Biology subjects

Sang, S.

Publications and source records attributed to Sang, S..

7 recordsLinked to original sources

bioRxiv2025

Apolipoprotein E ε4 exacerbates microglia-mediated complement-dependent synapse loss caused by neuronal Tpk deficiency

Thiamine pyrophosphokinse-1 (TPK) is a key enzyme that converts thiamine to functional thiamine diphosphate (TDP). TPK insufficiency and hence TDP reduction in neurons induced by amyloid-{beta} deposition and diabetes, an independent risk factor of Alzheimers disease (AD), recapitulate multi-pathophysiological features in the brain of mice, similar to those in human AD. Apolipoprotein E {varepsilon}4 allele (APOE4) is the most well-known genetic risk factor for AD. Clinical trials by boosting TDP using benfotiamine, a derivative of thiamine that significantly elevates TDP level in human encrythrocytes, have shown the inferior clinical efficacies in APOE4 carriers compared to non-APOE4 carriers. Clarifying the relationship between APOE4 and TPK expression and multi-pathophysiological characteristics of AD induced by Tpk deficiency in neurons is imperative. Here, we find that humanized APOE4 didnt directly affect Tpk expression of mice, but markedly aggravates behavior abnormalities of Tpk-cKO mice. Pathologically, the Tpk-cKO mice with humanized APOE4 knock-in (AE-cKO mice) exhibit more synapse loss than the mice with only humanized APOE4 knock-in and the Tpk-cKO mice. Transcriptomics and pathologic analysis identified that APOE4 promoted the overactivation of microglia and the transition of microglia to a disease-associated and phagocytosis state via a complement-mediated pathway. Further, the C3aR antagonist significantly repressed microglia phagocytosis and synaptic elimination of the AE-cKO mice. Our results demonstrate that APOE4 exacerbates behavior dysfunction of Tpk-cKO mice through microglia-mediated complement-dependent synaptic elimination. These findings provide important insights into the role of APOE4 in the pathogenesis of AD.

neuroscience↗

bioRxiv2024

The mechanism and consequences of amyloid-β modulating thiamine pyrophosphokinase-1 expression in microglia

Ample studies attribute cognitive decline in Alzheimers disease to amyloid-{beta} deposition 1-6. However, brain amyloid-{beta} accumulation that saturates years before the manifestation of clinical symptoms is dissociated with cognitive decline of the disease 7. It is unknown how these two processes are mechanistically linked. In this and our accompanied study, we report that thiamine pyrophosphokinase-1 (TPK) deficiency plays essential roles in both processes via distinct mechanisms. Here we describe that diminished microglia Tpk controls the propagation of amyloid-{beta} plaques. In APP/PS1 transgenic mice, microglia showed elevated Tpk expression at 2-month-old, but reduction in a plaque-centric manner at 8-month-old. Interestingly, lipopolysaccharide, but not amyloid-{beta}, induceed Tpk reduction in cultured microglia. Tpk reduction led to microglia dysfunction, showing volatile motility but reduced phagocytosis and weak response to focal tissue injury, with accumulation of intracellular lipid droplets and abnormal mitochrondria. In Alzheimers disease mice, microglia-specific knockout of Tpk caused diminished plaque coverage, exacerbated plaque burden and synaptic loss. However, increased plaques were not accompanied by the development of neurofibrillary tangles or brain atrophy, in contrast to the phenotype described in our accompanied paper with neuronal Tpk deletion. In conclusion, plaque-induced inflammation reduces Tpk in microglia, selectively exacerbating the spread of amyloid pathology.

neuroscience↗

bioRxiv2024

Single-cell dissection of prognostic architecture and immunotherapy response in Helicobacter pylori infection associated gastric cancer

Most of the gastric cancer (GC) worldwide are ascribed to Helicobacter pylori (H. pylori) infections, which have a detrimental effect on the immunotherapys efficacy. Comprehensively dissecting the key cell players and molecular pathways associated with cancer immunotherapies is critical for developing novel therapeutic strategies against H. pylori infection associated GC. We performed a comprehensive single-cell transcriptome analysis of nine GC with current H. pylori infection (HpGC), three GC with previous H. pylori infection (ex-HpGC), six GC without H. pylori infection (non-HpGC), and six healthy controls (HC). We also investigated key cell players and molecular pathways associated with GC immunotherapy outcomes. We revealed the molecular heterogeneity of different cell components in GC including epithelium, immune cells, and cancer-associated fibroblasts (CAFs) at the single-cell level. The malignant epithelium of HpGC exhibited high expression level of inflammatory and epithelial-mesenchymal transition (EMT) signature, HpGC and ex-HpGC were enriched with VEGFA+ angiogenic tumor-associated macrophages (Angio-TAM) and IL11+ inflammatory CAF (iCAF), characterized by high expression levels of NECTIN2 and VEGFA/B. Additionally, we found significant correlations between the abundance of iCAF with Angio-TAM and TIGIT+ suppressive T cells, and iCAF interacted with Angio-TAM through the VEGF and ANGPTL angiogenic pathways. We also developed an immune signature and angiogenic signature and demonstrated that the iCAF abundance and angiogenic signature could predict poor immunotherapy outcomes in GC. We revealed the transcriptome characteristics and heterogeneity of various cellular constituents of HpGC and demonstrated that a synergistic combination of immunotherapy and anti-angiogenic targeted therapy may be an effective therapeutic modality for HpGC.

cancer biology↗

bioRxiv2022

SERM: a self-consistent deep learning solution forrapid and accurate gene expression recovery

Single cell RNA sequencing (scRNA-seq) is a promising technique to determine the states of individual cells and classify novel cell subtypes. Computationally, the processing of scRNA-seq data presents a daunting challenge because of the noisy nature and humongous size and dimensionality of the data. Compromised solution by omitting the genes with low expression is commonly taken in current scRNA-seq analysis, which leads to inaccurate gene counts. In this paper, we introduce a broadly applicable data-driven gene expression recovery framework, referred to as the self-consistent expression recovery machine (SERM), to impute the missing gene expression. Using deep learning, SERM first learns from a subset of the noisy gene expression data to estimate the underlying data distribution. SERM then recovers the overall gene expression data by imposing a self-consistency on the gene expression matrix, thus ensuring that the expression levels are similarly distributed in different parts of the matrix. We show that SERM significantly improves the accuracy of gene imputation with at least 100-fold increase in computational efficiency in comparison to the state-of-the-art techniques. Thus SERM promises to provide an urgently needed computational solution for rapid and accurate recovery of big genomic expression data. SERM is available as a web-based computational tool (https://www.analyxus.com/compute/serm) and its source codes can be found in https://github.com/xinglab-ai/self-consistent-expression-recovery-machine.

bioinformatics↗

bioRxiv2021

APRILE: Exploring the Molecular Mechanisms of Drug Side Effects with Explainable Graph Neural Networks

The majority of people over the age of 65 take two or more medications. While many individual drug side effects are known, polypharmacy side effects due to novel drug combinations poses great risk. Here, we present APRILE: an explainable artificial intelligence (XAI) framework that uses graph neural networks to explore the molecular mechanisms underlying polypharmacy side effects. Given a list of side effects and the pairs of drugs causing them, APRILE identifies a set of proteins (drug targets or non-targets) and associated Gene Ontology (GO) terms as mechanistic explanations of associated side effects. Using APRILE, we generate such explanations for 843,318 (learned) and 93,966 (novel) side effect-drug pair events, spanning 861 side effects (472 diseases, 485 symptoms and 9 mental disorders) and 20 disease cate-gories. We show that our two new metrics--pharmacogenomic information utilization and protein-protein interaction information utilization--provide quantitative estimates of mechanism complexity. Explanations were significantly consistent with state of the art disease-gene associations for 232/239 (97%) side effects. Further, APRILE generated new insights into molecular mechanisms of four diverse categories of adverse drug reactions: infection, metabolic diseases, gastrointestinal diseases, and mental disorders, including paradoxical side effects. We demonstrate the viability of discovering polypharmacy side effect mechanisms by training an XAI framework on massive biomedical data. Consequently, it facilitates wider and more reliable use of AI in healthcare.

bioinformatics↗

bioRxiv2020

Thiamine pyrophosphokinase deficiency induces Alzheimer's pathology

BackgroundThiamine diphosphate (TDP) reduction plays an important role in cerebral glucose hypometabolism, the neurodegenerative indicator, in Alzheimers disease (AD). The mechanism underlying TDP reduction remains elusive. Thus, it is critical to define the mechanism and its effect on neurodegeneration, the pathological basis of the disease occurrence and progression. MethodsThe mRNA levels of all known genes associated with thiamine metabolism, including thiamine pyrophosphokinase (TPK), Solute Carrier Family 19 Member 2 (SLC19A2), SLC19A3, and SLC25A19, in brain samples of patients with AD and other neurodegenerative disorders in multiple independent datasets were analyzed. TPK protein levels were further examined in the brain tissues of AD patients and control subjects. A mouse model with conditional knockout (cKO) of TPK gene in the excitatory neurons of adult brain was established. ResultsThe brain TPK mRNA level was markedly lower in AD patients, but not in other neurodegenerative disorders. The brain TPK protein level was also significantly decreased in AD patients. TPK gene knockout in the mice caused cerebral glucose hypometabolism, {beta}-amyloid deposition, Tau hyperphosphorylation, neuroinflammation, and neuronal loss and brain atrophy. Cross-species correlation analysis revealed the similar changes of gene profiling between the cKO mice and AD patients. ConclusionsThe deficiency of brain TPK, a key enzyme for TDP synthesis, is specific to AD. The cKO mice show AD-associated phenotypes and could serve as a new mouse model for AD studies. Our study provides a novel insight into the critical role of TPK in AD pathogenesis and its potential for the disease treatment.

neuroscience↗

bioRxiv2019

Multilayered N-glycoproteomics reveals impaired N-glycosylation promoting Alzheimer’s disease

Alzheimers disease (AD) is one of the most common neurodegenerative diseases that currently lacks clear pathogenesis and effective treatment. Protein glycosylation is ubiquitous in brain tissue and site-specific analysis of N-glycoproteome, which is technically challenging, can advance our understanding of the glycoproteins role in AD. In this study, we profiled the multilayered variations in proteins, N-glycosites, N-glycans, and in particular site-specific N-glycopeptides in the APP/PS1 and wild type mouse brain through combining pGlyco 2.0 strategy with other quantitative N-glycoproteomic strategies. The comprehensive brain N-glycoproteome landscape was constructed, and rich details of the heterogeneous site-specific protein N-glycosylations were exhibited. Quantitative analyses explored generally downregulated N-glycosylation involving proteins such as glutamate receptors, as well as fucosylated and oligo-mannose type glycans in APP/PS1 mice versus wild type mice. Moreover, our preliminary functional study revealed that N-glycosylation was crucial for the membrane localization of NCAM1 and for maintaining the excitability and viability of neuron cells. Our work offered a panoramic view of the N-glycoproteomes in Alzheimers disease and revealed that generally impaired N-glycosylation promotes Alzheimers disease progression.

systems biology↗