Dataset Information

Development of an optimized method for processing peripheral blood mononuclear cells for 1H-nuclear magnetic resonance-based metabolomic profiling.

ABSTRACT: Human peripheral blood mononuclear cells (PBMCs) are part of the innate and adaptive immune system, and form a critical interface between both systems. Studying the metabolic profile of PBMC could provide valuable information about the response to pathogens, toxins or cancer, the detection of drug toxicity, in drug discovery and cell replacement therapy. The primary purpose of this study was to develop an improved processing method for PBMCs metabolomic profiling with nuclear magnetic resonance (NMR) spectroscopy. To this end, an experimental design was applied to develop an alternative method to process PBMCs at low concentrations. The design included the isolation of PBMCs from the whole blood of four different volunteers, of whom 27 cell samples were processed by two different techniques for quenching and extraction of metabolites: a traditional one using organic solvents and an alternative one employing a high-intensity ultrasound probe, the latter with a variation that includes the use of deproteinizing filters. Finally, all the samples were characterized by 1H-NMR and the metabolomic profiles were compared by the method. As a result, two new methods for PBMCs processing, called Ultrasound Method (UM) and Ultrasound and Ultrafiltration Method (UUM), are described and compared to the Folch Method (FM), which is the standard protocol for extracting metabolites from cell samples. We found that UM and UUM were superior to FM in terms of sensitivity, processing time, spectrum quality, amount of identifiable, quantifiable metabolites and reproducibility.

SUBMITTER: Gomez-Archila LG

PROVIDER: S-EPMC7906414 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development of an optimized method for processing peripheral blood mononuclear cells for 1H-nuclear magnetic resonance-based metabolomic profiling.

Gómez-Archila León Gabriel LG Palomino-Schätzlein Martina M Zapata-Builes Wildeman W Galeano Elkin E

PloS one 20210225 2

Human peripheral blood mononuclear cells (PBMCs) are part of the innate and adaptive immune system, and form a critical interface between both systems. Studying the metabolic profile of PBMC could provide valuable information about the response to pathogens, toxins or cancer, the detection of drug toxicity, in drug discovery and cell replacement therapy. The primary purpose of this study was to develop an improved processing method for PBMCs metabolomic profiling with nuclear magnetic resonance ...[more]

PMID: 33630921

Similar Datasets

Project description:BACKGROUND:Objective and reliable methods to measure dietary exposure and prove associations and causation between diet and health are desirable. OBJECTIVE:The aim of this study was to investigate if 1H-nuclear magnetic resonance (1H-NMR) analysis of serum samples may be used as an objective method to discriminate vegan, vegetarian, and omnivore diets. Specifically, the aim was to identify a metabolite pattern that separated meat-eaters from non-meat-eaters and vegans from nonvegans. METHODS:Healthy volunteers (45 men and 75 women) complying with habitual vegan (n = 43), vegetarian (n = 24 + vegetarians adding fish n = 13), or omnivore (n = 40) diets were enrolled in the study. Data were collected on clinical phenotype, body composition, lifestyle including a food-frequency questionnaire (FFQ), and a 4-d weighed food diary. Serum samples were analyzed by routine clinical test and for metabolites by 1H-NMR spectroscopy. NMR data were nonnormalized, UV-scaled, and analyzed with multivariate data analysis [principal component analysis, orthogonal projections to latent structures (OPLS) and OPLS with discriminant analysis]. In the multivariate analysis volunteers were assigned as meat-eaters (omnivores), non-meat-eaters (vegans and vegetarians), vegans, or nonvegans (lacto-ovo-vegetarians, vegetarians adding fish, and omnivores). Metabolites were identified by line-fitting of 1D 1H-NMR spectra and the use of statistical total correlation spectroscopy. RESULTS:Although many metabolites differ in concentration between men and women as well as by age, body mass index, and body composition, it was possible to correctly classify 97.5% of the meat-eaters compared with non-meat-eaters and 92.5% of the vegans compared with nonvegans. The branched-chain amino acids, creatine, lysine, 2-aminobutyrate, glutamine, glycine, trimethylamine, and 1 unidentified metabolite were among the most important metabolites in the discriminating patterns in relation to intake of both meat and other animal products. CONCLUSIONS:1H-NMR serum metabolomics appears to be a possible objective tool to identify and predict habitual intake of meat and other animal products in healthy subjects. These results should be confirmed in larger cohort studies or intervention trials. This trial was registered at clinicaltrials.gov as NCT02039609.

Project description:UnlabelledDengue, due to its global burden, is the most important arthropod-borne flavivirus disease, and early detection lowers fatality rates to below 1%. Since the metabolic resources crucial for viral replication are provided by host cells, detection of changes in the metabolic profile associated with disease pathogenesis could help with the identification of markers of prognostic and diagnostic importance. We applied (1)H nuclear magnetic resonance exploratory metabolomics to study longitudinal changes in plasma metabolites in a cohort in Recife, Brazil. To gain statistical power, we used innovative paired multivariate analyses to discriminate individuals with primary and secondary infection presenting as dengue fever (DF; mild) and dengue hemorrhagic fever (DHF; severe) and subjects with a nonspecific nondengue (ND) illness (ND subjects). Our results showed that a decrease in plasma low-density lipoprotein (LDL) and very-low-density lipoprotein (VLDL) discriminated dengue virus (DENV)-infected subjects from ND subjects, and also, subjects with severe infection even presented a decrease in lipoprotein concentrations compared to the concentrations in subjects with mild infection. These results add to the ongoing discussion that the manipulation of lipid metabolism is crucial for DENV replication and infection. In addition, a decrease in plasma glutamine content was characteristic of DENV infection and disease severity, and an increase in plasma acetate levels discriminated subjects with DF and DHF from ND subjects. Several other metabolites shown to be altered in DENV infection and the implications of these alterations are discussed. We hypothesize that these changes in the plasma metabolome are suggestive of liver dysfunction, could provide insights into the underlying molecular mechanisms of dengue virus pathogenesis, and could help to discriminate individuals at risk of the development of severe infection and predict disease outcome.ImportanceDengue, due to its global burden, is the most important mosquito-borne viral disease. There is no specific treatment for dengue disease, and early detection lowers fatality rates to below 1%. In this study, we observed the effects of dengue virus infection on the profile of small molecules in the blood of patients with mild and severe infection. Variations in the profiles of these small molecules reflected the replication of dengue virus in different tissues and the extent of tissue damage during infection. The results of this study showed that the molecules that changed the most were VLDL, LDL, and amino acids. We propose that these changes reflect liver dysfunction and also that they can be used to discriminate subjects with mild dengue from those with severe dengue.

Dataset Information

Development of an optimized method for processing peripheral blood mononuclear cells for 1H-nuclear magnetic resonance-based metabolomic profiling.

Publications

Development of an optimized method for processing peripheral blood mononuclear cells for 1H-nuclear magnetic resonance-based metabolomic profiling.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets