Metabolomics最新文献

Introduction: Tempeh is an antioxidant-rich soybean fermentation product from Java, Indonesia. Cooking methods have an impact on the nutritional value and bioactivity of food.

Objective: This study aims to investigate how the cooking process affects the metabolites and antioxidant activity in tempeh using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS).

Methods: A nontargeted UHPLC-HRMS metabolomics and chemometric analysis were used to evaluate metabolite profiles and antioxidant activity changes because of food processing in tempeh.

Results: The score plots of tempeh produced by boiling and frying methods displayed a distinct separation from raw tempeh, revealing that the cooking process altered the metabolite composition of tempeh. Due to processing, L-glutamic acid, L-pyroglutamic acid, DL-glutamine, and D-( +)-proline became the most affected metabolites on tempeh. There were 70 metabolites that showed antioxidant activity using the DPPH assay; 23 metabolites significantly differ from DPPH and control for antioxidant activity for all processing tempeh. Metabolites with significantly different antioxidant activity in raw and processed tempeh were dominated by flavonoids, vitamin E, and bioactive lipids.

Conclusion: The DPPH antioxidant assay using UHPLC-HRMS is promising as a fast antioxidant assay by simplifying the conventional DPPH antioxidant assay. Further, it can be used to identify the name of metabolites responsible for its antioxidant activity.

Introduction: Atopic dermatitis (AD) is a common chronic inflammatory dermatosis. However, the exact molecular mechanism underlying the development of AD remain largely unclear.

Objective: To investigate comprehensive metabolomic alterations in serum and skin tissue between 2,4-dinitrofluorobenzene (DNFB)-induced AD-like mice and healthy controls, aiming to identify the potential disease biomarkers and explore the molecular mechanisms of AD.

Methods: In this study, Untargeted metabolomics analysis was used to investigate both skin and serum metabolic abnormalities of 2,4-dinitrofluorobenzene (DNFB)-induced AD-like mice. Then, the metabolic differences among the groups were determined through the application of multivariate analysis. Additionally, the selection of predictive biomarkers was accomplished using the receiver operating characteristic (ROC) module.

Results: Our findings showed that levels of 220 metabolites in the skin and 94 metabolites in the serum were different in AD-like mice that were treated with DNFB compared to control mice. Uracil, N-Acetyl-L-methionine, deoxyadenosine monophoosphate, 2-acetyl-l-alkyl-sn-glycero-3-phosphcholine, and prostaglandin D2 are considered potential biomarkers of AD as obtained by integrating skin and serum differential metabolite results. Metabolomic data analysis showed that the metabolic pathways in which skin and serum are involved together include histidine metabolism, pyrimidine metabolism, alanine, aspartate, and glutamate metabolism.

Conclusion: Our research explained the possible molecular mechanism of AD at the metabolite level and provided potential targets for the development of clinical drugs for AD.

Introduction: A better understanding of the physiological response of silage maize to a mild reduction in nitrogen (N) fertilization and the identification of predictive biochemical markers of N utilization efficiency could contribute to limit the detrimental effect of the overuse of N inputs.

Objectives: We integrated phenotypic and biochemical data to interpret the physiology of maize in response to a mild reduction in N fertilization under agronomic conditions and identify predictive leaf metabolic and proteic markers that could be used to pilot and rationalize N fertilization.

Methods: Eco-physiological, developmental and yield-related traits were measured and complemented with metabolomic and proteomic approaches performed on young leaves of a core panel of 29 European genetically diverse dent hybrids cultivated in the field under non-limiting and reduced N fertilization conditions.

Results: Metabolome and proteome data were analyzed either individually or in an integrated manner together with eco-physiological, developmental, phenotypic and yield-related traits. They allowed to identify (i) common N-responsive metabolites and proteins that could be used as predictive markers to monitor N fertilization, (ii) silage maize hybrids that exhibit improved agronomic performance when N fertilization is reduced.

Conclusions: Among the N-responsive metabolites and proteins identified, a cytosolic NADP-dependent malic enzyme and four metabolite signatures stand out as promising markers that could be used for both breeding and agronomic purposes.

Objectives: While some metals have been reported as carcinogens or potential carcinogens, only few modern-standard datasets including a large number of elements are available. The present analysis established a first trace elements spectrum by relating the concentration of metals and trace elements in the serum of sarcoma patients with survival data.

Methods: Patients with sarcoma and controls were retrospectively selected from the International Sarcoma Kindred Study database (ISKS). As part of the ISKS study, blood samples were prospectively collected at the Leon Bérard Cancer Center from February 2012 to July 2019. Stable specimens and copper isotopes (⁶⁵Cu/⁶³Cu) were analyzed using Triple Quadrupole Inductively Coupled Plasma Mass Spectrometer (ICP-MS) and the Multicollector MC-ICP-MS Nu Plasma HR 500. Wilcoxon rank sum test, log-rank test, and multivariate Cox regression models were used for statistics.

Results: In total, 151 patients and 59 healthy controls were included. At the time of blood sample collection, 62% of patients had locally advanced or metastatic disease. Copper (Cu), copper/zinc (Cu/Zn) and potassium/rubidium (K/Rb) ratio were significantly higher in patients compared to controls and were also significantly higher in patients with advanced compared to early-stage sarcoma. Whereas S and Se were significantly correlated in patients, no correlation was observed in controls. Importantly, levels of K, Rb, Se, Fe, P, Si, S, δ⁶⁵Cu, Cu, S/Se and Cu/Zn ratio were independently associated with overall survival.

Conclusions: These results depict the metallomic spectrum in sarcoma and highlight substantial variation associated with survival, enhancing our understanding of sarcoma's biology.

Background: Pulmonary tuberculosis (PTB) exacerbation can lead to respiratory failure, multi-organ failure, and symptoms related to central nervous system diseases. The purpose of this study is to screen biomarkers and metabolic pathways that can predict the progression of PTB, and to verify the role of the metabolic enzyme xanthine oxidase (XO) in the progression of PTB.

Methods: To explore the biomarkers and mechanisms underlying the progression of PTB, plasma metabolomics sequencing was conducted on patients with severe PTB, non-severe PTB, and healthy individuals. Screening differential metabolites and metabolic pathways that can predict the progression of PTB, and verifying the function and mechanism of action of XO through experiments.

Results: The purine metabolism, sphingolipid metabolism, and amino acid metabolism between the three groups differ. In patients with severe PTB, the levels of xanthosine and hypoxanthine are increased, while the levels of D-tryptophan, dihydroceramide and uric acid are decreased. Inhibition of XO activity has been observed to reduce the levels of tumor necrosis factor (TNF-α), interleukin-1 beta (IL-1β), and interleukin-6 (IL-6), as well as to suppress the production of reactive oxygen species (ROS) and the activation of the NF-κB pathway, while also promoting the growth of MTB within cells.

Conclusion: D-tryptophan, xanthosine, and dihydroceramide can be utilized as biomarkers for progression of PTB, assisting in the evaluation of disease progression, and XO stands out as a potential therapeutic target for impeding the progression of PTB.

Introduction: Human metabolomics has made significant strides in understanding metabolic changes and their implications for human health, with promising applications in diagnostics and treatment, particularly regarding the gut microbiome. However, progress is hampered by issues with data comparability and reproducibility across studies, limiting the translation of these discoveries into practical applications.

Objectives: This study aims to evaluate the fit-for-purpose of a suite of human stool samples as potential candidate reference materials (RMs) and assess the state of the field regarding harmonizing gut metabolomics measurements.

Methods: An interlaboratory study was conducted with 18 participating institutions. The study allowed for the use of preferred analytical techniques, including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR).

Results: Different laboratories used various methods and analytical platforms to identify the metabolites present in human stool RM samples. The study found a 40% to 70% recurrence in the reported top 20 most abundant metabolites across the four materials. In the full annotation list, the percentage of metabolites reported multiple times after nomenclature standardization was 36% (LC-MS), 58% (GC-MS) and 76% (NMR). Out of 9,300 unique metabolites, only 37 were reported across all three measurement techniques.

Conclusion: This collaborative exercise emphasized the broad chemical survey possible with multi-technique approaches. Community engagement is essential for the evaluation and characterization of common materials designed to facilitate comparability and ensure data quality underscoring the value of determining current practices, challenges, and progress of a field through interlaboratory studies.

Introduction: The placenta plays influential role in the fetal development of mammals. But how the metabolic need of the fetal organs is related to that of the placenta, and whether this relationship is influenced by the sex of the fetus remain poorly understood.

Objectives: This study used pigs to investigate metabolomic signatures of male and female fetal organs, and determine the relevance of gene expression of the placenta and brain to the metabolism of peripheral organs.

Methods: Untargeted metabolomics analysis was performed with the day-45 placenta, kidney, heart, liver, lung and brain of male and female pig fetuses to model sex differences in the metabolism of the peripheral organs relative to that of the brain and placenta. Transcriptomic analysis was performed to investigate the expression of metabolic genes in the placenta and fetal brain of both sexes.

Results: The results of this study show that the fetoplacental metabolic regulation was not only influenced by the fetal sex but also dependent on the metabolic requirement of  the individual organs of the fetus. Neural network modeling of metabolomics data revealed differential relationship of the metabolic changes of the peripheral organs with the placenta and fetal brain between males and females. RNA sequencing further showed that genes associated with the metabolism of the peripheral organs were differentially expressed in the placenta and fetal brain.

Conclusion: The findings of this study suggest a regulatory role of the fetal brain and placenta axis in the sex-bias metabolism of the peripheral organs.

Background: The global incidence of hypertension, a condition of elevated blood pressure, is rising alarmingly. According to the World Health Organization's Qatar Hypertension Profile for 2023, around 33% of adults are affected by hypertension. This is a significant public health concern that can lead to serious health complications if left untreated. Metabolic dysfunction is a primary cause of hypertension. By studying key biomarkers, we can discover new treatments to improve the lives of those with high blood pressure.

Aims: This study aims to use explainable artificial intelligence (XAI) to interpret novel metabolite biosignatures linked to hypertension in Qatari Population.

Methods: The study utilized liquid chromatography-mass spectrometry (LC/MS) method to profile metabolites from biosamples of Qatari nationals diagnosed with stage 1 hypertension (n = 224) and controls (n = 554). Metabolon platform was used for the annotation of raw metabolite data generated during the process. A comprehensive series of analytical procedures, including data trimming, imputation, undersampling, feature selection, and biomarker discovery through explainable AI (XAI) models, were meticulously executed to ensure the accuracy and reliability of the results.

Results: Elevated Vanillylmandelic acid (VMA) levels are markedly associated with stage 1 hypertension compared to controls. Glycerophosphorylcholine (GPC), N-Stearoylsphingosine (d18:1/18:0)*, and glycine are critical metabolites for accurate hypertension prediction. The light gradient boosting model yielded superior results, underscoring the potential of our research in enhancing hypertension diagnosis and treatment. The model's classification metrics: accuracy (78.13%), precision (78.13%), recall (78.13%), F1-score (78.13%), and AUROC (83.88%) affirm its efficacy. SHapley Additive exPlanations (SHAP) further elucidate the metabolite markers, providing a deeper understanding of the disease's pathology.

Conclusion: This study identified novel metabolite biomarkers for precise hypertension diagnosis using XAI, enhancing early detection and intervention in the Qatari population.

Introduction: Breast Cancer (BC) is one of the most diagnosed malignancies among women and the second leading cause of cancer related death in North America. Triple Negative BC (TNBC), one of the most severe subtypes of BC, is extremely aggressive and has a higher chance of occurrence in women under 50 years of age. Due to a lack of regular mammographic testing in women under 50, many individuals with TNBC are diagnosed late which can decrease their survival rate. Currently, liquid biopsy is being investigated as a potentially less-invasive alternative to traditional breast tissue biopsy, but this approach is not completely reliable. Blood contains extracellular vesicles (EVs), which carry biomolecular cargo and play a role in BC progression and metastasis. Examination of small EVs could potentially yield metabolite biomarkers for early BC diagnosis.

Objective: We aim to study metabolites in small EVs to find biomarkers for BC diagnosis.

Methods: In this work, an untargeted nano-LC MS/MS metabolomics approach was used to analyze metabolites from small EVs derived from metastatic MDA-MB-231 and compare it with a non-cancerous MCF10A cell line.

Results: Two metabolites, LysoPC 22:6/0:0 and N-acetyl-L-Phenylalanine, unique to sEVs of MDA-MB-231, were identified, validated, and proposed as potential BC biomarkers.

Conclusion: Metabolites from sEVs may be used for BC diagnosis.

Background: Chronic kidney disease (CKD) is common in patients with diabetes mellitus (DM). Volatile organic compounds (VOCs) are widespread pollutants that may impact DM development.

Objective: This study aims to explore the association between urinary VOC metabolites and CKD in patients with DM.

Methods: Adult National Health and Nutrition Examination Survey (NHANES) 2011 to 2018 participants with DM were included in this study. CKD was defined as an estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m² or urine albumin-to-creatinine ratio (UACR) ≥ 30 mg/g. Multivariable regression models were used to analyze the associations between urinary VOC metabolites and CKD.

Results: A total of 1,295 participants with DM and a mean age of 59 years were included. After adjustment for demographic and clinical characteristics, elevated levels of N-acetyl-S-(2-carbamoylethyl)-L-cysteine (AAMA) (tertile 2: adjusted odds ratio (aOR)  =   1.81, 95% confidence interval (CI): 1.15-2.85, p  =  0.012), N-acetyl-S-(N-methylcarbamoyl)-L-cysteine (AMCC) (tertile 2: aOR   =  1.84, 95% CI: 1.10-3.08, p  =  0.021), DHBMA (tertile 3: aOR  =  1.93, 95% CI: 1.12-3.35, p  =   0.020), and phenylglyoxylic acid (PGA) (tertile 3: aOR   =  1.71, 95% CI: 1.11-2.63, p  =  0.017) were significantly associated with increased likelihood of CKD.

Conclusion: Specific urinary VOC metabolite levels are positively associated with an increased risk of CKD in patients with DM. These findings suggest that monitoring urinary VOC metabolites could be important for the prevention and management of CKD in this population. Future longitudinal studies should focus on establishing causality and elucidating the underlying mechanisms of these associations.