Methyl jasmonate induced tolerance effect of Pinus koraiensis to Bursaphelenchus xylophilus.

BACKGROUND: Methyl jasmonate (MeJA) can affect the balance of hormones and regulate the disease resistance of plants. Exploring the application and mechanism of MeJA in inducing the tolerance of Pinus koraiensis to pine wood nematode (PWN) infection is of great significance for developing new strategies for pine wilt disease control. RESULTS: Different concentrations (0.1, 1, 5 and 10 mm) of MeJA treatment groups showed differences in relative tolerance index and relative anti-nematode index of P. koraiensis seedlings to PWN infection. The treatment of 5 mm MeJA solution induced the best tolerance effect, followed by the 1 mm MeJA solution. Transcriptome analysis indicated that many plant defense-related genes upregulated after treatment with 1, 5 and 10 mm MeJA solutions. Among them, genes such as jasmonate ZIM domain-containing protein, phenylalanine ammonia-lyase and peroxidase also continuously upregulated after PWN infection. Metabolome analysis indicated that jasmonic acid (JA) was significantly increased at 7 days postinoculation with PWN, and after treatment with both 1 and 5 mm MeJA solutions. Integrated analysis of transcriptome and metabolome indicated that differences in JA accumulation might lead to ubiquitin-mediated proteolysis, and expression changes in trans-caffeic acid and trans-cinnamic acid-related genes, leading to the abundance differences of these two metabolisms and the formation of multiple lignin and glucosides. CONCLUSIONS: MeJA treatment could activate the expression of defense-related genes that correlated with JA, regulate the abundance of defense-related secondary metabolites, and improve the tolerance of P. koraiensis seedlings to PWN infection. © 2024 Society of Chemical Industry.

Response analysis of Pinus sibirica to pine wood nematode infection through transcriptomics and metabolomics study.

Pinus sibirica is primarily distributed in Siberia. Owing to its excellent cold resistance and development potential, it has become an important introduced tree species in the Greater Xing'an area of China. Pine wilt disease, triggered by the pine wood nematode (PWN, Bursaphelenchus xylophilus), constitutes a profoundly critical affliction within forest ecosystems. Its incidence has extended to the northeastern region of China in recent years. To explore the potential host status of P. sibirica in the Greater Xing'an area for PWN and to elucidate the responses following inoculation, artificial inoculation, transcriptomics, and metabolomics methods were used. In the artificial inoculation experiments, quantitative analysis of nematode populations within the trees demonstrated that PWN exhibited normal growth and reproductive capabilities within P. sibirica. Subsequently, transcriptome and metabolome sequencing were conducted at four time points before disease onset (3-, 5-, 7-, and 9-days post inoculation). Gene trend analysis and differentially expressed gene screening were employed and the results indicated that genes associated with the flavonoid biosynthesis pathway exhibited predominant enrichment among the up-regulated genes. Metabolome analysis showed that the abundance of flavonoid-related metabolites in P. sibirica increased after inoculation with PWN. Integrated analysis of transcriptome and metabolome revealed that after PWN inoculation in P. sibirica, two chalcone synthase (chs) genes and a chalcone isomerase (chi) gene were significantly upregulated, and the upregulation should accumulate naringenin, pinocembrin, and apigenin to help P. sibirica resist infection of PWN. The results suggested that flavonoid biosynthesis pathway continued to respond after P. sibirica was infected with PWN and played an important role in the interaction between P. sibirica and PWN.

Disrupted Tuzzerella abundance and impaired L-glutamine levels induce Treg accumulation in ovarian endometriosis: a comprehensive multi-omics analysis.

INTRODUCTION: The microbial community plays a crucial role in the pathological microenvironment. However, the structure of the microbial community within endometriotic lesions and its impact on the microenvironment is still limited. METHODS: All 55 tissue samples, including ovarian ectopic (OEMs) and normal (NE) endometrium, were subjected to 16S rRNA sequencing, metabolomic and proteomic analysis. RESULTS: We found the abundance of Tuzzerella is significantly lower in OEMs compared to NE tissue (p < 0.01). We selected samples from these two groups that exhibited the most pronounced difference in Tuzzerella abundance for further metabolomic and proteomic analysis. Our findings indicated that endometriotic lesions were associated with a decrease in L-Glutamine levels. However, proteomic analysis revealed a significant upregulation of proteins related to the complement pathway, including C3, C7, C1S, CLU, and A2M. Subsequent metabolic and protein correlation predictions demonstrated a negative regulation between L-Glutamine and C7. In vitro experiments further confirmed that high concentrations of Glutamine significantly inhibit C7 protein expression. Additionally, immune cell infiltration analysis, multiplex immunofluorescence, and multifactorial testing demonstrated a positive correlation between C7 expression and the infiltration of regulatory T cells (Tregs) in ectopic lesions, while L-Glutamine was found to negatively regulate the expression of chemotactic factors for Tregs. CONCLUSION: In this study, we found a clear multi-omics pathway alteration, "Tuzzerella (microbe)-L-Glutamine (metabolite)-C7 (protein)," which affects the infiltration of Tregs in endometriotic lesions. Our findings provide insights into endometriosis classification and personalized treatment strategies based on microbial structures.

Effect of Mifepristone vs Placebo for Treatment of Adenomyosis With Pain Symptoms: A Randomized Clinical Trial.

Importance: Adenomyosis is a common chronic gynecological disorder, and its treatment is an unmet need. New therapies need to be developed. Mifepristone is being tested for adenomyosis treatment. Objective: To determine whether mifepristone is effective and safe for adenomyosis treatment. Design, Setting, and Participants: This multicenter, placebo-controlled, double-blind randomized clinical trial was conducted in 10 hospitals in China. In total, 134 patients with adenomyosis pain symptoms were enrolled. Trial enrollment began in May 2018 and was completed in April 2019, and analyses were conducted from October 2019 to February 2020. Interventions: Participants were randomized 1:1 to receive mifepristone 10 mg or placebo orally once a day for 12 weeks. Main Outcomes and Measures: The primary end point was the change in adenomyosis-associated dysmenorrhea intensity, evaluated by the visual analog scale (VAS) after 12 weeks of treatment. Secondary end points included the change in menstrual blood loss, increased level of hemoglobin in patients with anemia, CA125 level, platelet count, and uterine volume after 12 weeks of treatment. Safety was assessed according to adverse events, vital signs, gynecological examinations, and laboratory evaluations. Results: In total, 134 patients with adenomyosis and dysmenorrhea were randomly assigned, and 126 patients were included in the efficacy analysis, including 61 patients (mean [SD] age, 40.2 [4.6] years) randomized to receive mifepristone and 65 patients (mean [SD] age, 41.7 [5.0] years) randomized to received the placebo. The characteristics of the included patients at baseline were similar between groups. The mean (SD) change in VAS score was -6.63 (1.92) in the mifepristone group and -0.95 (1.75) in the placebo group (P < .001). The total remission rates for dysmenorrhea in the mifepristone group were significantly better than those in the placebo group (effective remission: 56 patients [91.8%] vs 15 patients [23.1%]; complete remission: 54 patients [88.5%] vs 4 patients [6.2%]). All the secondary end points showed significant improvements after mifepristone treatment for menstrual blood loss, hemoglobin (mean [SD] change from baseline: 2.13 [1.38] g/dL vs 0.48 [0.97] g/dL; P < .001), CA125 (mean [SD] change from baseline: -62.23 [76.99] U/mL vs 26.89 [118.70] U/mL; P < .001), platelet count (mean [SD] change from baseline: -28.87 [54.30]×103/µL vs 2.06 [41.78]×103/µL; P < .001), and uterine volume (mean [SD] change from baseline: -29.32 [39.34] cm3 vs 18.39 [66.46] cm3; P < .001). Safety analysis revealed no significant difference between groups, and no serious adverse events were reported. Conclusions and Relevance: This randomized clinical trial showed that mifepristone could be a new option for treating patients with adenomyosis, based on its efficacy and acceptable tolerability. Trial Registration: ClinicalTrials.gov Identifier: NCT03520439.

Integrated genomic analysis defines molecular subgroups in dilated cardiomyopathy and identifies novel biomarkers based on machine learning methods.

Aim: As the most common cardiomyopathy, dilated cardiomyopathy (DCM) often leads to progressive heart failure and sudden cardiac death. This study was designed to investigate the molecular subgroups of DCM. Methods: Three datasets of DCM were downloaded from GEO database (GSE17800, GSE79962 and GSE3585). After log2-transformation and background correction with "limma" package in R software, the three datasets were merged into a metadata cohort. The consensus clustering was conducted by the "Consensus Cluster Plus" package to uncover the molecular subgroups of DCM. Moreover, clinical characteristics of different molecular subgroups were compared in detail. We also adopted Weighted gene co-expression network analysis (WGCNA) analysis based on subgroup-specific signatures of gene expression profiles to further explore the specific gene modules of each molecular subgroup and its biological function. Two machine learning methods of LASSO regression algorithm and SVM-RFE algorithm was used to screen out the genetic biomarkers, of which the discriminative ability of molecular subgroups was evaluated by receiver operating characteristic (ROC) curve. Results: Based on the gene expression profiles, heart tissue samples from patients with DCM were clustered into three molecular subgroups. No statistical difference was found in age, body mass index (BMI) and left ventricular internal diameter at end-diastole (LVIDD) among three molecular subgroups. However, the results of left ventricular ejection fraction (LVEF) statistics showed that patients from subgroup 2 had a worse condition than the other group. We found that some of the gene modules (pink, black and grey) in WGCNA analysis were significantly related to cardiac function, and each molecular subgroup had its specific gene modules functions in modulating occurrence and progression of DCM. LASSO regression algorithm and SVM-RFE algorithm was used to further screen out genetic biomarkers of molecular subgroup 2, including TCEAL4, ISG15, RWDD1, ALG5, MRPL20, JTB and LITAF. The results of ROC curves showed that all of the genetic biomarkers had favorable discriminative effectiveness. Conclusion: Patients from different molecular subgroups have their unique gene expression patterns and different clinical characteristics. More personalized treatment under the guidance of gene expression patterns should be realized.