Ultrahigh-resolution Fourier Transform Mass Spectrometry Research Articles

Mass Difference Matching Unfolds Hidden Molecular Structures of Dissolved Organic Matter.

Ultrahigh-resolution Fourier transform mass spectrometry (FTMS) has revealed unprecedented details of natural complex mixtures such as dissolved organic matter (DOM) on a molecular formula level, but we lack approaches to access the underlying structural complexity. We here explore the hypothesis that every DOM precursor ion is potentially linked with all emerging product ions in FTMS2 experiments. The resulting mass difference (Δm) matrix is deconvoluted to isolate individual precursor ion Δm profiles and matched with structural information, which was derived from 42 Δm features from 14 in-house reference compounds and a global set of 11 477 Δm features with assigned structure specificities, using a dataset of ∼18 000 unique structures. We show that Δm matching is highly sensitive in predicting potential precursor ion identities in terms of molecular and structural composition. Additionally, the approach identified unresolved precursor ions and missing elements in molecular formula annotation (P, Cl, F). Our study provides first results on how Δm matching refines structural annotations in van Krevelen space but simultaneously demonstrates the wide overlap between potential structural classes. We show that this effect is likely driven by chemodiversity and offers an explanation for the observed ubiquitous presence of molecules in the center of the van Krevelen space. Our promising first results suggest that Δm matching can both unfold the structural information encrypted in DOM and assess the quality of FTMS-derived molecular formulas of complex mixtures in general.

Quantification of Isotopologues of Amino Acids by Multiplexed Stable Isotope-Resolved Metabolomics Using Ultrahigh-Resolution Mass Spectrometry Coupled with Direct Infusion.

Stable isotope-resolved metabolomics (SIRM) is increasingly used among researchers for metabolic studies including amino acid metabolism. However, the classical GC- or HPLC-based methods for amino acid quantification do not meet the needs for multiplexed stable isotope-enriched analysis by ultrahigh-resolution Fourier transform mass spectrometry (UHR-FTMS). This is due to insufficient acquisition time during chromatographic separations and large dynamic range in concentrations of analytes, which compromises detection and quantification of the numerous metabolite isotopologues present in crude extracts. This chapter discusses a modified ethyl chloroformate derivatization method to enable rapid quantitative analysis of stable isotope-enriched amino acids using direct infusion ion introduction coupled with UHR-FTMS.

Chloroformate derivatization for tracing the fate of Amino acids in cells and tissues by multiple stable isotope resolved metabolomics (mSIRM)

Amino acids have crucial roles in central metabolism, both anabolic and catabolic. To elucidate these roles, steady-state concentrations of amino acids alone are insufficient, as each amino acid participates in multiple pathways and functions in a complex network, which can also be compartmentalized. Stable Isotope-Resolved Metabolomics (SIRM) is an approach that uses atom-resolved tracking of metabolites through biochemical transformations in cells, tissues, or whole organisms. Using different elemental stable isotopes to label multiple metabolite precursors makes it possible to resolve simultaneously the utilization of these precursors in a single experiment. Conversely, a single precursor labeled with two (or more) different elemental isotopes can trace the allocation of e.g. C and N atoms through the network.Such dual-label experiments however challenge the resolution of conventional mass spectrometers, which must distinguish the neutron mass differences among different elemental isotopes. This requires ultrahigh resolution Fourier transform mass spectrometry (UHR-FTMS). When combined with direct infusion nano-electrospray ion source (nano-ESI), UHR-FTMS can provide rapid, global, and quantitative analysis of all possible mass isotopologues of metabolites. Unfortunately, very low mass polar metabolites such as amino acids can be difficult to analyze by current models of UHR-FTMS, plus the high salt content present in typical cell or tissue polar extracts may cause unacceptable ion suppression for sources such as nano-ESI.Here we describe a modified method of ethyl chloroformate (ECF) derivatization of amino acids to enable rapid quantitative analysis of stable isotope labeled amino acids using nano-ESI UHR-FTMS. This method showed excellent linearity with quantifiable limits in the low nanomolar range represented in microgram quantities of biological specimens, which results in extracts with total analyte abundances in the low to sub-femtomole range. We have applied this method to profile amino acids and their labeling patterns in 13C and 2H doubly labeled PC9 cell extracts, cancerous and non-cancerous tissue extracts from a lung cancer patient and their protein hydrolysates as well as plasma extracts from mice fed with a liquid diet containing 13C6-glucose (Glc).The multi-element isotopologue distributions provided key insights into amino acid metabolism and intracellular pools in human lung cancer tissues in high detail. The 13C labeling of Asp and Glu revealed de novo synthesis of these amino acids from 13C6-Glc via the Krebs cycle, specifically the elevated level of 13C3-labeled Asp and Glu in cancerous versus non-cancerous lung tissues was consistent with enhanced pyruvate carboxylation. In addition, tracking the fate of double tracers, (13C6-Glc + 2H2-Gly or 13C6-Glc + 2H3-Ser) in PC9 cells clearly resolved pools of Ser and Gly synthesized de novo from 13C6-Glc (13C3-Ser and 13C2-Gly) versus Ser and Gly derived from external sources (2H3-Ser, 2H2-Gly). Moreover the complex 2H labeling patterns of the latter were results of Ser and Gly exchange through active Ser-Gly one-carbon metabolic pathway in PC9 cells.