Proteolytic 18O labeling for comparative proteomics: model studies with two serotypes of adenovirus

Quantification of snake venom proteomes by mass spectrometry-considerations and perspectives

The advent of soft ionization mass spectrometry-based proteomics in the 1990s led to the development of a new dimension in biology that conceptually allows for the integral analysis of whole proteomes. This transition from a reductionist to a global-integrative approach is conditioned to the capability of proteomic platforms to generate and analyze complete qualitative and quantitative proteomics data. Paradoxically, the underlying analytical technique, molecular mass spectrometry, is inherently nonquantitative. The turn of the century witnessed the development of analytical strategies to endow proteomics with the ability to quantify proteomes of model organisms in the sense of "an organism for which comprehensive molecular (genomic and/or transcriptomic) resources are available." This essay presents an overview of the strategies and the lights and shadows of the most popular quantification methods highlighting the common misuse of label-free approaches developed for model species' when applied to quantify the individual components of proteomes of nonmodel species (In this essay we use the term "non-model" organisms for species lacking comprehensive molecular (genomic and/or transcriptomic) resources, a circumstance that, as we detail in this review-essay, conditions the quantification of their proteomes.). We also point out the opportunity of combining elemental and molecular mass spectrometry systems into a hybrid instrumental configuration for the parallel identification and absolute quantification of venom proteomes. The successful application of this novel mass spectrometry configuration in snake venomics represents a proof-of-concept for a broader and more routine application of hybrid elemental/molecular mass spectrometry setups in other areas of the proteomics field, such as phosphoproteomics, metallomics, and in general in any biological process where a heteroatom (i.e., any atom other than C, H, O, N) forms integral part of its mechanism.

Identification of Proteomic Biomarkers of Acetaminophen-Induced Hepatotoxicity Using Stable Isotope Labeling

Quantitative proteomics approaches based on stable isotopic labeling and mass spectrometry have been widely applied to disease research, drug target discovery, biomarker identification, and systems biology. One of the notable stable isotopic labeling approaches is trypsin-catalyzed 18O/16O labeling, which has its own advantages of low sample consumption, simple labeling procedure, cost-effectiveness, and absence of chemical reactions that potentially generate by-products. In this chapter, a protocol for 18O/16O labeling-based quantitative proteomics approach is described with an application to the identification of proteomic biomarkers of acetaminophen (APAP)-induced hepatotoxicity in rats. The protocol involves first the extraction of proteins from liver tissues of control and APAP-treated rats and digestion into peptides by trypsin. After cleaning of the peptides by solid-phase extraction, equal amounts of peptides from the APAP treatment and the control groups are then subject to trypsin-catalyzed 18O/16O labeling. The labeled peptides are combined and fractionated by off-line strong cation exchange liquid chromatography (SCXLC), and each fraction is then analyzed by nanoflow reversed-phase LC coupled online with tandem mass spectrometry (RPLC-MS/MS) for identification and quantification of differential protein expression between APAP-treated rats and controls. The protocol is applicable to quantitative proteomic analysis for a variety of biological samples.

Recent applications of quantitative mass spectrometry in biopharmaceutical process development and manufacturing

Biopharmaceutical products have seen rapid growth over the past few decades and continue to dominate the global pharmaceutical market. Aligning with the quality by design (QbD) framework and realization, recent advances in liquid chromatography-mass spectrometry (LC-MS) instrumentation and related techniques have enhanced biopharmaceutical characterization capabilities and have supported an increased development of biopharmaceutical products. Beyond its routine qualitative characterization, the quantitative feature of LC-MS has unique applications in biopharmaceutical process development and manufacturing. This review describes the recent applications and implications of the advancement of quantitative MS methods in biopharmaceutical process development, and characterization of biopharmaceutical product, product-related variants, and process-related impurities. We also provide insights on the emerging applications of quantitative MS in the lifecycle of biopharmaceutical product development including quality control in the Good Manufacturing Practice (GMP) environment and process analytical technology (PAT) practices during process development and manufacturing. Through collaboration with instrument and software vendors and regulatory agencies, we envision broader adoption of phase-appropriate quantitative MS-based methods for the analysis of biopharmaceutical products, which in turn has the potential to enable manufacture of higher quality products for patients.

Reverse-ChIP Techniques for Identifying Locus-Specific Proteomes: A Key Tool in Unlocking the Cancer Regulome

A phenotypic hallmark of cancer is aberrant transcriptional regulation. Transcriptional regulation is controlled by a complicated array of molecular factors, including the presence of transcription factors, the deposition of histone post-translational modifications, and long-range DNA interactions. Determining the molecular identity and function of these various factors is necessary to understand specific aspects of cancer biology and reveal potential therapeutic targets. Regulation of the genome by specific factors is typically studied using chromatin immunoprecipitation followed by sequencing (ChIP-Seq) that identifies genome-wide binding interactions through the use of factor-specific antibodies. A long-standing goal in many laboratories has been the development of a 'reverse-ChIP' approach to identify unknown binding partners at loci of interest. A variety of strategies have been employed to enable the selective biochemical purification of sequence-defined chromatin regions, including single-copy loci, and the subsequent analytical detection of associated proteins. This review covers mass spectrometry techniques that enable quantitative proteomics before providing a survey of approaches toward the development of strategies for the purification of sequence-specific chromatin as a 'reverse-ChIP' technique. A fully realized reverse-ChIP technique holds great potential for identifying cancer-specific targets and the development of personalized therapeutic regimens.

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

Mass spectrometry-based retina proteomics

A subfield of neuroproteomics, retina proteomics has experienced a transformative growth since its inception due to methodological advances in enabling chemical, biochemical, and molecular biology techniques. This review focuses on mass spectrometry's contributions to facilitate mammalian and avian retina proteomics to catalog and quantify retinal protein expressions, determine their posttranslational modifications, as well as its applications to study the proteome of the retina in the context of biology, health and diseases, and therapy developments.

Peptidomics

Peptides are biopolymers, typically consisting of 2-50 amino acids. They are biologically produced by the cellular ribosomal machinery or by non-ribosomal enzymes and, sometimes, other dedicated ligases. Peptides are arranged as linear chains or cycles, and include post-translational modifications, unusual amino acids and stabilizing motifs. Their structure and molecular size render them a unique chemical space, between small molecules and larger proteins. Peptides have important physiological functions as intrinsic signalling molecules, such as neuropeptides and peptide hormones, for cellular or interspecies communication, as toxins to catch prey or as defence molecules to fend off enemies and microorganisms. Clinically, they are gaining popularity as biomarkers or innovative therapeutics; to date there are more than 60 peptide drugs approved and more than 150 in clinical development. The emerging field of peptidomics comprises the comprehensive qualitative and quantitative analysis of the suite of peptides in a biological sample (endogenously produced, or exogenously administered as drugs). Peptidomics employs techniques of genomics, modern proteomics, state-of-the-art analytical chemistry and innovative computational biology, with a specialized set of tools. The complex biological matrices and often low abundance of analytes typically examined in peptidomics experiments require optimized sample preparation and isolation, including in silico analysis. This Primer covers the combination of techniques and workflows needed for peptide discovery and characterization and provides an overview of various biological and clinical applications of peptidomics.

Chemical isotope labeling for quantitative proteomics

Advancements in liquid chromatography and mass spectrometry over the last decades have led to a significant development in mass spectrometry-based proteome quantification approaches. An increasingly attractive strategy is multiplex isotope labeling, which significantly improves the accuracy, precision and throughput of quantitative proteomics in the data-dependent acquisition mode. Isotope labeling-based approaches can be classified into MS1-based and MS2-based quantification. In this review, we give an overview of approaches based on chemical isotope labeling and discuss their principles, benefits, and limitations with the goal to give insights into fundamental questions and provide a useful reference for choosing a method for quantitative proteomics. As a perspective, we discuss the current possibilities and limitations of multiplex, isotope labeling approaches for the data-independent acquisition mode, which is increasing in popularity.

Mass Spectrometry-Based Proteomics Workflows in Cancer Research: The Relevance of Choosing the Right Steps

The qualitative and quantitative evaluation of proteome changes that condition cancer development can be achieved with liquid chromatography-mass spectrometry (LC-MS). LC-MS-based proteomics strategies are carried out according to predesigned workflows that comprise several steps such as sample selection, sample processing including labeling, MS acquisition methods, statistical treatment, and bioinformatics to understand the biological meaning of the findings and set predictive classifiers. As the choice of best options might not be straightforward, we herein review and assess past and current proteomics approaches for the discovery of new cancer biomarkers. Moreover, we review major bioinformatics tools for interpreting and visualizing proteomics results and suggest the most popular machine learning techniques for the selection of predictive biomarkers. Finally, we consider the approximation of proteomics strategies for clinical diagnosis and prognosis by discussing current barriers and proposals to circumvent them.

DeGlyPHER: Highly sensitive site-specific analysis of N-linked glycans on proteins

Traditional mass spectrometry-based glycoproteomic approaches have been widely used for site-specific N-glycoform analysis, but a large amount of starting material is needed to obtain sampling that is representative of the vast diversity of N-glycans on glycoproteins. These methods also often include a complicated workflow and very challenging data analysis. These limitations have prevented glycoproteomics from being adapted to high-throughput platforms, and the sensitivity of the analysis is currently inadequate for elucidating N-glycan heterogeneity in clinical samples. Heavily glycosylated spike proteins of enveloped viruses, recombinantly expressed as potential vaccines, are prime targets for glycoproteomic analysis. Since the immunogenicity of spike proteins may be impacted by their glycosylation patterns, site-specific analysis of N-glycoforms provides critical information for vaccine design. Using recombinantly expressed soluble HIV Env trimer, we describe DeGlyPHER, a modification of our previously reported sequential deglycosylation strategy to yield a "single-pot" process. DeGlyPHER is an ultrasensitive, simple, rapid, robust, and efficient approach for site-specific analysis of protein N-glycoforms, that we developed for analysis of limited quantities of glycoproteins.

Proteomic Analysis of Adenovirus 5 by UHPLC-MS/MS: Development of a Robust and Reproducible Sample Preparation Workflow

Adenoviruses (AdVs) have recently become widely used therapeutic vectors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine. AdVs are large, nonenveloped viruses with an icosahedral capsid formed from several proteins that encloses double-stranded DNA. These proteins are the main components and key players in initial stages of infection by the virus particles, so their heterogeneity and content must be evaluated to ensure product and process consistency. Peptide mapping can provide detailed information on these proteins, e.g., their amino acid sequences and post-translational modifications (PTMs), which is crucial for the development and optimization of the manufacturing processes. However, sample preparation remains the main bottleneck for successful proteomic analysis of the viral proteins (VPs) of AdVs due to their low concentrations and vast stoichiometric ranges. To address this problem, we have developed a fast and efficient protocol for preparing samples for proteomic analysis of VPs of AdV5 that requires no cleaning step prior to liquid chromatography-tandem mass spectrometry (LC-MS/MS). The approach enabled identification of 92% of amino acids in AdV5 VPs on average and quantification of 53 PTMs in a single LC-MS/MS experiment using trypsin protease. The data obtained demonstrate the method's potential utility for supporting the development of novel AdV-based gene therapy products (GTPs).

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.

Mass Spectrometry-Based Proteomics for Biomarker Discovery

Proteomics plays a pivotal role in systems medicine, in which pharmacoproteomics and toxicoproteomics have been developed to address questions related to efficacy and toxicity of drugs. Mass spectrometry is the core technology for quantitative proteomics, providing the capabilities of identification and quantitation of thousands of proteins. The technology has been applied to biomarker discovery and understanding the mechanisms of drug action. Both stable isotope labeling of proteins or peptides and label-free approaches have been incorporated with multidimensional LC separation and tandem mass spectrometry (LC-MS/MS) to increase the coverage and depth of proteome analysis. A protocol of such an approach exemplified by dimethyl labeling in combination with 2D-LC-MS/MS is described. With further development of novel proteomic tools and increase in sample throughput, the full spectrum of mass spectrometry-based proteomic research will greatly advance systems medicine.

Oxygen Isotope Exchange Reaction for Untargeted LC-MS Analysis

LC-MS is a key technique for the identification of small molecules in complex samples. Accurate mass, retention time, and fragmentation spectra from LC-MS experiments are compared to reference values for pure chemical standards. However, this information is often unavailable or insufficient, leading to an assignment to a list of candidates instead of a single hit; therefore, additional features are desired to filter candidates. One such promising feature is the number of specific functional groups of a molecule that can be counted via derivatization or isotope-exchange techniques. Hydrogen/deuterium exchange (HDX) is the most widespread implementation of isotope exchange for mass spectrometry, while oxygen ¹⁶O/¹⁸O exchange is not applied as frequently as HDX. Nevertheless, it is known that some functional groups may be selectively exchanged in ¹⁸O enriched media. Here, we propose an implementation of ¹⁶O/¹⁸O isotope exchange to highlight various functional groups. We evaluated the possibility of using the number of exchanged oxygen atoms as a descriptor to filter database candidates in untargeted LC-MS-based workflows. It was shown that ¹⁶O/¹⁸O exchange provides 62% (median, n = 45) search space reduction for a panel of drug molecules. Additionally, it was demonstrated that studying the fragmentation spectra after ¹⁶O/¹⁸O can aid in eliminating false positives and, in some cases, help to annotate fragments formed with water traces in the collisional cell.

New advances in quantitative proteomics research and current applications in asthma

INTRODUCTION

Asthma is the most common chronic respiratory disease and has been declared a global public health problem by the World Health Organization. Due to the high heterogeneity and complexity, asthma can be classified into different 'phenotypes' and it is still difficult to assess the phenotypes and stages of asthma by traditional methods. In recent years, mass spectrometry-based proteomics studies have made significant progress in sensitivity and accuracy of protein identification and quantitation, and are able to obtain differences in protein expression across samples, which provides new insights into the mechanisms and classification of asthma.

AREAS COVERED

In this article, we summarize research strategies in quantitative proteomics, including labeled, label-free and targeted quantification, and highlight the advantages and disadvantages of each. In addition, new applications of quantitative proteomics and the current status of research in asthma have also been discussed. In this study, online resources such as PubMed and Google Scholar were used for literature retrieval.

EXPERT OPINION

The application of quantitative proteomics in asthma has an important role in identifying asthma subphenotypes, revealing potential pathogenesis and therapeutic targets. But the proteomic studies on asthma are not sufficient, as most of them are in the phase of biomarker discovery.

Comparative Proteomics of Mulberry Leaves at Different Developmental Stages Identify Novel Proteins Function Related to Photosynthesis

Mulberry leaves at different positions are different in photosynthetic rate, nutrient substance and feeding impact to silkworms. Here, we investigated the proteomic differences of the first (L1), sixth (L6), and twentieth (L20) mulberry leaves at different stem positions (from top to the base) using a label-free quantitative proteomics approach. L1 contained less developed photosynthetic apparatus but was more active in protein synthesis. L20 has more channel proteins and oxidoreductases relative to L6. Proteins that detected in all measured leaves were classified into three groups according to their expression patterns in L1, L6, and L20. The protein group that displayed the maximum amount in L6 has the highest possibility that function related to photosynthesis. Nine function unknown proteins belong to this group were further analyzed in the light responsive expression, evolutionary tree and sub-cellular localization analysis. Based on the results, five proteins were suggested to be involved in photosynthesis. Taken together, these results reveal the molecular details of different roles of mulberry leaves at different developmental stages and contribute to the identification of five proteins that might function related to photosynthesis.

Protein complexes and neighborhoods driving autophagy

Autophagy summarizes evolutionarily conserved, intracellular degradation processes targeting cytoplasmic material for lysosomal degradation. These encompass constitutive processes as well as stress responses, which are often found dysregulated in diseases. Autophagy pathways help in the clearance of damaged organelles, protein aggregates and macromolecules, mediating their recycling and maintaining cellular homeostasis. Protein-protein interaction networks contribute to autophagosome biogenesis, substrate loading, vesicular trafficking and fusion, protein translocations across membranes and degradation in lysosomes. Hypothesis-free proteomic approaches tremendously helped in the functional characterization of protein-protein interactions to uncover molecular mechanisms regulating autophagy. In this review, we elaborate on the importance of understanding protein-protein-interactions of varying affinities and on the strengths of mass spectrometry-based proteomic approaches to study these, generating new mechanistic insights into autophagy regulation. We discuss in detail affinity purification approaches and recent developments in proximity labeling coupled to mass spectrometry, which uncovered molecular principles of autophagy mechanisms.Abbreviations: AMPK: AMP-activated protein kinase; AP-MS: affinity purification-mass spectrometry; APEX2: ascorbate peroxidase-2; ATG: autophagy related; BioID: proximity-dependent biotin identification; ER: endoplasmic reticulum; GFP: green fluorescent protein; iTRAQ: isobaric tag for relative and absolute quantification; MS: mass spectrometry; PCA: protein-fragment complementation assay; PL-MS: proximity labeling-mass spectrometry; PtdIns3P: phosphatidylinositol-3-phosphate; PTM: posttranslational modification; PUP-IT: pupylation-based interaction tagging; RFP: red fluorescent protein; SILAC: stable isotope labeling by amino acids in cell culture; TAP: tandem affinity purification; TMT: tandem mass tag.

NHS-Ester Tandem Labeling in One Pot Enables 48-Plex Quantitative Proteomics

Stable-isotope labeling strategies are extensively used for multiplex quantitative proteomics. Hybrid-isotope labeling strategies that combine the use of isotopic mass difference labeling and isobaric tags can greatly increase sample multiplexity. In this work, we present a novel hybrid-isotope labeling approach that we termed NHS-ester tandem labeling in one pot (NETLOP). We first optimized 16-plex isobaric TMTpro labeling of lysine residues followed by 2-plex or 3-plex isotopic mTRAQ labeling of peptide N-termini, both of which with commercially available NHS-ester reactive reagents. We then demonstrated the utility of the NETLOP approach by labeling HeLa cell samples and performing proof-of-principle quantitative 32-plex and 48-plex proteomic analyses, each in a single LC-MS/MS experiment. Compared to current hybrid-isotope labeling methods, our NETLOP approach requires no sample cleanup between different labeling steps to minimize sample loss, induces no retention time shifts that compromise quantification accuracy, can be adapted to other NHS-ester isotopic labeling reagents to further increase multiplexity, and is compatible with samples from any origin in a wide array of biological and clinical proteomics applications.

Tissue Proteomic Approaches to Understand the Pathogenesis of Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) has become a global disease encompassing a group of progressive disorders characterized by recurrent chronic inflammation of the gut with variable disease courses and complications. Despite recent advances in the knowledge of IBD pathophysiology, the elucidation of its etiopathology and progression is far from fully understood, requiring complex and multiple approaches. Therefore, limited clinical progress in diagnosis, assessment of disease activity, and optimal therapeutic regimens have been made over the past few decades. This review explores recent advances and challenges in tissue proteomics with an emphasis on biomarker discovery and better understanding of the molecular mechanisms underlying IBD pathogenesis. Future multi-omic studies are required for the comprehensive molecular characterization of disease biology in real time with a future impact on early detection, disease monitoring, and prediction of the clinical outcome.

Recent advances in proteomics and its implications in pituitary endocrine disorders

Pituitary adenoma is considered as one of the most frequent intracranial tumors having salient impact on human health such as mass effects, hypopituitarism and visual defects etc. During the past few decades, there has been enormous advancement in mass spectrometry (MS)-based proteomics. However, very little is known about the molecular pathogenesis of pituitary adenomas in the context of proteomics. In this review article, we have focused on the provenance of pituitary tumors and their pathogenesis with the help of MS-based proteomics approaches. Recent advancements in quantitative proteomic approaches are outlined here that would be useful in the near pituitary adenoma proteomics research. This review discusses the enormous potential of pituitary adenomas research through proteomics with a common aim of deciphering disease pathobiology and identifying the work done in studying pituitary tumors during past decade.

Multiplexed imaging mass spectrometry of the extracellular matrix using serial enzyme digests from formalin-fixed paraffin-embedded tissue sections

We report a multiplexed imaging mass spectrometry method which spatially localizes and selectively accesses the extracellular matrix on formalin-fixed paraffin-embedded tissue sections. The extracellular matrix (ECM) consists of (1) fibrous proteins, post-translationally modified (PTM) via N- and O-linked glycosylation, as well as hydroxylation on prolines and lysines, and (2) glycosaminoglycan-decorated proteoglycans. Accessing all these components poses a unique analytical challenge. Conventional peptide analysis via trypsin inefficiently captures ECM peptides due to their low abundance, intra- and intermolecular cross-linking, and PTMs. In previous studies, we have developed matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS) techniques to capture collagen peptides via collagenase type III digestion, both alone and after N-glycan removal via PNGaseF digest. However, in fibrotic tissues, the buildup of ECM components other than collagen-type proteins, including elastin and glycosaminoglycans, limits efficacy of any single enzyme to access the complex ECM. Here, we have developed a novel serial enzyme strategy to define the extracellular matrix, including PTMs, from a single tissue section for MALDI-IMS applications. Graphical Abstract.

Understanding the pathway and kinetics of aspartic acid isomerization in peptide mapping methods for monoclonal antibodies

Isomerization of aspartic acid (Asp) in therapeutic proteins could lead to safety and efficacy concerns. Thus, accurate quantitation of various Asp isomerization along with kinetic understanding of the variant formations is needed to ensure optimal process development and sufficient product quality control. In this study, we first observed Asp-succinimide conversion in complementarity-determining regions (CDRs) Asp-Gly motif of a recombinant mAb through ion exchange chromatography, intact protein analysis by mass spectrometry, and LC-MS/MS. Then, we developed a specific peptide mapping method, with optimized sample digestion conditions, to accurately quantitate Asp-succinimide-isoAsp variants at peptide level without method-induced isomerization. Various kinetics of Asp-succinimide-isoAsp isomerization pathways were elucidated using ¹⁸O labeling followed by LC-MS analysis. Molecular modeling and molecular dynamic simulation provide additional insight on the kinetics of Asp-succinimide formation and stability of succinimide intermediate. Findings of this work shed light on the molecular construct and the kinetics of the formation of isoAsp and succinimide in peptides and proteins, which facilitates analytical method development, protein engineering, and late phase development for commercialization of therapeutic proteins.

Why and how to investigate the role of protein phosphorylation in ZIP and ZnT zinc transporter activity and regulation

Zinc is required for the regulation of proliferation, metabolism, and cell signaling. It is an intracellular second messenger, and the cellular level of ionic, mobile zinc is strictly controlled by zinc transporters. In mammals, zinc homeostasis is primarily regulated by ZIP and ZnT zinc transporters. The importance of these transporters is underscored by the list of diseases resulting from changes in transporter expression and activity. However, despite numerous structural studies of the transporters revealing both zinc binding sites and motifs important for transporter function, the exact molecular mechanisms regulating ZIP and ZnT activities are still not clear. For example, protein phosphorylation was found to regulate ZIP7 activity resulting in the release of Zn2+ from intracellular stores leading to phosphorylation of tyrosine kinases and activation of signaling pathways. In addition, sequence analyses predict all 24 human zinc transporters to be phosphorylated suggesting that protein phosphorylation is important for regulation of transporter function. This review describes how zinc transporters are implicated in a number of important human diseases. It summarizes the current knowledge regarding ZIP and ZnT transporter structures and points to how protein phosphorylation seems to be important for the regulation of zinc transporter activity. The review addresses the need to investigate the role of protein phosphorylation in zinc transporter function and regulation, and argues for a pressing need to introduce quantitative phosphoproteomics to specifically target zinc transporters and proteins involved in zinc signaling. Finally, different quantitative phosphoproteomic strategies are suggested.

An efficient solution for resolving iTRAQ and TMT channel cross-talk

Isobaric tagging reagents such as isobaric tag for relative and absolute quantitation (iTRAQ) and tandem mass tag (TMT) typically have isotopic impurities that cause significant cross-talk between channels. Here, we present an efficient solution to compensate for channel cross-talk using linear algebra and find that it is between 20× and 120× faster than previous methods. We also find that the effects of channel cross-talk are as important to manage as the effects of ratio compression because of precursor impurities, and we have released an open-source tool to perform both types of calculations.

Site-selective, reversible, pH-induced N-terminal maleylation and its application for proteomics research

RATIONALE

Compared with traditional labelling reagents used in proteomics, maleic anhydride is milder and can be easily removed under certain conditions, thus simplifying chemical derivatization.

METHODS

The proposed strategy combined a site-specific chemical labelling reaction with mass spectrometry. Site-selective, reversible N-terminal maleylation was controlled by pH.

RESULTS

Selective maleyl N-terminal labelling was achieved with high efficiency under the optimized reaction conditions. The demaleylation conditions were also optimized. The sequence coverage of histone H4 increased from 77% to 95% after the maleyl labels were removed, and the number of maleylated peptides was five times that of the unlabelled peptides. We further verified the reversible and selective N-terminal labelling properties of maleic anhydride through propionylation labelling at the peptide/protein level.

CONCLUSIONS

A new method for site-selective maleylation of the N-terminal amino groups of a peptide was explored. Through the optimization experiment, good efficiency was achieved for this labelling reaction. The reversibility of maleylation labelling was also explored and applied for the identification of post-translational modifications of histones. Thus, site-selective, reversible, pH-induced N-terminal labelling using maleic anhydride has greater potential for application in proteomics than any other labelling methods.

Methods and Algorithms for Quantitative Proteomics by Mass Spectrometry

Protein quantitation by mass spectrometry has always been a resourceful technique in protein discovery, and more recently it has leveraged the advent of clinical proteomics. A single mass spectrometry analysis experiment provides identification and quantitation of proteins as well as information on posttranslational modifications landscape. By contrast, protein array technologies are restricted to quantitation of targeted proteins and their modifications. Currently, there are an overwhelming number of quantitative mass spectrometry methods for protein and peptide quantitation. The aim here is to provide an overview of the most common mass spectrometry methods and algorithms used in quantitative proteomics and discuss the computational aspects to obtain reliable quantitative measures of proteins, peptides and their posttranslational modifications. The development of a pipeline using commercial or freely available software is one of the main challenges in data analysis of many experimental projects. Recent developments of R statistical programming language make it attractive to fully develop pipelines for quantitative proteomics. We discuss concepts of quantitative proteomics that together with current R packages can be used to build highly customizable pipelines.

Real-time laser induced chemical derivatizations of peptide N-Terminus for in-situ mass spectrometric sequencing at sub-picomole and nanosecond scale

Distinguishing b- and y-ions is essential to compute amino acid sequences from either N- or C-terminus in mass spectrometry. We described herein a solvent free and real time on-plate derivatization approach that can tag N-terminus of peptides at microliter level with p-chlorobenzaldehyde or 2-hydroxy-5-methylisophthalaldehyde for matrix assisted laser desorption ionization mass spectrometry (MALDI MS). Less than 1 μL of sample solutions can be directly mixed with equal volumes of p-chlorobenzaldehyde or 2-hydroxy-5-methylisophthalaldehyde and α-cyano-4-hydroxycinnamic acid (CHCA), a matrix compound to co-crystalize with analytes for efficient absorption of laser energy and peptide ionization. When the mixture spotted on the sample plate is irradiated with the 3rd harmonic (355 nm) of Nd³⁺:YAG laser pulses (3 ns width), N-terminal amine groups of peptides instantly react with carbonyl groups of chlorobenzaldehyde or 2-hydroxy-5-methylisophthalaldehyde. Resultant peptides carrying with on-plate formed azomethine group (-CN-) are simultaneously protonated and isolated as precursor ions for subsequent collision-activated dissociation. The mass shift with unique Cl isotopic signature unambiguously distinguishes b ions from y ions and other ions. This method does not need extensive sample preparation and is useful for those samples with limited quantities down to sub-picomole level in sub-microliter volumes. The efficiency was demonstrated with synthetic peptides and tryptic peptides of model proteins. It was found that 2-hydroxy-5-methylisophthalaldehyde provides improved yield for peptides containing lysine residues. Unknown proteins of human saliva and bovine milk as well as phosphopeptides have been identified.

N-glycopeptide Signatures of IgA2 in Serum from Patients with Hepatitis B Virus-related Liver Diseases

N-glycosylation alteration has been reported in liver diseases. Characterizing N-glycopeptides that correspond to N-glycan structure with specific site information enables better understanding of the molecular pathogenesis of liver damage and cancer. Here, unbiased quantification of N-glycopeptides of a cluster of serum glycoproteins with 40-55 kDa molecular weight (40-kDa band) was investigated in hepatitis B virus (HBV)-related liver diseases. We used an N-glycopeptide method based on 18O/16O C-terminal labeling to obtain 82 comparisons of serum from patients with HBV-related hepatocellular carcinoma (HCC) and liver cirrhosis (LC). Then, multiple reaction monitoring (MRM) was performed to quantify N-glycopeptide relative to the protein content, especially in the healthy donor-HBV-LC-HCC cascade. TPLTAN205ITK (H5N5S1F1) and (H5N4S2F1) corresponding to the glycopeptides of IgA2 were significantly elevated in serum from patients with HBV infection and even higher in HBV-related LC patients, as compared with healthy donor. In contrast, the two glycopeptides of IgA2 fell back down in HBV-related HCC patients. In addition, the variation in the abundance of two glycopeptides was not caused by its protein concentration. The altered N-glycopeptides might be part of a unique glycan signature indicating an IgA-mediated mechanism and providing potential diagnostic clues in HBV-related liver diseases.

MAP: model-based analysis of proteomic data to detect proteins with significant abundance changes

Isotope-labeling-based mass spectrometry (MS) is widely used in quantitative proteomic studies. With this technique, the relative abundance of thousands of proteins can be efficiently profiled in parallel, greatly facilitating the detection of proteins differentially expressed across samples. However, this task remains computationally challenging. Here we present a new approach, termed Model-based Analysis of Proteomic data (MAP), for this task. Unlike many existing methods, MAP does not require technical replicates to model technical and systematic errors, and instead utilizes a novel step-by-step regression analysis to directly assess the significance of observed protein abundance changes. We applied MAP to compare the proteomic profiles of undifferentiated and differentiated mouse embryonic stem cells (mESCs), and found it has superior performance compared with existing tools in detecting proteins differentially expressed during mESC differentiation. A web-based application of MAP is provided for online data processing at http://bioinfo.sibs.ac.cn/shaolab/MAP.

Mass Spectrometry-Based Biomarkers in Drug Development

Advances in mass spectrometry, proteomics, protein bioanalytical approaches, and biochemistry have led to a rapid evolution and expansion in the area of mass spectrometry-based biomarker discovery and development. The last decade has also seen significant progress in establishing accepted definitions, guidelines, and criteria for the analytical validation, acceptance and qualification of biomarkers. These advances have coincided with a decreased return on investment for pharmaceutical research and development and an increasing need for better early decision making tools. Empowering development teams with tools to measure a therapeutic interventions impact on disease state and progression, measure target engagement and to confirm predicted pharmacodynamic effects is critical to efficient data-driven decision making. Appropriate implementation of a biomarker or a combination of biomarkers can enhance understanding of a drugs mechanism, facilitate effective translation from the preclinical to clinical space, enable early proof of concept and dose selection, and increases the efficiency of drug development. Here we will provide descriptions of the different classes of biomarkers that have utility in the drug development process as well as review specific, protein-centric, mass spectrometry-based approaches for the discovery of biomarkers and development of targeted assays to measure these markers in a selective and analytically precise manner.

Recent advances in phosphoproteomics and application to neurological diseases

Phosphorylation has an incredible impact on the biological behavior of proteins, altering everything from intrinsic activity to cellular localization and complex formation. It is no surprise then that this post-translational modification has been the subject of intense study and that, with the advent of faster, more accurate instrumentation, the number of large-scale mass spectrometry-based phosphoproteomic studies has swelled over the past decade. Recent developments in sample preparation, phosphorylation enrichment, quantification, and data analysis strategies permit both targeted and ultra-deep phosphoproteome profiling, but challenges remain in pinpointing biologically relevant phosphorylation events. We describe here technological advances that have facilitated phosphoproteomic analysis of cells, tissues, and biofluids and note applications to neuropathologies in which the phosphorylation machinery may be dysregulated, much as it is in cancer.

Andrographolide Sulfonate Attenuates Acute Lung Injury by Reducing Expression of Myeloperoxidase and Neutrophil-Derived Proteases in Mice

Andrographolide sulfonate (Andro-S), a sulfonation derivative of andrographolide, is known to be effective in treating inflammation-related diseases, while the underlying mechanisms and global protein alterations in response to Andro-S remain unknown. This study aimed to investigate the pharmacological effects and potential targets of Andro-S in a murine model of acute lung injury (ALI). ALI was induced by aerosolized lipopolysaccharide (LPS) exposure before treatment with Andro-S. Inflammatory state of each treatment group was determined by histological analysis and quantification of inflammatory markers. Differentially expressed proteins in lung tissues were identified by an iTRAQ-based quantitative proteomic approach and further confirmed by immunohistochemistry analysis. Administration of Andro-S alleviated LPS-induced histological changes in the lung and reduced the expression of inflammatory markers in serum, bronchoalveolar fluid and lung tissues. Proteomic analysis identified 31 differentially expressed proteins from a total of 2,234 quantified proteins in the lung. According to bioinformatics analysis, neutrophil elastase (ELANE), cathepsin G (CTSG) and myeloperoxidase (MPO), three neutrophil-derived proteases related to immune system process and defense responses to fungi were chosen as potential targets of Andro-S. Further immunohistochemistry analysis confirmed the inhibitory effects of Andro-S on LPS-induced ELANE, CTSG and MPO up-regulation. These results indicate that Andro-S suppressed the severity of LPS-induced ALI, possibly by attenuating the expression of and neutrophil-derived proteases.

Gel-based proteomics in disease research: Is it still valuable?

Gel electrophoresis had been the primary method in proteomics. In the early era of proteomics, gel electrophoresis was a dominant technique of sample preparation for mass spectrometry analysis. Particularly, two-dimensional electrophoresis provided high-resolution proteome separation, and was regarded as the standard methodology for the separation of wide-range proteomes. However, gel electrophoresis turned downwards due to the progress of other separations including liquid chromatography and ionization techniques, resulting gel-free proteomics finally becoming dominant players at present. There are numerous advantages in gel-free approach in aspects of current trends of disease research. Interestingly, gel-free approaches are still advanced, it seems that gel electrophoresis will not be disappeared. The unique features of gel electrophoresis can be complementary for gel-free and it is suitable for the new wave of top-down functional proteomics.

diDO-IPTL: A Peptide-Labeling Strategy for Precision Quantitative Proteomics

We present an analytical strategy, dimethylation-deuteration and oxygen-exchange IPTL (diDO-IPTL), for high-precision, broad-coverage quantitative proteomics. The diDO-IPTL approach combines two advances in isobaric peptide terminal labeling (IPTL) methodology: first, a one-pot chemical labeling strategy for attaching isotopic tags to both the N- and C-termini of tryptic peptides, and second, a search engine (based on the Morpheus algorithm) optimized for identification and quantification of twinned peaks from peptide fragment ions in MS² spectra. The diDO-IPTL labeling chemistry uses only high-purity, relatively inexpensive isotopic reagents (¹⁸O water and deuterated formaldehyde) and requires no postlabeling cleanup or isotopic impurity corrections. This strategy produces proteome-scale relative quantification results with high accuracy and precision, suitable for the detection of small protein abundance variations between complex biological samples. In a two-proteome mixture experiment, diDO-IPTL quantification discriminates 1.5-fold changes in abundance of over 1000 proteins with 88% accuracy. The diDO-IPTL methodology is a high-precision, economical approach to quantitative proteomics that is applicable to a wide variety of sample types.

Investigating the Relationship between the Substrates' Consumption and Their Abundances in a Complex Enzymatic System

The enzymatic process involving the incubation of a library of substrates with an enzyme is the key step for a few important experiments for bioanalytical chemistry including proteomics analysis, enzymatic labeling, substrate screening, etc. The relationship between the substrates' consumption and their abundances in a complex enzymatic system with a huge number of coexisting substrates of different abundances was not well-known. In this study, we have demonstrated theoretically and experimentally that the priority of substrate consumption depended on their specificity constants but not abundances. We derived the expression between the fractions of the substrates consumed (p_i) and their specificity constants. Using the enzymatic system of five synthetic peptide substrates of trypsin, we validated through 24 experiments that the ln(1 - p_i) values of competing substrates have linear correlation with their specificity constants, and thus, the priority of substrate depletion has no relation with their abundances. Using a state of the art quantitative proteomics approach, we found that the ln(1 - p_i) values of 144 competing substrates between any two of four experiments have a linear relationship and the prioritization of substrates can be achieved by sorting their consumption rates in the experiment. This study will improve our understanding of the enzymatic kinetics in the complex system and will benefit the design of enzymatic analytical approaches.

pyQms enables universal and accurate quantification of mass spectrometry data

Quantitative mass spectrometry (MS) is a key technique in many research areas (1), including proteomics, metabolomics, glycomics, and lipidomics. Because all of the corresponding molecules can be described by chemical formulas, universal quantification tools are highly desirable. Here, we present pyQms, an open-source software for accurate quantification of all types of molecules measurable by MS. pyQms uses isotope pattern matching that offers an accurate quality assessment of all quantifications and the ability to directly incorporate mass spectrometer accuracy. pyQms is, due to its universal design, applicable to every research field, labeling strategy, and acquisition technique. This opens ultimate flexibility for researchers to design experiments employing innovative and hitherto unexplored labeling strategies. Importantly, pyQms performs very well to accurately quantify partially labeled proteomes in large scale and high throughput, the most challenging task for a quantification algorithm.

Enhanced Sample Multiplexing of Tissues Using Combined Precursor Isotopic Labeling and Isobaric Tagging (cPILOT)

There is an increasing demand to analyze many biological samples for disease understanding and biomarker discovery. Quantitative proteomics strategies that allow simultaneous measurement of multiple samples have become widespread and greatly reduce experimental costs and times. Our laboratory developed a technique called combined precursor isotopic labeling and isobaric tagging (cPILOT), which enhances sample multiplexing of traditional isotopic labeling or isobaric tagging approaches. Global cPILOT can be applied to samples originating from cells, tissues, bodily fluids, or whole organisms and gives information on relative protein abundances across different sample conditions. cPILOT works by 1) using low pH buffer conditions to selectively dimethylate peptide N-termini and 2) using high pH buffer conditions to label primary amines of lysine residues with commercially-available isobaric reagents (see Table of Materials/Reagents). The degree of sample multiplexing available is dependent on the number of precursor labels used and the isobaric tagging reagent. Here, we present a 12-plex analysis using light and heavy dimethylation combined with six-plex isobaric reagents to analyze 12 samples from mouse tissues in a single analysis. Enhanced multiplexing is helpful for reducing experimental time and cost and more importantly, allowing comparison across many sample conditions (biological replicates, disease stage, drug treatments, genotypes, or longitudinal time-points) with less experimental bias and error. In this work, the global cPILOT approach is used to analyze brain, heart, and liver tissues across biological replicates from an Alzheimer's disease mouse model and wild-type controls. Global cPILOT can be applied to study other biological processes and adapted to increase sample multiplexing to greater than 20 samples.

Recent advances in proteomics of cereals

Cereals contribute a major part of human nutrition and are considered as an integral source of energy for human diets. With genomic databases already available in cereals such as rice, wheat, barley, and maize, the focus has now moved to proteome analysis. Proteomics studies involve the development of appropriate databases based on developing suitable separation and purification protocols, identification of protein functions, and can confirm their functional networks based on already available data from other sources. Tremendous progress has been made in the past decade in generating huge data-sets for covering interactions among proteins, protein composition of various organs and organelles, quantitative and qualitative analysis of proteins, and to characterize their modulation during plant development, biotic, and abiotic stresses. Proteomics platforms have been used to identify and improve our understanding of various metabolic pathways. This article gives a brief review of efforts made by different research groups on comparative descriptive and functional analysis of proteomics applications achieved in the cereal science so far.

Protein-species quantitative venomics: looking through a crystal ball

In this paper we discuss recent significant developments in the field of venom research, specifically the emergence of top-down proteomic applications that allow achieving compositional resolution at the level of the protein species present in the venom, and the absolute quantification of the venom proteins (the term “protein species” is used here to refer to all the different molecular forms in which a protein can be found. Please consult the special issue of Jornal of Proteomics “Towards deciphering proteomes via the proteoform, protein speciation, moonlighting and protein code concepts” published in 2016, vol. 134, pages 1-202). Challenges remain to be solved in order to achieve a compact and automated platform with which to routinely carry out comprehensive quantitative analysis of all toxins present in a venom. This short essay reflects the authors’ view of the immediate future in this direction for the proteomic analysis of venoms, particularly of snakes.

Ex vivo 18O-labeling mass spectrometry identifies a peripheral amyloid β clearance pathway

Background

Proteolytic degradation of amyloid β (Aβ) peptides has been intensely studied due to the central role of Aβ in Alzheimer’s disease (AD) pathogenesis. While several enzymes have been shown to degrade Aβ peptides, the main pathway of Aβ degradation in vivo is unknown. Cerebrospinal fluid (CSF) Aβ42 is reduced in AD, reflecting aggregation and deposition in the brain, but low CSF Aβ42 is, for unknown reasons, also found in some inflammatory brain disorders such as bacterial meningitis.

Method

Using ¹⁸O-labeling mass spectrometry and immune-affinity purification, we examined endogenous proteolytic processing of Aβ in human CSF.

Results

The Aβ peptide profile was stable in CSF samples from healthy controls but in CSF samples from patients with bacterial meningitis, showing increased leukocyte cell count, ¹⁸O-labeling mass spectrometry identified proteolytic activities degrading Aβ into several short fragments, including abundant Aβ1–19 and 1–20. After antibiotic treatment, no degradation of Aβ was detected. In vitro experiments located the source of the proteolytic activity to blood components, including leukocytes and erythrocytes, with insulin-degrading enzyme as the likely protease. A recombinant version of the mid-domain anti-Aβ antibody solanezumab was found to inhibit insulin-degrading enzyme-mediated Aβ degradation.

Conclusion

¹⁸O labeling-mass spectrometry can be used to detect endogenous proteolytic activity in human CSF. Using this technique, we found an enzymatic activity that was identified as insulin-degrading enzyme that cleaves Aβ in the mid-domain of the peptide, and could be inhibited by a recombinant version of the mid-domain anti-Aβ antibody solanezumab.

Electronic supplementary material

The online version of this article (doi:10.1186/s13024-017-0152-5) contains supplementary material, which is available to authorized users.

Target identification with quantitative activity based protein profiling (ABPP)

As many small bioactive molecules fulfill their functions through interacting with protein targets, the identification of such targets is crucial in understanding their mechanisms of action (MOA) and side effects. With technological advancements in target identification, it has become possible to accurately and comprehensively study the MOA and side effects of small molecules. While small molecules with therapeutic potential were derived solely from nature in the past, the remodeling and synthesis of such molecules have now been made possible. Presently, while some small molecules have seen successful application as drugs, the majority remain undeveloped, requiring further understanding of their MOA and side effects to fully tap into their potential. Given the typical promiscuity of many small molecules and the complexity of the cellular proteome, a high-flux and high-accuracy method is necessary. While affinity chromatography approaches combined with MS have had successes in target identification, limitations associated with nonspecific results remain. To overcome these complications, quantitative chemical proteomics approaches have been developed including metabolic labeling, chemical labeling, and label-free methods. These new approaches are adopted in conjunction with activity-based protein profiling (ABPP), allowing for a rapid process and accurate results. This review will briefly introduce the principles involved in ABPP, then summarize current advances in quantitative chemical proteomics approaches as well as illustrate with examples how ABPP coupled with quantitative chemical proteomics has been used to detect the targets of drugs and other bioactive small molecules including natural products.

Advancement of mass spectrometry-based proteomics technologies to explore triple negative breast cancer

Understanding the complexity of cancer biology requires extensive information about the cancer proteome over the course of the disease. The recent advances in mass spectrometry-based proteomics technologies have led to the accumulation of an incredible amount of such proteomic information. This information allows us to identify protein signatures or protein biomarkers, which can be used to improve cancer diagnosis, prognosis and treatment. For example, mass spectrometry-based proteomics has been used in breast cancer research for over two decades to elucidate protein function. Breast cancer is a heterogeneous group of diseases with distinct molecular features that are reflected in tumour characteristics and clinical outcomes. Compared with all other subtypes of breast cancer, triple-negative breast cancer is perhaps the most distinct in nature and heterogeneity. In this review, we provide an introductory overview of the application of advanced proteomic technologies to triple-negative breast cancer research.

Common errors in mass spectrometry-based analysis of post-translational modifications

Mass spectrometry (MS) is a powerful tool to analyze complex mixtures of proteins in a high-throughput fashion. Proteome analysis has already become a routine task in biomedical research with the emergence of proteomics core facilities in most research institutions. Post-translational modifications (PTMs) represent a mechanism by which complex biological processes are orchestrated dynamically at the systems level. MS is rapidly becoming popular to discover new modifications and novel sites of known PTMs, revolutionizing the current understanding of diverse signaling pathways and biological processes. However, MS-based analysis of PTMs has its own caveats and pitfalls that can lead to erroneous conclusions. Here, we review the most common errors in MS-based PTM analyses with the goal of adopting strategies that maximize correct interpretation in the context of biological questions that are being addressed. Finally, we provide suggestions that should help mass spectrometrists, bioinformaticians and biologists to perform and interpret MS-based PTM analyses more accurately.