap in individual TFs but identified changes in inflammatory, glial, and stress-related programs. Agreement between inferred activity and transcript-level changes ranged from 64% to 100% in these comparisons. Human PD data showed cell-type-dependent agreement with mouse findings. EN1 and PITX3 were shared between the mouse and human networks upstream of Th/TH and showed reduced inferred activity in all seven human cell types, alongside nonsignificant decreases in the mouse dataset. These analyses identified changes in dopaminergic-identity, protein homeostasis, and inflammatory transcriptional programs across mouse PFF models, with partial support in human PD.

neuroscience↗

bioRxiv2025

Spatial profiling of chromatin accessibility reveals alteration of glial cells in Alzheimer's disease mouse brain

Abnormal epigenetic modifications, including altered chromatin accessibility, have been implicated in the development and progression of Alzheimers disease (AD). In this study, we applied spatially resolved chromatin accessibility profiling by performing spatial assay for transposase-accessible chromatin using sequencing (ATAC-seq) to analyze brain tissues from 5xFAD AD model and C57BL/6J control mice. Our analysis identified seven major cell types across 11 brain regions and further characterized glial subtypes--microglia and astrocytes-- revealing subtype-specific chromatin accessibility changes in 5xFAD mice relative to controls. These alterations were associated with AD-related pathways, including neuroinflammation and immune dysregulation, and synaptic dysfunction and neuronal signaling in microglia, as well as lysosomal and proteasomal activity, lipoprotein metabolism, and mitochondrial dysfunction in astrocytes. We also characterized cell-type-specific enrichments of motifs and transcription factors, including enrichment of Bcl11a in microglia. Furthermore, we linked chromatin accessibility changes in 5xFAD mice to human AD risk genes, highlighting altered epigenetic signatures in genes such as Trem2. Supporting the spatial ATAC-seq findings, flow cytometry validated a selective increase in VISTA (encoded by Vsir) protein expression in 5xFAD microglia, supporting the spatial ATAC-seq findings and indicating a shift toward a pro-inflammatory, disease-associated microglial (DAM-like) phenotype. These findings underscore the utility of spatial chromatin accessibility profiling for uncovering brain-region specific cell identities and epigenetic mechanisms underlying AD pathogenesis.

bioinformatics↗

bioRxiv2024

Genetic Modulation of Protein Expression in Rat Brain

Genetic variations in protein expression are implicated in a broad spectrum of common diseases and complex traits. However, the fundamental genetic architecture and variation of protein expression have received comparatively less attention than either mRNA or classical phenotypes. In this study, we systematically quantified proteins in the brains of a large family of rats using tandem mass tag (TMT)-based quantitative mass-spectrometry (MS) technology. We identified and quantified a comprehensive proteome of 8,119 proteins from Spontaneously Hypertensive (SHR/Olalpcv), Brown Norway with polydactyly-luxate (BN-Lx/Cub), and 29 of their fully inbred HXB/BXH progeny. Differential expression (DE) analysis identified 597 proteins with significant differences in expression between the parental strains (fold change > 2 and FDR < 0.01). We characterized 95 variant peptides by proteogenomics approach and discovered 464 proteins linked to strong cis-acting quantitative trait loci (pQTLs, FDR < 0.05). We also explored the linkage of pQTLs with behavioral phenotypes in rats and examined the sex-specific pQTLs to reveal both distinct and shared cis-pQTLs between sexes. Furthermore, by creating a novel view of the rat pangenome, we improved the ability to pinpoint candidate genes underlying pQTL. Finally, we explored the connection between the pQTLs in rat and human disorders, underscoring the translational potential of our findings. Collectively, this work demonstrates the value of large and systematic proteo-genetic datasets in understanding protein modulation in the brain and its functional linkage to complex central nervous system (CNS) traits.

genetics↗

bioRxiv2019

Novel pipeline of high-frequency neoantigens heathy donor-based validation in breast cancer

Neoantigen, a peptide fragment formed by genetic mutation, gives immunologist a new target for cancer therapy. Development of biotechnology has opened a new era for discovering high-frequency neoantigens. The aim of our study was to identify breast cancer neoantigens for tumor immunotherapy using an efficient way. Here, we established a computational pipeline to identify neoantigens associated with breast cancer using data from database and evaluated the immunogenicity of neoantigens using the peripheral blood of healthy donators in vitro. We identified 39,401 missense mutation sites from 285,283 single nucleotide variations (SNVs) obtained from database, and confirmed candidate epitopes by analyzing the binding affinity of mutant epitopes and human leukocyte antigen (HLA) using 6 algorithms. Peptide-binding assay was used as a complement for affinity testing. The immunogenicity of candidate peptides with high affinity were assessed through enzyme-linked immunospot (ELISPOT) assay and Cytotoxicity assay. In our study, we identified 10 candidate peptides with high binding affinity of HLA-A*0201 alleles, and seven of ten peptides showed the ability of inducing specific cytotoxic lymphocytes(CTLs) ex vivo, in healthy HLA-A2+ donors. We found that the peptide derived from TWISTNB have the highest immunogenicity and cytotoxicity among those candidate peptides. Furthermore, it can trigger the immune response of specific-CTLs to destroy target cells expressing this neoantigen in vitro, and without cross-reactivity with wild-type peptides. We conclude that the effective pipeline will provide potential possibilities to rapidly identify abundant high-frequency neoantigens and create neoantigen library for immunotherapy of breast cancer and even other tumors.

cancer biology↗