Isotope-labeled differential profiling of metabolites using N-benzoyloxysuccinimide derivatization coupled to liquid chromatography/high-resolution tandem mass spectrometry

Challenges and recent advances in quantitative mass spectrometry-based metabolomics

The field of metabolomics has gained tremendous interest in recent years. Whether the goal is to discover biomarkers related to certain pathologies or to better understand the impact of a drug or contaminant, numerous studies have demonstrated how crucial it is to understand variations in metabolism. Detailed knowledge of metabolic variabilities can lead to more effective treatments, as well as faster or less invasive diagnostics. Exploratory approaches are often employed in metabolomics, using relative quantitation to look at perturbations between groups of samples. Most metabolomics studies have been based on metabolite profiling using relative quantitation, with very few studies using an approach for absolute quantitation. Using accurate quantitation facilitates the comparison between different studies, as well as enabling longitudinal studies. In this review, we discuss the most widely used techniques for quantitative metabolomics using mass spectrometry (MS). Various aspects will be addressed, such as the use of external and/or internal standards, derivatization techniques, in vivo isotopic labelling, or quantitative MS imaging. The principles, as well as the associated limitations and challenges, will be described for each approach.

Fully automated 18F-fluorination of N-succinimidyl-4-[18F]fluorobenzoate ([18F]SFB) for indirect labelling of nanobodies

N-succinimidyl-4-[¹⁸F]fluorobenzoate ([¹⁸F]SFB), a widely used labeling agent to introduce the 4-[¹⁸F]fluorobenzoyl-prosthetic group, is normally obtained in three consecutive steps from [¹⁸F]fluoride ion. Here, we describe an efficient one-step labeling procedure of [¹⁸F]SFB starting from a tin precursor. This method circumvents volatile radioactive side-products and simplifies automatization. [¹⁸F]SFB was obtained after HPLC purification in a yield of 42 + 4% and a radiochemical purity (RCP) > 99% (n = 6). In addition, we investigate the automation of the coupling of [¹⁸F]SFB to a nanobody (cAbBcII10, targeting β-lactamase enzyme) and purification by size exclusion chromatography (PD-10 desalting column) to remove unconjugated reagent. Production and use of [¹⁸F]SFB were implemented on a radiosynthesis unit (Neptis^®). The fully automated radiosynthesis process including purification and formulation required 160 min of synthesis time. [¹⁸F]SFB-labeled nanobody was obtained in a yield of 21 + 2% (activity yield 12 + 1% non-decay corrected) and a radiochemical purity (RCP) of > 95% (n = 3). This approach simplifies [¹⁸F]SFB synthesis to one-step, enhances the yield in comparison to the previous report and enables the production of radiolabeled nanobody on the same synthesis module.

Chemical Isotope Labeling LC-MS for Metabolomics

Due to the great diversity of chemical and physical properties of metabolites as well as a wide range of concentrations of metabolites present in metabolomic samples, performing comprehensive and quantitative metabolome analysis is a major analytical challenge. Conventional approach of combining various techniques and methods with each detecting a fraction of the metabolome can lead to the increase in overall metabolomic coverage. However, this approach requires extensive investment in equipment and analytical expertise with still relatively low coverage and low sample throughput. Chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) offers an alternative means of increasing metabolomic coverage while maintaining high quantification precision and accuracy. This chapter describes the CIL LC-MS method and its key features for metabolomic analysis.

Systematic Analysis of Fatty Acids in Human Cells with a Multiplexed Isobaric Tag (TMT)-Based Method

Fatty acids (FAs) are essential components in cells and are involved in many cellular activities. Abnormal FA metabolism has been reported to be related to human diseases such as cancer and cardiovascular diseases. Identification and quantification of FAs provide insights into their functions in biological systems, but it is very challenging to analyze them due to their structures and properties. In this work, we developed a novel method by integrating FAs tagged with stable isotope labeled aminoxy tandem mass tags (aminoxyTMTs) and mass spectrometric analysis in the positive mode. On the basis of their structures, the aminoxyTMT reagents reacted with the carboxylic acid group of the FAs, resulting in an amine group with high proton affinity covalently attached to the analytes. This enabled the analysis of FAs under the positive electrospray ionization-mass spectrometry (ESI-MS) mode, which is normally more popular and sensitive compared to the negative mode. More importantly, the multiplexed TMT tags allowed us to quantify FAs from several samples simultaneously, which increased the experimental throughput and quantification accuracy. FAs extracted from three types of breast cells, i.e., MCF 10A (normal), MCF7 (minimally invasive) and MDA-MB-231 (highly invasive) cells, were labeled with the six-plexed aminoxyTMTs and quantified by LC-MS/MS. The results demonstrated that the abundances of some FAs, such as C22:5 and C20:3, were markedly increased in MCF7 and MDA-MB-231 cancer cells compared to normal MCF 10A cells. For the first time, aminoxyTMT reagents were exploited to label FAs for their identification and quantification in complex biological samples in the positive MS mode. The current method enabled us to confidently identify FAs and to accurately quantify them from several samples simultaneously. Because this method does not have sample restrictions, it can be extensively applied for biological and biomedical research.

Development of High-Performance Chemical Isotope Labeling LC-MS for Profiling the Carbonyl Submetabolome

Metabolites containing a carbonyl group represent several important classes of molecules including various forms of ketones and aldehydes such as steroids and sugars. We report a high-performance chemical isotope labeling (CIL) LC-MS method for profiling the carbonyl submetabolome with high coverage and high accuracy and precision of relative quantification. This method is based on the use of dansylhydrazine (DnsHz) labeling of carbonyl metabolites to change their chemical and physical properties to such an extent that the labeled metabolites can be efficiently separated by reversed phase LC and ionized by electrospray ionization MS. In the analysis of six standards representing different carbonyl classes, acetaldehyde could be ionized only after labeling and MS signals were significantly increased for other 5 standards with an enhancement factor ranging from ∼15-fold for androsterone to ∼940-fold for 2-butanone. Differential ¹²C- and ¹³C-DnsHz labeling was developed for quantifying metabolic differences in comparative samples where individual samples were separately labeled with ¹²C-labeling and spiked with a ¹³C-labeled pooled sample, followed by LC-MS analysis, peak pair picking, and peak intensity ratio measurement. In the replicate analysis of a 1:1 ¹²C-/¹³C-labeled human urine mixture (n = 6), an average of 2030 ± 39 pairs per run were detected with 1737 pairs in common, indicating the possibility of detecting a large number of carbonyl metabolites as well as high reproducibility of peak pair detection. The average RSD of the peak pair ratios was 7.6%, and 95.6% of the pairs had a RSD value of less than 20%, demonstrating high precision for peak ratio measurement. In addition, the ratios of most peak pairs were close to the expected value of 1.0 (e.g., 95.5% of them had ratios of between 0.67 and 1.5), showing the high accuracy of the method. For metabolite identification, a library of DnsHz-labeled standards was constructed, including 78 carbonyl metabolites with each containing MS, retention time (RT), and MS/MS information. This library and an online search program for labeled carbonyl metabolite identification based on MS, RT, and MS/MS matches have been implemented in a freely available Website, www.mycompoundid.org . Using this library, out of the 1737 peak pairs detected in urine, 33 metabolites were positively identified. In addition, 1333 peak pairs could be matched to the metabolome databases with most of them belonging to the carbonyl metabolites. These results show that ¹²C-/¹³C-DnsHz labeling LC-MS is a useful tool for profiling the carbonyl submetabolome of complex samples with high coverage.