Continued improvements in analytical methodology and related data-handling systems are compressing the development cycle for many emerging scientific disciplines, including metabolomics.
Metabolomics—the study of mostly small-molecule metabolites—has caught the eyes of medical researchers for its ability to provide a snapshot of an organism’s current status vis-a-vis health, disease, and treatment. The term “metabolomics” is barely 20 years old, but in many ways is already mature thanks to its embrace by instrument makers who have adapted their offerings for complex metabolomic workflows.
A 2019 BCC Research Report (Metabolomics: Technologies and Global Markets) estimates growth in metabolomics-related products and services published at 12 percent per year, and predicts a global market of $17.1 billion by 2023.
Metabolomics studies rely on several instrument platforms, including gas chromatography (GC) and capillary electrophoresis (CE) on the purification side, and nuclear magnetic resonance (NMR) on the confirmation side. NMR is not as sensitive as mass spectrometry, however, and while it provides more information, it does not provide molecular weight, the one data point considered to be diagnostic for both known and unknown small-molecule species. Similarly, CE and GC are limited in the types of molecules they handle, whereas liquid chromatography can be adapted, by switching columns and mobile phases, to nearly any analyte class.
For those reasons, metabolomics experts now rely heavily on what have become the field’s analytical workhorses, liquid chromatography coupled to mass spectrometry (LC-MS). Information systems already primed to handle large proteomic and gene datasets have also stepped up to accommodate the large volume of data from metabolomics experiments.
The polarity question
Many metabolites are highly polar, which makes conventional LC-MS inappropriate. “These small molecules are widely diverse in size and polarity, so capturing them all on a single column chemistry is incredibly difficult,” says Baljit Ubhi, market manager for metabolomics and lipidomics at SCIEX (Framingham, MA). To detect and quantify key metabolites, samples must be run on both reverse and normal phase, in negative and positive ionization modes, requiring a total of four injections. Lipid metabolite analysis adds another dimension to this exercise. The SCIEX approach uses hydrophilic interaction microflow (HILIC) LC and mass spectrometry methods capable of identifying many more metabolites than standard chromatography. HILIC is a mixed-mode separation that uses traditional polar stationary phases such as silica, amino, or cyano groups, but with mobile phases typically used in reverse-phase LC. A typical mobile phase has a high organic fraction, moderate salt concentration, and pH ranging from around 4.4 to 5.5. “Our method deviates by having 20 mM ammonium hydroxide in both mobile phases to provide constant pH of 9.0 during the chromatographic separation. The high pH deprotonates the stationary phase and allows for better selectivity of the polar metabolites,” Ubhi says.
In June 2019, SCIEX entered a comarketing agreement with Elucidata, which provides tools for metabolomics data processing. The goal is to address the challenges in processing metabolomics data from a diverse range of workflows.
“We are at a point in metabolomics where generating terabytes of data is the simplest part of the workflow,” Ubhi says. “The question then becomes how to draw meaningful insights from these datasets when extracting knowledge from them is challenging and the steps often fragmented. And, once you have extracted the data’s salient features, how do you identify them, and infer biological meaning from that list of identified metabolites?” Polly, Elucidata’s data platform, standardizes and streamlines metabolomics data workflows. Polly is compatible with data-independent acquisition, an approach increasingly used in untargeted metabolomics workflows.
HILIC: the best compromise?
HILIC is not the only LC mode suitable for metabolites. In addition to hydrophobic interaction, some researchers use ion-pair, reverse phase, or pentafluorophenyl reverse phase chromatography. “Of these, HILIC has the broadest applicability to polar metabolites,” says Steve Fischer, market director for Academia and Government/Life Science Research Segment at Agilent Technologies (Santa Clara, CA). “But HILIC has historically been the last method considered due to its run-to-run irreproducibility and sensitivity to salt concentrations. HILIC uses a hydrophilic stationary phase with reverse phase-type mobile phases. Continuous development of HILIC phases has greatly reduced the problems associated with HILIC methods.”
HILIC is in fact adaptable to most polar metabolites. Agilent recently published an application note describing high- and low-pH methods for comprehensive coverage of metabolite classes that include vitamins, amino acids, polyamines, sugars, nucleotides, and others at concentrations ranging from about 20 mg/ml to 20 ng/ml. In this work, researchers optimized the chromatographic gradient and ion source for isomer separations, using high-resolution, accurate-mass LC/Q-TOF (time-of-flight) mass spectrometry. Concentration dynamic ranges varied by 1,000x for individual metabolites, and by as much as one million across all the molecules studied.
The methodology, with obvious research applications, is suitable to monitor metabolic events; for example, metabolome profiling for personalized health monitoring, by taking “snapshots” of an individual’s metabolome and comparing changes in its composition over time. “Metabolomics is commonly used to study metabolite response to determine drug effectiveness, toxicity, or mode of action,” Fischer adds.
Unlike proteomics or genomics, where the basic building blocks and units of analysis are very well-characterized, nobody knows how many metabolites exist or the identities of all such molecules relevant to a study. “Researchers believe that primary metabolism contains roughly 2,500 biologically active molecules, but that likely is an underestimate of the size of the metabolome,” Fischer says. “As methodologies and detection limits keep getting better, we will likely discover more metabolites. The analytical challenge is the size and chemical diversity of the metabolome.”
Even with these robust analytical tools, obtaining absolute metabolite concentrations is difficult. “Metabolomics is a comparative technique [that] requires running many samples to achieve sufficient statistical power to be confident in concentration differences,” Fischer notes. “Since samples are typically analyzed in both positive and negative ion mode, analysis time becomes a factor in achieving satisfactory throughput. Add that many metabolites are isobaric, and it becomes obvious why it behooves analysts to use an efficient chromatographic separation to reduce the analysis time as much as is possible.”
Metabolomics may be mature, or maturing in research markets, but as a biomedical technique it still has a way to go. While many approved drugs modulate metabolic pathways, most of these are based on the effect on a single biomarker (e.g. cholesterol and derivatives) rather than a metabolomic pattern. In the case of cholesterol biosynthesis, the process is actually anabolism, not metabolism. Similarly, the cholesterol measured in diagnostic tests is a product of the anabolic synthesis of a 27-carbon molecule from acetate and mevalonate (two and six carbons, respectively). Many other tests that target metabolites or small molecules use immunoassays rather than LC-MS.
Then there is the issue of instrumentation. Diagnostics companies like bioprocessors view LC as too complex, expensive, and time-consuming for general use. That is why the first LC-based medical tests based on metabolomics will probably involve treatment-monitoring for serious diseases like cancer or heart disease.
“Metabolomics is applicable to so many biological problems,” observes Fischer, “and this broad applicability has driven innovation in analytical method development. The ongoing evolution of chromatography and mass spectrometry will open up even more possibilities for problems that can be understood using metabolomics.”