Search Results (50)

Background: Alzheimer’s disease is a neurodegenerative disease of unknown etiology. Employing a combination of techniques such as imaging modalities, cognitive tests and medical history evaluations is considered to be a reliable approach in diagnosing the disease. A characteristic feature of Alzheimer’s disease is the gradual atrophy of the hippocampus, which is also seen with aging but at a faster rate in individuals suffering from the disease. The trigger responsible for the atrophy remains unknown. Methods: In this study, patients were assessed using MRI brain imaging, blood and cerebrospinal fluid analysis. Results: The findings indicate that the levels of erythrocytes in the cerebrospinal fluid have a statistically significant longitudinal predictive marker effect on hippocampal atrophy. Mean arterial pressure showed modest statistical significance in hippocampal volume only in the Alzheimer’s disease group. Conclusions: The results of the study point to the significance of cerebrospinal fluid homeostasis in terms of elements capable of causing hippocampal atrophy under chronic conditions. Monitoring of the presence of erythrocytes in cerebrospinal fluid and their related metabolites may be of clinical significance in the long-term management of Alzheimer’s disease. Full article

This study investigated the phytochemical profiles and bioactivities of two edible boletes from Southwestern China, Phlebopus portentosus and Butyriboletus roseoflavus. A total of 33 secondary metabolites, comprising 15 alkaloids, 4 pulvinic acid derivative pigments, and 14 ergosterols, were isolated and identified. To our best knowledge, boletesine A (1), boletesine B (2), and cis-xerocomic acid (16) were previously undescribed compounds. The new structures were established by extensive spectroscopic methods and chemical calculations. Compound 1 features a hitherto unknown hybrid skeleton formed between a 2-formylpyrrole-alkaloid and a dopacetic acid (DOPAC) via a Michael addition reaction. Bioactivity assays revealed the neuroprotective effects of compounds 18 and 19 against Aβ_25–35- or H₂O₂-induced toxicity. In a cytotoxic assay against a small panel of cancer cell lines, compound 9 exhibited significant activity against HeLa cells (IC₅₀ = 10.76 µM), while 33 demonstrated broad-spectrum cytotoxicity against Hela229, SGC7901, PC-3, and BEL7402 cells (IC_50s in the range of 20~30 µM). Of particular note is the anti-influenza virus activities against A/H3N2 and B/Victoria strains of compounds 22 and 26 (EC₅₀ values ranging from 3.6 to 9.6 µM). Along with these, compound 29 showed a moderate antiviral effect against coxsackievirus B3. These findings underscore the therapeutic potential of the two edible boletes in addressing neurodegenerative diseases, cancer, and viral infections, paving the way for their prospective applications in the development of functional foods and pharmaceuticals. Full article

Rapeseed (Brassica napus) is an important oilseed crop and yellow-seeded and black-seeded varieties have different metabolite profiles, which determines the quality and edibility of their oil. In this study, we performed a non-targeted metabolomics analysis of seeds from four rapeseed varieties at eight developmental stages. This analysis identified 4540 features, of which 366 were annotated as known metabolites. The content of these metabolites was closely related to seed developmental stage, with the critical period for seed metabolite accumulation being between 10 and 20 days after pollination. Through a comparative analysis, we identified 18 differentially abundant flavonoid features between yellow-seeded and black-seeded rapeseed varieties. By combining the flavonoid data with transcriptome data, we constructed a gene regulatory network that may reflect the accumulation of differentially abundant flavonoid features. Finally, we predicted 38 unknown features as being flavonoid features through molecular networking. These results provide valuable metabolomics information for the breeding of yellow-seeded rapeseed varieties. Full article

The ‘Jingbaili’ pear is a national geographical indication product of China, featuring an oblate shape and being rich in nutrients. But the quality of the ‘Jingbaili’ pear is unstable. Xenia can cause changes in the quality of pears, but the effect of xenia on the ‘Jingbaili’ pear is unknown, and its mechanism is still unclear. In order to clarify the effect of pollination on the fruit quality of the ’Jingbaili’ pear, this research pollinated ‘Jingbaili’ pear flowers with the pollen of ‘Yali’ (JY), ‘Suli’ (JS) and ‘Huangli’ (JH). The results indicated that the mass, transverse diameter and longitudinal diameter of the JY group were significantly higher than the JS group and JH group. On the other hand, the pears of the JY group and JS group obtained higher soluble sugar content. The aroma content of characteristic compounds was higher in the JY group than in the JS group and JH group. Multivariate analysis revealed significant differences in the nonvolatile metabolites among the JY group, JS group and JH group, potentially explaining the variations in the nutritional and flavor compounds of the pears. Furthermore, this research investigated metabolic changes in the pears during development and ripening under the three types of pollination. The results showed that amino acid metabolism differed among these pollination types during development. These differences may be the cause of the observed variations in the pears. This research clarified the effect of xenia on the nutritional components and flavor substances in the ‘Jingbaili’ pear and could provide data support for improving the quality of the ‘Jingbaili’ pear. Full article

Gastric cancer (GC) is the fifth most common cause of cancer-related death worldwide. Early detection is crucial for improving survival rates and treatment outcomes. However, accurate GC-specific biomarkers remain unknown. This study aimed to identify the metabolic differences between intestinal metaplasia (IM) and GC to determine the pathways involved in GC. A metabolic analysis of IM and tissue samples from 37 patients with GC was conducted using ultra-performance liquid chromatography with tandem mass spectrometry. Overall, 665 and 278 significant features were identified in the aqueous and 278 organic phases, respectively, using false discovery rate analysis, which controls the expected proportion of false positives among the significant results. sPLS-DA revealed a clear separation between IM and GC samples. Steroid hormone biosynthesis, tryptophan metabolism, purine metabolism, and arginine and proline metabolism were the most significantly altered pathways. The intensity of 11 metabolites, including N1, N2-diacetylspermine, creatine riboside, and N-formylkynurenine, showed significant elevation in more advanced GC. Based on pathway enrichment analysis and cancer stage-specific alterations, we identified six potential candidates as diagnostic biomarkers: aldosterone, N-formylkynurenine, guanosine triphosphate, arginine, S-adenosylmethioninamine, and creatine riboside. These metabolic differences between IM and GC provide valuable insights into gastric carcinogenesis. Further validation is needed to develop noninvasive diagnostic tools and targeted therapies to improve the outcomes of patients with GC. Full article

Background: Data suggest that metabolites, other than blood phenylalanine (Phe), better and independently predict clinical outcomes in patients with phenylketonuria (PKU). Methods: To find new biomarkers, we compared the results of untargeted lipidomics and metabolomics in treated adult PKU patients to those of matched controls. Samples (lipidomics in EDTA-plasma (22 PKU and 22 controls) and metabolomics in serum (35 PKU and 20 controls)) were analyzed using ultra-high-performance liquid chromatography and high-resolution mass spectrometry. Data were subjected to multivariate (PCA, OPLS-DA) and univariate (Mann–Whitney U test, p < 0.05) analyses. Results: Levels of 33 (of 20,443) lipid features and 56 (of 5885) metabolite features differed statistically between PKU patients and controls. For lipidomics, findings include higher glycerolipids, glycerophospholipids, and sphingolipids species. Significantly lower values were found for sterols and glycerophospholipids species. Seven features had unknown identities. Total triglyceride content was higher. Higher Phe and Phe catabolites, tryptophan derivatives, pantothenic acid, and dipeptides were observed for metabolomics. Ornithine levels were lower. Twenty-six metabolite features were not annotated. Conclusions: This study provides insight into the metabolic phenotype of PKU patients. Additional studies are required to establish whether the observed changes result from PKU itself, diet, and/or an unknown reason. Full article

The entero–mammary pathway is a specialized route that selectively translocates bacteria to the newborn’s gut, playing a crucial role in neonatal development. Previous studies report shared bacterial and archaeal taxa between human milk and neonatal intestine. However, the functional implications for neonatal development are not fully understood due to limited evidence. This study aimed to identify and characterize the microbiota and metabolome of human milk, mother, and infant stool samples using high-throughput DNA sequencing and FT-ICR MS methodology at delivery and 4 months post-partum. Twenty-one mothers and twenty-five infants were included in this study. Our results on bacterial composition suggest vertical transmission of bacteria through breastfeeding, with major changes occurring during the first 4 months of life. Metabolite chemical characterization sheds light on the growing complexity of the metabolites. Further data integration and network analysis disclosed the interactions between different bacteria and metabolites in the biological system as well as possible unknown pathways. Our findings suggest a shared bacteriome in breastfed mother–neonate pairs, influenced by maternal lifestyle and delivery conditions, serving as probiotic agents in infants for their healthy development. Also, the presence of food biomarkers in infants suggests their origin from breast milk, implying selective vertical transmission of these features. Full article

Several hepatic disorders are influenced by gut microbiota, but its role in idiosyncratic drug-induced liver injury (iDILI), whose main causative agent is amoxicillin–clavulanate, remains unknown. This pioneering study aims to unravel particular patterns of gut microbiota composition and associated metabolites in iDILI and iDILI patients by amoxicillin–clavulanate (iDILI-AC). Thus, serum and fecal samples from 46 patients were divided into three study groups: healthy controls (n = 10), non-iDILI acute hepatitis (n = 12) and iDILI patients (n = 24). To evaluate the amoxicillin–clavulanate effect, iDILI patients were separated into two subgroups: iDILI non-caused by amoxicillin–clavulanate (iDILI-nonAC) (n = 18) and iDILI-AC patients (n = 6). Gut microbiota composition and fecal metabolome plus serum and fecal bile acid (BA) analyses were performed, along with correlation analyses. iDILI patients presented a particular microbiome profile associated with reduced fecal secondary BAs and fecal metabolites linked to lower inflammation, such as dodecanedioic acid and pyridoxamine. Moreover, certain taxa like Barnesiella, Clostridia UCG-014 and Eubacterium spp. correlated with significant metabolites and BAs. Additionally, comparisons between iDILI-nonAC and iDILI-AC groups unraveled unique features associated with iDILI when caused by amoxicillin–clavulanate. In conclusion, specific gut microbiota profiles in iDILI and iDILI-AC patients were associated with particular metabolic and BA status, which could affect disease onset and progression. Full article

Liquid chromatography with mass spectrometry (LC-MS)-based metabolomics detects thousands of molecular features (retention time–m/z pairs) in biological samples per analysis, yet the metabolite annotation rate remains low, with 90% of signals classified as unknowns. To enhance the metabolite annotation rates, researchers employ tandem mass spectral libraries and challenging in silico fragmentation software. Hydrogen/deuterium exchange mass spectrometry (HDX-MS) may offer an additional layer of structural information in untargeted metabolomics, especially for identifying specific unidentified metabolites that are revealed to be statistically significant. Here, we investigate the potential of hydrophilic interaction liquid chromatography (HILIC)-HDX-MS in untargeted metabolomics. Specifically, we evaluate the effectiveness of two approaches using hypothetical targets: the post-column addition of deuterium oxide (D₂O) and the on-column HILIC-HDX-MS method. To illustrate the practical application of HILIC-HDX-MS, we apply this methodology using the in silico fragmentation software MS-FINDER to an unknown compound detected in various biological samples, including plasma, serum, tissues, and feces during HILIC-MS profiling, subsequently identified as N¹-acetylspermidine. Full article

Piperazic acid is a cyclic nonproteinogenic amino acid that contains a hydrazine N-N bond formed by a piperazate synthase (KtzT-like). This amino acid, found in bioactive natural products synthesized by non-ribosomal peptide synthetases (NRPSs), confers conformational constraint to peptides, an important feature for their biological activities. Genome mining of Streptomyces strains has been revealed as a strategy to identify biosynthetic gene clusters (BGCs) for potentially active compounds. Moreover, the isolation of new strains from underexplored habitats or associated with other organisms has allowed to uncover new BGCs for unknown compounds. The in-house “Carlos Sialer (CS)” strain collection consists of seventy-one Streptomyces strains isolated from the cuticle of leaf-cutting ants of the tribe Attini. Genomes from twelve of these strains have been sequenced and mined using bioinformatics tools, highlighting their potential to encode secondary metabolites. In this work, we have screened in silico those genomes, using KtzT as a hook to identify BGCs encoding piperazic acid-containing compounds. This resulted in uncovering the new BGC dpn in Streptomyces sp. CS113, which encodes the biosynthesis of the hybrid polyketide–depsipeptide diperamycin. Analysis of the diperamycin polyketide synthase (PKS) and NRPS reveals their functional similarity to those from the aurantimycin A biosynthetic pathway. Experimental proof linking the dpn BGC to its encoded compound was achieved by determining the growth conditions for the expression of the cluster and by inactivating the NRPS encoding gene dpnS2 and the piperazate synthase gene dpnZ. The identity of diperamycin was confirmed by High-Resolution Mass Spectrometry (HRMS) and Nuclear Magnetic Resonance (NMR) and by analysis of the domain composition of modules from the DpnP PKS and DpnS NRPS. The identification of the dpn BGC expands the number of BGCs that have been confirmed to encode the relatively scarcely represented BGCs for depsipeptides of the azinothricin family of compounds and will facilitate the generation of new-to-nature analogues by combinatorial biosynthesis. Full article

Restricted production of fungal secondary metabolites hinders the ability to conduct comprehensive research and development of novel biopesticides. Okaramine B from Penicillium demonstrates remarkable insecticidal efficacy; however, its biosynthetic yield is low, and its regulatory mechanism remains unknown. The present study found that the yield difference was influenced by fermentation modes in okaramine-producing strains and performed genomic and comparative transcriptome analysis of P. daleae strain NBP-49626, which exhibits significant features. The NBP-49626 genome is 37.4 Mb, and it encodes 10,131 protein-encoding genes. Up to 5097 differentially expressed genes (DEGs) were identified during the submerged and semi-solid fermentation processes. The oka gene cluster, lacking regulatory and transport genes, displayed distinct transcriptional patterns in response to the fermentation modes and yield of Okaramine B. Although transcription trends of most known global regulatory genes are inconsistent with those of oka, this study identified five potential regulatory genes, including two novel Zn(II)2Cys6 transcription factors, Reg2 and Reg19. A significant correlation was also observed between tryptophan metabolism and Okaramine B yields. In addition, several transporter genes were identified as DEGs. These results were confirmed using real-time quantitative PCR. This study provides comprehensive information regarding the regulatory mechanism of Okaramine B biosynthesis in Penicillium and is critical to the further yield improvement for the development of insecticides. Full article

Background: gastritis is a common stomach disease with a high global incidence and can potentially develop into gastric cancer. The treatment of gastritis focuses on medication or diets based on national guidelines. However, the specific diet that can alleviate gastritis remains largely unknown. Methods: we propose a microbiota-directed dietary strategy that investigates potential food factors using microbial exogenous metabolites. Given the current lack of understanding of the repeatable characteristics of gastric microbiota, we conducted a meta-analysis to identify the features of gastric bacteria. Local samples were collected as validation cohorts. Furthermore, RevEcoR was employed to identify bacteria’s exogenous metabolites, and FooDB was used to retrieve foods that can target specific bacteria. Results: Bacteroides, Weissella, Actinomyces, Atopobium, Oribacterium, Peptostreptococcus, and Rothia were biomarkers between superficial gastritis (SG) and atrophic gastritis (AG) (AG_N) without H. pylori infection, whereas Bacillus, Actinomyces, Cutibacterium, Helicobacter, Novosphingobium, Pseudomonas, and Streptococcus were signatures between SG and AG (AG_P) with H. pylori infection. According to the exogenous metabolites, adenosyloobalamin, soybean, common wheat, dates, and barley were regarded as potential candidates for AG_N treatment, while gallate was regarded as a candidate for AG_P treatment. Conclusions: this study firstly profiled the gastric microbiota of AG and SG with or without H. pylori and provided a recommended diet for global AG according to exogenous metabolites. Full article

Non-alcoholic fatty liver disease is a multifaceted disease that progresses through multiple phases; it involves metabolic as well as structural changes. These alterations can be measured directly or indirectly through blood, non-invasive imaging, and/or tissue analyses. While some studies have evaluated the correlations between two sets of measurements (e.g., histopathology with cross-sectional imaging or blood biomarkers), the interrelationships, if any, among histopathology, clinical blood profiles, cross-sectional imaging, and metabolomics in a pediatric cohort remain unknown. We created a multiparametric clinical MRI–histopathologic NMR network map of pediatric NAFLD through multimodal correlation networks, in order to gain insight into how these different sets of measurements are related. We found that leptin and other blood markers were correlated with many other measurements; however, upon filtering out the blood biomarkers, the network was decomposed into three independent hubs centered around histopathological features, each with associated MRI and plasma metabolites. These multi-modality maps could serve as a framework for characterizing disease status and progression and could potentially guide medical interventions. Full article

The analysis of metabolite mediators has allowed a broader understanding of disease mechanisms. Experimental evidence indicates that metabolic rewiring is a key feature of inflammatory cells to restore tissue homeostasis upon damage. Over the last two decades, next-generation sequencing techniques have offered the possibility of looking at the genome-wide effect of the exposure of inflammatory cells to external stimuli. During gout flares, monosodium urate crystals activate a distinct metabolic profile and inflammatory transcriptional program in inflammatory cells. The extracellular signals are transduced through distinct signalling pathways, which are regulated by non-coding RNA and DNA sequences, and modification of histones. During response to inflammatory stimuli, changes in the abundance of metabolic mediators can regulate the activation of histones and of chromatin remodellers. The interplay between metabolic changes by MSUc, the regulation of epigenetic changes and the activation of transcription factor networks in inflammatory cells remains unknown. A better understanding of the interplay between metabolites and how it alters inflammatory response may provide novel insights into disease mechanisms during gout. In this review, we aim to provide a deeper understanding of the current view of how metabolic deregulation could alter the epigenetic landscape of inflammatory cells during gout. Full article

Chickpea is the second-most-cultivated legume globally, with India and Australia being the two largest producers. In both of these locations, the crop is sown on residual summer soil moisture and left to grow on progressively depleting water content, finally maturing under terminal drought conditions. The metabolic profile of plants is commonly, correlatively associated with performance or stress responses, e.g., the accumulation of osmoprotective metabolites during cold stress. In animals and humans, metabolites are also prognostically used to predict the likelihood of an event (usually a disease) before it occurs, e.g., blood cholesterol and heart disease. We sought to discover metabolic biomarkers in chickpea that could be used to predict grain yield traits under terminal drought, from the leaf tissue of young, watered, healthy plants. The metabolic profile (GC-MS and enzyme assays) of field-grown chickpea leaves was analysed over two growing seasons, and then predictive modelling was applied to associate the most strongly correlated metabolites with the final seed number plant⁻¹. Pinitol (negatively), sucrose (negatively) and GABA (positively) were significantly correlated with seed number in both years of study. The feature selection algorithm of the model selected a larger range of metabolites including carbohydrates, sugar alcohols and GABA. The correlation between the predicted seed number and actual seed number was R² adj = 0.62, demonstrating that the metabolic profile could be used to predict a complex trait with a high degree of accuracy. A previously unknown association between D-pinitol and hundred-kernel weight was also discovered and may provide a single metabolic marker with which to predict large seeded chickpea varieties from new crosses. The use of metabolic biomarkers could be used by breeders to identify superior-performing genotypes before maturity is reached. Full article