Efficient denoising algorithms for large experimental datasets and their applications in Fourier transform ion cyclotron resonance mass spectrometry

Fellgett Revisited: On the Nature of Noise in Two-Dimensional Mass Spectrometry

Two-dimensional mass spectrometry (2DMS) is a truly data-independent acquisition technique used in the analysis of complex mixtures; however, the nature of the noise within these spectra is not well understood. In this work, 2DMS is tested for conformity with the Fellgett principle: (signal/noise) ∝ √ (no. of data points). Since 2DMS functions through the modulation of ions through a fragmentation region across many scans, the individual scans are considered data points in this experiment. Random noise was shown to be prevalent as the main source of noise in this experiment with minor systematic noise. This means that the minimum size for a 2DMS spectrum that displays a target fragment ion can be determined using a fast-2D equation detailed herein. The effects of existing denoising algorithms were also found to change the relationship between the signal-to-noise ratio and the scan numbers to be of a quasi-linear nature rather than the square root trend observed before denoising.

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.

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.

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.

In Silico Demonstration of Two-Dimensional Mass Spectrometry Using Spatially Dependent Fragmentation

Two-dimensional mass spectrometry (2DMS) allows for the analysis of complex mixtures of all kinds at high speed and resolution without data loss from isolation or biased acquisition, effectively generating tandem mass spectrometry information for all ions at once. Currently, this technique is limited to instruments utilizing an ion trap such as the Fourier transform ion cyclotron resonance or linear ion traps. To overcome this limitation, new fragmentation waveforms were used in either a temporal or spatial configuration, allowing for the application of 2DMS on a much wider array of instruments. A simulated example of a time-of-flight-based instrument is shown with the new waveforms, which allowed for the correlation of fragment ions to their respective precursors through the processing of the modulation of fragmentation intensity with a Fourier transform. This application indicated that 2D modulation and Fourier precursor/fragment intensity correlation are possible in any case where separation, either temporally or spatially, can be achieved, allowing 2DMS to be applied to almost every type of mass spectrometry instrument.

DESPERATE: A Python library for processing and denoising NMR spectra

NMR spectroscopy is an inherently insensitive technique with respect to the amount of observable signal. A common element in all NMR spectra is random thermal noise that is often characterized by a signal-to-noise ratio (SNR). SNR can be generically improved experimentally with repetitive signal averaging or during post-processing with apodization; the former of which often results in long experimental times and the latter results in the loss of spectral resolution. Denoising techniques can instead be used during post-processing to enhance SNR without compromising resolution. The most common approach relies on the singular-value decomposition (SVD) to discard noisy components of NMR data. SVD-based approaches work well, such as Cadzow and PCA, but are computationally expensive when used for large datasets that are often encountered in NMR (e.g., Carr-Purcell/Meiboom-Gill and nD datasets). Herein, we describe the implementation of a new wavelet transform (WT) routine for the fast and robust denoising of 1D and 2D NMR spectra. Several simulated and experimental datasets are denoised with both SVD-based Cadzow or PCA and WT's, and the resulting SNR enhancements and spectral uniformity are compared. WT denoising offers similar and improved denoising compared with SVD and operates faster by several orders-of-magnitude in some cases. All denoising and processing routines used in this work are included in a free and open-source Python library called DESPERATE.

Solid-state NMR methods for the characterization of bioconjugations and protein-material interactions

Protein solid-state NMR has evolved dramatically over the last two decades, with the development of new hardware and sample preparation methodologies. This technique is now ripe for complex applications, among which one can count bioconjugation, protein chemistry and functional biomaterials. In this review, we provide our account on this aspect of protein solid-state NMR.

Fully Automated Unconstrained Analysis of High-Resolution Mass Spectrometry Data with Machine Learning

Mass spectrometry (MS) is a convenient, highly sensitive, and reliable method for the analysis of complex mixtures, which is vital for materials science, life sciences fields such as metabolomics and proteomics, and mechanistic research in chemistry. Although it is one of the most powerful methods for individual compound detection, complete signal assignment in complex mixtures is still a great challenge. The unconstrained formula-generating algorithm, covering the entire spectra and revealing components, is a "dream tool" for researchers. We present the framework for efficient MS data interpretation, describing a novel approach for detailed analysis based on deisotoping performed by gradient-boosted decision trees and a neural network that generates molecular formulas from the fine isotopic structure, approaching the long-standing inverse spectral problem. The methods were successfully tested on three examples: fragment ion analysis in protein sequencing for proteomics, analysis of the natural samples for life sciences, and study of the cross-coupling catalytic system for chemistry.

Two-Dimensional Mass Spectrometry Analysis of IgG1 Antibodies

Two-dimensional mass spectrometry (2DMS) is a new, and theoretically ideal, data-independent analysis tool, which allows the characterization of a complex mixture and was used in the bottom-up analysis of IgG1 for the identification of post-translational modifications. The new peak picking algorithm allows the distinction between chimeric peaks in proteomics. In this application, the processing of 2DMS data correlates fragments to their corresponding precursors, with fragments from precursors which are <0.1 m/z at m/z 840 easily resolved, without the need for quadrupole or chromatographic separation.

Combining Ultraviolet Photodissociation and Two-Dimensional Mass Spectrometry: A Contemporary Approach for Characterizing Singly Charged Agrochemicals

Ultraviolet photodissociation (UVPD) has been shown to produce extensive structurally informative data for a variety of chemically diverse compounds. Herein, we demonstrate the performance of the 193 nm UVPD fragmentation technique on structural/moiety characterization of 14 singly charged agrochemicals. Two-dimensional mass spectrometry (2DMS) using infrared multiphoton dissociation (IRMPD) and electron-induced dissociation (EID) have previously been applied to a select range of singly charged pesticides. The ≥80% moiety coverage achieved for the majority of the species by the UVPD and 2D-UVPD methods was on par with and, in some cases, superior to the data obtained by other fragmentation techniques in previous studies, demonstrating that UVPD is viable for these types of species. A three-dimensional (3D) peak picking method was implemented to extract the data from the 2DMS spectrum, overcoming the limitations of the line extraction method used in previous studies, successfully separating precursor specific fragments with milli-Dalton accuracy. Whole spectrum internal calibration combined with 3D peak picking obtained sub-part-per-million (ppm) to part-per-billion (ppb) mass accuracies across the entire 2DMS spectrum.

Early Days of Two-Dimensional Ion Cyclotron Resonance

This contribution is an attempt to evoke the favorable atmosphere that prevailed in Lausanne around 1986 and provided the backdrop of our invention of two-dimensional ion cyclotron resonance mass spectroscopy (2D ICR-MS). To avoid a self-centered histoire d'ancien combattant, we shall try to emphasize the context: the contributions of key players within our nascent research group at UNIL and the established group of Tino Gäumann at EPFL, the role of external speakers, and the open atmosphere that was not yet polluted by bibliometrics, obsessive concern with impact factors, and top-down management of research. We shall also explain why the idea of 2D ICR-MS has been ignored for many years and still has a limited impact: different scientific cultures in the ICR and NMR communities, different concerns with fundamental vs. applied research, different status of theory and numerical simulations, different levels of commitment of instrument manufacturers, not to mention many theoretical problems that appear to be at least as challenging in ICR as in NMR.

Phase Correction for Absorption Mode Two-Dimensional Mass Spectrometry

Two-dimensional mass spectrometry (2D MS) is a tandem mass spectrometry method that relies on manipulating ion motions to correlate precursor and fragment ion signals. 2D mass spectra are obtained by performing a Fourier transform in both the precursor ion mass-to-charge ratio (m/z) dimension and the fragment ion m/z dimension. The phase of the ion signals evolves linearly in the precursor m/z dimension and quadratically in the fragment m/z dimension. This study demonstrates that phase-corrected absorption mode 2D mass spectrometry improves signal-to-noise ratios by a factor of 2 and resolving power by a factor of 2 in each dimension compared to magnitude mode. Furthermore, phase correction leads to an easier differentiation between ion signals and artefacts, and therefore easier data interpretation.

Review and prospect: NMR spectroscopy denoising and reconstruction with low-rank Hankel matrices and tensors

Nuclear magnetic resonance (NMR) spectroscopy is an important analytical tool in chemistry, biology, and life science, but it suffers from relatively low sensitivity and long acquisition time. Thus, improving the apparent signal-to-noise ratio and accelerating data acquisition became indispensable. In this review, we summarize the recent progress on low-rank Hankel matrix and tensor methods, which exploit the exponential property of free-induction decay signals, to enable effective denoising and spectra reconstruction. We also outline future developments that are likely to make NMR spectroscopy a far more powerful technique.

Accelerating Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry Imaging Using a Subspace Approach

We present a subspace method that accelerates data acquisition using Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometry imaging (MSI). For MSI of biological tissue samples, there is a finite number of heterogeneous tissue types with distinct chemical profiles that introduce redundancy in the high-dimensional measurements. Our subspace model exploits the redundancy in data measured from whole-slice tissue samples by decomposing the transient signals into linear combinations of a set of basis transients with the desired spectral resolution. This decomposition allowed us to design a strategy that acquires a subset of long transients for basis determination and short transients for the remaining pixels, drastically reducing the acquisition time. The computational reconstruction strategy can maintain high-mass-resolution and spatial-resolution MSI while providing a 10-fold improvement in throughput. We validated the capability of the subspace model using a rat sagittal brain slice imaging data set. Comprehensive evaluation of the quality of the mass spectral and ion images demonstrated that the reconstructed data produced by the reported method required only 15% of the typical acquisition time and exhibited both qualitative and quantitative consistency when compared to the original data. Our method enables either higher sample throughput or higher-resolution images at similar acquisition lengths, providing greater flexibility in obtaining FT-ICR MSI measurements.

Narrowband Modulation Two-Dimensional Mass Spectrometry and Label-Free Relative Quantification of Histone Peptides

Two-dimensional mass spectrometry (2D MS) on a Fourier transform ion cyclotron resonance (FT-ICR) mass analyzer allows for tandem mass spectrometry without requiring ion isolation. In the ICR cell, the precursor ion radii are modulated before fragmentation, which results in modulation of the abundance of their fragments. The resulting 2D mass spectrum enables a correlation between the precursor and fragment ions. In a standard broadband 2D MS, the range of precursor ion cyclotron frequencies is determined by the lowest mass-to-charge (m/z) ratio to be fragmented in the 2D MS experiment, which leads to precursor ion m/z ranges that are much wider than necessary, thereby limiting the resolving power for precursor ions and the accuracy of the correlation between the precursor and fragment ions. We present narrowband modulation 2D MS, which increases the precursor ion resolving power by reducing the precursor ion m/z range, with the aim of resolving the fragment ion patterns of overlapping isotopic distributions. In this proof-of-concept study, we compare broadband and narrowband modulation 2D mass spectra of an equimolar mixture of histone peptide isoforms. In narrowband modulation 2D MS, we were able to separate the fragment ion patterns of all ¹³C isotopes of the different histone peptide forms. We further demonstrate the potential of narrowband 2D MS for label-free quantification of peptides.

Advantages of Two-Dimensional Electron-Induced Dissociation and Infrared Multiphoton Dissociation Mass Spectrometry for the Analysis of Agrochemicals

Analysis of agrochemicals in an environmental matrix is challenging because these samples contain multiple agrochemicals, their metabolites, degradation products, and endogenous compounds. The analysis of such complex samples is achieved using chromatographic separation techniques coupled to mass spectrometry. Herein, we demonstrate a two-dimensional mass spectrometry (2DMS) technique on a 12 T Fourier transform ion cyclotron resonance mass spectrometer that can analyze a mixture of agrochemicals without using chromatography or quadrupole isolation in a single experiment. The resulting 2DMS contour plot contains abundant tandem MS information for each component in the sample and correlates product ions to their corresponding precursor ions. Two different fragmentation methods are employed, infrared multiphoton dissociation (IRMPD) and electron-induced dissociation (EID), with 2DMS to analyze the mixture of singly charged agrochemicals. The product ions of one of the agrochemicals, pirimiphos-methyl, present in the sample was used to internally calibrate the entire 2DMS spectrum, achieving sub part per million (ppm) to part per billion (ppb) mass accuracies for all species analyzed. The work described in this study will show the advantages of the 2DMS approach, by grouping species with common fragments/core structure and mutual functional groups, using precursor lines and neutral loss lines. In addition, the rich spectral information obtained from IRMPD and EID 2DMS contour plots can accurately identify and characterize agrochemicals.

Facile Determination of Phosphorylation Sites in Peptides Using Two-Dimensional Mass Spectrometry

Detection and characterization of phosphopeptides by infrared multiphoton dissociation two-dimensional mass spectrometry (IRMPD 2DMS) is shown to be particularly effective. A mixture of phosphopeptides was analyzed by 2DMS without any prior separation. 2DMS enables the data independent analysis of the mixture and the correlation of the fragments to their precursor ions. The extraction of neutral loss lines corresponding to the loss of phosphate under IRMPD fragmentation allows the selective identification of phosphopeptides. Resonance of the 10.6 μm infrared radiation with the vibrational modes of the phosphate functional group produced efficient absorption and high cleavage coverage of the phosphopeptides at much lower irradiation fluence than for nonphosphorylated peptides improving discrimination. Additionally, the localization of the phosphate group was determined.

Multivariate Curve Resolution for 2D Solid-State NMR spectra

We present a processing method, based on the multivariate curve resolution approach (MCR), to denoise 2D solid-state NMR spectra, yielding a substantial S/N ratio increase while preserving the lineshapes and relative signal intensities. These spectral features are particularly important in the quantification of silicon species, where sensitivity is limited by the low natural abundance of the ²⁹Si nuclei and by the dilution of the intrinsic protons of silica, but can be of interest also when dealing with other intermediate-to-low receptivity nuclei. This method also offers the possibility of coprocessing multiple 2D spectra that have the signals at the same frequencies but with different intensities (e.g.: as a result of a variation in the mixing time). The processing can be carried out on the time-domain data, thus preserving the possibility of applying further processing to the data. As a demonstration, we have applied Cadzow denoising on the MCR-processed FIDs, achieving a further increase in the S/N ratio and more effective denoising also on the transients at longer indirect evolution times. We have applied the combined denoising on a set of experimental data from a lysozyme-silica composite.

Phase relationships in two-dimensional mass spectrometry

Two-dimensional mass spectrometry (2D MS) is a data-independent tandem mass spectrometry technique in which precursor and fragment ion species can be correlated without the need for prior ion isolation. The behavior of phase in 2D Fourier transform mass spectrometry is investigated with respect to the calculation of phase-corrected absorption-mode 2D mass spectra. 2D MS datasets have a phase that is defined differently in each dimension. In both dimensions, the phase behavior of precursor and fragment ions is found to be different. The dependence of the phase for both precursor and fragment ion signals on various parameters (e.g., modulation frequency, shape of the fragmentation zone) is discussed. Experimental data confirms the theoretical calculations of the phase in each dimension. Understanding the phase relationships in a 2D mass spectrum is beneficial to the development of possible algorithms for phase correction, which may improve both the signal-to-noise ratio and the resolving power of peaks in 2D mass spectra.

Two-Dimensional Tandem Mass Spectrometry in a Single Scan on a Linear Quadrupole Ion Trap

A two-dimensional tandem mass spectrometry (2D MS/MS) scan has been developed for the linear quadrupole ion trap. Precursor ions are mass-selectively excited using a nonlinear ac frequency sweep at constant rf voltage, while simultaneously, all product ions of the excited precursor ions are ejected from the ion trap using a broad-band waveform. The fragmentation time of the precursor ions correlates with the precursor m/z value (the first mass dimension) and also with the ejection time of the product ions, allowing the correlation between precursor and product ions. Additionally, the second mass dimension (product ions' m/z values) is recovered through fast Fourier transform of each mass spectral peak, revealing either intentionally introduced "frequency tags" or the product ion micropacket frequencies, both of which can be converted to product ion m/z through the classical Mathieu parameters, thereby revealing a product ion mass spectrum for every precursor ion without prior isolation. We demonstrate the utility of this method for analyzing a broad range of structurally related precursor ions, including chemical warfare agent simulants, fentanyls and other opioids, amphetamines, cathinones, antihistamines, and tetracyclic antidepressants.

Denoising scheme based on singular-value decomposition for one-dimensional spectra and its application in precision storage-ring mass spectrometry

This work concerns noise reduction for one-dimensional spectra in the case that the signal is corrupted by an additive white noise. The proposed method starts with mapping the noisy spectrum to a partial circulant matrix. In virtue of singular-value decomposition of the matrix, components belonging to the signal are determined by inspecting the total variations of left singular vectors. Afterwards, a smoothed spectrum is reconstructed from the low-rank approximation of the matrix consisting of the signal components only. The denoising effect of the proposed method is shown to be highly competitive among other existing nonparametric methods, including moving average, wavelet shrinkage, and total variation. Furthermore, its applicable scenarios in precision storage-ring mass spectrometry are demonstrated to be rather diverse and appealing.

Two-dimensional mass spectrometry: new perspectives for tandem mass spectrometry

Fourier transform ion cyclotron resonance mass analysers (FT-ICR MS) can offer the highest resolutions and mass accuracies in mass spectrometry. Mass spectra acquired in an FT-ICR MS can yield accurate elemental compositions of all compounds in a complex sample. Fragmentation caused by ion-neutral, ion-electron, or ion-photon interactions leads to more detailed structural information on compounds. The most often used method to correlate compounds and their fragment ions is to isolate the precursor ions from the sample before fragmentation. Two-dimensional mass spectrometry (2D MS) offers a method to correlate precursor and fragment ions without requiring precursor isolation. 2D MS therefore enables easy access to the fragmentation patterns of all compounds from complex samples. In this article, the principles of FT-ICR MS are reviewed and the 2D MS experiment is explained. Data processing for 2D MS is detailed, and the interpretation of 2D mass spectra is described.

Application of Tandem Two-Dimensional Mass Spectrometry for Top-Down Deep Sequencing of Calmodulin

Two-dimensional mass spectrometry (2DMS) involves simultaneous acquisition of the fragmentation patterns of all the analytes in a mixture by correlating their precursor and fragment ions by modulating precursor ions systematically through a fragmentation zone. Tandem two-dimensional mass spectrometry (MS/2DMS) unites the ultra-high accuracy of Fourier transform ion cyclotron resonance (FT-ICR) MS/MS and the simultaneous data-independent fragmentation of 2DMS to achieve extensive inter-residue fragmentation of entire proteins. 2DMS was recently developed for top-down proteomics (TDP), and applied to the analysis of calmodulin (CaM), reporting a cleavage coverage of about ~23% using infrared multiphoton dissociation (IRMPD) as fragmentation technique. The goal of this work is to expand the utility of top-down protein analysis using MS/2DMS in order to extend the cleavage coverage in top-down proteomics further into the interior regions of the protein. In this case, using MS/2DMS, the cleavage coverage of CaM increased from ~23% to ~42%. Graphical Abstract Two-dimensional mass spectrometry, when applied to primary fragment ions from the source, allows deep-sequencing of the protein calmodulin.

Automatic differential analysis of NMR experiments in complex samples

Liquid state nuclear magnetic resonance (NMR) is a powerful tool for the analysis of complex mixtures of unknown molecules. This capacity has been used in many analytical approaches: metabolomics, identification of active compounds in natural extracts, and characterization of species, and such studies require the acquisition of many diverse NMR measurements on series of samples. Although acquisition can easily be performed automatically, the number of NMR experiments involved in these studies increases very rapidly, and this data avalanche requires to resort to automatic processing and analysis. We present here a program that allows the autonomous, unsupervised processing of a large corpus of 1D, 2D, and diffusion-ordered spectroscopy experiments from a series of samples acquired in different conditions. The program provides all the signal processing steps, as well as peak-picking and bucketing of 1D and 2D spectra, the program and its components are fully available. In an experiment mimicking the search of a bioactive species in a natural extract, we use it for the automatic detection of small amounts of artemisinin added to a series of plant extracts and for the generation of the spectral fingerprint of this molecule. This program called Plasmodesma is a novel tool that should be useful to decipher complex mixtures, particularly in the discovery of biologically active natural products from plants extracts but can also in drug discovery or metabolomics studies.

Can Two-Dimensional IR-ECD Mass Spectrometry Improve Peptide de Novo Sequencing?

Two-dimensional mass spectrometry (2D MS) correlates precursor and fragment ions without ion isolation in a Fourier transform ion cyclotron resonance mass spectrometer (FTICR MS) for tandem mass spectrometry. Infrared activated electron capture dissociation (IR-ECD), using a hollow cathode configuration, generally yields more information for peptide sequencing in tandem mass spectrometry than ECD (electron capture dissociation) alone. The effects of the fragmentation zone on the 2D mass spectrum are investigated as well as the structural information that can be derived from it. The enhanced structural information gathered from the 2D mass spectrum is discussed in terms of how de novo peptide sequencing can be performed with increased confidence. 2D IR-ECD MS is shown to sequence peptides, to distinguish between leucine and isoleucine residues through the production of w ions as well as between C-terminal ( b/ c) and N-terminal ( y/ z) fragments through the use of higher harmonics, and to assign and locate peptide modifications.

Bottom-Up Two-Dimensional Electron-Capture Dissociation Mass Spectrometry of Calmodulin

Two-dimensional mass spectrometry (2D MS) is a tandem mass spectrometry technique that allows data-independent fragmentation of all precursors in a mixture without previous isolation, through modulation of the ion cyclotron frequency in the ICR-cell prior to fragmentation. Its power as an analytical technique has been proven particularly for proteomics. Recently, a comparison study between 1D and 2D MS has been performed using infrared multiphoton dissociation (IRMPD) on calmodulin (CaM), highlighting the capabilities of the technique in both top-down (TDP) and bottom-up proteomics (BUP). The goal of this work is to expand this study on CaM using electron-capture dissociation (ECD) 2D MS as a single complementary BUP experiment in order to enhance the cleavage coverage of the protein under analysis. By adding the results of the BUP 2D ECD MS to the 2D IRMPD MS analysis of CaM, the total cleavage coverage increased from ~40% to ~68%. Graphical abstract ᅟ.

Nonuniform Sampling Acquisition of Two-Dimensional Fourier Transform Ion Cyclotron Resonance Mass Spectrometry for Increased Mass Resolution of Tandem Mass Spectrometry Precursor Ions

Obtaining the full MS/MS map for fragments and precursors of complex mixtures without hyphenation with chromatographic separation by a data-independent acquisition is a challenge in mass spectrometry which is solved by two-dimensional (2D) Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS). Until now 2D FTICR MS afforded only a moderate resolution for precursor ion since this resolution is limited by the number of evolution interval steps to which the number of scans, the acquisition time, and the sample consumption are proportional. An overnight acquisition is already required to reach a quadrupole mass filter-like unit mass resolution. Here, we report that 2D FTICR MS using nonuniform sampling (NUS) obtained by randomly skipping points in the first dimension corresponding to the precursor selection gives access, after data processing, to the same structural information contained in a complex mixture. The resolution increases roughly as the inverse of the NUS ratio, up to 26 times at NUS 1/32, leading to an acquisition time reduced in the same ratio compared to a classical acquisition at the same resolution. As an example, the analysis of a natural oil is presented.

Two-dimensional mass spectrometry in a linear ion trap, an in silico model

RATIONALE

Two-dimensional mass spectrometry (2D MS) is a technique that correlates precursor and product ions in a sample without requiring prior ion isolation. Until now, this technique has only been implemented on Fourier transform ion cyclotron resonance mass spectrometers. By coupling 2D MS techniques in linear ion traps (LITs) with a mass analyser with a fast duty cycle (e.g. time-of-flight), data-independent tandem mass spectrometry techniques can be compatible on a liquid chromatography (LC) or gas chromatography (GC) timescale.

METHODS

The feasibility of 2D MS in a LIT is explored using SIMION ion trajectory calculations.

RESULTS

By applying stored waveform inverse Fourier transform techniques for radial excitation on a LIT, the sizes of ion clouds were found to be modulated according to the ions' resonant frequencies in the LIT. By simulating a laser-based fragmentation at the centre of the LIT after the radius modulation step, product ion abundances were found to be modulated according to the resonant frequency of their precursor.

CONCLUSIONS

A 2D mass spectrum could be obtained using the results from the simulation. This in silico model shows the feasibility of 2D MS on a LIT. 2D MS in a LIT allows for tandem mass spectrometry without ion isolation. Copyright © 2017 John Wiley & Sons, Ltd.

Theory for spiralling ions for 2D FT-ICR and comparison with precessing magnetization vectors in 2D NMR

Two-dimensional (2D) Fourier transform ion cyclotron resonance (FT-ICR) offers an approach to mass spectrometry (MS) that pursuits similar objectives as MS/MS experiments. While the latter must focus on one ion species at a time, 2D FT ICR can examine all possible correlations due to ion fragmentation in a single experiment: correlations between precursors, charged and neutral fragments. We revisited the original 2D FT-ICR experiment that has hitherto fallen short of stimulating significant analytical applications, probably because it is technically demanding. These shortcomings can now be overcome by improved FT-ICR instrumentation and computer hard- and software. We seek to achieve a better understanding of the intricacies of the behavior of ions during a basic two-dimensional ICR sequence comprising three simple monochromatic pulses. Through simulations based on Lorentzian equations, we have mapped the ion trajectories for different pulse durations and phases.

2D FT-ICR MS of Calmodulin: A Top-Down and Bottom-Up Approach

Two-dimensional Fourier transform ion cyclotron resonance mass spectrometry (2D FT-ICR MS) allows data-independent fragmentation of all ions in a sample and correlation of fragment ions to their precursors through the modulation of precursor ion cyclotron radii prior to fragmentation. Previous results show that implementation of 2D FT-ICR MS with infrared multi-photon dissociation (IRMPD) and electron capture dissociation (ECD) has turned this method into a useful analytical tool. In this work, IRMPD tandem mass spectrometry of calmodulin (CaM) has been performed both in one-dimensional and two-dimensional FT-ICR MS using a top-down and bottom-up approach. 2D IRMPD FT-ICR MS is used to achieve extensive inter-residue bond cleavage and assignment for CaM, using its unique features for fragment identification in a less time- and sample-consuming experiment than doing the same thing using sequential MS/MS experiments. Graphical Abstract ᅟ.

Two-Dimensional Mass Spectrometry for Proteomics, a Comparative Study with Cytochrome c

Two-dimensional Fourier transform ion cyclotron resonance mass spectrometry (2D FT-ICR MS) allows the correlation between precursor and fragment ions in tandem mass spectrometry without the need to isolate the precursor ion beforehand. 2D FT-ICR MS has been optimized as a data-independent method for the structural analysis of compounds in complex samples. Data processing methods and denoising algorithms have been developed to use it as an analytical tool. In the present study, the capabilities of 2D FT-ICR MS are explored with a tryptic digest of cytochrome c with both ECD and IRMPD as fragmentation modes. The 2D mass spectra showed useful fragmentation patterns of peptides over a dynamic range of almost 400. By using a quadratic calibration, fragment ion peaks could be successfully assigned. The correlation between precursor and fragment ions in the 2D mass spectra was more accurate than in MS/MS spectra after quadrupole isolation, due to the limitations of quadrupole isolation. The use of the second dimension allowed for successful fragment assignment from precursors that were separated by only m/z 0.0156. The resulting cleavage coverage of cytochrome c almost matched data provided by high-resolution FT-ICR MS/MS analysis, but the 2D FT-ICR MS method required only one experimental scan.

Uncoiling collagen: a multidimensional mass spectrometry study

Two dimensional mass spectrometry can provide structural information on all peptide ions simultaneously from the tryptic digest of a large protein complex.

Differentiating Fragmentation Pathways of Cholesterol by Two-Dimensional Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

Two-dimensional Fourier transform ion cyclotron resonance mass spectrometry is a data-independent analytical method that records the fragmentation patterns of all the compounds in a sample. This study shows the implementation of atmospheric pressure photoionization with two-dimensional (2D) Fourier transform ion cyclotron resonance mass spectrometry. In the resulting 2D mass spectrum, the fragmentation patterns of the radical and protonated species from cholesterol are differentiated. This study shows the use of fragment ion lines, precursor ion lines, and neutral loss lines in the 2D mass spectrum to determine fragmentation mechanisms of known compounds and to gain information on unknown ion species in the spectrum. In concert with high resolution mass spectrometry, 2D Fourier transform ion cyclotron resonance mass spectrometry can be a useful tool for the structural analysis of small molecules. Graphical Abstract ᅟ.

Big Data Analytics in Healthcare

The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined.

A method detection limit for the analysis of natural organic matter via Fourier transform ion cyclotron resonance mass spectrometry

Fourier Transform Ion Cyclotron Resonance mass spectra (FT-ICR-MS) of natural organic matter are complex and consist of several thousands of peaks. The corresponding mass to charge ratios (m/z) and signal intensities result from analytes and noise. The most commonly applied way of distinguishing between analyte and noise is a fixed signal-to-noise ratio below which a detected peak is considered noise. However, this procedure is problematic and can yield ambiguous results. For example, random noise peaks can occur slightly above the signal-to-noise threshold (false positives), while peaks of low abundance analytes may occasionally fall below the fixed threshold (false negatives). Thus, cumulative results from repeated measurements of the same sample contain more peaks than a single measurement. False positive and false negative signals are difficult to distinguish, which affects the reproducibility between replicates of a sample. To target this issue, we tested the feasibility of a method detection limit (MDL) for the analysis of natural organic matter to identify peaks that can reliably be distinguished from noise by estimating the uncertainty of the noise. We performed 556 replicate analyses of a dissolved organic matter sample from the deep North Pacific on a 15 T FT-ICR-MS; each of these replicate runs consisted of 500 cumulated broadband scans. To unambiguously identify analyte peaks in the mass spectra, the sample was also run at time-consuming high-sensitivity settings. The resulting data set was used to establish and thoroughly test a MDL. The new method is easy to establish with software help, does only require the additional analysis of replicate blanks (low time increase), and can implement all steps of sample preparation. Especially when analysis time does not allow for replicate runs, major merits of the MDL are reliable removal of false positive (noise) peaks and better reproducibility, while the risk of losing analytes with low signal intensities (false negative) is comparatively low. When replicate analyses are feasible, the removal of all singly detected peaks is further recommended, as these have the highest probability of being noise peaks. We suggest that the here proposed detection limit should become routine in FT-ICR-MS data processing.