Evaluation of Lipid In-Source Fragmentation on Different Orbitrap-based Mass Spectrometers

Development of a New Binary Matrix for the Comprehensive Analysis of Lipids and Pigments in Micro- and Macroalgae Using MALDI-ToF/ToF Mass Spectrometry

While edible algae might seem low in fat, the lipids they contain are crucial for good health and preventing chronic diseases. This study introduces a binary matrix to analyze all the polar lipids in both macroalgae (Wakame-Undaria pinnatifida, Dulse-Palmaria palmata, and Nori-Porphyra spp.) and microalgae (Spirulina-Arthrospira platensis, and Chlorella-Chlorella vulgaris) using matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS). The key lies in a new dual matrix made by combining equimolar amounts of 1,5-diaminonaphthalene (DAN) and 9-aminoacridine (9AA). This combination solves the limitations of single matrices: 9AA is suitable for sulfur-containing lipids and acidic phospholipids, while DAN excels as an electron-transfer secondary reaction matrix for intact chlorophylls and their derivatives. By employing the equimolar binary matrix, a wider range of algal lipids, including free fatty acids, phospholipids, glycolipids, pigments, and even rare arsenosugarphospholipids were successfully detected, overcoming drawbacks related to ion suppression from readily ionizable lipids. The resulting mass spectra exhibited a good signal-to-noise ratio at a lower laser fluence and minimized background noise. This improvement stems from the binary matrix's ability to mitigate in-source decay effects, a phenomenon often encountered for certain matrices. Consequently, the data obtained are more reliable, facilitating a faster and more comprehensive exploration of algal lipidomes using high-throughput MALDI-MS/MS analysis.

Oxygen Isotope Analysis of Nanomole Phosphate Using PO3- Fragment in ESI-Orbitrap-MS

The oxygen isotope composition of phosphate is a useful tool for studying biogeochemical phosphorus cycling. However, the current Ag3PO4 method is not only tedious in PO43- extraction and purification but also requires a large-sized sample at the micromole level, thereby limiting its application. Here, we present an approach to measuring the oxygen isotope composition, δ18O, of dissolved phosphate at the nanomole level using electrospray ionization Orbitrap mass spectrometry (ESI-Orbitrap-MS). We compared the reproducibility of δ18O measurements using the H2PO4- ions (m/z = 97 and 99 for H2P16O4- and H2P18O16O3-, respectively) and using the PO3- fragment ions (m/z = 79 and 81 for P16O3- and P18O16O2-, respectively) generated by source fragmentation and by higher-energy collisional dissociation, respectively. The results demonstrate that phosphate δ18O can be more reliably measured by the PO3- ions than by the H2PO4- ions. PO3- generated by source fragmentation at 40 V achieved the highest reproducibility for δ18O based on precision tests. Furthermore, the mass spectrum for a 50:50 μM mixed solution of phosphate and sulfate revealed that PO3- ions resulting from source fragmentation at 40 V are the predominant species in the Orbitrap analyzer. Notably, P16O3- ions (m/z: 79) are not interfered with by 32S16O3- (m/z: 80) ions. This is in contrast to the case for 1H2P16O4- ions, which share the same m/z value with 1H32S16O4- ions and exhibit much lower signal intensity than HSO4- ions. Using the PO3- fragment method and six phosphate standards with a wide range of δ18O values, we obtained a calibration line with a slope of 0.94 (R2 = 0.98). The overall uncertainty for ESI-Orbitrap-MS phosphate δ18O measurement was 0.8‰ (n = 30; 1 SD). With much room for improvement, the PO3- fragment method presents a better approach to measuring the phosphate oxygen isotope composition, applicable to nanomole sample sizes in a liquid phase.

Improving Quantitative Accuracy in Nontargeted Lipidomics by Evaluating Adduct Formation

For large-scale lipidomic analyses, accurate and reproducible quantification of endogenous lipids is crucial for comparing results within and across studies. Many lipids present in liquid chromatography-electrospray ionization-mass spectrometry form various adducts with buffer components. The mechanisms and conditions that dictate adduct formation are still poorly understood. In a positive mode, neutral lipids like mono-, di-, and triacylglycerides and cholesteryl esters typically generate [M + NH4]+ adduct ions, although [M + Na]+, [M + K]+, and other (more complex) species can also be significantly abundant in MS1 precursor ion spectra. Variations in the ratios of these adducts (within and between matrices) can lead to dramatic inaccuracies during quantification. Here, we examine 48 unique diacylglycerol (DAG) species across 2366 mouse samples for eight matrix-specific data sets of plasma, liver, kidney, brain, heart muscle, gastrocnemius muscle, gonadal, and inguinal fat. Typically, no single adduct ion species accounted for more than 60% of the total observed abundance across each data set. Even within a single matrix, DAGs showed a high variability of adduct ratios. The ratio of [M + NH4]+ adduct ions was increased for longer-chain DAGs and for polyunsaturated DAGs, at the expense of reduced ratios of [M + Na]+ adducts. When using three deuterated internal DAG standards, we found that absolute concentrations were estimated with up to 70% error when only one adduct ion was used instead of all adducts combined. Importantly, when combining [M + NH4]+ and [M + Na]+ adduct ions, quantification results were within 5% accuracy compared to all adduct ions combined. Additional variance can be caused by other factors, such as instrument conditions or matrix effects.

Widespread occurrence of in-source fragmentation in the analysis of natural compounds by liquid chromatography-electrospray ionization mass spectrometry

RATIONALE

The in-source fragmentation (ISF) of analyte or co-eluting substances produces unintentional fragment ions, which hampers identification and quantification by liquid chromatography-mass spectrometry (LC/MS). Natural compounds derived from plants also contain fragile moieties that may undergo ISF. However, the characteristics of ISF of natural compounds in LC/MS are still unclear.

METHODS

The ISF behavior of 214 natural compounds was assayed in LC with Q/orbitrap MS in electrospray ionization (ESI) mode and the extent of ISF was evaluated.

RESULTS

Up to 82% of tested compounds underwent ISF and half of the tested natural compounds that contain more than one fragile moiety underwent successive and severe ISF to generate serial structurally related ISF products. The major ISF-altering moieties for natural compounds were hydroxyl, lactone, glycosyl and ether, resulting in neutral loss of H₂ O or CO, deglycosylation or cleavage of ether bond, respectively. Some compounds such as terpenoids underwent severe ISF and less than 1% parent form can be observed. For natural compounds, ISF products with similar structures are more likely to cause interference in analysis because the ISF products may share identical mass-to-charge ratio and similar MS² fragmentation patterns with precursor ions of the homologs in plants. Furthermore, severe ISF may cause a false negative in the identification of the parent form.

CONCLUSIONS

In summary, ISF was a highly frequent phenomenon for analysis of natural compounds by LC/ESI-MS, and extensive and successive ISF of natural products may cause misannotation and misidentification with homologs in plants. The study should raise awareness of ISF interference during the analysis of natural compounds.

In-source fragmentation of nucleosides in electrospray ionization towards more sensitive and accurate nucleoside analysis

Nucleosides have been found to suffer in-source fragmentation (ISF) in electrospray ionization mass spectrometry, which leads to reduced sensitivity and ambiguous identification. In this work, a combination of theoretical calculations and nuclear magnetic resonance analysis revealed the key role of protonation at N3 near the glycosidic bond during ISF. Therefore, an ultrasensitive liquid chromatography-tandem mass spectrometry system for 5-formylcytosine detection was developed with 300 fold signal enhancement. Also, we established a MS1-only platform for nucleoside profiling and successfully identified sixteen nucleosides in the total RNA of MCF-7 cells. Taking ISF into account, we can realize analysis with higher sensitivity and less ambiguity, not only for nucleosides, but for other molecules with similar protonation and fragmentation behaviors.

Guidelines and considerations for building multidimensional libraries for untargeted MS-based metabolomics

INTRODUCTION

Feature annotation is crucial in untargeted metabolomics but remains a major challenge. The large pool of metabolites collected under various instrumental conditions is underrepresented in publicly available databases. Retention time (RT) and collision cross section (CCS) measurements from liquid chromatography ion mobility high-resolution mass spectrometers can be employed in addition to MS/MS spectra to improve the confidence of metabolite annotation. Recent advancements in machine learning focus on improving the accuracy of predictions for CCS and RT values. Therefore, high-quality experimental data are crucial to be used either as training datasets or as a reference for high-confidence matching.

METHODS

This manuscript provides an easy-to-use workflow for the creation of an in-house metabolite library, offers an overview of alternative solutions, and discusses the challenges and advantages of using open-source software. A total of 100 metabolite standards from various classes were analyzed and subjected to the described workflow for library generation.

RESULTS AND DISCUSSION

The outcome was an open-access available NIST format metabolite library (.msp) with multidimensional information. The library was used to evaluate CCS prediction tools, MS/MS spectra heterogeneities (e.g., multiple adducts, in-source fragmentation, radical fragment ions using collision-induced dissociation), and the reporting of RT.

Analytical and computational workflow for in-depth analysis of oxidized complex lipids in blood plasma

Lipids are a structurally diverse class of biomolecules which can undergo a variety of chemical modifications. Among them, lipid (per)oxidation attracts most of the attention due to its significance in the regulation of inflammation, cell proliferation and death programs. Despite their apparent regulatory significance, the molecular repertoire of oxidized lipids remains largely elusive as accurate annotation of lipid modifications is complicated by their low abundance and often unknown, biological context-dependent structural diversity. Here, we provide a workflow based on the combination of bioinformatics and LC-MS/MS technologies to support identification and relative quantification of oxidized complex lipids in a modification type- and position-specific manner. The developed methodology is used to identify epilipidomics signatures of lean and obese individuals with and without type 2 diabetes. The characteristic signature of lipid modifications in lean individuals, dominated by the presence of modified octadecanoid acyl chains in phospho- and neutral lipids, is drastically shifted towards lipid peroxidation-driven accumulation of oxidized eicosanoids, suggesting significant alteration of endocrine signalling by oxidized lipids in metabolic disorders.

How Soft Is Secondary Electrospray Ionization?

Secondary electrospray ionization (SESI) mass spectrometry (MS) is a direct infusion technique often used for untargeted metabolomics, e.g., for online breath analysis. SESI is thought to be a soft ionization method, which is important to avoid interference from in-source fragments and to simplify compound annotation. In this work, benzylammonium ions, formed from volatile benzylamines, with known bond dissociation enthalpies were used as thermometer ions to investigate the internal energy distribution of ions that are produced by SESI. It is shown that SESI is softer than electrospray ionization (ESI), and therefore, SESI indeed qualifies as a soft ionization technique. However, we also found that the standard MS instrument settings used in the SESI community are relatively harsh. Proper soft tuning of the instrument is essential to fully benefit from the softness that SESI can provide. Moreover, there is evidence from in-source collision-induced dissociation (CID) experiments that analytes can be solvated in SESI under soft conditions, which supports a recently proposed SESI mechanism referred to as ligand switching.

Addressing big data challenges in mass spectrometry-based metabolomics

Advancements in computer science and software engineering have greatly facilitated mass spectrometry (MS)-based untargeted metabolomics. Nowadays, gigabytes of metabolomics data are routinely generated from MS platforms, containing condensed structural and quantitative information from thousands of metabolites. Manual data processing is almost impossible due to the large data size. Therefore, in the "omics" era, we are faced with new challenges, the big data challenges of how to accurately and efficiently process the raw data, extract the biological information, and visualize the results from the gigantic amount of collected data. Although important, proposing solutions to address these big data challenges requires broad interdisciplinary knowledge, which can be challenging for many metabolomics practitioners. Our laboratory in the Department of Chemistry at the University of British Columbia is committed to combining analytical chemistry, computer science, and statistics to develop bioinformatics tools that address these big data challenges. In this Feature Article, we elaborate on the major big data challenges in metabolomics, including data acquisition, feature extraction, quantitative measurements, statistical analysis, and metabolite annotation. We also introduce our recently developed bioinformatics solutions for these challenges. Notably, all of the bioinformatics tools and source codes are freely available on GitHub (https://www.github.com/HuanLab), along with revised and regularly updated content.

Lipidomics profiling of zebrafish liver through untargeted liquid chromatography-high resolution mass spectrometry

Lipidomics analysis of zebrafish tissues has shown promising results to understand disease-related outcomes of exposure to toxic substances at molecular level. However, knowledge about their lipidome is limited, as most untargeted studies only identify the lipids that are statistically significant in their setup. In this work, liquid chromatography-high resolution mass spectrometry was used to study different aspects of the analytical workflow, i.e., extraction solvents (methanol/chloroform/water (3/2/2, v/v/v), methanol/dichloromethane/water (2/3/2, v/v/v) and methanol/methyl-tert-butyl ether/water (3/10/2.5, v/v/v), instrumental response, and strategies used for lipid annotation. The number of high-quality features (relative standard deviation of the intensity values ≤ 10% in the range 10³ -10⁷ counts) was affected by the dilution of lipid extracts, indicating that it is an important parameter for developing untargeted methods. The workflows used allowed the selection of a dilution factor to annotate 712 lipid species (507 bulk lipids) in zebrafish liver using four software (LipidMatch, LipidHunter, MS-DIAL and Lipostar). Retention time mapping was a valuable tool to filter lipid annotations obtained from automatic software annotations. The lipid profiling of zebrafish livers will help in a better understanding of the true constitution of their lipidome at the species level, as well as in the use of zebrafish in toxicological studies. This article is protected by copyright. All rights reserved.

Maximizing MS/MS Acquisition for Lipidomics Using Capillary Separation and Orbitrap Tribrid Mass Spectrometer

Liquid chromatography-mass spectrometry (LC-MS) is a typical strategy for lipidomics analysis. Although capillary LC-MS is a common analytical technique for proteomics analysis, its application to lipidomics has been limited. In this study, we aim at improving lipid identifications achieved in a single LC-MS analysis by a 3-fold approach: capillary LC and nanoelectrospray for enhanced ionization, ion trap for higher sensitivity tandem MS, and parallelization of mass analyzers for increased speed of acquisition on an Orbitrap hybrid system. By applying the methods to a complex lipid mixture of human plasma, we identified and performed relative quantification on over 1500 lipids within a 60 min capillary LC-MS analysis.

RECOGNITION AND AVOIDANCE OF ION SOURCE-GENERATED ARTIFACTS IN LIPIDOMICS ANALYSIS

Lipid research is attracting more and more attention as various key roles and novel biological functions of lipids have been demonstrated and discovered in the organism. Mass spectrometry (MS)-based lipidomics approaches are the most powerful and effective tools for analysis of cellular lipidomes with very high sensitivity and specificity. However, the artifacts generated from in-source fragmentation are always present in all kinds of ion sources, even soft ionization techniques (i.e., electrospray ionization and matrix-assisted laser desorption/ionization [MALDI]). These artifacts can cause many problems for lipidomics, especially when the fragment ions correspond to/are isomeric species of other endogenous lipid species in complex biological samples. These commonly observed artifacts could lead to misannotation, false identification, and consequently, incorrect attribution of phenotypes, and will have negative impact on any MS-based lipidomics research including but not limited to biomarker discovery, drug development, etc. Liquid chromatography-MS, shotgun lipidomics, and MALDI-MS imaging are three representative lipidomics approaches in which ion source-generated artifacts are all manifested and are comprehensively summarized in this article. The strategies on how to avoid/reduce the artifacts of in-source fragmentation on lipidomics analysis are also discussed in detail. We believe that with the recognition and avoidance of ion source-generated artifacts, MS-based lipidomics approaches will provide better accuracy on comprehensive analysis of biological samples and will make greater contribution to the research on metabolism and translational/precision medicine (collectively termed functional lipidomics). © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Integration of Chemical Derivatization and in-Source Fragmentation Mass Spectrometry for High-Coverage Profiling of Submetabolomes

In-source fragmentation-based high-resolution mass spectrometry (ISF-HRMS) is a potential analytical technique, which is usually used to profile some specific compounds that can generate diagnostic neutral loss (NL) or fragment ion (FI) in ion source inherently. However, the ISF-HRMS method does not work for those compounds that cannot inherently produce diagnostic NL or FI in ion source. In this study, a derivatization-based in-source fragmentation-information-dependent acquisition (DISF-IDA) strategy was proposed for profiling the metabolites with easily labeled functional groups (submetabolomes) by liquid chromatography-electrospray ionization-quadrupole time-of-flight mass spectrometry (LC-ESI-Q-TOF MS). As a proof-of-concept study, 36 carboxylated compounds labeled with N,N-dimethylethylenediamine (DMED) were selected as model compounds to examine performance of DISF-IDA strategy in screening the carboxylated metabolites and acquiring their MSⁿ spectra. In ESI source, the DEMD-derived carboxylated compounds were fragmented to produce characteristic neutral losses of 45.0578, 63.0684, and/or 88.1000 Da that were further used as diagnostic features for screening the carboxylated metabolites by DISF-IDA-based LC-Q-TOF MS. Furthermore, high-resolution MSⁿ spectra of the model compounds were also obtained within a single run of DISF-IDA-based LC-Q-TOF MS analysis, which contributed to the improvement of the annotation confidence. To further verify its applicability, DISF-IDA strategy was used for profiling carboxylated submetabolome in mice feces. Using this strategy, a total of 351 carboxylated metabolites were detected from mice feces, of which 178 metabolites (51% of the total) were positively or putatively identified. Moreover, DISF-IDA strategy was also demonstrated to be applicable for profiling other submetabolomes with easily labeled functional groups such as amino, carbonyl, and cis-diol groups. Overall, our proposed DISF-IDA strategy is a promising technique for high-coverage profiling of submetabolomes with easily labeled functional groups in biological samples.

Qualitative Characterization of the Rat Liver Mitochondrial Lipidome Using All Ion Fragmentation on an Exactive Benchtop Orbitrap MS

Untargeted lipidomics profiling by liquid chromatography -mass spectrometry (LC-MS) allows researchers to observe the occurrences of lipids in a biological sample without showing intentional bias to any specific class of lipids and allows retrospective reanalysis of data collected. Typically, and in the specific method described, a general extraction method followed by LC separation is used to achieve nonspecific class coverage of the lipidome prior to high resolution accurate mass (HRAM) MS detection . Here we describe a workflow including the isolation of mitochondria from liver tissue, followed by mitochondrial lipid extraction and the LC-MS conditions used for data acquisition. We also highlight how, in this method, all ion fragmentation can be used to identify species of lower abundances, often missed by data dependent fragmentation techniques. Here we describe the isolation of mitochondria from liver tissue, followed by mitochondrial lipid extraction and the LC-MS conditions used for data acquisition.

ISFrag: De Novo Recognition of In-Source Fragments for Liquid Chromatography-Mass Spectrometry Data

In-source fragmentation (ISF) is a naturally occurring phenomenon during electrospray ionization (ESI) in liquid chromatography-mass spectrometry (LC-MS) analysis. ISF leads to false metabolite annotation in untargeted metabolomics, prompting misinterpretation of the underlying biological mechanisms. Conventional metabolomic data cleaning mainly focuses on the annotation of adducts and isotopes, and the recognition of ISF features is mainly based on common neutral losses and the LC coelution pattern. In this work, we recognized three increasingly important patterns of ISF features, including (1) coeluting with their precursor ions, (2) being in the tandem MS (MS²) spectra of their precursor ions, and (3) sharing similar MS² fragmentation patterns with their precursor ions. Based on these patterns, we developed an R package, ISFrag, to comprehensively recognize all possible ISF features from LC-MS data generated from full-scan, data-dependent acquisition, and data-independent acquisition modes without the assistance of common neutral loss information or MS² spectral library. Tested using metabolite standards, we achieved a 100% correct recognition of level 1 ISF features and over 80% correct recognition for level 2 ISF features. Further application of ISFrag on untargeted metabolomics data allows us to identify ISF features that can potentially cause false metabolite annotation at an omics-scale. With the help of ISFrag, we performed a systematic investigation of how ISF features are influenced by different MS parameters, including capillary voltage, end plate offset, ion energy, and "collision energy". Our results show that while increasing energies can increase the number of real metabolic features and ISF features, the percentage of ISF features might not necessarily increase. Finally, using ISFrag, we created an ISF pathway to visualize the relationships between multiple ISF features that belong to the same precursor ion. ISFrag is freely available on GitHub (https://github.com/HuanLab/ISFrag).

Rapid screening of glycoalkaloids in Solanum scabrum and S. nigrum berries using ultra-high-performance liquid chromatography with pathway-specified in-source fragmentation tandem mass spectrometry

RATIONALE

The safe consumption of Solanum scabrum and S. nigrum berries (SNBs) depends on a reliable and rapid chemical screen for the testing of the fruit and/or final food and industrial products for the presence and level of toxic glycoalkaloids. Such a rapid and sensitive screen could also be used by those involved in food safety and forensics, industry, research labs and those in agriculture production, breeding and food processing. Significant variation in the content and composition of glycoalkaloids across SNBs has been reported. To facilitate high-throughput targeted analysis, this work overcame the slow scan speed of a traditional triple quadruple mass spectrometry (QqQ) method by development of a pseudo-MS³ method.

METHODS

In-source fragmentation functioned as a pseudo-MS or pseudo-hydrolysis to trim down the structurally diverse and complex glycosides into five types of aglycone ions, which were then analyzed using multiple reaction monitoring (MRM). Characteristic product ions were selected based on the aglycone skeleton and substitution pattern and associated fragmentation pathway.

RESULTS

A compact method with only 15 MRM transitions were developed for high-throughput screening of very diverse glycoalkaloids. Glycosides of the same aglycone type were readily identified in the same transition window without the need for mass spectra interpretation. Validated using solamargine, the sole available standard, the accuracy was 99.7-101.3%, the intra- and inter-day precision were, respectively, 2.5-5.0% and 8.0-9.2%, and the lower limit of detection and quantification were, respectively, 3.1 and 10.2 ng/mL (with 1 μL injection volume).

CONCLUSIONS

The peudo-MS³ method allowed for high-throughput targeted analysis with compact MRM transitions to address a large number of glycoalkaloids with diverse structures. This method could serve to meet the most heavy-duty demand for rapid inspection of glycoalkaloids in SNBs. This method can be adopted and used by those involved in food safety and forensics, in developing food and industrial products and in genetics and breeding.