Metabolomics最新文献

Background: The National Cancer Institute issued a Request for Information (RFI; NOT-CA-23-007) in October 2022, soliciting input on using and reusing metabolomics data. This RFI aimed to gather input on best practices for metabolomics data storage, management, and use/reuse.

Aim of review: The nuclear magnetic resonance (NMR) Interest Group within the Metabolomics Association of North America (MANA) prepared a set of recommendations regarding the deposition, archiving, use, and reuse of NMR-based and, to a lesser extent, mass spectrometry (MS)-based metabolomics datasets. These recommendations were built on the collective experiences of metabolomics researchers within MANA who are generating, handling, and analyzing diverse metabolomics datasets spanning experimental (sample handling and preparation, NMR/MS metabolomics data acquisition, processing, and spectral analyses) to computational (automation of spectral processing, univariate and multivariate statistical analysis, metabolite prediction and identification, multi-omics data integration, etc.) studies.

Key scientific concepts of review: We provide a synopsis of our collective view regarding the use and reuse of metabolomics data and articulate several recommendations regarding best practices, which are aimed at encouraging researchers to strengthen efforts toward maximizing the utility of metabolomics data, multi-omics data integration, and enhancing the overall scientific impact of metabolomics studies.

Introduction: Kidney transplantation (KTx) necessarily conveys an ischemia/reperfusion (I/R) process, which impacts on allograft outcomes. Delayed graft function (DGF) is defined as a non-decrease of serum creatinine by at least 10% daily on 3 consecutive days during the first 7 days post-KTx. DGF significantly conditions both short- and long-term graft outcomes. Still there is a lack of DGF predictive biomarkers.

Objectives: This study aimed to explore the potential of kidney graft perfusate metabolomics to predict DGF occurrence.

Methods: 49 human perfusates from grafts categorized upon donor type [donation after brain death (DBD)/donation after circulatory death (DCD)] and DGF occurrence and 19 perfusates from a murine model classified upon death type (DBD/DCD) were collected and analyzed by NMR-based metabolomics.

Results: The multivariate analysis of the murine data highlighted significant differences between perfusate metabolomes of DBD versus DCD. These differences were similarly observed in the human perfusates. After correcting for the type of donor, multivariate analysis of human data demonstrated a metabolomics signature that could be correlated with DGF occurrence.

Conclusions: The metabolome of kidney grafts is influenced by the donor's type in both human and pre-clinical studies and could be correlated with DGF in the human DBD cohort. Thus, metabolomic analysis of perfusate applied prior to KTx may represent a new predictive tool for clinicians in a more personalized management of DGF. Moreover, our data paves the way to better understand the impact of donor's types on the biochemical events occurring between death and the hypothermic storage.

Introduction: Studies of gastrointestinal physiology and the gut microbiome often consider the influence of intestinal region on experimental endpoints. However, this same consideration is not often applied to the gut metabolome. Understanding the contribution of gut regionality may be critically important to the rapidly changing metabolic environments, such as during pregnancy.

Objectives: We sought to characterize the difference in the gut metabolome in pregnant mice stratified by region-comparing the small intestine, cecum, and feces. Pre-pregnancy feces were collected to understand the influence of pregnancy on the fecal metabolome.

Methods: Feces were collected from CD-1 female mice before breeding. On gestation day (GD) 18, gut contents were collected from the small intestine, cecum, and descending colon. Metabolites were analyzed with LC-MS/MS using the Biocrates MetaboINDICATOR™ MxP® Quant 500 kit.

Results: Of the 104 small molecule metabolites meeting analysis criteria, we found that 84 (81%) were differentially abundant based on gut region. The most significant regional comparison observed was between the cecum and small intestines, with 52 (50%) differentially abundant metabolites. Pregnancy itself altered 41 (39.4%) fecal small molecule metabolites.

Conclusions: The regional variation observed in the gut metabolome are likely due to the microbial and physiological differences between the different parts of the intestines. Additionally, pregnancy impacts the fecal metabolome, which may be due to evolving needs of both the dam and fetus.

Introduction: Changes in the categories and concentrations of salivary metabolites may be closely related to oral, intestinal or systemic diseases. To study salivary metabolites, the first analytical step is to extract them from saliva samples as much as possible, while reducing interferences to a minimum. Frequently used extraction methods are protein precipitation (PPT), liquid-liquid extraction (LLE) and solid-phase extraction (SPE), with various organic solvents. The types and quantities of metabolites extracted with different methods may vary greatly, but few studies have systematically evaluated them.

Objectives: This study aimed to select the most suitable methods and solvents for the extraction of saliva according to different analytical targets.

Methods: An untargeted metabolomics approach based on liquid chromatography-mass spectrometry was applied to obtain the raw data. The numbers of metabolites, repeatability of the data and intensities of mass spectrometry signals were used as evaluation criteria.

Results: PPT resulted in the highest coverage. Among the PPT solvents, acetonitrile displayed the best repeatability and the highest coverage, while acetone resulted in the best signal intensities for the extracted compounds. LLE with the mixture of chloroform and methanol was the most suitable for the extraction of small hydrophobic compounds.

Conclusion: PPT with acetonitrile or acetone was recommended for untargeted analysis, while LLE with the mixture of chloroform and methanol was recommended for small hydrophobic compounds.

Background: Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

Aim of the review: The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

Key scientific concepts of review: Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Introduction: Sepsis is a highly morbid condition characterized by multi-organ dysfunction resulting from dysregulated inflammation in response to acute infection. Mitochondrial dysfunction may contribute to sepsis pathogenesis, but quantifying mitochondrial dysfunction remains challenging.

Objective: To assess the extent to which circulating markers of mitochondrial dysfunction are increased in septic shock, and their relationship to severity and mortality.

Methods: We performed both full-scan and targeted (known markers of genetic mitochondrial disease) metabolomics on plasma to determine markers of mitochondrial dysfunction which distinguish subjects with septic shock (n = 42) from cardiogenic shock without infection (n = 19), bacteremia without sepsis (n = 18), and ambulatory controls (n = 19) - the latter three being conditions in which mitochondrial function, proxied by peripheral oxygen consumption, is presumed intact.

Results: Nine metabolites were significantly increased in septic shock compared to all three comparator groups. This list includes N-formyl-L-methionine (f-Met), a marker of dysregulated mitochondrial protein translation, and N-lactoyl-phenylalanine (lac-Phe), representative of the N-lactoyl-amino acids (lac-AAs), which are elevated in plasma of patients with monogenic mitochondrial disease. Compared to lactate, the clinical biomarker used to define septic shock, there was greater separation between survivors and non-survivors of septic shock for both f-Met and the lac-AAs measured within 24 h of ICU admission. Additionally, tryptophan was the one metabolite significantly decreased in septic shock compared to all other groups, while its breakdown product kynurenate was one of the 9 significantly increased.

Conclusion: Future studies which validate the measurement of lac-AAs and f-Met in conjunction with lactate could define a sepsis subtype characterized by mitochondrial dysfunction.

Introduction: Longitudinal biomarkers in patients with community-acquired pneumonia (CAP) may help in monitoring of disease progression and treatment response. The metabolic host response could be a potential source of such biomarkers since it closely associates with the current health status of the patient.

Objectives: In this study we performed longitudinal metabolite profiling in patients with CAP for a comprehensive range of metabolites to identify potential host response biomarkers.

Methods: Previously collected serum samples from CAP patients with confirmed Streptococcus pneumoniae infection (n = 25) were used. Samples were collected at multiple time points, up to 30 days after admission. A wide range of metabolites was measured, including amines, acylcarnitines, organic acids, and lipids. The associations between metabolites and C-reactive protein (CRP), procalcitonin, CURB disease severity score at admission, and total length of stay were evaluated.

Results: Distinct longitudinal profiles of metabolite profiles were identified, including cholesteryl esters, diacyl-phosphatidylethanolamine, diacylglycerols, lysophosphatidylcholines, sphingomyelin, and triglycerides. Positive correlations were found between CRP and phosphatidylcholine (34:1) (cor = 0.63) and negative correlations were found for CRP and nine lysophosphocholines (cor = - 0.57 to - 0.74). The CURB disease severity score was negatively associated with six metabolites, including acylcarnitines (tau = - 0.64 to - 0.58). Negative correlations were found between the length of stay and six triglycerides (TGs), especially TGs (60:3) and (58:2) (cor = - 0.63 and - 0.61).

Conclusion: The identified metabolites may provide insight into biological mechanisms underlying disease severity and may be of interest for exploration as potential treatment response monitoring biomarker.

Introduction: Accumulating data on the associations between food consumption and lipid composition in the body is essential for understanding the effects of dietary habits on health.

Objectives: As part of omics research in the Tohoku Medical Megabank Community-Based Cohort Study, this study sought to reveal the dietary impact on plasma lipid concentration in a Japanese population.

Methods: We conducted a correlation analysis of food consumption and plasma lipid concentrations measured using mass spectrometry, for 4032 participants in Miyagi Prefecture, Japan.

Results: Our analysis revealed 83 marked correlations between six food categories and the concentrations of plasma lipids in nine subclasses. Previously reported associations, including those between seafood consumption and omega-3 fatty acids, were validated, while those between dairy product consumption and odd-carbon-number fatty acids (odd-FAs) were validated for the first time in an Asian population. Further analysis suggested that dairy product consumption is associated with odd-FAs via sphingomyelin (SM), which suggests that SM is a carrier of odd-FAs. These results are important for understanding odd-FA metabolism with regards to dairy product consumption.

Conclusion: This study provides insight into the dietary impact on plasma lipid concentration in a Japanese population.

Introduction:  Because cerebrospinal fluid (CSF) samples are difficult to obtain for paediatric HIV, few studies have attempted to profile neurometabolic dysregulation.

Aim and objective: The aim of this exploratory study was to profile the neurometabolic state of CSF from a South African paediatric cohort using GCxGC-TOF/MS. The study included 54 paediatric cases (< 12 years), 42 HIV-negative controls and 12 HIV-positive individuals.

Results: The results revealed distinct metabolic alterations in the HIV-infected cohort. In the PLS-DA model, 18 metabolites significantly discriminated between HIV-infected and control groups. In addition, fold-change analysis, Mann-Whitney U tests, and effect size measurements verified these findings. Notably, lactose, myo-inositol, and glycerol, although not significant by p-value alone, demonstrated practical significance based on the effect size.

Conclusions: This study provided valuable insights on the impact of HIV on metabolic pathways, including damage to the gut and blood-brain barrier, disruption of bioenergetics processes, gliosis, and a potential marker for antiretroviral therapy. Nevertheless, the study recognized certain constraints, notably a limited sample size and the absence of a validation cohort. Despite these limitations, the rarity of the study's focus on paediatric HIV research underscores the significance and unique contributions of its findings.

Introduction: The microbial community plays a crucial role in the pathological microenvironment. However, the structure of the microbial community within endometriotic lesions and its impact on the microenvironment is still limited.

Methods: All 55 tissue samples, including ovarian ectopic (OEMs) and normal (NE) endometrium, were subjected to 16S rRNA sequencing, metabolomic and proteomic analysis.

Results: We found the abundance of Tuzzerella is significantly lower in OEMs compared to NE tissue (p < 0.01). We selected samples from these two groups that exhibited the most pronounced difference in Tuzzerella abundance for further metabolomic and proteomic analysis. Our findings indicated that endometriotic lesions were associated with a decrease in L-Glutamine levels. However, proteomic analysis revealed a significant upregulation of proteins related to the complement pathway, including C3, C7, C1S, CLU, and A2M. Subsequent metabolic and protein correlation predictions demonstrated a negative regulation between L-Glutamine and C7. In vitro experiments further confirmed that high concentrations of Glutamine significantly inhibit C7 protein expression. Additionally, immune cell infiltration analysis, multiplex immunofluorescence, and multifactorial testing demonstrated a positive correlation between C7 expression and the infiltration of regulatory T cells (Tregs) in ectopic lesions, while L-Glutamine was found to negatively regulate the expression of chemotactic factors for Tregs.

Conclusion: In this study, we found a clear multi-omics pathway alteration, "Tuzzerella (microbe)-L-Glutamine (metabolite)-C7 (protein)," which affects the infiltration of Tregs in endometriotic lesions. Our findings provide insights into endometriosis classification and personalized treatment strategies based on microbial structures.