Metabolomics最新文献

Plants of the Himalayan region produce a wide spectrum of metabolites whose abundance is strongly influenced by species identity, genotype, developmental stage, and environmental factors such as altitude and temperature. These metabolites are of major relevance to the food, cosmetic, and pharmaceutical industries, yet their quality and composition often fluctuate with changing climatic conditions. This review synthesizes available evidence on the influence of environmental gradients particularly altitude and temperature on metabolite production in Himalayan plants, with a special emphasis on seabuckthorn (Hippophae spp.), a species of considerable commercial and pharmacological value. Unlike broader reviews of plant environment interactions, this work focuses specifically on Himalayan taxa, identifies emerging trends across metabolite classes (phenolics, flavonoids, alkaloids, terpenoids, and fatty acids), and highlights the adaptive significance of these compounds under climatic stress. In addition, 16 threatened medicinal plants of the Himalaya are considered, for which information on metabolite responses to environmental variables remains scarce. By integrating findings across species and metabolite groups, this review provides new insights into how Himalayan plants adapt to climatic challenges. Such knowledge is critical for guiding conservation strategies, optimizing cultivation practices, and ensuring the sustainable utilization of these species for nutraceutical and therapeutic applications.

Introduction: Since the early 2000s, metabolomics has grown rapidly, becoming integral to fields like life sciences, health, and environmental research. This expansion has led to the formation of national and international societies, such as Germany's DGMet, to tackle emerging challenges. One of DGMet's goals is to improve measurement quality by assessing community needs for harmonization and standardization. A recent survey within the German-speaking community aimed to identify current practices and gaps in the use of chemical standards and reference materials, to guide future standardization efforts and collaborative initiatives.

Methods: An online survey was conducted between June 2023 and April 2024. The survey consisted of 38 key questions and was open to research institutions from Germany, Austria, and Switzerland.

Results: The survey was accessed by 68 laboratories, with 23 institutes providing complete or partial responses (34% response rate), which is comparable to rates reported in similar surveys within the metabolomics and lipidomics communities. Respondents were mainly experienced researchers from Germany, focusing mainly on health-related ("red") metabolomics, as indicated by 78% of the respondents, followed by microbial ("grey", 48%) and plant ("green", 39%) metabolomics (multiple answers possible). The use of targeted methods was reported more frequently (91%) than that of non-targeted methods (78%), whereas metabolite fractions studied were equally split between polar, midpolar and lipid fractions (83% each). Human (74%), mouse (61%) and Arabidopsis (30%) were the most frequently studied organisms. Most participants used synthetic chemical standards for instrument qualification (83%), calibration (78%), and metabolite identification (74%), while matrix reference materials were mainly applied for quality control (52%) and method validation (44%). There was a strong demand for more standards, especially for metabolite identification and quantification, with cost being a major barrier, particularly for isotopically labelled standards and certified reference materials.

Conclusions: Valuable insights into the use of standards and reference materials within the German-speaking metabolomics community were obtained. Moving forward, the community should address critical gaps in metabolomics standardization. To achieve this, it must share its knowledge, articulate its needs clearly, and actively engage in joint efforts with national metrology institutes and international standardization initiatives.

Introduction: Identifying the phytochemistry underpinning a plant's observed therapeutic benefits is essential for understanding mechanisms of action and developing novel therapeutics. More recent efforts fusing global metabolomics and multivariate predictive modeling have improved compound discovery; however, these models rely on chemical variations between samples, which often necessitates at least one round of fractionation and may result in compound loss or degradation.

Objectives: This study uses multiple whole botanical extracts to explore whether a metabolome-wide association study approach can accurately identify bioactive phytochemicals without prior fractionation.

Methods: We employed 40 Ocimum extracts with a range of IC₅₀ levels against HT-29 cells in an in vitro MTT assay and combined this data with untargeted UPLC-MS/MS metabolomics for biochemometric modeling of the potential bioactives. Multiple chemometric tools and statistical filters were employed to improve feature selection.

Results: The metabolomic profiles resulted in ca. 1600 metabolite features; implementing source-based filters, followed by LASSO dimension reduction, improved the reliability of Partial Least Squares (PLS) bioactivity predictions. The resulting model highlighted four biomarkers positively correlated with activity, one of which was putatively identified as gallic acid. Gallic acid's cytotoxicity against HT-29 cells was confirmed with the purified compound.

Conclusion: This study results demonstrated that predictive modeling of botanicals using a metabolome-wide association study of extracts with no fractionation was capable of identifying biologically active compounds.

Purpose: Fish aquaculture faces sustainable production challenges. Among them are the pathogenic outbreaks that can compromise the health of the stocks from various perspectives, including broodstock reproduction. This study focused on identifying the metabolite alterations produced after a bacterial infection by Vibrio anguillarum in the gonads of European seabass (Dicentrarchus labrax). Sex-related response to the infection challenge was studied using a metabolomics approach.

Method: The metabolome of testes and ovaries of adult fish were extracted and analyzed after 48 h of bacterial exposure by ultra-high-performance liquid chromatography-mass spectrometer using negative-mode electrospray ionization (ESI) (UHPLC-MS, Vanquish Horizon UHPLC coupled to a Thermo Fisher Scientific Q-Exactive HF). To further decipher the molecular events, metabolomic and transcriptomic data were interconnected.

Results: In total, 97 metabolites were identified. In the ovary, uric acid, O-phosphoethanolamine, allantoin, and acetoacetic acid were more represented. By contrast, nine metabolites were altered after the infection in testes, including uridine, N-acetylglucosamine-6-Phosphate, and Gamma-aminobutyric acid (GABA). The most abundant metabolic cascades triggered by infection in ovaries were related to glyoxylate and dicarboxylate metabolism, nitrogen metabolism, and purine metabolism, while in testes, we observed changes in glycerolipid metabolism, glycerophospholipid metabolism, and galactose metabolism.

Conclusion: The present results demonstrate, for the first time in fish, that changes in metabolic pathways induced following infection are sex-dependent. The findings will help develop sex-specific immune therapies, identify resistant phenotypes, and improve aquaculture infection protocols.

Objective: Metabolomic risk factors for dementia are under studied, especially in Latinos. We examined the relationship between plasma metabolomic profiles and a Magnetic-Resonance Imaging (MRI)-based markers of brain aging in a cohort of older adult Puerto Ricans residing in the greater Boston area.

Methods: We used multiple linear regression, adjusted for covariates, to examine the association between metabolite concentration and MRI-derived brain age deviation. Metabolites were measured at baseline with untargeted metabolomic profiling (Metabolon, Inc). Brain age deviation was calculated at wave 4 (~ 9 years from Boston Puerto Rican Health Study (BPRHS) baseline) as chronologic age, minus MRI-estimated brain age, representing the rate of biological brain aging relative to chronologic age. We also examined if metabolites associated with brain age deviation were similarly associated with hippocampal volume and global cognitive function.

Results: Several metabolites, including isobutyrylcarnitine, propionylcarnitine, phenylacetylglutamine, phenylacetylcarnitine (acetylated peptides), p-cresol-glucuronide, phenylacetylglutamate, and trimethylamine N-oxide (TMAO) were associated with worse brain aging. Taurocholate sulfate, a bile salt, was marginally associated with better brain aging. Most metabolites with negative associations with brain age deviation also were inversely, although not significantly, associated with hippocampal volume and cognitive function.

Conclusion: The metabolites associated with brain aging in this study are generally consistent with prior literature and highlight the potential role of TMAO, BCAA and other microbially derived metabolites in dementia.

Background: The dairy cow is an integral part of the global agricultural economy and plays a vital role in human nutrition. Compromised health in dairy cows leads to substantial economic losses and adverse environmental impacts. Understanding cow physiology and the etiology of common diseases is essential for developing effective strategies to improve animal health and mitigate negative consequences. Over the past two decades, metabolomics has emerged as a powerful approach not only for assessing and monitoring the health status of dairy cows but also for predicting and diagnosing diseases.

Aim of review: To review current metabolomics research aimed at improving the understanding of cow health status and metabolic changes associated with common diseases in dairy cows.

Key scientific concept of review: This review discusses findings from nearly 100 studies that report metabolic changes linked to health status and common diseases in dairy cows. It focuses on disease-specific metabolite alterations across different biofluids in conditions such as mastitis, lameness, acidosis, ketosis, and hypocalcemia, highlighting their relevance to pathological significance. The review also discusses how metabolomics can support early diagnosis and examines metabolic shifts related to physiological factors such as pregnancy, lactation, transition period, and parity.

Introduction: Robust evidence endorsed by the International Agency for Research on Cancer demonstrates that excess body fat represents a risk for the development of at least 13 types of cancer.

Objective: We investigated the serum of individuals with obesity who had no history of cancer (either personal or familial) to identify biomarkers.

Methods: 45 individuals were included in this study; they did not show significant differences regarding age, sex, or physical activity. A quality-of-life questionnaire was administered to all participants, revealing that the obese group self-reported difficulties in functional capacity and a greater association with comorbidities, notably hypertension. FTIR, metabolomic, and lipidomic analyses were performed to identify spectral peaks, metabolic, and lipids differentiating between the NO (non-obese) and OB (obese) groups.

Results: The identified peaks are predominantly associated with profiles of lipids, carbohydrates, and nitrogenous compounds. A total of six metabolites and lipids were identified at different levels in the serum of the OB group that have a direct relationship with the development or metabolism of cancer cells (three metabolites and three lipids). Among these, some suggest a reduced likelihood of cancer development, while others indicate an increased potential for cancer development. In this context, we can highlight two substances: the metabolite 4-Hydroxyphenylglyoxylate, which is reduced in the serum of individuals with obesity, and the lipid Glycidyl palmitate, which is elevated in individuals with obesity.

Conclusion: 4-Hydroxyphenylglyoxylate and Glycidyl palmitate can be used as biomarkers for cancer and obesity correlation. New experiments manipulating these substances may contribute to a better understanding of their interactions with cancer cells.

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) (formerly Non-Alcoholic Fatty Liver Disease, NAFLD) encompasses a spectrum of metabolic disorders ranging from isolated steatosis to Metabolic Dysfunction-Associated Steatohepatitis (MASH), potentially progressing to cirrhosis and hepatocellular carcinoma (HCC). In this study, we investigated metabolic changes in MASLD by analysing plasma lipidomics and metabolomics profiles from 315 biopsy-characterized patients. We observed significant alterations in alanine/serine (ala/ser) ratio, 1-deoxysphingolipids, alanine aminotransferase (ALT), and waist/hip ratio (whr) between patients with and without MASH. These findings highlight a close interplay between amino acid metabolism and sphingolipid biosynthesis in MASLD progression. The shift in ala/ser ratio particularly distinguished non-MASH from borderline MASH patients, suggesting that early metabolic disruptions precede overt liver damage. Additionally, elevated branched-chain and aromatic amino acids correlated with steatosis severity, reinforcing the central role of amino acid dysregulation in MASLD. While a simple model combining ALT, ala/ser ratio, and whr showed some potential to support risk stratification, the primary significance of our findings lies in the mechanistic insights into metabolic dysfunction. In conclusion, this study emphasizes the importance of metabolic network alterations in MASLD and points toward future opportunities for both mechanistic research and the development of supportive diagnostic strategies.