Qi Lang formula relieves constipation via targeting SCF/c-kit signaling pathway: An integrated study of network pharmacology and experimental validation.

Background: Constipation is one of the chronic gastrointestinal functional diseases that affects the quality of life. While Qi Lang Formula (QLF) has demonstrated effectiveness in alleviating constipation symptoms, its precise mechanism remains elusive. Methods: QLF was analyzed using UPLC-MS/MS. Targets for QLF were collected from SwissADME, Herb, ITCM databases, and constipation-related targets from scRNA-seq and Genecards databases. Overlapping targets suggested potential QLF therapy targets for constipation. Enrichment analysis used the KOBAS database. A "drug-ingredient-target" network was constructed with Cytoscape, and AutoDock verified active ingredient binding. H&E staining assessed colonic mucosa changes, TEM examined ICC structural changes. ELISA measured neurotransmitter levels, and Western blot verified QLF's effect on target proteins. ICC proliferation was observed through immunofluorescence. Results: We identified 89 targets of QLF associated with ICC-related constipation, with c-Kit emerging as the pivotal target. Molecular docking studies revealed that Atractylenolide Ⅲ, Apigenin, Formononetin, Isorhamnetin, Naringenin, and Ononin exhibited strong binding affinities for the c-Kit structural domain. QLF significantly enhanced first stool passage time, fecal frequency, fecal moisture content, and intestinal propulsion rate. Further analysis unveiled that QLF not only restored neurotransmitter levels but also mitigated colon muscular fiber ruptures. ICC ultrastructure exhibited partial recovery, while Western blot confirmed upregulated c-Kit expression and downstream targets. Immunofluorescence results indicated ICC proliferation post QLF treatment in rat colon. Conclusion: Our findings suggest that QLF may promote ICC proliferation by targeting SCF/c-Kit and its downstream signaling pathway, thereby regulating intestinal motility.

Ursolic acid targets secreted phosphoprotein 1 to regulate Th17 cells against non-alcoholic fatty liver disease.

Background/Aims: Non-alcoholic fatty liver disease (NAFLD) has become an increasingly important health challenge, with a substantial rise linked to changing lifestyles and global obesity. Ursolic acid, a natural pentacyclic triterpenoid, has been explored for its potential therapeutic effects. Given its multifunctional bioactive properties, this research further revealed the pharmacological mechanisms of ursolic acid on NAFLD. Methods: Drug target chips and bioinformatics analysis were combined in this study to explore the potential therapeutic effects of ursolic acid on NAFLD. Molecular docking simulations, surface plasmon resonance analyses, pull-down experiments, and co-immunoprecipitation assays were used to verify the direct interactions. Gene knockdown mice were generated, and high-fat diets were used to validate drug efficacy. Furthermore, initial CD4+ T cells were isolated and stimulated to demonstrate our findings. Results: In this study, the multifunctional extracellular matrix phosphorylated glycoprotein secreted phosphoprotein 1 (SPP1) was investigated, highlighting its capability to induce Th17 cell differentiation, amplifying inflammatory cascades, and subsequently promoting the evolution of NAFLD. In addition, this study revealed that in addition to the canonical TGF-ß/IL-6 cytokine pathway, SPP1 can directly interact with ITGB1 and CD44, orchestrating Th17 cell differentiation via their joint downstream ERK signaling pathway. Remarkably, ursolic acid intervention notably suppressed the protein activity of SPP1, suggesting a promising avenue for ameliorating the immunoinflammatory trajectory in NAFLD progression. Conclusions: Ursolic acid could improve immune inflammation in NAFLD by modulating SPP1-mediated Th17 cell differentiation via the ERK signaling pathway, which is orchestrated jointly by ITGB1 and CD44, emerging as a linchpin in this molecular cascade.

Research progress, challenges and perspectives of phospholipids metabolism in the LXR­LPCAT3 signaling pathway and its relation to NAFLD (Review).

Phospholipids (PLs) are principle constituents of biofilms, with their fatty acyl chain composition significantly impacting the biophysical properties of membranes, thereby influencing biological processes. Recent studies have elucidated that fatty acyl chains, under the enzymatic action of lyso­phosphatidyl­choline acyltransferases (LPCATs), expedite incorporation into the sn­2 site of phosphatidyl­choline (PC), profoundly affecting pathophysiology. Accumulating evidence suggests that alterations in LPCAT activity are implicated in various diseases, including non­alcoholic fatty liver disease (NAFLD), hepatitis C, atherosclerosis and cancer. Specifically, LPCAT3 is instrumental in maintaining systemic lipid homeostasis through its roles in hepatic lipogenesis, intestinal lipid absorption and lipoprotein secretion. The liver X receptor (LXR), pivotal in lipid homeostasis, modulates cholesterol, fatty acid (FA) and PL metabolism. LXR's capacity to modify PL composition in response to cellular sterol fluctuations is a vital mechanism for protecting biofilms against lipid stress. Concurrently, LXR activation enhances LPCAT3 expression on cell membranes and elevates polyunsaturated PL levels. This activation can ameliorate saturated free FA effects in vitro or endoplasmic reticulum stress in vivo due to lipid accumulation in hepatic cells. Pharmacological interventions targeting LXR, LPCAT and membrane PL components could offer novel therapeutic directions for NAFLD management. The present review primarily focused on recent advancements in understanding the LPCAT3 signaling pathway's role in lipid metabolism related to NAFLD, aiming to identify new treatment targets for the disease.

Causal effects of gut microbiome on autoimmune liver disease: a two-sample Mendelian randomization study.

BACKGROUND: Epidemiological studies have indicated a potential link between the gut microbiome and autoimmune liver disease (AILD) such as autoimmune hepatitis (AIH), primary biliary cholangitis (PBC), and primary sclerosing cholangitis (PSC). The relationship between the gut microbiome and autoimmune liver disease is still uncertain due to confounding variables. In our study, we aim to shed light on this relationship by employing a two-sample Mendelian randomization approach. METHODS: We conducted a two-sample Mendelian randomization (MR) study using the R package "TwoSampleMR". The exposure data consisted of genetic variants associated with 194 bacterial traits obtained from the MiBioGen consortium. Summary statistics for AILD were obtained from the GWAS Catalog website. Furthermore, a series of sensitivity analyses were performed to validate the initial MR results. RESULTS: There were two, four and three bacteria traits associated with an increased risk of AIH. PBC, and PSC respectively. In contrast, there were five, two and five bacteria traits associated with a decreased risk for AIH, PBC and PSC. Notably, the genus_Clostridium_innocuum_group showed a negative association with AIH (OR = 0.67, 95% CI: 0.49-0.93), and the genus_Actinomyces was found to be genetically associated with a decreased risk of PSC (OR = 0.62, 95% CI: 0.42-0.90). CONCLUSIONS: Our study identified the causal impact of specific bacterial features on the risk of AILD subtypes. Particularly, the genus_Clostridium_innocuum_group and the genus_Actinomyces demonstrated significant protective effects against AIH and PSC respectively. These findings provide further support for the potential use of targeted probiotics in the management of AILD.

A novel enterocyte-related 4-gene signature for predicting prognosis in colon adenocarcinoma.

Background: Colon adenocarcinoma (COAD) is a fatal disease, and its cases are constantly increasing worldwide. Further, the therapeutic and management strategies for patients with COAD are still unsatisfactory due to the lack of accurate patient classification and prognostic models. Therefore, our study aims to identify prognostic markers in patients with COAD and construct a cell subtype-specific prognostic model with high accuracy and robustness. Methods: Single-cell transcriptomic data of six samples were retrieved from the Gene expression omnibus (GEO) database. The cluster annotation and cell-cell communication analysis identified enterocytes as a key player mediating signal communication networks. A four-gene signature prognostic model was constructed based on the enterocyte-related differentially expressed genes (ERDEGs) in patients with COAD of the Cancer Genome Atlas cohort. The prognostic model was validated on three external validation cohorts from the GEO database. The correlation between immune cell infiltration, immunotherapy response, drug sensitivity, and the four-gene signature prognostic model was investigated. Finally, immunohistochemistry (IHC) was performed to determine the expression of the four genes. Results: We found that the proportion of epithelial cells was obviously large in COAD samples. Further analysis of epithelial cells showed that the activity of the enterocytes was highest in the cell-cell communication network. Based on enterocyte data, 30 ERDEGs were identified and a 4-gene prognostic model including CPM, CLCA4, ELOVL6, and ATP2A3 was developed and validated. The risk score derived from this model was considered as an independent variable factor to predict overall survival. The patients were divided into high- and low-risk groups based on the median riskscore value. The correlation between immune cell infiltration, immunotherapy response, immune status, clinical characteristics, drug sensitivity, and risk score was analyzed. IHC confirmed the expression of signature genes in tissues from normal individuals, patients with polyps, and COAD. Conclusion: In this study, we constructed and validated a novel four-gene signature prognostic model, which could effectively predict the response to immunotherapy and overall survival in patients with COAD. More importantly, this model provides useful insight into the management of colon cancer patients and aids in designing personalized therapy.

Integration of Bulk and Single-Cell RNA-Seq Data to Construct a Prognostic Model of Membrane Tension-Related Genes for Colon Cancer.

BACKGROUND: The plasma membrane provides a highly dynamic barrier for cancer cells to interact with their surrounding microenvironment. Membrane tension, a pivotal physical property of the plasma membrane, has attracted widespread attention since it plays a role in the progression of various cancers. This study aimed to identify a prognostic signature in colon cancer from membrane tension-related genes (MTRGs) and explore its implications for the disease. METHODS: Bulk RNA-seq data were obtained from The Cancer Genome Atlas (TCGA) database, and then applied to the differentially expressed gene analysis. By implementing a univariate Cox regression and a LASSO-Cox regression, we developed a prognostic model based on four MTRGs. The prognostic efficacy of this model was evaluated in combination with a Kaplan-Meier analysis and receiver operating characteristic (ROC) curve analysis. Moreover, the relationships between the signature and immune cell infiltration, immune status, and somatic mutation were further explored. Lastly, by utilizing single-cell RNA-seq data, cell type annotation, pseudo-time analysis, drug sensitivity, and molecular docking were implemented. RESULTS: We constructed a 4-MTRG signature. The risk score derived from the model was further validated as an independent variable for survival prediction. Two risk groups were divided based on the risk score calculated by the 4-MTRG signature. In addition, we observed a significant difference in immune cell infiltration, such as subsets of CD4 T cells and macrophages, between the high- and low-risk groups. Moreover, in the pseudo-time analysis, TIMP1 was found to be more highly expressed with the progression of time. Finally, three small molecule drugs, elesclomol, shikonin, and bryostatin-1, exhibited a binding potential to TIMP-1. CONCLUSIONS: The novel 4-MTRG signature is a promising biomarker in predicting clinical outcomes for colon cancer patients, and TIMP1, a member of the signature, may be a sensitive regulator of the progression of colon cancer.