Counting individual sulfur atoms in a protein by ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry: experimental resolution of isotopic fine structure in proteins

Unveiling the intricacy of gapmer oligonucleotides through advanced tandem mass spectrometry approaches and scan accumulation for 2DMS

Antisense oligonucleotides (ASOs) are crucial for biological applications as they bind to complementary RNA sequences, modulating protein expression. ASOs undergo synthetic modifications like phosphorothioate (PS) backbone and locked nucleic acid (LNA) to enhance stability and specificity. Tandem mass spectrometry (MS) techniques were employed to study gapmer ASOs, which feature a DNA chain within RNA segments at both termini, revealing enhanced cleavages with ultraviolet photodissociation (UVPD) and complementary fragment ions from collision-induced dissociation (CID) and electron detachment dissociation (EDD). 2DMS, a data-independent analysis technique, allowed for comprehensive coverage and identification of shared fragments across multiple precursor ions. EDD fragmentation efficiency correlated with precursor ion charge states, with higher charges facilitating dissociation due to intramolecular repulsions. An electron energy of 22.8 eV enabled electron capture and radical-based cleavage. Accumulating multiple scans and generating average spectra improved signal intensity, aided by denoising algorithms. Data analysis utilised a custom Python script capable of handling modifications and generating unique mass lists.

High-Definition Ion Mobility/Mass Spectrometry with Structural Isotopic Shifts for Nominally Isobaric Isotopologues

We had reported the isotopic envelopes in differential IMS (FAIMS) separations depending on the ion structure. However, this new approach to distinguish isomers was constrained by the unit-mass resolution commingling all nominally isobaric isotopologues. Here, we directly couple high-definition FAIMS to ultrahigh-resolution (Orbitrap) MS and employ the resulting platform to explore the FAIMS spectra for isotopic fine structure. The peak shifts therein for isotopologues of halogenated anilines with ¹⁵N and ¹³C (split by 6 mDa) in N₂/CO₂ buffers dramatically differ, more than for the ¹³C, ³⁷Cl, or ⁸¹Br species apart by 1 or 2 Da. The shifts in FAIMS space upon different elemental isotopic substitutions are orthogonal mutually and to the underlying separations, forming fingerprint multidimensional matrices and 3-D trajectories across gas compositions that redundantly delineate all isomers considered. The interlocking instrumental and methodological upgrades in this work take the structural isotopic shift approach to the next level.

Machine learning approach for the prediction of the number of sulphur atoms in peptides using the theoretical aggregated isotope distribution

RATIONALE

The observed isotope distribution is an important attribute for the identification of peptides and proteins in mass spectrometry-based proteomics. Sulphur atoms have a very distinctive elemental isotope definition, and therefore, the presence of sulphur atoms has a substantial effect on the isotope distribution of biomolecules. Hence, knowledge of the number of sulphur atoms can improve the identification of peptides and proteins.

METHODS

In this paper, we conducted a theoretical investigation on the isotope properties of sulphur-containing peptides. We proposed a gradient boosting approach to predict the number of sulphur atoms based on the aggregated isotope distribution. We compared prediction accuracy and assessed the predictive power of the features using the mass and isotope abundance information from the first three, five and eight aggregated isotope peaks.

RESULTS

Mass features alone are not sufficient to accurately predict the number of sulphur atoms. However, we reach near-perfect prediction when we include isotope abundance features. The abundance ratios of the eighth and the seventh, the fifth and the fourth, and the third and the second aggregated isotope peaks are the most important abundance features. The mass difference between the eighth, the fifth or the third aggregated isotope peaks and the monoisotopic peak are the most predictive mass features.

CONCLUSIONS

Based on the validation analysis it can be concluded that the prediction of the number of sulphur atoms based on the isotope profile fails, because the isotope ratios are not measured accurately. These results indicate that it is valuable for future instrument developments to focus more on improving spectral accuracy to measure peak intensities of higher-order isotope peaks more accurately.

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.

Fine Structure in Isotopic Peak Distributions Measured Using Fourier Transform Ion Cyclotron Resonance Mass Spectrometry: A Comparison between an Infinity ICR Cell and a Dynamically Harmonized ICR Cell

The fine structure of isotopic peak distributions of glutathione in mass spectra is measured using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) at 12 and 15 T magnetic field, with an infinity cell and a dynamically harmonized cell (DHC) respectively. The resolved peaks in the fine structure of glutathione consist of ²H, ¹³C, ¹⁵N, ¹⁷O, ¹⁸O, ³³S, ³⁴S, ³⁶S, and combinations of them. The positions of the measured fine structure peaks agree with the simulated isotopic distributions with the mass error less than 250 ppb in broadband mode for the infinity cell and no more than 125 ppb with the DHC after internal calibration. The 15 T FT-ICR MS with DHC cell also resolved around 30 isotopic peaks in broadband with a resolving power (RP) of 2 M. In narrowband (m/z 307-313), our current highest RP of 13.9 M in magnitude mode was observed with a 36 s transient length by the 15 T FT-ICR MS with the DHC and 2ω detection on the 15 T offers slightly higher RP (14.8 M) in only 18 s. For the 12 T FT-ICR MS with the infinity cell, the highest RP achieved was 15.6 M in magnitude mode with a transient length of 45 s. Peak decay was observed for low abundance peaks, which could be due to the suppression effects from the most abundant peak, as result of ion cloud Coulombic interactions (space-charge).

Characterization of the Time-Domain Isotopic Beat Patterns of Monoclonal Antibodies in Fourier Transform Mass Spectrometry

The time-domain transients in the Fourier transform mass spectrometry (FTMS) analysis of monoclonal antibodies (mAbs) are known to exhibit characteristic isotopic beat patterns. These patterns are defined by the isotopic distributions of all gaseous mAb ions present in the FTMS mass analyzer, originating from single or multiple charge states, and from single or multiple proteoforms. For an isolated charge state of a single proteoform, the mAb isotopic beat pattern resembles narrow splashes of signal amplitude (beats), spaced periodically in the time-domain transient, with broad (often exceeding 1 s) "valleys" between them. Here, we reinforce the importance of isotopic beat patterns for the accurate interpretation and presentation of FTMS data in the analysis of mAbs and other large biopolymers. An updated, mAb-grade version of the transient-mediated FTMS data simulation and visualization tool, FTMS Simulator is introduced and benchmarked. We then apply this tool to evaluate the charge-state dependent characteristics of isotopic beats in mAbs analyses with modern models of Orbitrap and ion cyclotron resonance (ICR) FTMS instruments, including detection of higher-order harmonics. We demonstrate the impact of the isotopic beat patterns on the analytical characteristics of the resulting mass spectra of individual and overlapping mAb proteoforms. The results reported here detail highly nonlinear dependences of resolution and signal-to-noise ratio on the time-domain transient period, absorption or magnitude mode spectra representation, and apodization functions. The provided description and the demonstrated ability to routinely conduct accurate simulations of FTMS data for large biopolymers should aid the end-users of Orbitrap and ICR FTMS instruments in the analysis of mAbs and other biopolymers, including viruses.

Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution

RATIONALE

Identification of peptides and proteins is a challenging task in mass spectrometry-based proteomics. Knowledge of the number of sulfur atoms can improve the identification of peptides and proteins.

METHODS

In this article, we propose a method for the prediction of S-atoms based on the aggregated isotope distribution. The Mahalanobis distance is used as dissimilarity measure to compare mass- and intensity-based features from the observed and theoretical isotope distributions.

RESULTS

The relative abundance of the second and the third aggregated isotopic variants (as compared to the monoisotopic one) and the mass difference between the second and third aggregated isotopic variants are the most important features to predict the number of S-atoms.

CONCLUSIONS

The mass and intensity accuracies of the observed aggregated isotopic variants are insufficient to accurately predict the number of atoms. However, using a limited set of predictions for a peptide, rather than predicting a single number of S-atoms, has a reasonably high prediction accuracy.

Dissociation of Biomolecules by an Intense Low-Energy Electron Beam in a High Sensitivity Time-of-Flight Mass Spectrometer

We report the progress on an electron-activated dissociation (EAD) device coupled to a quadrupole TOF mass spectrometer (QqTOF MS) developed in our group. This device features a new electron beam optics design allowing up to 100 times stronger electron currents in the reaction cell. The electron beam current reached the space-charge limit of 0.5 μA at near-zero electron kinetic energies. These advances enable fast and efficient dissociation of various analytes ranging from singly charged small molecules to multiply protonated proteins. Tunable electron energy provides access to different fragmentation regimes: ECD, hot ECD, and electron-impact excitation of ions from organics (EIEIO). The efficiency of the device was tested on a wide range of precursor charge states. The EAD device was installed in a QqTOF MS employing a novel trap-and-release strategy facilitating spatial mass focusing of ions at the center of the TOF accelerator. This technique increased the sensitivity 6-10 times and allows for the first time comprehensive structural lipidomics on an LC time scale. The system was evaluated for other compound classes such as intact proteins and glycopeptides. Application of hot ECD for the analysis of glycopeptides resulted in rich fragmentation with predominantly peptide backbone fragments; however, glycan fragments attributed to the ECD process were also observed. A standard small protein ubiquitin (8.6 kDa) was sequenced with 90% cleavage coverage at spectrum accumulation times of 100 ms and 98% at 800 ms. Comparable cleavage coverage for a medium-size protein (carbonic anhydrase: 29 kDa) could be achieved, albeit with longer accumulation times.

What's in a mass?

This short essay pretends to make the reader reflect on the concept of biological mass and on the added value that the determination of this molecular property of a protein brings to the interpretation of evolutionary and translational snake venomics research. Starting from the premise that the amino acid sequence is the most distinctive primary molecular characteristics of any protein, the thesis underlying the first part of this essay is that the isotopic distribution of a protein's molecular mass serves to unambiguously differentiate it from any other of an organism's proteome. In the second part of the essay, we discuss examples of collaborative projects among our laboratories, where mass profiling of snake venom PLA2 across conspecific populations played a key role revealing dispersal routes that determined the current phylogeographic pattern of the species.

Novel Insights into Quantitative Proteomics from an Innovative Bottom-Up Simple Light Isotope Metabolic (bSLIM) Labeling Data Processing Strategy

Simple light isotope metabolic labeling (SLIM labeling) is an innovative method to quantify variations in the proteome based on an original in vivo labeling strategy. Heterotrophic cells grown in U-[12C] as the sole source of carbon synthesize U-[12C]-amino acids, which are incorporated into proteins, giving rise to U-[12C]-proteins. This results in a large increase in the intensity of the monoisotope ion of peptides and proteins, thus allowing higher identification scores and protein sequence coverage in mass spectrometry experiments. This method, initially developed for signal processing and quantification of the incorporation rate of 12C into peptides, was based on a multistep process that was difficult to implement for many laboratories. To overcome these limitations, we developed a new theoretical background to analyze bottom-up proteomics data using SLIM-labeling (bSLIM) and established simple procedures based on open-source software, using dedicated OpenMS modules, and embedded R scripts to process the bSLIM experimental data. These new tools allow computation of both the 12C abundance in peptides to follow the kinetics of protein labeling and the molar fraction of unlabeled and 12C-labeled peptides in multiplexing experiments to determine the relative abundance of proteins extracted under different biological conditions. They also make it possible to consider incomplete 12C labeling, such as that observed in cells with nutritional requirements for nonlabeled amino acids. These tools were validated on an experimental dataset produced using various yeast strains of Saccharomyces cerevisiae and growth conditions. The workflows are built on the implementation of appropriate calculation modules in a KNIME working environment. These new integrated tools provide a convenient framework for the wider use of the SLIM-labeling strategy.

An Enhanced Isotopic Fine Structure Method for Exact Mass Analysis in Discovery Metabolomics: FIA-CASI-FTMS

A major bottleneck in metabolomics is the annotation of a molecular formula as a first step to a tentative structure assignment of known and unknown metabolites. The direct observation of an isotopic fine structure (IFS) provides the ability to confidently assign an unknown's molecular formula out of a complex mass spectrum. However, the majority of mass spectrometers deployed for metabolomic studies do not have sufficient resolving power and high-fidelity isotope ratios in the mass range of interest to determine molecular formulas from IFS data. To increase the number of unknowns for which IFS can be determined, a segmented "boxcar" approach using a selection quadrupole as a broadband mass filter is used. In this longer, enhanced dynamic range discovery experiment, selected ions in a specific mass range are accumulated before detection by the analyzer cell. The mass filter window is then moved across the entire mass range resulting in a composite mass spectrum covering the m/z range of interest for phenomics research. The effectiveness of the FIA-CASI-FTMS workflow utilizing IFS for molecular formula assignment is realized with the implementation of the dynamically harmonized cell, which distinguishes the approach from other segmented workflows because of the analytical properties of the cell. The discovery approach was applied to a human plasma sample to confidently assign an unknown molecular formula as part of the quest to illuminate its metabolic "dark matter" via high-fidelity IFS ratio determinations. The FIA-CASI-FTMS workflow showed a 2.6-fold increase in both matching with the Human Metabolome Database and an increase in the IFS pattern.

Isotope Depletion Mass Spectrometry (ID-MS) for Accurate Mass Determination and Improved Top-Down Sequence Coverage of Intact Proteins

Top-down mass spectrometry (MS) is an increasingly important technique for protein characterization. However, in many biological MS experiments, the practicality of applying top-down methodologies is still limited at higher molecular mass. In large part, this is due to the detrimental effect resulting from the partitioning of the mass spectral signal into an increasing number of isotopic peaks as molecular mass increases. Reducing the isotopologue distribution of proteins via depletion of heavy stable isotopes was first reported over 20 years ago (Marshall, A. G.; Senko, M. W.; Li, W.; Li, M.; Dillon, S., Guan, S.; Logan, T. M.. Protein Molecular Mass to 1 Da by ¹³C, ¹⁵N Double-Depletion and FT-ICR Mass Spectrometry. J. Am. Chem. Soc. 1997, 119, 433-434.) and has been demonstrated for several small proteins. Here we extend this approach, introducing a new highly efficient method for the production of recombinant proteins depleted in ¹³C and ¹⁵N and demonstrating its advantages for top-down analysis of larger proteins (up to ∼50 kDa). FT-ICR MS of isotopically depleted proteins reveals dramatically reduced isotope distributions with monoisotopic signal observed up to 50 kDa. In top-down fragmentation experiments, the reduced spectral complexity alleviates fragment-ion signal overlap, the presence of monoisotopic signals allows assignment with higher mass accuracy, and the dramatic increase in signal-to-noise ratio (up to 7-fold) permits vastly reduced acquisition times. These compounding benefits allow the assignment of ∼3-fold more fragment ions than comparable analyses of proteins with natural isotopic abundances. Finally, we demonstrate greatly increased sequence coverage in time-limited top-down experiments-highlighting advantages for top-down LC-MS/MS workflows and top-down proteomics.

Three-Dimensional Imaging with Infrared Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry

Mass spectrometry imaging as a field has pushed its frontiers to three dimensions. Most three-dimensional mass spectrometry imaging (3D MSI) approaches require serial sectioning that results in a loss of biological information between analyzed slices and difficulty in reconstruction of 3D images. In this contribution, infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) was demonstrated to be applicable for 3D MSI that does not require sectioning because IR laser ablates material on a micrometer scale. A commercially available over-the-counter pharmaceutical was used as a model to demonstrate the feasibility of IR-MALDESI for 3D MSI. Depth resolution (i.e., z-resolution) as a function of laser energy levels and density of ablated material was investigated. The best achievable depth resolution from a pill was 2.3 μm at 0.3 mJ/pulse. 2D and 3D MSI were performed on the tablet to show the distribution of pill-specific molecules. A 3D MSI analysis on a region of interest of 15 × 15 voxels across 50 layers was performed. Our results demonstrate that IR-MALDESI is feasible with 3D MSI on a pill, and future work will be focused on analyses of biological tissues.

A feasible strategy based on isotopic fine structures to enhance the reliability of metabolite identification by Fourier transform ion cyclotron resonance mass spectrometry

RATIONALE

In the process of the identification of unknown metabolites, the most important thing is to determine their real chemical formulae according to the accurate masses which are determined by high-resolution mass spectrometry. However, high mass accuracy alone is not enough to exclude false candidates. Use of isotopic fine structures (IFSs) derived from Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) as a single further constraint could decisively determine the molecular formulae for unknown metabolites.

METHODS

Gastrodin, an active constituent from Gastrodia elata Bl., which can penetrate through the blood-brain barrier and rapidly decompose to p-hydroxybenzyl alcohol in the brain, was selected as a model drug. The accurate masses, possible chemical formulae and IFSs of its metabolites in rat plasma were acquired using FT-ICR MS.

RESULTS

Besides gastrodin, a total of eight metabolites including two phase I and six phase II metabolites were detected. Their chemical formulae were decisively determined by IFSs. Furthermore, their chemical structures were identified by comparing their fragment ions with those of gastrodin. Results indicated the metabolic pathways of gastrodin in rats including deglycosylation, oxidation, glucuronidation, sulfate conjugation and glycine conjugation.

CONCLUSIONS

It is demonstrated that IFSs are effective in unambiguous determination of chemical formulae of metabolites. It could be used as a feasible strategy to enhance the reliability of metabolite identification in drug metabolism studies.

Routine Absorption Mode FTMS Data Display with an Ethoxylated Anionic Detergent as a Dual-Role (Mass and Phase) Calibrant

Absorption mode display of Fourier transform mass spectrometry (FTMS) data is known to improve both peak shape and resolution. Most FTMS data, however, are shown in magnitude mode due to the lack of a routine for determining the phase of ions that are necessary for absorption mode display. Despite the recent development of phase calibration methods, the use of absorption mode processing as a routine has been inhibited by the lack of a good phase calibration standard, particularly a standard that can be used as both a mass and a phase calibrant. A dual-role calibrant will enable the consolidation of mass and phase calibration into a single step making phase calibration as accessible as mass calibration without any incremental increase in complexity in the calibration procedure. We tested a series of detergents and found Triton QS-15, an anionic detergent, suitable as a dual-role calibrant. Additionally, Triton QS-15 produces both positive and negative ion series and thus can be used as a calibrant in both ionization modes. The establishment of a phase calibration routine helps to enable the application of FTMS in areas that require extreme mass resolution. One of the areas is the separation of the fine isotopic peaks of molecules with a large molecular mass (e.g., > 500 u). For data acquired using an ion cyclotron resonance instrument with a small magnet (e.g., 7 Tesla), there may not be adequate mass resolution to establish a useful isotopic fine structure if the data is displayed in the historical magnitude mode. A mere switch to the absorption mode display makes the isotopic fine structure (IFS) readily available for molecular formula determination. Graphical Abstract x.

A Simple Light Isotope Metabolic Labeling (SLIM-labeling) Strategy: A Powerful Tool to Address the Dynamics of Proteome Variations In Vivo

Many quantitative proteomics strategies rely on in vivo metabolic incorporation of amino acids with modified stable isotope profiles into proteins. These methods give rise to multiple ions for each peptide, with possible distortion of the isotopolog distribution, making the overall analytical process complex. We validated an alternative strategy, simple light isotope metabolic labeling (SLIM-labeling), which alleviates many of these problems. SLIM-labeling is based on the in vivo reduction of the isotopic composition of proteins using metabolic precursors with a unique light isotope composition to label all amino acids. This brings a new dimension to in-depth, high resolution MS-based quantitative proteomics. Here, we describe a ¹²C-based SLIM-labeling strategy using U-[¹²C]-glucose as the metabolic precursor of all amino acids in the pathogenic yeast Candida albicans Monoisotopic ion intensity increased exponentially following ¹²C enrichment, substantially improving peptide identification scores and protein sequence coverage in bottom-up analyses. Multiplexing samples of ¹²C composition varying from natural abundance (98.93%) to 100% makes it possible to address relative quantification issues, keeping all the critical information for each peptide within a single isotopolog cluster. We applied this method to measure, for the first time, protein turnover at the proteome scale in Candida albicans and its modulation by inhibitors of the proteasome and vacuolar protein degradation systems.

Polarity switching mass spectrometry imaging of healthy and cancerous hen ovarian tissue sections by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI)

Mass spectrometry imaging (MSI) is a rapidly evolving field for monitoring the spatial distribution and abundance of analytes in biological tissue sections. It allows for direct and simultaneous analysis of hundreds of different compounds in a label-free manner. In order to obtain a comprehensive metabolite and lipid data, a polarity switching MSI method using infrared matrix assisted laser desorption electrospray ionization (IR-MALDESI) was developed and optimized where the electrospray polarity was alternated from one voxel to the next. Healthy and cancerous ovarian hen tissue sections were analyzed using this method. Distribution and relative abundance of different metabolites and lipids within each tissue section were discerned, and differences between the two were revealed. Additionally, the utility of using mass spectrometry concepts such as spectral accuracy and sulfur counting for confident identification of analytes in an untargeted method are discussed.

High-throughput detection of antioxidants in mulberry fruit using correlations between high-resolution mass and activity profiles of chromatographic fractions

BACKGROUND

Plant extracts contain a huge variety of pharmacologically active substances. Conventionally, various chromatographic methods must be applied several times to purify functional compounds to measure their functional activity. However, conventional purification methods are time-consuming and expensive due to the laborious purification process. Recently, a high-throughput discovery method that replaces such time-consuming purification processes was introduced; this method uses 15 T ultra-high-resolution Fourier transform ion cyclotron resonance mass spectrometry (15 T FT-ICR MS) and a high-throughput screening method. This 15 T FT-ICR MS provides unparalleled resolution and sub-ppm accuracy in mass measurements, while simultaneously detecting multiple compounds without separation. The high-throughput, simultaneous multi-component discovery method known as Scaling of Correlations between Activity and Mass Profiles (SCAMP) was used to detect functional compounds in a plant extract. We validated the performance of SCAMP using 33 fractions from antioxidant-rich mulberry ethyl acetate extract and known standard antioxidants.

RESULTS

The mulberry fruit was first separated into 33 fractions by LC and analyzed using high-resolution mass spectrometry. The antioxidative strength of the 33 fractions and standard antioxidants was measured. To validate the efficiency of this antioxidant discovery method, correlations between the antioxidation activity profile and changes in mass intensity of components within the 33 fractions were calculated to provide relative scores for the antioxidant candidate list. Enrichment curves and area under the curve (AUC) values were then calculated to compare the performance of the methods. Using this improved scoring method, five strong antioxidants, chlorogenic acid (14.2 ng), dihydoxy quercetin (46.2 ng), rutin (154.0 ng), quercetin (71.7 ng) and luteolin (3.5 ng) in 2 kg mulberry fruit, were found within the top 20 candidates.

CONCLUSIONS

We calculated AUCs in order to compare scoring methods quantitatively. Scoring systems were compared and calculated AUCs, where the AUCs for new scoring systems (0.98 and 0.99) were higher than the previously used correlation coefficient (AUC = 0.89). Using the new scoring algorithms, we successfully enriched thirteen unknown strong antioxidant candidates in addition to known antioxidants, methyl syringin and naringenin (3.5 ng) in mulberry extract. Targeted purification of these unknown candidates will significantly reduce purification time and labor.

A timeline of stable isotopes and mass spectrometry in the life sciences

This review retraces the role of stable isotopes and mass spectrometry in the life sciences. The timeline is divided into four segments covering the years 1920-1950, 1950-1980, 1980-2000, and 2000 until today. For each period methodic progress and typical applications are discussed. Application of stable isotopes is driven by improvements of mass spectrometry, chromatography, and related fields in sensitivity, mass accuracy, structural specificity, complex sample handling ability, data output, and data evaluation. We currently experience the vision of omics-type analyses, that is, the comprehensive identification and quantification of a complete compound class within one or a few analytical runs. This development is driven by stable isotopes without competition by radioisotopes. In metabolic studies as classic field of isotopic tracer experiments, stable isotopes and radioisotopes were competing solutions, with stable isotopes as the long-term junior partner. Since the 1990s the number of metabolic studies with radioisotopes decreases, whereas stable isotope studies retain their slow but stable upward tendency. Unique fields of stable isotopes are metabolic tests in newborns, metabolic experiments in healthy controls, newborn screening for inborn errors, quantification of drugs and drug metabolites in doping control, natural isotope fractionation in geology, ecology, food authentication, or doping control, and more recently the field of quantitative omics-type analyses. There, cells or whole organisms are systematically labeled with stable isotopes to study proteomic differences or specific responses to stimuli or genetic manipulation. The duo of stable isotopes and mass spectrometry will probably continue to grow in the life sciences, since it delivers reference-quality quantitative data with molecular specificity, often combined with informative isotope effects. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:58-85, 2017.

Ion Mobility Separation of Peptide Isotopomers

Differential or field asymmetric waveform ion mobility spectrometry (FAIMS) operating at high electric fields fully resolves isotopic isomers for a peptide with labeled residues. The naturally present isotopes, alone and together with targeted labels, also cause spectral shifts that approximately add for multiple heavy atoms. Separation qualitatively depends on the gas composition. These findings may enable novel strategies in proteomic and metabolomic analyses using stable isotope labeling.

Amyloid Hydrogen Bonding Polymorphism Evaluated by (15)N{(17)O}REAPDOR Solid-State NMR and Ultra-High Resolution Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

A combined approach, using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) and solid-state NMR (Nuclear Magnetic Resonance), shows a high degree of polymorphism exhibited by Aβ species in forming hydrogen-bonded networks. Two Alzheimer's Aβ peptides, Ac-Aβ(16-22)-NH2 and Aβ(11-25), selectively labeled with (17)O and (15)N at specific amino acid residues were investigated. The total amount of peptides labeled with (17)O as measured by FTICR-MS enabled the interpretation of dephasing observed in (15)N{(17)O}REAPDOR solid-state NMR experiments. Specifically, about one-third of the Aβ peptides were found to be involved in the formation of a specific >C═(17)O···H-(15)N hydrogen bond with their neighbor peptide molecules, and we hypothesize that the rest of the molecules undergo ± n off-registry shifts in their hydrogen bonding networks.

Direct Analysis in Real Time (DART) of an Organothiophosphate at Ultrahigh Resolution by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry and Tandem Mass Spectrometry

Direct analysis in real time (DART) is a recently developed ambient ionization technique for mass spectrometry to enable rapid and sensitive analyses with little or no sample preparation. After swab-based field sampling, the organothiophosphate malathion was analyzed using DART-Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry (MS) and tandem mass spectrometry (MS/MS). Mass resolution was documented to be over 800,000 in full-scan MS mode and over 1,000,000 for an MS/MS product ion produced by collision-induced dissociation of the protonated analyte. Mass measurement accuracy below 1 ppm was obtained for all DART-generated ions that belonged to the test compound in the mass spectra acquired using only external mass calibration. This high mass measurement accuracy, achievable at present only through FTMS, was required for unequivocal identification of the corresponding molecular formulae.

Improved ion optics for introduction of ions into a 9.4-T Fourier transform ion cyclotron resonance mass spectrometer

Enhancements to the ion source and transfer optics of our 9.4 T Fourier transform ion cyclotron resonance (ICR) mass spectrometer have resulted in improved ion transmission efficiency for more sensitive mass measurement of complex mixtures at the MS and MS/MS levels. The tube lens/skimmer has been replaced by a dual ion funnel and the following octopole by a quadrupole for reduced ion cloud radial expansion before transmission into a mass-selective quadrupole. The number of ions that reach the ICR cell is increased by an order of magnitude for the funnel/quadrupole relative to the tube lens/skimmer/octopole.

Mass spectral peak distortion due to Fourier transform signal processing

Distortions of peaks can occur when one uses the standard method of signal processing of data from the Orbitrap and other FT-based methods of mass spectrometry. These distortions arise because the standard method of signal processing is not a linear process. If one adds two or more functions, such as time-dependent signals from a Fourier transform mass spectrometer and performs a linear operation on the sum, the result is the same as if the operation was performed on separate functions and the results added. If this relationship is not valid, the operation is non-linear and can produce unexpected and/or distorted results. Although the Fourier transform itself is a linear operator, the standard algorithm for processing spectra in Fourier transform-based methods include non-linear mathematical operators such that spectra processed by the standard algorithm may become distorted. The most serious consequence is that apparent abundances of the peaks in the spectrum may be incorrect. In light of these considerations, we performed theoretical modeling studies to illustrate several distortion effects that can be observed, including abundance distortions. In addition, we discuss experimental systems where these effects may manifest, including suggested systems for study that should demonstrate these peak distortions. Finally, we point to several examples in the literature where peak distortions may be rationalized by the phenomena presented here.

Twelve million resolving power on 4.7 T Fourier transform ion cyclotron resonance instrument with dynamically harmonized cell--observation of fine structure in peptide mass spectra

Resolving power of about 12,000 000 at m/z 675 has been achieved on low field homogeneity 4.7 T magnet using a dynamically harmonized Fourier transform ion cyclotron resonance (FT ICR) cell. Mass spectra of the fine structure of the isotopic distribution of a peptide were obtained and strong discrimination of small intensity peaks was observed in case of resonance excitation of the ions of the whole isotopic cluster to the same cyclotron radius. The absence of some peaks from the mass spectra of the fine structure was explained basing on results of computer simulations showing strong ion cloud interactions, which cause the coalescence of peaks with m/z close to that of the highest magnitude peak. The way to prevent peak discrimination is to excite ion clouds of different m/z to different cyclotron radii, which was demonstrated and investigated both experimentally and by computer simulations.

Integrative biological analysis for neuropsychopharmacology

Although advances in psychotherapy have been made in recent years, drug discovery for brain diseases such as schizophrenia and mood disorders has stagnated. The need for new biomarkers and validated therapeutic targets in the field of neuropsychopharmacology is widely unmet. The brain is the most complex part of human anatomy from the standpoint of number and types of cells, their interconnections, and circuitry. To better meet patient needs, improved methods to approach brain studies by understanding functional networks that interact with the genome are being developed. The integrated biological approaches--proteomics, transcriptomics, metabolomics, and glycomics--have a strong record in several areas of biomedicine, including neurochemistry and neuro-oncology. Published applications of an integrated approach to projects of neurological, psychiatric, and pharmacological natures are still few but show promise to provide deep biological knowledge derived from cells, animal models, and clinical materials. Future studies that yield insights based on integrated analyses promise to deliver new therapeutic targets and biomarkers for personalized medicine.

Resolving isotopic fine structure to detect and quantify natural abundance- and hydrogen/deuterium exchange-derived isotopomers

Hydrogen/deuterium exchange (HDX) mass spectrometry (MS) is used for analyzing protein dynamics, protein folding/unfolding, and molecular interactions. Until this study, HDX MS experiments employed mass spectral resolving powers that afforded only one peak per nominal mass in a given peptide's isotope distribution, and HDX MS data analysis methods were developed accordingly. A level of complexity that is inherent to HDX MS remained unaddressed, namely, various combinations of natural abundance heavy isotopes and exchanged deuterium shared the same nominal mass and overlapped at previous resolving powers. For example, an A + 2 peak is comprised of (among other isotopomers) a two-(2)H-exchanged/zero-(13)C isotopomer, a one-(2)H-exchanged/one-(13)C isotopomer, and a zero-(2)H-exchanged/two-(13)C isotopomer. Notably, such isotopomers differ slightly in mass as a result of the ∼3 mDa mass defect between (2)H and (13)C atoms. Previous HDX MS methods did not resolve these isotopomers, requiring a natural-abundance-only (before HDX or "time zero") spectrum and data processing to remove its contribution. It is demonstrated here that high-resolution mass spectrometry can be used to detect isotopic fine structure, such as in the A + 2 profile example above, deconvolving the isotopomer species resulting from deuterium incorporation. Resolving isotopic fine structure during HDX MS therefore permits direct monitoring of HDX, which can be calculated as the sum of the fractional peak magnitudes of the deuterium-exchanged isotopomers. This obviates both the need for a time zero spectrum as well as data processing to account for natural abundance heavy isotopes, saving instrument and analysis time.

Elemental composition validation from stored waveform inverse Fourier transform (SWIFT) isolation FT-ICR MS isotopic fine structure

Elemental composition assignment confidence in mass spectrometry is typically assessed by monoisotopic mass accuracy. For a given mass accuracy, resolution and detection of other isotopologues can further narrow the number of possible elemental compositions. However, such measurements require ultrahigh resolving power and high dynamic range, particularly for compounds containing low numbers of nitrogen and oxygen (both (15)N and (18)O occur at less than 0.4% natural abundance). Here, we demonstrate validation of molecular formula assignment from isotopic fine structure, based on ultrahigh resolution broadband Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Dynamic range is enhanced by external quadrupole and internal stored waveform inverse Fourier transform (SWIFT) isolation to facilitate detection of low abundance heavy atom isotopologues.

Integration of proteomics, bioinformatics, and systems biology in traumatic brain injury biomarker discovery

Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high-throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics, and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform, and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics, and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed.

Simultaneous molecular formula determinations of natural compounds in a plant extract using 15 T Fourier transform ion cyclotron resonance mass spectrometry

BACKGROUND

Plant extracts are a reservoir of pharmacologically active substances; however, conventional analytical methods can analyze only a small portion of an extract. Here, we report a high-throughput analytical method capable of determining most phytochemicals in a plant extract and of providing their molecular formulae from a single experiment using ultra-high-resolution electrospray ionization mass spectrometry (UHR ESI MS). UHR mass profiling was used to analyze natural compounds in a 70% ethanol ginseng extract, which was directly infused into a 15 T Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometer for less than 10 min without a separation process.

RESULTS

The UHR FT-ICR MS yielded a mass accuracy of 0.5 ppm and a mass resolving power (m/Δm) of 1,000,000-270,000 for the range m/z 290-1,100. The mass resolution was sufficient to resolve the isotopic fine structure (IFS) of many compounds in the extract. After noise removal from 1,552 peaks, 405 compounds were detected. The molecular formulae of 123 compounds, including 33 ginsenosides, were determined using the observed IFS, exact monoisotopic mass, and exact mass difference. Liquid chromatography (LC)/FT-ICR MS of the extract was performed to compare the high-throughput performance of UHR ESI FT-ICR MS. The LC/FT-ICR MS detected only 129 compounds, including 19 ginsenosides. The result showed that UHR ESI FT-ICR MS identified three times more compounds than LC/FT-ICR MS and in a relatively shorter time. The molecular formula determination by UHR FT-ICR MS was validated by LC and tandem MS analyses of three known ginsenosides.

CONCLUSIONS

UHR mass profiling of a plant extract by 15 T FT-ICR MS showed that multiple compounds were simultaneously detected and their molecular formulae were decisively determined by a single experiment with ultra-high mass resolution and mass accuracy. Simultaneous molecular determination of multiple natural products by UHR ESI FT-ICR MS would be a powerful method to profile a wide range of natural compounds.

High mass accuracy and high mass resolving power FT-ICR secondary ion mass spectrometry for biological tissue imaging

Biological tissue imaging by secondary ion mass spectrometry has seen rapid development with the commercial availability of polyatomic primary ion sources. Endogenous lipids and other small bio-molecules can now be routinely mapped on the sub-micrometer scale. Such experiments are typically performed on time-of-flight mass spectrometers for high sensitivity and high repetition rate imaging. However, such mass analyzers lack the mass resolving power to ensure separation of isobaric ions and the mass accuracy for elemental formula assignment based on exact mass measurement. We have recently reported a secondary ion mass spectrometer with the combination of a C60 primary ion gun with a Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR MS) for high mass resolving power, high mass measurement accuracy, and tandem mass spectrometry capabilities. In this work, high specificity and high sensitivity secondary ion FT-ICR MS was applied to chemical imaging of biological tissue. An entire rat brain tissue was measured with 150 μm spatial resolution (75 μm primary ion spot size) with mass resolving power (m/Δm(50%)) of 67,500 (at m/z 750) and root-mean-square measurement accuracy less than two parts-per-million for intact phospholipids, small molecules and fragments. For the first time, ultra-high mass resolving power SIMS has been demonstrated, with m/Δm(50%) > 3,000,000. Higher spatial resolution capabilities of the platform were tested at a spatial resolution of 20 μm. The results represent order of magnitude improvements in mass resolving power and mass measurement accuracy for SIMS imaging and the promise of the platform for ultra-high mass resolving power and high spatial resolution imaging.

Properties of isotope patterns and their utility for peptide identification in large-scale proteomic experiments

RATIONALE

In proteomic experiments, isotope patterns are routinely generated for all detected peptides. While this pattern is determined by peptide composition, it has not been evaluated as a parameter that can help in the process of peptide identification.

METHODS

First, we investigated how the relative isotope abundance (RIA) accuracy in proteomic data sets depends on the spectral intensity, resolution, and the number of mass spectrometry (MS) 1 scans, using an Orbitrap Velos mass spectrometer. Next, we explored the discriminatory power of isotope patterns in the context of proteome analyses of various complexities, either alone or in combination with a Mascot database search. Finally, we provide a theoretical framework for the required accuracies of both peptide mass and RIA for peptide identification.

RESULTS

We demonstrate that the RIA error obtained in routine proteome analyses is 4-5%, and that this is only modestly influenced by spectral intensity, resolution, and the number of MS1 scans. While RIA alone has no discriminatory power, in a Mascot search isotope patterns can distinguish top scoring hits from runner-up hits in 70-95% of cases. Our theoretical approach shows that RIA accuracy needs to be ~0.2% in order to uniquely identify peptides in full proteomes.

CONCLUSIONS

Our results demonstrate that isotope patterns can have discriminatory power when used in combination with a classical database search. Inclusion of this parameter in proteomic workflows may help to increase confidence in peptide identification, but in practical terms this will be limited to small proteomes.

Mass resolution and mass accuracy: how much is enough?

Accurate mass measurement requires the highest possible mass resolution, to ensure that only a single elemental composition contributes to the mass spectral peak in question. Although mass resolution is conventionally defined as the closest distinguishable separation between two peaks of equal height and width, the required mass resolving power can be ∼10× higher for equal width peaks whose peak height ratio is 100 : 1. Ergo, minimum resolving power requires specification of maximum dynamic range, and is thus 10-100× higher than the conventional definition. Mass resolving power also depends on mass-to-charge ratio. Mass accuracy depends on mass spectral signal-to-noise ratio and digital resolution. Finally, the reliability of elemental composition assignment can be improved by resolution of isotopic fine structure. Thus, the answer to the question of "how much is enough mass resolving power" requires that one first specify S/N ratio, dynamic range, digital resolution, mass-to-charge ratio, and (if available) isotopic fine structure. The highest available broadband mass resolving power and mass accuracy is from Fourier transform ion cyclotron resonance mass spectrometry. Over the past five years, FT-ICR MS mass accuracy has improved by about an order of magnitude, based on higher magnetic field strength, conditional averaging of time-domain transients, better mass calibration (spectral segmentation; inclusion of a space charge term); radially dispersed excitation; phase correction to yield absorption-mode display; and new ICR cell segmentation designs.

Absorption-mode spectra on the dynamically harmonized Fourier transform ion cyclotron resonance cell

RATIONALE

The recently designed dynamically harmonized Fourier transform ion cyclotron resonance (FT-ICR) cell creates a more harmonized electric field for the detection of the cyclotron motion of ions and prolongs the ion transient from seconds to minutes. In order to achieve its best performance, phase correction was applied in the spectra, and new advantages of the absorption-mode were revealed.

METHODS

Spectra were acquired from both simple standard and complex mixtures using either narrowband or broadband mode, and the data were processed to compare the performance of the spectra in magnitude and absorption-mode.

RESULTS

The research shows that phase correction works well with data from Nikolaev's new cell, which produces the maximum improvement in resolving power (2×), and improves the match with the theoretical intensities of the isotopic peaks. In addition, the harmonic peaks can be diagnosed immediately in the absorption-mode.

CONCLUSIONS

The manuscript demonstrates absorption-mode spectra from Nikolaev's ICR cell, which will be of interest to the community. The improved relative peak intensities and immediate identification of harmonic peaks will facilitate data interpretation.

Expanding the data depth for the analysis of complex crude oil samples by Fourier transform ion cyclotron resonance mass spectrometry using the spectral stitching method

RATIONALE

Crude oil samples are very complex mixtures of compounds and only Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) provides the ultra-high mass resolution necessary to resolve them. However, FT-ICR MS operates best when only a small amount of ions is present during each transient. This cannot be accomplished with crude oil samples without chromatography because more than 50,000 compounds can be present, with the result that species with low intensity may be suppressed and are detected either with low intensity or not at all.

METHODS

Spectral stitching was used to overcome the problems associated with suppression effects, where only short mass windows of 30 amu were scanned to reduce the amount of ions present in each individual scan. Afterwards, all the scans were co-added and the subsequent spectrum was used to calculate individual class distributions.

RESULTS

A heavy crude oil sample was analyzed using spectral stitching and this approach was compared with analysis using a broadband-method in order to illustrate the enhancement in depth of information. Although both methods took the same analysis time a seven-times increase in the number of detected species was observed when the spectral stitching method was used compared with the commonly applied broadband method in a 900 amu mass window.

CONCLUSIONS

Spectral stitching using smaller selected ion monitoring (SIM) windows for complex crude oil samples allows better class distribution to be obtained because less ion suppression is observed.

Analysis of cancer cell lipids using matrix-assisted laser desorption/ionization 15-T Fourier transform ion cyclotron resonance mass spectrometry

A combination of methodologies using the extremely high mass accuracy and resolution of 15-T Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry (MS) was introduced for the identification of intact cancer cell phospholipids. Lipids from a malignant glioma cell line were initially analyzed at a resolution of >200,000 and identified by setting the mass tolerance to ±1 mDa using matrix-assisted laser desorption/ionization (MALDI) 15-T FT-ICR MS in positive ion mode. In most cases, a database search of potential lipid candidates using the exact masses of the lipids yielded only one possible chemical composition. Extremely high mass accuracy (<0.1 ppm) was then attained by using previously identified lipids as internal standards. This, combined with an extremely high resolution (>800,000), yielded well-resolved isotopic fine structures allowing for the identification of lipids by MALDI 15-T FT-ICR MS without using tandem mass spectrometric (MS/MS) analysis. Using this method, a total of 38 unique lipids were successfully identified.

Top-down FTICR MS for the identification of fluorescent labeling efficiency and specificity of the Cu-protein azurin

Fluorescent protein labeling has been an indispensable tool in many applications of biochemical, biophysical, and cell biological research. Although detailed information about the labeling stoichiometry and exact location of the label is often not necessary, for other purposes, this information is crucial. We have studied the potential of top-down electrospray ionization (ESI)-15T Fourier transform ion cyclotron resonance (FTICR) mass spectrometry to study the degree and positioning of fluorescent labeling. For this purpose, we have labeled the Cu-protein azurin with the fluorescent label ATTO 655-N-hydroxysuccinimide(NHS)-ester and fractionated the sample using anion exchange chromatography. Subsequently, individual fractions were analyzed by ESI-15T FTICR to determine the labeling stoichiometry, followed by top-down MS fragmentation, to locate the position of the label. Results showed that, upon labeling with ATTO 655-NHS, multiple different species of either singly or doubly labeled azurin were formed. Top-down fragmentation of different species, either with or without the copper, resulted in a sequence coverage of approximately 50%. Different primary amine groups were found to be (potential) labeling sites, and Lys-122 was identified as the major labeling attachment site. In conclusion, we have demonstrated that anion exchange chromatography in combination with ultrahigh resolution 15T ESI-FTICR top-down mass spectrometry is a valuable tool for measuring fluorescent labeling efficiency and specificity.