Identification Of Proteoforms Research Articles

A simple and efficient approach for preparing cationic coating with tunable electroosmotic flow for capillary zone electrophoresis-mass spectrometry-based top-down proteomics

BackgroundCapillary zone electrophoresis-tandem mass spectrometry (CZE-MS/MS) has become a valuable analytical technique in top-down proteomics (TDP). CZE-MS/MS-based TDP typically employs separation capillaries with neutral coatings (i.e., linear polyacrylamide, LPA). However, issues related to separation resolution and reproducibility remain with the LPA-coated capillaries due to the unavoidable non-specific protein adsorption onto the capillary wall. Cationic coatings can be critical alternatives to LPA coating for CZE-MS/MS-based TDP due to the electrostatic repulsion between the positively charged capillary inner wall and proteoform molecules in the acidic separation buffer. Unfortunately, there are only very few studies using cationic coating-based CZE-MS/MS for TDP studies. ResultsIn this work, we aimed to develop a simple and efficient approach for preparing separation capillaries with a cationic coating, i.e., poly (acrylamide-co-(3-acrylamidopropyl) trimethylammonium chloride [PAMAPTAC]) for CZE-MS/MS-based TDP. The PAMAPTAC coating-based CZE-MS produced significantly better separation resolution of proteoforms compared to the traditionally used LPA-coated approach. It achieved reproducible separation and measurement of a simple proteoform mixture and a complex proteome sample (i.e., a yeast cell lysate) regarding migration time, proteoform intensity, and the number of proteoform identifications. The PAMAPTAC coating-based CZE-MS enabled the detection of large proteoforms (≥30 kDa) from the yeast cell lysate reproducibly without any size-based prefractionation. Interestingly, the mobility of proteoforms using the PAMAPTAC coating can be predicted accurately using a simple semi-empirical model. SignificanceThe results render the PAMAPTAC coating as a valuable alternative to the LPA coating to advance CZE-MS-based TDP towards high-resolution separation and highly reproducible measurement of proteoforms in complex samples.

Filling the gaps in peptide maps with a platform assay for top-down characterization of purified protein samples.

Liquid chromatography-mass spectrometry (LC-MS) intact mass analysis and LC-MS/MS peptide mapping are decisional assays for developing biological drugs and other commercial protein products. Certain PTM types, such as truncation and oxidation, increase the difficulty of precise proteoform characterization owing to inherent limitations in peptide and intact protein analyses. Top-down MS (TDMS) can resolve this ambiguity via fragmentation of specific proteoforms. We leveraged the strengths of flow-programmed (fp) denaturing online buffer exchange (dOBE) chromatography, including robust automation, relatively high ESI sensitivity, and long MS/MS window time, to support a TDMS platform for industrial protein characterization. We tested data-dependent (DDA) and targeted strategies using 14 different MS/MS scan types featuring combinations of collisional- and electron-based fragmentation as well as proton transfer charge reduction. This large, focused dataset was processed using a new software platform, named TDAcquireX, that improves proteoform characterization through TDMS data aggregation. A DDA-based workflow provided objective identification of αLac truncation proteoforms with a two-termini clipping search. A targeted TDMS workflow facilitated the characterization of αLac oxidation positional isomers. This strategy relied on using sliding window-based fragment ion deconvolution to generate composite proteoform spectral match (cPrSM) results amenable to fragment noise filtering, which is a fundamental enhancement relevant to TDMS applications generally.

Top-down proteomics.

Proteoforms, which arise from post-translational modifications, genetic polymorphisms and RNA splice variants, play a pivotal role as drivers in biology. Understanding proteoforms is essential to unravel the intricacies of biological systems and bridge the gap between genotypes and phenotypes. By analysing whole proteins without digestion, top-down proteomics (TDP) provides a holistic view of the proteome and can decipher protein function, uncover disease mechanisms and advance precision medicine. This Primer explores TDP, including the underlying principles, recent advances and an outlook on the future. The experimental section discusses instrumentation, sample preparation, intact protein separation, tandem mass spectrometry techniques and data collection. The results section looks at how to decipher raw data, visualize intact protein spectra and unravel data analysis. Additionally, proteoform identification, characterization and quantification are summarized, alongside approaches for statistical analysis. Various applications are described, including the human proteoform project and biomedical, biopharmaceutical and clinical sciences. These are complemented by discussions on measurement reproducibility, limitations and a forward-looking perspective that outlines areas where the field can advance, including potential future applications.

Abstract 7092: Cancer biomarker discovery with scalable biofluid proteomics

Abstract Biofluid proteomics opens opportunities for the discovery of early detection, diagnostic, and prognostic cancer biomarkers through non-invasive or minimally invasive screening. Plasma and serum are accessible sample types, however, the high dynamic range of proteins creates analytical challenges for the sensitive detection of potential biomarkers. In this work, we compare two proteomic approaches for large-scale cancer biomarker discovery: the Olink Proximity Extension Assay and the Seer Proteograph Product Suite. Olink Explore 3072 is an immunoassay that gains specificity by using dual antibody recognition to measure approx. 3,000 proteins in each sample. Antibody pairs are tagged with oligonucleotides, which hybridize and are amplified before measurement by next generation sequencing. Seer Proteograph is an enrichment strategy that uses a proprietary mix of functionalized magnetic nanoparticles with affinity for certain amino acids and functional groups in native state proteins. The resulting peptides are measured using untargeted mass spectrometry to identify proteins at the peptide level, paving the way for the identification of proteoforms and peptide variants. Aliquots of human plasma from 78 samples representing a range of cancer indications were obtained through the Discovery Life Sciences biobank and used for analysis by both the Olink and Proteograph workflows. Olink analysis achieved Pearson correlation scores of greater than or equal to 0.8 when correlating each of seven process controls to each other for all approx. 3000 proteins. On average, greater than or equal to 75% of the proteins were detected across all panels in all sample groups except for Normal and Benign groups (64% and 74% respectively). After stringent FDR filtering to ensure only high-quality data was analyzed, the Seer Proteograph workflow quantified 4,323 proteins across all 78 samples. Pearson correlation scores of greater than or equal to 0.96 were achieved when comparing digestion controls, process controls, and sample cleanup controls. Both platforms achieved detection of proteins across the dynamic range of plasma, including low abundance proteins. The Olink Explore 3072 and Seer Proteograph platforms were found to be complementary, with approx. 15% overlap in measured proteins. Cancer biomarker discovery at the proteomic level is bolstered by recent advances in analytical capabilities, as revealed by the Olink Explore and Seer Proteograph platforms. Importantly, complementary implementation of these two workflows will enable comprehensive biomarker analysis. Citation Format: Danielle B. Gutierrez, Jessica L. Moore, Jaison Arivalagan, Tiffany Louie, Leslie Wilkinson, Ray Clemens. Cancer biomarker discovery with scalable biofluid proteomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7092.

Full-Length Single Protein Molecules Tracking and Counting in Thin Silicon Channels.

Emerging single-molecule protein sensing techniques are ushering in a transformative era in biomedical research. Nevertheless, challenges persist in realizing ultra-fast full-length protein sensing, including loss of molecular integrity due to protein fragmentation, biases introduced by antibodies affinity, identification of proteoforms, and low throughputs. Here, a single-molecule method for parallel protein separation and tracking is introduced, yielding multi-dimensional molecular properties used for their identification. Proteins are tagged by chemo-selective dual amino-acid specific labels and are electrophoretically separated by their mass/charge in custom-designed thin silicon channel with subwavelength height. This approach allows analysis of thousands of individual proteins within a few minutes by tracking their motion during the migration. The power of the method is demonstrated by quantifying a cytokine panel for host-response discrimination between viral and bacterial infections. Moreover, it is shown that two clinically-relevant splice isoforms of Vascular endothelial growth factor (VEGF) can be accurately quantified from human serum samples. Being non-destructive and compatible with full-length intact proteins, this method opens up ways for antibody-free single-protein molecule quantification.

Fast peak error correction algorithms for proteoform identification using top-down tandem mass spectra.

Proteoform identification is an important problem in proteomics. The main task is to find a modified protein that best fits the input spectrum. To overcome the combinatorial explosion of possible proteoforms, the proteoform mass graph and spectrum mass graph are used to represent the protein database and the spectrum, respectively. The problem becomes finding an optimal alignment between the proteoform mass graph and the spectrum mass graph. Peak error correction is an important issue for computing an optimal alignment between the two input mass graphs. We propose a faster algorithm for the error correction alignment of spectrum mass graph and proteoform mass graph problem and produce a program package TopMGFast. The newly designed algorithms require less space and running time so that we are able to compute global optimal alignments for the two input mass graphs in a reasonable time. For the local alignment version, experiments show that the running time of the new algorithm is reduced by 2.5 times. For the global alignment version, experiments show that the maximum mass errors between any pair of matched nodes in the alignments obtained by our method are within a small range as designed, while the alignments produced by the state-of-the-art method, TopMG, have very large maximum mass errors for many cases. The obtained alignment sizes are roughly the same for both TopMG and TopMGFast. Of course, TopMGFast needs more running time than TopMG. Therefore, our new algorithm can obtain more reliable global alignments within a reasonable time. This is the first time that global optimal error correction alignments can be obtained using real datasets. The source code of the algorithm is available at https://github.com/Zeirdo/TopMGFast.

Spectral averaging with outlier rejection algorithms to increase identifications in top-down proteomics.

The identification of proteoforms by top-down proteomics requires both high quality fragmentation spectra and the neutral mass of the proteoform from which the fragments derive. Intact proteoform spectra can be highly complex and may include multiple overlapping proteoforms, as well as many isotopic peaks and charge states. The resulting lower signal-to-noise ratios for intact proteins complicates downstream analyses such as deconvolution. Averaging multiple scans is a common way to improve signal-to-noise, but mass spectrometry data contains artifacts unique to it that can degrade the quality of an averaged spectra. To overcome these limitations and increase signal-to-noise, we have implemented outlier rejection algorithms to remove outlier measurements efficiently and robustly in a set of MS1 scans prior to averaging. We have implemented averaging with rejection algorithms in the open-source, freely available, proteomics search engine MetaMorpheus. Herein, we report the application of the averaging with rejection algorithms to direct injection and online liquid chromatography mass spectrometry data. Averaging with rejection algorithms demonstrated a 45% increase in the number of proteoforms detected in Jurkat T cell lysate. We show that the increase is due to improved spectral quality, particularly in regions surrounding isotopic envelopes.

Pilot Evaluation of the Long-Term Reproducibility of Capillary Zone Electrophoresis-Tandem Mass Spectrometry for Top-Down Proteomics of a Complex Proteome Sample.

Mass spectrometry (MS)-based top-down proteomics (TDP) has revolutionized biological research by measuring intact proteoforms in cells, tissues, and biofluids. Capillary zone electrophoresis-tandem MS (CZE-MS/MS) is a valuable technique for TDP, offering a high peak capacity and sensitivity for proteoform separation and detection. However, the long-term reproducibility of CZE-MS/MS in TDP remains unstudied, which is a crucial aspect for large-scale studies. This work investigated the long-term qualitative and quantitative reproducibility of CZE-MS/MS for TDP for the first time, focusing on a yeast cell lysate. Over 1000 proteoforms were identified per run across 62 runs using one linear polyacrylamide (LPA)-coated separation capillary, highlighting the robustness of the CZE-MS/MS technique. However, substantial decreases in proteoform intensity and identification were observed after some initial runs due to proteoform adsorption onto the capillary inner wall. To address this issue, we developed an efficient capillary cleanup procedure using diluted ammonium hydroxide, achieving high qualitative and quantitative reproducibility for the yeast sample across at least 23 runs. The data underscore the capability of CZE-MS/MS for large-scale quantitative TDP of complex samples, signaling its readiness for deployment in broad biological applications. The MS RAW files were deposited in ProteomeXchange Consortium with the data set identifier of PXD046651.

Structural-functional diversity of CD47 proteoforms.

The ubiquitously expressed transmembrane glycoprotein CD47 participates in various important physiological cell functions, including phagocytosis, apoptosis, proliferation, adhesion, and migration, through interactions with its ligands, including the inhibitory receptor signal regulatory protein α (SIRPα), secreted glycoprotein thrombospondin-1 (TSP-1), and integrins. Elevated expression of CD47 is observed in a wide range of cancer cells as a mechanism for evading the immune system, blocking the interaction between the CD47 and SIRPα is the most advanced and promising therapeutic approach currently investigated in multiple clinical trials. The widely held view that a single type of CD47 protein acts through membrane interactions has been challenged by the discovery of a large cohort of CD47 proteins with cell-, tissue-, and temporal-specific expression and functional profiles. These profiles have been derived from a single gene through alternative splicing and post-translational modifications, such as glycosylation, pyroglutamate modification, glycosaminoglycan modification, and proteolytic cleavage and, to some extent, via specific CD47 clustering in aging and tumor cells and the regulation of its subcellular localization by a pre-translational modification, alternative cleavage and polyadenylation (APA). This review explores the origins and molecular properties of CD47 proteoforms and their roles under physiological and pathological conditions, mentioning the new methods to improve the response to the therapeutic inhibition of CD47-SIRPα immune checkpoints, contributing to the understanding of CD47 proteoform diversity and identification of novel clinical targets and immune-related therapeutic candidates.

Full-length single-molecule protein fingerprinting.

Proteins are the primary functional actors of the cell. While proteoform diversity is known to be highly biologically relevant, current protein analysis methods are of limited use for distinguishing proteoforms. Mass spectrometric methods, in particular, often provide only ambiguous information on post-translational modification sites, and sequences of co-existing modifications may not be resolved. Here we demonstrate fluorescence resonance energy transfer (FRET)-based single-molecule protein fingerprinting to map the location of individual amino acids and post-translational modifications within single full-length protein molecules. Our data show that both intrinsically disordered proteins and folded globular proteins can be fingerprinted with a subnanometer resolution, achieved by probing the amino acids one by one using single-molecule FRET via DNA exchange. This capability was demonstrated through the analysis of alpha-synuclein, an intrinsically disordered protein, by accurately quantifying isoforms in mixtures using a machine learning classifier, and by determining the locations of two O-GlcNAc moieties. Furthermore, we demonstrate fingerprinting of the globular proteins Bcl-2-like protein 1, procalcitonin and S100A9. We anticipate that our ability to perform proteoform identification with the ultimate sensitivity may unlock exciting new venues in proteomics research and biomarker-based diagnosis.

Top-down ion mobility/mass spectrometry reveals enzyme specificity: Separation and sequencing of isomeric proteoforms.

Enzymatic catalysis is one of the fundamental processes that drives the dynamic landscape of post-translational modifications (PTMs), expanding the structural and functional diversity of proteins. Here, we assessed enzyme specificity using a top-down ion mobility spectrometry (IMS) and tandem mass spectrometry (MS/MS) workflow. We successfully applied trapped IMS (TIMS) to investigate site-specific N-ε-acetylation of lysine residues of full-length histone H4 catalyzed by histone lysine acetyltransferase KAT8. We demonstrate that KAT8 exhibits a preference for N-ε-acetylation of residue K16, while also adding acetyl groups on residues K5 and K8 as the first degree of acetylation. Achieving TIMS resolving power values of up to 300, we fully separated mono-acetylated regioisomers (H4K5ac, H4K8ac, and H4K16ac). Each of these separated regioisomers produce unique MS/MS fragment ions, enabling estimation of their individual mobility distributions and the exact localization of the N-ε-acetylation sites. This study highlights the potential of top-down TIMS-MS/MS for conducting enzymatic assays at the intact protein level and, more generally, for separation and identification of intact isomeric proteoforms and precise PTM localization.

Identification of proteoforms of short open reading frame-encoded peptides in Blautia producta under different cultivation conditions.

Short open reading frames (sORF) have the potential to encode small proteins, sORF-encoded peptides (SEP), which are less than or equal to 100 amino acids in length. These SEP have been associated with various physiological processes and are known for their potential roles in modulating immune responses, signaling pathways, and cellular functions. Using bottom-up and top-down proteomics, we identified 45 novel and formerly reported SEP under different growth conditions and stress exposure in single cultures of Blautia producta that plays a central role in mediating colonization resistance and dampening inflammation in the human gut microbiome. Top-down analysis improved identification confidence and allowed the detection of a number of full-length and N- or C-terminal truncated proteoforms of the SEP and of proteoforms carrying post-translational modifications such as disulfides, which provides hints for a wide functional potential of these molecules. The identification of the SEP in single cultures of this bacterium shows that, in contrast to previous results, the biosynthesis of specific SEP is not restricted to direct bacterial interactions within the microbiome but is dependent on growth and environmental conditions during cultivation. IMPORTANCE The identification of short open reading frame-encoded peptides (SEP) and different proteoforms in single cultures of gut microbes offers new insights into a largely neglected part of the microbial proteome landscape. This is of particular importance as SEP provide various predicted functions, such as acting as antimicrobial peptides, maintaining cell homeostasis under stress conditions, or even contributing to the virulence pattern. They are, thus, taking a poorly understood role in structure and function of microbial networks in the human body. A better understanding of SEP in the context of human health requires a precise understanding of the abundance of SEP both in commensal microbes as well as pathogens. For the gut beneficial B. producta, we demonstrate the importance of specific environmental conditions for biosynthesis of SEP expanding previous findings about their role in microbial interactions.

Characterization and Quantification of Von Willebrand Factor Proteoforms in Von Willebrand Disease Patients and Healthy Controls: Insights from the Win-Study

Background: Von Willebrand disease (VWD) is a commonly inherited bleeding disorder which is characterized by either low (type 1) or absent (type 3) levels of Von Willebrand factor (VWF) or by the occurrence of dysfunctional VWF proteoforms (type 2) in plasma. The complexity of diagnosing and managing VWD arises from limited understanding of the diverse VWF proteoforms present in both healthy individuals as well as in VWD patients. Objective: The aim of this study was to investigate the plasma proteome and to characterize VWF proteoforms in Von Willebrand disease (VWD) patients, that were enrolled in the Willebrand in the Netherlands (WiN) 1 study, compared with healthy controls. Method: We selected type 1, type 2A, type 2M, type 2N and type 3 patients from the WiN cohort for which extensive laboratory- and genotype data were available. Plasma from 64 VWD patients and ten healthy controls was analyzed using a combination of discovery- and targeted mass spectrometry-based approaches. Results: Both discovery-based as well as targeted quantitative proteomics analysis revealed significant variation in VWF levels across the selected VWD patient group, which was in line with reported clinical laboratory data. Elevated VWF-propeptide/VWF ratios were observed in plasma samples from a range of VWD patients, with notable increases observed in VWD type 2A, B, and M, indicating accelerated clearance of these VWF proteoforms. Discovery-based proteomics revealed a strong VWF-F8 relationship in all VWD subtypes and healthy controls, except for type 2N VWD. We were able to identify peptides corresponding with common polymorphisms ( e.g. p.Thr798Ala, p.Gln852Arg, p.Thr1381Ala), for which the observed peptide distribution was in line with the minor allele frequency reported by the Broad institute. In addition, we identified peptides corresponding with 16 pathogenic VWF variants (e.g. p.Arg1306Trp, p. Phe1293Leu, p.Cys1190Arg, p.Arg1374His or p.Tyr1584Cys) of which p.Cys1190Arg wild-type and variant peptide aligned with the zygosity at DNA level (Figure X). Based on spike-in with stable isotope-labeled peptides, the variant-to-wildtype ratios varied among VWD patients with distinct pathogenic variants, ranging from 0.5-2.5 in type 2M (p.Phe1293Leu) and type 1 patients (p.Tyr1584Cys), <1 in type 2A patients (p.Arg1374His), to >8 in type 2B patients (p.Arg1306Trp), suggesting distinct stoichiometry of VWF variants among these patients (Figure 2). Conclusion: Our study highlights the feasibility of VWF proteoform identification and quantification from plasma and suggest a potential role in unravelling their contribution to the biological variations and clinical diversity observed in VWD. 1 De Wee et al., Determinants of bleeding phenotype in adult patients with moderate or severe von Willebrand disease. Thromb Haemost. 2012 Oct;108(4):683-92.

Mass spectrometry-based proteomics for advancing solid organ transplantation research.

Scarcity of high-quality organs, suboptimal organ quality assessment, unsatisfactory pre-implantation procedures, and poor long-term organ and patient survival are the main challenges currently faced by the solid organ transplant (SOT) field. New biomarkers for assessing graft quality pre-implantation, detecting, and predicting graft injury, rejection, dysfunction, and survival are critical to provide clinicians with invaluable prediction tools and guidance for personalized patients' treatment. Additionally, new therapeutic targets are also needed to reduce injury and rejection and improve transplant outcomes. Proteins, which underlie phenotypes, are ideal candidate biomarkers of health and disease statuses and therapeutic targets. A protein can exist in different molecular forms, called proteoforms. As the function of a protein depends on its exact composition, proteoforms can offer a more accurate basis for connection to complex phenotypes than protein from which they derive. Mass spectrometry-based proteomics has been largely used in SOT research for identification of candidate biomarkers and therapeutic intervention targets by so-called "bottom-up" proteomics (BUP). However, such BUP approaches analyze small peptides in lieu of intact proteins and provide incomplete information on the exact molecular composition of the proteins of interest. In contrast, "Top-down" proteomics (TDP), which analyze intact proteins retaining proteoform-level information, have been only recently adopted in transplantation studies and already led to the identification of promising proteoforms as biomarkers for organ rejection and dysfunction. We anticipate that the use of top-down strategies in combination with new technological advancements in single-cell and spatial proteomics could drive future breakthroughs in biomarker and therapeutic target discovery in SOT.

Capillary zone electrophoresis-high field asymmetric ion mobility spectrometry-tandem mass spectrometry for top-down characterization of histone proteoforms.

Characterization of histone proteoforms with various post-translational modifications (PTMs) is critical for a better understanding of functions of histone proteoforms in epigenetic control of gene expression. Mass spectrometry (MS)-based top-down proteomics (TDP) is a valuable approach for delineating histone proteoforms because it can provide us with a bird's-eye view of histone proteoforms carrying diverse combinations of PTMs. Here, we present the first example of coupling capillary zone electrophoresis (CZE), ion mobility spectrometry (IMS), and MS for online multi-dimensional separations of histone proteoforms. Our CZE-high-field asymmetric waveform IMS (FAIMS)-MS/MS platform identified 366 (ProSight PD) and 602 (TopPIC) histone proteoforms from a commercial calf histone sample using a low microgram amount of histone sample as the starting material. CZE-FAIMS-MS/MS improved the number of histone proteoform identifications by about 3 folds compared to CZE-MS/MS alone (without FAIMS). The results indicate that CZE-FAIMS-MS/MS could be a useful tool for comprehensive characterization of histone proteoforms with high sensitivity.

Automated imaging and identification of proteoforms directly from ovarian cancer tissue

The molecular identification of tissue proteoforms by top-down mass spectrometry (TDMS) is significantly limited by throughput and dynamic range. We introduce AutoPiMS, a single-ion MS based multiplexed workflow for top-down tandem MS (MS2) directly from tissue microenvironments in a semi-automated manner. AutoPiMS directly off human ovarian cancer sections allowed for MS2 identification of 73 proteoforms up to 54 kDa at a rate of <1 min per proteoform. AutoPiMS is directly interfaced with multifaceted proteoform imaging MS data modalities for the identification of proteoform signatures in tumor and stromal regions in ovarian cancer biopsies. From a total of ~1000 proteoforms detected by region-of-interest label-free quantitation, we discover 303 differential proteoforms in stroma versus tumor from the same patient. 14 of the top proteoform signatures are corroborated by MSI at 20 micron resolution including the differential localization of methylated forms of CRIP1, indicating the importance of proteoform-enabled spatial biology in ovarian cancer.

Cysteine Counting via Isotopic Chemical Labeling for Intact Mass Proteoform Identifications in Tissue.

Top-down proteomics, the tandem mass spectrometric analysis of intact proteoforms, is the dominant method for proteoform characterization in complex mixtures. While this strategy produces detailed molecular information, it also requires extensive instrument time per mass spectrum obtained and thus compromises the depth of proteoform coverage that is accessible on liquid chromatography time scales. Such a top-down analysis is necessary for making original proteoform identifications, but once a proteoform has been confidently identified, the extensive characterization it provides may no longer be required for a subsequent identification of the same proteoform. We present a strategy to identify proteoforms in tissue samples on the basis of the combination of an intact mass determination with a measured count of the number of cysteine residues present in each proteoform. We developed and characterized a cysteine tagging chemistry suitable for the efficient and specific labeling of cysteine residues within intact proteoforms and for providing a count of the cysteine amino acids present. On simple protein mixtures, the tagging chemistry yields greater than 98% labeling of all cysteine residues, with a labeling specificity of greater than 95%. Similar results are observed on more complex samples. In a proof-of-principle study, proteoforms present in a human prostate tumor biopsy were characterized. Observed proteoforms, each characterized by an intact mass and a cysteine count, were grouped into proteoform families (groups of proteoforms originating from the same gene). We observed 2190 unique experimental proteoforms, 703 of which were grouped into 275 proteoform families.

Application of sample displacement batch chromatography for fractionation of proteoforms.

Fractionation of proteoforms is currently the most challenging topic in the field of proteoform analysis. The need for considering the existence of proteoforms in experimental approaches is not only important in Life Science research in general but especially in the manufacturing of therapeutic proteins (TPs) like recombinant therapeutic antibodies (mAbs). Some of the proteoforms of TPs have significantly decreased actions or even cause side effects. The identification and removal of proteoforms differing from the main species, having the desired action, is challenging because the difference in the composition of atoms is often very small and their concentration in comparison to the main proteoform can be low. In this study, we demonstrate that sample displacement batch chromatography (SDBC) is an easy-to-handle, economical, and efficient method for fractionating proteoforms. As a model sample a commercial ovalbumin fraction was used, containing many ovalbumin proteoforms. The most promising parameters for the SDBC were determined by a screening approach and applied for a 10-segment fractionation of ovalbumin with cation exchange chromatography resins. Mass spectrometry of intact proteoforms was used for characterizing the SDBC fractionation process. By SDBC, a significant separation of different proteoforms was obtained.

A robust nanoscale RP HPLC-MS approach for sensitive Fc proteoform profiling of IgG allotypes

The conserved region (Fc) of IgG antibodies dictates the interactions with designated receptors thus defining the immunological effector functions of IgG. Amino acid sequence variations in the Fc, recognized as subclasses and allotypes, as well as post-translational modifications (PTMs) modulate these interactions. Yet, the high similarity of Fc sequences hinders allotype-specific PTM analysis by state-of-the-art bottom-up methods and current subunit approaches lack sensitivity and face co-elution of near-isobaric allotypes.To circumvent these shortcomings, we present a nanoscale reversed-phase (RP) HPLC-MS workflow of intact Fc subunits for comprehensive characterization of Fc proteoforms in an allotype- and subclass-specific manner. Polyclonal IgGs were purified from individuals followed by enzymatic digestion releasing single chain Fc subunits (Fc/2) that were directly subjected to analysis. Chromatographic conditions were optimized to separate Fc/2 subunits of near-isobaric allotypes and subclasses allowing allotype and proteoform identification and quantification across all four IgG subclasses. The workflow was complemented by a semi-automated data analysis pipeline based on the open-source software Skyline followed by post-processing in R. The approach revealed pronounced differences in Fc glycosylation between donors, besides inter-subclass and inter-allotype variability within donors. Notably, partial occupancy of the N-glycosylation site in the CH3 domain of IgG3 was observed that is generally neglected by established approaches. The described method was benchmarked across several hundred runs and showed good precision and robustness.This methodology represents a first mature Fc subunit profiling approach allowing truly subclass- and allotype-specific Fc proteoform characterization beyond established approaches. The comprehensive information obtained paired with the high sensitivity provided by the miniaturization of the approach guarantees applicability to a broad range of research questions including clinically relevant (auto)antibody characterization or pharmacokinetics assessment of therapeutic IgGs.

Infrared Photoactivation Enables Improved Native Top-Down Mass Spectrometry of Transmembrane Proteins.

Membrane proteins are often challenging targets for native top-down mass spectrometry experimentation. The requisite use of membrane mimetics to solubilize such proteins necessitates the application of supplementary activation methods to liberate protein ions prior to sequencing, which typically limits the sequence coverage achieved. Recently, infrared photoactivation has emerged as an alternative to collisional activation for the liberation of membrane proteins from surfactant micelles. However, much remains unknown regarding the mechanism by which IR activation liberates membrane protein ions from such micelles, the extent to which such methods can improve membrane protein sequence coverage, and the degree to which such approaches can be extended to support native proteomics. Here, we describe experiments designed to evaluate and probe infrared photoactivation for membrane protein sequencing, proteoform identification, and native proteomics applications. Our data reveal that infrared photoactivation can dissociate micelles composed of a variety of detergent classes, without the need for a strong IR chromophore by leveraging the relatively weak association energies of such detergent clusters in the gas phase. Additionally, our data illustrate how IR photoactivation can be extended to include membrane mimetics beyond micelles and liberate proteins from nanodiscs, liposomes, and bicelles. Finally, our data quantify the improvements in membrane protein sequence coverage produced through the use of IR photoactivation, which typically leads to membrane protein sequence coverage values ranging from 40 to 60%.