Metabolic Pathway Analysis Research Articles

Transcriptomics-driven metabolic pathway analysis reveals similar alterations in lipid metabolism in mouse MASH model and human

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) is a prevalent chronic liver disease worldwide, and can rapidly progress to metabolic dysfunction-associated steatohepatitis (MASH). Accurate preclinical models and methodologies are needed to understand underlying metabolic mechanisms and develop treatment strategies. Through meta-analysis of currently proposed mouse models, we hypothesized that a diet- and chemical-induced MASH model closely resembles the observed lipid metabolism alterations in humans.MethodsWe developed transcriptomics-driven metabolic pathway analysis (TDMPA), a method to aid in the evaluation of metabolic resemblance. TDMPA uses genome-scale metabolic models to calculate enzymatic reaction perturbations from gene expression data. We performed TDMPA to score and compare metabolic pathway alterations in MASH mouse models to human MASH signatures. We used an already-established WD+CCl4-induced MASH model and performed functional assays and lipidomics to confirm TDMPA findings.ResultsBoth human MASH and mouse models exhibit numerous altered metabolic pathways, including triglyceride biosynthesis, fatty acid beta-oxidation, bile acid biosynthesis, cholesterol metabolism, and oxidative phosphorylation. We confirm a significant reduction in mitochondrial functions and bioenergetics, as well as in acylcarnitines for the mouse model. We identify a wide range of lipid species within the most perturbed pathways predicted by TDMPA. Triglycerides, phospholipids, and bile acids are increased significantly in mouse MASH liver, confirming our initial observations.ConclusionsWe introduce TDMPA, a methodology for evaluating metabolic pathway alterations in metabolic disorders. By comparing metabolic signatures that typify human MASH, we show a good metabolic resemblance of the WD+CCl4 mouse model. Our presented approach provides a valuable tool for defining metabolic space to aid experimental design for assessing metabolism.

A human milk oligosaccharide prevents intestinal inflammation in adulthood via modulating gut microbial metabolism.

Observational evidence suggests that human milk oligosaccharides (HMOs) promote the growth of commensal bacteria in early life and adulthood. However, the mechanisms by which HMOs benefit health through modulation of gut microbial homeostasis remain largely unknown. 2'-fucosyllactose (2'-FL) is the most abundant oligosaccharide in human milk and contributes to the essential health benefits associated with human milk consumption. Here, we investigated how 2'-FL prevents colitis in adulthood through its effects on the gut microbial community. We found that the gut microbiota from adult mice that consumed 2'-FL exhibited an increase in abundance of several health-associated genera, including Bifidobacterium and Lactobacillus. The 2'-FL-modulated gut microbial community exerted preventive effects on colitis in adult mice. By using Bifidobacterium infantis as a 2'-FL-consuming bacterial model, exploratory metabolomics revealed novel 2'-FL-enriched secretory metabolites by Bifidobacterium infantis, including pantothenol. Importantly, pantothenate significantly protected the intestinal barrier against oxidative stress and mitigated colitis in adult mice. Furthermore, microbial metabolic pathway analysis identified 26 dysregulated metabolic pathways in fecal microbiota from patients with ulcerative colitis, which were significantly regulated by 2'-FL treatment in adult mice, indicating that 2'-FL has the potential to rectify dysregulated microbial metabolism in colitis. These findings support the contribution of the 2'-FL-shaped gut microbial community and bacterial metabolite production to the protection of intestinal integrity and prevention of intestinal inflammation in adulthood.IMPORTANCEAt present, neither basic research nor clinical studies have revealed the exact biological functions or mechanisms of action of individual oligosaccharides during development or in adulthood. Thus, it remains largely unknown whether human milk oligosaccharides could serve as effective therapeutics for gastrointestinal-related diseases. Results from the present study uncover 2'-FL-driven alterations in bacterial metabolism and identify novel B. infantis-secreted metabolites following the consumption of 2'-FL, including pantothenol. This work further demonstrates a previously unrecognized role of pantothenate in significantly protecting the intestinal barrier against oxidative stress and mitigating colitis in adult mice. Remarkably, 2'-FL-enhanced bacterial metabolic pathways are found to be dysregulated in the fecal microbiota of ulcerative colitis patients. These novel metabolic pathways underlying the bioactivities of 2'-FL may lay a foundation for applying individual oligosaccharides for prophylactic intervention for diseases associated with impaired intestinal homeostasis.

Cutaneous Melanoma and 486 Human Blood Metabolites: A Mendelian Randomization Study.

Cutaneous melanoma (CM) has long been recognized as a lethal form of cancer. Despite persistent research endeavors, the precise underlying pathological mechanisms remain largely unclear, and the optimal treatment for this patient population remains undetermined. This study aims to examine the causal associations between CM and 486 metabolites. A two-sample Mendelian randomization (MR) analysis was conducted to ascertain the causal relationship between blood metabolites and CM. The causality analysis involved the inverse variance weighted (IVW) method, followed by the MR-Egger and weighted median (WM) methods. To increase the robustness of our findings, several sensitivity analyses, including the MR-Egger intercept, Cochran's Q test, and MR-pleiotropy residual sum and outlier (MR-PRESSO), were performed. The robustness of our results was further validated in independent outcome samples followed by a meta-analysis. Additionally, a metabolic pathway analysis was carried out. The two-sample MR analysis yielded a total of 27 metabolites as potential causal metabolites. After incorporating the outcomes of the sensitivity analyses, seven causal metabolites remained. Palmitoylcarnitine (OR 0.9903 95% CI 0.9848-0.9958, p = 0.0005) emerged as the sole metabolite with a significant causality after Bonferroni correction. Furthermore, the reverse MR analysis provided no evidence of reverse causality from CM to the identified metabolites. This study suggested a causal relationship between seven human blood metabolites and the development of CM, thereby offering novel insights into the underlying mechanisms involved. This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Abstract PR005: Patients with endometrial cancer and benign gynecologic conditions exhibit unique vaginal and rectal microbiomes

Abstract Endometrial cancer (EC) rates are increasing in the United States, with 66,200 women diagnosed this year. The microbiome may be a key target for understanding EC etiology and progression and hold vital information for prevention strategies. With the largest cross-sectional cohort to date, a rich set of patient-related meta-data, and samples from multiple mucosal sites, we explored the gut-vagina axis in EC compared to benign gynecologic conditions. Vaginal and rectal swabs were collected from 192 patients diagnosed with benign conditions (n=108), hyperplasia (n= 18), and EC (n= 66). 16S rRNA amplicon sequencing was conducted on DNA samples, and data analysis was performed with QIIME 2 and R software. The clinical and demographic analysis identified risk factors associated with EC, such as BMI and menopausal status, that differed between disease groups. Global microbial analyses identified a distinct microbial composition between benign and EC, as well as higher diversity in rectal samples and lower diversity in vaginal samples in benign patients compared to cancer patients. Differential abundance analysis, even after adjustment for known risk factors, revealed unique microbial features such as depletion of Lactobacillus and increase of Anaerococcus, Porphyromonas, and Peptoniphilus in vaginal samples when EC is compared to benign conditions. While Rectal samples indicated a depletion of Peptoniphilus and Prevotella and an increase in Buttiaxella in EC compared to benign conditions. Additionally, community networks were different between cancer patients compared to benign, where taxa in Peptoniphilaceae had the most microbial network connections in EC compared to benign conditions. Notably, putative metabolic pathway analysis identified dysregulation of amino acid metabolism, complex carbohydrate metabolism, and hormone metabolism between cancer patients and benign, which provide key insight into the potential pathophysiological mechanisms employed by the microbiome in EC. This study provides key findings on unique singular and community microbial signatures that may directly affect EC development and be important targets for prevention. Citation Format: Nicole R. Jimenez, Chloe Herman, Pawel Laniewski, Emily K. Cope, Jamal Mourad, Nichole Mahnert, Dana M. Chase, J. G. Caporaso, Melissa M. Herbst-Kralovetz. Patients with endometrial cancer and benign gynecologic conditions exhibit unique vaginal and rectal microbiomes [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr PR005.

Transcriptomic analysis of nitrogen metabolism pathways in Klebsiella aerogenes under nitrogen-rich conditions.

The acceleration of the nitrogen cycle and the nitrogen excess observed in some coastal waters has increased interest into understanding the biochemical and molecular basis of nitrogen metabolism in various microorganisms. To investigate nitrogen metabolism of a novel heterotrophic nitrification and aerobic denitrification bacterium Klebsiella aerogenes strain (B23) under nitrogen-rich conditions, we conducted physiological and transcriptomic high-throughput sequencing analyses on strain B23 cultured on potassium nitrate-free or potassium nitrate-rich media. Overall, K. aerogenes B23 assimilated 82.47% of the nitrate present into cellular nitrogen. Further, 1,195 differentially expressed genes were observed between K. aerogenes B23 cultured on potassium nitrate-free media and those cultured on potassium nitrate-rich media. Gene annotation and metabolic pathway analysis of the transcriptome were performed using a series of bioinformatics tools, including Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Non-Redundant Protein Database annotation. Accordingly, the nitrogen metabolism pathway of K. aerogenes B23 was analyzed; overall, 39 genes were determined to be involved in this pathway. Differential expression analysis of the genes involved in the nitrogen metabolism pathway demonstrated that, compared to the control, FNR, NarK/14945, fdx, gshA, proB, proA, gapA, argH, artQ, artJ, artM, ArgR, GAT1, prmB, pyrG, glnS, and Ca1 were significantly upregulated in the nitrogen-treated K. aerogenes B23; these genes have been established to be involved in the regulation of nitrate, arginine, glutamate, and ammonia assimilation. Further, norV, norR, and narI were also upregulated in nitrogen-treated K. aerogenes B23; these genes are involved in the regulation of NO metabolism. These differential expression results are important for understanding the regulation process of key nitrogen metabolism enzyme genes in K. aerogenes B23. Therefore, this study establishes a solid foundation for further research into the expression regulation patterns of nitrogen metabolism-associated genes in K. aerogenes B23 under nitrogen-rich conditions; moreover, this research provides essential insight into how K. aerogenes B23 utilizes nutritional elements.

Plasma metabolomic differences in early-onset compared to average-onset colorectal cancer

Deleterious effects of environmental exposures may contribute to the rising incidence of early-onset colorectal cancer (eoCRC). We assessed the metabolomic differences between patients with eoCRC, average-onset CRC (aoCRC), and non-CRC controls, to understand pathogenic mechanisms. Patients with stage I–IV CRC and non-CRC controls were categorized based on age ≤ 50 years (eoCRC or young non-CRC controls) or ≥ 60 years (aoCRC or older non-CRC controls). Differential metabolite abundance and metabolic pathway analyses were performed on plasma samples. Multivariate Cox proportional hazards modeling was used for survival analyses. All P values were adjusted for multiple testing (false discovery rate, FDR P < 0.15 considered significant). The study population comprised 170 patients with CRC (66 eoCRC and 104 aoCRC) and 49 non-CRC controls (34 young and 15 older). Citrate was differentially abundant in aoCRC vs. eoCRC in adjusted analysis (Odds Ratio = 21.8, FDR P = 0.04). Metabolic pathways altered in patients with aoCRC versus eoCRC included arginine biosynthesis, FDR P = 0.02; glyoxylate and dicarboxylate metabolism, FDR P = 0.005; citrate cycle, FDR P = 0.04; alanine, aspartate, and glutamate metabolism, FDR P = 0.01; glycine, serine, and threonine metabolism, FDR P = 0.14; and amino-acid t-RNA biosynthesis, FDR P = 0.01. 4-hydroxyhippuric acid was significantly associated with overall survival in all patients with CRC (Hazards ratio, HR = 0.4, 95% CI 0.3–0.7, FDR P = 0.05). We identified several unique metabolic alterations, particularly the significant differential abundance of citrate in aoCRC versus eoCRC. Arginine biosynthesis was the most enriched by the differentially altered metabolites. The findings hold promise in developing strategies for early detection and novel therapies.

Effects of Microplastics on Endophytes in Different Niches of Chinese Flowering Cabbage (Brassica campestris).

Microplastics (MPs) are present in soil as emerging contaminants and pose a threat to soil as well as plants. Here, the effects of MPs on Chinese flowering cabbage from a microbiology perspective were explored. MP size and concentration significantly affected endophytic communities of plant root and petiole (p < 0.05). Under MP treatments, the root, petiole, and leaf exhibited a substantial abundance of pathogenic biomarkers, such as Pseudomonas, Burkholderia, Ralstonia, and Escherichia, resulting in the slow growth and morbidity of the plant. Difference analysis of metabolic pathways revealed that MPs significantly upregulated the pathogenic metabolic pathways (p < 0.05), and the presence of Vibrio infectious and pathogenic metabolic pathways was detected in all three niches of the plant. Moreover, MPs significantly inhibited the contents of carotenoids, iron, vitamin C, and calcium in edible niches of the plant (p < 0.05), and most of the high-abundant biomarkers were negatively correlated with their nutritional qualities.

Metabolome-Wide Mendelian Randomization Assessing the Causal Relationship Between Blood Metabolites and Sarcopenia-Related Traits.

Sarcopenia is among the most common musculoskeletal illnesses, yet its underlying biochemical mechanisms remain incompletely understood. In this study, we used Mendelian randomization (MR) to investigate the causal relationship between the genetically determined blood metabolites and sarcopenia, with the overall objective of identifying likely molecular pathways for sarcopenia. We used 2-sample MR to investigate the effects of blood metabolites on sarcopenia-related traits. 452 metabolites were exposure, and 3 sarcopenia-related traits as the outcomes: handgrip strength, appendicular lean mass, and walking pace. The inverse-variance weighted (IVW) causal estimates were determined. For sensitivity analysis, methods such as MR-Egger regression, the weighted median, the weighted mode, and the heterogeneity test were used. Additionally, for complementation, we performed replication, meta-analysis, and metabolic pathway analyses. Candidate biomarkers were defined by meeting one of the following criteria: (1) significant metabolites are defined as pIVW < pBonferroni [1.11 × 10-4 (.05/452)]; (2) strong metabolites are defined as 4 MR methods p < .05; and (3) suggestive metabolites are defined as passing sensitivity analysis. Three metabolites (creatine, 1-arachidonoylglycerophosphocholine, and pentadecanoate [15:0]) with significant causality, 3 metabolites (glycine, 1-arachidonoylglycerophosphocholine, and epiandrosterone sulfate) with strong causality, and 25 metabolites (including leucylleucin, pyruvic acid, etc.) with suggestive causality were associated with sarcopenia-related traits. After further replication analyses and meta-analysis, these metabolites maintained substantial effects on sarcopenia-related traits. We additionally identified 14 important sarcopenia-related trait metabolic pathways. By combining metabolomics with genomics, these candidate metabolites and metabolic pathways identified in our study may provide new clues regarding the mechanisms underlying sarcopenia.

The causal association between serum metabolites and lung cancer based on multivariate Mendelian randomization.

This study seeks to understand the causal association between serum metabolites and different lung cancer types, an area yet to be extensively studied. We Used a two-sample Mendelian randomization (TSMR) approach, utilizing 486 blood metabolites as exposures and 3 distinct lung cancer types genome-wide association studies datasets as outcomes. We employed inverse variance weighting, MR-Egger, weighted median, simple mode, and weighted mode to estimate causal effects. We performed sensitivity analyses using Cochran Q test, MR-Egger intercept test, and MR-pleiotropy residual sum and outlier (MR-PRESSO). Linkage disequilibrium score (LDSC) analysis was conducted on the selected metabolites, and common confounding single nucleotide polymorphisms were eliminated using the human genotype-phenotype association Database. Metabolic pathway analysis was performed with MetaboAnalyst 5.0 software. Subsequently, a multivariate Mendelian randomization analysis was conducted to ascertain independent risk exposures. Our findings suggest independent risk factors for specific types of lung cancer: 7-methylxanthine and isoleucine for lung adenocarcinoma, cysteine and 1-arachidonoylglycerophosphocholine are identified as independent protective and risk factors for squamous lung cancer. Undecanoate (11:0) with Linoleate (18:2n6) showed a protective effect for small cell lung cancer. Additionally, 11 metabolic pathways were associated with lung cancer. This novel perspective offers a multidimensional understanding of lung cancer phenotypes, providing valuable guidance for identifying and screening of diverse lung cancer phenotypes.

Metabolic clues to aging: exploring the role of circulating metabolites in frailty, sarcopenia and vascular aging related traits and diseases.

Background: Physical weakness and cardiovascular risk increase significantly with age, but the underlying biological mechanisms remain largely unknown. This study aims to reveal the causal effect of circulating metabolites on frailty, sarcopenia and vascular aging related traits and diseases through a two-sample Mendelian Randomization (MR) analysis. Methods: Exposures were 486 metabolites analyzed in a genome-wide association study (GWAS), while outcomes included frailty, sarcopenia, arterial stiffness, atherosclerosis, peripheral vascular disease (PAD) and aortic aneurysm. Primary causal estimates were calculated using the inverse-variance weighted (IVW) method. Methods including MR Egger, weighted median, Q-test, and leave-one-out analysis were used for the sensitive analysis. Results: A total of 125 suggestive causative associations between metabolites and outcomes were identified. Seven strong causal links were ultimately identified between six metabolites (kynurenine, pentadecanoate (15:0), 1-arachidonoylglycerophosphocholine, androsterone sulfate, glycine and mannose) and three diseases (sarcopenia, PAD and atherosclerosis). Besides, metabolic pathway analysis identified 13 significant metabolic pathways in 6 age-related diseases. Furthermore, the metabolite-gene interaction networks were constructed. Conclusion: Our research suggested new evidence of the relationship between identified metabolites and 6 age-related diseases, which may hold promise as valuable biomarkers.

Evaluating for Correlations between Specific Metabolites in Patients Receiving First-Line or Second-Line Immunotherapy for Metastatic or Recurrent NSCLC: An Exploratory Study Based on Two Cohorts.

Immune checkpoint inhibitors (ICI) have displayed impressive clinical efficacy in the context of non-small cell lung cancer (NSCLC). However, most patients do not achieve long-term survival. Minimally invasive collected samples are attracting significant interest as new fields of biomarker study, and metabolomics is one of these growing fields. We concentrated on the augmented value of the metabolomic profile in differentiating long-term survival from short-term survival in patients with NSCLC subjected to ICIs. We prospectively recruited 97 patients with stage IV NSCLC who were treated with anti-PD-1 inhibitor, including patients treated with monoimmunotherapy as second-line treatment (Cohort 1), and patients treated with combination immunotherapy as first-line treatment (Cohort 2). Each cohort was divided into long-term and short-term survival groups. All blood samples were collected before beginning immunotherapy. Serum metabolomic profiling was performed by UHPLC-Q-TOF MS analysis. Pareto-scaled principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis were performed. In Cohort 1, the mPFS and mOS of long-survival patients are 27.05 and NR months, respectively, and those of short-survival patients are 2.79 and 10.59 months. In Cohort 2, the mPFS and mOS of long-survival patients are 27.35 and NR months, respectively, and those of short-survival patients are 3.77 and 12.17 months. A total of 41 unique metabolites in Cohort 1 and 47 in Cohort 2 were screened. In Cohorts 1 and 2, there are 6 differential metabolites each that are significantly associated with both progression-free survival and overall survival. The AUC values for all groups ranged from 0.73 to 0.95. In cohort 1, the top 3 enriched KEGG pathways, as determined through significant different metabolic pathway analysis, were primary bile acid biosynthesis, African trypanosomiasis, and choline metabolism in cancer. In Cohort 2, the top 3 enriched KEGG pathways were the citrate cycle (TCA cycle), PPAR signaling pathway, and primary bile acid biosynthesis. The primary bile acid synthesis pathway had significant differences in the long-term and short-term survival groups in both Cohorts 1 and 2. Our study suggests that peripheral blood metabolomic analysis is critical for identifying metabolic biomarkers and pathways responsible for the patients with NSCLC treated with ICIs.

Comparative Transcriptome Analysis Reveals the Genes and Pathways Related to Wheat Root Hair Length.

Tube-like outgrowths from root epidermal cells, known as root hairs, enhance water and nutrient absorption, facilitate microbial interactions, and contribute to plant anchorage by expanding the root surface area. Genetically regulated and strongly influenced by environmental conditions, longer root hairs generally enhance water and nutrient absorption, correlating with increased stress resistance. Wheat, a globally predominant crop pivotal for human nutrition, necessitates the identification of long root hair genotypes and their regulatory genes to enhance nutrient capture and yield potential. This study focused on 261 wheat samples of diverse genotypes during germination, revealing noticeable disparities in the length of the root hair among the genotypes. Notably, two long root hair genotypes (W106 and W136) and two short root hair genotypes (W90 and W100) were identified. Transcriptome sequencing resulted in the development of 12 root cDNA libraries, unveiling 1180 shared differentially expressed genes (DEGs). Further analyses, including GO function annotation, KEGG enrichment, MapMan metabolic pathway analysis, and protein-protein interaction (PPI) network prediction, underscored the upregulation of root hair length regulatory genes in the long root hair genotypes. These included genes are associated with GA and BA hormone signaling pathways, FRS/FRF and bHLH transcription factors, phenylpropanoid, lignin, lignan secondary metabolic pathways, the peroxidase gene for maintaining ROS steady state, and the ankyrin gene with diverse biological functions. This study contributes valuable insights into modulating the length of wheat root hair and identifies candidate genes for the genetic improvement of wheat root traits.

Alterations in metabolome and microbiome: new clues on cathelicidin-related antimicrobial peptide alleviates acute ulcerative colitis.

Ulcerative colitis (UC) is a chronic and recurrent inflammatory disease of the gastrointestinal tract. This study aimed to determine the effect of cathelicidin-related antimicrobial peptide (Cramp) on dextran sulfate sodium (DSS)-induced acute experimental colitis in mice and to investigate the underlying mechanisms. Acute UC was induced in C57BL/6 mice with 3% DSS for 7 days, 4 mg/kg b.w. synthetic Cramp peptide was administrated once daily starting on day 4 of the experimental period. Mice were evaluated for body weight, colon length, colon histopathology, and inflammatory cytokines in colon tissue. Using 16 s rRNA sequencing, the composition structure of gut microbiota was characterized. Metabolomic profiling of the serum was performed. The results showed that DSS treatment significantly induced intestinal damage as reflected by disease activity index, histopathological features, and colon length, while Cramp treatment significantly prevented these trends. Meanwhile, Cramp treatment decreased the levels of inflammatory cytokines in both serum and colonic tissue on DSS-induced colitis. It was also observed that DSS damaged the integrity of the intestinal epithelial barrier, whereas Cramp also played a protective role by attenuating these deteriorated effects. Furthermore, Cramp treatment reversed the oxidative stress by increasing the antioxidant enzymes of GSH-PX and decreasing the oxidant content of MDA. Notably, compared to the DSS group, Cramp treatment significantly elevated the abundance of Verrucomicrobiota at the phylum level. Furthermore, at the genus level, Parasutterella and Mucispirllum abundance was increased significantly in response to Cramp treatment, although Roseburia and Enterorhabdus reduced remarkably. Metabolic pathway analysis of serum metabolomics showed that Cramp intervention can regulate various metabolic pathways such as α-linolenic acid, taurine and hypotaurine, sphingolipid, and arachidonic acid metabolism. The study concluded that Cramp significantly ameliorated DSS-induced colonic injury, colonic inflammation, and intestinal barrier dysfunction in mice. The underlying mechanism is closely related to the metabolic alterations derived from gut microbiota.

NMR-based metabolomic signature: An important tool for the diagnosis and study of pathogenesis of autoimmune hepatitis.

Metabolomics is used to predict, diagnose, and monitor metabolic disorders but altered metabolomic signatures have also been reported in diverse diseases, including autoimmune disorders. However, the metabolomic profile in autoimmune hepatitis (AIH) has not been investigated in depth. Therefore, we investigated the metabolomic signature of AIH and its significance as a diagnostic and pathogenetic tool. Metabolites in plasma samples from 50 patients with AIH at diagnosis, 43 healthy controls, 72 patients with primary biliary cholangitis (PBC), 26 patients with metabolic dysfunction-associated liver disease, and 101 patients with chronic viral hepatitis were determined by 1 H NMR (nuclear magnetic resonance) spectroscopy. Fifty-two metabolites were quantified, and metabolic pathway analysis was performed. Multivariate analysis revealed that AIH could be differentiated from healthy controls and each of the disease controls ( p <0.001). Fifteen metabolites differentiated AIH from disease controls (PBC+chronic viral hepatitis+metabolic dysfunction-associated liver disease) (95% sensitivity and 92% specificity). Ten distinct metabolic pathways were altered in AIH compared to disease controls. The metabolic pathway of branched-chain amino acids (lower valine, leucine, and isoleucine levels and their catabolic intermediates in PBC), methionine (lower methionine, 2-aminobutyrate, and 2-hydroxybutyrate levels in PBC), alanine-aspartate-glutamate (lower metabolites in PBC), and that of metabolites associated with gut microbiota (lower choline, betaine, and dimethylamine levels in PBC) were significantly different between AIH and PBC ( p <0.01). 1 H NMR spectroscopy could be a promising novel tool to diagnose and study AIH pathogenesis as there is no need for much sample handling, is highly reproducible with high sensitivity and specificity, and low cost.

Mechanistic Insights into Nitrite Degradation by Metabolites of L. plantarum A50: An LC-MS-Based Untargeted Metabolomics Analysis

Nitrites are universally acknowledged natural toxic substances that frequently lead to poisoning in humans and animals. During fermentation, certain microorganisms utilize a portion of the nitrogen element and reduce nitrates to nitrites through specific metabolic pathways. In this study, a highly effective lactic acid bacterial strain, Lactiplantibacillus plantarum A50, was isolated and screened from alfalfa silage for its remarkable ability to degrade nitrites. L. plantarum A50 exhibits exceptional nitrite removal capacity, with a degradation rate of 99.06% within 24 h. Furthermore, L. plantarum A50 demonstrates normal growth under pH values ranging from 4 to 9 and salt concentrations of 5%, displaying excellent tolerance to acidity, alkalinity, and salinity. Additionally, it undergoes fermentation using various carbon sources. Within the first 6–12 h of culture, L. plantarum A50 primarily achieves nitrite degradation through non-acidic processes, resulting in a degradation rate of 82.67% by the 12th hour. Moreover, the metabolites produced by L. plantarum A50 exhibit a synergistic interaction with acidity, leading to a nitrite degradation rate of 98.48% within 24 h. Notably, both L. plantarum A50 and MRS broth were found to degrade nitrites. Consequently, a non-targeted metabolomic analysis using LC-MS was conducted to identify 342 significantly different metabolites between L. plantarum A50 and MRS broth. Among these, lipids and lipid-like molecules, organic acids and derivatives, organic oxygen compounds, and organoheterocyclic compounds emerged as the main constituents. Lipids and lipid-like molecules, derivatives of glucose and galactose, amino acids and their derivatives, as well as organoheterocyclic compounds, are likely to play a role in nitrite elimination. Through the enrichment analysis of differential metabolic pathways using KEGG, nine distinct pathways were identified. These pathways provide essential nutrients, maintain cellular structure and function, participate in substance transport, regulate metabolic activities, and enhance resistance against pathogenic microorganisms in L. plantarum A50.

Differences of serum glucose and lipid metabolism and immune parameters and blood metabolomics regarding the transition cows in the antepartum and postpartum period.

This study aims to investigate differences in metabolism regarding the transition cows. Eight cows were selected for the test. Serum was collected on antepartum days 14th (ap14) and 7th (ap7) and postpartum days 1st (pp1), 7th (pp7), and 14th (pp14) to detect biochemical parameters. The experiment screened out differential metabolites in the antepartum (ap) and postpartum (pp) periods and combined with metabolic pathway analysis to study the relationship and role between metabolites and metabolic abnormalities. Results: (1) The glucose (Glu) levels in ap7 were significantly higher than the other groups (p < 0.01). The insulin (Ins) levels of ap7 were significantly higher than pp7 (p = 0.028) and pp14 (p < 0.01), and pp1 was also significantly higher than pp14 (p = 0.016). The insulin resistance (HOMA-IR) levels of ap7 were significantly higher than ap14, pp7, and pp14 (p < 0.01). The cholestenone (CHO) levels of ap14 and pp14 were significantly higher than pp1 (p < 0.01). The CHO levels of pp14 were significantly higher than pp7 (p < 0.01). The high density lipoprotein cholesterol (DHDL) levels of pp1 were significantly lower than ap14 (p = 0.04), pp7 (p < 0.01), and pp14 (p < 0.01), and pp14 was also significantly higher than ap14 and ap7 (p < 0.01). (2) The interferon-gamma (IFN-γ) and tumor necrosis factor α (TNF-α) levels of ap7 were significantly higher than pp1 and pp7 (p < 0.01); the immunoglobulin A (IgA) levels of pp1 were significantly higher than ap7 and pp7 (p < 0.01); the interleukin-4 (IL-4) levels of pp7 were significantly higher than ap7 and pp1 (p < 0.01), the interleukin-6 (IL-6) levels of ap7 and pp1 were significantly higher than pp7 (p < 0.01). (3) Metabolomics identified differential metabolites mainly involved in metabolic pathways, such as tryptophan metabolism, alpha-linolenic acid metabolism, tyrosine metabolism, and lysine degradation. The main relevant metabolism was concentrated in lipid and lipid-like molecules, organic heterocyclic compounds, organic acids, and their derivatives. The results displayed the metabolic changes in the transition period, which laid a foundation for further exploring the mechanism of metabolic abnormalities in dairy cows in the transition period.

Deciphering the potential of Sargassum tenerrimum extract: metabolic profiling and pathway analysis of groundnut (Arachis hypogaea) in response to Sargassum extract and Sclerotium rolfsii.

The online version contains supplementary material available at 10.1007/s12298-024-01418-9.

A novel gene signature related to fatty acid metabolism predicts prognosis, immune landscape, and drug sensitivity in early-stage lung squamous cell carcinoma.

Dysregulation of fatty acid metabolism (FAM) represents a significant metabolic alteration in tumorigenesis. However, the role of FAM-related genes (FAMRGs) in early-stage lung squamous cell carcinoma (LUSC) remains incompletely understood. A series of bioinformatic analyses and machine learning strategies were performed to construct a FAMRGs-based signature to predict prognosis and guide personalized treatment for early-stage LUSC patients. FAMRGs were screened through the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the Molecular Signature Database (MSigDB). Prognosis FAMRGs were identified using univariate Cox regression, and unsupervised clustering analysis facilitated the division of the cohort into different clusters. The least absolute shrinkage and selection operator (LASSO)-Cox regression and multivariate regression analysis were employed to develop a FAMRGs-based signature for predicting overall survival (OS). A nomogram was subsequently constructed to facilitate risk assessment for individual patients. Comprehensive analyses of metabolic pathways, immune infiltration, immunomodulators, and potentially applicable drugs were conducted across different FAMRGs-related risk groups. The FAMRGs-based signature, comprising nine genes (ACOT11, APOH, BMX, CYP2R1, DPEP3, FABP6, FADS2, GLYATL2, and THRSP), demonstrated robust predictive capabilities for prognosis in The Cancer Genome Atlas (TCGA)-LUSC dataset and validated across six independent Gene Expression Omnibus (GEO)-LUSC datasets. Notably, the FAMRGs-base signature exhibited superior prognostic capacity and accurate survival prediction compared to conventional clinicopathological features. Furthermore, the signature was closely associated with immune cell infiltration, human leukocyte antigen (HLA) genes, and immune checkpoint genes expression. Additionally, the signature demonstrated potential sensitivity to chemo-/target-therapy. The FAMRGs-based signature demonstrated superior sensitivity in predicting the prognosis of early-stage LUSC. Detecting FAMRGs may provide predictive targets for the development of clinical treatment strategies.

Genome-wide transcriptome profiling reveals molecular response pathways of Trichoderma harzianum in response to salt stress.

Trichoderma harzianum exhibits a strong biological control effect on many important plant pathogens, such as Fusarium oxysporum, Botrytis cinerea, and Meloidogyne. However, its biocontrol effectiveness is weakened or reduced under salt stress. The aim of this study was to investigate the molecular response of T. harzianum to salt stress at the whole-genome level. Here, we present a 44.47 Mb near-complete genome assembly of the T. harzianum qt40003 strain for the first time, which was assembled de novo with 7.59 Gb Nanopore sequencing long reads (~170-fold) and 5.2 Gb Illumina short reads (~116-fold). The assembled qt40003 genome contains 12 contigs, with a contig N50 of 4.81 Mb, in which four of the 12 contigs were entirely reconstructed in a single chromosome from telomere to telomere. The qt40003 genome contains 4.27 Mb of repeat sequences and 12,238 protein-coding genes with a BUSCO completeness of 97.5%, indicating the high accuracy and completeness of our gene annotations. Genome-wide transcriptomic analysis was used to investigate gene expression changes related to salt stress in qt40003 at 0, 2% (T2), and 4% (T4) sodium chloride concentrations. A total of 2,937 and 3,527 differentially expressed genes (DEGs) were obtained under T2 and T4 conditions, respectively. GO enrichment analysis showed that the T2-treatment DEGs were highly enriched in detoxification (p < 0.001), while the T4 DEGs were mainly enriched in cell components, mostly in cellular detoxification, cell surface, and cell wall. KEGG metabolic pathway analysis showed that 91 and 173 DEGs were significantly enriched in the T2 and T4 treatments, respectively (p < 0.01), mainly in the glutathione metabolism pathway. We further experimentally analyzed the differentially expressed glutathione transferase genes in the glutathione metabolic pathway, most of which were downregulated (13/15). In addition, we screened 13 genes related to active oxygen clearance, including six upregulated and seven downregulated genes, alongside five fungal hydrophobic proteins, of which two genes were highly expressed. Our study provides high-quality genome information for the use of T. harzianum for biological control and offers significant insights into the molecular responses of T. harzianum under salt-stress conditions.

Non-targeted metabolomics analysis of indoleamine 2,3-dioxygenase inhibitor treatment in a mouse model of early-stage lung adenocarcinoma.

Lung adenocarcinoma is a common malignant tumor, and its early diagnosis and treatment are key to improving patient survival rates. However, due to the non-specific early symptoms, many patients are already at an advanced stage when diagnosed. Non-targeted metabolomics analysis, as a method for comprehensive analysis of metabolites in the body, has been shown to have potential in the early diagnosis of cancer. This study aims to identify early-stage lung adenocarcinoma-specific biomarkers using non-targeted metabolomics analysis in an established mouse model. The intervention mechanism of indoleamine 2,3-dioxygenase (IDO) inhibitor in early-stage lung adenocarcinoma is explored to provide evidence for clinical disease treatment. Twenty specific-pathogen-free-grade female Kunming mice were divided into control group, experimental group, Epacadostatlow group, and Epacadostathigh group. After modeling, immune therapy intervention (epacadostat) was administered to the mice, and plasma and urine samples were collected from all mice on day 7 and day 28. Ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) analysis was performed to identify potential biomarkers for diagnosing early-stage lung adenocarcinoma. Cluster analysis and correlation analysis were used to explore the differential expression patterns of metabolites in different samples. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was used to identify enriched pathways of differentially expressed metabolites. A total of 348 metabolites were identified after merging the positive and negative ion modes. Among them, organic acids and derivatives (16.954%) and lipids and lipid-like molecules (15.517%) were the two major classes of metabolites in the early-stage lung adenocarcinoma mice. Anthranilic acid (vitamin L1), 1-methylhistidine, 12(R)-HETE, and hippuric acid were the major differentially expressed metabolites on both day 7 and day 28, and they showed correlations with each other. Metabolic pathway analysis revealed multiple dysregulated pathways in lung adenocarcinoma mice. UPLC-QTOF-MS analysis is a feasible method for identifying biomarkers of lung adenocarcinoma. Epacadostat, a novel and promising IDO inhibitor, may exert its therapeutic effect by modulating 1-methylhistidine and anthranilic acid (vitamin L1).