By definition, isomers are compounds with identical atomic compositions but different bonding arrangements of atoms or orientations of their atoms in space. This creates a serious challenge across all areas of omics research as the separation and identification of complex isomeric materials can be tedious and resource intensive, because structural separation power must be high to differentiate between isomer species.
This isomer problem has a significant impact on omics research because the gaps that are left in characterization can potentially slow down the discovery of disease diagnosis and the development of life-saving therapeutics. There is a clear need, therefore, to identify new separation technologies with improved resolution and throughput that can separate isomers quickly and efficiently.
Why is better characterization needed?
A recent study of the PubChem library of compounds found over 60 million unique chemical structures comprising the library.1 When increasing the mass resolution to try to identify those compounds from around 300 parts per million down to one part per million in mass resolving power, the chemical formula may be well characterized, but many isomers at that chemical formula may be present. The real challenge is in identifying which isomers are being observed, as once you get to a one part per million many of the chemical formulas are resolved. Figure 1 shows the number of compounds at specific masses, for example C20H22N2O4, which has 10,000 different isomers with this chemical formula, meaning that it is very challenging to know which of those are being observed in the sample. This places a huge pressure on the use of orthogonal data to decipher which of the molecules are present.
Figure 1. An example of the isomer challenge using over 60 million validated chemical structures in the PubChem database. Using increasing levels of mass resolution, here going left to right from unit mass resolving power to 1 part-per-million (ppm) separation, most of the chemical formulas can be determined, however, in one case over 10,000 chemical structure variations exist for one chemical formula, C20H22N2O4. Here, mass measurement alone cannot provide any more information on these isomers, thus requiring additional separation dimensions which are selective to chemical structure.1
Case example: lipids
The heterogeneity of lipid structures, coupled with their low concentrations in the body, means that it can take typically long separation strategies to tease them apart. Although many lipid molecules have the same mass, charge, and physical properties, at a given mass or chemical formula different lipid classes tend to adopt unique structures based on the gas-phase folding propensity of the molecule type. Subtle structural motifs of lipid collisional cross section structure can reveal more granular detail about the chemical class being observed, such as cerebrosides, sphingomyelins, phosphatidylcholines, or other lipid classes.2
Lipids are vital structural components of biological membranes and, as active molecules, they exert a wide range of regulatory and cell signaling functions. Different lipid categories have a variety of purposes that makes their separation and identification important. For example, sphingolipids are thought to participate in signaling pathways in neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and Huntington’s. The ability to accurately identify lipid profiles in a high-throughput manner permits the rapid separation of isomeric gangliosides without the need for extensive sample preparation or liquid chromatography (LC) coupling, opening potential new avenues in diagnosis and treatment of important neurodegenerative diseases.
Limitations of current techniques
Traditional separation methods using LC together with mass spectrometry (LC-MS) are generally time-consuming and can lack the resolution to fully separate and differentiate all crucial isomers.
Ion mobility provides separations that are much faster—milliseconds to seconds versus minutes to hours. Different types of molecules, such as lipids, peptides, and carbohydrates, at a given mass or chemical formula tend to adopt very different structures based on the gas-phase folding of the molecules. In one run, a complex biological sample can be resolved into different chemical classes in a multi-omics experiment. Ion mobility-mass spectrometry enables omics-scale measurements equivalent to massive sample numbers if each analyte were characterized separately. Researchers can measure both dimensions very quickly and, using advanced bioinformatics and biostatistical tools, the data can be interrogated more accurately.
High-resolution ion mobility-mass spectrometry (HRIM-MS) has emerged as a separations technique that can help separate isomers with increased throughput. This additional information is provided in reduced analysis time with easily transferrable methods. For example, in glycobiology, HRIM can identify the same glycosylation profiles that LC can in a six-hour separation but in only two minutes.3
Figure 2. Four examples of isomer mixtures, which are resolvable using next-generation HRIM technology. From left to right, peptides, triglycerides, carbohydrates, and ganglioside lipid isomers demonstrate significant improvements in their structural resolution, which when analyzed using HRIM based on SLIM-IMS technology (lower panels) as compared to conventional resolution DTIMS (middle panels).4 Abbreviations used in the figure: CCS is collision cross section, RA is relative abundance, Rp is single-peak resolving power, Rpp is two-peak resolution, and V is the percent valley separation.
Although the isomer problem makes the different areas of omics research complicated to study, it is important to be able to separate the isomers of these biological entities. In doing so, we will have endless opportunities to better understand and tailor biology. Applying new, high-resolution technologies to drug development processes allows us to ask more complex biological questions and get the answers we need rapidly, unleashing next-generation approaches to healthcare such as personalized medicine.
References
1. J.C May and J.A. McLean. Advanced Multidimensional Separations in Mass Spectrometry: Navigating the Big Data Deluge. Annual Reviews in Analytical Chemistry vol. 9,1 (2016): 387-409
2. J, May, C.R. Goodwin, N. Lareau, K. Leaptrot et al. Analytical Chemistry 86, 22107-2116 (2014)
3. MOBILion Systems, High-Resolution Ion Mobility Mass Spectrometry for High Throughput and High Resolution Permethylated N- and O- Glycan Analysis (2020)
4. J.C May et al. Resolving Power and Collision Cross Section Measurement Accuracy of a Prototype High-Resolution Ion Mobility Platform Incorporating Structures for Lossless Ion Manipulation Journal of the American Society for Mass Spectrometry 2021 32(4)
John McLean is Stevenson Professor of Chemistry at Vanderbilt University, Jody May is Research Assistant Professor of Chemistry at Vanderbilt University, and Melissa Sherman is CEO at MOBILion Systems. Disclosure: John McLean is a member of the Scientific Advisory Board for MOBILion Systems. He certifies that his contributions are scientifically objective and are not influenced by his SAB participation.