Quantitative Top-Down Proteomics in Complex Samples Using Protein-Level Tandem Mass Tag Labeling

Proteomic study of vitreous in proliferative diabetic retinopathy patients after treatment with aflibercept: a quantitative analysis based on 4D label-free technique

AIM

To identify different metabolites, proteins and related pathways to elucidate the causes of proliferative diabetic retinopathy (PDR) and resistance to anti-vascular endothelial growth factor (VEGF) drugs, and to provide biomarkers for the diagnosis and treatment of PDR.

METHODS

Vitreous specimens from patients with diabetic retinopathy were collected and analyzed by Liquid Chromatography-Mass Spectrometry (LC-MS/MS) analyses based on 4D label-free technology. Statistically differentially expressed proteins (DEPs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway representation and protein interactions were analyzed.

RESULTS

A total of 12 samples were analyzed. The proteomics results showed that a total of 58 proteins were identified as DEPs, of which 47 proteins were up-regulated and 11 proteins were down-regulated. We found that C1q and tumor necrosis factor related protein 5 (C1QTNF5), Clusterin (CLU), tissue inhibitor of metal protease 1 (TIMP1) and signal regulatory protein alpha (SIRPα) can all be specifically regulated after aflibercept treatment. GO functional analysis showed that some DEPs are related to changes in inflammatory regulatory pathways caused by PDR. In addition, protein-protein interaction (PPI) network evaluation revealed that TIMP1 plays a central role in neural regulation. In addition, CD47/SIRPα may become a key target to resolve anti-VEGF drug resistance in PDR.

CONCLUSION

Proteomic analysis is an approach of choice to explore the molecular mechanisms of PDR. Our data show that multiple proteins are differentially changed in PDR patients after intravitreal injection of aflibercept, among which C1QTNF5, CLU, TIMP1 and SIRPα may become targets for future treatment of PDR and resolution of anti-VEGF resistance.

Targeted Quantification of Proteoforms in Complex Samples by Proteoform Reaction Monitoring

Existing mass spectrometric assays used for sensitive and specific measurements of target proteins across multiple samples, such as selected/multiple reaction monitoring (SRM/MRM) or parallel reaction monitoring (PRM), are peptide-based methods for bottom-up proteomics. Here, we describe an approach based on the principle of PRM for the measurement of intact proteoforms by targeted top-down proteomics, termed proteoform reaction monitoring (PfRM). We explore the ability of our method to circumvent traditional limitations of top-down proteomics, such as sensitivity and reproducibility. We also introduce a new software program, Proteoform Finder (part of ProSight Native), specifically designed for the easy analysis of PfRM data. PfRM was initially benchmarked by quantifying three standard proteins. The linearity of the assay was shown over almost 3 orders of magnitude in the femtomole range, with limits of detection and quantification in the low femtomolar range. We later applied our multiplexed PfRM assay to complex samples to quantify biomarker candidates in peripheral blood mononuclear cells (PBMCs) from liver-transplanted patients, suggesting their possible translational applications. These results demonstrate that PfRM has the potential to contribute to the accurate quantification of protein biomarkers for diagnostic purposes and to improve our understanding of disease etiology at the proteoform level.

Precursor deconvolution error estimation: The missing puzzle piece in false discovery rate in top-down proteomics

Top-down proteomics (TDP) directly analyzes intact proteins and thus provides more comprehensive qualitative and quantitative proteoform-level information than conventional bottom-up proteomics (BUP) that relies on digested peptides and protein inference. While significant advancements have been made in TDP in sample preparation, separation, instrumentation, and data analysis, reliable and reproducible data analysis still remains one of the major bottlenecks in TDP. A key step for robust data analysis is the establishment of an objective estimation of proteoform-level false discovery rate (FDR) in proteoform identification. The most widely used FDR estimation scheme is based on the target-decoy approach (TDA), which has primarily been established for BUP. We present evidence that the TDA-based FDR estimation may not work at the proteoform-level due to an overlooked factor, namely the erroneous deconvolution of precursor masses, which leads to incorrect FDR estimation. We argue that the conventional TDA-based FDR in proteoform identification is in fact protein-level FDR rather than proteoform-level FDR unless precursor deconvolution error rate is taken into account. To address this issue, we propose a formula to correct for proteoform-level FDR bias by combining TDA-based FDR and precursor deconvolution error rate.

Characterizing Age-related Changes in Intact Mitochondrial Proteoforms in Murine Hearts using Quantitative Top-Down Proteomics

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and the prevalence of CVDs increases markedly with age. Due to the high energetic demand, the heart is highly sensitive to mitochondrial dysfunction. The complexity of the cardiac mitochondrial proteome hinders the development of effective strategies that target mitochondrial dysfunction in CVDs. Mammalian mitochondria are composed of over 1000 proteins, most of which can undergo post-translational protein modifications (PTMs). Top-down proteomics is a powerful technique for characterizing and quantifying all protein sequence variations and PTMs. However, there are still knowledge gaps in the study of age-related mitochondrial proteoform changes using this technique. In this study, we used top-down proteomics to identify intact mitochondrial proteoforms in young and old hearts and determined changes in protein abundance and PTMs in cardiac aging.

METHODS

Intact mitochondria were isolated from the hearts of young (4-month-old) and old (24-25-month-old) mice. The mitochondria were lysed, and mitochondrial lysates were subjected to denaturation, reduction, and alkylation. For quantitative top-down analysis, there were 12 runs in total arising from 3 biological replicates in two conditions, with technical duplicates for each sample. The collected top-down datasets were deconvoluted and quantified, and then the proteoforms were identified.

RESULTS

From a total of 12 LC-MS/MS runs, we identified 134 unique mitochondrial proteins in the different sub-mitochondrial compartments (OMM, IMS, IMM, matrix). 823 unique proteoforms in different mass ranges were identified. Compared to cardiac mitochondria of young mice, 7 proteoforms exhibited increased abundance and 13 proteoforms exhibited decreased abundance in cardiac mitochondria of old mice. Our analysis also detected PTMs of mitochondrial proteoforms, including N-terminal acetylation, lysine succinylation, lysine acetylation, oxidation, and phosphorylation.

CONCLUSION

By combining mitochondrial protein enrichment using mitochondrial fractionation with quantitative top-down analysis using ultrahigh-pressure liquid chromatography (UPLC)-MS and label-free quantitation, we successfully identified and quantified intact proteoforms in the complex mitochondrial proteome. Using this approach, we detected age-related changes in abundance and PTMs of mitochondrial proteoforms in the heart.

Biological mass spectrometry enables spatiotemporal 'omics: From tissues to cells to organelles

Biological processes unfold across broad spatial and temporal dimensions, and measurement of the underlying molecular world is essential to their understanding. Interdisciplinary efforts advanced mass spectrometry (MS) into a tour de force for assessing virtually all levels of the molecular architecture, some in exquisite detection sensitivity and scalability in space-time. In this review, we offer vignettes of milestones in technology innovations that ushered sample collection and processing, chemical separation, ionization, and 'omics analyses to progressively finer resolutions in the realms of tissue biopsies and limited cell populations, single cells, and subcellular organelles. Also highlighted are methodologies that empowered the acquisition and analysis of multidimensional MS data sets to reveal proteomes, peptidomes, and metabolomes in ever-deepening coverage in these limited and dynamic specimens. In pursuit of richer knowledge of biological processes, we discuss efforts pioneering the integration of orthogonal approaches from molecular and functional studies, both within and beyond MS. With established and emerging community-wide efforts ensuring scientific rigor and reproducibility, spatiotemporal MS emerged as an exciting and powerful resource to study biological systems in space-time.

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.

Proteomic studies on apoB-containing lipoprotein in cardiovascular research: A comprehensive review

The complexity of cardiovascular diseases (CVDs), which remains the leading cause of death worldwide, makes the current clinical pathway for cardiovascular risk assessment unsatisfactory, as there remains a substantial unexplained residual risk. Simultaneous assessment of a large number of plasma proteins may be a promising tool to further refine risk assessment, and lipoprotein-associated proteins have the potential to fill this gap. Technical advances now allow for high-throughput proteomic analysis in a reproducible and cost-effective manner. Proteomics has great potential to identify and quantify hundreds of candidate marker proteins in a sample and allows the translation from isolated lipoproteins to whole plasma, thus providing an individual multiplexed proteomic fingerprint. This narrative review describes the pathophysiological roles of atherogenic apoB-containing lipoproteins and the recent advances in their mass spectrometry-based proteomic characterization and quantitation for better refinement of CVD risk assessment.

Establishing 20S Proteasome Genetic, Translational and Post-Translational Status from Precious Biological and Patient Samples with Top-Down MS

The mammalian 20S catalytic core of the proteasome is made of 14 different subunits (α1-7 and β1-7) but exists as different subtypes depending on the cell type. In immune cells, for instance, constitutive catalytic proteasome subunits can be replaced by the so-called immuno-catalytic subunits, giving rise to the immunoproteasome. Proteasome activity is also altered by post-translational modifications (PTMs) and by genetic variants. Immunochemical methods are commonly used to investigate these PTMs whereby protein-tagging is necessary to monitor their effect on 20S assembly. Here, we present a new miniaturized workflow combining top-down and bottom-up mass spectrometry of immunopurified 20S proteasomes that analyze the proteasome assembly status as well as the full proteoform footprint, revealing PTMs, mutations, single nucleotide polymorphisms (SNPs) and induction of immune-subunits in different biological samples, including organoids, biopsies and B-lymphoblastoid cell lines derived from patients with proteasome-associated autoinflammatory syndromes (PRAAS). We emphasize the benefits of using top-down mass spectrometry in preserving the endogenous conformation of protein modifications, while enabling a rapid turnaround (1 h run) and ensuring high sensitivity (1–2 pmol) and demonstrate its capacity to semi-quantify constitutive and immune proteasome subunits.

Proteoforms expand the world of microproteins and short open reading frame-encoded peptides

Microproteins and short open reading frame-encoded peptides (SEPs) can, like all proteins, carry numerous posttranslational modifications. Together with posttranscriptional processes, this leads to a high number of possible distinct protein molecules, the proteoforms, out of a limited number of genes. The identification, quantification, and molecular characterization of proteoforms possess special challenges to established, mainly bottom-up proteomics (BUP) based analytical approaches. While BUP methods are powerful, proteins have to be inferred rather than directly identified, which hampers the detection of proteoforms. An alternative approach is top-down proteomics (TDP) which allows to identify intact proteoforms. This perspective article provides a brief overview of modified microproteins and SEPs, introduces the proteoform terminology, and compares present BUP and TDP workflows highlighting their major advantages and caveats. Necessary future developments in TDP to fully accentuate its potential for proteoform-centric analytics of microproteins and SEPs will be discussed.

Optimization of Higher-Energy Collisional Dissociation Fragmentation Energy for Intact Protein-Level Tandem Mass Tag Labeling

Isobaric chemical tag labeling (e.g., TMT) is a commonly used approach in quantitative proteomics, and quantification is enabled through detection of low-mass reporter ions generated after MS2 fragmentation. Recently, we have introduced and optimized an intact protein-level TMT labeling platform that demonstrated >90% labeling efficiency in complex samples with top-down proteomics. Higher-energy collisional dissociation (HCD) is commonly utilized for isobaric tag-labeled peptide fragmentation because it produces accurate reporter ion intensities and avoids loss of low mass ions. HCD energies have been optimized for isobaric tag labeled-peptides but have not been systematically evaluated for isobaric tag-labeled intact proteins. In this study, we report a systematic evaluation of normalized HCD fragmentation energies (NCEs) on TMT-labeled HeLa cell lysate using top-down proteomics. Our results suggested that reporter ions often result in higher ion intensities at higher NCEs. Optimal fragmentation of intact proteins for identification, however, required relatively lower NCE. We further demonstrated that a stepped NCE scheme with energies from 30% to 50% resulted in optimal quantification and identification of TMT-labeled HeLa proteins. These parameters resulted in an average reporter ion intensity of ∼4E4 and average proteoform spectrum matches (PrSMs) of >1000 per RPLC-MS/MS run with a 1% false discovery rate (FDR) cutoff.

Middle-Down Mass Spectrometry Reveals Activity-Modifying Phosphorylation Barcode in a Class C G Protein-Coupled Receptor

G protein-coupled receptors (GPCRs) are the largest family of membrane receptors in humans. They mediate nearly all aspects of human physiology and thus are of high therapeutic interest. GPCR signaling is regulated in space and time by receptor phosphorylation. It is believed that different phosphorylation states are possible for a single receptor, and each encodes for unique signaling outcomes. Methods to determine the phosphorylation status of GPCRs are critical for understanding receptor physiology and signaling properties of GPCR ligands and therapeutics. However, common proteomic techniques have provided limited quantitative information regarding total receptor phosphorylation stoichiometry, relative abundances of isomeric modification states, and temporal dynamics of these parameters. Here, we report a novel middle-down proteomic strategy and parallel reaction monitoring (PRM) to quantify the phosphorylation states of the C-terminal tail of metabotropic glutamate receptor 2 (mGluR2). By this approach, we found that mGluR2 is subject to both basal and agonist-induced phosphorylation at up to four simultaneous sites with varying probability. Using a PRM tandem mass spectrometry methodology, we localized the positions and quantified the relative abundance of phosphorylations following treatment with an agonist. Our analysis showed that phosphorylation within specific regions of the C-terminal tail of mGluR2 is sensitive to receptor activation, and subsequent site-directed mutagenesis of these sites identified key regions which tune receptor sensitivity. This study demonstrates that middle-down purification followed by label-free quantification is a powerful, quantitative, and accessible tool for characterizing phosphorylation states of GPCRs and other challenging proteins.

Decreased histidine-rich glycoprotein and increased complement C4-B protein levels in follicular fluid predict the IVF outcomes of recurrent spontaneous abortion

BACKGROUND

Recurrent spontaneous abortion (RSA) is a common and complicated pregnancy-related disease that lacks a suitable biomarker to predict its recrudescence.

METHODS

Tandem mass tag (TMT) analysis was conducted to obtain quantitative proteomic profiles in follicular fluid from patients with a history of RSA and from control group. ELISA validation of candidate differentially expressed proteins was conducted in a larger group of patients.

RESULTS

A total of 836 proteins were identified by TMT analysis; 51 were upregulated and 47 were downregulated in follicular fluid from cases of RSA versus control group. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis revealed several important pathways were enriched, involving a dysregulated immunoglobulin Fc receptor signaling pathway and overactivated complement cascade pathways. ELISA validated the differential expression of two proteins, histidine-rich globulin (HRG) and complement C4-B (C4B), which were downregulated and upregulated, respectively, in follicular fluid of patients with RSA. We performed receiver operating characteristic curve analysis of the ELISA results with the outcomes of current IVF cycles as classification variables. The area under the curve results for HRG alone, C4B alone and HRG-C4B combined were 0.785, 0.710 and 0.895, respectively.

CONCLUSIONS

TMT analysis identified 98 differentially expressed proteins in follicular fluid from patients with RSA, indicating follicle factors that act as early warning factors for the occurrence of RSA. Among them, HRG and C4B provide candidate markers to predict the clinical outcomes of IVF/ICSI cycles, and the potential for modeling an early detection system for RSA.

Seeing the complete picture: proteins in top-down mass spectrometry

Top-down protein mass spectrometry can provide unique insights into protein sequence and structure, including precise proteoform identification and study of protein–ligand and protein–protein interactions. In contrast with the commonly applied bottom-up approach, top-down approaches do not include digestion of the protein of interest into small peptides, but instead rely on the ionization and subsequent fragmentation of intact proteins. As such, it is fundamentally the only way to fully characterize the composition of a proteoform. Here, we provide an overview of how a top-down protein mass spectrometry experiment is performed and point out recent applications from the literature to the reader. While some parts of the top-down workflow are broadly applicable, different research questions are best addressed with specific experimental designs. The most important divide is between studies that prioritize sequence information (i.e., proteoform identification) versus structural information (e.g., conformational studies, or mapping protein–protein or protein–ligand interactions). Another important consideration is whether to work under native or denaturing solution conditions, and the overall complexity of the sample also needs to be taken into account, as it determines whether (chromatographic) separation is required prior to MS analysis. In this review, we aim to provide enough information to support both newcomers and more experienced readers in the decision process of how to answer a potential research question most efficiently and to provide an overview of the methods that exist to answer these questions.

Effects and mechanisms of decabromodiphenyl ethane on Chlorella sorokiniana: Transcriptomics, proteins and fatty acid production

Decabromodiphenyl ethane is a novel brominated flame retardant, that has always been dissolved in organic solvents to explore its activities on aquatic organisms. In this study, the influences of decabromodiphenyl ethane on the microalga Chlorella sorokiniana (C. sorokiniana) were studied, and three microalgae treatments, including decabromodiphenyl ethane dissolved in dimethyl sulfoxide solvent (DBDPE treatment), dimethyl sulfoxide alone (control II) or untreated (control I) were used in the experiment, respectively. The results showed that the growth of C. sorokiniana was remarkably enhanced in the DBDPE treatment compared with the control I and II groups. Conjoint analysis of transcriptomics and quantitative proteome displayed that the upregulated differentially expressed genes and proteins of DBDPE:control I were enriched in 6 pathways, and downregulated genes/proteins of DBDPE:control I were enriched in 3 pathways. The upregulated differentially expressed genes and proteins of DBDPE:control II were enriched in 4 pathways, and downregulated genes/proteins of DBDPE:control II were enriched in 6 pathways. In addition, decabromodiphenyl ethane changed the fatty acid concentration in C. sorokiniana cells. The activities of superoxide dismutase were enhanced when C. sorokiniana were treated by decabromodiphenyl ethane. The data highlighted that the mRNA and protein expression relating to the fatty acid production, of C. sorokiniana were significantly affected by decabromodiphenyl ethane, and decabromodiphenyl ethane pollution changed the physiological metabolism of microalgae and had harmful effects on natural environments.

Tandem mass tag-based proteomics analysis reveals the multitarget mechanisms of Phyllanthus emblica against liver fibrosis

Phyllanthus emblica (PE), a traditional multiethnic herbal medicine, is commonly applied to treat liver diseases. Our previous study demonstrated that aqueous extract of PE (AEPE) could alleviate carbon tetrachloride (CCl₄)-induced liver fibrosis in vivo, but the underlying molecular mechanisms are still unclear. The present study was undertaken to clarify the multitarget mechanisms of PE in treating liver fibrosis by proteomics clues. A CCl₄-induced liver fibrosis rat model was established. The anti-liver fibrosis effects of chemical fractions from AEPE were evaluated by serum biochemical indicators and pathological staining. Additionally, tandem mass tag (TMT) - based quantitative proteomics technology was used to detect the hepatic differentially expressed proteins (DEPs). The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, gene ontology (GO) enrichment and protein-protein interaction (PPI) network were used to perform bioinformatics analysis of DEPs. Western blot analysis was used to verify the key potential targets regulated by the effective fraction of AEPE. The low-molecular-weight fraction of AEPE (LWPE) was determined to be the optimal anti-liver fibrosis active fraction, that could significantly improve ALT, AST, HA, Col IV, PCIII, LN, Hyp levels and reduce the pathological fibrotic lesion of liver tissue in model rats. A total of 195 DEPs were screened after LWPE intervention. GO analysis showed that the DEPs were related mostly to extracellular matrix organization, actin binding, and extracellular exosomes. KEGG pathway analysis showed that DEPs are mainly related to ECM-receptor interactions, focal adhesion and PI3K-Akt signaling pathway. Combined with the GO, KEGG and Western blot results, COL1A2, ITGAV, TLR2, ACE, and PDGFRB may be potential targets for PE treatment of liver fibrosis. In conclusion, LWPE exerts therapeutic effects through multiple pathways and multiple targets regulation in the treatment of liver fibrosis. This study may provide proteomics clues for the continuation of research on liver fibrosis treatment with PE.

A benchmarking protocol for intact protein-level Tandem Mass Tag (TMT) labeling for quantitative top-down proteomics

Isobaric chemical tag labeling for quantification of intact proteins in complex samples is limited due to the tendency of intact proteins precipitate under labeling conditions and increased sample complexity as a result of side products (i.e., incomplete labeling or labeling of unintended residues). To reduce precipitation under labeling conditions, we developed a technique to remove large proteoforms that allowed for the labeling and characterization of small proteoforms (<35 kDa) using top-down proteomics. We also systematically optimized protein-level Tandem Mass Tag (TMT) labeling conditions to obtain optimal labeling parameters for complex samples. Here, we present a benchmarking protocol for protein-level TMT labeling for quantitative top-down proteomics, including complex intact protein sample preparation, protein-level TMT labeling, top-down LC/MS analysis, and TMT reporter ion quantification.•

An optimized protocol for protein-level TMT labeling in complex sample.

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Limits production of incorrectly labeled side products for minimization of spectral complexity.

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A guideline for isobaric chemical tag quantification in top-down proteomics.

Recent advances in isobaric labeling and applications in quantitative proteomics

Mass spectrometry (MS) has emerged at the forefront of quantitative proteomic techniques. Liquid chromatography-mass spectrometry (LC-MS) can be used to determine abundances of proteins and peptides in complex biological samples. Several methods have been developed and adapted for accurate quantification based on chemical isotopic labeling. Among various chemical isotopic labeling techniques, isobaric tagging approaches rely on the analysis of peptides from MS2-based quantification rather than MS1-based quantification. In this review, we will provide an overview of several isobaric tags along with some recent developments including complementary ion tags, improvements in sensitive quantitation of analytes with lower abundance, strategies to increase multiplexing capabilities, and targeted analysis strategies. We will also discuss limitations of isobaric tags and approaches to alleviate these restrictions through bioinformatic tools and data acquisition methods. This review will highlight several applications of isobaric tags, including biomarker discovery and validation, thermal proteome profiling, cross-linking for structural investigations, single-cell analysis, top-down proteomics, along with applications to different molecules including neuropeptides, glycans, metabolites, and lipids, while providing considerations and evaluations to each application.

Validation of Top-Down Proteomics Data by Bottom-Up-Based N-Terminomics Reveals Pitfalls in Top-Down-Based Terminomics Workflows

Bottom-up proteomics (BUP)-based N-terminomics techniques have become standard to identify protein N-termini. While these methods rely on the identification of N-terminal peptides only, top-down proteomics (TDP) comes with the promise to provide additional information about post-translational modifications and the respective C-termini. To evaluate the potential of TDP for terminomics, two established TDP workflows were employed for the proteome analysis of the nematode Caenorhabditis elegans. The N-termini of the identified proteoforms were validated using a BUP-based N-terminomics approach. The TDP workflows used here identified 1658 proteoforms, the N-termini of which were verified by BUP in 25% of entities only. Caveats in both the BUP- and TDP-based workflows were shown to contribute to this low overlap. In BUP, the use of trypsin prohibits the detection of arginine-rich or arginine-deficient N-termini, while in TDP, the formation of artificially generated termini was observed in particular in a workflow encompassing sample treatment with high acid concentrations. Furthermore, we demonstrate the applicability of reductive dimethylation in TDP to confirm biological N-termini. Overall, our study shows not only the potential but also current limitations of TDP for terminomics studies and also presents suggestions for future developments, for example, for data quality control, allowing improvement of the detection of protein termini by TDP.

Optimization of protein-level tandem mass tag (TMT) labeling conditions in complex samples with top-down proteomics

Isobaric chemical tag labels (e.g., iTRAQ and TMT) have been extensively utilized as a standard quantification approach in bottom-up proteomics, which provides high multiplexing capacity and enables MS2-level quantification while not complicating the MS1 scans. We recently demonstrated the feasibility of intact protein TMT labeling for the identification and quantification with top-down proteomics of smaller intact proteoforms (<35 kDa) in complex biological samples through the removal of large proteins prior to labeling. Still, the production of side products during TMT labeling (i.e., incomplete labeling or labeling of unintended residues) complicated the analysis of complex protein samples. In this study, we systematically evaluated the protein-level TMT labeling reaction parameters, including TMT-to-protein mass ratio, pH/concentration of quenching buffer, protein concentration, reaction time, and reaction buffer. Our results indicated that: (1) high TMT-to-protein mass ratio (e.g., 8:1, 4:1), (2) high pH/concentration of quenching buffer (pH > 9.1, final hydroxylamine concentration >0.3%), and (3) high protein concentration (e.g., > 1.0 μg/μL) resulted in optimal labeling efficiency and minimized production of over/underlabeled side products. >90% labeling efficiency was achieved for E. coli cell lysate after optimization of protein-level TMT labeling conditions. In addition, a double labeling approach was developed for efficiently labeling limited biological samples with low concentrations. This research provides practical guidance for efficient TMT labeling of complex intact protein samples, which can be readily adopted in the high-throughput quantification top-down proteomics.

Proteoform-Selective Imaging of Tissues Using Mass Spectrometry

Unraveling the complexity of biological systems relies on the development of new approaches for spatially resolved proteoform‐specific analysis of the proteome. Herein, we employ nanospray desorption electrospray ionization mass spectrometry imaging (nano‐DESI MSI) for the proteoform‐selective imaging of biological tissues. Nano‐DESI generates multiply charged protein ions, which is advantageous for their structural characterization using tandem mass spectrometry (MS/MS) directly on the tissue. Proof‐of‐concept experiments demonstrate that nano‐DESI MSI combined with on‐tissue top‐down proteomics is ideally suited for the proteoform‐selective imaging of tissue sections. Using rat brain tissue as a model system, we provide the first evidence of differential proteoform expression in different regions of the brain.

Mass-Encoded Suspension Array for Multiplex Detection of Matrix Metalloproteinase Activities

This work designed a mass spectrometric biosensing strategy for the multiplex detection of matrix metalloproteinases (MMPs) with a mass-encoded suspension array. This array was fabricated as multiplex sensing probes by functionalizing magnetic beads with MMP-specific peptide-isobaric tags for relative and absolute quantification (iTRAQ) conjugates, which contained a hexahistidine tag for surface binding, a substrate region for MMP cleavage, and a coding region for the specific MMP. The integration of the multiplex coding ability of iTRAQ with ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and the proteolysis method for peptide digestion endowed the biosensing method with high throughput and ultrahigh sensitivity. This strategy could be conveniently performed by mixing the sample and the suspension array for enzymatic reactions and then digesting the uncleaved peptides with trypsin to release the coding regions for UPLC-MS/MS analysis. With MMP-2 and MMP-7 as analytes, the relative changes of peak area ratios of coding regions showed good linear responses in the ranges of 0.2-100 and 0.5-400 ng mL^-1, with detection limits of 0.064 and 0.17 ng mL^-1, respectively. The analysis of MMP activity in serum samples and its change responding to inhibitors demonstrated the specificity, practicability, and expansibility of the proposed strategy. This work paves a new avenue for the activity assays of multiplex enzymes and promotes the development of mass spectrometric biosensing.

MSTopDiff: A Tool for the Visualization of Mass Shifts in Deconvoluted Top-Down Proteomics Data for the Database-Independent Detection of Protein Modifications

Top-down proteomics analyzes intact proteoforms with all of their post-translational modifications and genetic and RNA splice variants. In addition, modifications introduced either deliberately or inadvertently during sample preparation, that is, via oxidation, alkylation, or labeling reagents, or through the formation of noncovalent adducts (e.g., detergents) further increase the sample complexity. To facilitate the recognition of protein modifications introduced during top-down analysis, we developed MSTopDiff, a software tool with a graphical user interface written in Python, which allows one to detect protein modifications by calculating and visualizing mass differences in top-down data without the prerequisite of a database search. We demonstrate the successful application of MSTopDiff for the detection of artifacts originating from oxidation, formylation, overlabeling during isobaric labeling, and adduct formation with cations or sodium dodecyl sulfate. MSTopDiff offers several modes of data representation using deconvoluted MS1 or MS2 spectra. In addition to artificial modifications, the tool enables the visualization of biological modifications such as phosphorylation and acetylation. MSTopDiff provides an overview of the artificial and biological modifications in top-down proteomics samples, which makes it a valuable tool in quality control of standard workflows and for parameter evaluation during method development.

Shedding light on both ends: An update on analytical approaches for N- and C-terminomics

Though proteases were long regarded as nonspecific degradative enzymes, over time, it was recognized that they also hydrolyze peptide bonds very specifically with a limited substrate pool. This irreversible posttranslational modification modulates the fate and activity of many proteins, making proteolytic processing a master switch in the regulation of e.g., the immune system, apoptosis and cancer progression. N- and C-terminomics, the identification of protein termini, has become indispensable in elucidating protease substrates and therefore protease function. Further, terminomics has the potential to identify yet unknown proteoforms, e.g. formed by alternative splicing or the recently discovered alternative ORFs. Different strategies and workflows have been developed that achieve higher sensitivity, a greater depth of coverage or higher throughput. In this review, we summarize recent developments in both N- and C-terminomics and include the potential of top-down proteomics which inherently delivers information on both ends of analytes in a single analysis.

Quantitative Top-Down Proteomics by Isobaric Labeling with Thiol-Directed Tandem Mass Tags

While identification-centric (qualitative) top-down proteomics (TDP) has seen rapid progress in the recent past, the quantification of intact proteoforms within complex proteomes is still challenging. The by far mostly applied approach is label-free quantification, which, however, provides limited multiplexing capacity, and its use in combination with multidimensional separation is encountered with a number of problems. Isobaric labeling, which is a standard quantification approach in bottom-up proteomics, circumvents these limitations. Here, we introduce the application of thiol-directed isobaric labeling for quantitative TDP. For this purpose, we analyzed the labeling efficiency and optimized tandem mass spectrometry parameters for optimal backbone fragmentation for identification and reporter ion formation for quantification. Two different separation schemes, gel-eluted liquid fraction entrapment electrophoresis × liquid chromatography-mass spectrometry (LC-MS) and high/low-pH LC-MS, were employed for the analyses of either Escherichia coli (E. coli) proteomes or combined E. coli/yeast samples (two-proteome interference model) to study potential ratio compression. While the thiol-directed labeling introduces a bias in the quantifiable proteoforms, being restricted to Cys-containing proteoforms, our approach showed excellent accuracy in quantification, which is similar to that achievable in bottom-up proteomics. For example, 876 proteoforms could be quantified with high accuracy in an E. coli lysate. The LC-MS data were deposited to the ProteomeXchange with the dataset identifier PXD026310.