Lc-ms Metabolomics
Lc-ms Metabolomics - Related Videos
07:34
Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
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Cited by 18 •
2013
Non-targeted metabolite profiling by ultra performance liquid chromatography coupled with mass spectrometry (UPLC-MS) is a powerful technique to investigate metabolism. This article outlines a typical workflow utilized for non-targeted metabolite profiling of serum including sample organization and preparation, data acquisition, data analysis, quality control, and metabolite identification.
14:18
A Strategy for Sensitive, Large Scale Quantitative Metabolomics
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Cited by 28 •
2014
Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. Utilizing normal-phased liquid chromatography coupled to high-resolution mass spectrometry with polarity switching and a rapid duty cycle, we describe a protocol to analyze the polar metabolic composition of biological material with high sensitivity, accuracy, and resolution.
13:02
The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics
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Cited by 10 •
2016
This article describes the application of untargeted metabolomics, transcriptomics and multivariate statistical analysis to grape berry transcripts and metabolites in order to gain insight into the terroir concept, i.e., the impact of the environment on berry quality traits.
09:28
One-step Metabolomics: Carbohydrates, Organic and Amino Acids Quantified in a Single Procedure
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Cited by 12 •
2010
The urease method of sample preparation for GC/MS analysis of intermediary metabolites is presented by its inventor. The method allows one-step follow-up of newborn screening for inborn errors by tandem mass spectrometry by quantifying carbohydrates, organic and amino acids all in a single process.
03:01
Sample Preparation for Metabolomics: A Method to Prepare Cell Samples for Metabolite Profiling
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2023
This video describes a technique of preparing breast cancer cell samples for metabolite profiling. Breast cancer cells are treated with estradiol, which binds to the estrogen receptor alpha and causes change in the metabolite...
FAQs
Liquid chromatography separates compounds according to their chemical properties before mass spectrometry examines them. This two-stage arrangement helps distinguish metabolites that might otherwise appear together in a complex biological sample. Chromatographic separation provides chemical-resolution context, while mass-to-charge measurements support metabolite detection and quantification, making the combined approach informative for comparing cellular states.
Mass spectrometry records the mass-to-charge ratios of ionized compounds, creating measurements that can be compared across biological samples. These data may support relative quantification, which compares metabolite levels between conditions, or absolute quantification, which determines amounts more directly. The choice affects how confidently researchers interpret biochemical differences among samples.
Metabolite profiles can reveal biochemical changes associated with gene variants or regulatory alterations. When those changes are examined alongside genetic data, researchers can identify pathways whose activity differs between genetic states and relate those shifts to observed phenotypes. This provides a functional layer for studying how inherited or regulatory differences influence cellular chemistry.
A metabolite pattern may reflect both genetic influences and environmental conditions rather than genotype alone. Examining these interactions helps researchers determine whether a biochemical difference is consistently associated with a genetic change or emerges only under particular environmental circumstances. This distinction improves interpretation of cellular responses and can clarify variation among related biological samples.
The workflow begins with biological samples containing small-molecule metabolites. Liquid chromatography separates the compounds based on their chemical properties, after which mass spectrometry ionizes them and records their mass-to-charge ratios. Researchers then use the resulting measurements for relative or absolute quantification and connect the observed metabolite patterns with pathways, genetic variation, or phenotypes.
Researchers can apply LC-MS metabolomics when genomic information alone does not explain how a genetic difference affects cellular function. The resulting profiles support biomarker discovery, pathway analysis, and evaluation of genotype-environment interactions. These applications help translate variants or regulatory changes into measurable biochemical consequences and can connect molecular changes with phenotypic differences.
Genomic data describe inherited information and regulatory changes, whereas metabolite profiles show consequences at the level of cellular chemistry. Combining both types of information can help trace relationships from genetic variation through altered biochemical pathways to phenotypes. This complementary perspective is useful for interpreting functional effects that sequence-based measurements may not reveal directly.