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Trapped ion mobility spectrometry (TIMS) has enhanced the use of mass spectrometry (MS) for accurate metabolite analysis, and increased understanding of metabolic processes in human health and disease, as well as agricultural, plant, food, and nutritional sciences. This article will discuss the importance of TIMS as it enhances the sensitivity, specificity, and speed of metabolite measurement, which in turn accelerates the pace of metabolomics research.
The field of “metabolomics” emerged in the early 2000s as a new branch of “omics” science. It focuses on the characterization of metabolites and metabolic pathways within biological systems. The metabolome itself represents the dynamic confluence of endogenous metabolism and the effects of exogenous exposures from the environment (1). Comprehensive measurement of the metabolome has long been challenged by the limited analytical sensitivity and specificity of available instrumentation, combined with a lack of robustness in sample preparation methods, which can lead to selective loss of metabolites and ambiguity in metabolite annotation. If metabolites cannot be well detected and measured with specificity in complex samples, it becomes difficult to understand what significance they hold with respect to physiological processes (1,2). When combined with the natural complexity of biological samples and the structural diversity of metabolites in living systems, these challenges directly affect the interpretation and downstream impact (translation) of analytical results. From the outset, metabolomics has been widely applied across scientific disciplines. At the 18th annual conference of The Metabolomics Society, held in June 2022 in Spain, the plenary lecture programme featured speakers with interests in personalized and translational medicine, uncovering molecular mechanisms underlying the production of plant metabolites and the regulation of cell metabolism. Much of the conference was also given over to discussions of advanced methods, instrumentation, and bioinformatics/data analysis (3).
This article will examine how researchers at the University of Copenhagen are using advanced mass spectrometry (MS)-based approaches such as trapped ion mobility spectrometry (TIMS) to improve the speed and specificity of their metabolite measurements while adding confidence in their metabolite annotation efforts.
TIMS is an analyte separation technique where ions exhibit differential mobility according to their size and shape, complementing mass analyzers that separate ions according to their mass and charge state. In contrast to a conventional drift analyzer where the ions are passed through stationary gas, TIMS utilizes a stream of moving gas and opposing electric fields to both trap and selectively release ions in the TIMS tunnel (4). In doing so, TIMS provides researchers with an added layer of separation and analytical specificity beyond those provided by mass analysis alone and by chromatography.
A recent study found that when compared to a quadrupole time-of-flight (QTOF)-only mode, TIMS visualized additional metabolite isomers and isobars, enabling imaging-based metabolomics with enhanced sensitivity and specificity at high spatial resolution (5). The result is a more comprehensive analysis of the metabolic profile including nutrients, metabolic by-products, food additives, and more.
Researchers at the Moritz Group (Novo Nordisk Foundation for Basic Metabolic Research; CBMR) have been working to understand the role of the metabolome in the human body. They suggest that metabolomics holds huge promise in spearheading our understanding of metabolic diseases such as type 2 diabetes, liver diseases, and inflammatory bowel disease to name just a few. Their philosophy is that better knowledge of the metabolome will lead to a greater likelihood of developing novel diagnostic procedures and therapeutics that can improve the quality of life for affected patients. The Moritz Group specializes in studying the metabolome in both large-scale analysis of human cohorts and in detailed investigation of metabolite flux in pathways (fluxomics). To achieve this, they devise novel methods to analyze and characterize metabolites that utilize MS technology and benefit from its ability to detect low concentrations of metabolites and characterize the composition of samples more comprehensively than other techniques.
Recent work at CBMR includes a focus on the measurement of nicotinamide adenine dinucleotide (NAD) and its metabolites (the so-called NADome). NAD is an essential coenzyme that is present in all organisms. It serves as a major coenzyme for enzymatic reduction–oxidation reactions and adenosine triphosphate (ATP) production. More recently, NAD has also been shown to be a crucial co-substrate for numerous other enzymes. By identifying NAD levels within the blood, assessments can be made regarding whether or not the individual has a healthy metabolic function. If not, this could indicate the likelihood of a range of age-related or neurodegenerative diseases (6).
Another area of research focuses on identifying defects in the enzymes and transporters that facilitate normal physiological function. Using metabolomics, the Moritz Group is working to identify new biomarkers, altered physiological pathways, and treatment options to diagnose and treat disease in its earlier stages. The group uses technologies such as TIMS and vacuum-insulated probe heated electrospray ionization (VIP-HESI) to enhance analysis of small molecules, achieving high resolution accurate mass measurement with accurate isotropic patterns and detecting even minuscule amounts of metabolites in the samples (Figure 1).
The team has started to include TIMS for different kinds of metabolic profiling. Although the examples—taken from recently published work—that follow show interesting results, how TIMS improves the metabolic profiling in such projects remains an important question.
Most data-driven health programmes fail to understand the association between molecular and phenotypic variability, as the means to analyze these insights is limited. In a recent study, researchers from several European institutions came together to evaluate how the human body responds to lifestyle coaching using several parameters such as clinical measurements, surveys, proteomics, genomics, metabolomics, autoantibodies, and the gut microbiome (7). Researchers at the Moritz Group assisted with metabolomic experiments and interpretations of that data. They identified the metabolites using the retention index obtained from liquid chromatography–mass spectrometry (LC–MS) and gas chromatography–mass spectrometry (GC–MS) systems. The dataset included 136 metabolites obtained from the GC–MS experiments, 104 LC–MS-negative, and 163 positive-LC–MS metabolites verified against a predefined list of metabolites found in plasma and serum.
Using this information, the researchers could integrate the data with datasets obtained for various other parameters (from different institutions). It was found that there was a great degree of individual variation—between 56% and 71% on average—indicating high variability between individuals. The method also allowed them to profile the metabolites based on several parameters such as dietary habits, hepatic function, physical exercise, sleep activity, and body mass index (BMI), which are all influenced by the presence of specific metabolites.
For example, specific factors increased when participants indicated they increased their caffeine consumption. In addition, several metabolites were found to be increased in individuals affected by liver disease. Ultimately, the method allowed them to prove that metabolic pathways differ between individuals based on genetic factors, habits, and current physical state (7).
Carboxylic acids are a critical part of the tricarboxylic acid (TCA) cycle—the core pathway of central carbon metabolism. Essentially, these acids are involved in the glucose metabolism process and are usually studied extensively to understand how these pathways are impacted during diseased states such as cancer and respiratory disorders. It is challenging to extract and characterize them using LC methods because they have high polarity and low retention, which can lead to sample loss. In the case of GC–MS analysis, derivatization is necessary but extremely time‑consuming and laborious. To circumvent these issues, researchers at the Moritz Group devised a method to extract TCA cycle carboxylic acids using mixed mode chromatography (8).
They tested the method on samples such as human plasma, murine brown preadipocytes, and A. thaliana leaves. In this method, LC–MS/MS was used to separate and quantify the underivatized carboxylates. In addition, they used an ultrahigh-pressure liquid chromatography (UHPLC) system to identify untargeted fatty acids in the samples. They changed the mobile phase composition and pH to optimize the process and ensure that the TCA carboxylates were separated and quantified as needed. By doing so, they quantified eight out of 10 carboxylic acids in the murine preadipocyte cells, five acids in the plasma, and six acids in plant tissue, indicating the validity of the method (Figure 2). They also identified 23 fatty acids in plasma, suggesting that its metabolic profiling is possible once the separation process is optimized (8).
Wood formation is a developmental process in which the fully mature xylem has undergone several stages such as cell division, expansion, secondary wall formation, lignification, and apoptosis. Many interactions between transcriptional regulators and signal transduction pathways assist in moving this process along, yet the role of the specific metabolites involved in this process is still unclear. Researchers at the Moritz Group evaluated the impact of metabolites in the wood-forming zone of P. tremula. They used LC–MS and GC–MS to conduct the untargeted profiling of phytohormones in the developing phloem and wood-forming tissue. Aspen ray and fibre cells were also profiled to uncover the metabolic activity in different cell types.
The study found distinct metabolic changes between the primary and secondary wall formation. Visible gradients of metabolites were observed in each stage. For example, Indole 3-acetic acid (IAA) concentrations were much higher in the xylem, whereas cytokinin concentrations were higher in the phloem, signifying the role of hormones in the cell division process (Figure 3).
On the other hand, when xylem vessels and fibres reached the end of the expansion process, there was a marked increase in glucose concentrations. Once the glucose concentrations decreased, the xylose concentrations increased, indicating the progression from primary to secondary wall formation. It was also observed that oligomer concentration increased, showing accumulation and polymerization during the lignification process, although biosynthesis of monolignols does begin during the primary to secondary wall transition phase. This level of profiling was possible due to the LC–QTOF‑MS setup, which allowed the researchers to establish the metabolic gradients at different stages of the wood formation process (9).
Metabolomics plays a significant role in many areas of life science, as it offers the opportunity to profile major genomic and epigenomic pathways. From a clinical standpoint, scientists will be better able to confidently identify metabolites responsible for critical biological pathways and understand how they change when our physiological conditions change—paving the way to highly targeted and personalized treatments for many metabolic and genetic disorders.
Major advances are being made in other areas too, with plant metabolomics being proposed as a new strategy and tool for quality assurance of traditional Chinese medicines (10), and researchers looking to use metabolomics to inform decisions on plant breeding and crop development (11).
In each case, techniques such as TIMS are enhancing the sensitivity, specificity, and speed of metabolite measurement, accelerating the pace of metabolomics research.
(1) Di Minno, A.; Gelzo, M.; Caterino, M.; et al. Challenges in Metabolomics-Based Tests, Biomarkers Revealed by Metabolomic Analysis, and the Promise of the Application of Metabolomics in Precision Medicine. Int. J. Mol. Sci. 2022, 23 (9), 5213. DOI: 10.3390/ijms23095213
(2) Wishart, D.S. Emerging applications of metabolomics in drug discovery and precision medicine. Nat. Rev. Drug Discov. 2016, 15, 473–484. DOI: 10.1038/nrd.2016.32
(3) Metabolomics 2022 Conference Home Page. www.metabolomics2022.org
(4) Ridgeway, M.E.; Lubeck, M.; Jordens, J.; Mann, M.; Park, M.A. Trapped ion mobility spectrometry: A short review. Int. J. Mass Spectrom. 2018, 425, 22–35. DOI: 10.1016/j.ijms.2018.01.006
(5) Neumann, E.K.; Migas, L.G.; Allen, J.L.; et al. Spatial Metabolomics of the Human Kidney Using MALDI Trapped Ion Mobility Imaging Mass Spectrometry. Anal. Chem. 2020, 92 (19), 13084–13091. DOI: 10.1021/acs.analchem.0c02051
(6) Lautrup, S.; Sinclair, D.A.; Mattson, M.P.; Fang, E.F. NAD+ in Brain Aging and Neurodegenerative Disorders. Cell Metab. 2019, 30 (4), 630–655. DOI: 10.1016/j.cmet.2019.09.001
(7) Marabita, F.; James, T.; Karhu, A.; et al. Multiomics and digital monitoring during lifestyle changes reveal independent dimensions of human biology and health. Cell Syst. 2022, 13 (3), 241–255. DOI: 10.1016/j.cels.2021.11.001
(8) Hodek, O.; Argemi-Muntadas, L.; Khan, A.; Moritz, T. Mixed-mode chromatography-mass spectrometry enables targeted and untargeted screening of carboxylic acids in biological samples. Anal. Methods 2022, 14 (10), 1015– 1022. DOI: 10.1039/d1ay02143e
(9) Abreu, I.N.; Johansson, A.I.; Sokołowska, K.; et al. A metabolite roadmap of the wood-forming tissue in Populus tremula. New Phytol. 2020, 22 (5), 1559–1572. DOI: 10.1111/nph.16799
(10) Xiao, Q.; Mu, X.; Liu, J.; et al. Plant metabolomics: a new strategy and tool for quality evaluation of Chinese medicinal materials. Chin. Med. 2022, 17, 45. DOI: 10.1186/s13020-022-00601-y
(11) Sharma, K.; Sarma, S.; Bohra, A.; et al. Plant Metabolomics: An Emerging Technology for Crop Improvement. In New Visions in Plant Science; InTech, 2018. DOI: 10.5772/intechopen.72517
Thomas Moritz is group leader at the Moritz Group, Novo Nordisk Foundation for Basic Metabolic Research, University of Copenhagen, Denmark.
Matthew R. Lewis is director of Metabolomics Applications, Bruker Life Sciences Mass Spectrometry Division.