Biology subjects

Li, Y.-M.

Publications and source records attributed to Li, Y.-M..

12 recordsLinked to original sources

bioRxiv2026

PlantRegMoD: An integrative and AI-driven multi-omics database for plant regeneration research

Plant regeneration underpins plant developmental plasticity, tissue culture, genetic transformation and crop improvement. Although numerous related omics datasets have been generated, specialized multi-omics databases for this field are still scarce. Here, we constructed PlantRegMoD, an AI-powered integrated database dedicated to plant regeneration. This platform hosts 20.54 TB standardized multi-omics data from 147 projects across 32 plant species and 2,593 samples. We established a unified hierarchical classification system covering five major categories and nine regeneration models, and curated 236 regeneration genes as well as their 28,190 homologs across 58 representative plant species. It contains extensive transcriptomic resources across all regeneration models, together with 196,423 single cells and over 8.81 million epigenetic peaks to dissect cellular heterogeneity and multi-layered epigenetic regulation. Equipped with nine online omics-related tools and a RAG-based intelligent Q&A system, PlantRegMoD greatly reduces bioinformatic barriers and serves as a robust resource for mechanistic, functional and evolutionary studies of plant regeneration.

plant biology↗

bioRxiv2026

Cytokines driven by caspase-1 and RIPK3 are antagonistic

Pyroptosis, apoptosis, and necroptosis are thought to provide redundant protection against intracellular pathogens. We found that mice lacking inflammasomes, caspase-8, and MLKL were highly susceptible to infection by an environmental cytosol-invasive bacterium. Surprisingly, deletion of Ripk3 completely restored resistance despite the continued absence of all three cell death pathways. The infection outcome was determined instead by the production of antagonistic cytokines arising from these pathways. Deletion of Casp8 and Mlkl initiated an effector-triggered immunity-like response, in which RIPK3 induced type I interferons causing catastrophic susceptibility by impeding neutrophil responses. Opposing this, caspase-1-dependent IL-1{beta} production counteracted these type I interferons and restored resistance. Thus, susceptibility arose not from failure of regulated cell death, but from the activation of RIPK3-driven type I interferons unopposed by caspase-1-driven IL-1{beta}. Therefore, antagonistic cytokines embedded within cell death pathway signaling, distinct from cell death itself, can dictate the immune response to intracellular infection.

immunology↗

bioRxiv2023

Di- and tri-methylation of histone H3K36 play distinct roles in DNA double-strand break repair

Histone H3 Lys36 (H3K36) methylation and its associated modifiers are crucial for DNA double-strand break (DSB) repair, but the mechanism governing whether and how different H3K36 methylation forms impact repair pathways is unclear. Here, we unveil the distinct roles of H3K36 dimethylation (H3K36me2) and H3K36 trimethylation (H3K36me3) in DSB repair via non-homologous end joining (NHEJ) or homologous recombination (HR). Yeast cells lacking H3K36me2 or H3K36me3 exhibit reduced NHEJ or HR efficiency. yKu70 and Rfa1 bind H3K36me2- or H3K36me3-modified peptides and chromatin, respectively. Disrupting these interactions impairs yKu70 and Rfa1 recruitment to damaged H3K36me2- or H3K36me3-rich loci, increasing DNA damage sensitivity and decreasing repair efficiency. Conversely, H3K36me2-enriched intergenic regions and H3K36me3-enriched gene bodies independently recruit yKu70 or Rfa1 under DSB stress. Importantly, human KU70 and RPA1, the homologs of yKu70 and Rfa1, exclusively associate with H3K36me2 and H3K36me3 in a conserved manner. These findings provide valuable insights into how H3K36me2 and H3K36me3 regulate distinct DSB repair pathways, highlighting H3K36 methylation as a critical element in the choice of DSB repair pathway.

biochemistry↗

bioRxiv2023

Phosphorylation and O-GlcNAcylation at the same alpha-synuclein site generate distinct fibril structures

-Synuclein (-syn) forms amyloid fibrils that are critical in the progression of Parkinsons disease (PD) and serves as the pathological hallmark of PD. Different posttranslational modifications (PTMs) have been identified at multiple sites of -syn, influencing its conformation, aggregation and function. Here, we investigate how disease-related phosphorylation and O-GlcNAcylation at the same -syn site (S87) affect fibril structure and neuropathology. Using semi-synthesis, we obtained homogenous -syn monomer with site-specific phosphorylation (pS87) and O-GlcNAcylation (gS87) at S87, respectively. Cryo-EM analysis revealed that pS87 and gS87 -syn form two novel but distinct fibril structures. The GlcNAc situated at S87 establishes interactions with K80 and E61, inducing a unique iron-like fold with the GlcNAc molecule on the iron handle. While, phosphorylation at the same site prevents a lengthy C-terminal region including residues 73-140 from incorporating into the fibril core due to electrostatic repulsion. Instead, the N-terminal half (1-72) shapes a novel arch-like fibril structure. We further show that both pS87 and gS87 -syn fibrils display reduced neurotoxicity and propagation activity compared with unmodified -syn fibril. Our findings demonstrate that different PTMs at the same site can produce distinct fibril structures, which emphasizes the precise regulation of PTMs to amyloid fibril formation and pathology.

biochemistry↗

bioRxiv2020

GSAP regulates mitochondrial function through the Mitochondria-associated ER membrane in the pathogenesis of Alzheimer's disease

Biochemical, pathogenic and human genetic data confirm that GSAP ({gamma}-secretase activating protein), a selective {gamma}-secretase modulatory protein, plays important roles in Alzheimers disease (AD) and Down syndrome. However, the molecular mechanism(s) underlying GSAP-dependent pathogenesis remains largely elusive. Here, through unbiased proteomics and single-nuclei RNA-seq, we identified that GSAP regulates multiple biological pathways, including protein phosphorylation, trafficking, lipid metabolism, and mitochondrial function. We demonstrated that GSAP physically interacts with Fe65:APP complex to regulate APP trafficking/partitioning. GSAP is enriched in the mitochondria-associated membrane (MAM) and regulates lipid homeostasis through the amyloidogenic processing of APP. GSAP deletion generates a lipid environment unfavorable for AD pathogenesis, leading to improved mitochondrial function and the rescue of cognitive deficits in an AD mouse model. Finally, we identified a novel GSAP single-nucleotide polymorphism that regulates its brain transcript level and is associated with an increased AD risk. Together, our findings indicate that GSAP impairs mitochondrial function through its MAM localization, and lowering GSAP expression reduces pathological effects associated with AD.

neuroscience↗

bioRxiv2020

GSAP Regulates Amyloid Beta Production through Modulation of Amyloid Precursor Protein Trafficking

In addition to participating in {gamma}-secretase activity, presenilin 1 (PS1) regulates trafficking and subcellular localization of {beta}-amyloid precursor protein (APP). We previously showed that gamma-secretase activating protein (GSAP) selectively modulates {gamma}-secretase activity by inducing conformational change in PS1. However, little is known whether and how GSAP might influence APP trafficking and consequent generation of {beta}-amyloid (A{beta}) peptides. Here, to explore whether GSAP has any role in regulating APP trafficking, and to systematically investigate the intracellular trafficking routes of APP, we paired total internal reflection fluorescence microscopy, high-speed line scanning microscopy, and 4D microscopy with comprehensive imaging analysis methodologies to depict the elusive modes of APP trafficking at a single-vesicle level. Mobility and diffusivity changes reveal the existence of two kinetically distinct pathways, classified into mobile and immobile pools, for vesicular APP trafficking, suggesting high association between immobile vesicle pool and amyloidogenic processing. GSAP knockdown significantly lowers immobile pool without overturning APP vesicle diffusivity, suggesting that GSAP affects vesicular APP trafficking by retaining APP in membrane microdomains known to favor amyloidogenic processing. Our study reveals a novel role of GSAP in the regulation of A{beta}-peptide formation that modulates switching of APP vesicles between immobile and mobile pools, which may help identifying new therapeutic strategies to treat Alzheimers disease.

neuroscience↗

bioRxiv2020

Large-scale single-cell analysis reveals critical immune characteristics of COVID-19 patients

Dysfunctional immune response in the COVID-19 patients is a recurrent theme impacting symptoms and mortality, yet the detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 205 COVID-19 patients and controls to create a comprehensive immune landscape. Lymphopenia and active T and B cell responses were found to coexist and associated with age, sex and their interactions with COVID-19. Diverse epithelial and immune cell types were observed to be virus-positive and showed dramatic transcriptomic changes. Elevation of ANXA1 and S100A9 in virus-positive squamous epithelial cells may enable the initiation of neutrophil and macrophage responses via the ANXA1-FPR1 and S100A8/9-TLR4 axes. Systemic upregulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis and designing effective therapeutic strategies for COVID-19. HIGHLIGHTSO_LILarge-scale scRNA-seq analysis depicts the immune landscape of COVID-19 C_LIO_LILymphopenia and active T and B cell responses coexist and are shaped by age and sex C_LIO_LISARS-CoV-2 infects diverse epithelial and immune cells, inducing distinct responses C_LIO_LICytokine storms with systemic S100A8/A9 are associated with COVID-19 severity C_LI

genomics↗

bioRxiv2020

Adopting STING agonist cyclic dinucleotides as a potential adjuvant for SARS-CoV-2 vaccine

A novel STING agonist CDGSF unilaterally modified with phosphorothioate and fluorine was synthesized. CDGSF displayed better STING activity over dithio CDG. Immunization of SARS-CoV-2 Spike protein with CDGSF as an adjuvant elicited an exceptional high antibody titer and a robust T cell response, which were better than the group using aluminium hydroxide as a adjuvant. These results highlighted the adjuvant potential of STING agonist in SARS-CoV-2 vaccine preparation for the first time.

immunology↗

bioRxiv2020

Parkinson's disease-related phosphorylation at Tyr39 rearranges α-synuclein amyloid fibril structure revealed by cryo-EM

Post-translational modifications (PTMs) of -synuclein (-syn), e.g. phosphorylation, play an important role in modulating -syn pathology in Parkinsons disease (PD) and -synucleinopathies. Accumulation of phosphorylated -syn fibrils in Lewy bodies and Lewy neurites is the histological hallmark of these diseases. However, it is unclear how phosphorylation relates to -syn pathology. Here, by combining chemical synthesis and bacterial expression, we obtained homogeneous -syn fibrils with site-specific phosphorylation at Y39, which exhibits enhanced neuronal pathology in rat primary cortical neurons. We determined the cryo-EM structure of pY39 -syn fibril, which reveals a new fold of -syn with pY39 in the center of the fibril core forming electrostatic interaction network with eight charged residues in the N-terminal region of -syn. This structure composed of residues 1-100 represents the largest -syn fibril core determined so far. This work provides structural understanding on the pathology of pY39 -syn fibril, and highlights the importance of PTMs in defining the polymorphism and pathology of amyloid fibrils in neurodegenerative diseases.

biophysics↗

bioRxiv2019

GCNCDA: A New Method for Predicting CircRNA-Disease Associations Based on Graph Convolutional Network Algorithm

Numerous evidences indicate that Circular RNAs (circRNAs) are widely involved in the occurrence and development of diseases. Identifying the association between circRNAs and diseases plays a crucial role in exploring the pathogenesis of complex diseases and improving the diagnosis and treatment of diseases. However, due to the complex mechanisms between circRNAs and diseases, it is expensive and time-consuming to discover the new circRNA-disease associations by biological experiment. Therefore, there is increasingly urgent need for utilizing the computational methods to predict novel circRNA-disease associations. In this study, we propose a computational method called GCNCDA based on the deep learning Fast learning with Graph Convolutional Networks (FastGCN) algorithm to predict the potential disease-associated circRNAs. Specifically, the method first forms the unified descriptor by fusing disease semantic similarity information, disease and circRNA Gaussian Interaction Profile (GIP) kernel similarity information based on known circRNA-disease associations. The FastGCN algorithm is then used to objectively extract the high-level features contained in the fusion descriptor. Finally, the new circRNA-disease associations are accurately predicted by the Forest by Penalizing Attributes (Forest PA) classifier. The 5-fold cross-validation experiment of GCNCDA achieved 91.2% accuracy with 92.78% sensitivity at the AUC of 90.90% on circR2Disease benchmark dataset. In comparison with different classifier models, feature extraction models and other state-of-the-art methods, GCNCDA shows strong competitiveness. Furthermore, 10 of the top 15 circRNA-disease association candidates with the highest prediction scores were confirmed by recently published literature. These results suggest that GCNCDA can effectively predict potential circRNA-disease associations and provide highly credible candidates for biological experiments. Author SummaryThe recognition of circRNA-disease association is the key of disease diagnosis and treatment, and it is of great significance for exploring the pathogenesis of complex diseases. Computational methods can predicte the potential disease-related circRNAs quickly and accurately. Based on the hypothesis that circRNA with similar function tends to associate with similar disease, GCNCDA model is proposed to effectively predict the potential association between circRNAs and diseases by combining FastGCN algorithm. The performance of the model was verified by cross-validation experiments, different feature extraction algorithm and classifier models comparison experiments. Furthermore, 10 of the top 15 disease-associated circRNAs with the highest prediction scores were confirmed by recently published literature. It is anticipated that GCNCDA model can give priority to the most promising circRNA-disease associations on a large scale to provide reliable candidates for further biological experiment.

bioinformatics↗

bioRxiv2018

GSAP modulates γ-secretase specificity by inducing conformational change in PS1

The mechanism by which GSAP ({gamma}-secretase activating protein) regulates {gamma}-secretase activity has not yet been elucidated. Here, we show that knockout of GSAP in cultured cells directly reduces {gamma}-secretase activity for A{beta} production, but not for Notch1 cleavage, suggesting that GSAP may induce a conformational change contributing to the specificity of {gamma}-secretase. Furthermore, using an active site directed photoprobe with double cross-linking moieties, we demonstrate that GSAP modifies the orientation and/or distance of PS1-NTF and PS1-CTF, a region containing the active site of {gamma}-secretase. This work offers insight into how GSAP regulates {gamma}-secretase specificity.

neuroscience↗

bioRxiv2018

Changes in pregnancy-related serum biomarkers early in gestation are associated with later development of preeclampsia

BackgroundPlacental protein expression plays a crucial biological role during normal and complicated pregnancies. We hypothesized that: (1) circulating pregnancy-associated, placenta-related protein levels throughout gestation reflect the uncomplicated, full-term temporal progression of human gestation, and effectively estimates gestational ages (GAs); (2) pregnancies with underlying placental pathology, such as preeclampsia (PE), are associated with disruptions in this GA estimation in early gestation; (3) malfunctions of this GA estimation can be employed to identify impending PE. In addition, to explore the underlying biology and PE etiology, we set to compare protein gestational patterns of human and mouse, using pregnant heme oxygenase-1 (HO-1) heterozygote (Het) mice, a mouse model reflecting PE-like symptoms.\n\nMethodsSerum levels of circulating placenta-related proteins - leptin (LEP), chorionic somatomammotropin hormone like 1 (CSHL1), elabela (ELA), activin A, soluble fms-like tyrosine kinase 1 (sFlt-1), and placental growth factor (PlGF)- were quantified by ELISA in blood serially collected throughout human pregnancies (20 normal subjects with 66 samples, and 20 PE subjects with 61 samples). Linear multivariate analysis of the targeted serological protein levels was performed to estimate the normal GA. Logarithmic transformed mean-squared errors of GA estimations were used to identify impending PE. Then the human gestational protein patterns were compared to those in the pregnant HO-1 mice.\n\nResultsAn elastic net (EN)-based gestational dating model was developed (R2 = 0.76) and validated (R2 = 0.61) using the serum levels of the 6 proteins at various GAs from women with normal uncomplicated pregnancies (n = 10 for training and n = 6 for validation). In pregnancies complicated by PE (n = 14), the EN model was not (R2 = -0.17) associated with GA at sampling in PE. Statistically significant deviations from the normal GA EN model estimations were observed in PE-associated pregnancies between GAs of 16-30 weeks (P = 0.01). The EN model developed with 5 proteins (ELA excluded due to the lack of robustness of the mouse ELA essay) performed similarly on normal human (R2 = 0.68) and WT mouse (R2 = 0.85) pregnancies. Disruptions of this model were observed in both human PE-associated (human: R2 = 0.27) and mouse HO-1 Het (mouse: R2 = 0.30) pregnancies. LEP out performed sFlt-1 and PlGF in differentiating impending PE at early human and late mouse gestations.\n\nConclusionsAs revealed in both human and mouse GA EN analyses, temporal serological placenta-related protein patterns are tightly regulated throughout normal human pregnancies and can be significantly disrupted in pathologic PE states. LEP changes earlier during gestation than the well-established late GA PE biomarkers (sFlt-1 and PlGF). Our HO-1 Het mouse analysis provides direct evidence of the causative action of HO-1 deficiency in LEP upregulation in a PE-like murine model. Therefore, longitudinal analyses of pregnancy-related protein patterns in sera, may not only help in the exploration of underlying PE pathophysiology but also provide better clinical utility in PE assessment.

molecular biology↗