Top-down proteomics for the analysis of proteolytic events - Methods, applications and perspectives

Digital Microfluidics for Sample Preparation in Low-Input Proteomics

Low-input proteomics, also referred to as micro- or nanoproteomics, has become increasingly popular as it allows one to elucidate molecular processes in rare biological materials. A major prerequisite for the analytics of minute protein amounts, e.g., derived from low cell numbers, down to single cells, is the availability of efficient sample preparation methods. Digital microfluidics (DMF), a technology allowing the handling and manipulation of low liquid volumes, has recently been shown to be a powerful and versatile tool to address the challenges in low-input proteomics. Here, an overview is provided on recent advances in proteomics sample preparation using DMF. In particular, the capability of DMF to isolate proteomes from cells and small model organisms, and to perform all necessary chemical sample preparation steps, such as protein denaturation and proteolytic digestion on-chip, are highlighted. Additionally, major prerequisites to making these steps compatible with follow-up analytical methods such as liquid chromatography-mass spectrometry will be discussed.

GeLC-FAIMS-MS workflow for in-depth middle-down proteomics

Middle-down proteomics (MDP) is an analytical approach in which protein samples are digested with proteases such as Glu-C to generate large peptides (>3 kDa) that are analyzed by mass spectrometry (MS). This method is useful for characterizing high-molecular-weight proteins that are difficult to detect by top-down proteomics (TDP), in which intact proteins are analyzed by MS. In this study, we applied GeLC-FAIMS-MS, a multidimensional separation workflow that combines gel-based prefractionation with LC-FAIMS MS, for deep MDP. Middle-down peptides generated by optimized limited Glu-C digestion conditions were first size-fractionated by polyacrylamide gel electrophoresis, followed by C4 reversed-phase liquid chromatography separation and additional ion mobility fractionation, resulting in a significant increase in peptide length detectable by MS. In addition to global analysis, the GeLC-FAIMS-MS concept can also be applied to targeted MDP, where only proteins in the desired molecular weight range are gel-fractionated and their Glu-C digestion products are analyzed, as demonstrated by targeted analysis of integrins in exosomes. In-depth MDP achieved by global and targeted GeLC-FAIMS-MS supports the exploration of proteoform information not covered by conventional TDP by increasing the number of detectable protein groups or post-translational modifications (PTMs) and improving the sequence coverage.

Selenium Decipher: Trapping of Native Selenomethionine-Containing Peptides in Selenium-Enriched Milk and Unveiling the Deterioration after Ultrahigh-Temperature Treatment

Selenopeptide identification relies on databases to interpret the selenopeptide spectra. A common database search strategy is to set selenium as a variable modification instead of sulfur on peptides. However, this approach generally detects only a fraction of selenopeptides. An alternative approach, termed Selenium Decipher, is proposed in the present study. It involves identifying collision-induced dissociation-cleavable selenomethionine-containing peptides by iteratively matching the masses of seleno-amino acids in selenopeptide spectra. This approach uses variable-data-independent acquisition (vDIA) for peptide detection, providing a flexible and customizable window for secondary mass spectral fragmentation. The attention mechanism was used to capture global information on peptides and determine selenomethionine-containing peptide backbones. The core structure of selenium on selenomethionine-containing peptides generates a series of fragment ions, namely, C3H7Se+, C4H10NSe+, C5H7OSe+, C5H8NOSe+, and C7H11N2O2Se+, with known mass gaps during higher-energy collisional dissociation (HCD) fragmentation. De-selenium spectra are generated by removing selenium originating from selenium replacement and then reassigning the precursors to peptides. Selenium-enriched milk is obtained by feeding selenium-rich forage fed to cattle, which leads to the formation of native selenium through biotransformation. A novel antihypertensive selenopeptide Thr-Asp-Asp-Ile-SeMet-Cys-Val-Lys TDDI(Se)MCVK was identified from selenium-enriched milk. The selenopeptide (IC50 = 60.71 μM) is bound to four active residues of the angiotensin-converting enzyme (ACE) active pocket (Ala354, Tyr523, His353, and His513) and two active residues of zinc ligand (His387 and Glu411) and exerted a competitive inhibitory effect on the spatial blocking of active sites. The integration of vDIA and the iteratively matched seleno-amino acids was applied for Selenium Decipher, which provides high validity for selenomethionine-containing peptide identification.

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

IMPORTANCE

The identification of short open reading frame-encoded peptides (SEP) and different proteoforms in single cultures of gut microbes offers new insights into a largely neglected part of the microbial proteome landscape. This is of particular importance as SEP provide various predicted functions, such as acting as antimicrobial peptides, maintaining cell homeostasis under stress conditions, or even contributing to the virulence pattern. They are, thus, taking a poorly understood role in structure and function of microbial networks in the human body. A better understanding of SEP in the context of human health requires a precise understanding of the abundance of SEP both in commensal microbes as well as pathogens. For the gut beneficial B. producta, we demonstrate the importance of specific environmental conditions for biosynthesis of SEP expanding previous findings about their role in microbial interactions.

Human exhaled air diagnostic markers for respiratory tract infections in subjects receiving mechanical ventilation

Diagnosing respiratory tract infections (RTIs) in critical care settings is essential for appropriate antibiotic treatment and lowering mortality. The current diagnostic method, which primarily relies on clinical symptoms, lacks sensitivity and specificity, resulting in incorrect or delayed diagnoses, putting patients at a heightened risk. In this study we developed a noninvasive diagnosis method based on collecting non-volatile compounds in human exhaled air. We hypothesized that non-volatile compound profiles could be effectively used for bacterial RTI diagnosis. Exhaled air samples were collected from subjects receiving mechanical ventilation diagnosed with or without bacterial RTI in intensive care units at the Johns Hopkins Hospital. Truncated proteoforms, a class of non-volatile compounds, were characterized by top-down proteomics, and significant features associated with RTI were identified using feature selection algorithms. The results showed that three truncated proteoforms, collagen type VI alpha three chain protein, matrix metalloproteinase-9, and putative homeodomain transcription factor II were independently associated with RTI with thep-values of 2.0 × 10^-5, 1.1 × 10^-4, and 1.7 × 10^-3, respectively, using multiple logistic regression. Furthermore, a score system named 'TrunScore' was constructed by combining the three truncated proteoforms, and the diagnostic accuracy was significantly improved compared to that of individual truncated proteoforms, with an area under the receiver operator characteristic curve of 96.9%. This study supports the ability of this noninvasive breath analysis method to provide an accurate diagnosis for RTIs in subjects receiving mechanical ventilation. The results of this study open the doors to be able to potentially diagnose a broad range of diseases using this non-volatile breath analysis technique.

Current Role of Modern Chromatography with Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy in the Investigation of Biomarkers of Endometriosis

Endometriosis has a wide range of clinical manifestations, and the disease course is unpredictable, making the diagnosis a challenging task. Despite significant advances in the pathophysiology of endometriosis and various proposed theories, the exact etiology is not fully understood and is still unknown. The most commonly used biomarker of endometriosis is CA-125, however, it is nonspecific and is applied for cancers diagnosis. Therefore, the development of reliable noninvasive diagnostic tests for the early diagnosis of endometriosis remains one of the top priorities. Omics technologies are very promising approaches for constructing diagnostic models and biomarker discovery. Their use can greatly facilitate the study of such a complex disease as endometriosis. Nowadays, powerful analytical platforms commonly used in omics, such as gas and liquid chromatography with mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, have proven to be a promising tools for biomarker discovery. The aim of this review is to summarize the various features of the analytical approaches, practical challenges and features of gas and liquid chromatography with MS and NMR spectroscopy (including sample processing protocols, technological advancements, and methodology) used for profiling of metabolites, lipids, peptides and proteins in physiological fluids and tissues from patients with endometriosis. In addition, this report devotes special attention to the issue of how comprehensive analyses of these profiles can effectively contribute to the study of endometriosis. The search query included reports published between 2012 and 2022 years in PubMed, Web-of-Science, SCOPUS, Science Direct.

Targeted Bottom-Up Mass Spectrometry Approach for the Relative Quantification of Post-Translational Modification of Bovine κ-Casein during Milk Fermentation

κ-casein (κ-CN) is one of the key components in bovine milk, playing a unique role in the structuration of casein micelles. It contains in its chemical structure up to sixteen amino acid residues (mainly serine and threonine) susceptible to modifications, including glycosylation and phosphorylation, which may further be formed during milk processing. In this study, changes in post-translational modification (PTM) of κ-CN during bovine milk fermentation were investigated. One-to-five-day fermented milk samples were produced. A traditional bottom−up proteomics approach was used to establish a multiple-reaction monitoring (MRM) method for relative quantification of κ-CN PTM. Endoproteinase Glu-C was found to efficiently digest the κ-CN molecule. The developed LC-MS method was validated by performing assessments of linearity, precision, repeatability, reproducibility, limit of detection (LOD), and limit of quantification (LOQ). Among the yielded peptides, four of them containing serine and threonine residues were identified and the unmodified as well as the modified variants of each of them were relatively quantified. These peptides were (1) IPTINTIASGEPTSTTE [140, 158], (2) STVATLE [162, 168], (3) DSPE [169, 172], and (4) INTVQVTSTAV [180, 190]. Distribution analysis between unmodified and modified peptides revealed that over 50% of κ-CN was found in one of its modified forms in milk. The fermentation process further significantly altered the composition between unmodified/modified κ-CN, with glycoslaytion being predominant compared to phosphorylation (p < 0.01). Further method development towards α and β-CN fractions and their PTM behavior would be an asset to better understand the changes undergone by milk proteins and the micellar structure during fermentation.

Mass spectrometry and the cellular surfaceome

The collection of exposed plasma membrane proteins, collectively termed the surfaceome, is involved in multiple vital cellular processes, such as the communication of cells with their surroundings and the regulation of transport across the lipid bilayer. The surfaceome also plays key roles in the immune system by recognizing and presenting antigens, with its possible malfunctioning linked to disease. Surface proteins have long been explored as potential cell markers, disease biomarkers, and therapeutic drug targets. Despite its importance, a detailed study of the surfaceome continues to pose major challenges for mass spectrometry-driven proteomics due to the inherent biophysical characteristics of surface proteins. Their inefficient extraction from hydrophobic membranes to an aqueous medium and their lower abundance compared to intracellular proteins hamper the analysis of surface proteins, which are therefore usually underrepresented in proteomic datasets. To tackle such problems, several innovative analytical methodologies have been developed. This review aims at providing an extensive overview of the different methods for surfaceome analysis, with respective considerations for downstream mass spectrometry-based proteomics.

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.

Nonspecific adsorption evaluation and general minimization strategy in peptide analysis based on ultra-performance liquid chromatography-mass spectrometry

蛋白质组学技术在多肽和蛋白质类新型治疗药物的开发、临床诊断生物标志物的深入发掘中应用广泛。然而,多肽和蛋白质类大分子的非特异性吸附性质给分析方法的开发带来极大挑战,亟须一种通用型的策略去评估和降低非特异吸附对超高效液相色谱-质谱(UPLC-MS)大分子检测造成的负面影响。研究以牛血清白蛋白(BSA)为模型,探讨其酶解后多肽组理化性质与吸附程度之间的相关性;根据肽段的响应和吸附程度设计分级策略;针对高响应、强吸附的Class Ⅱ类肽段,从样品制备中离心管、进样瓶的选择,乃至液相色谱系统中色谱柱固定相、流速、梯度、柱温、洗针液的选择全过程设计试验,探讨非特异吸附的影响因素及其通用型最小化策略。结果显示,肽段的被吸附程度与其理化参数HPLC指数(HPLC Index)、肽段长度等显著相关(p<0.05),但仅凭上述参数仅能解释30%肽段的被吸附程度。改性的聚丙烯材料可使肽段溶液在储存或前处理过程中获得较高的回收率(24 h内回收率大于80%)。在对液相色谱条件的考察和优化过程中发现,C₈填料的色谱柱、高流速、缓梯度以及强洗针液,可使残留量降至最低(降低为原来的1/150)。柱温对残留的影响在肽段间存在较大个体差异,需要对不同的肽段具体分析以得到较少量的残留。研究以详实的数据考察并最小化模型肽段组在分析过程中的非特异吸附,提示了蛋白质类大分子药物分析方法建立中应重点关注的影响因素及其有效的解决方案。

Mass Spectrometry Based Protein Biomarkers and Drug Target Discovery and Clinical Diagnosis in Age-Related Progressing Neurodegenerative Diseases

Neurodegenerative diseases correspond to overly complex health disorders that are driven by intersecting pathophysiology that are often trapped in vicious cycles of degeneration and cognitive decline. The usual diagnostic route of these diseases is based on postmortem examination that involves identifying pathology that is specific to the disease in the brain. However, in such cases, accurate diagnosis of the specific disease is limited because clinical disease presentations are often complex that do not easily allow to discriminate patient's cognitive, behavioral, and functional impairment profiles. Additionally, an early identification and therapeutic intervention of these diseases is pivotal to slow the progression of neurodegeneration and extend healthy life span. Mass spectrometry-based techniques have proven to be hugely promising in biological sample analysis and discovery of biomarkers including protein and peptide biomarkers for potential drug target discovery. Recent studies on these biomarkers have demonstrated their potential for applications in early diagnostics and identifying therapeutic targets to battle against neurodegenerative diseases. In this review, we have presented principles of mass spectrometry (MS) and the associated workflows in analyzing and imaging biological samples for discovery of biomarkers. We have especially focused on age- related progressing neurodegenerative diseases such as Alzheimer's (AD) and Parkinson's disease (PD), Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal dementia (FTD) and the related MS-based biomarkers developments for these diseases. Finally, we present a future perspective discussing the potential research directions ahead.

Proteolytic Profiling of Streptococcal Pyrogenic Exotoxin B (SpeB) by Complementary HPLC-MS Approaches

Streptococcal pyrogenic exotoxin B (SpeB) is a cysteine protease expressed during group A streptococcal infection that represents a major virulence factor. Although subject to several studies, its role during infection is still under debate, and its proteolytic properties remain insufficiently characterized. Here, we revisited this protease through a set of complementary approaches relying on state of-the-art HPLC-MS methods. After conceiving an efficient protocol to recombinantly express SpeB, the zymogen of the protease and its activation were characterized. Employing proteome-derived peptide libraries, a strong preference for hydrophobic and aromatic residues at P2 alongside negatively charged amino acids at P3′ to P6′ was revealed. To identify relevant in vivo substrates, native proteins were obtained from monocytic secretome and plasma to assess their cleavage under physiological conditions. Besides corroborating our findings concerning specificity, more than 200 cleaved proteins were identified, including proteins of the extracellular matrix, proteins of the immune system, and proteins involved in inflammation. Finally, the cleavage of IgG subclasses was studied in detail. This study precisely depicts the proteolytic properties of SpeB and provides a library of potential host substrates, including their exact cleavage positions, as a valuable source for further research to unravel the role of SpeB during streptococcal infection.

Complementing the pulp proteome via sampling with a picosecond infrared laser (PIRL)

OBJECTIVES

The aim of this investigation was the detailed analysis of the human pulp proteome using the new picosecond infrared laser (PIRL)-based sampling technique, which is based on a completely different mechanism compared to mechanical sampling. Proteome analysis of healthy pulp can provide data to define changes in the proteome associated with dental disease.

MATERIAL AND METHODS

Immediately after extraction of the entire, undamaged tooth, 15 wisdom teeth were deep frozen in liquid nitrogen and preserved at -80°C. Teeth were crushed, and the excised frozen pulps were conditioned for further analysis. The pulps were sampled using PIRL, and the aspirates digested with trypsin and analyzed with mass spectrometry. Pulp proteins were categorized according to their gene ontology terminus. Proteins identified exclusively in this study were searched in the Human Protein Atlas (HPA) for gaining information about the main known localization and function.

RESULTS

A total of 1348 proteins were identified in this study. The comparison with prior studies showed a match of 72%. Twenty-eight percent of the proteins were identified exclusively in this study. Considering HPA, almost half of these proteins were assigned to tissues that could be pulp specific.

CONCLUSION

PIRL is releasing proteins from the dental pulp which are not dissolved by conventional sampling techniques. Clinical Relevance The presented data extend current knowledge on dental pulp proteomics in healthy teeth and can serve as a reference for studies on pulp proteomics in dental disease.

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.

Advances in mass spectrometry-based glycoproteomics: An update covering the period 2017-2021

Protein glycosylation is one of the most common posttranslational modifications, and plays an essential role in a wide range of biological processes such as immune response, intercellular signaling, inflammation, host-pathogen interaction, and protein stability. Glycoproteomics is a proteomics subfield dedicated to identifying and characterizing the glycans and glycoproteins in a given cell or tissue. Aberrant glycosylation has been associated with various diseases such as Alzheimer's disease, viral infections, inflammation, immune deficiencies, congenital disorders, and cancers. However, glycoproteomic analysis remains challenging because of the low abundance, site-specific heterogeneity, and poor ionization efficiency of glycopeptides during LC-MS analyses. Therefore, the development of sensitive and accurate approaches to efficiently characterize protein glycosylation is crucial. Methods such as metabolic labeling, enrichment, and derivatization of glycopeptides, coupled with different mass spectrometry techniques and bioinformatics tools, have been developed to achieve sophisticated levels of quantitative and qualitative analyses of glycoproteins. This review attempts to update the recent developments in the field of glycoproteomics reported between 2017 and 2021.

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.

Understanding the Gastrointestinal Protective Effects of Polyphenols using Foodomics-Based Approaches

Plant polyphenols are rich sources of natural anti-oxidants and prebiotics. After ingestion, most polyphenols are absorbed in the intestine and interact with the gut microbiota and modulated metabolites produced by bacterial fermentation, such as short-chain fatty acids (SCFAs). Dietary polyphenols immunomodulatory role by regulating intestinal microorganisms, inhibiting the etiology and pathogenesis of various diseases including colon cancer, colorectal cancer, inflammatory bowel disease (IBD) and colitis. Foodomics is a novel high-throughput analysis approach widely applied in food and nutrition studies, incorporating genomics, transcriptomics, proteomics, metabolomics, and integrating multi-omics technologies. In this review, we present an overview of foodomics technologies for identifying active polyphenol components from natural foods, as well as a summary of the gastrointestinal protective effects of polyphenols based on foodomics approaches. Furthermore, we critically assess the limitations in applying foodomics technologies to investigate the protective effect of polyphenols on the gastrointestinal (GI) system. Finally, we outline future directions of foodomics techniques to investigate GI protective effects of polyphenols. Foodomics based on the combination of several analytical platforms and data processing for genomics, transcriptomics, proteomics and metabolomics studies, provides abundant data and a more comprehensive understanding of the interactions between polyphenols and the GI tract at the molecular level. This contribution provides a basis for further exploring the protective mechanisms of polyphenols on the GI system.

Mass spectrometric investigations of caloric restriction mimetics

Caloric restriction (CR) is an innovative therapy used in tumor tissue and tumor model studies to promote cell death and decrease cell viability. Caloric restriction mimetics (CRMs) are a class of drugs that induce CR and starvation conditions within a cell. When used simultaneously with other chemotherapy agents, the effects are synergistic and effective at promoting tumor cell death. In this review, we discuss CRMs and their potential as cancer therapeutics. Firstly, we establish an overview of CR and its impacts on healthy and tumor cells. CR and CRM drugs have shown to decrease age-related diseases and can act as an anti-cancer agent. As it can be challenging for an individual to diligently stick to a diet that would induce CR, CRMs are even more desirable. Then, we discuss the drug class by highlighting three CRMs: resveratrol, (-)-hydroxycitric acid, and rapamycin. These CRMs are commonly known for their dietary effects, but the underlying mechanisms that drive cellular metabolic and proteomic changes show promise as a cancer therapeutic. Lastly, we highlight the use of mass spectrometry and proteomic techniques on experiments utilizing CRM drugs to understand the cellular pathways impacted by this drug class, leading to a better understanding of the anti-cancer properties and potentials of CRM.

In vivo interactome profiling by enzyme-catalyzed proximity labeling

Enzyme-catalyzed proximity labeling (PL) combined with mass spectrometry (MS) has emerged as a revolutionary approach to reveal the protein-protein interaction networks, dissect complex biological processes, and characterize the subcellular proteome in a more physiological setting than before. The enzymatic tags are being upgraded to improve temporal and spatial resolution and obtain faster catalytic dynamics and higher catalytic efficiency. In vivo application of PL integrated with other state of the art techniques has recently been adapted in live animals and plants, allowing questions to be addressed that were previously inaccessible. It is timely to summarize the current state of PL-dependent interactome studies and their potential applications. We will focus on in vivo uses of newer versions of PL and highlight critical considerations for successful in vivo PL experiments that will provide novel insights into the protein interactome in the context of human diseases.

Proteomics in idiopathic pulmonary fibrosis: the quest for biomarkers

Idiopathic pulmonary fibrosis (IPF) is a debilitating chronic progressive and fibrosing lung disease that culminates in the destruction of alveolar integrity and dismal prognosis. Its etiology is unknown and pathophysiology remains unclear. While great advances have been made in elucidating the pathogenesis mechanism, considerable gaps related to information on pathogenetic pathways and key protein targets involved in the clinical course of the disease exist. These issues need to be addressed for better clinical management of this highly challenging disease. Omics approach has revolutionized the entire area of disease understanding and holds promise in its translation to clinical biomarker discovery. This review outlines the contribution of proteomics towards identification of important biomarkers in IPF in terms of their clinical utility, i.e. prognosis, differential diagnosis, disease progression and treatment monitoring. The major dysregulated pathways associated with IPF are also discussed. Based on numerous proteomics studies on human and animal models, it is proposed that IPF pathogenesis involves complex interactions of several pathways such as oxidative stress, endoplasmic reticulum stress, unfolded protein response, coagulation system, inflammation, abnormal wounding, fibroblast proliferation, fibrogenesis and deposition of extracellular matrix. These pathways and their key path-changing mediators need further validation in large well-planned multi-centric trials at various geographical locations for successful development of clinical biomarkers of this confounding disease.

N-terminomics - its past and recent advancements

N-terminomics is a rapidly evolving branch of proteomics that encompasses the study of protein N-terminal sequence. A proteome-wide collection of such sequences has been widely used to understand the proteolytic cascades and in annotating the genome. Over the last two decades, various N-terminomic strategies have been developed for achieving high sensitivity, greater depth of coverage, and high-throughputness. We, in this review, cover how the field of N-terminomics has evolved to date, including discussion on various sample preparation and N-terminal peptide enrichment strategies. We also compare different N-terminomic methods and highlight their relative benefits and shortcomings in their implementation. In addition, an overview of the currently available bioinformatics tools and data analysis pipelines for the annotation of N-terminomic datasets is also included. SIGNIFICANCE: It has been recognized that proteins undergo several post-translational modifications (PTM), and a number of perturbed biological pathways are directly associated with modifications at the terminal sites of a protein. In this regard, N-terminomics can be applied to generate a proteome-wide landscape of mature N-terminal sequences, annotate their source of generation, and recognize their significance in the biological pathways. Besides, a system-wide study can be used to study complicated proteolytic machinery and protease cleavage patterns for potential therapeutic targets. Moreover, due to unprecedented improvements in the analytical methods and mass spectrometry instrumentation in recent times, the N-terminomic methodologies now offers an unparalleled ability to study proteoforms and their implications in clinical conditions. Such approaches can further be applied for the detection of low abundant proteoforms, annotation of non-canonical protein coding sites, identification of candidate disease biomarkers, and, last but not least, the discovery of novel drug targets.

Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey

Big Data Proteogenomics lies at the intersection of high-throughput Mass Spectrometry (MS) based proteomics and Next Generation Sequencing based genomics. The combined and integrated analysis of these two high-throughput technologies can help discover novel proteins using genomic, and transcriptomic data. Due to the biological significance of integrated analysis, the recent past has seen an influx of proteogenomic tools that perform various tasks, including mapping proteins to the genomic data, searching experimental MS spectra against a six-frame translation genome database, and automating the process of annotating genome sequences. To date, most of such tools have not focused on scalability issues that are inherent in proteogenomic data analysis where the size of the database is much larger than a typical protein database. These state-of-the-art tools can take more than half a month to process a small-scale dataset of one million spectra against a genome of 3 GB. In this article, we provide an up-to-date review of tools that can analyze proteogenomic datasets, providing a critical analysis of the techniques' relative merits and potential pitfalls. We also point out potential bottlenecks and recommendations that can be incorporated in the future design of these workflows to ensure scalability with the increasing size of proteogenomic data. Lastly, we make a case of how high-performance computing (HPC) solutions may be the best bet to ensure the scalability of future big data proteogenomic data analysis.

Can proteomics contribute to biomonitoring of aquatic pollution? A critical review

Aquatic pollution is one of the greatest environmental problems, and therefore its control represents one of the major challenges in this century. In recent years, proteomics has emerged as a powerful tool for searching protein biomarkers in the field of pollution biomonitoring. For biomonitoring marine contamination, there is a consensus that bivalves are preferred organisms to assess organic and inorganic pollutants. Thus, the bivalve proteome was intensively studied, particularly the mussel. It is well documented that heavy metal pollution and organic chemicals altered the structural proteins causing degradation of tissues of molluscs. Also, it is well known that proteins involved in stress oxidative such as glutathione and enzymes as catalase, superoxide dismutase or peroxisomes are overexpressed in response to contaminants. Additionally, using bivalves, other groups of proteins proposed as pollution biomarkers are the metabolic proteins. Even though other marine species are used to monitor the pollution, the presence of proteomic tools in these studies is scarce. Concerning freshwater pollution field, a great variety of animal species (fish and crustaceans) are used as biomonitors in proteomics studies compared to plants that are scarcely analysed. In fish species, proteins involved in stress oxidative such as heat shock family or proteins from lipid and carbohydrate metabolism were proposed as candidate biomarkers. On the contrary, for crustaceans there is a lack of proteomic studies individually assessing the contaminants. Novel scenarios, including emerging contaminants and new threats, will require proteomic technology for a systematic search of protein biomarkers and a greater knowledge at molecular level of those cellular pathways induced by contamination.

Recent Advances of Functional Proteomics in Gastrointestinal Cancers- a Path towards the Identification of Candidate Diagnostic, Prognostic, and Therapeutic Molecular Biomarkers

Gastrointestinal (GI) cancer remains one of the common causes of morbidity and mortality. A high number of cases are diagnosed at an advanced stage, leading to a poor survival rate. This is primarily attributed to the lack of reliable diagnostic biomarkers and limited treatment options. Therefore, more sensitive, specific biomarkers and curative treatments are desirable. Functional proteomics as a research area in the proteomic field aims to elucidate the biological function of unknown proteins and unravel the cellular mechanisms at the molecular level. Phosphoproteomic and glycoproteomic studies have emerged as two efficient functional proteomics approaches used to identify diagnostic biomarkers, therapeutic targets, the molecular basis of disease and mechanisms underlying drug resistance in GI cancers. In this review, we present an overview on how functional proteomics may contribute to the understanding of GI cancers, namely colorectal, gastric, hepatocellular carcinoma and pancreatic cancers. Moreover, we have summarized recent methodological developments in phosphoproteomics and glycoproteomics for GI cancer studies.

Bottom-Up Design Approach for OBOC Peptide Libraries

One-bead-one-compound peptide libraries, developed following the top-down experimental approach, have attracted great interest in the identification of potential ligands or active peptides. By exploiting a reverse experimental design approach based on the bottom-up strategy, we aimed to develop simplified, maximally diverse peptide libraries that resulted in the successful characterization of mixture components. We show that libraries of 32 and 48 components can be successfully detected in a single run using chromatography coupled to mass spectrometry (UPLC-MS). The proposed libraries were further theoretically evaluated in terms of their composition and physico-chemical properties. By combining the knowledge obtained on single libraries we can cover larger sequence spaces and provide a controlled exploration of the peptide chemical space both theoretically and experimentally. Designing libraries by using the bottom-up approach opens up the possibility of rationally fine-tuning the library complexity based on the available analytical methods.

Top-Down Proteomic Characterization of Truncated Proteoforms

A top-down proteomic strategy with semiautomated analysis of data sets has proven successful for the global identification of truncated proteins without the use of chemical derivatization, enzymatic manipulation, immunoprecipitation, or other enrichment. This approach provides the reliable identification of internal polypeptides formed from precursor gene products by proteolytic cleavage of both the N- and C-termini, as well as truncated proteoforms that retain one or the other termini. The strategy has been evaluated by application to the immunosuppressive extracellular vesicles released by myeloid-derived suppressor cells. More than 1000 truncated proteoforms have been identified, from which binding motifs are derived to allow characterization of the putative proteases responsible for truncation.

Proteomic studies of bone and skeletal health outcomes

Proteins are an essential part of essentially all biological processes, and there is enormous variation in protein forms and concentrations that is not reflected in DNA or RNA. Recently there have been rapid advances in the ability to measure protein sequence, modification and concentration, particularly with methods based in mass spectrometry. Global measures of proteins in tissues or in the circulation provide a broad assessment of the proteome that can be extremely useful for discovery, and targeted proteomic measures can yield specific and sensitive assessments of specific peptides and proteins. While most proteomic measures are directed at the detection of consensus peptide sequences, mass spectrometry based proteomic methods also allow a detailed examination of the peptide sequence differences that result from genetic variants and that may have important effects on protein function. In evaluating proteomic data, a number of analytical considerations are important, including an understanding of missing data, the challenge of multiple testing and replication, and the use of rapidly evolving methods in systems biology. While proteomics has not yet had a major impact in skeletal research, interesting recent research has used these approaches in the study of bone cell biology and the discovery of biomarkers of skeletal disorders. Proteomics can be expected to have an increasing influence in the study of bone biology and pathophysiology.

Bottom-Up Proteomic Analysis of Polypeptide Venom Components of the Giant Ant Dinoponera Quadriceps

Ant species have specialized venom systems developed to sting and inoculate a biological cocktail of organic compounds, including peptide and polypeptide toxins, for the purpose of predation and defense. The genus Dinoponera comprises predatory giant ants that inoculate venom capable of causing long-lasting local pain, involuntary shaking, lymphadenopathy, and cardiac arrhythmias, among other symptoms. To deepen our knowledge about venom composition with regard to protein toxins and their roles in the chemical-ecological relationship and human health, we performed a bottom-up proteomics analysis of the crude venom of the giant ant D. quadriceps, popularly known as the "false" tocandiras. For this purpose, we used two different analytical approaches: (i) gel-based proteomics approach, wherein the crude venom was resolved by denaturing sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and all protein bands were excised for analysis; (ii) solution-based proteomics approach, wherein the crude venom protein components were directly fragmented into tryptic peptides in solution for analysis. The proteomic data that resulted from these two methodologies were compared against a previously annotated transcriptomic database of D. quadriceps, and subsequently, a homology search was performed for all identified transcript products. The gel-based proteomics approach unequivocally identified nine toxins of high molecular mass in the venom, as for example, enzymes [hyaluronidase, phospholipase A1, dipeptidyl peptidase and glucose dehydrogenase/flavin adenine dinucleotide (FAD) quinone] and diverse venom allergens (homologous of the red fire ant Selenopsis invicta) and venom-related proteins (major royal jelly-like). Moreover, the solution-based proteomics revealed and confirmed the presence of several hydrolases, oxidoreductases, proteases, Kunitz-like polypeptides, and the less abundant inhibitor cysteine knot (ICK)-like (knottin) neurotoxins and insect defensin. Our results showed that the major components of the D. quadriceps venom are toxins that are highly likely to damage cell membranes and tissue, to cause neurotoxicity, and to induce allergic reactions, thus, expanding the knowledge about D. quadriceps venom composition and its potential biological effects on prey and victims.

Characterization of Contractile Proteins from Skeletal Muscle Using Gel-Based Top-Down Proteomics

The mass spectrometric analysis of skeletal muscle proteins has used both peptide-centric and protein-focused approaches. The term 'top-down proteomics' is often used in relation to studying purified proteoforms and their post-translational modifications. Two-dimensional gel electrophoresis, in combination with peptide generation for the identification and characterization of intact proteoforms being present in two-dimensional spots, plays a critical role in specific applications of top-down proteomics. A decisive bioanalytical advantage of gel-based and top-down approaches is the initial bioanalytical focus on intact proteins, which usually enables the swift identification and detailed characterisation of specific proteoforms. In this review, we describe the usage of two-dimensional gel electrophoretic top-down proteomics and related approaches for the systematic analysis of key components of the contractile apparatus, with a special focus on myosin heavy and light chains and their associated regulatory proteins. The detailed biochemical analysis of proteins belonging to the thick and thin skeletal muscle filaments has decisively improved our biochemical understanding of structure-function relationships within the contractile apparatus. Gel-based and top-down proteomics has clearly established a variety of slow and fast isoforms of myosin, troponin and tropomyosin as excellent markers of fibre type specification and dynamic muscle transition processes.

Proteomics Approaches for Biomarker and Drug Target Discovery in ALS and FTD

Neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are increasing in prevalence but lack targeted therapeutics. Although the pathological mechanisms behind these diseases remain unclear, both ALS and FTD are characterized pathologically by aberrant protein aggregation and inclusion formation within neurons, which correlates with neurodegeneration. Notably, aggregation of several key proteins, including TAR DNA binding protein of 43 kDa (TDP-43), superoxide dismutase 1 (SOD1), and tau, have been implicated in these diseases. Proteomics methods are being increasingly applied to better understand disease-related mechanisms and to identify biomarkers of disease, using model systems as well as human samples. Proteomics-based approaches offer unbiased, high-throughput, and quantitative results with numerous applications for investigating proteins of interest. Here, we review recent advances in the understanding of ALS and FTD pathophysiology obtained using proteomics approaches, and we assess technical and experimental limitations. We compare findings from various mass spectrometry (MS) approaches including quantitative proteomics methods such as stable isotope labeling by amino acids in cell culture (SILAC) and tandem mass tagging (TMT) to approaches such as label-free quantitation (LFQ) and sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) in studies of ALS and FTD. Similarly, we describe disease-related protein-protein interaction (PPI) studies using approaches including immunoprecipitation mass spectrometry (IP-MS) and proximity-dependent biotin identification (BioID) and discuss future application of new techniques including proximity-dependent ascorbic acid peroxidase labeling (APEX), and biotinylation by antibody recognition (BAR). Furthermore, we explore the use of MS to detect post-translational modifications (PTMs), such as ubiquitination and phosphorylation, of disease-relevant proteins in ALS and FTD. We also discuss upstream technologies that enable enrichment of proteins of interest, highlighting the contributions of new techniques to isolate disease-relevant protein inclusions including flow cytometric analysis of inclusions and trafficking (FloIT). These recently developed approaches, as well as related advances yet to be applied to studies of these neurodegenerative diseases, offer numerous opportunities for discovery of potential therapeutic targets and biomarkers for ALS and FTD.

Advances in mass spectrometry-based glycoproteomics

Protein glycosylation, an important PTM, plays an essential role in a wide range of biological processes such as immune response, intercellular signaling, inflammation, and host-pathogen interaction. Aberrant glycosylation has been correlated with various diseases. However, studying protein glycosylation remains challenging because of low abundance, microheterogeneities of glycosylation sites, and poor ionization efficiency of glycopeptides. Therefore, the development of sensitive and accurate approaches to characterize protein glycosylation is crucial. The identification and characterization of protein glycosylation by MS is referred to as the field of glycoproteomics. Methods such as enrichment, metabolic labeling, and derivatization of glycopeptides in conjunction with different MS techniques and bioinformatics tools, have been developed to achieve an unequivocal quantitative and qualitative characterization of glycoproteins. This review summarizes the recent developments in the field of glycoproteomics over the past 6 years (2012 to 2018).

Time-Resolved NMR Analysis of Proteolytic α-Synuclein Processing in vitro and in cellulo

Targeted proteolysis of the disordered Parkinson's disease protein alpha-synuclein (αSyn) constitutes an important event under physiological and pathological cell conditions. In this work, site-specific αSyn cleavage by different endopeptidases in vitro and by endogenous proteases in extracts of challenged and unchallenged cells was studied by time-resolved NMR spectroscopy. Specifically, proteolytic processing was monitored under neutral and low pH conditions and in response to Rotenone-induced oxidative stress. Further, time-dependent degradation of electroporation-delivered αSyn in intact SH-SY5Y and A2780 cells was analyzed. Results presented here delineate a general framework for NMR-based proteolysis studies in vitro and in cellulo, and confirm earlier reports pertaining to the exceptional proteolytic stability of αSyn under physiological cell conditions. However, experimental findings also reveal altered protease susceptibilities in selected mammalian cell lines and upon induced cell stress.

Approaches to identify and characterize microProteins and their potential uses in biotechnology

MicroProteins are small proteins that contain a single protein domain and are related to larger, often multi-domain proteins. At the molecular level, microProteins act by interfering with the formation of higher order protein complexes. In the past years, several microProteins have been identified in plants and animals that strongly influence biological processes. Due to their ability to act as dominant regulators in a targeted manner, microProteins have a high potential for biotechnological use. In this review, we present different ways in which microProteins are generated and we elaborate on techniques used to identify and characterize them. Finally, we give an outlook on possible applications in biotechnology.