Metabolomics in the Past, Present, and Future

Metabolomics is having a significant impact on many fields, including life, food, and plant sciences, drug development, toxicology, environmental science, and medicine. As the downstream products of cellular function, metabolites provide a sensitive measure of the actions of upstream molecular species such as genes, transcripts, and enzymes, as well as the effects of disease, drugs, toxicity, and the environment. As a result, the identification and quantitative analysis of metabolites in humans and animal and cell models of a variety of human diseases provides avenues for understanding, diagnosing, and managing human diseases; assessing disease risk factors associated with drugs, toxins, and the environment; and, ultimately, developing personalised treatment options.

Metabolomics is a rapidly growing omics field that follows genomics, transcriptomics, and proteomics, and it is an important component of systems biology. In metabolomics, the most common analysis objects are biological fluids (e.g., serum, plasma, urine, saliva, cerebrospinal fluid, bile, amniotic fluid, tears, pancreatic juice, intestinal fluid, and breast milk), human tissues, and cells. Metabolites are the end products of complex cellular regulatory networks, and they can influence or even change regulations through feedback loops.

The terms metabolomics and metabonomics are frequently used interchangeably; both are classified as ‘technology.’Sequence genomics identifies genes, transcriptomics indicates which genes are being converted into RNA, proteomics indicates whether or not the RNA is translated into protein and what post-translation modifications are made to the protein, and metabolomics/metabonomics indicates whether or not protein expression results in metabolic changes. Metabonomics is defined as the “quantitative measurement of time-related multiparametric metabolic responses of multicellular systems to pathophysiological stimuli or genetic modification.” Fiehn defines metabolomics as “a comprehensive and quantitative analysis of all metabolites that could help researchers understand such (biological) systems.” Because such an analysis reveals the metabolome of the biological system under investigation, this method should be referred to as metabolomics.

Metabolite identification and quantification requires sophisticated instruments such as MS, NMR spectroscopy, and laser-induced fluorescence detection. Nuclear magnetic resonance spectroscopy and mass spectrometry are the most commonly used analytical techniques in metabolomics (MS). Each of these technologies has its own set of benefits and drawbacks. The optimal choice of a particular technology is determined by the study’s objectives and is usually a trade-off between sensitivity, selectivity, and speed. Advances in the field allow for the identification of numerous potential disease biomarkers and provide insights into the pathogenesis of numerous diseases. Several findings have also been tested for translational applications, such as early disease detection, therapy prediction and prognosis, treatment monitoring, and recurrence detection.

PAST: METABOLOMICS’ ORIGIN IN THE PAST

Although metabolic profiling or metabolomics is a relatively new field in systems biology, the first reports of metabolic studies can be traced back to ancient China, where ants were used to detect diabetes by assessing glucose levels in urine samples. “Urine charts,” which correlated the smell, taste, and colour of urine, were used in the Middle Ages to diagnose a variety of metabolic-related medical conditions. Roger Williams and his colleagues proposed and tested the idea that individuals may have a distinct “metabolic pattern” that can be “fingerprinted” by studying their biological fluids in the late 1940s. They used paper chromatography to discover that metabolic patterns differed significantly between subjects but remained relatively constant within an individual. Their research on a variety of subjects, including alcoholics and schizophrenics, has revealed that each of these groups has a distinct metabolic pattern. In the 1960s and 1970s, technological advances in gas chromatography (GC), liquid chromatography (LC), and mass spectrometry (MS) enabled quantitative metabolic profiling studies. Horning and colleagues used GC-MS to measure metabolites in human urine and tissue extracts successfully in 1971. Through the 1970s and early 1980s, Horning, Pauling, Robinson, and their research groups led the development of GC-MS-based techniques for metabolic measurements in biological fluids. Later, advances in high-resolution/sensitivity MS and NMR instrumentation, combined with multivariate statistical analysis, enabled metabolomics to become a rapidly growing field in system biology over the last decade.

PRESENT: CURRENT STATUS AND CHALLENGES

Given the high complexity of biological mixtures, the vast majority of MS analysis methods include prior separation via LC, GC, or CE. However, the rapidly expanding number of applications that use constantly evolving separation methods and protocols presents both opportunities and challenges. Clearly, advances in chromatography methods have allowed for more efficient metabolite separation and have increased the number of detected metabolites. The inability to compare and correlate the results of such studies with the same or similar samples obtained by independent research groups is a significant challenge. This is a significant impediment to the field’s growth. Other factors that contribute to data variability include sample preparation, sample matrix, and carryover effects. To overcome these obstacles, it is necessary to shift away from the commonly used relative metabolite concentration measurements and toward more reliable absolute concentration determinations, which will then be independent of the analytical platforms, methods, and protocols used. This approach is difficult for MS because it necessitates appropriate internal standards and calibration, but it is critical. Such efforts not only allow for the comparison and correlation of vast amounts of data accumulated in the literature, but the results are more meaningful because clinical translation of metabolite-based biomarker technology ultimately requires biomarkers to be measured and validated in absolute concentration. The advancements in fast MS methods that have emerged relatively recently promise a wide range of applications in biomedicine. These approaches’ ambient ionisation methods enable real-time analysis of tissue in situ, potentially under intraoperative conditions. Fast MS methods, on the other hand, are even more difficult to calibrate on an absolute basis than chromatography-based MS methods. Thus, testing the reproducibility of these methods for real clinical utility is critical.

FUTURE: FUTURE OBJECTIVES

Metabolomics has the potential to be an effective tool for disease early detection by identifying one or a signature of prognostic biomarkers. It may also be used to predict treatment response and survival. Because the metabolome responds quickly to environmental stimuli, including therapeutic or surgical intervention, it could be used to monitor an individual’s metabolic status and indicate any potential toxic effects; it could also be used to detect any remaining disease or recurrence after therapy.