Tracking single-cell evolution using clock-like chromatin accessibility loci.

Single-cell chromatin accessibility sequencing (scATAC-seq) reconstructs developmental trajectory by phenotypic similarity. However, inferring the exact developmental trajectory is challenging. Previous studies showed age-associated DNA methylation (DNAm) changes in specific genomic regions, termed clock-like differential methylation loci (ClockDML). Age-associated DNAm could either result from or result in chromatin accessibility changes at ClockDML. As cells undergo mitosis, the heterogeneity of chromatin accessibility on clock-like loci is reduced, providing a measure of mitotic age. In this study, we developed a method, called EpiTrace, that counts the fraction of opened clock-like loci from scATAC-seq data to determine cell age and perform lineage tracing in various cell lineages and animal species. It shows concordance with known developmental hierarchies, correlates well with DNAm-based clocks and is complementary with mutation-based lineage tracing, RNA velocity and stemness predictions. Applying EpiTrace to scATAC-seq data reveals biological insights with clinically relevant implications, ranging from hematopoiesis, organ development, tumor biology and immunity to cortical gyrification.

ACAT1 promotes proliferation and metastasis of bladder cancer via AKT/GSK3ß/c-Myc signaling pathway.

Acetyl-CoA acetyltransferase 1 (ACAT1) plays a significant role in the regulation of gene expression and tumorigenesis. However, the biological role of ACAT1 in bladder cancer (BLCA) has yet to be elucidated. This research aimed to elucidate the bioinformatics features and biological functions of ACAT1 in BLCA. Here, we demonstrate that ACAT1 is elevated in BLCA tissues and is correlated with specific clinicopathological features and an unfavorable prognosis for survival in BLCA patients. ACAT1 was identified as an independent risk factor in BLCA. Phenotypically, both in vitro and in vivo, ACAT1 knockdown suppressed BLCA cell proliferation and migration, while ACAT1 overexpression had the opposite effect. Mechanistic assays revealed that ACAT1 enhances BLCA cell proliferation and metastasis through the AKT/GSK3ß/c-Myc signaling pathway by modulating the cell cycle and EMT. Taken together, the results of our study reveal that ACAT1 is an oncogenic driver in BLCA that enhances tumor proliferation and metastasis, indicating its potential as a diagnostic and therapeutic target for this disease.

Strategies for the Enhancement of Secondary Metabolite Production via Biosynthesis Gene Cluster Regulation in Aspergillus oryzae.

The filamentous fungus Aspergillus oryzae (A. oryzae) has been extensively used for the biosynthesis of numerous secondary metabolites with significant applications in agriculture and food and medical industries, among others. However, the identification and functional prediction of metabolites through genome mining in A. oryzae are hindered by the complex regulatory mechanisms of secondary metabolite biosynthesis and the inactivity of most of the biosynthetic gene clusters involved. The global regulatory factors, pathway-specific regulatory factors, epigenetics, and environmental signals significantly impact the production of secondary metabolites, indicating that appropriate gene-level modulations are expected to promote the biosynthesis of secondary metabolites in A. oryzae. This review mainly focuses on illuminating the molecular regulatory mechanisms for the activation of potentially unexpressed pathways, possibly revealing the effects of transcriptional, epigenetic, and environmental signal regulation. By gaining a comprehensive understanding of the regulatory mechanisms of secondary metabolite biosynthesis, strategies can be developed to enhance the production and utilization of these metabolites, and potential functions can be fully exploited.

Causal association of smoking, blood lipids, and bladder cancer: Insights from a multivariable and mediation mendelian randomization investigation.

We used Mendelian randomization (MR) to examine the relationship between smoking, various categories of blood lipids, and bladder cancer (BLCA). Data for this study were drawn from the genome-wide association studies of the GSCAN consortium (~1.2 million participants), a subset of the UK Biobank (~120,000 participants), and the FinnGen consortium (2,072 cases and 307,082 controls). Initially, we utilized inverse variance weighted (IVW), complementary and sensitivity analyses, multivariable MR, and meta-analysis to confirm the association between blood lipids and BLCA. We then performed mediation MR to elucidate the relationship between smoking, blood lipids, and BLCA. Our analysis identified five lipids, including triglycerides in very large HDL, cholesterol in small VLDL, free cholesterol in very large HDL, total free cholesterol, and apolipoprotein B, as having strong and inverse associations with BLCA. These lipids demonstrated no heterogeneity or pleiotropy and exhibited consistent direction and magnitude across IVW, weighted median, and MR-Egger analyses. Our mediation MR further revealed that triglycerides in very large HDL and cholesterol in small VLDL could reduce the impact of smoking on BLCA, mediating -4.3% and -4.5% of the effect, respectively. In conclusion, our study identified five lipids exhibiting a robust inverse relationship with BLCA, two of which can buffer the impact of smoking on BLCA.

SMGCN: Multiple Similarity and Multiple Kernel Fusion Based Graph Convolutional Neural Network for Drug-Target Interactions Prediction.

Accurately identifying potential drug-target interactions (DTIs) is a critical step in accelerating drug discovery. Despite many studies that have been conducted over the past decades, detecting DTIs remains a highly challenging and complicated process. Therefore, we propose a novel method called SMGCN, which combines multiple similarity and multiple kernel fusion based on Graph Convolutional Network (GCN) to predict DTIs. In order to capture the features of the network structure and fully explore direct or indirect relationships between nodes, we propose the method of multiple similarity, which combines similarity fusion matrices with Random Walk with Restart (RWR) and cosine similarity. Then, we use GCN to extract multi-layer low-dimensional embedding features. Unlike traditional GCN methods, we incorporate Multiple Kernel Learning (MKL). Finally, we use the Dual Laplace Regularized Least Squares method to predict novel DTIs through combinatorial kernels in drug and target spaces. We conduct experiments on a golden standard dataset, and demonstrate the effectiveness of our proposed model in predicting DTIs through showing significant improvements in Area Under the Curve (AUC) and Area Under the Precision-Recall Curve (AUPR). In addition, our model can also discover some new DTIs, which can be verified by the KEGG BRITE Database and relevant literature.

Pectolinarigenin inhibits bladder urothelial carcinoma cell proliferation by regulating DNA damage/autophagy pathways.

Pectolinarigenin (PEC), an active compound isolated from traditional herbal medicine, has shown potential anti-tumor properties against various types of cancer cells. However, its mechanism of action in bladder cancer (BLCA), which is one of the fatal human carcinomas, remains unexplored. In this study, we first revealed that PEC, as a potential DNA topoisomerase II alpha (TOP2A) poison, can target TOP2A and cause significant DNA damage. PEC induced G2/M phase cell cycle arrest via p53 pathway. Simultaneously, PEC can perform its unique function by inhibiting the late autophagic flux. The blocking of autophagy caused proliferation inhibition of BLCA and further enhanced the DNA damage effect of PEC. In addition, we proved that PEC could intensify the cytotoxic effect of gemcitabine (GEM) on BLCA cells in vivo and in vitro. Summarily, we first systematically revealed that PEC had great potential as a novel TOP2A poison and an inhibitor of late autophagic flux in treating BLCA.

GraphPLBR: Protein-Ligand Binding Residue Prediction With Deep Graph Convolution Network.

The intermolecular interactions between proteins and ligands occur through site-specific amino acid residues in the proteins, and the identification of these key residues plays a critical role in both interpreting protein function and facilitating drug design based on virtual screening. In general, the information about the ligands-binding residues on proteins is unknown, and the detection of the binding residues by the biological wet experiments is time consuming. Therefore, many computational methods have been developed to identify the protein-ligand binding residues in recent years. We propose GraphPLBR, a framework based on Graph Convolutional Neural (GCN) networks, to predict protein-ligand binding residues (PLBR). The proteins are represented as a graph with residues as nodes through 3D protein structure data, such that the PLBR prediction task is transformed into a graph node classification task. A deep graph convolutional network is applied to extract information from higher-order neighbors, and initial residue connection with identity mapping is applied to cope with the over-smoothing problem caused by increasing the number of graph convolutional layers. To the best of our knowledge, this is a more unique and innovative perspective that utilizes the idea of graph node classification for protein-ligand binding residues prediction. By comparing with some state-of-the-art methods, our method performs better on several metrics.

Melatonin inhibits bladder tumorigenesis by suppressing PPARγ/ENO1-mediated glycolysis.

Melatonin is a well-known natural hormone, which shows a potential anticancer effect in many human cancers. Bladder cancer (BLCA) is one of the most malignant human cancers in the world. Chemoresistance is an increasingly prominent phenomenon that presents an obstacle to the clinical treatment of BLCA. There is an urgent need to investigate novel drugs to improve the current clinical status. In our study, we comprehensively explored the inhibitory effect of melatonin on BLCA and found that it could suppress glycolysis process. Moreover, we discovered that ENO1, a glycolytic enzyme involved in the ninth step of glycolysis, was the downstream effector of melatonin and could be a predictive biomarker of BLCA. We also proved that enhanced glycolysis simulated by adding exogenous pyruvate could induce gemcitabine resistance, and melatonin treatment or silencing of ENO1 could intensify the cytotoxic effect of gemcitabine on BLCA cells. Excessive accumulation of reactive oxygen species (ROS) mediated the inhibitory effect of melatonin on BLCA cells. Additionally, we uncovered that PPARγ was a novel upstream regulator of ENO1, which mediated the downregulation of ENO1 caused by melatonin. Our study offers a fresh perspective on the anticancer effect of melatonin and encourages further studies on clinical chemoresistance.

Histone methyltransferase SETD2: An epigenetic driver in clear cell renal cell carcinoma.

SET domain-containing 2 (SETD2) is a lysine methyltransferase that catalyzes histone H3 lysine36 trimethylation (H3K36me3) and has been revealed to play important roles in the regulation of transcriptional elongation, RNA splicing, and DNA damage repair. SETD2 mutations have been documented in several cancers, including clear cell renal cell carcinoma (ccRCC). SETD2 deficiency is associated with cancer occurrence and progression by regulating autophagy flux, general metabolic activity, and replication fork speed. Therefore, SETD2 is considered a potential epigenetic therapeutic target and is the subject of ongoing research on cancer-related diagnosis and treatment. This review presents an overview of the molecular functions of SETD2 in H3K36me3 regulation and its relationship with ccRCC, providing a theoretical basis for subsequent antitumor therapy based on SETD2 or H3K36me3 targets.

AAV9-HGF cooperating with TGF-beta/Smad inhibitor attenuates silicosis fibrosis via inhibiting ferroptosis.

Silicosis is a devastating interstitial lung disease characterized by silicon nodules and diffuse pulmonary fibrosis. To date, inefficient therapy is still a challenge of this disease due to its complicated pathogenesis. Hepatocyte growth factor (HGF) which is highly expressed in hepatocyte with anti-fibrotic and anti-apoptotic function was downregulated in silicosis. In addition, the upregulation of transforming growth factor-beta (TGF-ß), another pathological molecular was observed to aggravate the severity and accelerate the progression of silicosis. Here AAV expressed HGF with targeting pulmonary capillaries and SB431542, the inhibitor of TGF-ß signal pathway, were simultaneously adopted to synergistically reduce silicosis fibrosis. In vivo result demonstrated that the cooperation of HGF with SB431542 showed strong anti-fibrosis effects on the silicosis mice via tracheal administration of silica, compared to the separate treatment. The high efficacy was mainly achieved by remarkably by reducing ferroptosis of lung tissue. In our point, the combination of AAV9-HGF with SB431542 provide an alternative to relieve silicosis fibrosis from the perspective of targeting pulmonary capillaries.

Targeting Notch1-YAP Circuit Reprograms Macrophage Polarization and Alleviates Acute Liver Injury in Mice.

BACKGROUND & AIMS: Hepatic immune system disorder plays a critical role in the pathogenesis of acute liver injury. The intrinsic signaling mechanisms responsible for dampening excessive activation of liver macrophages are not completely understood. The Notch and Hippo-YAP signaling pathways have been implicated in immune homeostasis. In this study, we investigated the interactive cell signaling networks of Notch1/YAP pathway during acute liver injury. METHODS: Myeloid-specific Notch1 knockout (Notch1M-KO) mice and the floxed Notch1 (Notch1FL/FL) mice were subjected to lipopolysaccharide/D-galactosamine toxicity. Some mice were injected via the tail vein with bone marrow-derived macrophages transfected with lentivirus-expressing YAP. Some mice were injected with YAP siRNA using an in vivo mannose-mediated delivery system. RESULTS: We found that the activated Notch1 and YAP signaling in liver macrophages were closely related to lipopolysaccharide/D-galactosamine-induced acute liver injury. Macrophage/neutrophil infiltration, proinflammatory mediators, and hepatocellular apoptosis were markedly ameliorated in Notch1M-KO mice. Importantly, myeloid Notch1 deficiency depressed YAP signaling and facilitated M2 macrophage polarization in the injured liver. Furthermore, YAP overexpression in Notch1M-KO livers exacerbated liver damage and shifted macrophage polarization toward the M1 phenotype. Mechanistically, macrophage Notch1 signaling could transcriptionally activate YAP gene expression. Reciprocally, YAP transcriptionally upregulated the Notch ligand Jagged1 gene expression and was essential for Notch1-mediated macrophage polarization. Finally, dual inhibition of Notch1 and YAP in macrophages further promoted M2 polarization and alleviated liver damage. CONCLUSIONS: Our findings underscore a novel molecular insight into the Notch1-YAP circuit for controlling macrophage polarization in acute liver injury, raising the possibility of targeting macrophage Notch1-YAP circuit as an effective strategy for liver inflammation-related diseases.

GCHN-DTI: Predicting drug-target interactions by graph convolution on heterogeneous networks.

Determining the interaction of drug and target plays a key role in the process of drug development and discovery. The calculation methods can predict new interactions and speed up the process of drug development. In recent studies, the network-based approaches have been proposed to predict drug-target interactions. However, these methods cannot fully utilize the node information from heterogeneous networks. Therefore, we propose a method based on heterogeneous graph convolutional neural network for drug-target interaction prediction, GCHN-DTI (Predicting drug-target interactions by graph convolution on heterogeneous net-works), to predict potential DTIs. GCHN-DTI integrates network information from drug-target interactions, drug-drug interactions, drug-similarities, target-target interactions, and target-similarities. Then, the graph convolution operation is used in the heterogeneous network to obtain the node embedding of the drugs and the targets. Furthermore, we incorporate an attention mechanism between graph convolutional layers to combine node embedding from each layer. Finally, the drug-target interaction score is predicted based on the node embedding of the drugs and the targets. Our model uses fewer network types and achieves higher prediction performance. In addition, the prediction performance of the model will be significantly improved on the dataset with a higher proportion of positive samples. The experimental evaluations show that GCHN-DTI outperforms several state-of-the-art prediction methods.

The peroxins BcPex8, BcPex10, and BcPex12 are required for the development and pathogenicity of Botrytis cinerea.

Peroxisomes have been proved playing roles in infection of several plant pathogens. Although the contribution of a portion of peroxins in pathogenicity was demonstrated, most of them are undocumented in fungi, especially, Botrytis cinerea. The homologs of Pex8, Pex10, and Pex12 in B. cinerea were functionally characterized in this work using gene disruption strategies. Compared with the wild-type strain (WT), the Δbcpex8, Δbcpex10, and Δbcpex12 mutants exhibited significant reduction in melanin production, fatty acid utilization, and decreased tolerance to high osmotic pressure and reactive oxygen species (ROS). The mycelial growth and conidiation of were significantly inhibited in Δbcpex8, Δbcpex10, and Δbcpex12 strains. The mycelial growth rates of Δbcpex8, Δbcpex10, and Δbcpex12 were reduced by 32, 35, and 34%, respectively, compared with WT and ectopic transformant (ET), and the conidiation was reduced by approximately 89, 27, and 88%, respectively. The conidial germination, germ tube elongation, and the formation of initiate infection structures (IFSs) were also reduced by the deletion of the genes. The pathogenicity was tested on the leaves of tobacco and strawberry, and fruits of tomato. On the leaves of tobacco and strawberry, the Δbcpex8, Δbcpex10, and Δbcpex12 mutants could not induce necrotic lesions, and the lesions on tomato fruits infected with the mutants were significantly reduced than those of the wide type. The results indicated that BcPEX8, BcPEX10, and BcPEX12 are indispensable for the development and pathogenicity of B. cinerea.

Notch-activated mesenchymal stromal/stem cells enhance the protective effect against acetaminophen-induced acute liver injury by activating AMPK/SIRT1 pathway.

BACKGROUND: Notch signaling plays important roles in regulating innate immunity. However, little is known about the role of Notch in mesenchymal stromal/stem cell (MSC)-mediated immunomodulation during liver inflammatory response. METHODS: Notch activation in human umbilical cord-derived MSCs was performed by a tissue culture plate coated with Notch ligand, recombinant human Jagged1 (JAG1). Mice were given intravenous injection of Notch-activated MSCs after acetaminophen (APAP)-induced acute liver injury. Liver tissues were collected and analyzed by histology and immunohistochemistry. RESULTS: MSC administration reduced APAP-induced hepatocellular damage, as manifested by decreased serum ALT levels, intrahepatic macrophage/neutrophil infiltration, hepatocellular apoptosis and proinflammatory mediators. The anti-inflammatory activity and therapeutic effects of MSCs were greatly enhanced by Notch activation via its ligand JAG1. However, Notch2 disruption in MSCs markedly diminished the protective effect of MSCs against APAP-induced acute liver injury, even in the presence of JAG1 pretreatment. Strikingly, Notch-activated MSCs promoted AMP-activated protein kinase (AMPKα) phosphorylation, increased the sirtuins 1 (SIRT1) deacetylase expression, but downregulated spliced X-box-binding protein 1 (XBP1s) expression and consequently reduced NLR family pyrin domain-containing 3 (NLRP3) inflammasome activation. Furthermore, SIRT1 disruption or XBP1s overexpression in macrophages exacerbated APAP-triggered liver inflammation and augmented NLRP3/caspase-1 activity in MSC-administrated mice. Mechanistic studies further demonstrated that JAG1-pretreated MSCs activated Notch2/COX2/PGE2 signaling, which in turn induced macrophage AMPK/SIRT1 activation, leading to XBP1s deacetylation and inhibition of NLRP3 activity. CONCLUSIONS: Activation of Notch2 is required for the ability of MSCs to reduce the severity of APAP-induced liver damage in mice. Our findings underscore a novel molecular insights into MSCs-mediated immunomodulation by activating Notch2/COX2/AMPK/SIRT1 pathway and thus provide a new strategy for the treatment of liver inflammatory diseases.

Deacetylation of Notch1 by SIRT1 contributes to HBsAg- and HBeAg-mediated M2 macrophage polarization.

Hepatic macrophages are involved in both pathogen clearance and immunopathogenesis. Emerging evidence demonstrates that macrophage polarization plays a critical role in hepatitis B virus (HBV)-induced immune impairment and liver pathology. However, it remains largely unknown as to how HBV infection facilitates M2 macrophage polarization. Here, a mouse HBV infection model was established by hydrodynamic injection with a vector containing 1.3-fold overlength HBV genome via the tail vein. Coculture experiments with HBV-producing HepG2.2.15 cells and macrophages were established in vitro. We found that HBV-inhibited M1 while enhancing M2 markers, which was accompanied by decreased proinflammatory tumor necrosis factor-α (TNF-α) and augmented anti-inflammatory IL-10 expression. Furthermore, both hepatitis B surface antigen (HBsAg) and hepatitis B e antigen (HBeAg) secretion contributed to HBV-triggered macrophage polarization from M1 toward M2 phenotype. Mechanistically, HBsAg and HBeAg could upregulate the sirtuins 1 (SIRT1) deacetylase expression, which in turn promote deacetylation of the Notch1 intracellular domain (NICD), leading to increased Akt phosphorylation and decreased NF-κB nuclear translocation in macrophages. Our findings suggest that NICD deacetylation by SIRT1 contributes to HBsAg- and HBeAg-mediated M2 macrophage polarization, raising the possibility of targeting SIRT1/Notch1 pathway in macrophages to treat HBV immune evasion and chronic HBV infection.NEW & NOTEWORTHY This study identified a previously unrecognized molecular mechanism of HBV-mediated suppression of innate immune responses. We demonstrate that deacetylation of NICD by SIRT1 contributes to HBsAg- and HBeAg-mediated M2 macrophage polarization, which may aid in the development of new macrophage-based immunotherapy for chronic HBV infection and related diseases.

Botrytis cinerea BcSSP2 protein is a late infection phase, cytotoxic effector.

Botrytis cinerea is a broad-host-range necrotrophic phytopathogen responsible for serious diseases in leading crops. To facilitate infection, B. cinerea secretes a large number of effectors that induce plant cell death. In screening secretome data of B. cinerea during infection stage, we identified a phytotoxic protein (BcSSP2) that can also induce immune resistance in plants. BcSSP2 is a small, cysteine-rich protein without any known domains. Transient expression of BcSSP2 in leaves caused chlorosis that intensifies with time and eventually leads to death. Point mutations in eight of 10 cysteine residues abolished phytotoxicity, but residual toxic activity remained after heating treatment, suggesting contribution of unknown epitopes to protein phytotoxicity. The expression of bcssp2 was low during the first 36 h after inoculation and increased sharply upon transition to late infection stage. Deletion of bcssp2 did not cause statistically significant changes in lesions size on bean and tobacco leaves. Further analyses indicated that the phytotoxicity of BcSSP2 is negatively regulated by the receptor-like kinases BAK1 and SOBIR1. Collectively, our findings show that BcSSP2 is an effector protein that toxifies the host cells, but is also recognized by the plant immune system.

E3 ubiquitin ligase RNF126 affects bladder cancer progression through regulation of PTEN stability.

E3 ubiquitin ligase RNF126 (ring finger protein 126) is highly expressed in various cancers and strongly associated with tumorigenesis. However, its specific function in bladder cancer (BCa) is still debatable. Here, we found that RNF126 was significantly upregulated in BCa tissue by TCGA database, and our studies indicated that downregulation of RNF126 significantly inhibited cell proliferation and metastasis through the EGFR/PI3K/AKT signaling pathway in BCa cells. Furthermore, we identified PTEN, an inhibitor of the PI3K/AKT signaling pathway, as a novel substrate for RNF126. By co-immunoprecipitation assays, we proved that RNF126 directly interacts with PTEN. Predominantly, PTEN binds to the C-terminal containing the RING domain of RNF126. The in vivo ubiquitination assay showed that RNF126 specifically regulates PTEN stability through poly-ubiquitination. Furthermore, PTEN knockdown restored cell proliferation, metastasis, and tumor formation of BCa cells inhibited by RNF126 silencing in vitro and in vivo. In conclusion, these results identified RNF126 as an oncogene that functions through ubiquitination and degradation of PTEN in BCa.

The inhibitory effect of melatonin on human prostate cancer.

Prostate cancer (PCa) is one of the most commonly diagnosed human cancers in males. Nearly 191,930 new cases and 33,330 new deaths of PCa are estimated in 2020. Androgen and androgen receptor pathways played essential roles in the pathogenesis of PCa. Androgen depletion therapy is the most used therapies for primary PCa patients. However, due to the high relapse and mortality of PCa, developing novel noninvasive therapies have become the focus of research. Melatonin is an indole-like neurohormone mainly produced in the human pineal gland with a prominent anti-oxidant property. The anti-tumor ability of melatonin has been substantially confirmed and several related articles have also reported the inhibitory effect of melatonin on PCa, while reviews of this inhibitory effect of melatonin on PCa in recent 10 years are absent. Therefore, we systematically discuss the relationship between melatonin disruption and the risk of PCa, the mechanism of how melatonin inhibited PCa, and the synergistic benefits of melatonin and other drugs to summarize current understandings about the function of melatonin in suppressing human prostate cancer. We also raise several unsolved issues that need to be resolved to translate currently non-clinical trials of melatonin for clinic use. We hope this literature review could provide a solid theoretical basis for the future utilization of melatonin in preventing, diagnosing and treating human prostate cancer. Video abstract.