High-Throughput Analysis of Intact Human Proteins Using UVPD and HCD on an Orbitrap Mass Spectrometer

Structural Characterization and Absolute Quantification of Microcystin Peptides Using Collision-Induced and Ultraviolet Photo-Dissociation Tandem Mass Spectrometry

Microcystin (MC) peptides produced by cyanobacteria pose a hepatotoxic threat to human health upon ingestion from contaminated drinking water. While rapid MC identification and quantification in contaminated body fluids or tissue samples is important for patient treatment and outcomes, conventional immunoassay-based measurement strategies typically lack the specificity required for unambiguous determination of specific MC variants, whose toxicity can significantly vary depending on their structures. Furthermore, the unambiguous identification and accurate quantitation of MC variants using tandem mass spectrometry (MS/MS)-based methods can be limited due to a current lack of appropriate stable isotope-labeled internal standards. To address these limitations, we have systematically examined here the sequence and charge state dependence to the formation and absolute abundance of both "global" and "variant-specific" product ions from representative MC-LR, MC-YR, MC-RR, and MC-LA peptides, using higher-energy collisional dissociation (HCD)-MS/MS, ion-trap collision-induced dissociation (CID)-MS/MS and CID-MS³, and 193 nm ultraviolet photodissociation (UPVD)-MS/MS. HCD-MS/MS was found to provide the greatest detection sensitivity for both global and variant-specific product ions in each of the MC variants, except for MC-YR where a variant-specific product uniquely formed via UPVD-MS/MS was observed with the greatest absolute abundance. A simple methodology for the preparation and characterization of ¹⁸O-stable isotope-labeled MC reference materials for use as internal standards was also developed. Finally, we have demonstrated the applicability of the methods developed herein for absolute quantification of MC-LR present in human urine samples, using capillary scale liquid chromatography coupled with ultra-high resolution / accurate mass spectrometry and HCD-MS/MS. Graphical abstract ᅟ.

Multistage Ultraviolet Photodissociation Mass Spectrometry To Characterize Single Amino Acid Variants of Human Mitochondrial BCAT2

Unraveling disease mechanisms requires a comprehensive understanding of how the interplay between higher-order structure and protein-ligand interactions impacts the function of a given protein. Recent advances in native mass spectrometry (MS) involving multimodal or higher-energy activation methods have allowed direct interrogation of intact protein complexes in the gas phase, allowing analysis of both composition and subunit connectivity. We report a multistage approach combining collisional activation and 193 nm ultraviolet photodissociation (UVPD) to characterize single amino acid variants of the human mitochondrial enzyme branched-chain amino acid transferase 2 (BCAT2), a protein implicated in chemotherapeutic resistance in glioblastoma tumors. Native electrospray ionization confirms that both proteins exist as homodimers. Front-end collisional activation disassembles the dimers into monomeric subunits that are further interrogated using UVPD to yield high sequence coverage of the mutated region. Additionally, holo (ligand-bound) fragment ions resulting from photodissociation reveal that the mutation causes destabilization of the interactions with a bound cofactor. This study demonstrates the unique advantages of implementing UVPD in a multistage MS approach for analyzing intact protein assemblies.

Implementation of Fragment Ion Protection (FIP) during Ultraviolet Photodissociation (UVPD) Mass Spectrometry

Ultraviolet photodissociation (UVPD) is a nonselective activation method in which both precursor and fragment ions may absorb photons and dissociate. Photoactivation of fragment ions may result in secondary or multiple generations of dissociation, which decreases the signal-to-noise ratio (S/N) of larger fragment ions owing to the prevalent subdivision of the ion current into many smaller, often less informative, fragment ions. Here we report the use of dipolar excitation waveforms to displace fragment ions out of the laser beam path, thus alleviating the extent of secondary dissociation during 193 nm UVPD. This fragment ion protection (FIP) strategy increases S/N of larger fragment ions and improves the sequence coverage obtained for proteins via retaining information deeper into the midsection of protein sequences.

The Value of Activated Ion Electron Transfer Dissociation for High-Throughput Top-Down Characterization of Intact Proteins

High-throughput top-down proteomic experiments directly identify proteoforms in complex mixtures, making high quality tandem mass spectra necessary to deeply characterize proteins with many sources of variation. Collision-based dissociation methods offer expedient data acquisition but often fail to extensively fragment proteoforms for thorough analysis. Electron-driven dissociation methods are a popular alternative approach, especially for precursor ions with high charge density. Combining infrared photoactivation concurrent with electron transfer dissociation (ETD) reactions, i.e., activated ion ETD (AI-ETD), can significantly improve ETD characterization of intact proteins, but benefits of AI-ETD have yet to be quantified in high-throughput top-down proteomics. Here, we report the first application of AI-ETD to LC-MS/MS characterization of intact proteins (<20 kDa), highlighting improved proteoform identification the method offers over higher energy-collisional dissociation (HCD), standard ETD, and ETD followed by supplemental HCD activation (EThcD). We identified 935 proteoforms from 295 proteins from human colorectal cancer cell line HCT116 using AI-ETD compared to 1014 proteoforms, 915 proteoforms, and 871 proteoforms with HCD, ETD, and EThcD, respectively. Importantly, AI-ETD outperformed each of the three other methods in MS/MS success rates and spectral quality metrics (e.g., sequence coverage achieved and proteoform characterization scores). In all, this four-method analysis offers the most extensive comparisons to date and demonstrates that AI-ETD both increases identifications over other ETD methods and improves proteoform characterization via higher sequence coverage, positioning it as a premier method for high-throughput top-down proteomics.

Accurate Sequence Analysis of a Monoclonal Antibody by Top-Down and Middle-Down Orbitrap Mass Spectrometry Applying Multiple Ion Activation Techniques

Targeted top-down (TD) and middle-down (MD) mass spectrometry (MS) offer reduced sample manipulation during protein analysis, limiting the risk of introducing artifactual modifications to better capture sequence information on the proteoforms present. This provides some advantages when characterizing biotherapeutic molecules such as monoclonal antibodies, particularly for the class of biosimilars. Here, we describe the results obtained analyzing a monoclonal IgG1, either in its ∼150 kDa intact form or after highly specific digestions yielding ∼25 and ∼50 kDa subunits, using an Orbitrap mass spectrometer on a liquid chromatography (LC) time scale with fragmentation from ion-photon, ion-ion, and ion-neutral interactions. Ultraviolet photodissociation (UVPD) used a new 213 nm solid-state laser. Alternatively, we applied high-capacity electron-transfer dissociation (ETD HD), alone or in combination with higher energy collisional dissociation (EThcD). Notably, we verify the degree of complementarity of these ion activation methods, with the combination of 213 nm UVPD and ETD HD producing a new record sequence coverage of ∼40% for TD MS experiments. The addition of EThcD for the >25 kDa products from MD strategies generated up to 90% of complete sequence information in six LC runs. Importantly, we determined an optimal signal-to-noise threshold for fragment ion deconvolution to suppress false positives yet maximize sequence coverage and implemented a systematic validation of this process using the new software TDValidator. This rigorous data analysis should elevate confidence for assignment of dense MS² spectra and represents a purposeful step toward the application of TD and MD MS for deep sequencing of monoclonal antibodies.

Expanding the Scope of Cross-Link Identifications by Incorporating Collisional Activated Dissociation and Ultraviolet Photodissociation Methods

With the advent of new cross-linking chemistries, analytical technologies, and search algorithms, cross-linking has become an increasingly popular strategy for evaluating tertiary and quaternary structures of proteins. Collisional activated dissociation remains the primary MS/MS method for identifications of peptide cross-links in high throughput workflows. Ultraviolet photodissociation (UVPD) at 193 nm has emerged as an alternative ion activation method well-suited for characterization of peptides and has been found in some cases to identify different peptides or provide distinctive sequence information than obtained by collisional activation methods. Complementary high energy collision dissociation (HCD) and UVPD were used in the present study to characterize protein cross-linking for bovine serum albumin, hemoglobin, and E. coli ribosome. Cross-links identified by HCD and UVPD using bis(sulfosuccinimidyl)suberate (BS3), a homobifunctional amine-to-amine cross-linker, and 4-(4,6-dimethoxy-1,3,5-triazin-2-yl)-4-methylmorpholinium chloride (DMTMM), a heterofunctional amine-to-carboxylic acid cross-linker, were evaluated in the present study. While more unique BS3 cross-links were identified by HCD, UVPD, and HCD provided a complementary panel of DMTMM cross-links which extended the degree of structural insight obtained for the proteins.

A Targeted, Differential Top-Down Proteomic Methodology for Comparison of ApoA-I Proteoforms in Individuals with High and Low HDL Efflux Capacity

Top-down proteomics (TDP) allows precise determination/characterization of the different proteoforms derived from the expression of a single gene. In this study, we targeted apolipoprotein A-I (ApoA-I), a mediator of high-density-lipoprotein cholesterol efflux (HDL-E), which is inversely associated with coronary heart disease risk. Absolute ApoA-I concentration and allelic variation only partially explain interindividual HDL-E variation. Therefore, we hypothesize that differences in HDL-E are associated with the abundances of different ApoA-I proteoforms. Here, we present a targeted TDP methodology to characterize ApoA-I proteoforms in serum samples and compare their abundances between individuals. We characterized 18 ApoA-I proteoforms using selected-ion monitoring coupled to electron-transfer dissociation mass spectrometry. We then compared the abundances of these proteoforms between two groups of four participants, representing the individuals with highest and lowest HDL-E values within the Chicago Healthy Aging Study ( n = 420). Six proteoforms showed significantly ( p < 0.0005) higher intensity in high HDL-E individuals: canonical ApoA-I [fold difference (fd) = 1.17], carboxymethylated ApoA-I (fd = 1.24) and, with highest difference, four fatty acylated forms: palmitoylated (fd = 2.16), oleoylated (fd = 2.08), arachidonoylated (fd = 2.31) and one bearing two modifications: palmitoylation and truncation (fd = 2.13). These results demonstrate translational potential for targeted TDP in revealing, with high sensitivity, associations between interindividual proteoform variation and physiological differences underlying disease risk.

Chemical-Mediated Digestion: An Alternative Realm for Middle-down Proteomics?

Protein digestion in mass spectrometry (MS)-based bottom-up proteomics targets mainly lysine and arginine residues, yielding primarily 0.6-3 kDa peptides for the proteomes of organisms of all major kingdoms. Recent advances in MS technology enable analysis of complex mixtures of increasingly longer (>3 kDa) peptides in a high-throughput manner supporting the development of a middle-down proteomics (MDP) approach. Generating longer peptides is a paramount step in launching an MDP pipeline, but the quest for the selection of a cleaving agent that would provide the desired 3-15 kDa peptides remains open. Recent bioinformatics studies have shown that cleavage at the rarely occurring amino acid residues such as methionine (Met), tryptophan (Trp), or cysteine (Cys) would be suitable for MDP approach. Interestingly, chemical-mediated proteolytic cleavages uniquely allow targeting these rare amino acids, for which no specific proteolytic enzymes are known. Herein, as potential candidates for MDP-grade proteolysis, we have investigated the performance of chemical agents previously reported to target primarily Met, Trp, and Cys residues: CNBr, BNPS-Skatole (3-bromo-3-methyl-2-(2-nitrophenyl)sulfanylindole), and NTCB (2-nitro-5-thiobenzoic acid), respectively. Figures of merit such as digestion reproducibility, peptide size distribution, and occurrence of side reactions are discussed. The NTCB-based MDP workflow has demonstrated particularly attractive performance, and NTCB is put forward here as a potential cleaving agent for further MDP development.

The cancer proteomic landscape and the HUPO Cancer Proteome Project

The Human Cancer Proteome Project (Cancer-HPP) is an international initiative organized by HUPO whose key objective is to decipher the human cancer proteome through a coordinated effort by cancer proteome researchers around the world. The ultimate goal is to map the entire human cancer proteome to disclose tumor biology and drive improved diagnostics, treatment and management of cancer. Here we report the progress in the cancer proteomics field to date, and discuss future proteomic developments that will be needed to optimally delineate cancer phenotypes and advance the molecular characterization of this significant disease that is one of the leading causes of death worldwide.

The Ups and Downs of Repeated Cleavage and Internal Fragment Production in Top-Down Proteomics

Analysis of whole proteins by mass spectrometry, or top-down proteomics, has several advantages over methods relying on proteolysis. For example, proteoforms can be unambiguously identified and examined. However, from a gas-phase ion-chemistry perspective, proteins are enormous molecules that present novel challenges relative to peptide analysis. Herein, the statistics of cleaving the peptide backbone multiple times are examined to evaluate the inherent propensity for generating internal versus terminal ions. The raw statistics reveal an inherent bias favoring production of terminal ions, which holds true regardless of protein size. Importantly, even if the full suite of internal ions is generated by statistical dissociation, terminal ions are predicted to account for at least 50% of the total ion current, regardless of protein size, if there are three backbone dissociations or fewer. Top-down analysis should therefore be a viable approach for examining proteins of significant size. Comparison of the purely statistical analysis with actual top-down data derived from ultraviolet photodissociation (UVPD) and higher-energy collisional dissociation (HCD) reveals that terminal ions account for much of the total ion current in both experiments. Terminal ion production is more favored in UVPD relative to HCD, which is likely due to differences in the mechanisms controlling fragmentation. Importantly, internal ions are not found to dominate from either the theoretical or experimental point of view. Graphical abstract ᅟ.

Expanding Proteoform Identifications in Top-Down Proteomic Analyses by Constructing Proteoform Families

In top-down proteomics, intact proteins are analyzed by tandem mass spectrometry and proteoforms, which are defined forms of a protein with specific sequences of amino acids and localized post-translational modifications, are identified using precursor mass and fragmentation data. Many proteoforms that are detected in the precursor scan (MS1) are not selected for fragmentation by the instrument and therefore remain unidentified in typical top-down proteomic workflows. Our laboratory has developed the open source software program Proteoform Suite to analyze MS1-only intact proteoform data. Here, we have adapted it to provide identifications of proteoform masses in precursor MS1 spectra of top-down data, supplementing the top-down identifications obtained using the MS2 fragmentation data. Proteoform Suite performs mass calibration using high-scoring top-down identifications and identifies additional proteoforms using calibrated, accurate intact masses. Proteoform families, the set of proteoforms from a given gene, are constructed and visualized from proteoforms identified by both top-down and intact-mass analyses. Using this strategy, we constructed proteoform families and identified 1861 proteoforms in yeast lysate, yielding an approximately 40% increase over the original 1291 proteoform identifications observed using traditional top-down analysis alone.

Data acquisition workflows in liquid chromatography coupled to high resolution mass spectrometry-based metabolomics: Where do we stand?

Typical mass spectrometry (MS) based untargeted metabolomics protocols are tedious as well as time- and sample-consuming. In particular, they often rely on "full-scan-only" analyses using liquid chromatography (LC) coupled to high resolution mass spectrometry (HRMS) from which metabolites of interest are first highlighted, and then tentatively identified by using targeted MS/MS experiments. However, this situation is evolving with the emergence of integrated HRMS based-data acquisition protocols able to perform multi-event acquisitions. Most of these protocols, referring to as data dependent and data independent acquisition (DDA and DIA, respectively), have been initially developed for proteomic applications and have recently demonstrated their applicability to biomedical studies. In this context, the aim of this article is to take stock of the progress made in the field of DDA- and DIA-based protocols, and evaluate their ability to change conventional metabolomic and lipidomic data acquisition workflows, through a review of HRMS instrumentation, DDA and DIA workflows, and also associated informatics tools.

It is time for top-down venomics

The protein composition of animal venoms is usually determined by peptide-centric proteomics approaches (bottom-up proteomics). However, this technique cannot, in most cases, distinguish among toxin proteoforms, herein called toxiforms, because of the protein inference problem. Top-down proteomics (TDP) analyzes intact proteins without digestion and provides high quality data to identify and characterize toxiforms. Denaturing top-down proteomics is the most disseminated subarea of TDP, which performs qualitative and quantitative analyzes of proteoforms up to ~30 kDa in high-throughput and automated fashion. On the other hand, native top-down proteomics provides access to information on large proteins (> 50 kDA) and protein interactions preserving non-covalent bonds and physiological complex stoichiometry. The use of native and denaturing top-down venomics introduced novel and useful techniques to toxinology, allowing an unprecedented characterization of venom proteins and protein complexes at the toxiform level. The collected data contribute to a deep understanding of venom natural history, open new possibilities to study the toxin evolution, and help in the development of better biotherapeutics.