Gábor Transform-Based Signal Isolation, Rapid Deconvolution, and Quantitation of Intact Protein Ions with Mass Spectrometry

High-resolution mass spectrometry (HRMS) is a powerful technique for the characterization and quantitation of complex biological mixtures, with several applications including clinical monitoring and tissue imaging. However, these medical and pharmaceutical applications are pushing the analytical limits of modern HRMS techniques, requiring either further development in instrumentation or data processing methods. Here, we demonstrate new developments in the interactive Fourier-transform analysis for mass spectrometry (iFAMS) software including the first application of Gábor transform (GT) to protein quantitation. Newly added automation tools detect signals from minimal user input and apply thresholds for signal selection, deconvolution, and baseline correction to improve the objectivity and reproducibility of deconvolution. Additional tools were added to improve the deconvolution of highly complex or congested mass spectra and are demonstrated here for the first time. The "Gábor Slicer" enables the user to explore trends in the Gábor spectrogram with instantaneous ion mass estimates accurate to 10 Da. The charge adjuster allows for easy visual confirmation of accurate charge state assignments and quick adjustment if necessary. Deconvolution refinement utilizes a second GT of isotopically resolved data to remove common deconvolution artifacts. To assess the quality of deconvolution from iFAMS, several comparisons are made to deconvolutions using other algorithms such as UniDec and an implementation of MaxEnt in Agilent MassHunter BioConfirm. Lastly, the newly added batch processing and quantitation capabilities of iFAMS are demonstrated and compared to a common extracted ion chromatogram approach.

Label-Free Composition Analysis of Supramolecular Polymer-Nanoparticle Hydrogels by Reversed-Phase Liquid Chromatography Coupled with a Charged Aerosol Detector

Supramolecular hydrogels formed through polymer-nanoparticle interactions are promising biocompatible materials for translational medicines. This class of hydrogels exhibits shear-thinning behavior and rapid recovery of mechanical properties, providing desirable attributes for formulating sprayable and injectable therapeutics. Characterization of hydrogel composition and loading of encapsulated drugs is critical to achieving the desired rheological behavior as well as tunable in vitro and in vivo payload release kinetics. However, quantitation of hydrogel composition is challenging due to material complexity, heterogeneity, high molecular weight, and the lack of chromophores. Here, we present a label-free approach to simultaneously determine hydrogel polymeric components and encapsulated payloads by coupling a reversed phase liquid chromatographic method with a charged aerosol detector (RPLC-CAD). The hydrogel studied consists of modified hydroxypropylmethylcellulose, self-assembled PEG-b-PLA nanoparticles, and a therapeutic compound, bimatoprost. The three components were resolved and quantitated using the RPLC-CAD method with a C4 stationary phase. The method demonstrated robust performance, applicability to alternative cargos (i.e., proteins) and was suitable for composition analysis as well as for evaluating in vitro release of cargos from the hydrogel. Moreover, this method can be used to monitor polymer degradation and material stability, which can be further elucidated by coupling the RPLC method with (1) a multi-angle light scattering detector (RPLC-MALS) or (2) high resolution mass spectrometry (RPLC-MS) and a Fourier-transform based deconvolution algorithm. We envision that this analytical strategy could be generalized to characterize critical quality attributes of other classes of supramolecular hydrogels, establish structure-property relationships, and provide rational design guidance in hydrogel drug product development.

Mass spectrometry-based methods to characterize highly heterogeneous biopharmaceuticals, vaccines, and nonbiological complex drugs at the intact-mass level

The intact-mass MS measurements are becoming increasingly popular in characterization of a range of biopolymers, especially those of interest to biopharmaceutical industry. However, as the complexity of protein therapeutics and other macromolecular medicines increases, the new challenges arise, one of which is the high levels of structural heterogeneity that are frequently exhibited by such products. The very notion of the molecular mass measurement loses its clear and intuitive meaning when applied to an extremely heterogenous system that cannot be characterized by a unique mass, but instead requires that a mass distribution be considered. Furthermore, convoluted mass distributions frequently give rise to unresolved ionic signal in mass spectra, from which little-to-none meaningful information can be extracted using standard approaches that work well for homogeneous systems. However, a range of technological advances made in the last decade, such as the hyphenation of intact-mass MS measurements with front-end separations, better integration of ion mobility in MS workflows, development of an impressive arsenal of gas-phase ion chemistry tools to supplement MS methods, as well as the revival of the charge detection MS and its triumphant entry into the field of bioanalysis already made impressive contributions towards addressing the structural heterogeneity challenge. An overview of these techniques is accompanied by critical analysis of the strengths and weaknesses of different approaches, and a brief overview of their applications to specific classes of biopharmaceutical products, vaccines, and nonbiological complex drugs.

What's the defect? Using mass defects to study oligomerization of membrane proteins and peptides in nanodiscs with native mass spectrometry

Many membrane proteins form functional complexes that are either homo- or hetero-oligomeric. However, it is challenging to characterize membrane protein oligomerization in intact lipid bilayers, especially for polydisperse mixtures. Native mass spectrometry of membrane proteins and peptides inserted in lipid nanodiscs provides a unique method to study the oligomeric state distribution and lipid preferences of oligomeric assemblies. To interpret these complex spectra, we developed novel data analysis methods using macromolecular mass defect analysis. Here, we provide an overview of how mass defect analysis can be used to study oligomerization in nanodiscs, discuss potential limitations in interpretation, and explore strategies to resolve these ambiguities. Finally, we review recent work applying this technique to studying formation of antimicrobial peptide, amyloid protein, and viroporin complexes with lipid membranes.

On the Chemistry of Aqueous Ammonium Acetate Droplets during Native Electrospray Ionization Mass Spectrometry

Ammonium acetate (NH4Ac) is a widely used solvent additive in native electrospray ionization (ESI) mass spectrometry. NH4Ac can undergo proton transfer to form ammonia and acetic acid (NH4+ + Ac- → NH3 + HAc). The volatility of these products ensures that electrosprayed ions are free of undesired adducts. NH4Ac dissolution in water yields pH 7, providing "physiological" conditions. However, NH4Ac is not a buffer at pH 7 because NH4+ and Ac- are not a conjugate acid/base pair (Konermann, L. J. Am. Soc. Mass Spectrom. 2017, 28, 1827-1835.). In native ESI, it is desirable that analytes experience physiological conditions not only in bulk solution but also while they reside in ESI droplets. Little is known about the internal milieu of NH4Ac-containing ESI droplets. The current work explored the acid/base chemistry of such droplets, starting from a pH 7 analyte solution. We used a two-pronged approach involving evaporation experiments on bulk solutions under ESI-mimicking conditions, as well as molecular dynamics simulations using a newly developed algorithm that allows for proton transfer. Our results reveal that during droplet formation at the tip of the Taylor cone, electrolytically generated protons get neutralized by Ac-, making NH4+ the net charge carriers in the weakly acidic nascent droplets. During the subsequent evaporation, the droplets lose water as well as NH3 and HAc that were generated by proton transfer. NH3 departs more quickly because of its greater volatility, causing the accumulation of HAc. Together with residual Ac-, these HAc molecules form an acetate buffer that stabilizes the average droplet pH at 5.4 ± 0.1, as governed by the Henderson-Hasselbalch equation. The remarkable success of native ESI investigations in the literature implies that this pH drop by ∼1.6 units relative to the initially neutral analyte solution can be tolerated by most biomolecular analytes on the short time scale of the ESI process.

Label-Free Composition Analysis of Supramolecular Polymer - Nanoparticle Hydrogels by Reversed-Phase Liquid Chromatography Coupled with a Charged Aerosol Detector

Supramolecular hydrogels formed through polymer-nanoparticle interactions are promising biocompatible materials for translational medicines. This class of hydrogels exhibits shear-thinning behavior and rapid recovery of mechanical properties following applied stresses, providing desirable attributes for formulating sprayable and injectable therapeutics. Characterization of hydrogel composition and loading of encapsulated drugs is critical to achieving desired rheological behavior as well as tunable in vitro and in vivo payload release kinetics. However, quantitation of hydrogel compositions is challenging due to material complexity, heterogeneity, high molecular weight, and the lack of chromophores. Here, we present a label-free approach to simultaneously determine hydrogel polymeric components and encapsulated payloads by coupling a reversed phase liquid chromatographic method with a charged aerosol detector (RPLC-CAD). The hydrogel studied consists of modified hydroxypropylmethylcellulose, self-assembled PEG-b-PLA nanoparticles, and a therapeutic compound, Bimatoprost. The three components were resolved and quantitated using the RPLC-CAD method with a C4 stationary phase. The method demonstrated robust performance, applicability to alternative cargos (i.e. proteins), and was suitable for composition analysis as well as for evaluating in vitro release of cargos from the hydrogel. Moreover, this method can be used to monitor polymer degradation and material stability, which can be further elucidated by coupling the RPLC method with high resolution mass spectrometry and a Fourier-transform based deconvolution algorithm. To our knowledge, this is the first RPLC-CAD method for characterizing the critical quality attributes of supramolecular hydrogels. We envision this analytical strategy could be generalized to characterize other classes of supramolecular hydrogels, establish structure-property relationships, and provide rational design guidance in hydrogel drug product development.

Fourier-Transform Approach for Reconstructing Macromolecular Mass Defect Profiles

State-of-the-art native mass spectrometry (MS) methods have been developed for analysis of highly heterogeneous intact complexes and have provided much insight into the structure and properties of noncovalent assemblies that can be difficult to study using denatured proteins. These native MS methods can often be used to study even highly polydisperse membrane proteins embedded in detergent micelles, nanodiscs, and other membrane mimics. However, characterizing highly polydisperse native complexes which are also heterogeneous presents additional challenges for native MS. Macromolecular mass defect (MMD) analysis aims to characterize heterogeneous ion populations obfuscated by adduct polydispersity and reveal the distribution of "base" masses, and was recently implemented in the Bayesian analysis software UniDec. Here, we illustrate an alternative, orthogonal MMD analysis method implemented in the deconvolution program iFAMS, which takes advantage of Fourier transform (FT) to deconvolve low-resolution data with few user-input parameters and which can provide high quality results even for mass spectra with a signal-to-noise ratio of ∼5:1. Agreement between this method, which is based on frequency-domain data, and the mass-domain algorithm of UniDec provides strong evidence that both methods can accurately characterize highly polydisperse and heterogeneous ion populations. The FT algorithm is expected to be very useful in characterizing many types of analytes ranging from membrane proteins to polymer-conjugated proteins, branched polymers, and other large analytes, as well as for reconstructing isotope profiles for highly complex but still isotope-resolved mass spectra.

Deconvolving Native and Intact Protein Mass Spectra with UniDec

Intact protein, top-down, and native mass spectrometry (MS) generally requires the deconvolution of electrospray ionization (ESI) mass spectra to assign the mass of components from their charge state distribution. For small, well-resolved proteins, the charge can usually be assigned based on the isotope distribution. However, it can be challenging to determine charge states with larger proteins that lack isotopic resolution, in complex mass spectra with overlapping charge states, and in native spectra that show adduction. To overcome these challenges, UniDec uses Bayesian deconvolution to assign charge states and to create a zero-charge mass distribution. UniDec is fast, user-friendly, and includes a range of advanced tools to assist in intact protein, top-down, and native MS data analysis. This chapter provides a step-by-step protocol and an in-depth explanation of the UniDec algorithm, and highlights the parameters that affect the deconvolution. It also covers advanced data analysis tools, such as macromolecular mass defect analysis and tools for assigning potential PTMs and bound ligands. Overall, this chapter provides users with a deeper understanding of UniDec, which will enhance the quality of deconvolutions and allow for more intricate MS experiments.

Approaches to Heterogeneity in Native Mass Spectrometry

Native mass spectrometry (MS) is aimed at preserving and determining the native structure, composition, and stoichiometry of biomolecules and their complexes from solution after they are transferred into the gas phase. Major improvements in native MS instrumentation and experimental methods over the past few decades have led to a concomitant increase in the complexity and heterogeneity of samples that can be analyzed, including protein-ligand complexes, protein complexes with multiple coexisting stoichiometries, and membrane protein-lipid assemblies. Heterogeneous features of these biomolecular samples can be important for understanding structure and function. However, sample heterogeneity can make assignment of ion mass, charge, composition, and structure very challenging due to the overlap of tens or even hundreds of peaks in the mass spectrum. In this review, we cover data analysis, experimental, and instrumental advances and strategies aimed at solving this problem, with an in-depth discussion of theoretical and practical aspects of the use of available deconvolution algorithms and tools. We also reflect upon current challenges and provide a view of the future of this exciting field.

Increasing Collisional Activation of Protein Complexes Using Smaller Aperture Source Sampling Cones on a Synapt Q-IM-TOF Instrument with a Stepwave Source

Quadrupole ion mobility time-of-flight (Q-IM-TOF) mass spectrometers have revolutionized investigation of native biomolecular complexes. High pressures in the sources of these instruments aid transmission of protein complexes through damping of kinetic energy by collisional cooling. As adducts are removed through collisional heating (declustering), excessive collisional cooling can prevent removal of nonspecific adducts from protein ions, leading to inaccurate mass measurements, broad mass spectral peaks, and obfuscation of ligand binding. We show that reducing the source pressure using smaller aperture source sampling cones (SC) in a Waters Synapt G2-Si instrument increases protein ion heating by decreasing collisional cooling, providing a simple way to enhance removal of adducted salts from soluble proteins (GroEL 14-mer) and detergents from a transmembrane protein complex (heptameric Staphylococcus aureus α-hemolysin, αHL). These experiments are supported by ion heating and cooling simulations which demonstrate reduced collisional cooling at lower source pressures. Using these easily swapped sample cones of different apertures is a facile approach to reproducibly extend the range of activation in Synapt-type instruments.

Distinct classes of multi-subunit heterogeneity: analysis using Fourier Transform methods and native mass spectrometry

Native electrospray mass spectrometry is a powerful method for determining the native stoichiometry of many polydisperse multi-subunit biological complexes, including multi-subunit protein complexes and lipid-bound transmembrane proteins. However, when polydispersity results from incorporation of multiple copies of two or more different subunits, it can be difficult to analyze subunit stoichiometry using conventional mass spectrometry analysis methods, especially when m/z distributions for different charge states overlap in the mass spectrum. It was recently demonstrated by Marty and co-workers (K. K. Hoi, et al., Anal. Chem., 2016, 88, 6199-6204) that Fourier Transform (FT)-based methods can determine the bulk average lipid composition of protein-lipid Nanodiscs assembled with two different lipids, but a detailed statistical description of the composition of more general polydisperse two-subunit populations is still difficult to achieve. This results from the vast number of ways in which the two types of subunit can be distributed within the analyte ensemble. Here, we present a theoretical description of three common classes of heterogeneity for mixed-subunit analytes and demonstrate how to differentiate and analyze them using mass spectrometry and FT methods. First, we first describe FT-based analysis of mass spectra corresponding to simple superpositions, convolutions, and multinomial distributions for two or more different subunit types using model data sets. We then apply these principles with real samples, including mixtures of single-lipid Nanodiscs in the same solution (superposition), mixed-lipid Nanodiscs and copolymers (convolutions), and isotope distribution for ubiquitin (multinomial distribution). This classification scheme and the FT method used to study these analyte classes should be broadly useful in mass spectrometry as well as other techniques where overlapping, periodic signals arising from analyte mixtures are common.

The use of sonicated lipid vesicles for mass spectrometry of membrane protein complexes

Recent applications of mass spectrometry (MS) to study membrane protein complexes are yielding valuable insights into the binding of lipids and their structural and functional roles. To date, most native MS experiments with membrane proteins are based on detergent solubilization. Many insights into the structure and function of membrane proteins have been obtained using detergents; however, these can promote local lipid rearrangement and can cause fluctuations in the oligomeric state of protein complexes. To overcome these problems, we developed a method that does not use detergents or other chemicals. Here we report a detailed protocol that enables direct ejection of protein complexes from membranes for analysis by native MS. Briefly, lipid vesicles are prepared directly from membranes of different sources and subjected to sonication pulses. The resulting destabilized vesicles are concentrated, introduced into a mass spectrometer and ionized. The mass of the observed protein complexes is determined and this information, in conjunction with 'omics'-based strategies, is used to determine subunit stoichiometry as well as cofactor and lipid binding. Within this protocol, we expand the applications of the method to include peripheral membrane proteins of the S-layer and amyloid protein export machineries overexpressed in membranes from which the most abundant components have been removed. The described experimental procedure takes approximately 3 d from preparation to MS. The time required for data analysis depends on the complexity of the protein assemblies embedded in the membrane under investigation.

A Universal Score for Deconvolution of Intact Protein and Native Electrospray Mass Spectra

The growing use of intact protein mass analysis, top-down proteomics, and native mass spectrometry have created a need for improved data analysis pipelines for deconvolution of electrospray (ESI) mass spectra containing multiple charge states and potentially without isotopic resolution. Although there are multiple deconvolution algorithms, there is no consensus for how to judge the quality of the deconvolution, and many scoring schemes are not published. Here, an intuitive universal score (UniScore) for ESI deconvolution is presented. The UniScore is the weighted average of deconvolution scores (DScores) for each peak multiplied by the R² of the fit to the data. Each DScore is composed of separate components to score (1) the uniqueness and fit of the deconvolution to the data, (2) the consistency of the peak shape across different charge states, (3) the smoothness of the charge state distribution, and (4) symmetry and separation of the peak. Example scores are provided for a range of experimental and simulated data. By providing a means of judging the quality of the overall deconvolution as well as individual mass peaks, the UniScore scheme provides a foundation for standardizing ESI data analysis of larger molecules and enabling the use of ESI deconvolution in automated data analysis pipelines.

Eliminating Artifacts in Electrospray Deconvolution with a SoftMax Function

UniDec provides a rapid and robust approach to deconvolving electrospray mass spectra into their corresponding mass and charge components. However, the UniDec algorithm can produce artifacts depending on the quality and complexity of the data. Here, a SoftMax function is applied to the charge state distribution of each data point, which pushes the algorithm towards assigning each data point to one primary charge state. As shown for several data sets of increasing complexity, the SoftMax function significantly reduces deconvolution artifacts, even for data with overlapping charge states.

Ion Mobility-Mass Spectrometry Reveals That α-Hemolysin from Staphylococcus aureus Simultaneously Forms Hexameric and Heptameric Complexes in Detergent Micelle Solutions

Many soluble and membrane proteins form symmetrical homooligomeric complexes. However, determining the oligomeric state of protein complexes can be difficult. Alpha-hemolysin (αHL) from Staphylococcus aureus is a symmetrical homooligomeric protein toxin that forms transmembrane β-barrel pores in host cell membranes. The stable pore structure of αHL has also been exploited in vitro as a nanopore tool. Early structural experiments suggested αHL forms a hexameric pore, while more recent X-ray crystal structure and solution studies have identified a heptameric pore structure. Here, using native ion mobility-mass spectrometry (IM-MS) we find that αHL simultaneously forms hexameric and heptameric oligomers in both tetraethylene glycol monooctyl ether (C₈E₄) and tetradecylphosphocholine (FOS-14) detergent solutions. We also analyze intact detergent micelle-embedded αHL porelike complexes by native IM-MS without the need to fully strip the detergent micelle, which can cause significant gas-phase unfolding. The highly congested native mass spectra are deconvolved using Fourier- and Gábor-transform (FT and GT) methods to determine charge states and detergent stoichiometry distributions. The intact αHL micelle complexes are found to contain oligomeric state-proportional numbers of detergent molecules. This evidence, combined with IM data and results from vacuum molecular dynamics simulations, is consistent with both the hexamer and the heptamer forming porelike complexes. The ability of αHL to form both oligomeric states simultaneously has implications for its use as a nanopore tool and its pore formation mechanism in vivo. This study also demonstrates more generally the power of FT and GT to deconvolve the charge state and stoichiometry distributions of polydisperse ions.