Urinary Metabolite Analysis
Urinary Metabolite Analysis - Related Videos
11:17
A Simple Fractionated Extraction Method for the Comprehensive Analysis of Metabolites, Lipids, and Proteins from a Single Sample
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Cited by 67 •
2017
A protocol for comprehensive extraction of lipids, metabolites and proteins from biological tissues using one sample is presented.
08:03
A Tandem Liquid Chromatography–Mass Spectrometry-based Approach for Metabolite Analysis of Staphylococcus aureus
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Cited by 1 •
2017
Here we describe a protocol for the extraction of metabolites from Staphylococcus aureus and their subsequent analysis via liquid chromatography and mass spectrometry.
11:25
Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
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Cited by 29 •
2014
The reliability of results in metabolomics experiments depends on the effectiveness and reproducibility of the sample preparation. Described is a rigorous and in-depth method that enables extraction of metabolites from biological fluids with the option of subsequently analyzing up to thousands of compounds, or just the compound classes of interest.
05:05
A Modified Precipitation Method to Isolate Urinary Exosomes
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Cited by 32 •
2015
This manuscript describes a protocol for isolating exosomes from human urine using a modified precipitation technique.
12:49
Purification of Transcripts and Metabolites from Drosophila Heads
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Cited by 12 •
2013
We describe here the procedures for the extraction and purification of mRNA and metabolites from Drosophila heads. We are applying these techniques to better understand the cellular perturbations underlying neuronal degeneration. These methodologies can be easily scaled and adapted for other "omic" projects.
FAQs
Changes in urine metabolites may represent several overlapping processes, including host inflammatory responses, microbial activity, tissue injury, and effects of antimicrobial therapy. Comparing profiles from healthy and infected states helps researchers identify coordinated biochemical changes rather than focusing on a single molecule. This pattern-based view can reveal pathways associated with infection and support disease classification.
Liquid chromatography–mass spectrometry and nuclear magnetic resonance spectroscopy provide complementary ways to separate or detect urinary metabolites. Their use generates molecular profiles that can be compared across physiological or disease states. Selecting one of these analytical approaches allows investigators to characterize biochemical differences relevant to infection, inflammation, tissue damage, or treatment response.
Urinary changes may arise from more than the infectious organism itself. A profile can contain evidence of host inflammation, microbial activity, tissue injury, or biochemical effects caused by antimicrobial therapy. Separating these possible sources improves interpretation of the findings and helps determine whether a metabolite pattern is most useful for describing disease activity or monitoring therapeutic response.
Standardized urine collection and sample preparation help make metabolite profiles more comparable between individuals and study groups. Without consistent handling, differences in the measured profiles may be harder to relate to infection, physiological state, or treatment. These preparation steps therefore support reliable comparisons between healthy and infected samples and strengthen subsequent biomarker or classification analyses.
A typical workflow begins with standardized urine collection, followed by sample preparation and analytical measurement. The prepared material is examined using liquid chromatography–mass spectrometry, nuclear magnetic resonance spectroscopy, or another supported separation or detection approach. Researchers then compare the resulting metabolite profiles across relevant states, such as healthy versus infected or before versus after therapy.
This approach is useful when researchers need molecular indicators of infection-related changes or treatment effects. Profile comparisons can support biomarker discovery, disease classification, and monitoring of therapeutic outcomes. In immunology and infection studies, the findings may also help connect urinary biochemical patterns with host inflammatory responses, microbial activity, tissue injury, or changes following antimicrobial therapy.