Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Antibiotic course frequency and recovery strategies alter gut microbial composition and metabolism.

ISME communications·2026
Same author

Investigating the gut microbiota in advanced heart failure and cardiac cachexia.

Gut microbes reports·2026
Same author

Recent advances in our understanding of the gut microbiome: an analysis from the Gut Microbiota for Health Expert Panel of the British Society of Gastroenterology.

Gut·2026
Same author

A metabolic constraint in de novo NAD+ synthesis drives mucosal inflammation in IBD.

Journal of Crohn's & colitis·2026
Same author

Alternative antibiotic regimens improve palatability and welfare in mice for gut bacterial depletion.

Lab animal·2026
Same author

Disease phenotype affects treatment of late-onset inflammatory bowel disease: Analysis of a large UK cohort.

Inflammatory bowel diseases·2026

Related Experiment Video

Updated: Jun 11, 2025

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
11:02

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

483

Evaluating protocols for reproducible targeted metabolomics by NMR.

Darcy Cochran1,2, Panteleimon G Takis3,4,5, James L Alexander6,7,8

  • 1Department of Chemistry, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588-0304, USA.

The Analyst
|October 8, 2024
PubMed
Summary

Clinical metabolomics requires standardized sample preparation and data analysis for accurate results. Protein precipitation and assisted-fit analysis improve metabolite extraction and quantification, enhancing reliability for biomarker discovery.

More Related Videos

Assessing Hepatic Metabolic Changes During Progressive Colonization of Germ-free Mouse by 1H NMR Spectroscopy
07:54

Assessing Hepatic Metabolic Changes During Progressive Colonization of Germ-free Mouse by 1H NMR Spectroscopy

Published on: December 15, 2011

13.1K
A Strategy for Sensitive, Large Scale Quantitative Metabolomics
14:18

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

20.9K

Related Experiment Videos

Last Updated: Jun 11, 2025

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
11:02

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

483
Assessing Hepatic Metabolic Changes During Progressive Colonization of Germ-free Mouse by 1H NMR Spectroscopy
07:54

Assessing Hepatic Metabolic Changes During Progressive Colonization of Germ-free Mouse by 1H NMR Spectroscopy

Published on: December 15, 2011

13.1K
A Strategy for Sensitive, Large Scale Quantitative Metabolomics
14:18

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

20.9K

Area of Science:

  • Clinical metabolomics
  • Biomarker discovery
  • Analytical chemistry

Background:

  • Metabolomics studies biological responses to various factors but faces challenges in reproducibility and accuracy due to inconsistent protocols.
  • Variability in sample preparation and data analysis significantly impacts the reliability of metabolomic data.

Purpose of the Study:

  • To systematically evaluate the impact of different sample preparation methods and data analysis platforms on metabolite profiles in clinical samples.
  • To identify common metabolites with high variability that require careful consideration for biomarker annotation.

Main Methods:

  • Evaluated 25 metabolites in 69 clinical samples using three preparation methods: intact, ultrafiltration, and protein precipitation.
  • Utilized 1D 1H nuclear magnetic resonance (NMR) spectroscopy for metabolic profiling.
  • Analyzed data using Chenomx v8.3 and SMolESY software, comparing batch-fitting and assisted-fit methods.

Main Results:

  • Protein precipitation demonstrated over 90% more efficient metabolite extraction compared to filtration.
  • Chenomx batch-fitting tended to overestimate metabolite concentrations, making it less reliable for absolute quantification.
  • An assisted-fit approach in data analysis provided accurate results efficiently.
  • Identified 5 common metabolites (2-hydroxybutyrate, choline, dimethylamine, glutamate, lactate) exhibiting high variability in fold changes and standard deviations.

Conclusions:

  • Sample preparation and data processing significantly influence the success and reliability of clinical metabolomics studies.
  • Standardization and harmonization of methods are crucial for ensuring reproducible and accurate outcomes in the metabolomics community.
  • Careful consideration of metabolite variability is essential before annotating potential biomarkers.