Top-down proteomics: challenges, innovations, and applications in basic and clinical research

Top-Down Proteomics Analysis of Picogram-Level Complex Samples Using Spray-Capillary-Based Capillary Electrophoresis-Mass Spectrometry

Proteomics analysis of mass-limited samples has become increasingly important for understanding biological systems in physiologically relevant contexts such as patient samples, multicellular organoids, spheroids, and single cells. However, relatively low sensitivity in top-down proteomics methods makes their application to mass-limited samples challenging. Capillary electrophoresis (CE) has emerged as an ideal separation method for mass-limited samples due to its high separation resolution, ultralow detection limit, and minimal sample volume requirements. Recently, we developed "spray-capillary", an electrospray ionization (ESI)-assisted device, that is capable of quantitative ultralow-volume sampling (e.g., pL-nL level). Here, we developed a spray-capillary-CE-MS platform for ultrasensitive top-down proteomics analysis of intact proteins in mass-limited complex biological samples. Specifically, to improve the sensitivity of the spray-capillary platform, we incorporated a polyethylenimine (PEI)-coated capillary and optimized the spray-capillary inner diameter. Under optimized conditions, we successfully detected over 200 proteoforms from 50 pg of E. coli lysate. To our knowledge, the spray-capillary CE-MS platform developed here represents one of the most sensitive detection methods for top-down proteomics. Furthermore, in a proof-of-principle experiment, we detected 261 ± 65 and 174 ± 45 intact proteoforms from fewer than 50 HeLa and OVCAR-8 cells, respectively, by coupling nanodroplet-based sample preparation with our optimized CE-MS platform. Overall, our results demonstrate the capability of the modified spray-capillary CE-MS platform to perform top-down proteomics analysis on picogram amounts of samples. This advancement presents the possibility of meaningful top-down proteomics analysis of mass-limited samples down to the level of single mammalian cells.

Top-down mass spectrometry of native proteoforms and their complexes: a community study

The combination of native electrospray ionization with top-down fragmentation in mass spectrometry (MS) allows simultaneous determination of the stoichiometry of noncovalent complexes and identification of their component proteoforms and cofactors. Although this approach is powerful, both native MS and top-down MS are not yet well standardized, and only a limited number of laboratories regularly carry out this type of research. To address this challenge, the Consortium for Top-Down Proteomics initiated a study to develop and test protocols for native MS combined with top-down fragmentation of proteins and protein complexes across 11 instruments in nine laboratories. Here we report the summary of the outcomes to provide robust benchmarks and a valuable entry point for the scientific community.

Use of dried blood spots for monitoring inflammatory and nutritional biomarkers in the elderly

OBJECTIVES

Blood microsampling, particularly dried blood spots (DBSs), is an attractive minimally-invasive approach that is well suited for home sampling and predictive medicine associated with longitudinal follow-up of the elderly. However, in vitro diagnostic quantification of biomarkers from DBS poses a major challenge. Clinical mass spectrometry can reliably quantify blood proteins in various research projects. Our goal here was to use mass spectrometry of DBS in a real-world clinical setting and compared it to the standard immunoassay method. We also sought to correlate DBS mass spectrometry measurements with clinical indices.

METHODS

A clinical trial of diagnostic equivalence was conducted to compare conventional venous samples quantified by immunoassay and DBSs quantified by mass spectrometry in an elderly population. We assayed three protein biomarkers of nutritional and inflammatory status: prealbumin (transthyretin), C-reactive protein, and transferrin.

RESULTS

The analysis of DBSs showed satisfactory variability and low detection limits. Statistical analysis confirmed that the two methods give comparable results at clinical levels of accuracy. In conclusion, we demonstrated, in a real-life setting, that DBSs can be used to measure prealbumin, CRP and transferrin, which are commonly used markers of nutritional status and inflammation in the elderly. However, there was no correlation with patient frailty for these proteins.

CONCLUSIONS

Early detection and regular monitoring of nutritional and inflammatory problems using DBS appear to be clinically feasible. This could help resolve major public health challenges in the elderly for whom frailty leads to serious risks of health complications.

Comprehensive transcriptome analysis reveals altered mRNA splicing and post-transcriptional changes in the aged mouse brain

A comprehensive understanding of molecular changes during brain aging is essential to mitigate cognitive decline and delay neurodegenerative diseases. The interpretation of mRNA alterations during brain aging is influenced by the health and age of the animal cohorts studied. Here, we carefully consider these factors and provide an in-depth investigation of mRNA splicing and dynamics in the aging mouse brain, combining short- and long-read sequencing technologies with extensive bioinformatic analyses. Our findings encompass a spectrum of age-related changes, including differences in isoform usage, decreased mRNA dynamics and a module showing increased expression of neuronal genes. Notably, our results indicate a reduced abundance of mRNA isoforms leading to nonsense-mediated RNA decay and suggest a regulatory role for RNA-binding proteins, indicating that their regulation may be altered leading to the reshaping of the aged brain transcriptome. Collectively, our study highlights the importance of studying mRNA splicing events during brain aging.

TopDIA: A Software Tool for Top-Down Data-Independent Acquisition Proteomics

Top-down mass spectrometry is widely used for proteoform identification, characterization, and quantification owing to its ability to analyze intact proteoforms. In the last decade, top-down proteomics has been dominated by top-down data-dependent acquisition mass spectrometry (TD-DDA-MS), and top-down data-independent acquisition mass spectrometry (TD-DIA-MS) has not been well studied. While TD-DIA-MS produces complex multiplexed tandem mass spectrometry (MS/MS) spectra, which are challenging to confidently identify, it selects more precursor ions for MS/MS analysis and has the potential to increase proteoform identifications compared with TD-DDA-MS. Here we present TopDIA, the first software tool for proteoform identification by TD-DIA-MS. It generates demultiplexed pseudo MS/MS spectra from TD-DIA-MS data and then searches the pseudo MS/MS spectra against a protein sequence database for proteoform identification. We compared the performance of TD-DDA-MS and TD-DIA-MS using Escherichia coli K-12 MG1655 cells and demonstrated that TD-DIA-MS with TopDIA increased proteoform and protein identifications compared with TD-DDA-MS.

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.

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

MOTIVATION

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.

RESULTS

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.

AVAILABILITY AND IMPLEMENTATION

The source code of the algorithm is available at https://github.com/Zeirdo/TopMGFast.

Mass Spectrometry Strategies for O-Glycoproteomics

Glycoproteomics has accelerated in recent decades owing to numerous innovations in the analytical workflow. In particular, new mass spectrometry strategies have contributed to inroads in O-glycoproteomics, a field that lags behind N-glycoproteomics due to several unique challenges associated with the complexity of O-glycosylation. This review will focus on progress in sample preparation, enrichment strategies, and MS/MS techniques for the identification and characterization of O-glycoproteins.

Characterisation of the forest cobra (Naja melanoleuca) venom using a multifaceted mass spectrometric-based approach

Snake venoms consist of highly biologically active proteins and peptides that are responsible for the lethal physiological effects of snakebite envenomation. In order to guide the development of targeted antivenom strategies, comprehensive understanding of venom compositions and in-depth characterisation of various proteoforms, often not captured by traditional bottom-up proteomic workflows, is necessary. Here, we employ an integrated 'omics' and intact mass spectrometry (MS)-based approach to profile the heterogeneity within the venom of the forest cobra (Naja melanoleuca), adopting different analytical strategies to accommodate for the dynamic molecular mass range of venom proteins present. The venom proteome of N. melanoleuca was catalogued using a venom gland transcriptome-guided bottom-up proteomics approach, revealing a venom consisting of six toxin superfamilies. The subtle diversity present in the venom components was further explored using reversed phase-ultra performance liquid chromatography (RP-UPLC) coupled to intact MS. This approach showed a significant increase in the number of venom proteoforms within various toxin families that were not captured in previous studies. Furthermore, we probed at the higher-order structures of the larger venom proteins using a combination of native MS and mass photometry and revealed significant structural heterogeneity along with extensive post-translational modifications in the form of glycosylation in these larger toxins. Here, we show the diverse structural heterogeneity of snake venom proteins in the venom of N. melanoleuca using an integrated workflow that incorporates analytical strategies that profile snake venom at the proteoform level, complementing traditional venom characterisation approaches.

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.

Top-Down Proteomics and the Challenges of True Proteoform Characterization

Top-down proteomics (TDP) aims to identify and profile intact protein forms (proteoforms) extracted from biological samples. True proteoform characterization requires that both the base protein sequence be defined and any mass shifts identified, ideally localizing their positions within the protein sequence. Being able to fully elucidate proteoform profiles lends insight into characterizing proteoform-unique roles, and is a crucial aspect of defining protein structure-function relationships and the specific roles of different (combinations of) protein modifications. However, defining and pinpointing protein post-translational modifications (PTMs) on intact proteins remains a challenge. Characterization of (heavily) modified proteins (>∼30 kDa) remains problematic, especially when they exist in a population of similarly modified, or kindred, proteoforms. This issue is compounded as the number of modifications increases, and thus the number of theoretical combinations. Here, we present our perspective on the challenges of analyzing kindred proteoform populations, focusing on annotation of protein modifications on an "average" protein. Furthermore, we discuss the technical requirements to obtain high quality fragmentation spectral data to robustly define site-specific PTMs, and the fact that this is tempered by the time requirements necessary to separate proteoforms in advance of mass spectrometry analysis.

Spatial -omics technologies: the new enterprise in 3D breast cancer models

The fields of tissue bioengineering, -omics, and spatial biology are advancing rapidly, each offering the opportunity for a paradigm shift in breast cancer research. However, to date, collaboration between these fields has not reached its full potential. In this review, we describe the most recently generated 3D breast cancer models regarding the biomaterials and technological platforms employed. Additionally, their biological evaluation is reported, highlighting their advantages and limitations. Specifically, we focus on the most up-to-date -omics and spatial biology techniques, which can generate a deeper understanding of the biological relevance of bioengineered 3D breast cancer in vitro models, thus paving the way towards truly clinically relevant microphysiological systems, improved drug development success rates, and personalised medicine approaches.

Food allergen detection by mass spectrometry: From common to novel protein ingredients

Food allergens are molecules, mainly proteins, that trigger immune responses in susceptible individuals upon consumption even when they would otherwise be harmless. Symptoms of a food allergy can range from mild to acute; this last effect is a severe and potentially life-threatening reaction. The European Union (EU) has identified 14 common food allergens, but new allergens are likely to emerge with constantly changing food habits. Mass spectrometry (MS) is a promising alternative to traditional antibody-based assays for quantifying multiple allergenic proteins in complex matrices with high sensitivity and selectivity. Here, the main allergenic proteins and the advantages and drawbacks of some MS acquisition protocols, such as multiple reaction monitoring (MRM) and data-dependent analysis (DDA) for identifying and quantifying common allergenic proteins in processed foodstuffs are summarized. Sections dedicated to novel foods like microalgae and insects as new sources of allergenic proteins are included, emphasizing the significance of establishing stable marker peptides and validated methods using database searches. The discussion involves the in-silico digestion of allergenic proteins, providing insights into their potential impact on immunogenicity. Finally, case studies focussing on microalgae highlight the value of MS as an effective analytical tool for ensuring regulatory compliance throughout the food control chain.

Orbitrap Mass Spectrometry and High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Enable the in-Depth Analysis of Human Serum Proteoforms

Blood serum and plasma are arguably the most commonly analyzed clinical samples, with dozens of proteins serving as validated biomarkers for various human diseases. Top-down proteomics may provide additional insights into disease etiopathogenesis since this approach focuses on protein forms, or proteoforms, originally circulating in blood, potentially providing access to information about relevant post-translational modifications, truncations, single amino acid substitutions, and many other sources of protein variation. However, the vast majority of proteomic studies on serum and plasma are carried out using peptide-centric, bottom-up approaches that cannot recapitulate the original proteoform content of samples. Clinical laboratories have been slow to adopt top-down analysis, also due to higher sample handling requirements. In this study, we describe a straightforward protocol for intact proteoform sample preparation based on the depletion of albumin and immunoglobulins, followed by simplified protein fractionation via polyacrylamide gel electrophoresis. After molecular weight-based fractionation, we supplemented the traditional liquid chromatography-tandem mass spectrometry (LC-MS2) data acquisition with high-field asymmetric waveform ion mobility spectrometry (FAIMS) to further simplify serum proteoform mixtures. This LC-FAIMS-MS2 method led to the identification of over 1000 serum proteoforms < 30 kDa, outperforming traditional LC-MS2 data acquisition and more than doubling the number of proteoforms identified in previous studies.

Top-Down Proteomics of Mouse Islets With Beta Cell CPE Deletion Reveals Molecular Details in Prohormone Processing

Altered prohormone processing, such as with proinsulin and pro-islet amyloid polypeptide (proIAPP), has been reported as an important feature of prediabetes and diabetes. Proinsulin processing includes removal of several C-terminal basic amino acids and is performed principally by the exopeptidase carboxypeptidase E (CPE), and mutations in CPE or other prohormone convertase enzymes (PC1/3 and PC2) result in hyperproinsulinemia. A comprehensive characterization of the forms and quantities of improperly processed insulin and other hormone products following Cpe deletion in pancreatic islets has yet to be attempted. In the present study we applied top-down proteomics to globally evaluate the numerous proteoforms of hormone processing intermediates in a β-cell-specific Cpe knockout mouse model. Increases in dibasic residue-containing proinsulin and other novel proteoforms of improperly processed proinsulin were found, and we could classify several processed proteoforms as novel substrates of CPE. Interestingly, some other known substrates of CPE remained unaffected despite its deletion, implying that paralogous processing enzymes such as carboxypeptidase D (CPD) can compensate for CPE loss and maintain near normal levels of hormone processing. In summary, our quantitative results from top-down proteomics of islets provide unique insights into the complexity of hormone processing products and the regulatory mechanisms.

Characterization of Unbranched Ubiquitin Tetramers by Combining Ultraviolet Photodissociation with Proton Transfer Charge Reduction Reactions

Polyubiquitination is an important post-translational modification (PTM) that regulates various biological functions. The linkage sites and topologies of polyubiquitination chains are important factors in determining the fate of polyubiquitinated proteins. Characterization of polyubiquitin chains is the first step in understanding the biological functions of protein ubiquitination, but it is challenging owing to the repeating nature of the ubiquitin chains and the difficulty in deciphering linkage positions. Here, we combine ultraviolet photodissociation (UVPD) mass spectrometry and gas-phase proton transfer charge reduction (PTCR) to facilitate the assignment of product ions generated from Lys6-, Lys11-, Lys29-, Lys33-, Lys48-, and Lys63-linked ubiquitin tetramers. UVPD results in extensive fragmentation of intact proteins in a manner that allows the localization of PTMs. However, UVPD mass spectra of large proteins (>30 kDa) are often congested due to the overlapping isotopic distribution of highly charged fragment ions. UVPD + PTCR improved the identification of PTM-containing fragment ions, allowing the localization of linkage sites in all six tetramers analyzed. UVPD + PTCR also increased the sequence coverage obtained from the PTM-containing fragment ions in each of the four chains of each tetramer by 7 to 44% when compared to UVPD alone.

Study of β1-transferrin and β2-transferrin using microprobe-capture in-emitter elution and high-resolution mass spectrometry

Cerebrospinal fluid (CSF) leak can be diagnosed in clinical laboratories by detecting a diagnostic marker β2-transferrin (β2-Tf) in secretion samples. β2-Tf and the typical transferrin (Tf) proteoform in serum, β1-transferrin (β1-Tf), are Tf glycoforms. An innovative affinity capture technique for sample preparation, called microprobe-capture in-emitter elution (MPIE), was incorporated with high-resolution mass spectrometry (HR-MS) to study the Tf glycoforms and the primary structures of β1-Tf and β2-Tf. To implement MPIE, an analyte is first captured on the surface of a microprobe, and subsequently eluted from the microprobe inside an electrospray emitter. The capture process is monitored in real-time via next-generation biolayer interferometry (BLI). When electrospray is established from the emitter to a mass spectrometer, the analyte is immediately ionized via electrospray ionization (ESI) for HR-MS analysis. Serum, CSF, and secretion samples were analyzed using MPIE-ESI-MS. Based on the MPIE-ESI-MS results, the primary structures of β1-Tf and β2-Tf were elucidated. As Tf glycoforms, β1-Tf and β2-Tf share the amino acid sequence but contain varying N-glycans: (1) β1-Tf, the major serum-type Tf, has two G2S2 N-glycans on Asn413 and Asn611; and (2) β2-Tf, the major brain-type Tf, has an M5 N-glycan on Asn413 and a G0FB N-glycan on Asn611. The resolving power of the innovative MPIE-ESI-MS method was demonstrated in the study of β2-Tf as well as β1-Tf. Knowing the N-glycan structures on β2-Tf allows for the design of more novel test methods for β2-Tf in the future.

Exploiting ion-mobility mass spectrometry for unraveling proteome complexity

Ion mobility spectrometry-mass spectrometry (IMS-MS) is experiencing rapid growth in proteomic studies, driven by its enhancements in dynamic range and throughput, increasing the quantitation precision, and the depth of proteome coverage. The core principle of ion mobility spectrometry is to separate ions in an inert gas under the influence of an electric field based on differences in drift time. This minireview provides an introduction to IMS operation modes and a description of advantages and limitations is presented. Moreover, the principles of trapped IMS-MS (TIMS-MS), including parallel accumulation-serial fragmentation are discussed. Finally, emerging applications linked to TIMS focusing on sample throughput (in clinical proteomics) and sensitivity (single-cell proteomics) are reviewed, and the possibilities of intact protein analysis are discussed.

Top-down mass spectrometry of native proteoforms and their complexes: A community study

The combination of native electrospray ionisation with top-down fragmentation in mass spectrometry allows simultaneous determination of the stoichiometry of noncovalent complexes and identification of their component proteoforms and co-factors. While this approach is powerful, both native mass spectrometry and top-down mass spectrometry are not yet well standardised, and only a limited number of laboratories regularly carry out this type of research. To address this challenge, the Consortium for Top-Down Proteomics (CTDP) initiated a study to develop and test protocols for native mass spectrometry combined with top-down fragmentation of proteins and protein complexes across eleven instruments in nine laboratories. The outcomes are summarised in this report to provide robust benchmarks and a valuable entry point for the scientific community.

Top-down proteomics of myosin light chain isoforms define chamber-specific expression in the human heart

Myosin functions as the "molecular motor" of the sarcomere and generates the contractile force necessary for cardiac muscle contraction. Myosin light chains 1 and 2 (MLC-1 and -2) play important functional roles in regulating the structure of the hexameric myosin molecule. Each of these light chains has an 'atrial' and 'ventricular' isoform, so called because they are believed to exhibit chamber-restricted expression in the heart. However, recently the chamber-specific expression of MLC isoforms in the human heart has been questioned. Herein, we analyzed the expression of MLC-1 and -2 atrial and ventricular isoforms in each of the four cardiac chambers in adult non-failing donor hearts using top-down mass spectrometry (MS)-based proteomics. Strikingly, we detected an isoform thought to be ventricular, MLC-2v (gene: MYL2), in the atria and confirmed the protein sequence using tandem MS (MS/MS). For the first time, a putative deamidation post-translation modification (PTM) located on MLC-2v in atrial tissue was localized to amino acid N13. MLC-1v (MYL3) and MLC-2a (MYL7) were the only MLC isoforms exhibiting chamber-restricted expression patterns across all donor hearts. Importantly, our results unambiguously show that MLC-1v, not MLC-2v, is ventricle-specific in adult human hearts. Moreover, we found elevated MLC-2 phosphorylation in male hearts compared to female hearts across each cardiac chamber. Overall, top-down proteomics allowed an unbiased analysis of MLC isoform expression throughout the human heart, uncovering previously unexpected isoform expression patterns and PTMs.

Multidimensional Separations in Top-Down Proteomics

Top-down proteomics (TDP) identifies, quantifies, and characterizes proteins at the intact proteoform level in complex biological samples to understand proteoform function and cellular mechanisms. However, analyzing complex biological samples using TDP is still challenging due to high sample complexity and wide dynamic range. High-resolution separation methods are often applied prior to mass spectrometry (MS) analysis to decrease sample complexity and increase proteomics throughput. These separation methods, however, may not be efficient enough to characterize low abundance intact proteins in complex samples. As such, multidimensional separation techniques (combination of two or more separation methods with high orthogonality) have been developed and applied that demonstrate improved separation resolution and more comprehensive identification in TDP. A suite of multidimensional separation methods that couple various types of liquid chromatography (LC), capillary electrophoresis (CE), and/or gel electrophoresis-based separation approaches have been developed and applied in TDP to analyze complex biological samples. Here, we reviewed multidimensional separation strategies employed for TDP, summarized current applications, and discussed the gaps that may be addressed in the future.

TopFD: A Proteoform Feature Detection Tool for Top-Down Proteomics

Top-down liquid chromatography-mass spectrometry (LC-MS) analyzes intact proteoforms and generates mass spectra containing peaks of proteoforms with various isotopic compositions, charge states, and retention times. An essential step in top-down MS data analysis is proteoform feature detection, which aims to group these peaks into peak sets (features), each containing all peaks of a proteoform. Accurate protein feature detection enhances the accuracy in MS-based proteoform identification and quantification. Here, we present TopFD, a software tool for top-down MS feature detection that integrates algorithms for proteoform feature detection, feature boundary refinement, and machine learning models for proteoform feature evaluation. We performed extensive benchmarking of TopFD, ProMex, FlashDeconv, and Xtract using seven top-down MS data sets and demonstrated that TopFD outperforms other tools in feature accuracy, reproducibility, and feature abundance reproducibility.

High sensitivity top-down proteomics captures single muscle cell heterogeneity in large proteoforms

Single-cell proteomics has emerged as a powerful method to characterize cellular phenotypic heterogeneity and the cell-specific functional networks underlying biological processes. However, significant challenges remain in single-cell proteomics for the analysis of proteoforms arising from genetic mutations, alternative splicing, and post-translational modifications. Herein, we have developed a highly sensitive functionally integrated top-down proteomics method for the comprehensive analysis of proteoforms from single cells. We applied this method to single muscle fibers (SMFs) to resolve their heterogeneous functional and proteomic properties at the single-cell level. Notably, we have detected single-cell heterogeneity in large proteoforms (>200 kDa) from the SMFs. Using SMFs obtained from three functionally distinct muscles, we found fiber-to-fiber heterogeneity among the sarcomeric proteoforms which can be related to the functional heterogeneity. Importantly, we detected multiple isoforms of myosin heavy chain (~223 kDa), a motor protein that drives muscle contraction, with high reproducibility to enable the classification of individual fiber types. This study reveals single muscle cell heterogeneity in large proteoforms and establishes a direct relationship between sarcomeric proteoforms and muscle fiber types, highlighting the potential of top-down proteomics for uncovering the molecular underpinnings of cell-to-cell variation in complex systems.

Posttranslational-modifications of human-serum-albumin analysis by a top-down approach validated by a comprehensive bottom-up analysis

The posttranslational modifications (PTM) of human serum albumin (HSA) can result in the development of isoforms that have been identified as potential biomarkers for advanced hepatic diseases. However, previous approaches using top-down (TD) analysis to identify isoforms based on molecular weight may have resulted in misidentifications. The nature of the identified isoforms has never been confirmed in previous works. Here, we aimed to critically evaluate TD for the characterization and determination of HSA isoforms in patients and make an inventory of HSA-PTM. Serum samples from control subjects and patients with liver dysfunctions were analyzed using both top-down (TD) and bottom-up (BU) approaches. TD analysis involved using a LC-TOF-MS system to obtain a multicharged spectrum of HSA, which was deconvoluted to identify isoforms. Spectra were then used for relative quantitation analysis of albumin isoform abundances based on trapezoidal integration. For BU analysis, serums were reduced +/- alkylated, digested with trypsin and analyzed in the Q-TOF, data-dependent acquisition (DDA) mode to generate a SWATH-MS high-resolution mass spectral library of all HSA peptides. Tryptic digests of another set of serum samples were then analyzed using data-independent acquisition (DIA) mode to confirm the presence of HSA isoforms and their modification sites. TD detected 15 isoforms corresponding to various modifications, including glycation, cysteinylation, nitrosylation, and oxidation (di- and tri-). In BU, the spectral library containing 127 peptides allowed for the characterization of the important isoforms with their modified sites, including some modifications that were only characterized in BU (carbamylation, deamidation, and amino-acid substitution). The method used for determining isoforms offered acceptable reproducibility (intra-/inter-assay CVs < 15%) for all isoforms present at relative abundances higher than 2%. Overall, the study found that several isoforms could be missed or misidentified by TD. However, all HSA isoforms identified by TD and reported to be relevant in liver dysfunctions were confirmed by BU. This critical evaluation of TD approach helped design an adequate and reliable method for the characterization of HSA isoforms in patients and offers the possibility to estimate isoform abundances within 3 min. These findings have significant implications for the diagnosis and treatment of liver dysfunctions.

Critical considerations in N-glycoproteomics

N-Glycoproteomics, the system-wide study of glycans asparagine-linked to protein carriers, holds a unique and still largely untapped potential to provide deep insights into the complexity and dynamics of the heterogeneous N-glycoproteome. Despite the advent of innovative analytical and informatics tools aiding the analysis, N-glycoproteomics remains challenging and consequently largely restricted to specialised laboratories. Aiming to stimulate discussions of method harmonisation, data standardisation and reporting guidelines to make N-glycoproteomics more reproducible and accessible to the community, we here discuss critical considerations related to the design and execution of N-glycoproteomics experiments and highlight good practices in N-glycopeptide data collection, analysis, interpretation and sharing. Giving the rapid maturation and, expectedly, a wide-spread implementation of N-glycoproteomics capabilities across the community in future years, this piece aims to point out common pitfalls, to encourage good data sharing and documentation practices, and to highlight practical solutions and strategies to enhance the insight into the N-glycoproteome.

Recent advances in top-down proteome sample processing ahead of MS analysis

Top-down proteomics is emerging as a preferred approach to investigate biological systems, with objectives ranging from the detailed assessment of a single protein therapeutic, to the complete characterization of every possible protein including their modifications, which define the human proteoform. Given the controlling influence of protein modifications on their biological function, understanding how gene products manifest or respond to disease is most precisely achieved by characterization at the intact protein level. Top-down mass spectrometry (MS) analysis of proteins entails unique challenges associated with processing whole proteins while maintaining their integrity throughout the processes of extraction, enrichment, purification, and fractionation. Recent advances in each of these critical front-end preparation processes, including minimalistic workflows, have greatly expanded the capacity of MS for top-down proteome analysis. Acknowledging the many contributions in MS technology and sample processing, the present review aims to highlight the diverse strategies that have forged a pathway for top-down proteomics. We comprehensively discuss the evolution of front-end workflows that today facilitate optimal characterization of proteoform-driven biology, including a brief description of the clinical applications that have motivated these impactful contributions.

Top-down Proteomics of Myosin Light Chain Isoforms Define Chamber-Specific Expression in the Human Heart

Myosin functions as the "molecular motor" of the sarcomere and generates the contractile force necessary for cardiac muscle contraction. Myosin light chains 1 and 2 (MLC-1 and -2) play important functional roles in regulating the structure of the hexameric myosin molecule. Each of these light chains has an "atrial" and "ventricular" isoform, so called because they are believed to exhibit chamber-restricted expression in the heart. However, recently the chamber-specific expression of MLC isoforms in the human heart has been questioned. Herein, we analyzed the expression of MLC-1 and -2 atrial and ventricular isoforms in each of the four cardiac chambers in adult non-failing donor hearts using top-down mass spectrometry (MS)-based proteomics. Strikingly, we detected an isoform thought to be ventricular, MLC-2v, in the atria and confirmed the protein sequence using tandem MS (MS/MS). For the first time, a putative deamidation post-translation modification (PTM) located on MLC-2v in atrial tissue was localized to amino acid N13. MLC-1v and MLC-2a were the only MLC isoforms exhibiting chamber-restricted expression patterns across all donor hearts. Importantly, our results unambiguously show that MLC-1v, not MLC-2v, is ventricle-specific in adult human hearts. Overall, top-down proteomics allowed us an unbiased analysis of MLC isoform expression throughout the human heart, uncovering previously unexpected isoform expression patterns and PTMs.

Fiber-Type Shifting in Sarcopenia of Old Age: Proteomic Profiling of the Contractile Apparatus of Skeletal Muscles

The progressive loss of skeletal muscle mass and concomitant reduction in contractile strength plays a central role in frailty syndrome. Age-related neuronal impairments are closely associated with sarcopenia in the elderly, which is characterized by severe muscular atrophy that can considerably lessen the overall quality of life at old age. Mass-spectrometry-based proteomic surveys of senescent human skeletal muscles, as well as animal models of sarcopenia, have decisively improved our understanding of the molecular and cellular consequences of muscular atrophy and associated fiber-type shifting during aging. This review outlines the mass spectrometric identification of proteome-wide changes in atrophying skeletal muscles, with a focus on contractile proteins as potential markers of changes in fiber-type distribution patterns. The observed trend of fast-to-slow transitions in individual human skeletal muscles during the aging process is most likely linked to a preferential susceptibility of fast-twitching muscle fibers to muscular atrophy. Studies with senescent animal models, including mostly aged rodent skeletal muscles, have confirmed fiber-type shifting. The proteomic analysis of fast versus slow isoforms of key contractile proteins, such as myosin heavy chains, myosin light chains, actins, troponins and tropomyosins, suggests them as suitable bioanalytical tools of fiber-type transitions during aging.

Nonionic, Cleavable Surfactant for Top-Down Proteomics

Nonionic surfactants are often used as general reagents for cell lysis enabling protein extraction, stabilization, and purification under nondenaturing conditions for downstream analysis in structural biology. However, the presence of surfactants in the sample matrix often has a deleterious effect on electrospray ionization (ESI)-mass spectrometry (MS) analysis of proteins and complexes. Here, we report a nonionic, cleavable surfactant, n-decyl-disulfide-β-D-maltoside (DSSM), for top-down proteomics. DSSM was designed to mimic the properties of one of the most common surfactants used in structural biology, n-dodecyl-β-D-maltoside (DDM), but contains a disulfide bond that allows for facile cleavage and surfactant removal before or during MS analysis. We have shown that DSSM is compatible with direct electrospray ionization (ESI)-MS analysis and reversed-phase liquid chromatography (RPLC)-MS analysis of proteins and protein complexes. We have demonstrated that DSSM can facilitate top-down proteomic characterization of membrane proteins such as a model ion channel protein and a G protein-coupled receptor as well as endogenous proteins from cell lysates for the determination of sequence variations and posttranslational modifications (PTMs). Conceivably, DSSM could serve as a general replacement for DDM in proteomic experiments and structural biology studies.

Chromatographic separation of peptides and proteins for characterization of proteomes

Characterization of proteomes aims to comprehensively characterize proteins in cells or tissues via two main strategies: (1) bottom-up strategy based on the separation and identification of enzymatic peptides; (2) top-down strategy based on the separation and identification of intact proteins. However, it is challenged by the high complexity of proteomes. Consequently, the improvements in peptide and protein separation technologies for simplifying the sample should be critical. In this feature article, separation columns for peptide and protein separation were introduced, and peptide separation technologies for bottom-up proteomic analysis as well as protein separation technologies for top-down proteomic analysis were summarized. The achievement, recent development, limitation and future trends are discussed. Besides, the outlook on challenges and future directions of chromatographic separation in the field of proteomics was also presented.

Identification of Subproteomic Markers for Skeletal Muscle Profiling

The biochemical and cell biological profiling of contractile fiber types and subcellular structures plays a central role in basic and applied myology. Mass spectrometry-based proteomics presents an ideal approach for the systematic identification of proteomic and subproteomic markers. These representative components of fast versus slow muscle fibers and their subcellular fractions are highly useful for in-depth surveys of skeletal muscle adaptations to physiological challenges, as well as the improvement of diagnostic, prognostic, and therapy-monitoring methodologies in muscle pathology. This chapter outlines the identification of subproteomic markers for skeletal muscle profiling based on bottom-up and top-down approaches, including fluorescence two-dimensional difference gel electrophoresis (2D-DIGE).

Top-Down Proteomics and Comparative 2D-DIGE Analysis

The combination of large-scale protein separation techniques, sophisticated mass spectrometry, and systems bioinformatics has led to the establishment of proteomics as a distinct discipline within the wider field of protein biochemistry. Both discovery proteomics and targeted proteomics are widely used in biological and biomedical research, whereby the analytical approaches can be broadly divided into proteoform-centric top-down proteomics versus peptide-centric bottom-up proteomics. This chapter outlines the scientific value of top-down proteomics and describes how fluorescence two-dimensional difference gel electrophoresis can be combined with the systematic analysis of crucial post-translational modifications. The concept of on-membrane digestion following the electrophoretic transfer of proteins and the usefulness of comparative two-dimensional immunoblotting are discussed.

Emerging chemistry and biology in protein glutathionylation

Protein S-glutathionylation serves a regulatory role in proteins and modulates distinct biological processes implicated in health and diseases. Despite challenges in analyzing the dynamic and reversible nature of S-glutathionylation, recent chemical and biological methods have significantly advanced the field of S-glutathionylation, culminating in selective identification and detection, structural motif analysis, and functional studies of S-glutathionylation. This review will highlight emerging studies of protein glutathionylation, beginning by introducing biochemical tools that enable mass spectrometric identification and live-cell imaging of S-glutathionylation. Next, it will spotlight recent examples of S-glutathionylation regulating physiology and inflammation. Lastly, we will feature two emerging lines of glutathionylation research in cryptic cysteine glutathionylation and protein C-glutathionylation.

Envemind: Accurate Monoisotopic Mass Determination Based On Isotopic Envelope

Nowadays, monoisotopic mass is used as an important feature in top-down proteomics. Knowing the exact monoisotopic mass is helpful for precise and quick protein identification in large protein databases. However, only in spectra of small molecules the monoisotopic peak is visible. For bigger molecules like proteins, it is hidden in noise or undetected at all, and therefore its position has to be predicted. By improving the prediction of the peak, we contribute to a more accurate identification of molecules, which is crucial in fields such as chemistry and medicine. In this work, we present the envemind algorithm, which is a two-step procedure to predict monoisotopic masses of proteins. The prediction is based on an isotopic envelope. Therefore, envemind is dedicated to spectra where we are able to resolve the one dalton separated isotopic variants. Furthermore, only single-molecule spectra are allowed, that is, spectra that do not require prior deconvolution. The algorithm deals with the problem of off-by-one dalton errors, which are common in monoisotopic mass prediction. A novel aspect of this work is a mathematical exploration of the space of molecules, where we equate chemical formulas and their theoretical spectrum. Since the space of molecules consists of all possible chemical formulas, this approach is not limited to known substances only. This makes optimization processes faster and enables to approximate theoretical spectrum for a given experimental one. The algorithm is available as a Python package envemind on our GitHub page https://github.com/PiotrRadzinski/envemind.

Distinct core glycan and O-glycoform utilization of SARS-CoV-2 Omicron variant Spike protein RBD revealed by top-down mass spectrometry

The SARS-CoV-2 Omicron (B.1.1.529) variant possesses numerous spike (S) mutations particularly in the S receptor-binding domain (S-RBD) that significantly improve transmissibility and evasion of neutralizing antibodies. But exactly how the mutations in the Omicron variant enhance viral escape from immunological protection remains to be understood. The S-RBD remains the principal target for neutralizing antibodies and therapeutics, thus new structural insights into the Omicron S-RBD and characterization of the post-translational glycosylation changes can inform rational design of vaccines and therapeutics. Here we report the molecular variations and O-glycoform changes of the Omicron S-RBD variant as compared to wild-type (WA1/2020) and Delta (B.1.617.2) variants using high-resolution top-down mass spectrometry (MS). A novel O-glycosite (Thr376) unique to the Omicron variant is identified. Moreover, we have directly quantified the Core 1 and Core 2 O-glycan structures and characterized the O-glycoform structural heterogeneity of the three variants. Our findings reveal high resolution detail of Omicron O-glycoforms and their utilization to provide direct molecular evidence of proteoform alterations in the Omicron variant which could shed light on how this variant escapes immunological protection.

FLASHIda enables intelligent data acquisition for top-down proteomics to boost proteoform identification counts

The detailed analysis and structural characterization of proteoforms by top-down proteomics (TDP) has gained a lot of interest in biomedical research. Data-dependent acquisition (DDA) of intact proteins is non-trivial due to the diversity and complexity of proteoforms. Dedicated acquisition methods thus have the potential to greatly improve TDP. Here, we present FLASHIda, an intelligent online data acquisition algorithm for TDP that ensures the real-time selection of high-quality precursors of diverse proteoforms. FLASHIda combines fast charge deconvolution algorithms and machine learning-based quality assessment for optimal precursor selection. In an analysis of E. coli lysate, FLASHIda increases the number of unique proteoform level identifications from 800 to 1500 or generates a near-identical number of identifications in one third of the instrument time when compared to standard DDA mode. Furthermore, FLASHIda enables sensitive mapping of post-translational modifications and detection of chemical adducts. As a software extension module to the instrument, FLASHIda can be readily adopted for TDP studies of complex samples to enhance proteoform identification rates.

Data acquisition suitable for top-down proteomics (TDP) has the potential to significantly improve proteoform analysis. Here, the authors present FLASHIda, an intelligent online data acquisition algorithm for TDP that nearly doubles the number of proteoform-level identifications in complex samples.

The Crucial Step in Every Analytical Workflow: Sample Preparation—Are We Ready For a Growing Area of Intact Protein Analysis?

Proteins are biomolecules with a lot of essential functions in a human body. Their varied expression during complex disorders, including cancer, predicts their potential use as biomarkers. Therefore, there is a need for reliable analytical workflows for their analysis in complex biological matrices. Despite the very sensitive and advanced instrumentation we have available for protein analysis today, sample preparation still remains one of the biggest challenges.

Native top-down mass spectrometry for higher-order structural characterization of proteins and complexes

Progress in structural biology research has led to a high demand for powerful and yet complementary analytical tools for structural characterization of proteins and protein complexes. This demand has significantly increased interest in native mass spectrometry (nMS), particularly native top-down mass spectrometry (nTDMS) in the past decade. This review highlights recent advances in nTDMS for structural research of biological assemblies, with a particular focus on the extra multi-layers of information enabled by TDMS. We include a short introduction of sample preparation and ionization to nMS, tandem fragmentation techniques as well as mass analyzers and software/analysis pipelines used for nTDMS. We highlight unique structural information offered by nTDMS and examples of its broad range of applications in proteins, protein-ligand interactions (metal, cofactor/drug, DNA/RNA, and protein), therapeutic antibodies and antigen-antibody complexes, membrane proteins, macromolecular machineries (ribosome, nucleosome, proteosome, and viruses), to endogenous protein complexes. The challenges, potential, along with perspectives of nTDMS methods for the analysis of proteins and protein assemblies in recombinant and biological samples are discussed.

Distinct Core Glycan and O-Glycoform Utilization of SARS-CoV-2 Omicron Variant Spike Protein RBD Revealed by Top-Down Mass Spectrometry

The SARS-CoV-2 Omicron (B.1.1.529) variant possesses numerous spike (S) mutations particularly in the S receptor-binding domain (S-RBD) that significantly improve transmissibility and evasion of neutralizing antibodies. But exactly how the mutations in the Omicron variant enhance viral escape from immunological protection remains to be understood. The S-RBD remains the principal target for neutralizing antibodies and therapeutics, thus new structural insights into the Omicron S-RBD and characterization of the post-translational glycosylation changes can inform rational design of vaccines and therapeutics. Here we report the molecular variations and O-glycoform changes of the Omicron S-RBD variant as compared to wild-type (WA1/2020) and Delta (B.1.617.2) variants using high-resolution top-down mass spectrometry (MS). A novel O-glycosite (Thr376) unique to the Omicron variant is identified. Moreover, we have directly quantified the Core 1 and Core 2 O-glycan structures and characterized the O-glycoform structural heterogeneity of the three variants. Our findings reveal high resolution detail of Omicron O-glycoforms and their utilization to provide direct molecular evidence of proteoform alterations in the Omicron variant which could shed light on how this variant escapes immunological protection.

Ethane-Bridged Hybrid Monolithic Column with Large Mesopores for Boosting Top-Down Proteomic Analysis

Top-down proteomics is challenged by the high complexity of biological samples. The coelution of intact proteins results in overlapped mass spectra, and hence, an increased peak capacity for protein separation is needed. Herein, ethane-bridged hybrid monoliths with well-defined large mesopores were successfully prepared based on the sol-gel condensation of 1,2-bis(trimethoxysilyl)ethane and tetramethoxysilane, followed by two-step base etching of the Si-O-Si domain while maintaining the Si-C-C-Si domain in the structure. Relatively homogeneous macropores of 1.1 μm and large mesopores of 24 nm were obtained, permitting fast mass transfer of large molecules and efficient diffusion without obstruction. The use of less hydrophobic C1 ligand further sharpened the peak shape and improved peak capacity. A 120 cm-long capillary column was used for top-down proteomic analysis of E. coli lysates under low backpressure with 16 MPa. High peak capacity of 646 was achieved within 240 min gradient. With MS/MS analysis, 959 proteoforms corresponding to 263 proteins could be unambiguously identified from E. coli lysates in a single run. Furthermore, to illustrate the separation performance for large proteoforms, such monoliths were applied to top-down analysis of the SEC fraction of E. coli lysates with Mw ranging from 30 to 70 kDa. With highly effective separation, 347 large proteoforms with Mw higher than 30 kDa were detected in the single 75 min run. These results showed great potential for top-down proteomic analysis in complex samples.

Investigating Toxin Diversity and Abundance in Snake Venom Proteomes

Understanding snake venom proteomes is becoming increasingly important to understand snake venom biology, evolution and especially clinical effects of venoms and approaches to antivenom development. To explore the current state of snake venom proteomics and transcriptomics we investigated venom proteomic methods, associations between methodological and biological variability and the diversity and abundance of protein families. We reviewed available studies on snake venom proteomes from September 2017 to April 2021. This included 81 studies characterising venom proteomes of 79 snake species, providing data on relative toxin abundance for 70 species and toxin diversity (number of different toxins) for 37 species. Methodologies utilised in these studies were summarised and compared. Several comparative studies showed that preliminary decomplexation of crude venom by chromatography leads to increased protein identification, as does the use of transcriptomics. Combining different methodological strategies in venomic approaches appears to maximize proteome coverage. 48% of studies used the RP-HPLC →1D SDS-PAGE →in-gel trypsin digestion → ESI -LC-MS/MS pathway. Protein quantification by MS1-based spectral intensity was used twice as commonly as MS2-based spectral counting (33–15 studies). Total toxin diversity was 25–225 toxins/species, with a median of 48. The relative mean abundance of the four dominant protein families was for elapids; 3FTx–52%, PLA₂–27%, SVMP–2.8%, and SVSP–0.1%, and for vipers: 3FTx–0.5%, PLA₂–24%, SVMP–27%, and SVSP–12%. Viper venoms were compositionally more complex than elapid venoms in terms of number of protein families making up most of the venom, in contrast, elapid venoms were made up of fewer, but more toxin diverse, protein families. No relationship was observed between relative toxin diversity and abundance. For equivalent comparisons to be made between studies, there is a need to clarify the differences between methodological approaches and for acceptance of a standardised protein classification, nomenclature and reporting procedure. Correctly measuring and comparing toxin diversity and abundance is essential for understanding biological, clinical and evolutionary implications of snake venom composition.

The Blood Proteoform Atlas: A reference map of proteoforms in human hematopoietic cells

Human biology is tightly linked to proteins, yet most measurements do not precisely determine alternatively spliced sequences or posttranslational modifications. Here, we present the primary structures of ~30,000 unique proteoforms, nearly 10 times more than in previous studies, expressed from 1690 human genes across 21 cell types and plasma from human blood and bone marrow. The results, compiled in the Blood Proteoform Atlas (BPA), indicate that proteoforms better describe protein-level biology and are more specific indicators of differentiation than their corresponding proteins, which are more broadly expressed across cell types. We demonstrate the potential for clinical application, by interrogating the BPA in the context of liver transplantation and identifying cell and proteoform signatures that distinguish normal graft function from acute rejection and other causes of graft dysfunction.

Accurate Proteoform Identification and Quantitation Using pTop 2.0

The remarkable advancement of top-down proteomics in the past decade is driven by the technological development in separation, mass spectrometry (MS) instrumentation, novel fragmentation, and bioinformatics. However, the accurate identification and quantification of proteoforms, all clearly-defined molecular forms of protein products from a single gene, remain a challenging computational task. This is in part due to the complicated mass spectra from intact proteoforms when compared to those from the digested peptides. Herein, pTop 2.0 is developed to fill in the gap between the large-scale complex top-down MS data and the shortage of high-accuracy bioinformatic tools. Compared with pTop 1.0, the first version, pTop 2.0 concentrates mainly on the identification of the proteoforms with unexpected modifications or a terminal truncation. The quantitation based on isotopic labeling is also a new function, which can be carried out by the convenient and user-friendly "one-key operation," integrated together with the qualitative identifications. The accuracy and running speed of pTop 2.0 is significantly improved on the test data sets. This chapter will introduce the main features, step-by-step running operations, and algorithmic developments of pTop 2.0 in order to push the identification and quantitation of intact proteoforms to a higher-accuracy level in top-down proteomics.

Size Exclusion Chromatography Strategies and MASH Explorer for Large Proteoform Characterization

Top-down mass spectrometry (MS)-based analysis of larger proteoforms (>50 kDa) is typically challenging due to an exponential decay in the signal-to-noise ratio with increasing protein molecular weight (MW) and coelution with low-MW proteoforms. Size exclusion chromatography (SEC) fractionates proteins based on their size, separating larger proteoforms from those of smaller size in the proteome. In this protocol, we initially describe the use of SEC to fractionate high-MW proteoforms from low-MW proteoforms. Subsequently, the SEC fractions containing the proteoforms of interest are subjected to reverse-phase liquid chromatography (RPLC) coupled online with high-resolution MS. Finally, proteoforms are characterized using MASH Explorer, a user-friendly software environment for in-depth proteoform characterization.

A Direct MS-Based Approach to Profile Human Milk Secretory Immunoglobulin A (IgA1) Reveals Donor-Specific Clonal Repertoires With High Longitudinal Stability

Recently, a mass spectrometry-based approach was introduced to directly assess the IgG1 immunoglobulin clonal repertoires in plasma. Here we expanded upon this approach by describing a mass spectrometry-based technique to assess specifically the clonal repertoire of another important class of immunoglobulin molecules, IgA1, and show it is efficiently and robustly applicable to either milk or plasma samples. Focusing on two individual healthy donors, whose milk was sampled longitudinally during the first 16 weeks of lactation, we demonstrate that the total repertoire of milk sIgA1 is dominated by only 50-500 clones, even though the human body theoretically can generate several orders of magnitude more clones. We show that in each donor the sIgA1 repertoire only changes marginally and quite gradually over the monitored 16-week period of lactation. Furthermore, the observed overlap in clonal repertoires between the two individual donors is close to non-existent. Mothers provide protection to their newborn infants directly by the transfer of antibodies via breastfeeding. The approach introduced here, can be used to visualize the clonal repertoire transferred from mother to infant and to detect changes in-time in that repertoire adapting to changes in maternal physiology.

Online μSEC2-nRPLC-MS for Improved Sensitivity of Intact Protein Detection of IEF-Separated Nonhuman Primate Cerebrospinal Fluid Proteins

Proteoform-resolved information, obtained by top-down (TD) "intact protein" proteomics, is expected to contribute substantially to the understanding of molecular pathogenic mechanisms and, in turn, identify novel therapeutic and diagnostic targets. However, the robustness of mass spectrometry (MS) analysis of intact proteins in complex biological samples is hindered by the high dynamic range in protein concentration and mass, protein instability, and buffer complexity. Here, we describe an evolutionary step for intact protein investigations through the online implementation of tandem microflow size-exclusion chromatography with nanoflow reversed-phase liquid chromatography and MS (μSEC2-nRPLC-MS). Online serial high-/low-pass SEC filtration overcomes the aforementioned hurdles to intact proteomic analysis through automated sample desalting/cleanup and enrichment of target mass ranges (5-155 kDa) prior to nRPLC-MS. The coupling of μSEC to nRPLC is achieved through a novel injection volume control (IVC) strategy of inserting protein trap columns, pre- and post-μSEC columns, to enable injection of dilute samples in high volumes without loss of sensitivity or resolution. Critical characteristics of the approach are tested via rigorous investigations on samples of varied complexity and chemical background. Application of the platform to cerebrospinal fluid (CSF) prefractionated by OFFGEL isoelectric focusing drastically increases the number of intact mass tags (IMTs) detected within the target mass range (5-30 kDa) in comparison to one-dimensional nRPLC-MS with approximately 100× less CSF than previous OFFGEL studies. Furthermore, the modular design of the μSEC2-nRPLC-MS platform is robust and promises significant flexibility for large-scale TDMS analysis of diverse samples either directly or in concert with other multidimensional fractionation steps.

Proteomic Analysis of the Functional Inward Rectifier Potassium Channel (Kir) 2.1 Reveals Several Novel Phosphorylation Sites

Membrane proteins represent a large family of proteins that perform vital physiological roles and represent key drug targets. Despite their importance, bioanalytical methods aiming to comprehensively characterize the post-translational modification (PTM) of membrane proteins remain challenging compared to other classes of proteins in part because of their inherent low expression and hydrophobicity. The inward rectifier potassium channel (Kir) 2.1, an integral membrane protein, is critical for the maintenance of the resting membrane potential and phase-3 repolarization of the cardiac action potential in the heart. The importance of this channel to cardiac physiology is highlighted by the recognition of several sudden arrhythmic death syndromes, Andersen-Tawil and short QT syndromes, which are associated with loss or gain of function mutations in Kir2.1, often triggered by changes in the β-adrenergic tone. Therefore, understanding the PTMs of this channel (particularly β-adrenergic tone-driven phosphorylation) is important for arrhythmia prevention. Here, we developed a proteomic method, integrating both top-down (intact protein) and bottom-up (after enzymatic digestion) proteomic analyses, to characterize the PTMs of recombinant wild-type and mutant Kir2.1, successfully mapping five novel sites of phosphorylation and confirming a sixth site. Our study provides a framework for future work to assess the role of PTMs in regulating Kir2.1 functions.