Metabolomics

What is Metabolomics?

Metabolomics is a field of “omics” research specializing in the near-global analysis of small molecule metabolites (<1500 Daltons) that are produced by cells, tissues, and organisms as part of their normal biochemical process. Metabolites are the end products of organism metabolism, and they can provide valuable information about the underlying biochemical and physiological processes occurring in a biological system.

Metabolomics profiles are time- and environment-sensitive, providing a direct and close representation of an organism’s health. By analyzing metabolite profiles, metabolomics can provide insights into the effects of genetics, environmental, and lifestyle factors on metabolism and identify biomarkers of disease and other physiological states. Metabolomics utilizes several different assays and techniques for quantitative analysis and identification of metabolites in various sample types.

Targeted vs. Untargeted Metabolomics

There are two approaches to metabolomics analysis: targeted and untargeted.

1. Targeted Metabolomic Analysis:

• Definition: Targeted metabolomics analyzes a specific, predefined set of metabolites.
• Approach: The metabolites selected for this type of analysis are usually known or hypothesized to be relevant to the particular biological question or pathway being studied.
• Applications: This method is commonly used when the research question is specific or when the roles of a particular metabolite are well understood, such as in a study of known metabolic pathways or disease biomarker identification.

2. Untargeted Metabolomic Analysis:

• Definition: Untargeted metabolomics aims to profile as many metabolites as possible in a sample without prior bias or selection
• Approach: This method does not focus on any specific metabolite. Instead, it attempts to capture the entire metabolite pool (or as much of it as possible) within the sample, often leading to the discovery of previously unrecognized or novel metabolites.
• Applications: Untargeted metabolomics is useful for exploratory studies, where the aim is to identify changes in metabolic profiles under different conditions or to discover new biomarkers

Examples of Metabolomics Applications

Metabolomics is used in many research areas, including drug development, personalized medicine, nutrition research, and environmental toxicology. Here are some examples of Metabolomics Applications:

• Characterize the precise chemical composition of biofuels and biofuel feedstock, including metabolites, lipids, and carbohydrates
• Map genotypic changes to quantifiable metabolic outputs
• Assist in the metabolic engineering of both microbes and plants
• Facilitate the design, testing, monitoring, and optimization of microbial fermentations
• Comprehensively characterize the phytochemical and nutrient content in plants
• Identify and quantify new chemical biomarkers associated with diseases and disease symptoms
• Assess the physiological effects of drugs or foods on human health

Metabolomics Techniques

Liquid Chromatography-Mass Spectrometry (LC-MS)

Liquid chromatography-mass spectrometry (LC-MS) is a powerful chemical identification technique that combines physical separation via liquid chromatography (HPLC) with mass spectrometry (MS). This technique is popular in metabolomics due to its superior metabolite detectability, versatility with different sample types, and accurate quantification compared to NMR. The high sensitivity and selectivity of LC-MS means it is generally used to detect and identify particular chemicals in a mixture, though it can also be used for purification purposes.

LC-MS typically starts with reverse phase chromatography (RPS) to separate the different chemical compounds. RPC uses a non-polar stationary phase with a moderately polar mobile phase, meaning polar molecules elute earlier. As the molecules elute off the column, they enter the mass spectrometer. The mass spectrometer removes the solvent, ionizes the remaining components, and sorts the ions by mass using electromagnetic fields. Tandem MS is often used in metabolomic profiling, in which multiple stages of mass analysis separation are performed with fragmentation of ions occurring in between. The Li Node uses this technique to perform Global (Untargeted) Lipidomics Profiling.

Chemical Isotope Labeling (CIL) LC-MS

The High-Performance Chemical Isotope Labeling (HP-CIL) LC-MS technique represents a significant leap forward in metabolomics, offering a comprehensive and precise approach to analyzing complex biological samples. This innovative method leverages the strengths of chemical isotope labeling to enhance metabolite detection and quantification. In HP-CIL LC-MS, metabolites are categorized based on four chemical groups (amine/phenol, carboxyl, carbonyl, and hydroxyl) rather than solely on their physical properties. This categorization is critical to the method’s effectiveness, as it allows for the use of specially designed labeling reagents that significantly improve the separation and ionization efficiency of a wide range of metabolites. As a result, CIL LC-MS achieves a broader metabolome coverage, uncovering a more extensive array of metabolites than traditional LC-MS techniques.

A central feature of the CIL LC-MS approach is its differential isotope labeling. By labeling one sample group with a heavy isotope reagent and the comparative group with a light isotope reagent, CIL LC-MS facilitates simultaneous LC-MS analysis of these samples. This process yields peak pairs in the mass spectra corresponding to each metabolite, thus allowing for precise relative quantification. This technique not only enhances the detection sensitivity but also significantly improves the accuracy and reproducibility of quantitative analyses.

Furthermore, IsoMS Pro complements the CIL LC-MS technique by providing sophisticated data interpretation capabilities. Through its access to extensive, curated ID databases, IsoMS Pro aids in precise and accurate metabolite identification, surpassing the capabilities of standard analytical tools. The CIL LC-MS method, therefore, stands out as a robust and highly effective tool in metabolomics, suitable for a wide range of applications, including biological research and biomarker discovery, and setting a new standard in the field for its precision and comprehensive coverage.