Biological Experiments Research Articles

RAEPI: Predicting Enhancer-Promoter Interactions Based on Restricted Attention Mechanism.

Enhancer-promoter interactions (EPIs) are crucial in gene transcription regulation and cell differentiation. Traditional biological experiments are costly and time-consuming, motivating the development of computational prediction methods. However, existing EPI prediction methods inadequately capture the intricate direct interactions between enhancer and promoter sequences, which limits their prediction performance to some extent. In this work, we propose an innovative attention-based approach RAEPI, which uses convolutional neural networks to extract initial features of enhancers and promoters, combined with a specially designed Restricted Attention mechanism with Query-Key-Value constrained to simulate the interactions between them for further feature extraction. To improve cross-cell line prediction, we employ a transfer learning strategy for pre-training. Furthermore, we extracted sequence motifs to evaluate the RAEPI's effectiveness from a visualization perspective. Experimental results show that RAEPI achieves competitive prediction performance to existing methods on the benchmark dataset.

Ethanol extract of cassia seed alleviates metabolic dysfunction-associated steatotic liver disease by acting on multiple lipid metabolism-related pathways

Abstract Background and objective In northern China’s cold regions, the prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) exceeds 50%, significantly higher than the national and global rates. MASLD is an important risk factor for cardiovascular and cerebrovascular diseases, including coronary heart disease, stroke, and tumors, with no specific therapeutic drugs currently available. The ethanol extract of cassia seed (CSEE) has shown promise in lowering blood lipids and improving hepatic steatosis, but its mechanism in treating MASLD remains underexplored. This study aims to investigate the therapeutic effects and mechanisms of CSEE. Methods MASLD models were established in male Wistar rats and golden hamsters using a high fat diet (HFD). CSEE (10, 50, 250 mg/kg) was administered via gavage for six weeks. Serum levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), aspartate aminotransferase (AST), and alanine aminotransferase (ALT), as well as liver TC and TG, were measured using biochemical kits. Histopathological changes in the liver were evaluated using Oil Red O staining, Hematoxylin-eosin (H&E) staining, and transmission electron microscopy (TEM). HepG2 cell viability was assessed using the cell counting kit-8 (CCK8) and Calcein-AM/PI staining. Network pharmacology was used to analyze drug-disease targets, and western blotting was used to confirm these predictions. Results CSEE treatment significantly reduced serum levels of TC, TG, LDL-C, ALT, and AST, and improved liver weight, liver index, and hepatic lipid deposition in rats and golden hamsters. In addition, CSEE alleviated free fatty acid (FFA)-induced lipid deposition in HepG2 cells. Molecular biology experiments demonstrated that CSEE increased the protein levels of p-AMPK, p-ACC, PPARα, CPT1A, PI3K P110 and p-AKT, while decreasing the protein levels of SREBP1, FASN, C/EBPα, and PPARγ, thus improving hepatic lipid metabolism and reducing lipid deposition. The beneficial effects of CSEE were reversed by small molecule inhibitors of the signaling pathways in vitro. Conclusion CSEE improves liver lipid metabolism and reduces lipid droplet deposition in Wistar rats and golden hamsters with MASLD by activating hepatic AMPK, PPARα, and PI3K/AKT signaling pathways.

Simplified Flow Photosynthesis of Deuterium-Labeled Pyocyanin.

Deuterium-labeled pyocyanin was prepared from deuterium-labeled phenazine methosulfate in gram scale by a simplified flow photosynthesis in water. The main product was the protonated red form of pyocyanin-d3 (Pyo-d3-H+) in 85 % yield. Quantum chemical calculations of NMR support that nitrogen-10 is protonated. The by-products of the photolysis and the stability of the photolysis mixture were carefully characterized by LC-MS and NMR. Four by-products were identified: An isomer of pyocyanin-d3 (9%), 8-hydroxypyocyanin-d3 (4%), 1-hydroxyphenazine (0.4%), and phenazine (1%). The Pyo-d3-H+ product was stable in the photolysis solution after storage at 8°C for 2.5 years. Pure blue pyocyanin-d3 powder was isolated from the red photolysis solution by the Surrey method in 94 % yield. The addition of the red photolysis solution of Pyo-d3-H+ (100 μM) and commercial pyocyanin (100 μM) to Pseudomonas aeruginosa cultures showed the same growth curves demonstrating that the minor impurities in the photolysis solution do not affect the growth behavior of the bacteria. The protonated deuterium-labeled pyocyanin may be used directly in biological experiments, which make the methodology extremely simple and useful for biologists.

Exosome-derived circ-001422 promotes tumor-associated macrophage M2 polarization to accelerate the progression of glioma.

Cytokines, tumor cells, and tumor-associated macrophages play crucial roles in the composition of glioma tissue. Studies have demonstrated that certain cytokines can induce M2 polarization of tumor-associated macrophages and contribute to the progression of glioma. Nonetheless, the intricate molecular interactions among cytokines, glioma cells, and tumor-associated macrophages remain largely unexplored. To investigate this cross-talk, a combination of RNA-sequencing, chromatin immunoprecipitation, immunoprecipitation, exosome isolation, and biological experiments were employed. Treatment with IL-6 significantly increased circ-001422 expression in glioma cells. A poorer prognosis was associated with elevated levels of circ-001422 in glioma tissues. Circ-001422 was transcribed directly by STAT3 through binding to its promoter. Circ-001422 exerted cancer-promoting functions when co-cultured with M2 macrophages. Furthermore, glioma cells were found to transfer circ-001422 to macrophages via an exosomal pathway, promoting M2 polarization. Mechanically, circ-001422 interacted with p300, resulting in STAT3 acetylation, thus promoting nuclear localization and transcriptional activity of STAT3/NF-κB and M2 macrophage polarization. In conclusion, glioma cells released exosomes enriched with circ-001422, which in turn induce M2 macrophage polarization by activating the STAT3/NF-κB pathway, thereby enhancing the aggressive characteristics of glioma cells. Targeting circ-001422 may represent a potential therapeutic approach for glioma.

The Genus Commiphora: An Overview of Its Traditional Uses, Phytochemistry, Pharmacology, and Quality Control

Myrrh is the resinous substance secreted by plants of the genus Commiphora. In traditional Chinese medicine, Ayurvedic medicine, and traditional Arabic medicine, myrrh is regarded as an important medicinal material, widely used in the treatment of trauma, arthritis, hyperlipidemia, and other diseases. This review explores the evolving scientific understanding of the genus Commiphora, covering facets of ethnopharmacology, phytochemistry, pharmacology, artificial cultivation, and quality control. In particular, the chemical constituents and pharmacological research are reviewed. More than 300 types of secondary metabolites have been identified through phytochemical studies of this genus. Guggulsterone is a bioactive steroid isolated mainly from Commiphora mukul. The two isomers, Z- and E-guggulsterone, have shown a wide range of in vitro and in vivo pharmacological effects, including anti-proliferation, antioxidant, anti-inflammatory, and antibacterial. However, the current scientific research on quality control of medicinal materials and identification of original plants is insufficient, which limits the reproducibility and accuracy of biological activity evaluation experiments. Therefore, the establishment of analytical protocols and standardization of extracts is an important step before biological evaluation. At the same time, in order to find more bioactive substances, it is necessary to strengthen the research on the stems, barks, and leaves of this genus. The sources used in this study include PubMed, CNKI, Web of Science, Google Scholar, and other databases, as well as multinational pharmacopoeias, ancient books of traditional medicine, herbal classics, and modern monographs.

Bioinformatics analysis and identification of underlying biomarkers potentially linking allergic rhinitis and autophagy.

Allergic rhinitis (AR) resulted in impairing human health and quality of life seriously. There is currently no definitive remedy for AR. Recent studies have shown that autophagy may regulate airway inflammation. Our comprehension of autophagy and its molecular mechanism in the field of AR condition remains incomplete. Our research endeavors to bridge this knowledge deficit by investigating the correlation between AR and autophagy. The AR-related gene expression profile GSE50223 was screened and downloaded. The "limma" package of R software was utilized to identify differentially expressed genes associated with autophagy. GO, KEGG, and Gene set enrichment analyses were conducted. A PPI network of differentially expressed autophagy-related genes were established and further identified through the CytoHubba algorithm. A receiver operating characteristic curve analysis was employed to evaluate the diagnostic effectiveness of the hub genes and to examine the relationship between autophagy-related genes and AR. Finally, qRT-PCR was carried out to confirm the chosen autophagy-related genes using clinical samples. 21 autophagy-related genes in allergic rhinitis were identified. BECN1, PIK3C3, GABARAPL2, ULK2, and UVRAG were considered as significant differentially expressed autophagy-related genes. However, additional molecular biological experiments will be necessary to elucidate the underlying mechanism connecting autophagy and AR.

High expression of ADAR mediated by OGT promotes chemoresistance in colorectal cancer through the A-to-I editing pathway.

Colorectal cancer (CRC) is a malignant tumor with poor prognosis and adverse therapeutic effect. The study aims to elucidate the contribution of OGT-mediated glycosylation of ADAR to chemoresistance in CRC through its role and regulatory mechanisms. Variations in OGT expression levels and their impact on CRC cell chemoresistance were investigated using gain-of-function and loss-of-function assays. Through a series of molecular biology experiments, we confirmed that ADAR is the downstream target of OGT regulation, emphasizing the role of OGT-mediated glycosylation in stabilizing ADAR. Furthermore, RNA immunoprecipitation (RIP) assays were conducted to examine the effects of ADAR-mediated A-to-I editing on the mRNA stability and translation of genes associated with DNA damage repair. Elevated OGT expression was found to enhance CRC's malignancy and resistance to chemotherapy. OGT's influence leads to the glycosylation of ADAR, thereby increasing its protein levels. ADAR, through its role in A-to-I editing, modulates the mRNA editing of genes implicated in DNA damage repair. This regulation enhances the expression of these genes, improves DNA repair capabilities, and ultimately, fosters chemoresistance in CRC cells. In conclusion, ADAR promotes PARP1 expression under the positive regulation of OGT-mediated O-glycosylation modification to enhance drug resistance in COAD cells. It provides the research basis for overcoming the drug resistance of CRC.

Biomimetic Nano-delivery of Small-Molecule Piceatannol Modulates Tumor Stemness and Suppresses Colorectal Cancer Metastasis via Hippo/YAP1/SOX9 Signaling.

Suppressing tumor metastasis is a crucial strategy for improving survival rates in patients with colorectal cancer (CRC), with cancer stem cells (CSCs) being the primary drivers of metastasis. Current therapeutic approaches targeting CSCs are limited, and their molecular mechanisms remain unclear. To address this challenge, a biomimetic nanoparticle delivery system, CMD-BHQ3-PTL/DOX@RBCM is developed, to deliver the stem cell regulator, piceatannol (PTL). This system used carboxymethyl dextran (CMD) and Black Hole Quencher 3 (BHQ3) to encapsulate PTL and the cytotoxic drug doxorubicin (DOX) within a red blood cell membrane (RBCm), enhancing stability and biocompatibility while allowing gradual drug release under hypoxic conditions. The effects of PTL are investigated on CSCs using molecular biology experiments, plasmid construction, and high-throughput sequencing and elucidated the molecular mechanisms underlying this biomimetic nanoparticle delivery system. The therapeutic efficacy of PTL is validated at the tissue level using subcutaneous and metastatic tumor models in human and murine systems. The results demonstrated that CMD-BHQ3-PTL/DOX@RBCM effectively addressed the challenges of specificity and biocompatibility in vivo, significantly inhibiting CSC-related tumor metastasis. This inhibitory effect is closely associated with the Hippo/YAP1/SOX9 pathway. This study highlights the effectiveness of the pH-responsive biomimetic nanoparticle system CMD-BHQ3-PTL/DOX@RBCm in delivering PTL to tumor sites, with SOX9 and its upstream Hippo/YAP1 pathway playing a critical role in the underlying mechanism.

Natural Products-Based Anticancer Agents: Synthesis and Anticancer Activities of Funtumine Amide/Sulfonamide Derivatives.

Funtumine is a pregnene-type steroidal alkaloid exhibiting moderate anticancer activity. To discover novel natural product-based anticancer drugs, a series of novel funtumine amide/sulfonamide derivatives were papered and identified using spectroscopic techniques. Additionally, the structures of compounds 2j, 3a, and 4k were further confirmed through X-ray diffraction analysis. Biological activity experiments conducted against three cancer cell lines revealed that several of the synthesized compounds demonstrated inhibition activities comparable to or exceeding those of the commercial anticancer agent, 5-Fluorouracil. Especially compound 4i demonstrated a notably strong growth inhibitory effect on HePG2 (IC50=14.89 μM) and HCT116 (IC50=15.67 μM) cell lines, while exhibiting minimal cytotoxicity towards human normal BEAS-2B cells. Preliminary structure-activity relationships (SARs) analysis indicated that the conversion of the carbonyl group at the C-20 position of funtumine to a hydroxyl group could yield more potent compounds.

Prediction of antibody-antigen interaction based on backbone aware with invariant point attention.

Antibodies play a crucial role in disease treatment, leveraging their ability to selectively interact with the specific antigen. However, screening antibody gene sequences for target antigens via biological experiments is extremely time-consuming and labor-intensive. Several computational methods have been developed to predict antibody-antigen interaction while suffering from the lack of characterizing the underlying structure of the antibody. Beneficial from the recent breakthroughs in deep learning for antibody structure prediction, we propose a novel neural network architecture to predict antibody-antigen interaction. We first introduce AbAgIPA: an antibody structure prediction network to obtain the antibody backbone structure, where the structural features of antibodies and antigens are encoded into representation vectors according to the amino acid physicochemical features and Invariant Point Attention (IPA) computation methods. Finally, the antibody-antigen interaction is predicted by global max pooling, feature concatenation, and a fully connected layer. We evaluated our method on antigen diversity and antigen-specific antibody-antigen interaction datasets. Additionally, our model exhibits a commendable level of interpretability, essential for understanding underlying interaction mechanisms. Quantitative experimental results demonstrate that the new neural network architecture significantly outperforms the best sequence-based methods as well as the methods based on residue contact maps and graph convolution networks (GCNs). The source code is freely available on GitHub at https://github.com/gmthu66/AbAgIPA .

Effect of Structure on Osteogenesis of Bone Scaffold: Simulation Analysis Based on Mechanobiology and Animal Experiment Verification

Porous scaffolds, whose mechanical and biological properties are greatly affected by structure, are new treatments for bone defects. Since bone repair is related to biomechanics, analyzing the osteogenesis in scaffolds based on mechanical stimulation may become a more effective method than traditional biological experiments. A tissue regeneration algorithm based on mechanical regulation theory was implemented in this study to evaluate the osteogenesis of classical scaffolds (Gyroid, I-WP, and Diamond). In vivo experiments were used to verify and supplement the simulation results. Different approaches to describing osteogenesis were discussed. Bone formation was more obvious inside the Gyroid scaffold and outside the I-WP scaffold, while the new bone was more sufficient and evenly distributed in the Diamond scaffold. The osteogenesis pattern of the bone scaffold in the simulation analysis was consistent with the results of animal experiments, and the bone volume calculated by the tissue fraction threshold method and the elastic modulus threshold method was very similar to the in vivo experiment. The mechanical responses mediated by structure affect the osteogenesis of bone scaffolds. This study provided and confirmed a simulation analysis method based on mechanical regulation theory, which is more efficient and economical for analyzing tissue healing in bioengineering.

Molecular characterization of human HSPCs with different cell fates in vivo using single-cell transcriptome analysis and lentiviral barcoding technology.

Hematopoietic stem and progenitor cells (HSPCs) possess the potential to produce all types of blood cells throughout their lives. It is well recognized that HSPCs are heterogeneous, which is of great significance for their clinical applications and the treatment of diseases associated with HSPCs. This study presents a novel technology called Single-Cell transcriptome Analysis and Lentiviral Barcoding (SCALeBa) to investigate the molecular mechanisms underlying the heterogeneity of human HSPCs in vivo. The SCALeBa incorporates a transcribed barcoding library and algorithm to analyze the individual cell fates and their gene expression profiles simultaneously. Our findings using SCALeBa reveal that HSPCs subset with stronger stemness highly expressed MYL6B, ATP2A2, MYO19, MDN1, ING3, and so on. The high expression of COA3, RIF1, RAB14, and GOLGA4 may contribute to the pluripotent-lineage differentiation of HSPCs. Moreover, the roles of the representative genes revealed in this study regarding the stemness of HPSCs were confirmed with biological experiments. HSPCs expressing MRPL23 and RBM4 genes may contribute to differentiation bias into myeloid and lymphoid lineage, respectively. In addition, transcription factor (TF) characteristics of lymphoid and myeloid differentiation bias HSPCs subsets were identified and linked to previously identified genes. Furthermore, the stemness, pluripotency, and differentiation-bias genes identified with SCALeBa were verified in another independent HSPCs dataset. Finally, this study proposes using the SCALeBa-generated tracking trajectory to improve the accuracy of pseudo-time analysis results. In summary, our study provides valuable insights for understanding the heterogeneity of human HSPCs in vivo and introduces a novel technology, SCALeBa, which holds promise for broader applications. KEY POINTS: SCALeBa and its algorithm are developed to study the molecular mechanism underlying human HSPCs identity and function. The human HSPCs expressing MYL6B, MYO19, ATP2A2, MDN1, ING3, and PHF20 may have the capability for high stemness. The human HSPCs expressing COA3, RIF1, RAB14, and GOLGA4 may have the capability for pluripotent-lineage differentiation. The human HSPCs expressing MRPL23 and RBM4 genes may have the capability to differentiate into myeloid and lymphoid lineage respectively in vivo. The legitimacy of the identified genes with SCALeBa was validated using biological experiments and a public human HSPCs dataset. SCALeBa improves the accuracy of differentiation trajectories in monocle2-based pseudo-time analysis.

Development and validation of a machine learning model for predicting drug-drug interactions with oral diabetes medications

Diabetes management is often complicated by comorbidities, requiring complex medication regimens that increase the risk of drug-drug interactions (DDIs), potentially compromising treatment outcomes or causing toxicity. Although machine learning (ML) models have made strides in DDI prediction, existing approaches lack specificity for oral diabetes medications and face challenges in interpretability. To address these limitations, we propose a novel ML-based framework utilizing the Simplified Molecular Input Line Entry System (SMILES) to encode structural information of oral diabetes drugs. Using this representation, we developed an XGBoost model, selecting molecular features through LASSO. Our dataset, sourced from DrugBank, included 42 oral diabetes drugs and 1,884 interacting drugs, divided into training, validation, and testing sets. The model identified 606 optimal features, achieving an F1-score of 0.8182. SHAP analysis was employed for feature interpretation, enhancing model transparency and clinical relevance. By predicting adverse DDIs, our model offers a valuable tool for clinical decision-making, aiding safer prescription practices. The 606 critical features provide insights into atomic-level interactions, linking computational predictions with biological experiments. We present a classification model specifically designed for predicting DDIs associated with oral diabetes medications, with an openly accessible web application to support diabetes management in multi-drug regimens and comorbidity settings.

Exploring an indirect quantification strategy for PFOA in rat tissues via efficient degradation and fluorescence spectroscopy

Perfluorooctanoic acid (PFOA) has aroused global attention due to its persistence, biotoxicity and bioaccumulative properties. Monitoring PFOA levels in biological samples could give significant insights into its toxicity mechanism and health risk evaluation. Herein, to explore the distribution of PFOA in biological tissues, an indirect quantitation strategy for PFOA in biological samples was proposed based on fluorescence spectroscopy. F- ion was produced through highly efficient degradation of PFOA in polar aprotic solvent, and then F- ion was detected with highly selective F- ion fluorescent probe, which enabled the indirect quantitative detection of PFOA in biological samples. The sensitivity for PFOA was exhibited with limit of detection of 3.55 μM. The method’s accuracy and precision were validated by spiked biological sample experiment, with recovery rate ranging from 93.2 % to 105.5 % and relative standard deviation below 9.2 %. The content of PFOA was successfully detected in rats livers, kidneys and lungs tissues. Density function theory was employed to explore defluorination pathway, indicating that heating, alkaline and water conditions played a crucial role in the degradation of PFOA to produce F- ion. Thus, this novel strategy is suitable for quantitative analysis of PFOA in biological samples with high selectivity, sensitivity, recovery ratio, and simple sample preparation, which also provides a strategy for evaluating the levels of per- and polyfluoroalkyl substances in biological samples.

Transcriptome-wide association study discovers functional long non-coding RNAs in coronary artery disease

Abstract Genetically regulated long non-coding RNAs (lncRNAs) in coronary artery disease (CAD) have not been investigated. To discover CAD-relevant lncRNAs, we performed the transcriptome-wide association study (TWAS) using a subset genomic data of CARDIoGRAMplusC4D Consortium and transcriptomic data of nine CAD-relevant tissue types from Genotyped Tissue Expression (GTEx) and Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) projects. We identified 20 lncRNAs associated with CAD in a tissue-specific fashion. The eQTL-GWAS colocalization analysis associated 15 lncRNAs with cardiometabolic traits which could bridge the lncRNA to CAD risk. The co-expression analysis identified co-expressed protein-coding genes of 16 lncRNAs and suggested their involved biological pathways. Four antisense lncRNAs from the same locus, CDH13-AS2, CDH13-AS1, CEDORA, and CTD-3253I12.1, not only shared cardiometabolic traits but also exclusively co-expressed with the host gene, CDH13. Our biological experiments using dRfxCas13d-based RNA immunoprecipitation, CRISPR/Cas9 gene knockdown, and dCas9-VP64-based transcriptional activation in endothelial cells, elucidated CDH13-AS2 as a stabilizer of CDH13 mRNA and suggested therapeutic potential of CDH13-AS2 overexpression.

Human coronary blood single-cell sequencing combined with exosome proteomic profiling reveals the molecular mechanism of recurrent in-stent restenosis (R-ISR)

Abstract Background Percutaneous coronary intervention (PCI) is recognized as the core treatment for symptomatic myocardial ischemia and acute coronary syndrome (ACS). However, the complex pathogenesis of recurrent in-stent restenosis (R-ISR) after stent implantation is still insufficiently understood. Purpose This study reports the first single-cell RNA sequencing and proteomic profiling to characterize pathogenesis of R-ISR in humans. Methods To reveal the pathophysiology and molecular mechanism of R-ISR, we performed single-cell RNA sequencing to identify RISR-induced changes in transcriptional landscape in coronary blood mononuclear cell composition. Besides, proteomic profiling of human coronary plasma-derived exosomes was used to further screen different proteins. Transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA) and western blot analysis were performed to identify exosomes. In vitro cell biology experiments were used to validate the discoveries of bioinformatics analysis. Results Compared with normal subjects, the percentage of FCGR3B high monocytes, memory T cells and plasmacytoid dendritic cells (DCs) was increased in R-ISR. Furthermore, we observed a marked increase in the expression of JUN, FOS, CXCL8, S100A8 enriched in the IL-17 signaling pathway that is known to play a crucial role in activating inflammation, mediating immune response, and even maintaining inflammation to chronicity. According to in vitro experiments, the co-cultured system demonstrated that FCGR3B high monocytes isolated from RISR patients activated the expression of inflammatory factors in endothelial cells (ECs), such as IL-1β, IL-6 and TNF-α. Inflammatory activated endothelial cells could release a large amount of exosomes, proteomic profiling of exosomes isolated from ECs observed a significant upregulation of MYLK expression, which could promote proliferation and migration of vascular smooth muscle cells (VSMCs) by activating VEGFR-2 signaling pathway. Conclusions Our study reveals a novel subset of FCGR3B high monocytes in R-ISR patients that could activate ECs inflammation via IL-17 signaling pathway. Activated ECs release exosomes rich in MYLK, which promote proliferation and migration of VSMCs, ultimately leading to repeated restenosis.

BES-Designer: A Web Tool to Design Guide RNAs for Base Editing to Simplify Library.

CRISPR/Cas base editors offer precise conversion of single nucleotides without inducing double-strand breaks. This technology finds extensive applications in gene therapy, gene function analysis, and other domains. However, a crucial challenge lies in selecting the appropriate guide RNAs (gRNAs) for base editing. Although various gRNAs design tools exist, creating a simplified base-editing library with diverse protospacer adjacent motifs (PAM) sequences for gRNAs screening remains a challenge. We present a user-friendly web tool, BES-Designer ( https://bes-designer.aielab.net ), for gRNAs design based on base editors, aimed at streamlining the creation of a base-editing library. BES-Designer incorporates our proposed rules for target sequence simplification, helping researchers narrow down the scope of biological experiments in the lab. It allows users to design target sequences with various PAMs and editing types simultaneously, and prioritize them in the simplified base-editing library. This tool has been experimentally proven to achieve a 30% simplification efficiency on the base-editing-library.

Comprehensive analysis of clinical features, mRNA splicing, and immunological role of REEP5 in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a prevalent malignancy within the digestive system, characterized by high incidence and mortality rates. The biological role of REEP5 in ESCC progression remains poorly understood, despite its associations with various diseases, potentially accelerating tumor malignancy. We retrieved RNA-seq data and clinical information from 179 ESCC patients from the Gene Expression Omnibus (GEO) and 93 patients from The Cancer Genome Atlas (TCGA) databases. Bioinformatics analyses were conducted to explore the biological functions of REEP5 in ESCC, its role in the tumor microenvironment, and its prognostic value. Additionally, utilizing single-cell RNA-seq (scRNA-seq) data from 3 ESCC patients in the GEO database, we performed cluster analyses to investigate cell-specific expression differences of REEP5 between cancerous and adjacent non-cancerous tissues. Molecular biology experiments were also conducted to validate REEP5 expression disparities between tumor and non-tumor tissues. Compared to normal tissues, REEP5 was significantly enriched in ESCC tissues. High REEP5 expression was closely associated with poor prognosis in ESCC patients. Gene Ontology (GO) analysis revealed strong correlations between REEP5 and processes such as mRNA splicing and protein stabilization. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) indicated positive correlations between REEP5 and mRNA spliceosome assembly and disassembly. Pearson correlation analysis demonstrated positive associations between REEP5 and cancer-inhibitory immune checkpoints CTLA-4, TIM-3, and HVEM. Single-cell clustering and CIBERSORT analysis showed that REEP5 expression was closely related to T-cell infiltration in ESCC, with significant enrichment effects observed in CD8+ T-cell infiltration. REEP5 expression is closely correlated with the pathological and molecular pathology of ESCC, potentially playing a crucial role in Mast cell or T-cell-mediated immune responses in ESCC. Therefore, REEP5 holds promise as a novel therapeutic target for ESCC.

Synthesis of a Small Library of Glycoderivative Putative Ligands of SGLT1 and Preliminary Biological Evaluation.

Sodium-glucose co-transporter 1 (SGLT1) is primarily expressed on the membrane of enterocytes, a type of epithelial cell found in the intestines, where it mediates the unidirectional absorption of glucose and galactose. Beyond its well-established role in nutrient absorption, SGLT1 also plays a protective role in maintaining the integrity of the intestinal barrier. Specifically, the natural ligand of SGLT1 (d-glucose) and a synthetic C-glucoside developed by our group can induce a protective anti-inflammatory effect on the intestinal epithelium. In this paper, we report the creation of a small library of C-glycoside, putative ligands for SGLT1, to gain further insights into its unclear mechanism of action. Preliminary biological experiments performed on an in vitro model of doxorubicin-induced mucositis, a severe intestinal inflammatory condition, indicate that the aromatic moiety present in all the compounds of the library is crucial for biological activity, while the sugar component appears to have less influence. These findings will be exploited to develop new, more potent anti-inflammatory compounds and to better understand and rationalize the protective mechanism of action.

DOT1L protects against podocyte injury in diabetic kidney disease through phospholipase C-like 1

BackgroundPodocyte injury causes proteinuria and accelerates glomerular sclerosis during diabetic kidney disease (DKD). Disruptor of telomeric silencing 1-like (DOT1L), an evolutionarily conserved histone methyltransferase, has been reported in preventing kidney fibrosis in chronic kidney disease models. However, whether DOT1L exerts beneficial effects in diabetes induced podocyte injury and the underlying molecular mechanisms need further exploration.MethodsThe expression of DOT1L was confirmed by Western blotting in MPC-5 cells and cortex of kidney from db/db mice, as well as immunofluorescence staining in human renal biopsy samples. The effect of DOT1L on podocyte injury was obtained using MPC-5 cells and db/db mice. The potential target genes regulated by DOT1L was measured by RNA-sequencing. Then, a series of molecular biological experiments was performed to investigate the regulation of PLCL1 by DOT1L in MCP-5 cells and db/db mice. Lipid accumulation was assessed by UPLC-MS/MS analysis and Oil Red O staining.ResultsDOT1L expression was significantly declined in high glucose (HG)-treated MPC-5 cells, podocyte regions of kidney tissues from db/db mice and human renal biopsy samples. Subsequent investigations revealed that upregulation of DOT1L ameliorated HG-induced cell apoptosis in MPC-5 cells as well as primary podocytes. Furthermore, podocyte-specific DOT1L overexpression inhibited diabetic podocyte injury in db/db mice. Mechanistically, we revealed that DOT1L upregulated phospholipase C-like 1 (PLCL1) expression by mediating H3K79me2 at its promoter and PLCL1 silencing suppressed the protective role of DOT1L on podocyte injury. Moreover, DOT1L improved diabetes induced abnormal fatty acid metabolism in podocytes and PLCL1 knockdown reversed its protective effects.ConclusionsTaken together, our results indicate that DOT1L protects podocyte injury via PLCL1-mediated fatty acid metabolism and provides new insights into the therapeutic target of DKD.