Fourier Analysis Method for Analyzing Highly Congested Mass Spectra of Ion Populations with Repeated Subunits

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.

The complete assembly of human LAT1-4F2hc complex provides insights into its regulation, function and localisation

The LAT1-4F2hc complex (SLC7A5-SLC3A2) facilitates uptake of essential amino acids, hormones and drugs. Its dysfunction is associated with many cancers and immune/neurological disorders. Here, we apply native mass spectrometry (MS)-based approaches to provide evidence of super-dimer formation (LAT1-4F2hc)2. When combined with lipidomics, and site-directed mutagenesis, we discover four endogenous phosphatidylethanolamine (PE) molecules at the interface and C-terminus of both LAT1 subunits. We find that interfacial PE binding is regulated by 4F2hc-R183 and is critical for regulation of palmitoylation on neighbouring LAT1-C187. Combining native MS with mass photometry (MP), we reveal that super-dimerization is sensitive to pH, and modulated by complex N-glycans on the 4F2hc subunit. We further validate the dynamic assemblies of LAT1-4F2hc on plasma membrane and in the lysosome. Together our results link PTM and lipid binding with regulation and localisation of the LAT1-4F2hc super-dimer.

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.

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

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

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.

MASH Native: a unified solution for native top-down proteomics data processing

MOTIVATION

Native top-down proteomics (nTDP) integrates native mass spectrometry (nMS) with top-down proteomics (TDP) to provide comprehensive analysis of protein complexes together with proteoform identification and characterization. Despite significant advances in nMS and TDP software developments, a unified and user-friendly software package for analysis of nTDP data remains lacking.

RESULTS

We have developed MASH Native to provide a unified solution for nTDP to process complex datasets with database searching capabilities in a user-friendly interface. MASH Native supports various data formats and incorporates multiple options for deconvolution, database searching, and spectral summing to provide a "one-stop shop" for characterizing both native protein complexes and proteoforms.

AVAILABILITY AND IMPLEMENTATION

The MASH Native app, video tutorials, written tutorials, and additional documentation are freely available for download at https://labs.wisc.edu/gelab/MASH_Explorer/MASHSoftware.php. All data files shown in user tutorials are included with the MASH Native software in the download .zip file.

MASH Native: A Unified Solution for Native Top-Down Proteomics Data Processing

Native top-down proteomics (nTDP) integrates native mass spectrometry (nMS) with top-down proteomics (TDP) to provide comprehensive analysis of protein complexes together with proteoform identification and characterization. Despite significant advances in nMS and TDP software developments, a unified and user-friendly software package for analysis of nTDP data remains lacking. Herein, we have developed MASH Native to provide a unified solution for nTDP to process complex datasets with database searching capabilities in a user-friendly interface. MASH Native supports various data formats and incorporates multiple options for deconvolution, database searching, and spectral summing to provide a one-stop shop for characterizing both native protein complexes and proteoforms. The MASH Native app, video tutorials, written tutorials and additional documentation are freely available for download at https://labs.wisc.edu/gelab/MASH_Explorer/MASHNativeSoftware.php . All data files shown in user tutorials are included with the MASH Native software in the download .zip file.

Fundamentals: How Do We Calculate Mass, Error, and Uncertainty in Native Mass Spectrometry?

Mass spectrometry (MS) is uniquely powerful for measuring the mass of intact proteins and other biomolecules. New applications have expanded intact protein analysis into biopharmaceuticals, native MS, and top-down proteomics, all of which have driven the need for more automated data-processing pipelines. However, key metrics in the field are often not precisely defined. For example, there are different views on how to calculate uncertainty from spectra. This Critical Insight will explore the different definitions of mass, error, and uncertainty. It will discuss situations where different definitions may be more suitable and provide recommendations for best practices. Targeting both beginners and experts, the goal of the discussion is to provide a common foundation of terminology, enhance statistical rigor, and improve automation of data analysis.

Native Mass Spectrometry: Recent Progress and Remaining Challenges

Native mass spectrometry (nMS) has emerged as an important tool in studying the structure and function of macromolecules and their complexes in the gas phase. In this review, we cover recent advances in nMS and related techniques including sample preparation, instrumentation, activation methods, and data analysis software. These advances have enabled nMS-based techniques to address a variety of challenging questions in structural biology. The second half of this review highlights recent applications of these technologies and surveys the classes of complexes that can be studied with nMS. Complementarity of nMS to existing structural biology techniques and current challenges in nMS are also addressed.

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.

Lipid Head Group Adduction to Soluble Proteins Follows Gas-Phase Basicity Predictions: Dissociation Barriers and Charge Abstraction

Native mass spectrometry analysis of membrane proteins has yielded many useful insights in recent years with respect to membrane protein-lipid interactions, including identifying specific interactions and even measuring binding affinities based on observed abundances of lipid-bound ions after collision-induced dissociation (CID). However, the behavior of non-covalent complexes subjected to extensive CID can in principle be affected by numerous factors related to gas-phase chemistry, including gas-phase basicity (GB) and acidity, shared-proton bonds, and other factors. A recent report from our group showed that common lipids span a wide range of GB values. Notably, phosphatidylcholine (PC) and sphingomyelin lipids are more basic than arginine, suggesting they may strip charge upon dissociation in positive ion mode, while phosphoserine lipids are slightly less basic than arginine and may form especially strong shared-proton bonds. Here, we use CID to probe the strength of non-specific gas-phase interactions between lipid head groups and several soluble proteins, used to deliberately avoid possible physiological protein-lipid interactions. The strengths of the protein-head group interactions follow the trend predicted based solely on lipid and amino acid GBs: phosphoserine (PS) head group forms the strongest bonds with these proteins and out-competes the other head groups studied, while glycerophosphocholine (GPC) head groups form the weakest interactions and dissociate carrying away a positive charge. These results indicate that gas-phase thermochemistry can play an important role in determining which head groups remain bound to protein ions with native-like structures and charge states in positive ion mode upon extensive collisional activation.

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.

High-Resolution Native Mass Spectrometry

Native mass spectrometry (MS) involves the analysis and characterization of macromolecules, predominantly intact proteins and protein complexes, whereby as much as possible the native structural features of the analytes are retained. As such, native MS enables the study of secondary, tertiary, and even quaternary structure of proteins and other biomolecules. Native MS represents a relatively recent addition to the analytical toolbox of mass spectrometry and has over the past decade experienced immense growth, especially in enhancing sensitivity and resolving power but also in ease of use. With the advent of dedicated mass analyzers, sample preparation and separation approaches, targeted fragmentation techniques, and software solutions, the number of practitioners and novel applications has risen in both academia and industry. This review focuses on recent developments, particularly in high-resolution native MS, describing applications in the structural analysis of protein assemblies, proteoform profiling of—among others—biopharmaceuticals and plasma proteins, and quantitative and qualitative analysis of protein–ligand interactions, with the latter covering lipid, drug, and carbohydrate molecules, to name a few.

Denaturing and Native Mass Spectrometric Analytics for Biotherapeutic Drug Discovery Research: Historical, Current, and Future Personal Perspectives

Mass spectrometry (MS) plays a key role throughout all stages of drug development and is now as ubiquitous as other analytical techniques such as surface plasmon resonance, nuclear magnetic resonance, and supercritical fluid chromatography, among others. Herein, we aim to discuss the history of MS, both electrospray and matrix-assisted laser desorption ionization, specifically for the analysis of antibodies, evolving through to denaturing and native-MS analysis of newer biologic moieties such as antibody-drug conjugates, multispecific antibodies, and interfering nucleic acid-based therapies. We discuss challenging therapeutic target characterization such as membrane protein receptors. Importantly, we compare and contrast the MS and hyphenated analytical chromatographic methods used to characterize these therapeutic modalities and targets within biopharmaceutical research and highlight the importance of appropriate MS deconvolution software and its essential contribution to project progression. Finally, we describe emerging applications and MS technologies that are still predominantly within either a development or academic stage of use but are poised to have significant impact on future drug development within the biopharmaceutic industry once matured. The views reflected herein are personal and are not meant to be an exhaustive list of all relevant MS performed within biopharmaceutical research but are what we feel have been historically, are currently, and will be in the future the most impactful for the drug development process.

Scratching the surface: native mass spectrometry of peripheral membrane protein complexes

A growing number of integral membrane proteins have been shown to tune their activity by selectively interacting with specific lipids. The ability to regulate biological functions via lipid interactions extends to the diverse group of proteins that associate only peripherally with the lipid bilayer. However, the structural basis of these interactions remains challenging to study due to their transient and promiscuous nature. Recently, native mass spectrometry has come into focus as a new tool to investigate lipid interactions in membrane proteins. Here, we outline how the native MS strategies developed for integral membrane proteins can be applied to generate insights into the structure and function of peripheral membrane proteins. Specifically, native MS studies of proteins in complex with detergent-solubilized lipids, bound to lipid nanodiscs, and released from native-like lipid vesicles all shed new light on the role of lipid interactions. The unique ability of native MS to capture and interrogate protein–protein, protein–ligand, and protein–lipid interactions opens exciting new avenues for the study of peripheral membrane protein biology.

Nanodiscs and Mass Spectrometry: Making Membranes Fly

Cells are surrounded by a protective lipid bilayer membrane, and membrane proteins in the bilayer control the flow of chemicals, information, and energy across this barrier. Many therapeutics target membrane proteins, and some directly target the lipid membrane itself. However, interactions within biological membranes are challenging to study due to their heterogeneity and insolubility. Mass spectrometry (MS) has become a powerful technique for studying membrane proteins, especially how membrane proteins interact with their surrounding lipid environment. Although detergent micelles are the most common membrane mimetic, nanodiscs are emerging as a promising platform for MS. Nanodiscs, nanoscale lipid bilayers encircled by two scaffold proteins, provide a controllable lipid bilayer for solubilizing membrane proteins. This Young Scientist Perspective focuses on native MS of intact nanodiscs and highlights the unique experiments enabled by making membranes fly, including studying membrane protein-lipid interactions and exploring the specificity of fragile transmembrane peptide complexes. It will also explore current challenges and future perspectives for interfacing nanodiscs with MS.

Software Requirements for the Analysis and Interpretation of Native Ion Mobility Mass Spectrometry Data

The past few years have seen a dramatic increase in applications of native mass and ion mobility spectrometry, especially for the study of proteins and protein complexes. This increase has been catalyzed by the availability of commercial instrumentation capable of carrying out such analyses. As in most fields, however, the software to process the data generated from new instrumentation lags behind. Recently, a number of research groups have started addressing this by developing software, but further improvements are still required in order to realize the full potential of the data sets generated. In this perspective, we describe practical aspects as well as challenges in processing native mass spectrometry (MS) and ion mobility-MS data sets and provide a brief overview of currently available tools. We then set out our vision of future developments that would bring the community together and lead to the development of a common platform to expedite future computational developments, provide standardized processing approaches, and serve as a location for the deposition of data for this emerging field. This perspective has been written by members of the European Cooperation in Science and Technology Action on Native MS and Related Methods for Structural Biology (EU COST Action BM1403) as an introduction to the software tools available in this area. It is intended to serve as an overview for newcomers and to stimulate discussions in the community on further developments in this field, rather than being an in-depth review. Our complementary perspective (http://dx.doi.org/10.1021/acs.analchem.9b05791) focuses on computational approaches used in this field.

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.

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.

Sliding Window Adduct Removal Method (SWARM) for Enhanced Electrospray Ionization Mass Spectrometry Binding Data

Electrospray ionization mass spectrometry (ESI-MS) screening of compound libraries against target proteins enables the rapid identification of ligands and measurement of the stoichiometry and affinity of the interactions. However, non-specific association of buffer or salts (added or present as impurities) to the protein ions during gas-phase ion formation can complicate the analysis of ESI-MS data acquired for mixtures of compounds with similar molecular weights. Spectral overlap of ions corresponding to free protein and protein-ligand complexes and their corresponding adducts can hinder the identification of ligands and introduce errors in the measured affinities. Here, we present a straightforward approach, called the sliding window adduct removal method (SWARM), to quantitatively correct ESI mass spectra of low-to-moderate resolution for signal overlap associated with adducts. The method relies on the statistical nature of adduct formation in ESI and the assumption that the distributions of adducts associated with a given protein (free protein and ligand-bound forms) are identical at a given charge state. Analysis of ESI mass spectra measured for protein-oligosaccharide interactions using solutions that produced either low- or high-abundance adducts provides support for this assumption. Implementation of SWARM involves the stepwise subtraction of the adduct signal associated with the detected protein-ligand complexes from the mass spectrum. This is accomplished using the adduct distribution measured for an appropriate reference species (usually free protein). To demonstrate the utility of the method, we applied SWARM to ESI-MS screening data acquired for libraries of oligosaccharides and bifunctional ligands consisting of a sulfonamide moiety linked to human glycan structures. Graphical Abstract.

Alphabet Projection of Spectra

In the metabolomics, glycomics, and mass spectrometry of structured small molecules, the combinatoric nature of the problem renders a database impossibly large, and thus de novo analysis is necessary. De novo analysis requires an alphabet of mass difference values used to link peaks in fragmentation spectra when they are different by a mass in the alphabet divided by a charge. Often, this alphabet is not known, prohibiting de novo analysis. A method is proposed that, given fragmentation mass spectra, identifies an alphabet of m/z differences that can build large connected graphs from many intense peaks in each spectrum from a collection. We then introduce a novel approach to efficiently find recurring substructures in the de novo graph results.

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.

Native and Denaturing MS Protein Deconvolution for Biopharma: Monoclonal Antibodies and Antibody-Drug Conjugates to Polydisperse Membrane Proteins and Beyond

Electrospray ionization mass spectrometry (ESI-MS) is a ubiquitously used analytical method applied across multiple departments in biopharma, ranging from early research discovery to process development. Accurate, efficient, and consistent protein MS spectral deconvolution across multiple instrument and detector platforms (time-of-flight, Orbitrap, Fourier-transform ion cyclotron resonance) is essential. When proteins are ionized during the ESI process, a distribution of consecutive multiply charged ions are observed on the m/z scale, either positive [M + nH]ⁿ⁺ or negative [M - nH]^n- depending on the ionization polarity. The manual calculation of the neutral molecular weight (MW) of single proteins measured by ESI-MS is simple; however, algorithmic deconvolution is required for more complex protein mixtures to derive accurate MWs. Multiple deconvolution algorithms have evolved over the past two decades, all of which have their advantages and disadvantages, in terms of speed, user-input parameters (or ideally lack thereof), and whether they perform optimally on proteins analyzed under denatured or native-MS and solution conditions. Herein, we describe the utility of a parsimonious deconvolution algorithm (explaining the observed spectra with a minimum number of masses) to process a wide range of highly diverse biopharma relevant and research grade proteins and complexes (PEG-GCSF; an IgG1k; IgG1- and IgG2-biotin covalent conjugates; the membrane protein complex AqpZ; a highly polydisperse empty MSP1D1 nanodisc and the tetradecameric chaperone protein complex GroEL) analyzed under native-MS, denaturing LC-MS, and positive and negative modes of ionization, using multiple instruments and therefore multiple data formats. The implementation of a comb filter and peak sharpening option is also demonstrated to be highly effective for deconvolution of highly polydisperse and enhanced separation of a low level lysine glycation post-translational modification (+162.1 Da), partially processed heavy chain lysine residues (+128.1 Da), and loss of N-acetylglucosamine (GlcNAc; -203.1 Da).

MetaUniDec: High-Throughput Deconvolution of Native Mass Spectra

The expansion of native mass spectrometry (MS) methods for both academic and industrial applications has created a substantial need for analysis of large native MS datasets. Existing software tools are poorly suited for high-throughput deconvolution of native electrospray mass spectra from intact proteins and protein complexes. The UniDec Bayesian deconvolution algorithm is uniquely well suited for high-throughput analysis due to its speed and robustness but was previously tailored towards individual spectra. Here, we optimized UniDec for deconvolution, analysis, and visualization of large data sets. This new module, MetaUniDec, centers around a hierarchical data format 5 (HDF5) format for storing datasets that significantly improves speed, portability, and file size. It also includes code optimizations to improve speed and a new graphical user interface for visualization, interaction, and analysis of data. To demonstrate the utility of MetaUniDec, we applied the software to analyze automated collision voltage ramps with a small bacterial heme protein and large lipoprotein nanodiscs. Upon increasing collisional activation, bacterial heme-nitric oxide/oxygen binding (H-NOX) protein shows a discrete loss of bound heme, and nanodiscs show a continuous loss of lipids and charge. By using MetaUniDec to track changes in peak area or mass as a function of collision voltage, we explore the energetic profile of collisional activation in an ultra-high mass range Orbitrap mass spectrometer. Graphical abstract ᅟ.

Extracting Charge and Mass Information from Highly Congested Mass Spectra Using Fourier-Domain Harmonics

Native mass spectra of large, polydisperse biomolecules with repeated subunits, such as lipoprotein Nanodiscs, can often be challenging to analyze by conventional methods. The presence of tens of closely spaced, overlapping peaks in these mass spectra can make charge state, total mass, or subunit mass determinations difficult to measure by traditional methods. Recently, we introduced a Fourier Transform-based algorithm that can be used to deconvolve highly congested mass spectra for polydisperse ion populations with repeated subunits and facilitate identification of the charge states, subunit mass, charge-state-specific, and total mass distributions present in the ion population. Here, we extend this method by investigating the advantages of using overtone peaks in the Fourier spectrum, particularly for mass spectra with low signal-to-noise and poor resolution. This method is illustrated for lipoprotein Nanodisc mass spectra acquired on three common platforms, including the first reported native mass spectrum of empty "large" Nanodiscs assembled with MSP1E3D1 and over 300 noncovalently associated lipids. It is shown that overtone peaks contain nearly identical stoichiometry and charge state information to fundamental peaks but can be significantly better resolved, resulting in more reliable reconstruction of charge-state-specific mass spectra and peak width characterization. We further demonstrate how these parameters can be used to improve results from Bayesian spectral fitting algorithms, such as UniDec. Graphical Abstract ᅟ.

Engineering Nanodisc Scaffold Proteins for Native Mass Spectrometry

Lipoprotein nanodiscs are ideally suited for native mass spectrometry because they provide a relatively monodisperse nanoscale lipid bilayer environment for delivering membrane proteins into the gas phase. However, native mass spectrometry of nanodiscs produces complex spectra that can be challenging to assign unambiguously. To simplify interpretation of nanodisc spectra, we engineered a series of mutant membrane scaffold proteins (MSP) that do not affect nanodisc formation but shift the masses of nanodiscs in a controllable way, eliminating isobaric interference from the lipids. Moreover, by mixing two different belts before assembly, the stoichiometry of MSP is encoded in the peak shape, which allows the stoichiometry to be assigned unambiguously from a single spectrum. Finally, we demonstrate the use of mixed belt nanodiscs with embedded membrane proteins to confirm the dissociation of MSP prior to desolvation.

Interfacing Membrane Mimetics with Mass Spectrometry

Membrane proteins play critical physiological roles and make up the majority of drug targets. Due to their generally low expression levels and amphipathic nature, membrane proteins represent challenging molecular entities for biophysical study. Mass spectrometry offers several sensitive approaches to study the biophysics of membrane proteins. By preserving noncovalent interactions in the gas phase and using collisional activation to remove solubilization agents inside the mass spectrometer, native mass spectrometry (MS) is capable of studying isolated assemblies that would be insoluble in aqueous solution, such as membrane protein oligomers and protein-lipid complexes. Conventional methods use detergent to solubilize the protein prior to electrospray ionization. Gas-phase activation inside the mass spectrometer removes the detergent to yield the isolated proteins with bound ligands. This approach has proven highly successful for ionizing membrane proteins. With the appropriate choice of detergents, membrane proteins with bound lipid species can be observed, which allows characterization of protein-lipid interactions. However, detergents have several limitations. They do not necessarily replicate the native lipid bilayer environment, and only a small number of protein-lipid interactions can be resolved. In this Account, we summarize the development of different membrane mimetics as cassettes for MS analysis of membrane proteins. Examples include amphipols, bicelles, and picodiscs with a special emphasis on lipoprotein nanodiscs. Polydispersity and heterogeneity of the membrane mimetic cassette is a critical issue for study by MS. Ever more complex data sets consisting of overlapping protein charge states and multiple lipid-bound entities have required development of new computational, theoretical, and experimental approaches to interpret both mass and ion mobility spectra. We will present the rationale and limitations of these approaches. Starting with the early work on empty nanodiscs, we chart developments that culminate in recent high-resolution studies of membrane protein-lipid complexes ejected from nanodiscs. For the latter, increasing collision energies allowed progressive removal of nanodisc components, beginning with the scaffold proteins and continuing through successive shells of lipids, allowing direct characterization of the stoichiometry of the annular lipid belt that surrounds the membrane protein. We consider future directions for the study of membrane proteins in membrane mimetics, including the development of mixed lipid systems and native bilayer environments. Unambiguous assignment of these heterogeneous systems will rely heavily upon further enhancements in both data analysis protocols and instrumental resolution. We anticipate that these developments will provide new insights into the factors that control dynamic protein-lipid interactions in a variety of tailored and natural lipid environments.