Single-cell dissection, hdWGCNA and deep learning reveal the role of oxidatively stressed plasma cells in ulcerative colitis.

Ulcerative colitis (UC) develops as a result of complex interactions between various cell types in the mucosal microenvironment. In this study, we aim to elucidate the pathogenesis of ulcerative colitis at the single-cell level and unveil its clinical significance. Using single-cell RNA sequencing and high-dimensional weighted gene co-expression network analysis, we identify a subpopulation of plasma cells (PCs) with significantly increased infiltration in UC colonic mucosa, characterized by pronounced oxidative stress. Combining 10 machine learning approaches, we find that the PC oxidative stress genes accurately distinguish diseased mucosa from normal mucosa (independent external testing AUC=0.991, sensitivity=0.986, specificity=0.909). Using MCPcounter and non-negative matrix factorization, we identify the association between PC oxidative stress genes and immune cell infiltration as well as patient heterogeneity. Spatial transcriptome data is used to verify the infiltration of oxidatively stressed PCs in colitis. Finally, we develop a gene-immune convolutional neural network deep learning model to diagnose UC mucosa in different cohorts (independent external testing AUC=0.984, sensitivity=95.9%, specificity=100%). Our work sheds light on the key pathogenic cell subpopulations in UC and is essential for the development of future clinical disease diagnostic tools.

Identification of antigen-presentation related B cells as a key player in Crohn's disease using single-cell dissecting, hdWGCNA, and deep learning.

Crohn's disease (CD) arises from intricate intercellular interactions within the intestinal lamina propria. Our objective was to use single-cell RNA sequencing to investigate CD pathogenesis and explore its clinical significance. We identified a distinct subset of B cells, highly infiltrated in the CD lamina propria, that expressed genes related to antigen presentation. Using high-dimensional weighted gene co-expression network analysis and nine machine learning techniques, we demonstrated that the antigen-presenting CD-specific B cell signature effectively differentiated diseased mucosa from normal mucosa (Independent external testing AUC = 0.963). Additionally, using MCPcounter and non-negative matrix factorization, we established a relationship between the antigen-presenting CD-specific B cell signature and immune cell infiltration and patient heterogeneity. Finally, we developed a gene-immune convolutional neural network deep learning model that accurately diagnosed CD mucosa in diverse cohorts (Independent external testing AUC = 0.963). Our research has revealed a population of B cells with a potential promoting role in CD pathogenesis and represents a fundamental step in the development of future clinical diagnostic tools for the disease.

A precise molecular subtyping of ulcerative colitis reveals the immune heterogeneity and predicts clinical drug responses.

BACKGROUND AND AIMS: We sought to identify novel molecular subtypes of ulcerative colitis (UC) based on large-scale cohorts and establish a clinically applicable subtyping system for the precision treatment of the disease. METHODS: Eight microarray profiles containing colon samples from 357 patients were utilized. Expression heterogeneity was screened out and stable subtypes were identified among UC patients. Immune infiltration pattern and biological agent response were compared among subtypes to assess the value in guiding treatment. The relationship between PRLR and TNFSF13B genes with the highest predictive value was further validated by functional experiments. RESULTS: Three stable molecular subtypes were successfully identified. Immune cell infiltration analysis defined three subtypes as innate immune activated UC (IIA), whole immune activated UC (WIA), and immune homeostasis like UC (IHL). Notably, the response rate towards biological agents (infliximab/vedolizumab) in WIA patients was the lowest (less than 10%), while the response rate in IHL patients was the highest, ranging from 42 to 60%. Among the featured genes of subtypes, the ratio of PRLR to TNFSF13B could effectively screen for IHL UC subtype suitable for biological agent therapies (Area under curve: 0.961-0.986). Furthermore, we demonstrated that PRLR expressed in epithelial cells could inhibit the expression of TNFSF13B in monocyte-derived macrophages through the CXCL1-NF-κB pathway. CONCLUSIONS: We identified three stable UC subtypes with a heterogeneous immune pattern and different response rates towards biological agents for the first time. We also established a precise molecular subtyping system and classifier to predict clinical drug response and provide individualized treatment strategies for UC patients.

Single-cell dissection reveals the role of DNA damage response patterns in tumor microenvironment components contributing to colorectal cancer progression and immunotherapy.

Colorectal cancer (CRC) is one of the leading malignant cancers. DNA damage response (DDR), referring to the molecular process of DNA damage, is emerging as a promising field in targeted cancer therapy. However, the engagement of DDR in the remodeling of the tumor microenvironment is rarely studied. In this study, by sequential nonnegative matrix factorization (NMF) algorithm, pseudotime analysis, cell-cell interaction analysis, and SCENIC analysis, we have shown that DDR genes demonstrate various patterns among different cell types in CRC TME (tumor microenvironment), especially in epithelial cells, cancer-associated fibroblasts, CD8+ T cells, tumor-associated macrophages, which enhance the intensity of intercellular communication and transcription factor activation. Furthermore, based on the newly identified DDR-related TME signatures, cell subtypes including MNAT+CD8+T_cells-C5, POLR2E+Mac-C10, HMGB2+Epi-C4, HMGB1+Mac-C11, PER1+Mac-C5, PER1+CD8+T_cells-C1, POLR2A+Mac-C1, TDG+Epi-C5, TDG+CD8+T_cells-C8 are determined as critical prognostic factors for CRC patients and predictors of immune checkpoint blockade (ICB) therapy efficacy in two public CRC cohorts, TCGA-COAD and GSE39582. Our novel and systematic analysis on the level of the single-cell analysis has revealed the unique role of DDR in remodeling CRC TME for the first time, facilitating the prediction of prognosis and guidance of personalized ICB regimens in CRC.

Inhibition of the dopamine transporter promotes lysosome biogenesis and ameliorates Alzheimer's disease-like symptoms in mice.

INTRODUCTION: Lysosomes are degradative organelles that maintain cellular homeostasis and protein quality control. Transcription factor EB (TFEB)-mediated lysosome biogenesis enhances lysosome-dependent degradation and alleviates neurodegenerative diseases, but the mechanisms underlying TFEB regulation and modification are still poorly understood. METHODS: By screening novel small-molecule compounds, we identified a group of lysosome-enhancing compounds (LYECs) that promote TFEB activation and lysosome biogenesis. RESULTS: One of these compounds, LH2-051, significantly inhibited the function of the dopamine transporter (DAT) and subsequently promoted lysosome biogenesis. We uncovered cyclin-dependent kinase 9 (CDK9) as a novel regulator of DAT-mediated lysosome biogenesis and identified six novel CDK9-phosphorylated sites on TFEB. We observed that signal transduction by the DAT-CDK9-TFEB axis occurs on lysosomes. Finally, we found that LH2-051 enhanced the degradation of amyloid beta plaques and improved the memory of amyloid precursor protein (APP)/Presenilin 1 (PS1) mice. DISCUSSION: We identified the DAT-CDK9-TFEB signaling axis as a novel regulator of lysosome biogenesis. Our study sheds light on the mechanisms of protein quality control under pathophysiological conditions.

TFEB acetylation promotes lysosome biogenesis and ameliorates Alzheimer's disease-relevant phenotypes in mice.

Lysosomes are one of the major centers for regulating cargo degradation and protein quality control. Transcription factor EB (TFEB)-promoted lysosome biogenesis enhances lysosome-mediated degradation and alleviates neurodegenerative diseases, but the mechanisms underlying TFEB modification and activation are still poorly understood. Here, we report essential roles of TFEB acetylation in TFEB nuclear translocation and lysosome biogenesis, which are independent of TFEB dephosphorylation. By screening small molecules, we find that Trichostatin A (TSA), the pan-inhibitor of histone deacetylases (HDACs), promotes nuclear translocation of TFEB. TSA enhances the staining of cells by LysoTracker Red and increases the expression of lysosomal and autophagic genes. We identify four novel acetylated lysine residues in TFEB, which are important for TFEB nuclear translocation and lysosome biogenesis. We show that TFEB acetylation is regulated by HDACs (HDAC5, HDAC6, and HDAC9) and lysine acetyltransferases (KATs), including ELP3, CREBBP, and HAT1. During TSA-induced cytosol-to-nucleus translocation of TFEB, acetylation is independent of TFEB dephosphorylation, since the mTORC1- or GSK3ß-related phosphorylation sites on TFEB are still phosphorylated. Administration of TSA to APP/PS1 mice increases the expression of lysosomal and autophagic genes in mouse brains and also improves memory. Accordingly, the ß-amyloid plaque burden is decreased. These results show that the acetylation of TFEB, as a novel mechanism of TFEB activation, promotes lysosome biogenesis and alleviates the pathogenesis of Alzheimer's disease. Our results also suggest that HDAC inhibition can promote lysosome biogenesis, and this may be a potential therapeutic approach for the treatment of neurodegenerative diseases and disorders related to HDAC hyperactivation.

Reduction of WDR81 impairs autophagic clearance of aggregated proteins and cell viability in neurodegenerative phenotypes.

Neurodegenerative diseases are characterized by neuron loss and accumulation of undegraded protein aggregates. These phenotypes are partially due to defective protein degradation in neuronal cells. Autophagic clearance of aggregated proteins is critical to protein quality control, but the underlying mechanisms are still poorly understood. Here we report the essential role of WDR81 in autophagic clearance of protein aggregates in models of Huntington's disease (HD), Parkinson's disease (PD) and Alzheimer's disease (AD). In hippocampus and cortex of patients with HD, PD and AD, protein level of endogenous WDR81 is decreased but autophagic receptor p62 accumulates significantly. WDR81 facilitates the recruitment of autophagic proteins onto Htt polyQ aggregates and promotes autophagic clearance of Htt polyQ subsequently. The BEACH and MFS domains of WDR81 are sufficient for its recruitment onto Htt polyQ aggregates, and its WD40 repeats are essential for WDR81 interaction with covalent bound ATG5-ATG12. Reduction of WDR81 impairs the viability of mouse primary neurons, while overexpression of WDR81 restores the viability of fibroblasts from HD patients. Notably, in Caenorhabditis elegans, deletion of the WDR81 homolog (SORF-2) causes accumulation of p62 bodies and exacerbates neuron loss induced by overexpressed α-synuclein. As expected, overexpression of SORF-2 or human WDR81 restores neuron viability in worms. These results demonstrate that WDR81 has crucial evolutionarily conserved roles in autophagic clearance of protein aggregates and maintenance of cell viability under pathological conditions, and its reduction provides mechanistic insights into the pathogenesis of HD, PD, AD and brain disorders related to WDR81 mutations.