Metabolomics: Basic Principles and Strategies

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Submitted By:

Mrs.Purnima

Department of Bioinformatics

Metabolomics : Introduction

• Metabolomics is the study of metabolome within cells, biofluids, tissues, or organisms to comprehensively identify and quantify all endogenous and exogenous low-molecular-weight (<1KDa)small molecules/ metabolites in a biological system in a high-throughput manner.
• The composition of these endogenous compounds is affected by the upstream influence of the proteome and genome as well as environmental factors, lifestyle factors, medication, and underlying disease. Metabolomics is reported as the reflection of the phenotype.

Metabolome

• Metabolome can be defined as the small molecules and their interactions within a biological system which has been estimated as 3000–20,000 global metabolite profiles under a given genetic, nutritional, environmental conditions
• Since the 1 metabolome is the final downstream product, changes and interactions between gene expression, protein expression, and the environment are directly reflected in metabolome making it more physically and chemically complex than the other “omes.”
• The metabolome is closest to the phenotype among other omics approaches, and metabolomics best modulates and represents the molecular phenotype of health and disease .

Metabolome Contd..

• Due to the complexity of the metabolome, a wide variety of chemically diverse compounds such as lipids, organic acids, carbohydrates, amino acids, nucleotides, and steroids, among others, have not yet been validated and reported totally; thus, we do not know the complete number of metabolites present in the human.
• Human Metabolome Database (HMDB; http://www.hmdb.ca, version 4.0, 2018) reported 114,098 (April 2019) metabolite entries including both water-soluble and lipid-soluble metabolites as well as metabolites that would be regarded as either abundant (>1 uM) or relatively rare (<1nM) Those small molecules, which have been identified and experimentally confirmed in various human tissues and biofluids, have been suggested as only 20% of the total metabolome.

Basic workflow of MS-based metabolomics

MS is used to identify and quantify metabolites even at very low concentrations (femtomolar to attomolar) with high resolution, sensitivity, and dynamic range . MS-based analyses basically include sample preparation, extraction, capillary electrophoresis (CE), and/or chromatographic separation, introduction of sample for ionization process (charged molecules), and detection of possible metabolites on the basis of their mass-to-charge ratio (m/z). The main aspects of MS-based untargeted metabolomics strategies are briefly outlined below:

Workflow

1. Sample acquisition

2. Sample preparation/extraction

3. Separation

4. Ionization

5. Detection

6. Data analysis and metabolite identification

Challenges and affecting factors

• Though there are extensive tools and databases for analysis and identification of metabolites, challenges remain in the field of data analysis/integration, pathway analysis, and metabolite identification in untargeted metabolomics due to the highthroughput heterogeneous omics data which essentially requires improved bioinformatics and computational techniques to comprehensively evaluate the metabolomic profiles and completion of the human metabolome .
• Another challenge is the existence of isomers with identical masses and highly similar spectra which complicates distinguishing and differentiation during metabolite assignment to spectrum features

Challenges and affecting factors

• Chromatographic resolution, absolute MS signals, and compound identification can be affected during ionization process due to polarity, ion sources, ion suppression, flow rates, and MS vacuum, sample preparation strategies, purity and temperature (prechilled) of reagents and solvents, different laboratory staff and techniques in different analysis days (typical sources of variance), different mass analyzers, chromatographic separation columns and compositions that cause forming of different fragments of the same molecule, frequent detection of the most abundant molecules, ion suppression, and day-day variation.

Metabolomics in health and disease

• Metabolomics has several applications in health and disease including precision/ personalized medicine, single cell, epidemiologic population studies, metabolic phenotyping and metabolome-wide association studies (MWAS), precision metabolomics, and in combination with other omics disciplines as integrative omics.
• Single-cell metabolomics and single-cell lipidomics technologies allow highdimensional characterizations of individual cells, disease heterogeneity and complexity, identification, expression and abundance of disease-associated small molecules, metabolites, and by LC-MS/MS, GC-MS/MS, and live single-cell mass spectrometry (LSCMS) .
• Imaging MS analysis of human breast cancer samples at the single-cell level revealed cell-cell interactions and tumor heterogeneity

Contd..

• Clinical biomarkers and different metabotypes of disease severity correlated to exposures, and biological outcomes have been studied and identified through metabolomics profiling, MWAS, and metabolomics fingerprinting and footprinting techniques in individuals and populations which will enable precision medicine and public healthcare.
• Studies moving from genome-wide association studies (GWAS) to metabolome-wide association studies (MWAS) were first described in 2008 as “environmental and genomic influences to investigate the connections between phenotype variation and disease risk factors” . Rattray and colleagues suggested exposotypes on single individual phenotypes and populations, in epidemiologic research, and disease risk using metabolome-wide association studies and impacts on precision medicine

METABOLOMICS IN DRUG DISCOVERY

•Drug molecules generally act on specific targets at the cellular level, and upon binding to the receptors, they exert a desirable alteration of the cellular activities, regarded as the pharmaceutical effect

•The ability to effectively predict if a chemical compound is “drug-like” or “nondrug-like” is, thus, a valuable tool in the design, optimization, and selection of drug candidates for development

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Conclusion

• In conclusion, MS-based metabolomics/lipidomics provides a useful approach for both identification of disease-related metabolites in biofluids or tissue and also encompasses classification and/or characterization of disease or treatmentassociated molecular patterns generated from metabolites.