Fourier transform ion cyclotron resonance mass spectrometry: a primer

Ion Source Complementarity for Characterization of Complex Organic Mixtures Using Fourier Transform Mass Spectrometry: A Review

Complex organic mixtures are found in many areas of research, such as energy, environment, health, planetology, and cultural heritage, to name but a few. However, due to their complex chemical composition, which holds an extensive potential of information at the molecular level, their molecular characterization is challenging. In mass spectrometry, the ionization step is the key step, as it determines which species will be detected. This review presents an overview of the main ionization sources employed to characterize these kinds of samples in Fourier transform mass spectrometry (FT-MS), namely electrospray (ESI), atmospheric pressure photoionization (APPI), atmospheric pressure chemical ionization (APCI), atmospheric pressure laser ionization (APLI), and (matrix-assisted) laser desorption ionization ((MA)LDI), and their complementarity in the characterization of complex organic mixtures. First, the ionization techniques are examined in the common direct introduction (DI) usage. Second, these approaches are discussed in the context of coupling chromatographic techniques such as gas chromatography, liquid chromatography, and supercritical fluid chromatography.

Symmetry reduction induced by argon tagging gives access to low-lying excited states of FeH+ in the overtone region of the Fe-H stretching mode

Iron is the most abundant transition metal in the interstellar medium (ISM), and is thought to be involved in a variety of astrochemical processes. Here, we present the infrared multiple photon dissociation (IRMPD) spectra of Ar1,2FeH+ and their deuterated isotopologues in the region of 2240-14 000 cm-1. The Fe-H overtone stretching mode in ArFeH+ and Ar2FeH+ is observed at 3636 ± 28 cm-1 and 3659 ± 13 cm-1, respectively. Deuteration shifts these bands to 2618 ± 31 cm-1 and 2650 ± 14 cm-1 in ArFeD+ and Ar2FeD+, respectively. Additionally, the spectra of Ar2FeH+ and Ar2FeD+ feature broad transitions at ∼2200-4000 cm-1 and ∼4500-6500 cm-1. We assign these bands to electronic transitions from the thermally populated X5A2/X'5A1 ground state manifold into the A'5B2 and B5A1 states, which we model with multi-reference quantum chemical calculations including spin-orbit coupling. The calculations show that these transitions are symmetry forbidden in FeH+ and in the equilibrium geometry of ArFeH+/ArFeD+, while the zero-point oscillation of the bending mode of the triatomic molecule leads to some oscillator strength. Upon addition of the second argon atom, the transitions become weakly allowed in the equilibrium geometry of Ar2FeH+/Ar2FeD+ due to symmetry reduction from C∞v to C2v.

Biofunctionalized dissolvable hydrogel microbeads enable efficient characterization of native protein complexes

The characterization of protein complex is vital for unraveling biological mechanisms in various life processes. Despite advancements in biophysical tools, the capture of non-covalent complexes and deciphering of their biochemical composition continue to present challenges for low-input samples. Here we introduce SNAP-MS, a Stationary-phase-dissolvable Native Affinity Purification and Mass Spectrometric characterization strategy. It allows for highly efficient purification and characterization from inputs at the pico-mole level. SNAP-MS replaces traditional elution with matrix dissolving during the recovery of captured targets, enabling the use of high-affinity bait-target pairs and eliminates interstitial voids. The purified intact protein complexes are compatible with native MS, which provides structural information including stoichiometry, topology, and distribution of proteoforms, size variants and interaction states. An algorithm utilizes the bait as a charge remover and mass corrector significantly enhances the accuracy of analyzing heterogeneously glycosylated complexes. With a sample-to-data time as brief as 2 hours, SNAP-MS demonstrates considerable versatility in characterizing native complexes from biological samples, including blood samples.

Origin and characterization of cyclodepsipeptides: Comprehensive structural approaches with focus on mass spectrometry analysis of alkali-cationized molecular species

Cyclodepsipeptides (CDPs) represent a huge family of chemically and structurally diverse molecules with a wide ability for molecular interactions. CDPs are cyclic peptide-related natural products made up of both proteinogenic and nonproteinogenic amino acids linked by amide and ester bonds. The combined use of different analytical methods is required to accurately determine their integral structures including stereochemistry, thus allowing deeper insights into their often-intriguing bioactivities and their possible usefulness. Our goal is to present the various methods developed to accurately characterize CDPs. Presently, Marfey's method and NMR (nuclear magnetic resonance) are still considered the best for characterizing CDP configuration. Nevertheless, electrospray-high resolution tandem mass spectrometry (ESI-HRMS/MS) is of great value for efficiently resolving CDP's composition and sequences. For instance, recent data shows that the fragmentation of cationized CDPs (e.g., [M + Li]+ and [M + Na]+) leads to selective cleavage of ester bonds and specific cationized product ions (b series) useful to get unprecedented sequence information. Thus, after a brief presentation of their structure, biological functions, and biosynthesis, we also provide a historic overview of these various analytical approaches as well as their advantages and limitations with a special emphasis on the emergence of methods based on HRMS/MS through recent fundamental works and applications.

Compositional Characterization of Syngas-Based Glycolide Using Gas Chromatogram-Mass Spectrometry and Electrospray Ionization High-Resolution Mass Spectrometry

Polyglycolic acid (PGA) is a biologically friendly material with a wide range of applications. The production of dimethyl oxalate using coal-based syngas and the hydrogenation of dimethyl oxalate can produce the polymerization raw material of PGA, glycolide, which requires a methyl glycolate polymerization and depolymerization process. The intermediate products of the production process were analyzed using gas chromatogram-mass spectrometry (GC-MS) and Orbitrap mass spectrometry (Orbitrap MS), which revealed the presence of cyclic and linear PGAs with different capped ends. The impurities present in the oligomer were mostly methyl-capped PGA and were retained in the subsequent depolymerization process to glycolide, solvent washing can be used to remove this part of the impurity and ultimately obtain a refined glycolide product. Furthermore, it is proposed that the use of the specialized Kendrick Mass Defect (KMD) to plot and analyze PGA compounds obtained using mass spectrometry can enable the direct classification of PGAs without the need for exact molecular formula assignment.

Enhancing Spatial Resolution in Tandem Mass Spectrometry Ion/Ion Reaction Imaging Experiments through Image Fusion

We have recently developed a charge inversion ion/ion reaction to selectively derivatize phosphatidylserine lipids via gas-phase Schiff base formation. This tandem mass spectrometry (MS/MS) workflow enables the separation and detection of isobaric lipids in imaging mass spectrometry, but the images acquired using this workflow are limited to relatively poor spatial resolutions due to the current time and limit of detection requirements for these ion/ion reaction imaging mass spectrometry experiments. This trade-off between chemical specificity and spatial resolution can be overcome by using computational image fusion, which combines complementary information from multiple images. Herein, we demonstrate a proof-of-concept workflow that fuses a low spatial resolution (i.e., 125 μm) ion/ion reaction product ion image with higher spatial resolution (i.e., 25 μm) ion images from a full scan experiment performed using the same tissue section, which results in a predicted ion/ion reaction product ion image with a 5-fold improvement in spatial resolution. Linear regression, random forest regression, and two-dimensional convolutional neural network (2-D CNN) predictive models were tested for this workflow. Linear regression and 2D CNN models proved optimal for predicted ion/ion images of PS 40:6 and SHexCer d38:1, respectively.

Selective Profiling of Carboxylic Acid in Crude Oil by Halogen Labeling Combined with Liquid Chromatography and High-Resolution Mass Spectrometry

Carboxylic acids are a small but essential compound class within petroleum chemistry, influencing crude oil behaviors in production and processing and causing environmental impacts. Detailed structural information is fundamental to understanding their influence on petroleum characteristics. However, characterizing acids in crude oil remains challenging due to matrix effects, structural diversity, and low abundance. In this work, we present a new methodology for profiling carboxylic acids by liquid-liquid extraction and selective derivatization using 4-bromo-N-methylbenzylamine (4-BNMA) followed by liquid chromatography and electrospray ionization Orbitrap mass spectrometry (LC-ESI-Orbitrap MS). The fragmentation of 4-BNMA derivatives produces a unique product ion pair, m/z 169/171, enabling the identification of chromatographic fractions containing carboxylic acids. The mass spectra of the corresponding fractions are extracted, and the acids are further computationally isolated based on the isotopic pattern. The method was optimized and validated using acid standards and systematic experimental designs, assuring robustness and sensitivity for nontarget screening purposes. This method detected up to 380 carboxylic acids in six Danish North Sea crude oils, with up to two carboxyl and other heteroatom functionalities (NSO). The results indicated that the most populated species are fatty acids (double bond equivalent (DBE) = 1) and small aromatic acids (DBE = 2-6). The predominance and diversities of compound classes in different samples are consistent with their corresponding bulk properties. Polyfunctional acids (Ox, NxOx, and SxOx) were observed due to exposure to oxidation and biodegradation. Also, the approach's applicability benefits high-resolution MS analysis by simplifying data processing for crude oil and potentially other high-organic and aqueous samples.

Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Applications for Metabolomics

Metabolomics is an interdisciplinary field that aims to study all metabolites < 1500 Da that are ubiquitously found within all organisms. Metabolomics is experiencing exponential growth and commonly relies on high-resolution mass spectrometry (HRMS). Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a form of HRMS that is particularly well suited for metabolomics research due to its exceptionally high resolution (105-106) and sensitivity with a mass accuracy in parts per billion (ppb). In this regard, FT-ICR-MS can provide valuable insights into the metabolomics analysis of complex biological systems due to unique capabilities such as the easy separation of isobaric and isomeric species, isotopic fine structure analysis, spatial resolution of metabolites in cells and tissues, and a high confidence (<1 ppm mass error) in metabolite identification. Alternatively, the large and complex data sets, long acquisition times, high cost, and limited access mainly through national mass spectrometry facilities may impede the routine adoption of FT-ICR-MS by metabolomics researchers. This review examines recent applications of FT-ICR-MS metabolomics in the search for clinical and non-human biomarkers; for the analysis of food, beverage, and environmental samples; and for the high-resolution imaging of tissues and other biological samples. We provide recent examples of metabolomics studies that highlight the advantages of FT-ICR-MS for the detailed and reliable characterization of the metabolome. Additionally, we offer some practical considerations for implementing FT-ICR-MS into a research program by providing a list of FT-ICR-MS facilities and by identifying different high-throughput interfaces, varieties of sample types, analysis methods (e.g., van Krevelen diagrams, Kendrick mass defect plot, etc.), and sample preparation and handling protocols used in FT-ICR-MS experiments. Overall, FT-ICR-MS holds great promise as a vital research tool for advancing metabolomics investigations.

Investigating the Intramolecular Competition of Different RNA Binding Motifs for Neomycin B by Native Top-Down Mass Spectrometry

The ongoing search for small molecule drugs that target ribonucleic acids (RNA) is complicated by a limited understanding of the principles that govern RNA-small molecule interactions. Here we have used stoichiometry-resolved native top-down mass spectrometry (MS) to study the binding of neomycin B to small model hairpin RNAs, an unstructured RNA, and a viral RNA construct. For 15-22 nt model RNAs with hairpin structure, we found that neomycin B binding to hairpin loops relies on interactions with both the nucleobases and the 2'-OH groups, and that a simple 5' or 3' overhang can introduce an additional binding motif. For a 47 nt RNA construct derived from stem IA of the human immunodeficiency virus 1 (HIV-1) rev response element (RRE) RNA, native top-down MS identified four different binding motifs, of which the purine-rich internal loop showed the highest affinity for neomycin B. Stoichiometry-resolved binding site mapping by native top-down MS allows for a new perspective on binding specificity, and has the potential to reveal unexpected principles of small molecule binding to RNA.

External Data Systems Enable Enhanced (and Sustainable) Fourier Transform Mass Spectrometry Imaging for Legacy Hybrid Linear Ion Trap-Orbitrap Platforms

Legacy Fourier transform (FT) mass spectrometers provide robust platforms for bioanalytical mass spectrometry (MS) yet lack the most modern performance capabilities. For many laboratories, the routine investment in next generation instrumentation is cost prohibitive. Field-based upgrades provide a direct path to extend the usable lifespan of MS platforms which may be considered antiquated based on performance specifications at the time of manufacture. Here we demonstrate and evaluate the performance of a hybrid linear ion trap (LTQ)-Orbitrap mass spectrometer that has been enhanced via an external high-performance data acquisition and processing system to provide true absorption mode FT processing during an experimental acquisition. For the application to mass spectrometry imaging, several performance metrics have been improved including mass resolving power, mass accuracy, and dynamic range to provide an FTMS system comparable to current platforms. We also demonstrate, perhaps, the unexpected ability of these legacy platforms to detect usable time-domain signals up to 5 s in duration to achieve a mass resolving power 8× higher than the original platform specification.

Enhancing Molecular Characterization of Dissolved Organic Matter by Integrative Direct Infusion and Liquid Chromatography Nontargeted Workflows

Dissolved organic matter (DOM) in aquatic systems is a highly heterogeneous mixture of water-soluble organic compounds, acting as a major carbon reservoir driving biogeochemical cycles. Understanding DOM molecular composition is thus of vital interest for the health assessment of aquatic ecosystems, yet its characterization poses challenges due to its complex and dynamic chemical profile. Here, we performed a comprehensive chemical analysis of DOM from highly urbanized river and seawater sources and compared it to drinking water. Extensive analyses by nontargeted direct infusion (DI) and liquid chromatography (LC) high-resolution mass spectrometry (HRMS) through Orbitrap were integrated with novel computational workflows to allow molecular- and structural-level characterization of DOM. Across all water samples, over 7000 molecular formulas were calculated using both methods (∼4200 in DI and ∼3600 in LC). While the DI approach was limited to molecular formula calculation, the downstream data processing of MS2 spectral information combining library matching and in silico predictions enabled a comprehensive structural-level characterization of 16% of the molecular space detected by LC-HRMS across all water samples. Both analytical methods proved complementary, covering a broad chemical space that includes more highly polar compounds with DI and more less polar ones with LC. The innovative integration of diverse analytical techniques and computational workflow introduces a robust and largely available framework in the field, providing a widely applicable approach that significantly contributes to understanding the complex molecular composition of DOM.

Detection and Exclusion of False-Positive Molecular Formula Assignments via Mass Error Distributions in UHR Mass Spectra of Natural Organic Matter

Ultrahigh resolution mass spectrometry (UHRMS) routinely detects and identifies thousands of mass peaks in complex mixtures, such as natural organic matter (NOM) and petroleum. The assignment of several chemically plausible molecular formulas (MFs) for a single accurate mass still poses a major problem for the reliable interpretation of NOM composition in a biogeochemical context. Applying sensible chemical rules for MF validation is often insufficient to eliminate multiple assignments (MultiAs)─especially for mass peaks with low abundance or if ample heteroatoms or isotopes are included - and requires manual inspection or expert judgment. Here, we present a new approach based on mass error distributions for the identification of true and false assignments among MultiAs. To this end, we used the mass error in millidalton (mDa), which was superior to the commonly used relative mass error in ppm. We developed an automatic workflow to group MultiAs based on their shared formula units and Kendrick mass defect values and to evaluate the mass error distribution. In this way, the number of valid assignments of chlorinated disinfection byproducts was increased by 8-fold as compared to only applying 37Cl/35Cl isotope ratio filters. Likewise, phosphorus-containing MFs can be differentiated against chlorine-containing MFs with high confidence. Further, false assignments of highly aromatic sulfur-containing MFs ("black sulfur") to sodium adducts in negative ionization mode can be excluded by applying our approach. Overall, MFs for mass peaks that are close to the detection limit or where naturally occurring isotopes are rare (e.g., 15N) or absent (e.g., P and F) can now be validated, substantially increasing the reliability of MF assignments and broadening the applicability of UHRMS analysis to even more complex samples and processes.

Size-Resolved Molecular Characterization of Water-Soluble Organic Matter in Atmospheric Particulate Matter from Northern China

Atmospheric particulate matter (PM) affects visibility, climate, biogeochemical cycles and human health. Water-soluble organic matter (WSOM) is an important component of PM. In this study, PM samples with size-resolved measurements at aerodynamic cut-point diameters (Dp) of 0.01-18μm were collected in the rural area of Baoding and the urban area of Dalian, Northern China. Non-targeted analysis was adopted for the characterization of the molecule constitutes of WSOM in different sized particles using Fourier transform-ion cyclotron resonance mass spectrometry. Regardless of the location, the composition of WSOM in Aitken mode particles (aerodynamic diameter < 0.05 μm) was similar. The WSOM in accumulation mode particles (0.05-2 μm) in Baoding was predominantly composed of CHO compounds (84.9%), which were mainly recognized as lignins and lipids species. However, S-containing compounds (64.2%), especially protein and carbohydrates species, accounted for most of the WSOM in the accumulation mode particles in Dalian. The CHO compounds (67.6%-79.7%) contributed the most to the WSOM in coarse mode particles (> 2 μm) from both sites. Potential sources analysis indicated the WSOM in Baoding were mainly derived from biomass burning and oxidation reactions, while the WSOM in Dalian arose from coal combustion, oxidation reactions, and regional transport.

Two-Dimensional Fourier Transform Ion Cyclotron Resonance Mass Spectrometry of N-Linked Glycopeptides

Glycosylation is a common modification across living organisms and plays a central role in understanding biological systems and disease. Our ability to probe the gylcome has grown exponentially in the past several decades. However, further improvements to the analytical toolbox available to researchers would allow for increased capabilities to probe structure and function of biological systems and to improve disease treatment. This article applies the developing technique of two-dimensional Fourier transform ion cyclotron resonance mass spectrometry to a glycoproteomic workflow for the standard glycoproteins coral tree lectin (CTL) and bovine ribonuclease B (BRB) to demonstrate its feasibility as a tool for glycoproteomic workflows. 2D infrared multiphoton dissociation and electron capture dissociation spectra of CTL reveal comparable structural information to their 1D counterparts, confirming the site of glycosylation and monosaccharide composition of the glycan. Spectra collected in 2D of BRB reveal correlation lines of fragment ion scans and vertical precursor ion scans for data collected using infrared multiphoton dissociation and diagonal cleavage lines for data collected by electron capture dissociation. The use of similar techniques for glycoproteomic analysis may prove valuable in instances where chromatographic separation is undesirable or quadrupole isolation is insufficient.

Strong Bases and beyond: The Prominent Contribution of Neutral Push-Pull Organic Molecules towards Superbases in the Gas Phase

In this review, the principles of gas-phase proton basicity measurements and theoretical calculations are recalled as a reminder of how the basicity PA/GB scale, based on Brønsted-Lowry theory, was constructed in the gas-phase (PA-proton affinity and/or GB-gas-phase basicity in the enthalpy and Gibbs energy scale, respectively). The origins of exceptionally strong gas-phase basicity of some organic nitrogen bases containing N-sp3 (amines), N-sp2 (imines, amidines, guanidines, polyguanides, phosphazenes), and N-sp (nitriles) are rationalized. In particular, the role of push-pull nitrogen bases in the development of the gas-phase basicity in the superbasicity region is emphasized. Some reasons for the difficulties in measurements for poly-functional nitrogen bases are highlighted. Various structural phenomena being in relation with gas-phase acid-base equilibria that should be considered in quantum-chemical calculations of PA/GB parameters are discussed. The preparation methods for strong organic push-pull bases containing a N-sp2 site of protonation are briefly reviewed. Finally, recent trends in research on neutral organic superbases, leaning toward catalytic and other remarkable applications, are underlined.

Ion parking in native mass spectrometry

A forced, damped harmonic oscillator model for gas-phase ion parking using single-frequency resonance excitation is described and applied to high-mass ions of relevance to native mass spectrometry. Experimental data are provided to illustrate key findings revealed by the modelling. These include: (i) ion secular frequency spacings between adjacent charge states of a given protein are essentially constant and decrease with the mass of the protein (ii) the mechanism for ion parking of high mass ions is the separation of the ion clouds of the oppositely-charged ions with much less influence from an increase in the relative ion velocity due to resonance excitation, (iii) the size of the parked ion cloud ultimately limits ion parking at high m/z ratio, and (iv) the extent of ion parking of off-target ions is highly sensitive to the bath gas pressure in the ion trap. The model is applied to ions of 17 kDa, 467 kDa, and 2 MDa while experimental data are also provided for ions of horse skeletal muscle myoglobin (≈17 kDa) and β-galactosidase (≈467 kDa). The model predicts and data show that it is possible to effect ion parking on a 17 kDa protein to the 1+ charge state under trapping conditions that are readily accessible with commercially available ion traps. It is also possible to park β-galactosidase efficiently to a roughly equivalent m/z ratio (i.e., the 26+ charge state) under the same trapping conditions. However, as charge states decrease, analyte ion cloud sizes become too large to allow for efficient ion trapping. The model allows for a semi-quantitative prediction of ion trapping performance as a function of ion trapping, resonance excitation, and pressure conditions.

Resolving the intricate binding of neomycin B to multiple binding motifs of a neomycin-sensing riboswitch aptamer by native top-down mass spectrometry and NMR spectroscopy

Understanding small molecule binding to RNA can be complicated by an intricate interplay between binding stoichiometry, multiple binding motifs, different occupancies of different binding motifs, and changes in the structure of the RNA under study. Here, we use native top-down mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy to experimentally resolve these factors and gain a better understanding of the interactions between neomycin B and the 40 nt aptamer domain of a neomycin-sensing riboswitch engineered in yeast. Data from collisionally activated dissociation of the 1:1, 1:2 and 1:3 RNA-neomycin B complexes identified a third binding motif C of the riboswitch in addition to the two motifs A and B found in our previous study, and provided occupancies of the different binding motifs for each complex stoichiometry. Binding of a fourth neomycin B molecule was unspecific according to both MS and NMR data. Intriguingly, all major changes in the aptamer structure can be induced by the binding of the first neomycin B molecule regardless of whether it binds to motif A or B as evidenced by stoichiometry-resolved MS data together with titration data from 1H NMR spectroscopy in the imino proton region. Specific binding of the second and third neomycin B molecules further stabilizes the riboswitch aptamer, thereby allowing for a gradual response to increasing concentrations of neomycin B, which likely leads to a fine-tuning of the cellular regulatory mechanism.

IR spectroscopic characterization of [M,C,2H]+ (M = Ru and Rh) products formed by reacting 4d transition metal cations with oxirane: Spectroscopic evidence for multireference character in RhCH2. Phys Chem Chem Phys 2024;26:11445-11458. [PMID: 38572552 PMCID: PMC11022548 DOI: 10.1039/d4cp00012a]

A combination of infrared multiple-photon dissociation (IRMPD) action spectroscopy and quantum chemical calculations was employed to investigate the [M,C,2H]+ (M = Ru and Rh) species. These ions were formed by reacting laser ablated M+ ions with oxirane (ethylene oxide, c-C2H4O) in a room-temperature ion trap. IRMPD spectra for the Ru species exhibit one major band and two side bands, whereas spectra for the Rh species contain more distinct bands. Comparison with density functional theory (DFT), coupled-cluster (CCSD), and equation-of-motion spin-flip CCSD (EOM-SF-CCSD) calculations allows assignment of the [M,C,2H]+ structures. For the spectrum of [Ru,C,2H]+, a combination of HRuCH+ and RuCH2+ structures reproduces the observed spectrum at all levels of theory. The well-resolved spectrum of [Rh,C,2H]+ could not be assigned unambiguously to any calculated structure using DFT approaches. The EOM-SF-CCSD calculations showed that the ground-state surface has multireference electronic character, and symmetric carbenes in both the 1A1 and 3A2 states are needed to reproduce the observed spectrum.

Multiple ion isolation and accumulation events for selective chemical noise reduction and dynamic range enhancement in MALDI imaging mass spectrometry

Abundant chemical noise in MALDI imaging mass spectrometry experiments can impede the detection of less abundant compounds of interest. This chemical noise commonly originates from the MALDI matrix as well as other endogenous compounds present in high concentrations and/or with high ionization efficiencies. MALDI imaging mass spectrometry of biological tissues measures numerous biomolecular compounds that exist in a wide range of concentrations in vivo. When ion trapping instruments are used, highly abundant ions can dominate the charge capacity and lead to space charge effects that hinder the dynamic range and detection of lowly abundant compounds of interest. Gas-phase fractionation has been previously utilized in mass spectrometry to isolate and enrich target analytes. Herein, we have characterized the use of multiple continuous accumulations of selected ions (Multi CASI) to reduce the abundance of chemical noise and diminish the effects of space charge in MALDI imaging mass spectrometry experiments. Multi CASI utilizes the mass-resolving capability of a quadrupole mass filter to perform multiple sequential ion isolation events prior to a single mass analysis of the combined ion population. Multi CASI was used to improve metabolite and lipid detection in the MALDI imaging mass spectrometry analysis of rat brain tissue.

Native Top-Down Mass Spectrometry for Characterizing Sarcomeric Proteins Directly from Cardiac Tissue Lysate

Native top-down mass spectrometry (nTDMS) has emerged as a powerful structural biology tool that can localize post-translational modifications (PTMs), explore ligand-binding interactions, and elucidate the three-dimensional structure of proteins and protein complexes in the gas-phase. Fourier-transform ion cyclotron resonance (FTICR) MS offers distinct capabilities for nTDMS, owing to its ultrahigh resolving power, mass accuracy, and robust fragmentation techniques. Previous nTDMS studies using FTICR have mainly been applied to overexpressed recombinant proteins and protein complexes. Here, we report the first nTDMS study that directly analyzes human heart tissue lysate by direct infusion FTICR MS without prior chromatographic separation strategies. We have achieved comprehensive nTDMS characterization of cardiac contractile proteins that play critical roles in heart contraction and relaxation. Specifically, our results reveal structural insights into ventricular myosin light chain 2 (MLC-2v), ventricular myosin light chain 1 (MLC-1v), and alpha-tropomyosin (α-Tpm) in the sarcomere, the basic contractile unit of cardiac muscle. Furthermore, we verified the calcium (Ca2+) binding domain in MLC-2v. In summary, our nTDMS platform extends the application of FTICR MS to directly characterize the structure, PTMs, and metal-binding of endogenous proteins from heart tissue lysate without prior separation methods.

IR spectroscopic characterization of 3d transition metal carbene cations, FeCH2+ and CoCH2+: periodic trends and a challenge for DFT approaches

A combination of IR multiple-photon dissociation (IRMPD) action spectroscopy and quantum chemical calculations was employed to investigate the [M,C,2H]+ (M = Fe and Co) species. These were formed by reacting laser ablated M+ ions with oxirane (ethylene oxide, c-C2H4O) in a room temperature ion trap. IRMPD spectra for the Fe and Co species are very similar and exhibit one major band. Comparison with density functional theory (DFT) and coupled cluster with single and double excitations (CCSD) calculations allows assignment of the spectra to MCH2+ carbene structures. For these 3d transition metal systems, experimental IRMPD spectra compare relatively poorly with DFT calculated IR spectra, but CCSD calculated spectra are a much better match primarily because the M-C stretch gains significant intensity. The origins of this behavior are explored in some detail. The present results are also compared to previous results for the 4d and 5d congeners and the periodic trends in these structures are evaluated.

Multiscale biochemical mapping of the brain through deep-learning-enhanced high-throughput mass spectrometry

Spatial omics technologies can reveal the molecular intricacy of the brain. While mass spectrometry imaging (MSI) provides spatial localization of compounds, comprehensive biochemical profiling at a brain-wide scale in three dimensions by MSI with single-cell resolution has not been achieved. We demonstrate complementary brain-wide and single-cell biochemical mapping using MEISTER, an integrative experimental and computational mass spectrometry (MS) framework. Our framework integrates a deep-learning-based reconstruction that accelerates high-mass-resolving MS by 15-fold, multimodal registration creating three-dimensional (3D) molecular distributions and a data integration method fitting cell-specific mass spectra to 3D datasets. We imaged detailed lipid profiles in tissues with millions of pixels and in large single-cell populations acquired from the rat brain. We identified region-specific lipid contents and cell-specific localizations of lipids depending on both cell subpopulations and anatomical origins of the cells. Our workflow establishes a blueprint for future development of multiscale technologies for biochemical characterization of the brain.

Recent Developments and Application of Mass Spectrometry Imaging in N-Glycosylation Studies: An Overview

Among the most typical posttranslational modifications is glycosylation, which often involves the covalent binding of an oligosaccharide (glycan) to either an asparagine (N-linked) or a serine/threonine (O-linked) residue. Studies imply that the N-glycan portion of a glycoprotein could serve as a particular disease biomarker rather than the protein itself because N-linked glycans have been widely recognized to evolve with the advancement of tumors and other diseases. N-glycans found on protein asparagine sites have been especially significant. Since N-glycans play clearly defined functions in the folding of proteins, cellular transport, and transmission of signals, modifications to them have been linked to several illnesses. However, because these N-glycans' production is not template driven, they have a substantial morphological range, rendering it difficult to distinguish the species that are most relevant to biology and medicine using standard techniques. Mass spectrometry (MS) techniques have emerged as effective analytical tools for investigating the role of glycosylation in health and illness. This is due to developments in MS equipment, data collection, and sample handling techniques. By recording the spatial dimension of a glycan's distribution in situ, mass spectrometry imaging (MSI) builds atop existing methods while offering added knowledge concerning the structure and functionality of biomolecules. In this review article, we address the current development of glycan MSI, starting with the most used tissue imaging techniques and ionization sources before proceeding on to a discussion on applications and concluding with implications for clinical research.

Chemometric Combination of Ultrahigh Resolving Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy for a Structural Characterization of Lignin Compounds

In recent years, the potential of lignins as a resource for material-based applications has been highlighted in many scientific and nonscientific publications. But still, to date, a lack of detailed structural knowledge about this ultracomplex biopolymer undermines its great potential. The chemical complexity of lignin demands a combination of different, powerful analytical methods, in order to obtain these necessary information. In this paper, we demonstrate a multispectroscopic approach using liquid-state and solid-state Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and nuclear magnetic resonance (NMR) spectroscopy to characterize a fractionated LignoBoost lignin. Individual FT-ICR-MS, tandem MS, and NMR results helped to determine relevant information about the different lignin fractions, such as molecular weight distributions, oligomer sizes, linkage types, and presence of specific functional groups. In addition, a hetero spectroscopic correlation approach was applied to chemometrically combine MS, MS/MS, and NMR data sets. From these correlation analyses, it became obvious that a combination of tandem MS and NMR data sets gives the opportunity to comprehensively study and describe the general structure of complex biopolymer samples. Compound-specific structural information are obtainable, if this correlation approach is extended to 1D-MS and NMR data, as specific functional groups or linkages are verifiable for a defined molecular formula. This enables structural characterization of individual lignin compounds without the necessity for tandem MS experiments. Hence, these correlation results significantly improve the depth of information of each individual analysis and will hopefully help to structurally elucidate entire lignin structures in the near future.

Advances in Imaging Mass Spectrometry for Biomedical and Clinical Research

Imaging mass spectrometry (IMS) allows for the untargeted mapping of biomolecules directly from tissue sections. This technology is increasingly integrated into biomedical and clinical research environments to supplement traditional microscopy and provide molecular context for tissue imaging. IMS has widespread clinical applicability in the fields of oncology, dermatology, microbiology, and others. This review summarizes the two most widely employed IMS technologies, matrix-assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI), and covers technological advancements, including efforts to increase spatial resolution, specificity, and throughput. We also highlight recent biomedical applications of IMS, primarily focusing on disease diagnosis, classification, and subtyping.

Integrative Multiscale Biochemical Mapping of the Brain via Deep-Learning-Enhanced High-Throughput Mass Spectrometry

Elucidating the spatial-biochemical organization of the brain across different scales produces invaluable insight into the molecular intricacy of the brain. While mass spectrometry imaging (MSI) provides spatial localization of compounds, comprehensive chemical profiling at a brain-wide scale in three dimensions by MSI with single-cell resolution has not been achieved. We demonstrate complementary brain-wide and single-cell biochemical mapping via MEISTER, an integrative experimental and computational mass spectrometry framework. MEISTER integrates a deep-learning-based reconstruction that accelerates high-mass-resolving MS by 15-fold, multimodal registration creating 3D molecular distributions, and a data integration method fitting cell-specific mass spectra to 3D data sets. We imaged detailed lipid profiles in tissues with data sets containing millions of pixels, and in large single-cell populations acquired from the rat brain. We identified region-specific lipid contents, and cell-specific localizations of lipids depending on both cell subpopulations and anatomical origins of the cells. Our workflow establishes a blueprint for future developments of multiscale technologies for biochemical characterization of the brain.

Top-Down Proteoform Analysis by 2D MS with Quadrupolar Detection

Two-dimensional mass spectrometry (2D MS) is a multiplexed tandem mass spectrometry method that does not rely on ion isolation to correlate the precursor and fragment ions. On a Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR MS), 2D MS instead uses the modulation of precursor ion radii inside the ICR cell before fragmentation and yields 2D mass spectra that show the fragmentation patterns of all the analytes. In this study, we perform 2D MS for the first time with quadrupolar detection in a dynamically harmonized ICR cell. We discuss the advantages of quadrupolar detection in 2D MS and how we adapted existing data processing techniques for accurate frequency-to-mass conversion. We apply 2D MS with quadrupolar detection to the top-down analysis of covalently labeled ubiquitin with ECD fragmentation, and we develop a workflow for label-free relative quantification of biomolecule isoforms in 2D MS.

Advances in high-resolution mass spectrometry techniques for analysis of high mass-to-charge ions

A major challenge in modern mass spectrometry (MS) is achieving high mass resolving power and accuracy for precision analyses in high mass-to-charge (m/z) regions. To advance the capability of MS for increasingly demanding applications, understanding limitations of state-of-the-art techniques and their status in applied sciences is essential. This review summarizes important instruments in high-resolution mass spectrometry (HRMS) and related advances to extend their working range to high m/z regions. It starts with an overview of HRMS techniques that provide adequate performance for macromolecular analysis, including Fourier-transform, time-of-flight (TOF), quadrupole-TOF, and related data-processing techniques. Methodologies and applications of HRMS for characterizing macromolecules in biochemistry and material sciences are summarized, such as top-down proteomics, native MS, drug discovery, structural virology, and polymer analyses.

Exploring Charge-Detection Mass Spectrometry on Chromatographic Time Scales

Charge-detection mass spectrometry (CDMS) enables direct measurement of the charge of an ion alongside its mass-to-charge ratio. CDMS offers unique capabilities for the analysis of samples where isotopic resolution or the separation of charge states cannot be achieved, i.e., heterogeneous macromolecules or highly complex mixtures. CDMS is usually performed using static nano-electrospray ionization-based direct infusion with acquisition times in the range of several tens of minutes to hours. Whether CDMS analysis is also attainable on shorter time scales, e.g., comparable to chromatographic peak widths, has not yet been extensively investigated. In this contribution, we probed the compatibility of CDMS with online liquid chromatography interfacing. Size exclusion chromatography was coupled to CDMS for separation and mass determination of a mixture of transferrin and β-galactosidase. Molecular masses obtained were compared to results from mass spectrometry based on ion ensembles. A relationship between the number of CDMS spectra acquired and the achievable mass accuracy was established. Both proteins were found to be confidently identified using CDMS spectra obtained from a single chromatographic run when peak widths in the range of 1.4-2.5 min, translating to 140-180 spectra per protein were achieved. After demonstration of the proof of concept, the approach was tested for the characterization of the highly complex glycoprotein α-1-acid glycoprotein and the Fc-fusion protein etanercept. With chromatographic peak widths of approximately 3 min, translating to ∼200 spectra, both proteins were successfully identified, demonstrating applicability for samples of high inherent molecular complexity.

A Research Journey: Over a Decade of Denaturing and Native-MS Analyses of Hydrophobic and Membrane Proteins in Amgen Therapeutic Discovery

Membrane proteins and associated complexes currently comprise the majority of therapeutic targets and remain among the most challenging classes of proteins for analytical characterization. Through long-term strategic collaborations forged between industrial and academic research groups, there has been tremendous progress in advancing membrane protein mass spectrometry (MS) analytical methods and their concomitant application to Amgen therapeutic project progression. Herein, I will describe a detailed and personal account of how electrospray ionization (ESI) native mass spectrometry (nMS), ion mobility-MS (IM-MS), reversed phase liquid chromatographic mass spectrometry (RPLC-MS), high-throughput solid phase extraction mass spectrometry, and matrix-assisted laser desorption ionization mass spectrometry methods were developed, optimized, and validated within Amgen Research, and importantly, how these analytical methods were applied for membrane and hydrophobic protein analyses and ultimately therapeutic project support and progression. Additionally, I will discuss all the highly important and productive collaborative efforts, both internal Amgen and external academic, which were key in generating the samples, methods, and associated data described herein. I will also describe some early and previously unpublished nano-ESI (nESI) native-MS data from Amgen Research and the highly productive University of California Los Angeles (UCLA) collaboration. I will also present previously unpublished examples of real-life Amgen biotherapeutic membrane protein projects that were supported by all the MS (and IM) analytical techniques described herein. I will start by describing the initial nESI nMS experiments performed at Amgen in 2011 on empty nanodisc molecules, using a quadrupole time-of-flight MS, and how these experiments progressed on to the 15 Tesla Fourier transform ion cyclotron resonance MS at UCLA. Then described are monomeric and multimeric membrane protein data acquired in both nESI nMS and tandem-MS modes, using multiple methods of ion activation, resulting in dramatic spectral simplification. Also described is how we investigated the far less established and less published subject, that is denaturing RPLC-MS analysis of membrane proteins, and how we developed a highly robust and reproducible RPLC-MS method capable of effective separation of membrane proteins differing in only the presence or absence of an N-terminal post translational modification. Also described is the evolution of the aforementioned RPLC-MS method into a high-throughput solid phase extraction MS method. Finally, I will give my opinion on key developments and how the area of nMS of membrane proteins needs to evolve to a state where it can be applied within the biopharmaceutical research environment for routine therapeutic project support.

Separation of Isobaric Lipids in Imaging Mass Spectrometry Using Gas-Phase Charge Inversion Ion/Ion Reactions

The diverse array of chemical compounds present in tissue samples results in many isobaric (i.e., same nominal mass) compounds in imaging mass spectrometry experiments. Adequate separation and differentiation of these compounds is necessary to ensure accurate analyte identification and avoid composite images comprising multiple compounds. High-resolution accurate mass (HRAM) measurements are able to resolve these compounds in some instances, but HRAM measurements are not always feasible depending on the instrument platform and the desired experimental time scale. Alternatively, tandem mass spectrometry (MS/MS) can be used to perform gas-phase transformations that improve molecular specificity. While conventional MS/MS methods employ collision induced dissociation (CID) to fragment compounds of interest and then analyze the product masses, gas-phase ion/ion reactions can be used to instead selectively react with desired classes of analytes. Herein, we have used gas-phase charge inversion ion/ion reactions to selectively resolve phosphatidylcholines (PCs) in isobaric lipid mixtures. A 1,4-phenylenedipropionic acid (PDPA) reagent dianion readily reacts with [M + H]+, [M + Na]+, and [M + K]+ ion types to produce demethylated product anions for each PC, [PC - CH3]-. These product anions are no longer isobaric and now differ in mass by 22 Da (protonated versus sodiated) and 16 Da (sodiated versus potassiated), respectively. This reaction has been used to differentiate isobaric lipids in the imaging mass spectrometry analysis of rat brain tissue.

Applications of mass spectrometry in cosmetic analysis: An overview

Mass spectrometry (MS) is a crucial tool in cosmetic analysis. It is widely used for ingredient screening, quality control, risk monitoring, authenticity verification, and efficacy evaluation. However, due to the diversity of cosmetic products and the rapid development of MS-based analytical methods, the relevant literature needs a more systematic collation of information on this subject to unravel the true potential of MS in cosmetic analysis. Herein, an overview of the role of MS in cosmetic analysis over the past two decades is presented. The currently used sample preparation methods, ionization techniques, and types of mass analyzers are demonstrated in detail. In addition, a brief perspective on the future development of MS for cosmetic analysis is provided.

Deep Characterization of Serum Metabolome Based on the Segment-Optimized Spectral-Stitching Direct-Infusion Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Approach

Direct-infusion Fourier transform ion cyclotron resonance mass spectrometry (DI-FTICR MS) shows great promise for metabolomic analysis due to ultrahigh mass accuracy and resolution. However, most of the DI-FTICR MS approaches focused on high-throughput metabolomics analysis at the expense of sensitivity and resolution and the potential for metabolome characterization has not been fully explored. Here, we proposed a novel deep characterization approach of serum metabolome using a segment-optimized spectral-stitching DI-FTICR MS method integrated with high-confidence and database-independent formula assignments. With varied acquisition parameters for each segment, a highly efficient acquisition was achieved for the whole mass range with sub-ppm mass accuracy. In a pooled human serum sample, thousands of features were assigned with unambiguous formulas and possible candidates based on highly accurate mass measurements. Furthermore, a reaction network was used to select confidently unique formulas from possible candidates, which was constructed by unambiguous formulas and possible candidates connected by the formula differences resulting from biochemical and MS transformation. Compared with full-range and conventional segment acquisition, 8- and 1.2-fold increases in observed features were achieved, respectively. Assignment accuracy was 93-94% for both a standard mixture containing 190 metabolites and a spiked serum sample with the root mean square mass error of 0.15-0.16 ppm. In total, 3534 unequivocal neutral molecular formulas were assigned in the pooled serum sample, 35% of which are contained in the HMDB. This method offers great enhancement in the deep characterization of serum metabolome by DI-FTICR MS.

Dynamic Energy Measurements in Charge Detection Mass Spectrometry Eliminate Adverse Effects of Ion-Ion Interactions

Ion-ion interactions in charge detection mass spectrometers that use electrostatic traps to measure masses of individual ions have not been reported previously, although ion trajectory simulations have shown that these types of interactions affect ion energies and thereby degrade measurement performance. Here, examples of interactions between simultaneously trapped ions that have masses ranging from ca. 2 to 350 MDa and ca. 100 to 1000 charges are studied in detail using a dynamic measurement method that makes it possible to track the evolution of the mass, charge, and energy of individual ions over their trapping lifetimes. Signals from ions that have similar oscillation frequencies can have overlapping spectral leakage artifacts that result in slightly increased uncertainties in the mass determination, but these effects can be mitigated by the careful choice of parameters used in the short-time Fourier transform analysis. Energy transfers between physically interacting ions are also observed and quantified with individual ion energy measurement resolution as high as ∼950. The mass and charge of interacting ions do not change, and their corresponding measurement uncertainties are equivalent to ions that do not undergo physical interactions. Simultaneous trapping of multiple ions in CDMS can greatly decrease the acquisition time necessary to accumulate a statistically meaningful number of individual ion measurements. These results demonstrate that while ion-ion interactions can occur when multiple ions are trapped, they have negligible effects on mass accuracy when using the dynamic measurement method.

The Crosstalk between Gut Microbiota and Nervous System: A Bidirectional Interaction between Microorganisms and Metabolome

Several studies have shown that the gut microbiota influences behavior and, in turn, changes in the immune system associated with symptoms of depression or anxiety disorder may be mirrored by corresponding changes in the gut microbiota. Although the composition/function of the intestinal microbiota appears to affect the central nervous system (CNS) activities through multiple mechanisms, accurate epidemiological evidence that clearly explains the connection between the CNS pathology and the intestinal dysbiosis is not yet available. The enteric nervous system (ENS) is a separate branch of the autonomic nervous system (ANS) and the largest part of the peripheral nervous system (PNS). It is composed of a vast and complex network of neurons which communicate via several neuromodulators and neurotransmitters, like those found in the CNS. Interestingly, despite its tight connections to both the PNS and ANS, the ENS is also capable of some independent activities. This concept, together with the suggested role played by intestinal microorganisms and the metabolome in the onset and progression of CNS neurological (neurodegenerative, autoimmune) and psychopathological (depression, anxiety disorders, autism) diseases, explains the large number of investigations exploring the functional role and the physiopathological implications of the gut microbiota/brain axis.

Sugars and Organic Acids in 25 Strawberry Cultivars: Qualitative and Quantitative Evaluation

(1) The nutritional quality of strawberry (Fragaria × ananassa Duch) fruits, among others, is largely maintained by the presence of soluble sugars and organic acids. As the primary products of photosynthesis, they are energy depots in plants, necessary for the construction of cell constituents, but also serve as precursors of aromatic compounds and signaling molecules. (2) In this study, fruits of 25 strawberry cultivars were qualitatively and quantitatively characterized concerning individual sugars and organic acids by HPLC, FT-ICR-MS, and MS imaging analysis. In addition, the total quality index (TQI), as a novel mathematical model, was used to compare all individual parameters evaluated to obtain a quantitative single score, as an indicator of overall fruit quality. (3) Regardless of a large number of cultivars and monitored parameters that were studded, several cultivars stood out in terms of selected primary metabolites, such as 'Rumba', 'Jeny', and 'Sandra', while the latter had the best TQI score. (4) Intercultivar variations in sugars and organic acids profiles, along with other bioactive compounds, should be considered for selection of promising cultivars with improved naturally occurring nutraceutical traits. Besides the search for a pleasant taste, increased awareness of healthy nutrition resulted in heightening consumer demand for high-quality fruit.

Hyphenation of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) with separation methods: The art of compromises and the possible - A review

This review provides an overview of the online hyphenation of Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) with separation methods to date. The online coupling between separation techniques (gas and liquid chromatography, capillary electrophoresis) and FT-ICR MS essentially raises questions of compromise and is not look as straightforward as hyphenation with other analyzers (QTOF-MS for instance). FT-ICR MS requires time to reach its highest resolving power and accuracy in mass measurement capabilities whereas chromatographic and electrophoretic peaks are transient. In many applications, the strengths and the weaknesses of each technique are balanced by their hyphenation. Untargeted "Omics" (e.g. proteomics, metabolomics, petroleomics, …) is one of the main areas of application for FT-ICR MS hyphenated to online separation techniques because of the complexity of the sample. FT-ICR MS achieves the required high mass measurement accuracy to determine accurate molecular formulae and resolution for isobar distinction. Meanwhile separation techniques highlight isomers and reduce the ion suppression effects extending the dynamic range. Even if the implementation of FT-ICR MS hyphenated with online separation methods is a little trickier (the art of compromise), this review shows that it provides unparalleled results to the scientific community (the art of the possible), along with raising the issue of its future in the field with the relentless technological progress.

Robust High-Throughput Proteomics Identification and Deamidation Quantitation of Extinct Species up to Pleistocene with Ultrahigh-Resolution MALDI-FTICR Mass Spectrometry

Peptide mass fingerprinting (PMF) using MALDI-TOF mass spectrometry allows the identification of bone species based on their type I collagen sequence. In the archaeological or paleontological field, PMF is known as zooarchaeology mass spectrometry (ZooMS) and is widely implemented to find markers for most species, including the extinct ones. In addition to the identification of bone species, ZooMS enables dating estimation by measuring the deamidation value of specific peptides. Herein, we report several enhancements to the classical ZooMS technique, which reduces to 10-fold the required bone sample amount (down to the milligram scale) and achieves robust deamidation value calculation in a high-throughput manner. These improvements rely on a 96-well plate samples preparation, a careful optimization of collagen extraction and digestion to avoid spurious post-translational modification production, and PMF at high resolution using matrix-assisted laser desorption ionization Fourier transform ion cyclotron resonance (MALDI-FTICR) analysis. This method was applied to the identification of a hundred bones of herbivores from the Middle Paleolithic site of Caours (Somme, France) well dated from the Eemian Last Interglacial climatic optimum. The method gave reliable species identification to bones already identified by their osteomorphology, as well as to more challenging samples consisting of small or burned bone fragments. Deamidation values of bones originating from the same geological layers have a low standard deviation. The method can be applied to archaeological bone remains and offers a robust capacity to identify traditionally unidentifiable bone fragments, thus increasing the number of identified specimens and providing invaluable information in specific contexts.

Ultra-Accurate Correlation between Precursor and Fragment Ions in Two-Dimensional Mass Spectrometry: Acetylated vs Trimethylated Histone Peptides

Two-dimensional mass spectrometry (2D MS) is a method for tandem mass spectrometry in which precursor and fragment ions are correlated by manipulating ion radii rather than by ion isolation. A 2D mass spectrum contains the fragmentation patterns of all analytes in a sample, acquired in parallel. We report ultrahigh-resolution narrowband 2D mass spectra of a mixture of two histone peptides with the same sequence, one of which carries an acetylation and the other a trimethylation (m/z 0.006 difference). We reduced the distance between data points in the precursor ion dimension and compared the accuracy of the precursor-fragment correlation with the resolving power. We manage to perform label-free quantification on the histone peptide mixture and show that precursor and fragment ions can be accurately correlated even though the precursor ions are not resolved. Finally, we show that increasing the resolution of a 2D mass spectrum in the precursor ion dimension too far can lead to a decline in the signal-to-noise ratio.

Dissolved organic matter in complex shale gas wastewater analyzed with ESI FT-ICR MS: Typical characteristics and potential of biological treatment

Knowledge on the composition and characteristics of dissolved organic matter (DOM) in complex shale gas wastewater (SGW) is critical to evaluate environmental risks and to determine effective management strategies. Herein, five SGW samples from four key shale gas blocks in the Sichuan Basin, China, were comprehensively characterized. Specifically, FT-ICR MS was employed to provide insights into the sources, composition, and characteristics of SGW DOM. Organic matter was characterized by low average molecular weight, high saturation degree, and low aromaticity. Notably, the absence of correlations between molecular-level parameters and spectral indexes might be attributed to the high complexity and variability of SGW. The unique distribution depicted in van Krevelen diagrams suggested various sources of DOM in SGW, such as microbially derived organics in shales and biochemical transformations. Moreover, linear alkyl benzene sulfonates, as well as associated biodegraded metabolites and coproducts, were identified in SGW, implying the distinct anthropogenic imprints and abundant microbial activities. Furthermore, high DOC removal rates (31.42-79.23 %) were achieved by biological treatment, fully supporting the inherently labile nature of SGW and the feasibility of biodegradation for SGW management. Therefore, we conclude that DOM in SGW is a complex but mostly labile mixture reflecting both autochthonous and anthropogenic sources.

Spatial probabilistic mapping of metabolite ensembles in mass spectrometry imaging

Mass spectrometry imaging vows to enable simultaneous spatially resolved investigation of hundreds of metabolites in tissues, but it primarily relies on traditional ion images for non-data-driven metabolite visualization and analysis. The rendering and interpretation of ion images neither considers nonlinearities in the resolving power of mass spectrometers nor does it yet evaluate the statistical significance of differential spatial metabolite abundance. Here, we outline the computational framework moleculaR ( https://github.com/CeMOS-Mannheim/moleculaR ) that is expected to improve signal reliability by data-dependent Gaussian-weighting of ion intensities and that introduces probabilistic molecular mapping of statistically significant nonrandom patterns of relative spatial abundance of metabolites-of-interest in tissue. moleculaR also enables cross-tissue statistical comparisons and collective molecular projections of entire biomolecular ensembles followed by their spatial statistical significance evaluation on a single tissue plane. It thereby fosters the spatially resolved investigation of ion milieus, lipid remodeling pathways, or complex scores like the adenylate energy charge within the same image.

A high resolution Fourier transform ion trap enabled by image current splicing: a theoretical study

The relatively high work pressure within an ion trap has limited the implementation of the Fourier transform technique for high resolution mass analysis. The main reason is that high buffer gas pressure will cause the rapid decay of ion oscillations. In this study, an image current splicing method based on the filter diagonalization method (FDM) and the Hilbert transform was developed to increase the resolving power of nondestructive mass analysis in a linear ion trap. First, multiple repeated experiments (or ion trajectory simulations) were performed to collect multiple sets of data. Using the FDM, the frequency component distribution was extracted from short image current transients collected from each experiment. The Hilbert transform was then applied to calculate and normalize the decay envelope of each transient. The relative abundance was calculated by counting the envelopes. Finally, image current transients collected from these multiple experiments were spliced and merged into a whole signal with much longer duration and continuous phase. This splicing method could effectively increase the duration of the image current, and thus improve the mass resolution of the ion trap mass analyzer. The mass resolution (m/Δm) was improved from 183.5 to 5.8 × 10³, and the average relative difference was 2.8%. The proposed method resolved 3 adjacent peaks which originally could not be resolved from the raw signal by the fast Fourier transform (FFT). Besides simulated data, this method was also applied to the experimental data collected from a Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometer. The influence of electronic noise on the proposed method was also discussed in this study.

Machine-learning assisted molecular formula assignment to high-resolution mass spectrometry data of dissolved organic matter

High-resolution mass spectrometry (HRMS) provides molecular compositional information of dissolved organic matter (DOM) through isotopic assignment from the molecular mass. However, due to the inevitable deviation of molecular mass measurement and the limitation of resolving power, multiple possible solutions frequently occur for a given molecular mass. Lowering the mass deviation threshold and adding assignment restriction rules are often applied to exclude the incorrect solutions, which generally involves time-consuming manual post-processing of mass data. To improve the result accuracy in an automated manner, we developed a molecular formula assignment algorithm based on machine-learning technology. The method integrated a logistic regression model using manually corrected isotopic composition and the peak features of HRMS data (m/z, signal-to-noise ratio, isotope type, and number, etc.) as training data. The developed model can evaluate the correctness of a candidate formula for the given mass peak based on the peak features. The method was verified by various DOM samples FT-ICR MS data (direct infusion negative mode electrospray), achieving a ∼90% accuracy (compared to the traditional approach) for formula assignment. The method was applied to a series of NOM samples and showed a significant improvement in formula assignment compared with the mass matching method.

Applications and continued evolution of glycan imaging mass spectrometry

Glycosylation is an important posttranslational modifier of proteins and lipid conjugates critical for the stability and function of these macromolecules. Particularly important are N-linked glycans attached to asparagine residues in proteins. N-glycans have well-defined roles in protein folding, cellular trafficking and signal transduction, and alterations to them are implicated in a variety of diseases. However, the non-template driven biosynthesis of these N-glycans leads to significant structural diversity, making it challenging to identify the most biologically and clinically relevant species using conventional analyses. Advances in mass spectrometry instrumentation and data acquisition, as well as in enzymatic and chemical sample preparation strategies, have positioned mass spectrometry approaches as powerful analytical tools for the characterization of glycosylation in health and disease. Imaging mass spectrometry expands upon these strategies by capturing the spatial component of a glycan's distribution in-situ, lending additional insight into the organization and function of these molecules. Herein we review the ongoing evolution of glycan imaging mass spectrometry beginning with widely adopted tissue imaging approaches and expanding to other matrices and sample types with potential research and clinical implications. Adaptations of these techniques, along with their applications to various states of disease, are discussed. Collectively, glycan imaging mass spectrometry analyses broaden our understanding of the biological and clinical relevance of N-glycosylation to human disease.

Advances in Ultra-High-Resolution Mass Spectrometry for Pharmaceutical Analysis

Pharmaceutical analysis refers to an area of analytical chemistry that deals with active compounds either by themselves (drug substance) or when formulated with excipients (drug product). In a less simplistic way, it can be defined as a complex science involving various disciplines, e.g., drug development, pharmacokinetics, drug metabolism, tissue distribution studies, and environmental contamination analyses. As such, the pharmaceutical analysis covers drug development to its impact on health and the environment. Moreover, due to the need for safe and effective medications, the pharmaceutical industry is one of the most heavily regulated sectors of the global economy. For this reason, powerful analytical instrumentation and efficient methods are required. In the last decades, mass spectrometry has been increasingly used in pharmaceutical analysis both for research aims and routine quality controls. Among different instrumental setups, ultra-high-resolution mass spectrometry with Fourier transform instruments, i.e., Fourier transform ion cyclotron resonance (FTICR) and Orbitrap, gives access to valuable molecular information for pharmaceutical analysis. In fact, thanks to their high resolving power, mass accuracy, and dynamic range, reliable molecular formula assignments or trace analysis in complex mixtures can be obtained. This review summarizes the principles of the two main types of Fourier transform mass spectrometers, and it highlights applications, developments, and future perspectives in pharmaceutical analysis.

The isotope distribution: A rose with thorns

The isotope distribution, which reflects the number and probabilities of occurrence of different isotopologues of a molecule, can be theoretically calculated. With the current generation of (ultra)-high-resolution mass spectrometers, the isotope distribution of molecules can be measured with high sensitivity, resolution, and mass accuracy. However, the observed isotope distribution can differ substantially from the expected isotope distribution. Although differences between the observed and expected isotope distribution can complicate the analysis and interpretation of mass spectral data, they can be helpful in a number of specific applications. These applications include, yet are not limited to, the identification of peptides in proteomics, elucidation of the elemental composition of small organic molecules and metabolites, as well as wading through peaks in mass spectra of complex bioorganic mixtures such as petroleum and humus. In this review, we give a nonexhaustive overview of factors that have an impact on the observed isotope distribution, such as elemental isotope deviations, ion sampling, ion interactions, electronic noise and dephasing, centroiding, and apodization. These factors occur at different stages of obtaining the isotope distribution: during the collection of the sample, during the ionization and intake of a molecule in a mass spectrometer, during the mass separation and detection of ionized molecules, and during signal processing.

Direct introduction MALDI FTICR MS based on dried droplet deposition applied to non-targeted metabolomics on Pisum Sativum root exudates

Non-targeted metabolomic approaches based on direct introduction (DI) through a soft ionization source are nowadays used for large-scale analysis and wide cover-up of metabolites in complex matrices. When coupled with ultra-high-resolution Fourier-Transform ion cyclotron resonance (FTICR MS), DI is generally performed through electrospray (ESI), which, despite the great analytical throughput, can suffer of matrix effects due to residual salts or charge competitors. In alternative, matrix assisted laser desorption ionization (MALDI) coupled with FTICR MS offers relatively high salt tolerance but it is mainly used for imaging of small molecule within biological tissues. In this study, we report a systematic evaluation on the performance of direct introduction ESI and MALDI coupled with FTICR MS applied to the analysis of root exudates (RE), a complex mixture of metabolites released from plant root tips and containing a relatively high salt concentration. Classic dried droplet deposition followed by screening of best matrices and ratio allowed the selection of high ranked conditions for non-targeted metabolomics on RE. Optimization of MALDI parameters led to improved reproducibility and precision. A RE desalted sample was used for comparison on ionization efficiency of the two sources and ion enhancement at high salinity was highlighted in MALDI by spiking desalted solution with inorganic salts. Application of a true lyophilized RE sample exhibited the complementarity of the two sources and the ability of MALDI in the detection of undisclosed metabolites suffering of matrix effects in ESI mode.

Binding Modes of a Cytotoxic Dinuclear Copper(II) Complex with Phosphate Ligands Probed by Vibrational Photodissociation Ion Spectroscopy

The dinuclear copper complex bearing a 2,7-disubstituted-1,8-naphthalenediol ligand, [(HtomMe){Cu(OAc)}₂](OAc), a potential anticancer drug able to bind to two neighboring phosphates in the DNA backbone, is endowed with stronger cytotoxic effects and inhibition ability of DNA synthesis in human cancer cells as compared to cisplatin. In this study, the intrinsic binding ability of the charged complex [(HtomMe){Cu(OAc)}₂]⁺ is investigated with representative phosphate diester ligands with growing chemical complexity, ranging from simple inorganic phosphate up to mononucleotides. An integrated method based on high-resolution mass spectrometry (MS), tandem MS, and infrared multiple photon dissociation (IRMPD) spectroscopy in the 600-1800 cm^-1 spectral range, backed by quantum chemical calculations, has been used to characterize complexes formed in solution and delivered as bare species by electrospray ionization. The structural features revealed by IRMPD spectroscopy have been interpreted by comparison with linear IR spectra of the lowest-energy structures, revealing diagnostic signatures of binding modes of the dinuclear copper(II) complex with phosphate groups, whereas the possible competitive interaction with the nucleobase is silenced in the gas phase. This result points to the prevailing interaction of [(HtomMe){Cu(OAc)}₂]⁺ with phosphate diesters and mononucleotides as a conceivable contribution to the observed anticancer activity.

Metabolomics and NMR

The purpose of this manuscript will be to convince the reader to dive deeper into NMR spectroscopy and prevent the technique from being just another "black-box" in the lab. We will try to concisely highlight interesting topics and supply additional references for further exploration at each stage. The advantages of delving into the technique will be shown. The secondary objective, i.e., avoiding common problems before starting, will hopefully then become clear. Lastly, we will emphasize the spectrometer information needed for manuscript reporting to allow reproduction of results and confirm findings.