Hydrogen/Deuterium Exchange Aiding Compound Identification for LC-MS and MALDI Imaging Lipidomics

In-Electrospray source Hydrogen/Deuterium exchange coupled to multistage fragmentation for the investigation of the protonation and fragmentation pathways of gas phase ions

Identification of molecules in complex natural matrices relies on matching the fragmentation spectra of ions under investigation and the spectra acquired for the corresponding analytical standards. Currently, there are many databases of experimentally measured tandem mass spectrometry spectra (such as NIST, MzCloud, and Metlin), and considerable progress has been made in the development of software for predicting tandem mass spectrometry fragments in silico using combinatorial, machine learning, and quantum chemistry approaches (such as MetFrag, CFM-ID, and QCxMS). However, the electrospray ionization molecules can be ionized at different sites (protonated or deprotonated), and the fragmentation spectra of such ions are different. Here, we are using the combination of the in-ESI source hydrogen/deuterium exchange reaction and MSn fragmentation for the investigation of the fragmentation pathways for different protomers of organic molecules. It is shown that the distribution of the deuterium in the fragment ions reflects the presence of different protomers. For several molecules, the distribution of deuterium was traced up to the MS5 level of fragmentation revealing many unusual and unexpected effects. For example, we investigated the loss of HF from the ciprofloxacin and norfloxacin ions and observed that for ions protonated at -COOH group, the eliminating hydrogen always comes from -NH group. When ions are protonated at another site, the elimination of hydrogen with a probability of 30% occurs from the -NH group, and with a probability of 70%, it originates from other sites on the molecule. Such effects were not described previously. Quantum chemical simulation was used for the verification of the protonated structures and simulation of the corresponding fragmentation spectra.

Hydrophilic Interaction Liquid Chromatography-Hydrogen/Deuterium Exchange-Mass Spectrometry (HILIC-HDX-MS) for Untargeted Metabolomics

Liquid chromatography with mass spectrometry (LC-MS)-based metabolomics detects thousands of molecular features (retention time-m/z pairs) in biological samples per analysis, yet the metabolite annotation rate remains low, with 90% of signals classified as unknowns. To enhance the metabolite annotation rates, researchers employ tandem mass spectral libraries and challenging in silico fragmentation software. Hydrogen/deuterium exchange mass spectrometry (HDX-MS) may offer an additional layer of structural information in untargeted metabolomics, especially for identifying specific unidentified metabolites that are revealed to be statistically significant. Here, we investigate the potential of hydrophilic interaction liquid chromatography (HILIC)-HDX-MS in untargeted metabolomics. Specifically, we evaluate the effectiveness of two approaches using hypothetical targets: the post-column addition of deuterium oxide (D2O) and the on-column HILIC-HDX-MS method. To illustrate the practical application of HILIC-HDX-MS, we apply this methodology using the in silico fragmentation software MS-FINDER to an unknown compound detected in various biological samples, including plasma, serum, tissues, and feces during HILIC-MS profiling, subsequently identified as N1-acetylspermidine.

Schisandra lignans ameliorate nonalcoholic steatohepatitis by regulating aberrant metabolism of phosphatidylethanolamines

Nonalcoholic steatohepatitis (NASH) is a spectrum of chronic liver disease characterized by hepatic lipid metabolism disorder. Recent reports emphasized the contribution of triglyceride and diglyceride accumulation to NASH, while the other lipids associated with the NASH pathogenesis remained unexplored. The specific purpose of our study was to explore a novel pathogenesis and treatment strategy of NASH via profiling the metabolic characteristics of lipids. Herein, multi-omics techniques based on LC-Q-TOF/MS, LC-MS/MS and MS imaging were developed and used to screen the action targets related to NASH progress and treatment. A methionine and choline deficient (MCD) diet-induced mouse model of NASH was then constructed, and Schisandra lignans extract (SLE) was applied to alleviate hepatic damage by regulating the lipid metabolism-related enzymes CES2A and CYP4A14. Hepatic lipidomics indicated that MCD-diet led to aberrant accumulation of phosphatidylethanolamines (PEs), and SLE could significantly reduce the accumulation of intrahepatic PEs. Notably, exogenous PE (18:0/18:1) was proved to significantly aggravate the mitochondrial damage and hepatocyte apoptosis. Supplementing PE (18:0/18:1) also deteriorated the NASH progress by up regulating intrahepatic proinflammatory and fibrotic factors, while PE synthase inhibitor exerted a prominent hepatoprotective role. The current work provides new insights into the relationship between PE metabolism and the pathogenesis of NASH.

Untargeted Lipidomics after D2O Administration Reveals the Turnover Rate of Individual Lipids in Various Organs of Living Organisms

The administration of low doses of D₂O to living organisms was used for decades for the investigation of metabolic pathways and for the measurement of the turnover rate for specific compounds. Usually, the investigation of the deuterium uptake in lipids is performed by measuring the deuteration level of the palmitic acid residue using GC-MS instruments, and to our knowledge, the application of the modern untargeted LC-MS/MS lipidomics approaches was only reported a few times. Here, we investigated the deuterium uptake for >500 lipids for 13 organs and body liquids of mice (brain, lung, heart, liver, kidney, spleen, plasma, urine, etc.) after 4 days of 100% D₂O administration. The maximum deuteration level was observed in the liver, plasma, and lung, while in the brain and heart, the deuteration level was lower. Using MS/MS, we demonstrated the incorporation of deuterium in palmitic and stearic fragments in lipids (PC, PE, TAG, PG, etc.) but not in the corresponding free forms. Our results were analyzed based on the metabolic pathways of lipids.

Identification of endogenous carbonyl steroids in human serum by chemical derivatization, hydrogen/deuterium exchange mass spectrometry and the quantitative structure-retention relationship

Steroids are tetracyclic aliphatic compounds, and most of them contain carbonyl groups. The disordered homeostasis of steroids is closely related to the occurrence and progression of various diseases. Due to high structural similarity, low concentrations in vivo, poor ionization efficiency, and interference from endogenous substances, it is very challenging to comprehensively and unambiguously identify endogenous steroids in biological matrix. Herein, an integrated strategy was developed for the characterization of endogenous steroids in serum based on chemical derivatization, ultra-performance liquid chromatography quadrupole Exactive mass spectrometry (UPLC-Q-Exactive-MS/MS), hydrogen/deuterium (H/D) exchange, and a quantitative structure-retention relationship (QSRR) model. To enhance the mass spectrometry (MS) response of carbonyl steroids, the ketonic carbonyl group was derivatized by Girard T (GT). Firstly, the fragmentation rules of derivatized carbonyl steroid standards by GT were summarized. Then, carbonyl steroids in serum were derivatized by GT and identified based on the fragmentation rules or by comparing retention time and MS/MS spectra with those of standards. H/D exchange MS was utilized to distinguish derivatized steroid isomers for the first time. Finally, a QSRR model was constructed to predict the retention time of the unknown steroid derivatives. With this strategy, 93 carbonyl steroids were identified from human serum, and 30 of them were determined to be dicarbonyl steroids by the charge number of characteristic ions and the number of exchangeable hrdrogen or comparing with standards. The QSRR model built by the machine learning algorithms has an excellent regression correlation, thus the accurate structures of 14 carbonyl steroids were determined, among which three steroids were reported for the first time in human serum. This study provides a new analytical method for the comprehensive and reliable identification of carbonyl steroids in biological matrix.

Hydrogen-Deuterium-Exchange-Based Mass Distribution Shifts in High-Resolution Cyclic Ion Mobility Separations

The mass distribution of ions influences separations in ion mobility spectrometry-mass spectrometry (IMS-MS). Herein, we introduce a method to induce mass distribution shifts for various analytes using hydrogen-deuterium exchange (HDX) immediately prior to ionization using a dual syringe approach. By replacing labile hydrogens on analytes with deuteriums, we were able to differentiate isomers using separations of isotopologues. For each analyte studied, every possible level of deuteration (from undeuterated to fully deuterated) was generated and then separated using cyclic ion mobility spectrometry-mass spectrometry (cIMS-MS). The information gained from such separations (relative arrival times; t_Rel. values) was found to be orthogonal to conventional IMS-MS separations. Additionally, the observed shifts were linearly additive with increasing deuteration, suggesting that this methodology could be extended to analytes with a larger number of labile hydrogens. For one isomer pair, as few as two deuteriums were able to produce a large enough mass distribution shift to differentiate isomers. In another experiment, we found that the mass distribution shift was large enough to overcome the reduced mass contribution, resulting in a "flipped" arrival time where the heavier deuterated isotopologue arrived before the lighter one. In this work, we present a proof-of-concept demonstration that mass-distribution-based shifts, t_Rel. values, could potentially act as an added dimension to characterize molecules in IMS-MS. We anticipate, along with future work in this area, that mass-distribution-based shifts could enable the identification of unknown molecules through a database-driven approach in an analogous fashion to collision cross section (CCS) measurements.

Separation of mass spectra of hydrogen-deuterium exchanged ions obtained by electrospray of solutions of biopolymers with unknown primary structure

The work is dedicated to further development of our described method for analyzing mass spectra of biomolecules acquired as a result of hydrogen-deuterium exchange reactions (HDXs). The modified method consists of separating HDX distributions via their approximations by a minimum number of components corresponding to independent H/D substitutions and independent charge carrier retentions in different spatial isoforms or conformations of biomolecules with unknown primary structures. In this case, neither the natural isotopic distribution nor the exact number of active sites involved in HDXs and H⁺ or D⁺ attachments can be determined in advance. Original H/D electrospray mass spectra of an apamin solution were taken from our previous work. In that work, taking into account the natural isotopic distribution of apamin molecules, three main conformations of apamin ions were found as a result of separating the H/D mass spectra of the apamin solution for the gas flow with the addition of about 10% ND₃ molecules. Using the proposed modified method that does not require knowledge of the primary structure of the biomolecules gave similar results with slight deviations of calculated HDX distributions of the apamin ions from those obtained earlier. The maximum difference between mean values of the calculated HDX distributions for ions of the same charge in both cases does not exceed a few percent. In addition, HDX mass spectra of the apamin complex with an adduct of unknown structure were processed. Such analysis gave also three main fractions of ions with relatively large contributions when ND₃ was injected into a radio-frequency quadrupole. In the absence of ND₃ flow, the results of calculations for apamin and its complex were close to each other too. The formation of the apamin complex most probably in solution was confirmed by performed calculations.

Single‐Photon‐Induced Post‐Ionization to Boost Ion Yields in MALDI Mass Spectrometry Imaging**

Matrix‐assisted laser desorption/ionization mass spectrometry imaging (MALDI‐MSI) is a rapidly growing method in the life sciences. However, for many analyte classes, its sensitivity is limited due to poor ionization efficiencies. To mitigate this problem, we here introduce a novel post‐ionization scheme based on single‐photon induced chemical ionization using pulsed RF‐Kr lamps. The fine‐vacuum conditions of a dual ion‐funnel ion source effectively thermalize the evolving MALDI plume and enable ample gas‐phase reactions. Injected chemical dopants crucially support fragment‐less ionization to [M+H]⁺/[M−H]⁻ species. Based on this interplay, numerous glycerophospho‐, sphingo‐, and further lipids, registered from mammalian tissue sections, were boosted by up to three orders of magnitude, similar to results obtained with laser‐based post‐ionization (MALDI‐2). Experiments with deuterated matrix and dopant, however, indicated complex chemical ionization pathways different from MALDI‐2.

Efficient Hydrogen-Deuterium Exchange in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging for Confident Metabolite Identification

Highly efficient hydrogen-deuterium exchange (HDX) is developed for mass spectrometry imaging (MSI) with low-vacuum matrix-assisted laser desorption/ionization (MALDI). A HDX efficiency of 73-85% is achieved by introducing D₂O vapor into a heated MALDI source in combination with a deuterium-labeled matrix, which allows correct determination of the number of possible H/D exchanges for up to 17 labile hydrogens. This provides valuable orthogonal information to supplement m/z, allowing for increased confidence in metabolite identification while retaining the spatial information MSI supplies. When combined with high-throughput METASPACE annotation, this approach can systematically improve untargeted metabolite annotations in MALDI-MS imaging. The developed method was applied to MALDI-MS imaging of the top surface, bottom surface, and middle section of Lemna minor fronds. Out of a total of 56 on-sample annotations made with the BraChem database using a 10% false discovery rate, 31 of these annotations (55%) matched our HDX data, providing additional confidence. For the remaining 45%, our data allowed us to narrow down structural possibilities and eliminate incorrect structures, greatly increasing confidence in metabolite identification.

Analysis of 16O/18O and H/D Exchange Reactions between Carbohydrates and Heavy Water Using High-Resolution Mass Spectrometry

Mono- and polysaccharides are an essential part of every biological system. Identifying underivatized carbohydrates using mass spectrometry is still a challenge because carbohydrates have a low capacity for ionization. Normally, the intensities of protonated carbohydrates are relatively low, and in order to increase the corresponding peak height, researchers add Na⁺, K⁺, or NH₄⁺to the solution. However, the fragmentation spectra of the corresponding ions are very poor. Based on this, reliably identifying carbohydrates in complex natural and biological objects can benefit frommeasuring additional molecular descriptors, especially those directly connected to the molecular structure. Previously, we reported that the application of the isotope exchange approach (H/D and ¹⁶O/¹⁸O) to high-resolution mass spectrometry can increase the reliability of identifying drug-like compounds. Carbohydrates possess many -OH and -COOH groups, making it reasonable to expect that the isotope exchange approach would have considerable potential for detecting carbohydrates. Here, we used a collection of standard carbohydrates to investigate the isotope exchange reaction (H/D and ¹⁶O/¹⁸O) in carbohydrates and estimate its analytical applications.

PyFragMS-A Web Tool for the Investigation of the Collision-Induced Fragmentation Pathways

Dissociation induced by the accumulation of internal energy via collisions of ions with neutral molecules is one of the most important fragmentation techniques in mass spectrometry (MS), and the identification of small singly charged molecules is based mainly on the consideration of the fragmentation spectrum. Many research studies have been dedicated to the creation of databases of experimentally measured tandem mass spectrometry (MS/MS) spectra (such as MzCloud, Metlin, etc.) and developing software for predicting MS/MS fragments in silico from the molecular structure (such as MetFrag, CFM-ID, CSI:FingerID, etc.). However, the fragmentation mechanisms and pathways are still not fully understood. One of the limiting obstacles is that protomers (positive ions protonated at different sites) produce different fragmentation spectra, and these spectra overlap in the case of the presence of different protomers. Here, we are proposing to use a combination of two powerful approaches: computing fragmentation trees that carry information of all consecutive fragmentations and consideration of the MS/MS data of isotopically labeled compounds. We have created PyFragMS-a web tool consisting of a database of annotated MS/MS spectra of isotopically labeled molecules (after H/D and/or ¹⁶O/¹⁸O exchange) and a collection of instruments for computing fragmentation trees for an arbitrary molecule. Using PyFragMS, we investigated how the site of protonation influences the fragmentation pathway for small molecules. Also, PyFragMS offers capabilities for performing database search when MS/MS data of the isotopically labeled compounds are taken into account.

Amine additives for improved in-ESI H/D exchange

In-ESI H/D exchange is a convenient technique for analyzing small-molecular complex mixtures.

Interactive Estimation of Heterogeneity from Mass Spectrometry Imaging

In this work, we demonstrate a new approach for interactively assessing hyperspectral data spatial structures for heterogeneity using mass spectrometry imaging. This approach is based on the visualization of the cosine distance as the similarity levels between mass spectra of a chosen region and the rest of the image (sample). The applicability of the method is demonstrated on a set of mass spectrometry images of frontal mouse brain slices. Selection of the reference pixel of the mass spectrometric image and a further view of the corresponding cosine distance map helps to prepare supporting vectors for further analysis, select features, and carry out biological interpretation of different tissues in the mass spectrometry context with or without histological annotation. Visual inspection of the similarity maps reveals the spatial distribution of features in tissue samples, which can serve as the molecular histological annotation of a slide.

Structure-Preserving and Perceptually Consistent Approach for Visualization of Mass Spectrometry Imaging Datasets

Mass spectrometry imaging (MSI) has become an important tool for 2D profiling of biological tissues, allowing for the visualization of individual compound distributions in the sample. Based on this information, it is possible to investigate the molecular organization within any particular tissue and detect abnormal regions (such as tumor regions) and many other biologically relevant phenomena. However, the large number of compounds present in the spectra hinders the productive analysis of large MSI datasets when utilizing standard tools. The heterogeneity of samples makes exploratory visualization (a presentation of the general idea of the molecular and structural organization of the inspected tissues) challenging. Here, we explore the application of various dimensionality reduction techniques that have been used extensively in the visualization of hyperspectral images and the MSI data specifically, such as principal component analysis, independent component analysis, non-negative matrix factorization, t-distributed stochastic neighbor embedding, and uniform manifold approximation and projection. Further, we propose a new approach based on a combination of structure preserving visualization with nonlinear manifold embedding of normalized spectral data. This way, we aim to preserve as much spatially overlapping signals as possible while augmenting them with information on compositional (spectral) variation. The proposed approach can be used for exploratory visualization of MSI datasets without prior deep chemical or histological knowledge of the sample. Thus, different datasets can be visually compared employing the proposed method. The proposed approach allowed for the clear visualization of the molecular layer, granular layer, and white matter in chimpanzee and macaque cerebellum slices.

A large-scale genome-lipid association map guides lipid identification

Despite the crucial roles of lipids in metabolism, we are still at the early stages of comprehensively annotating lipid species and their genetic basis. Mass spectrometry-based discovery lipidomics offers the potential to globally survey lipids and their relative abundances in various biological samples. To discover the genetics of lipid features obtained through high-resolution liquid chromatography-tandem mass spectrometry, we analysed liver and plasma from 384 diversity outbred mice, and quantified 3,283 molecular features. These features were mapped to 5,622 lipid quantitative trait loci and compiled into a public web resource termed LipidGenie. The data are cross-referenced to the human genome and offer a bridge between genetic associations in humans and mice. Harnessing this resource, we used genome-lipid association data as an additional aid to identify a number of lipids, for example gangliosides through their association with B4galnt1, and found evidence for a group of sex-specific phosphatidylcholines through their shared locus. Finally, LipidGenie's ability to query either mass or gene-centric terms suggests acyl-chain-specific functions for proteins of the ABHD family.

Hydrogen/Deuterium and 16O/18O-Exchange Mass Spectrometry Boosting the Reliability of Compound Identification

Accurate and reliable identification of chemical compounds is the ultimate goal of mass spectrometry analyses. Currently, identification of compounds is usually based on the measurement of the accurate mass and fragmentation spectrum, chromatographic elution time, and collisional cross section. Unfortunately, despite the growth of databases of experimentally measured MS/MS spectra (such as MzCloud and Metlin) and developing software for predicting MS/MS fragments in silico from SMILES patterns (such as MetFrag, CFM-ID, and Ms-Finder), the problem of identification is still unsolved. The major issue is that the elution time and fragmentation spectra depend considerably on the equipment used and are not the same for different LC-MS systems. It means that any additional descriptors depending only on the structure of the chemical compound will be of big help for LC-MS/MS-based omics. Our approach is based on the characterization of compounds by the number of labile hydrogen and oxygen atoms in the molecule, which can be measured using hydrogen/deuterium and ¹⁶O/¹⁸O-exchange approaches. The number of labile atoms (those from -OH, -NH, ═O, and -COOH groups) can be predicted from SMILES patterns and serves as an additional structural descriptor when performing a database search. In addition, distribution of isotope labels among MS/MS fragments can be roughly predicted by software such as MetFrag or CFM-ID. Here, we present an approach utilizing the selection of structural candidates from a database on the basis of the number of functional groups and analysis of isotope labels distribution among fragments. It was found that our approach allows reduction of the search space by a factor of 10 and considerably increases the reliability of the compound identification.