Advancing Untargeted Metabolomics Through FT‐ICR‐MS: Challenges and Applications

ABSTRACT

Metabolomics is the study of the complete set of small molecules involved in the biochemical processes within a biological system. It links directly to metabolism, capturing the biochemical pathways and processes in a state‐specific manner and aiming to understand the dynamic interactions within these metabolites, including how they reflect the physiological and environmental conditions as well as cellular and physiological responses. Presently, Fourier transform ion cyclotron resonance mass spectrometry (FT‐ICR‐MS) is the highest performance mass spectrometry technology for untargeted metabolomic analysis, allowing the simultaneous detection of thousands of compounds in a single analysis. This analytical performance is due to its extreme mass resolution and exceptional mass accuracy, unmatched by any other type of mass spectrometer. This technology enables precise identification and differentiation of metabolites within complex biological samples, providing highly accurate molecular formulas, based on exact mass and fine isotopic distribution. This review focuses on new developments in FT‐ICR‐MS technology for metabolomic analysis, new methodologies and recent applications. It also addresses the current challenges and perspectives for the use of FT‐ICR‐MS in metabolomics.

The main goal of untargeted metabolomics is to capture a comprehensive, unbiased profile of all metabolites within a sample, providing insights into biochemical pathways, evidencing differences between samples and identifying potential biomarkers. A successful identification of all metabolites depends on the ability of the analytical approach to distinguish compounds with similar masses (highest resolution) with the most accurate mass, and to use the most complete isotopic information to assign molecular formulas and obtain structural information. These characteristics can only be found in Fourier transform ion cyclotron resonance mass spectrometry (FT‐ICR‐MS) instruments. Offering an extreme mass accuracy and mass resolution enables the accurate identification and differentiation of metabolites within biological samples. Moreover, it allows direct infusion analysis for an unbiased sampling of the metabolome. Also, by capturing the precise isotopic pattern of a molecule, FT‐ICR‐MS provides the identification of the elements that make up a molecule, reducing the number of possible formula composition to just one. This is essential to identify unknown metabolites and to discover new ones that are not present in existing databases, thus expanding scientific knowledge of the metabolome. Finally, its high dynamic range allows for the simultaneous detection of both abundant and trace metabolites, giving a more comprehensive profile of the metabolome.

1. Technological and Analytical Versatility of FT‐ICR‐MS

One of the main advantages of using FT‐ICR‐MS in metabolomics analysis is the ability to perform direct injection of the diluted sample, without the need for chromatographic separation, usually followed by its ionization using electrospray (ESI). Using this approach, thousands of compounds can be detected, with a significant increase in metabolome coverage if the analysis is performed in positive and negative ionization modes. In FT‐ICR, it is also possible to use other ionization sources, significantly enhancing its versatility and effectiveness in metabolomics analysis by accommodating the diverse chemical properties of metabolites. Atmospheric Pressure Chemical Ionization (APCI) and Atmospheric Pressure Photoionization (APPI) can be used for non‐polar or less polar compounds [1]. Data obtained from these ionization techniques can be combined with ESI data to provide a more comprehensive metabolic profile, covering the analysis of both hydrophilic and lipophilic metabolites and offering a broader view of metabolic pathways. Matrix‐Assisted Laser Desorption/Ionization (MALDI) and Desorption Electrospray Ionization (DESI) are suitable to perform imaging metabolomics, allowing direct sampling from surfaces and tissues, preserving analyte integrity and enabling rapid profiling of compounds [2, 3]. Ambient ionization methods, such as DESI and Direct Analysis in Real Time (DART), eliminate the need for extensive sample preparation, reducing analysis time and preserving metabolites that might degrade during extraction or derivatization.

The long transient times in FT‐ICR‐MS, often seen as a drawback in high‐throughput contexts, can be an advantage in untargeted metabolomics (reviewed in [4]). The extended scan times allow the instrument to accumulate and analyse ion signals over a longer period, leading to extreme mass resolution and mass accuracy, reduced spectral noise and increased peak sharpness. Also, longer acquisition times enable FT‐ICR‐MS to detect the fine isotopic structure of higher intensity compounds, which is essential to determine the exact molecular formula, further increasing metabolite identification confidence. Another gain of having extended transient times is the improvement of the signal‐to‐noise ratio, therefore enhancing the detection of low‐abundance metabolites.

2. Surpassing Limitations and Challenges

When performing an untargeted metabolomics analysis using FT‐ICR‐MS, reducing ion suppression, being able to differentiate isomers, and analysing massive amounts of extreme‐resolution data, can still be challenging.

2.1. Ion Suppression

Ion suppression is a general concern in untargeted metabolomics analysis. The high sensitivity and resolution of FT‐ICR‐MS can make this effect more apparent and impactful on results, particularly when analysing complex biological samples, resulting in some metabolites being undetected. In ESI, there is a finite amount of charges available in the spray droplets, favouring compounds with higher ionization efficiency and therefore suppressing the ionization of less efficient molecules. Changing the ionization source can overcome this issue, for example, using APCI which is less prone to ion suppression (reviewed in ref. [5]). In addition, the presence of matrix components, such as salts or detergents, can interfere with the efficiency of ion formation, reducing the ionization of the target analytes. To avoid this problem, an effective clean‐up of the sample should be performed to remove interfering matrix components, either applying solid‐phase extraction (SPE) or liquid–liquid extraction (LLE) (reviewed in [5]). A novel approach involving a post‐column infusion of internal standards for reversed‐phase LC‐FT‐ICR‐MS was proposed to enable semi‐quantitative non‐targeted analysis [6]. This method helped in compensating for ion suppression effects, by providing a reference for signal normalization, and mass peak intensities can be used for semi‐quantification of compound abundances between compositionally similar samples.

2.2. Isomer Differentiation

Isomer differentiation is an important challenge in FT‐ICR‐MS, since compounds with identical molecular formulas and exact mass, but with a different structure, cannot be distinguished based on mass‐to‐charge (m/z) values alone. Chromatographic separation is the most easy and obvious approach to overcome this issue, with the successful separation of isomers through retention time. However, liquid chromatography (LC) separation leads to variable ion populations inside the ICR cell [7].

The use of ion mobility coupled to MS is an alternative strategy for isomer separation, since ions are separated inside the MS instrument based on their cross‐sectional area [7]. When coupled to FT‐ICR‐MS, trapped ion mobility separation (TIMS) improves small molecule coverage in complex mixtures and allows isomer separation [7, 8]. Recently, two new methodologies were developed, based on ion mobility separation integrated in an FT‐ICR mass spectrometer. The first, reports a dual accumulation analysis with gated trapped ion mobility spectrometry (gTIMS) coupled to an FT‐ICR‐MS [9]. The gated TIMS allowed for precise control over ion mobility separation, effectively separating isomers based on their collisional cross‐sections before mass analysis. This technology was used in the direct analysis of bio‐oils and allowed to distinguish all isomer molecules, with the same resolving power and mass accuracy characteristic of FT‐ICR‐MS [9]. The second one, explores the use of Selected Accumulation‐Trapped Ion Mobility Spectrometry (SA‐TIMS) combined with FT‐ICR MS for the separation and identification of isomeric glycan mixtures [10]. When applied to permethylated tetrasaccharides, this method achieved baseline separation of isomers, demonstrating its potential for detailed structural characterization of glycans [10].

2.3. Data Analysis and Interpretation

FT‐ICR‐MS generates massive amounts of extreme‐resolution data that are computationally intensive to process and analyse. Mass spectra are extremely complex, requiring advanced software tools and algorithms for peak assignment, normalization, isotopic pattern recognition and molecular formula determination. A recent study assessed the performance of eight post‐acquisition normalization methods to determine how data merging impacted the subsequent analyses [11]. The findings provide insights into optimizing data processing workflows in untargeted metabolomics to enhance analytical accuracy and reliability.

The creation of specialized software tools and analytical pipelines has streamlined the processing of complex FT‐ICR‐MS data, enabling more efficient data exploration, visualization and statistical analysis. MetaboDirect was recently developed as a free analytical pipeline designed for processing FT‐ICR‐MS data, facilitating data exploration and visualization in metabolomic profiles [12]. One of the novelties of these type of software is the ability to generate biochemical transformation networks based on mass differences, providing an experimental assessment of compound connections and revealing important information about the possible pathways involved.

The challenge of incomplete metabolite databases in untargeted metabolomics, especially concerning rare or unknown metabolites from secondary metabolism, has been a significant obstacle in comprehensive compound identification. Taking advantage of the extremely accurate mass and isotopic fine structure determinations only obtained from FT‐ICR‐MS, an extensive molecular formula library tailored for extreme resolution MS was created and used to annotate complex sample metabolomes [13]. This work represents a significant step forward in the analytical capabilities of FT‐ICR‐MS for studying complex mixtures, providing a valuable resource for future research in untargeted metabolomics.

2.4. Cost and Other Constraints

FT‐ICR‐MS instruments rely on extremely powerful superconducting magnets for ion‐trapping and to achieve their extreme resolution and mass accuracy. However, high‐field magnets (12T, 15T, 18T or higher) are physically large and heavy, require a very complex infrastructure (including cryogenic cooling systems), and are extremely expensive to manufacture, maintain and operate. The large footprint and costs of FT‐ICR‐MS instruments can be a limiting factor for many laboratories, with only a few specialized facilities being able to house high‐field FT‐ICR‐MS instruments. Being aware that these restrictions, the European network of FT‐ICR‐MS (https://www.eu‐fticr‐ms.eu/) was created to provide access to this technology in Europe and beyond, by sharing resources, expertise and infrastructure. Some centres of the network have high expertise in untargeted metabolomics analysis.

It is true that resolution increases linearly with the strength of the magnetic field, since higher fields enable better confinement of ions and longer detection periods. Nevertheless, extreme resolution can be achieved in lower field FT‐ICR instruments even at 7T, not just by increasing acquisition time but also by using data processing ‘boosters’ to enhance the resolution and analytical performance, by leveraging advanced computational techniques, such as Fourier Transform post‐processing and enhanced signal extraction algorithms. The integration of these ‘booster’ technologies with FT‐ICR‐MS instruments offers several advantages for untargeted metabolomics, like improved mass resolving power and accuracy, facilitating the detection and identification of a broader range of metabolites, reduced acquisition times, enabling the analysis of more samples within a given timeframe, and performance enhancement without the need for entirely new systems, offering a more accessible solution for advancing metabolomics research. While these advanced data acquisition and processing systems have been developed to enhance FT‐ICR‐MS performance, specific applications of these boosters in metabolomics are still limited. A booster system coupled to a 7T FT‐ICR‐MS instrument was used in mass spectrometry imaging to improve sensitivity, mass resolution and throughput, enabling faster acquisition times without compromising data quality [2]. Very recently, this technology was applied to a 9.4T FT‐ICR‐MS instrument, for external data acquisition and processing, to enhance the equipment performance in the characterization of dissolved organic matter (DOM) [14]. In this work, 2D‐IMS‐FT‐ICR mass spectrometry data of DOM were reprocessed with the 1D MS chemical framework acquired at 21T, having achieved a considerable increase in isomers identification. Despite this is not being metabolomics analysis, it deals with a sample of comparable complexity and of biological origin and highlights the future integration of 2D processing algorithms in these boosters’ data acquisition systems to improve the signal‐to‐noise ratio and resolution in lower field FT‐ICR‐MS instruments, essential for untargeted metabolomics.

3. Recent Applications in Untargeted Metabolomics

As mentioned, an untargeted metabolomics study links directly to metabolism, focusing on biologically relevant metabolites and aiming to understand how these detected compounds reflect the physiological or pathological state of the organism. Over the last year, FT‐ICR‐MS has been used for the untargeted analysis of different complex biological samples, from bacteria, plants and human.

Plants produce an extensive range of primary and secondary metabolites, including alkaloids, phenolics, flavonoids, terpenes and specialized lipids. FT‐ICR‐MS extreme resolution and mass accuracy enables the detection and differentiation of these compounds, even in highly complex samples (reviewed in [4]). The metabolome of Eugenia uniflora leaves, collected in three different regions and at three different time‐points of the day, were analysed by FT‐ICR‐MS, to assess the best metabolic conditions for the production of flavonoids and phenolic compounds [15]. Phenolic compounds were further characterized also by FT‐ICR‐MS to identify the ones responsible for the anti‐Helicobacter pylori activity and cytotoxicity against the gastric adenocarcinoma cells [16]. A similar study was conducted in Centella asiatica extracts, and bioactive compounds with significant antioxidant and antiglycation activities were identified [17]. The metabolomes of the peel and pulp of Aurantii Fructus Immaturus, the dried immature fruits of bitter orange (Citrus aurantium L.), were analysed using MALDI‐FT‐ICR mass spectrometry imaging to investigate the spatial distribution of several compounds [18]. The different parts of the fruit have shown distinct metabolome compositions, being particularly relevant upon harvesting to obtain fruits with increased nutrient content. In Arabidopsis thaliana, the FT‐ICR‐MS metabolomic analysis of pollen and roots, two apical growing cells’ structures, revealed quite a few similarities [19]. The metabolome analysis was also performed in the eca4 and epsin3 mutant cells, which exhibited a different pollen tube morphology, and significant changes were detected in their metabolism, particularly at the lipid profile, amino acids composition and carbohydrate metabolism. These results underscore the utility of FT‐ICR‐MS in providing a comprehensive metabolomic coverage, allowing for the identification of specific metabolic changes linked to the mutant plants and highlighting how metabolomic shifts contribute to the phenotypic abnormalities observed in these mutants [19]. The FT‐ICR‐MS analysis of pearl millet (Pennisetum glaucum (L.) R.Br.) compartments and root exudates also revealed significant differences in metabolic profiles across shoots, roots and root‐associated soil among the different plant lines, correlated with their soil aggregation abilities [20]. These findings highlight the pivotal role of root exudates in shaping root‐associated microbiota composition and rhizosheath structure, emphasizing the connection between plant metabolites and microbial communities in the rhizosphere [20]. FT‐ICR‐MS was also used to analyse the metabolome of plant growth‐promoting rhizobacteria (PGPR) of the genus Bacillus and Pseudomonas, revealing the compounds responsible for their antifungal activity [21]. The elucidation of these microorganisms’ metabolomes and the mechanisms underlying their interactions with plants will contribute to pave the way for innovative approaches towards sustainable agricultural practices.

FT‐ICR‐MS has been applied across various human and human‐related studies, showcasing its versatility and power in metabolomics. For instance, the lipid remodelling in antibiotic‐tolerant Acinetobacter baumannii persister cells was revealed using MALDI‐FT‐ICR‐MS, providing insights into bacterial adaptation mechanisms that may impact human health [22]. In a nutritional and child development context, FT‐ICR‐MS was employed to profile the bioactive compounds in maternal milk, identifying similarities between the gut microbiota of infants and the composition of human milk [23]. This study suggest that mothers shared their bacteriome and key metabolites with the child through their milk, thus acting as protective and health‐promoting agents in infants [23]. The cardiac metabolism was studied through a combined approach using FT‐ICR‐MS and high‐resolution liquid chromatography quadrupole time‐of‐flight tandem MS (LC‐Q‐TOF‐MS/MS), to obtain a comprehensive analysis of the human heart metabolome [24]. Collectively, these studies demonstrate the power of FT‐ICR‐MS in untargeted metabolomics studies to advance the understanding of human‐related biological systems and their interactions with health and disease.

4. Summary and Outlook

Technological developments in FT‐ICR‐MS are crucial for advancing untargeted metabolomics, as they directly address the challenges inherent in analysing complex biological samples. Enhanced ionization techniques and better integration of complementary technologies, such as ion mobility spectrometry (IMS), further improve the separation of isomers and the characterization of complex mixtures. In addition, advancements in data processing and software allow for more efficient handling and interpretation of the massive amounts of high‐resolution data generated by FT‐ICR‐MS, making it possible to identify and quantify a wider array of metabolites. These developments have transformed FT‐ICR‐MS into a powerful tool for comprehensive, unbiased metabolomic profiling, allowing for deeper insights into metabolic pathways, disease mechanisms and biomarker discovery. Overall, technological progress in FT‐ICR‐MS is fundamental to keep pushing the boundaries of untargeted metabolomics, enabling researchers to achieve more accurate, reliable and detailed metabolic analyses, with very small sample amounts and very little sample preparation. The analysis of single‐cell metabolomes, rare sample collections or studies involving endangered species or fragile tissues is a possibility using this technology.

Author Contributions

Marta Sousa Silva: conceptualization, funding acquisition, writing – original draft, writing – review and editing. Carlos Cordeiro: conceptualization, funding acquisition, investigation, methodology, writing – original draft, writing – review and editing.

Conflicts of Interest

The authors declare no conflicts of interest.

Silva M. S. and Cordeiro C., “Advancing Untargeted Metabolomics Through FT‐ICR‐MS: Challenges and Applications.” Analytical Science Advances 6, no. 2 (2025): 6, e70036. 10.1002/ansa.70036

Data Availability Statement

The authors have nothing to report.