6 Milestones in Metabolomics: Driving our understanding of the metabolome
Within systems biology, the field of metabolomics is considered relatively new1. Despite this, the first reports of metabolic studies can be traced back 1000’s of years. Remarkably, metabolic profiling occurred over 3,000 years ago in ancient China. Doctors used ants to evaluate the urine of patients to detect whether it contained high levels of glucose, using this as an indicator for diabetes2. Other mentions of ‘screening’ urine for high levels of glucose around the same time were recorded by Hindus and Egyptian physicians and included using flies and taste (I bet they wish they’d heard about using ants).
This list of milestones in metabolomics will focus on some of the modern-day breakthroughs and the analytical techniques used to enable them. For the first of these we jump to the 1940’s and the work of Roger Williams3.
Characteristic metabolic patterns
Williams and his co-workers suggested that individuals might have a “metabolic pattern” that could be fingerprinted by studying their biological fluids3. The team utilized data from over 200,000 paper chromatograms to show convincingly that metabolic patterns varied significantly among subjects but, were relatively consistent for an individual. Williams went on to use his methods to examine samples from a variety of subjects, including alcoholics, schizophrenics, and residents of mental hospitals, and produced evidence that each of these groups has a characteristic metabolic pattern.
Chromatography, mass spectrometry and coining a phrase
After the work of Williams and his team, the field lay dormant until the late 1960’s when advancements in gas chromatography (GC), liquid chromatography (LC), and mass spectrometry (MS) enabled quantitative measurements of metabolites. In 1971 Horning and his team successfully used GC-MS to measure metabolites in human urine and tissue, coining the term “metabolic profile”4. Through the 1970’s and 1980’s, the work of Horning, alongside Pauling and Robinson, led the development of GC-MS-based techniques for metabolic measurements in biological fluids5. MS -based metabolome profiling remains the method of choice in systems biology approaches6.
Running alongside the developments in GC, LC, and MS, NMR spectroscopy was also advancing rapidly. In 1974, Seeley and his group highlighted the value of NMR, utilising 31P NMR to detect metabolites in unmodified biological samples. This first study on muscle determined that 90% of cellular ATP is complexed with magnesium7. With higher magnetic field strengths and magic angle spinning8 came improved sensitivity, cementing NMR as a key analytical tool. The work of Professor Jeremy Nicholson’s laboratory has been a driving force for the use of NMR for metabolomics. In 1984, Nicholson and his team demonstrated the possible use of NMR in the diagnosis of diabetes mellitus. It is well worth mentioning Professor Nicholson’s commitment to the field, speaking to ASBMB Today he recalled, “I was driving my wife completely crazy, because I was doing experiments on myself and it was disrupting the household. I decided to fast completely for 48 hours and look at my urine every few hours. I watched my ketosis develop in near real time. She watched my temper get worse”9. The development and subsequent use of 1D, 2D, 3D, and solid-state NMR has provided many advantages and ensured that NMR continues to play a key role in many metabolomic studies10.
The first web database
Created in the Suizdak laboratory at The Scripps Research Institute in 2004 and containing over 10,000 metabolites and tandem mass spectral data. METLIN was the first metabolomics web database for characterising human metabolites. As of May 2017, METLIN includes over 960,000 molecules ranging from lipids, steroids, plant & bacteria metabolites, small peptides, carbohydrates, exogenous drugs/metabolites, central carbon metabolites and toxicants11. Although METLIN was the first web database it is by no means the only one, with the Metabolomics Society linking to a total 35 databases from their website12.
The First Draft of the Human Metabolome
Launched in January 2005, The Human Metabolome Project (HMP) was a multi-university, multi-investigator project led by Dr David Wishart of the University of Alberta which catalogued all of the known metabolites in human tissues and biofluids. The HMP produced the first draft of the human metabolome in January 2007, that consisted of a database of approximately 2,500 metabolites, 1,200 drugs and 3,500 food components13. All information from the HMP was archived on the Human Metabolome Database, a freely accessible web-resource. Since completion of the HMP, similar projects looking at plant species have been underway for several years including, Medicago truncatula and Arabidopsis thaliana.
The development of high-throughput methods for metabolomics applications is required for large-scale studies and routine clinical practice. However, MS-based metabolomics is limited by time-consuming analytical workflows and issues with robustness14.
In 2015, real-time metabolome profiling was demonstrated for the first time by Uwe Sauer and his team. Using flow injection TOF-MS, they developed a platform capable of rapid, continual and unattended operation applicable to whole cell-broth15.
Large scale metabolomics studies are increasingly being used. New MS approaches providing orders of magnitude more rapid analysis of small molecules within the cell’s metabolome are helping pave the way towards true high throughput metabolomics16.
In April 2017, Kirk Hansen and his team described a 3-min method that exploits recent technical advancements in UHPLC and fast scanning high-resolution MS technologies14. They describe this as combining the advantages of rapid flow-injection TOF-MS with the selectivity of conventional chromatography-based metabolomics. While not applicable for the measurement of all compounds, the robustness of this approach makes it useful for the analysis of a wide range of biological matrices relevant to basic science and clinical routine practice, including biofluids, cell and tissue extracts.
Now we can’t mention high-throughput metabolomics without touching on single cell metabolomics. When it comes to understanding cellular behaviour, there seems little doubt that this will be extraordinarily important. Yet in a recent article published in Current Opinion in Chemical Biology, Sauer describes this as ‘lagging behind,’ and being ‘hampered by present MS limitations, poor integration with microscopy, and missing automation of micromanipulations’16. Regardless of the current state of play, single cell metabolomics is clearly an area to keep an eye on.
What did you think of our list? Are there any other milestones we should have included? Get in touch to let us know.
1. Djukovic, D. and Nagana Gowda, G. A., ‘Overview of Mass SpectrometryBased Metabolomics: Opportunities and Challenges,’ Methods Mol. Biol. (2014), doi: 10.1007/978-1-4939-1258-2_1
2. van der Greef, J. and Smilde, A. K., ‘Symbios is of chemometrics and metabolomics: past, present, and future,’ J. Chemometrics (2005), doi: 10.1002/cem.941
3. Gates, S. C. and Sweeley, C. C., ‘Quantitative metabolic profiling based on gas chromatography.’ Clinical Chemistry, (1978), 24: 1663–1673.
4. Horning, E. C. and Horning, M. G., ‘Human metabolic profiles obtained by GC and GC/MS.’ J. Chromatogr Sci., https://doi.org/10.1093/ chromsci/9.3.129.
5. Griffiths, W. J. and Wang, Y. ‘Mass spectrometry: From proteomics to metabolomics and lipidomics,’ Chem Soc Rev (2009), doi:10.1039/ b618553n. PMID 19551169.
6. Aretz, I. and Meierhofer, D., ‘Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology’ Int J Mol Sci (2016) doi: 10.3390/ijms17050632
7. Seeley, P. J. et. al. ‘Observation of tissue metabolites using 31P nuclear magnetic resonance,’ Nature (1974), doi:10.1038/252285a0
10. Kruk, J. et al. ‘NMR Techniques in Metabolomic Studies: A Quick Overview on Examples of Utilization,’ Appl Magn Reson. (2017) doi: 10.1007/s00723-016-0846-9
13. Wishart, D. S., et. al. “HMDB: The Human Metabolome Database”. Nucleic Acids Research (2007), doi:10.1093/nar/gkl923.
14. Hansen, K. C. et. al. ‘A three-minute method for high-throughput quantitative metabolomics and quantitative tracing experiments of central carbon and nitrogen pathways,’ Rapid Communications in Mass Spectrometry (2017), doi: 10.1002/rcm.7834
15. Sauer, U., ‘Real-time metabolome profiling of the metabolic switch between starvation and growth,’ Nature Methods (2015) doi:10.1038/ nmeth.3584
16. Sauer, U. ‘Frontiers of high-throughput metabolomics,’ Current Opinion in Chemical Biology (2017), http://dx.doi.org/10.1016/j.cbpa.2016.12.006