PubMed

Eur J Pharmacol. 2023 Dec 12:176269. doi: 10.1016/j.ejphar.2023.176269. Online ahead of print.ABSTRACTThis study aimed to comparatively investigate the anti-tumor mechanisms of steroids including ergosterol, β-sitosterol, cholesterol, and fucosterol. The model of H22 tumor-bearing mice was constructed based on histopathological data and biochemical parameters, while serums were subjected to metabolomics analysis to study the potential anti-tumor mechanisms. The results indicated that the four steroids exhibited different degrees of anti-tumor effects on H22 mice. The tumor inhibition rates were 63.25% for ergosterol, 56.41% for β-sitosterol, 61.54% for cholesterol, and 72.65% for fucosterol. Metabolomic analyses revealed that 87, 71, and 129 differential metabolites were identified in ergosterol, cholesterol, and fucosterol treatment groups, respectively. The fucosterol treatment group had the highest number of differential metabolites. At the same time, it mainly inhibited purine and amino acid metabolism to exert anti-tumor effects. Ergosterol enhanced immunity and affected pyruvate metabolism, and cholesterol inhibited purine metabolism. The chemical structure difference among ergosterol, cholesterol, and fucosterol is mainly at the number and position of sterol double bonds and the number and length of side chain carbons. Therefore, there is a structure-activity relationship between the structure of steroid compounds and their efficacy. This study provides a key foundation for the exploitation of the anti-tumor effects of steroids derived from different organisms.PMID:38096966 | DOI:10.1016/j.ejphar.2023.176269

Cell. 2023 Dec 8:S0092-8674(23)01271-0. doi: 10.1016/j.cell.2023.11.018. Online ahead of print.ABSTRACTThe microbiota influences intestinal health and physiology, yet the contributions of commensal protists to the gut environment have been largely overlooked. Here, we discover human- and rodent-associated parabasalid protists, revealing substantial diversity and prevalence in nonindustrialized human populations. Genomic and metabolomic analyses of murine parabasalids from the genus Tritrichomonas revealed species-level differences in excretion of the metabolite succinate, which results in distinct small intestinal immune responses. Metabolic differences between Tritrichomonas species also determine their ecological niche within the microbiota. By manipulating dietary fibers and developing in vitro protist culture, we show that different Tritrichomonas species prefer dietary polysaccharides or mucus glycans. These polysaccharide preferences drive trans-kingdom competition with specific commensal bacteria, which affects intestinal immunity in a diet-dependent manner. Our findings reveal unappreciated diversity in commensal parabasalids, elucidate differences in commensal protist metabolism, and suggest how dietary interventions could regulate their impact on gut health.PMID:38096822 | DOI:10.1016/j.cell.2023.11.018

Phytomedicine. 2023 Dec 5;123:155259. doi: 10.1016/j.phymed.2023.155259. Online ahead of print.ABSTRACTBACKGROUND: Scutellaria baicalensis Georgi, a traditional Chinese medicine, is clinically applied mainly as the dried root of Scutellaria baicalensis, and the aerial parts of Scutellaria baicalensis, its stems and leaves, are often consumed as "Scutellaria baicalensis tea" to clear heat, dry dampness, reduce fire and detoxify, while few comparative analyses of the spatial metabolome of the aerial and underground parts of Scutellaria baicalensis have been carried out in current research.METHODS: In this work, Matrix-assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) was used to visualize the spatial imaging of the root, stem, and leaf of Scutellaria baicalensis at a high resolution of 10 μm, respectively, investigating the spatial distribution of the different secondary metabolites in the aerial and underground parts of Scutellaria baicalensis.RESULTS: In the present results, various metabolites, such as flavonoid glycosides, flavonoid metabolites, and phenolic acids, were systematically characterized in Scutellaria baicalensis root, stem, and leaf. Nine glycosides, 18 flavonoids, one organic acid, and four other metabolites in Scutellaria baicalensis root; nine glycosides, nine flavonoids, one organic acid in Scutellaria baicalensis stem; and seven flavonoids and seven glycosides in Scutellaria baicalensis leaf were visualized by MALDI-MSI. In the underground part of Scutellaria baicalensis, baicalein, wogonin, baicalin, wogonoside, and chrysin were widely distributed, while there was less spatial location in the aerial parts. Moreover, scutellarein, carthamidin/isocarthamidin, scutellarin, carthamidin/isocarthamidin-7-O-glucuronide had a high distribution in the aerial parts of Scutellaria baicalensis. In addition, the biosynthetic pathways involved in the biosynthesis of significant flavonoid metabolites in aerial and underground parts of Scutellaria baicalensis were successfully localized and visualized.CONCLUSIONS: MALDI-MSI offers a favorable approach for investigating the spatial distribution and effective utilization of metabolites of Scutellaria baicalensis. The detailed spatial chemical information can not only improve our understanding of the biosynthesis pathways of flavonoid metabolites, but more importantly, suggest that we need to fully exert the overall medicinal value of Scutellaria baicalensis, strengthening the reuse and development of the resources of Scutellaria baicalensis aboveground parts.PMID:38096718 | DOI:10.1016/j.phymed.2023.155259

Front Med. 2023 Dec 15. doi: 10.1007/s11684-023-1029-3. Online ahead of print.NO ABSTRACTPMID:38097819 | DOI:10.1007/s11684-023-1029-3

NPJ Parkinsons Dis. 2023 Dec 14;9(1):165. doi: 10.1038/s41531-023-00612-y.ABSTRACTGut microbial proteolytic metabolism has been reportedly altered in Parkinson's disease (PD). However, the circulating aromatic amino acids (AAA) described in PD are inconsistent. Here we aimed to investigate plasma AAA profiles in a large cohort of PD patients, and examine their correlations with clinical severity and gut microbiota changes. We enrolled 500 participants including 250 PD patients and 250 neurologically normal controls. Plasma metabolites were measured using liquid chromatography mass spectrometry. Faecal samples were newly collected from 154 PD patients for microbiota shotgun metagenomic sequencing combined with data derived from 96 PD patients reported before. Data were collected regarding diet, medications, and motor and non-motor symptoms of PD. Compared to controls, PD patients had higher plasma AAA levels, including phenylacetylglutamine (PAGln), p-cresol sulfate (Pcs), p-cresol glucuronide (Pcg), and indoxyl sulfate (IS). Multivariable linear regression analyses, with adjustment for age, sex, and medications, revealed that the plasma levels of PAGln (coefficient 4.49, 95% CI 0.40-8.58, P = 0.032) and Pcg (coefficient 1.79, 95% CI 0.07-3.52, P = 0.042) positively correlated with motor symptom severity but not cognitive function. After correcting for abovementioned potential confounders, these AAA metabolites were also associated with the occurrence of constipation in PD patients (all P < 0.05). Furthermore, plasma levels of AAA metabolites were correlated with the abundance of specific gut microbiota species, including Bacteroides sp. CF01-10NS, Bacteroides vulgatus, and Clostridium sp. AF50-3. In conclusion, elevated plasma AAA metabolite levels correlated with disease characteristics in PD, suggesting that upregulated proteolytic metabolism may contribute to the pathophysiology of PD.PMID:38097625 | DOI:10.1038/s41531-023-00612-y

Sci Rep. 2023 Dec 14;13(1):22260. doi: 10.1038/s41598-023-48539-x.ABSTRACTTraumatic brain injury (TBI) is a major cause of mortality and disability worldwide, particularly among individuals under the age of 45. It is a complex, and heterogeneous disease with a multifaceted pathophysiology that remains to be elucidated. Metabolomics has the potential to identify metabolic pathways and unique biochemical profiles associated with TBI. Herein, we employed a longitudinal metabolomics approach to study TBI in a weight drop mouse model to reveal metabolic changes associated with TBI pathogenesis, severity, and secondary injury. Using proton nuclear magnetic resonance (1H NMR) spectroscopy, we biochemically profiled post-mortem brain from mice that suffered mild TBI (N = 25; 13 male and 12 female), severe TBI (N = 24; 11 male and 13 female) and sham controls (N = 16; 11 male and 5 female) at baseline, day 1 and day 7 following the injury. 1H NMR-based metabolomics, in combination with bioinformatic analyses, highlights a few significant metabolites associated with TBI severity and perturbed metabolism related to the injury. We report that the concentrations of taurine, creatinine, adenine, dimethylamine, histidine, N-Acetyl aspartate, and glucose 1-phosphate are all associated with TBI severity. Longitudinal metabolic observation of brain tissue revealed that mild TBI and severe TBI lead distinct metabolic profile changes. A multi-class model was able to classify the severity of injury as well as time after TBI with estimated 86% accuracy. Further, we identified a high degree of correlation between respective hemisphere metabolic profiles (r > 0.84, p < 0.05, Pearson correlation). This study highlights the metabolic changes associated with underlying TBI severity and secondary injury. While comprehensive, future studies should investigate whether: (a) the biochemical pathways highlighted here are recapitulated in the brain of TBI sufferers and (b) if the panel of biomarkers are also as effective in less invasively harvested biomatrices, for objective and rapid identification of TBI severity and prognosis.PMID:38097614 | DOI:10.1038/s41598-023-48539-x

Transl Psychiatry. 2023 Dec 14;13(1):391. doi: 10.1038/s41398-023-02697-8.ABSTRACTLarge deletions at chromosome 22q11.2 are known to cause severe clinical conditions collectively known as 22q11.2 deletion syndrome. Notwithstanding the pathogenicity of these deletions, affected individuals are typically diagnosed in late childhood or early adolescence, and little is known of the molecular signaling cascades and biological consequences immediately downstream of the deleted genes. Here, we used targeted metabolomics to compare neonatal dried blood spot samples from 203 individuals clinically identified as carriers of a deletion at chromosome 22q11.2 with 203 unaffected individuals. A total of 173 metabolites were successfully identified and used to inform on systemic dysregulation caused by the genomic lesion and to discriminate carriers from non-carriers. We found 84 metabolites to be differentially abundant between carriers and non-carriers of the 22q11.2 deletion. A predictive model based on all 173 metabolites achieved high Accuracy (89%), Area Under the Curve (93%), F1 (88%), Positive Predictive Value (94%), and Negative Predictive Value (84%) with tyrosine and proline having the highest individual contributions to the model as well as the highest interaction strength. Targeted metabolomics provides insight into the molecular consequences possibly contributing to the pathology underlying the clinical manifestations of the 22q11 deletion and is an easily applicable approach to first-pass screening for carrier status of the 22q11 to prompt subsequent verification of the genomic diagnosis.PMID:38097559 | DOI:10.1038/s41398-023-02697-8

Transl Psychiatry. 2023 Dec 15;13(1):393. doi: 10.1038/s41398-023-02696-9.ABSTRACTPeripheral blood metabolomics was used to gain chemical insight into the biology of treatment-refractory Major Depressive Disorder with suicidal ideation, and to identify individualized differences for personalized care. The study cohort consisted of 99 patients with treatment-refractory major depressive disorder and suicidal ideation (trMDD-SI n = 52 females and 47 males) and 94 age- and sex-matched healthy controls (n = 48 females and 46 males). The median age was 29 years (IQR 22-42). Targeted, broad-spectrum metabolomics measured 448 metabolites. Fibroblast growth factor 21 (FGF21) and growth differentiation factor 15 (GDF15) were measured as biomarkers of mitochondrial dysfunction. The diagnostic accuracy of plasma metabolomics was over 90% (95%CI: 0.80-1.0) by area under the receiver operator characteristic (AUROC) curve analysis. Over 55% of the metabolic impact in males and 75% in females came from abnormalities in lipids. Modified purines and pyrimidines from tRNA, rRNA, and mRNA turnover were increased in the trMDD-SI group. FGF21 was increased in both males and females. Increased lactate, glutamate, and saccharopine, and decreased cystine provided evidence of reductive stress. Seventy-five percent of the metabolomic abnormalities found were individualized. Personalized deficiencies in CoQ10, flavin adenine dinucleotide (FAD), citrulline, lutein, carnitine, or folate were found. Pathways regulated by mitochondrial function dominated the metabolic signature. Peripheral blood metabolomics identified mitochondrial dysfunction and reductive stress as common denominators in suicidal ideation associated with treatment-refractory major depressive disorder. Individualized metabolic differences were found that may help with personalized management.PMID:38097555 | DOI:10.1038/s41398-023-02696-9

Metab Brain Dis. 2023 Dec 14. doi: 10.1007/s11011-023-01331-2. Online ahead of print.ABSTRACTBrain stroke (BS, also known as a cerebrovascular accident), represents a serious global health crisis. It has been a leading cause of permanent disability and unfortunately, frequent fatalities due to lack of timely medical intervention. While progress has been made in prevention and management, the complexities and consequences of stroke continue to pose significant challenges, especially, its impact on patient's quality of life and independence. During stroke, there is a substantial decrease in oxygen supply to the brain leading to alteration of cellular metabolic pathways, including those involved in mitochondrial-damage, leading to mitochondrial-dysfunction. The present proof-of-the-concept metabolomics study has been performed to gain insights into the metabolic pathways altered following a brain stroke and discover new potential targets for timely interventions to mitigate the effects of cellular and mitochondrial damage in BS. The serum metabolic profiles of 108 BS-patients were measured using 800 MHz NMR spectroscopy and compared with 60 age and sex matched normal control (NC) subjects. Compared to NC, the serum levels of glutamate, TCA-cycle intermediates (such as citrate, succinate, etc.), and membrane metabolites (betaine, choline, etc.) were found to be decreased BS patients, whereas those of methionine, mannose, mannitol, phenylalanine, urea, creatine and organic acids (such as 3-hydroxybutyrate and acetone) were found to be elevated in BS patients. These metabolic changes hinted towards hypoxia mediated mitochondrial dysfunction in BS-patients. Further, the area under receiver operating characteristic curve (ROC) values for five metabolic features (methionine, mannitol, phenylalanine, mannose and urea) found to be more than 0.9 suggesting their high sensitivity and specificity for differentiating BS from NC subjects.PMID:38095788 | DOI:10.1007/s11011-023-01331-2

Metabolomics. 2023 Dec 14;20(1):6. doi: 10.1007/s11306-023-02074-y.ABSTRACTINTRODUCTION: Prenatal exposure to polycyclic aromatic hydrocarbons (PAHs) has been associated with adverse human health outcomes. To explore the plausible associations between maternal PAH exposure and maternal/newborn metabolomic outcomes, we conducted a cross-sectional study among 75 pregnant people from Cincinnati, Ohio.METHOD: We quantified 8 monohydroxylated PAH metabolites in maternal urine samples collected at delivery. We then used an untargeted high-resolution mass spectrometry approach to examine alterations in the maternal (n = 72) and newborn (n = 63) serum metabolome associated with PAH metabolites. Associations between individual maternal urinary PAH metabolites and maternal/newborn metabolome were assessed using linear regression adjusted for maternal and newborn factors while accounting for multiple testing with the Benjamini-Hochberg method. We then conducted functional analysis to identify potential biological pathways.RESULTS: Our results from the metabolome-wide associations (MWAS) indicated that an average of 1% newborn metabolome features and 2% maternal metabolome features were associated with maternal urinary PAH metabolites. Individual PAH metabolite concentrations in maternal urine were associated with maternal/newborn metabolome related to metabolism of vitamins, amino acids, fatty acids, lipids, carbohydrates, nucleotides, energy, xenobiotics, glycan, and organic compounds.CONCLUSION: In this cross-sectional study, we identified associations between urinary PAH concentrations during late pregnancy and metabolic features associated with several metabolic pathways among pregnant women and newborns. Further studies are needed to explore the mediating role of the metabolome in the relationship between PAHs and adverse pregnancy outcomes.PMID:38095785 | DOI:10.1007/s11306-023-02074-y

Anal Sci. 2023 Dec 14. doi: 10.1007/s44211-023-00470-x. Online ahead of print.ABSTRACTDue to the different price and high quality, halal meat such as beef can be adulterated with non-halal meat with low price to get an economical price. The objective of this research was to develop an analytical method for halal authentication testing of beef meatballs (BM) from dog meat (DM) using a non-targeted metabolomics approach employing liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and chemometrics. The differentiation of authentic BM from that adulterated with DM was successfully performed using partial least square-discriminant analysis (PLS-DA) with high accuracy (R2X = 0.980, and R2Y = 0.980) and good predictivity (Q2 = 0.517). In addition, partial least square (PLS) and orthogonal PLS (OPLS) were successfully used to predict the DM added (% w/w) in BM with high accuracy (R2 > 0.990). A number of metabolites, potential for biomarker candidates, were identified to differentiate BM and that adulterated with DM. It showed that the combination of a non-targeted LC-HRMS Orbitrap metabolomics and chemometrics could detect up to 0.1% w/w of DM adulteration. The developed method was successfully applied for analysis of commercial meatball samples (n = 28). Moreover, pathway analysis revealed that beta-alanine, histidine, and ether lipid metabolism were significantly affected by dog meat adulteration. In summary, this developed method has great potential to be developed and used as an alternative method for analysis of non-halal meats in halal meat products.PMID:38095741 | DOI:10.1007/s44211-023-00470-x

Hum Genet. 2023 Dec 14. doi: 10.1007/s00439-023-02619-0. Online ahead of print.ABSTRACTComplex multi-omics effects drive the clustering of cardiometabolic risk factors, underscoring the imperative to comprehend how individual and combined omics shape phenotypic variation. Our study partitions phenotypic variance in metabolic syndrome (MetS), blood glucose (GLU), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and blood pressure through genome, transcriptome, metabolome, and exposome (i.e., lifestyle exposome) analyses. Our analysis included a cohort of 62,822 unrelated individuals with white British ancestry, sourced from the UK biobank. We employed linear mixed models to partition phenotypic variance using the restricted maximum likelihood (REML) method, implemented in MTG2 (v2.22). We initiated the analysis by individually modeling omics, followed by subsequent integration of pairwise omics in a joint model that also accounted for the covariance and interaction between omics layers. Finally, we estimated the correlations of various omics effects between the phenotypes using bivariate REML. Significant proportions of the MetS variance were attributed to distinct data sources: genome (9.47%), transcriptome (4.24%), metabolome (14.34%), and exposome (3.77%). The phenotypic variances explained by the genome, transcriptome, metabolome, and exposome ranged from 3.28% for GLU to 25.35% for HDL-C, 0% for GLU to 19.34% for HDL-C, 4.29% for systolic blood pressure (SBP) to 35.75% for TG, and 0.89% for GLU to 10.17% for HDL-C, respectively. Significant correlations were found between genomic and transcriptomic effects for TG and HDL-C. Furthermore, significant interaction effects between omics data were detected for both MetS and its components. Interestingly, significant correlation of omics effect between the phenotypes was found. This study underscores omics' roles, interaction effects, and random-effects covariance in unveiling phenotypic variation in multi-omics domains.PMID:38095720 | DOI:10.1007/s00439-023-02619-0

Arch Microbiol. 2023 Dec 14;206(1):21. doi: 10.1007/s00203-023-03737-z.ABSTRACTBone is a kind of meat processing by-product with high nutritional value but low in calorie, which is a typical food in China and parts of East Asian countries. Microbial fermentation by lactic acid bacteria showed remarkable advantages to increase the absorption of nutrients from bone cement by human body. Streptococcus thermophilus CICC 20372 is proven to be a good starter for bone cement fermentation. No genes encoding virulence traits or virulence factors were found in the genome of S. thermophilus CICC 20372 by a thorough genomic analysis. Its notable absence of antibiotic resistance further solidifies the safety. Furthermore, the genomic analysis identified four types of gene clusters responsible for the synthesis of antimicrobial metabolites. A comparative metabolomic analysis was performed by cultivating the strain in bone cement at 37 °C for 72 h, with the culture in de Man, Rogosa, and Sharpe (MRS) medium as control. Metabolome analysis results highlighted the upregulation of pathways involved in 2-oxocarboxylic acid metabolism, ATP-binding cassette (ABC) transporters, amino acid synthesis, and nucleotide metabolism during bone cement fermentation. S. thermophilus CICC 20372 produces several metabolites with health-promoting function during bone cement fermentation, including indole-3-lactic acid, which is demonstrated ameliorative effects on intestinal inflammation, tumor growth, and gut dysbiosis. In addition, lots of nucleotide and organic acids were accumulated at higher levels, which enriched the fermented bone cement with a variety of nutrients. Collectively, these features endow S. thermophilus CICC 20372 a great potential strain for bone food processing.PMID:38095705 | DOI:10.1007/s00203-023-03737-z

mSystems. 2023 Dec 14:e0067723. doi: 10.1128/msystems.00677-23. Online ahead of print.ABSTRACTComplex traits are characterized by many biological and environmental factors, such that multi-omic data sets are well-positioned to help us understand their underlying etiologies. We applied a prediction framework across multiple omics (metagenomics, metatranscriptomics, metabolomics, and viromics) from the gut ecosystem to predict inflammatory bowel disease (IBD) diagnosis. The predicted scores from our models highlighted key features and allowed us to compare the relative utility of each omic data set in single-omic versus multi-omic models. Our results emphasized the importance of metabolomics and viromics over metagenomics and metatranscriptomics for predicting IBD status. The greater predictive capability of metabolomics and viromics is likely because these omics serve as markers of lifestyle factors such as diet. This study provides a modeling framework for multi-omic data, and our results show the utility of combining multiple omic data types to disentangle complex disease etiologies and biological signatures.PMID:38095449 | DOI:10.1128/msystems.00677-23

Immunol Rev. 2023 Dec 14. doi: 10.1111/imr.13303. Online ahead of print.NO ABSTRACTPMID:38095327 | DOI:10.1111/imr.13303

J Diabetes Investig. 2023 Dec 14. doi: 10.1111/jdi.14119. Online ahead of print.ABSTRACTGestational diabetes mellitus (GDM) is a pathological condition during pregnancy characterized by impaired glucose tolerance, and the failure of pancreatic beta-cells to respond appropriately to an increased insulin demand. However, while the majority of women with GDM will return to normoglycemia after delivery, they have up to a seven times higher risk of developing type 2 diabetes during midlife, compared with those with no history of GDM. Gestational diabetes mellitus also increases the risk of multiple metabolic disorders, including non-alcoholic fatty liver disease, obesity, and cardiovascular diseases. Lipid metabolism undergoes significant changes throughout the gestational period, and lipid dysregulation is strongly associated with GDM and the progression to future type 2 diabetes. In addition to common lipid variables, discovery-based omics techniques, such as metabolomics and lipidomics, have identified lipid biomarkers that correlate with GDM. These lipid species also show considerable potential in predicting the onset of GDM and subsequent type 2 diabetes post-delivery. This review aims to update the current knowledge of the role that lipids play in the onset of GDM, with a focus on potential lipid biomarkers or metabolic pathways. These biomarkers may be useful in establishing predictive models to accurately predict the future onset of GDM and type 2 diabetes, and early intervention may help to reduce the complications associated with GDM.PMID:38095269 | DOI:10.1111/jdi.14119

Anal Chem. 2023 Dec 14. doi: 10.1021/acs.analchem.3c03785. Online ahead of print.ABSTRACTMetabolomics and proteomics offer significant advantages in understanding biological mechanisms at two hierarchical levels. However, conventional single omics analysis faces challenges due to the high demand for specimens and the complexity of intrinsic associations. To obtain comprehensive and accurate system biological information, we developed a multiomics analytical method called Windows Scanning Multiomics (WSM). In this method, we performed simultaneous extraction of metabolites and proteins from the same sample, resulting in a 10% increase in the coverage of the identified biomolecules. Both metabolomics and proteomics analyses were conducted by using ultrahigh-performance liquid chromatography mass spectrometry (UPLC-MS), eliminating the need for instrument conversions. Additionally, we designed an R-based program (WSM.R) to integrate mathematical and biological correlations between metabolites and proteins into a correlation network. The network created from simultaneously extracted biomolecules was more focused and comprehensive compared to those from separate extractions. Notably, we excluded six pairs of false-positive relationships between metabolites and proteins in the network established using simultaneously extracted biomolecules. In conclusion, this study introduces a novel approach for multiomics analysis and data processing that greatly aids in bioinformation mining from multiomics results. This method is poised to play an indispensable role in systems biology research.PMID:38095040 | DOI:10.1021/acs.analchem.3c03785

Front Nutr. 2023 Nov 29;10:1247683. doi: 10.3389/fnut.2023.1247683. eCollection 2023.ABSTRACTDietary fiber improves intestinal environments, by, among others, increasing stool frequency. Kale is a good source of dietary fiber and minerals; however, the effects of kale on the intestinal environment have not yet been evaluated. This study determined how the intestinal environment, including the intestinal microbiota and its metabolome, and stool frequency are affected by the consumption of kale, in humans. A randomized controlled crossover trial, with a 4-week consumption of kale or control food, was conducted. An integrated analysis of the intestinal microbiota and metabolome was performed, and their relationship with improvements in stool frequency was analyzed. Kale intake for 4 weeks significantly increased stool frequency and altered some intestinal microbes, such as an increase in the [Eubacterium] eligens group and a decrease in the [Ruminococcus] gnavus group. Analysis of subjects with increased stool frequency revealed that this group had smaller amounts of stool before kale intake. Our findings indicate that kale modifies certain gut microbes, such as [Eubacterium] eligens and [Ruminococcus] gnavus, and improves bowel movements, particularly in those with smaller stool amounts.PMID:38094924 | PMC:PMC10717843 | DOI:10.3389/fnut.2023.1247683

Front Fungal Biol. 2023 Nov 29;4:1295223. doi: 10.3389/ffunb.2023.1295223. eCollection 2023.ABSTRACTPsilocybe mushrooms, otherwise known as "magic" mushrooms, owe their psychedelic effect to psilocin, a serotonin subtype 2A (5-HT2A) receptor agonist and metabolite of psilocybin, the primary indole alkaloid found in Psilocybe species. Metabolomics is an advanced fingerprinting tool that can be utilized to identify the differences among fungal life stages that may otherwise be unaccounted for. In this study, by using targeted and untargeted (metabolomic) multivariate analysis, we demonstrate that the chemical composition of Psilocybe differs among mycelia, grain mycelia, and fruiting bodies. The preferential accumulation of psilocybin, baeocystin, tryptophan, ergothioneine, and phenylethylamine in fruiting bodies differentiated them from mycelia; however, the levels of alpha-glycerylphosphorylcholine (α-GPC), N-acetylglucosamine, and trimethylglycine were found to be proportionally higher in mycelia than in fruiting bodies based on Pareto-scaled data. Considering the wealth of compounds with therapeutic potential that have been isolated from various fungal genera, it would be pertinent to study the compounds found in Psilocybe mycelia as potential naturally derived therapeutic targets.PMID:38094868 | PMC:PMC10716206 | DOI:10.3389/ffunb.2023.1295223

Adv Life Sci. 2023 Jun;10(2):200-209. Epub 2023 Jun 30.ABSTRACTBACKGROUND: Plant-derived endophytic actinobacteria are the center of attention due to their capacity to produce diverse antimicrobial and anticancer compounds and their metabolites influence plant growth.METHODS: In this study, 40 endophytic actinobacteria strains were isolated from the roots of eight medicinal plants used as folk medicine in South Asian region. The isolates were characterized morphologically, biochemically and physiologically and the genus level identification of the selected strains was done by 16SrRNA gene sequencing. In small scale cultivation (50ml broth), the isolates were grown in A-medium to prepare the crude extracts. These crude extracts were subsequently evaluated for their antimicrobial, anticancer and antioxidant activity and the metabolomics profile of each of the extract was determined by TLC and HPLC-UV/MS.RESULTS: The taxonomic studies showed that the isolates belong to the group actinobacteria based on their morphological and physiological characteristics and the 16SrRNA gene sequencing of the selected strains identified the genera including Streptomyces, Micromonospora and Nocardia. Cumulatively,53% of extracts exhibited anti-Gram-(+) activity,47% exhibited anti-Gram-(-) activity,32% exhibited antifungal activity and 30% were cytotoxic to PC3 and A549 cancer cell lines and most of the extracts have shown antioxidant activity greater than 50%. The metabolomics analysis predicted the presence of an array of low molecular weight metabolites and indicated the promising isolates in collection for further studies for novel bioactive metabolite isolation and structure elucidation.CONCLUSION: Overall the study provides an overview of the endophytic actinobacteria residing in the roots of the selected medicinal plants prevalent in south Asian region and their potential to produce the medicinally and biotechnologically useful compounds.PMID:38094851 | PMC:PMC10716798