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Glycoproteome analysis at a site-specific level and proteome scale stands out as a highly promising approach for gaining insights into the intricate roles of glycans in biological systems. Recent years have witnessed an upsurge in the development of innovative methodologies tailored for precisely this purpose. Breakthroughs in mass spectrometry-based glycoproteomic techniques, enabling the identification, quantification, and systematic exploration of site-specific glycans, have significantly enhanced our capacity to comprehensively and thoroughly characterize glycoproteins. In this short review, we delve into novel tools in advancing site-specific glycoproteomic analysis and summarize pertinent studies published in the past two years. Lastly, we discuss the ongoing challenges and outline future prospects in the field, considering both the analytical strategies of mass spectrometry and the tools employed for data interpretation., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Weiqian Cao reports financial support and article publishing charges were provided by National Natural Science Foundation of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The ocular lens proteome undergoes post-translational and progressive degradation as fiber cells age. The oldest fiber cells and the proteins therein are present at birth and are retained through death. Transparency of the lens is maintained in part by the high abundance Crystallin family proteins (up to 300 mg/mL), which establishes a high dynamic range of protein abundance. As a result, previous data-dependent analysis (DDA) measurements of the lens proteome are less equipped to identify the lowest abundance proteins. To probe more deeply into the lens proteome, we measured the insoluble lens proteome of an 18-year-old human with DDA and data-independent analysis (DIA) methods. By applying more recent library-free DIA search methods, 5,161 protein groups, 50,386 peptides, and 4,960 deamidation sites were detected: significantly outperforming the quantity of identifications in using DDA and pan-human DIA library searches. Finally, by segmenting the lens into multiple fiber cell-age-related regions, we uncovered cell-age-related changes in proteome composition and putative function.

Circulating tumor cells (CTCs) are precursors of metastasis in various cancer types. Many aspects regarding CTC biology remain poorly understood. Here, we describe mass spectrometric analysis of CTCs from a breast cancer xenograft mouse model, including procedures comprising CTC enrichment, separation of different CTC subpopulations, and their quantitative proteomic assessment. This protocol aims to facilitate the identification of protein content dynamics in human CTCs that are physiologically shed from tumor-bearing xenografts, providing a framework for investigating metastasis biology. For complete details on the use and execution of this protocol, please refer to Donato et al. (2020)., Competing Interests: N.A. and C.D. are listed as inventors in patent application EP 19188215.8, ‘‘Angiogenesis promoting agents for prevention of metastatic cancer.’’ N.A. is a paid consultant for companies with an interest in liquid biopsy., (© 2021 The Author(s).)

Specific nuclear sub-compartments that are regions of fundamental processes such as gene expression or DNA repair, contain phosphoinositides (PIPs). PIPs thus potentially represent signals for the localization of specific proteins into different nuclear functional domains. We performed limited proteolysis followed by label-free quantitative mass spectrometry and identified nuclear protein effectors of the most abundant PIP-phosphatidylinositol 4,5-bisphosphate (PIP2). We identified 515 proteins with PIP2-binding capacity of which 191 'exposed' proteins represent a direct PIP2 interactors and 324 'hidden' proteins, where PIP2 binding was increased upon trypsin treatment. Gene ontology analysis revealed that 'exposed' proteins are involved in the gene expression as regulators of Pol II, mRNA splicing, and cell cycle. They localize mainly to non-membrane bound organelles-nuclear speckles and nucleolus and are connected to the actin nucleoskeleton. 'Hidden' proteins are linked to the gene expression, RNA splicing and transport, cell cycle regulation, and response to heat or viral infection. These proteins localize to the nuclear envelope, nuclear pore complex, or chromatin. Bioinformatic analysis of peptides bound in both groups revealed that PIP2-binding motifs are in general hydrophilic. Our data provide an insight into the molecular mechanism of nuclear PIP2 protein interaction and advance the methodology applicable for further studies of PIPs or other protein ligands.

Recent advances in mass spectrometry (MS)-based quantitative proteomics now allow the identification and quantification of deep proteomes and post-translational modifications (PTMs) in relatively short times. Therefore, in the last few years, this technology has proven successful in the circadian field to characterize temporal oscillations of the proteome and more recently PTMs in cellular systems and in tissues. In this chapter, we describe a robust and simple protocol, based on the EasyPhos workflow, to enable preparation of large number of proteomes and phosphoproteomes from mouse tissues for MS-based quantitative analysis. We additionally discuss computational methods to analyze proteome and phosphoproteome time series to determine circadian oscillations.

Snake venoms are complex chemical mixtures of biologically active proteins and non-protein components. Toxins have a wide range of targets and effects to include ion channels and membrane receptors, and platelet aggregation and platelet plug formation. Toxins target these effectors and effects at high affinity and selectivity. From a pharmacological perspective, snake venom compounds are a valuable resource for drug discovery and development. However, a major challenge to drug discovery using snake venoms is isolating and analyzing the bioactive proteins and peptides in these complex mixtures. Getting molecular information from complex mixtures such as snake venoms requires proteomic analyses, generally combined with transcriptomic analyses of venom glands. The present review summarizes current knowledge and highlights important recent advances in venomics with special emphasis on contemporary separation techniques and bioinformatics that have begun to elaborate the complexity of snake venoms. Several analytical techniques such as two-dimensional gel electrophoresis, RP-HPLC, size exclusion chromatography, ion exchange chromatography, MALDI-TOF-MS, and LC-ESI-QTOF-MS have been employed in this regard. The improvement of separation approaches such as multidimensional-HPLC, 2D-electrophoresis coupled to soft-ionization (MALDI and ESI) mass spectrometry has been critical to obtain an accurate picture of the startling complexity of venoms. In the case of bioinformatics, a variety of software tools such as PEAKS also has been used successfully. Such information gleaned from venomics is important to both predicting and resolving the biological activity of the active components of venoms, which in turn is key for the development of new drugs based on these venom components., (Published by Elsevier B.V.)

Cancer has no borders: Generation and analysis of molecular data across multiple centers worldwide is necessary to gain statistically significant clinical insights for the benefit of patients. Here we conceived and standardized a proteotype data generation and analysis workflow enabling distributed data generation and evaluated the quantitative data generated across laboratories of the international Cancer Moonshot consortium. Using harmonized mass spectrometry (MS) instrument platforms and standardized data acquisition procedures, we demonstrate robust, sensitive, and reproducible data generation across eleven international sites on seven consecutive days in a 24/7 operation mode. The data presented from the high-resolution MS1-based quantitative data-independent acquisition (HRMS1-DIA) workflow shows that coordinated proteotype data acquisition is feasible from clinical specimens using such standardized strategies. This work paves the way for the distributed multi-omic digitization of large clinical specimen cohorts across multiple sites as a prerequisite for turning molecular precision medicine into reality.

Sample multiplexing using isobaric tagging is a powerful strategy for proteome-wide protein quantification. One major caveat of isobaric tagging is ratio compression that results from the isolation, fragmentation, and quantification of coeluting, near-isobaric peptides, a phenomenon typically referred to as "ion interference". A robust platform to ensure quality control, optimize parameters, and enable comparisons across samples is essential as new instrumentation and analytical methods evolve. Here, we introduce TKO-iQC, an integrated platform consisting of the Triple Knockout (TKO) yeast digest standard and an automated web-based database search and protein profile visualization application. We highlight two new TKO standards based on the TMTpro reagent (TKOpro9 and TKOpro16) as well as an updated TKO Viewing Tool, TVT2.0. TKO-iQC greatly facilitates the comparison of instrument performance with a straightforward and streamlined workflow.

Immunohistochemistry (IHC) using formalin-fixed, paraffin embedded (FFPE) tissue is limited by epitope masking, posttranslational modification and immunoreactivity loss that occurs in stored tissue by poorly characterized mechanisms. Conformational epitopes recognized by many programmed-death-ligand-1 (PD-L1) IHC assays are particularly susceptible to degradation and provide an ideal model for understanding signal loss in stored FFPE tissue. Here we assessed 1206 tissue sections to evaluate environmental factors impacting immunoreactivity loss. PD-L1 IHC using four antibodies (22C3, 28-8, E1L3N, and SP142), raised against intracellular and extracellular epitopes, was assessed in stored FFPE tissue alongside quantitative mass spectrometry (MS). Global proteome analyses were used to assess proteome-wide oxidation across an inventory of 3041 protein groups (24,737 distinct peptides). PD-L1 quantitation correlated well with IHC expression on unaged sections (R 2  = 0.744; P < 0.001), with MS demonstrating no loss of PD-L1 protein, even in sections with significant signal loss by IHC impacting diagnostic category. Clones 22C3 and 28-8 were most susceptible to signal loss, with E1L3N demonstrating the most robust signal (56%, 58%, and 33% reduction respectively; p < 0.05). Increased humidity and temperature resulted in significant acceleration of immunoreactivity loss, which was mitigated by storage with desiccant. MS demonstrated only modest oxidation of 274 methionine-containing peptides and aligned with IHC results suggesting peptide oxidation is not a major factor. These data imply immunoreactivity loss driven by humidity and temperature results in structural distortion of epitopes rendering them unsuitable for antibody binding following epitope retrieval. Limitations of IHC biomarker analysis from stored tissue sections may be mitigated by cost-effective use of desiccant when appropriate. In some scenarios, complementary MS is a preferred approach for retrospective analyses of archival FFPE tissue collections.

One of the major goals of the Chromosome-Centric Human Proteome Project (C-HPP) is to catalog and annotate a myriad of heterogeneous proteoforms, produced by ca. 20 thousand genes. To achieve a detailed and personalized understanding into proteomes, we suggest using a customized RNA-seq library of potential proteoforms, which includes aberrant variants specific to certain biological samples. Two-dimensional electrophoresis coupled with high-performance liquid chromatography allowed us to downgrade the difficulty of biological mixing following shotgun mass spectrometry. To benchmark the proposed pipeline, we examined heterogeneity of the HepG2 hepatoblastoma cell line proteome. Data are available via ProteomeXchange with identifier PXD018450., Competing Interests: The authors declare no conflict of interest.

Plants are essential for life and are extremely diverse organisms with unique molecular capabilities 1 . Here we present a quantitative atlas of the transcriptomes, proteomes and phosphoproteomes of 30 tissues of the model plant Arabidopsis thaliana. Our analysis provides initial answers to how many genes exist as proteins (more than 18,000), where they are expressed, in which approximate quantities (a dynamic range of more than six orders of magnitude) and to what extent they are phosphorylated (over 43,000 sites). We present examples of how the data may be used, such as to discover proteins that are translated from short open-reading frames, to uncover sequence motifs that are involved in the regulation of protein production, and to identify tissue-specific protein complexes or phosphorylation-mediated signalling events. Interactive access to this resource for the plant community is provided by the ProteomicsDB and ATHENA databases, which include powerful bioinformatics tools to explore and characterize Arabidopsis proteins, their modifications and interactions.

Protein-protein interactions are essential biologic processes that occur at inter- and intracellular levels. To gain insight into the various complex cellular functions of these interactions, it is necessary to assess them under physiologic conditions. Recent advances in various proteomic technologies allow to investigate protein-protein interaction networks in living cells. The combination of proximity-dependent labelling and chemical cross-linking will greatly enhance our understanding of multi-protein complexes that are difficult to prepare, such as organelle-bound membrane proteins. In this review, we describe our current understanding of mass spectrometry-based proteomics mapping methods for elucidating organelle-bound membrane protein complexes in living cells, with a focus on protein-protein interactions in mitochondrial subcellular compartments., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Japanese Biochemical Society.)

Recently, several mass-spectrometry- and protein-denaturation-based proteomic methods have been developed to facilitate protein target discovery efforts in drug mode-of-action studies. These methods, which include the stability of proteins from rates of oxidation (SPROX), pulse proteolysis (PP), chemical denaturation and protein precipitation (CPP), and thermal proteome profiling (TPP) techniques, have been used in an increasing number of applications in recent years. However, while the advantages and disadvantages to using these different techniques have been reviewed, the analytical characteristics of these methods have not been directly compared. Reported here is such a direct comparison using the well-studied immunosuppressive drug, cyclosporine A (CsA), and the proteins in a yeast cell lysate. Also described is a one-pot strategy that can be utilized with each technique to streamline data acquisition and analysis. We find that there are benefits to utilizing all four strategies for protein target discovery including increased proteomic coverage and reduced false positive rates that approach 0%. Moreover, the one-pot strategy described here makes such an experiment feasible, because of the 10-fold reduction in reagent costs and instrument time it affords.

Mass spectrometry (MS)-based proteomics is moving beyond the simple generation of protein inventories of biological samples. The ability of MS to quantitatively probe complex protein mixtures is increasingly being used to study protein structural and biophysical properties at proteome-scale. MS provides a readout for proteome-wide structural alterations, folding and stability, aggregation, and molecular interactions, all in native-like conditions such as cell lysates or even intact cells. We provide an overview of methods that yield such proteome-wide structural information, covering cross-linking-MS, limited proteolysis-MS, co-fractionation-MS, hydroxyl radical footprinting-MS, thermal proteome profiling, and numerous approaches for monitoring molecular interactions at large scale. Methods to determine structural properties of the native proteome will drive structural systems biology., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Biological tissues exhibit complex spatial heterogeneity that directs the functions of multicellular organisms. Quantifying protein expression is essential for elucidating processes within complex biological assemblies. Imaging mass spectrometry (IMS) is a powerful emerging tool for mapping the spatial distribution of metabolites and lipids across tissue surfaces, but technical challenges have limited the application of IMS to the analysis of proteomes. Methods for probing the spatial distribution of the proteome have generally relied on the use of labels and/or antibodies, which limits multiplexing and requires a priori knowledge of protein targets. Past efforts to make spatially resolved proteome measurements across tissues have had limited spatial resolution and proteome coverage and have relied on manual workflows. Here, we demonstrate an automated approach to imaging that utilizes label-free nanoproteomics to analyze tissue voxels, generating quantitative cell-type-specific images for >2000 proteins with 100-µm spatial resolution across mouse uterine tissue sections preparing for blastocyst implantation.

Proteins are decorated with a diverse array of post-translational modifications (PTMs) that regulate their spatial and temporal functions. Recent mass spectrometry (MS)-based studies have identified hundreds of thousands of PTM sites in mammalian proteomes. However, the signaling cues and enzymes regulating individual sites are often not known and their functional roles remain uncharacterized. Quantification of PTM site stoichiometry can help in prioritizing sites for functional analyses and is important for constructing mechanistic models of PTM-dependent protein regulation. Here, we review the concept of PTM site stoichiometry, critically evaluate the merits and drawbacks of different MS-based methods used for quantifying PTM site stoichiometry, and discuss the usefulness and limitations of stoichiometry in informing on the biological function of modified sites., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Progress in proteomics research has led to a demand for powerful analytical tools with high separation efficiency and sensitivity for confident identification and quantification of proteins, posttranslational modifications, and protein complexes expressed in cells and tissues. This demand has significantly increased interest in capillary electrophoresis-mass spectrometry (CE-MS) in the past few years. This review provides highlights of recent advances in CE-MS for proteomics research, including a short introduction to top-down mass spectrometry and native mass spectrometry (native MS), as well as a detailed overview of CE methods. Both the potential and limitations of these methods for the analysis of proteins and peptides in synthetic and biological samples and the challenges of CE methods are discussed, along with perspectives about the future direction of CE-MS. @ 2019 Wiley Periodicals, Inc. Mass Spec Rev 00:1-16, 2019., (© 2019 Wiley Periodicals, Inc.)

Chemical cross-linking combined with mass spectrometry (CL-MS) is a powerful method for characterizing the architecture of protein assemblies and for mapping protein-protein interactions. Despite its proven utility, confident identification of cross-linked peptides remains a formidable challenge, especially when the peptides are derived from complex mixtures. MS cleavable cross-linkers are gaining importance for CL-MS as they permit reliable identification of cross-linked peptides by whole proteome database searching using MS/MS information. Here we introduce a novel class of MS cleavable cross-linkers called isotopomeric cross-linkers (ICLs), which allow for confident and efficient identification of cross-linked peptides by whole proteome database searching. ICLs are simple, symmetrical molecules that asymmetrically incorporate heavy and light stable isotopes into the two arms of the cross-linker. As a result of this property, ICLs automatically generate pairs of isotopomeric cross-linked peptides, which differ only by the positions of the heavy and light isotopes. Upon fragmentation during MS analysis, these isotopomeric cross-linked peptides generate unique isotopic doublet ions that correspond to the individual peptides in the cross-link. The doublet ion information is used to determine the masses of the two cross-linked peptides from the same MS2 spectrum that is also used for peptide spectrum matching (PSM) by sequence database searching. Here we present the rationale for and mechanism of cross-linked peptide identification by ICL-MS. We describe the synthesis of the ICL-1 reagent, the ICL-MS workflow, and the performance characteristics of ICL-MS for identifying cross-linked peptides derived from increasingly complex mixtures by whole proteome database searching.

Capillary electrophoresis combined with mass spectrometry (CE-MS) has been used for several years for the investigation of proteins and peptides as biomarkers for diagnosis and prognosis of diseases. In addition, the technology has recently been introduced to support the stratification of patients in clinical trials and in large clinical studies. In this review, we aim at presenting the development of CE-MS over the last 20 years, by focusing on the clinical potential of proteome and peptidome analysis and highlighting some of the key technical issues and advancements that have been made in this context towards implementation. Based on the reviewed literature, it has become evident that CE-MS is now an accepted tool in clinical application in several disease areas. Apart from a critical overview on the current state-of-the-art in CE-MS, we also indicate the expected developments for potential future use., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Biological processes supporting life are orchestrated by a highly dynamic array of protein structures and interactions comprising the interactome. Defining the interactome, visualizing how structures and interactions change and function to support life is essential to improved understanding of fundamental molecular processes, but represents a challenge unmet by any single analytical technique. Chemical cross-linking with mass spectrometry provides identification of proximal amino acid residues within proteins and protein complexes, yielding low resolution structural information. This approach has predominantly been employed to provide structural insight on isolated protein complexes, and has been particularly useful for molecules that are recalcitrant to conventional structural biology studies. Here we discuss recent developments in cross-linking and mass spectrometry technologies that are providing large-scale or systems-level interactome data with successful applications to isolated organelles, cell lysates, virus particles, intact bacterial and mammalian cultured cells and tissue samples., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Lysine acetylation is a prevalent posttranslational modification that acts as a regulator of protein function, subcellular localization, and interactions. A growing body of work has highlighted the importance of temporal alterations in protein acetylation during infection with a range of human viruses. It has become clear that both cellular and viral proteins are decorated by lysine acetylations, and that these modifications contribute to core host defense and virus replication processes. Further defining the extent and dynamics of protein acetylation events during the progression of an infection can provide an important new perspective on the intricate mechanisms underlying the biology and pathogenesis of virus infections. Here, we provide protocols for identifying, quantifying, and probing the regulation of lysine acetylations during viral infection. We describe the use of acetyl-lysine immunoaffinity purification and quantitative mass spectrometry for assessing the cellular acetylome at different stages of an infection. As an alternative to traditional antibody-mediated western blotting, we discuss the benefits of targeted mass spectrometry approaches for detecting and quantifying site-specific acetylations on proteins of interest. Specifically, we provide a protocol using parallel reaction monitoring (PRM). We further discuss experimental considerations that are specific to studying viral infections. Finally, we provide a brief overview of the types of assays that can be employed to characterize the function of an acetylation event in the context of infection. As a method to interrogate the regulation of acetylation, we describe the Fluor de Lys assay for monitoring the enzymatic activities of deacetylases., (© 2019 Elsevier Inc. All rights reserved.)

Selenoproteins, defined by the presence of selenocysteines (Sec), play important roles in a wide range of biological processes. All known selenoproteins are marked by the presence of Sec insertion sequence (SECIS) at their mRNA. The lack of an effective analytical method has hindered our ability to explore the selenoproteome and new selenoproteins beyond SECIS. Here, we develop a Sec-specific mass spectrometry-based technique, termed "SecMS," which allows the systematic profiling of selenoproteomes by selective alkylation of Sec. Using SecMS, we quantitatively characterized the age- and stress-regulated selenoproteomes for nine tissues from mice of different ages and mammalian cells, demonstrating tissue-specific selenoproteomes and an age-dependent decline in specific selenoproteins in brains and hearts. We established an integrated platform using SecMS and SECIS-independent selenoprotein (SIS) database and further identified five candidate selenoproteins. The application of this integrated platform provides an effective strategy to explore the selenoproteome independent of SECIS., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Over the past decade, a suite of new mass-spectrometry-based proteomics methods has been developed that now enables the conformational properties of proteins and protein-ligand complexes to be studied in complex biological mixtures, from cell lysates to intact cells. Highlighted here are seven of the techniques in this new toolbox. These techniques include chemical cross-linking (XL-MS), hydroxyl radical footprinting (HRF), Drug Affinity Responsive Target Stability (DARTS), Limited Proteolysis (LiP), Pulse Proteolysis (PP), Stability of Proteins from Rates of Oxidation (SPROX), and Thermal Proteome Profiling (TPP). The above techniques all rely on conventional bottom-up proteomics strategies for peptide sequencing and protein identification. However, they have required the development of unconventional proteomic data analysis strategies. Discussed here are the current technical challenges associated with these different data analysis strategies as well as the relative analytical capabilities of the different techniques. The new biophysical capabilities that the above techniques bring to bear on proteomic research are also highlighted in the context of several different application areas in which these techniques have been used, including the study of protein ligand binding interactions (e.g., protein target discovery studies and protein interaction network analyses) and the characterization of biological states.

CRISPR pools are being widely employed to identify gene functions. However, current technology, which utilizes DNA as barcodes, permits limited phenotyping and bulk-cell resolution. To enable novel screening capabilities, we developed a barcoding system operating at the protein level. We synthesized modules encoding triplet combinations of linear epitopes to generate >100 unique protein barcodes (Pro-Codes). Pro-Code-expressing vectors were introduced into cells and analyzed by CyTOF mass cytometry. Using just 14 antibodies, we detected 364 Pro-Code populations; establishing the largest set of protein-based reporters. By pairing each Pro-Code with a different CRISPR, we simultaneously analyzed multiple phenotypic markers, including phospho-signaling, on dozens of knockouts. Pro-Code/CRISPR screens found two interferon-stimulated genes, the immunoproteasome component Psmb8 and a chaperone Rtp4, are important for antigen-dependent immune editing of cancer cells and identified Socs1 as a negative regulator of Pd-l1. The Pro-Code technology enables simultaneous high-dimensional protein-level phenotyping of 100s of genes with single-cell resolution., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Over the past decade, cross-linking mass spectrometry (CLMS) has developed into a robust and flexible tool that provides medium-resolution structural information. CLMS data provide a measure of the proximity of amino acid residues and thus offer information on the folds of proteins and the topology of their complexes. Here, we highlight notable successes of this technique as well as common pipelines. Novel CLMS applications, such as in-cell cross-linking, probing conformational changes and tertiary-structure determination, are now beginning to make contributions to molecular biology and the emerging fields of structural systems biology and interactomics.

The increasing throughput and sharing of proteomics mass spectrometry data have now yielded over one-third of a million public mass spectrometry runs. However, these discoveries are not continuously aggregated in an open and error-controlled manner, which limits their utility. To facilitate the reusability of these data, we built the MassIVE Knowledge Base (MassIVE-KB), a community-wide, continuously updating knowledge base that aggregates proteomics mass spectrometry discoveries into an open reusable format with full provenance information for community scrutiny. Reusing >31 TB of public human data stored in a mass spectrometry interactive virtual environment (MassIVE), the MassIVE-KB contains >2.1 million precursors from 19,610 proteins (48% larger than before; 97% of the total) and doubles proteome coverage to 6 million amino acids (54% of the proteome) with strict library-scale false discovery controls, thereby providing evidence for 430 proteins for which sufficient protein-level evidence was previously missing. Furthermore, MassIVE-KB can inform experimental design, helps identify and quantify new data, and provides tools for community construction of specialized spectral libraries., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Mammalian selenocysteine (Sec)-containing proteins, selenoproteins, are important to (patho)physiological processes, including redox homeostasis. Sec residues have been recalcitrant to mass spectrometry-based chemoproteomic methods that enrich for reactive cysteine (Cys) residues with electrophilic chemical probes, despite confirmed reactivity of Sec with these electrophiles. Highly abundant Cys peptides likely suppress low-abundant Sec peptides. By exploiting the decreased pK a of Sec relative to Cys, we have developed a chemoproteomic platform that relies on low pH (pH 5.75) electrophile labeling, reducing Cys reactivity and enhancing identification of Sec-containing peptides across mouse tissues and cell lines. The utility of this Sec-profiling platform is underscored by evaluation of the selectivity of auranofin, an inhibitor of the selenoprotein, thioredoxin reductase, against both reactive Cys- and Sec-containing proteins. Platform limitations pertain to the non-physiological low-pH conditions that could perturb protein structure and function. Future work necessitates the discovery of Sec-selective electrophiles that function at physiological pH., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Deinagkistrodon acutus, Trimeresurus stejnegeri, Protobothrops mucrosquamatus, Daboia russelii siamensis, Bungarus multicinctus and Naja atra are the six medically important venomous snake species in Taiwan. In this study, we characterized and compared their venom protein profiles using proteomic approaches. The major snake venom proteins were identified by GeLC-MS/MS and the total venom proteome was characterized by in-solution digestion coupled with LC-MS/MS. A total of 27-52 proteins, categorized into 23 protein families, were identified in each snake's venom. The major venom components found in Viperidae species (D. acutus, T. stejnegeri, P. mucrosquamatus and D. russelii) were C-type lectin, snake venom serine proteinase, venom metalloproteinase and phospholipase A 2 , whereas three-finger toxin and phospholipase A 2 were the major components detected in the venom of Elapidae snakes (B. multicinctus and N. atra). This study also provided the first demonstration of some low-abundance proteins in these six snake venoms, including 5'-nucleotidase, glutaminyl-peptide cyclotransferase and phosphodiesterase, among others. Furthermore, we found that cobra venom factor (CVF) is a cobra-specific protein. We produced anti-peptide antibodies against CVF and used it to develop a highly sensitive SISCAPA-MRM assay for quantifying CVF. The limit of detection and lower limit of quantification were 3.2 and 9.6 attomoles, respectively. This assay was used to precisely quantify CVF in 1 μg crude venom proteins from three Naja species and king cobra. The amount of CVF varied from 0.9 to 54.36 femtomoles (equivalent to 0.16-10.03 mg/g of venom protein)., Biological Significance: There are six medically significant venomous snakes in Taiwan. The venoms of the four Viperidae species (Deinagkistrodon acutus, Trimeresurus stejnegeri, Protobothrops mucrosquamatus and Daboia russelii siamensis) cause local tissue swelling; this symptom is also seen in N. atra envenomation in humans, potentially complicating the differential diagnosis of envenomation by N. atra and Viperidae species. Thus, characterization of the venom proteomes of the six Taiwanese snakes, including the relative abundance of the major components and species-specific protein(s) in each venom type, could be useful for future venom research, including the development of new assay(s) for detecting snake species-specific venom protein(s) and new type(s) of antivenom., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Introduction: Exploring post-translational modifications (PTMs) with the use of mass spectrometry (PTMomics) is a rapidly developing area, with methods for discovery/quantification being developed and advanced on a regular basis. PTMs are highly important for the regulation of protein function, interaction and activity, both in physiological and disease states. Changes in PTMs can either cause, or be the result of a disease, making them central for biomarker studies and studies of disease pathogenesis. Recently, it became possible to study multiple PTMs simultaneously from low amount of sample material, thereby increasing coverage of the PTMome obtainable from a single sample. Thus, quantitative PTMomics holds great potential to discover biomarkers from tissue and body fluids as well as elucidating disease mechanisms through characterization of signaling pathways. Areas covered: Recent mass spectrometry-based methods for assessment of the PTMome, with focus on the most studied PTMs, are highlighted. Furthermore, both data dependent and data independent acquisition methods are evaluated. Finally, current challenges in the field are discussed. Expert commentary: PTMomics holds great potential for clinical and biomedical research, especially with the generation of spectral libraries of peptides and PTMs from individual patients (permanent PTM maps) for use in personalized medicine.

Owing to their close proximity, pericardial fluid (PF)'s proteome may mirror the pathophysiological status of the heart. Despite this diagnosis potential, the knowledge of PF's proteome is scarce. Large amounts of albumin hamper the characterization of the least abundant proteins in PF. Aiming to expand PF's proteome and to validate the technique for future applications, we have fractionated and characterized the PF, using N-(trimethoxysilylpropyl)ethylenediamine triacetic acid (EDTA)-functionalized magnetic nanoparticles (NPs@EDTA) followed by a GeLC-MS/MS approach. Similarly to an albumin-depletion kit, NPs@EDTA-based fractionation was efficient in removing albumin. Both methods displayed comparable inter-individual variability, but NPs@EDTA outperformed the former with regard to the protein dynamic range as well as to the monitoring of biological processes. Overall, 565 proteins were identified, of which 297 (>50%) have never been assigned to PF. Moreover, owing to this method's good proteome reproducibility, affordability, rapid automation and high binding ability of NP@EDTA, it bears a great potential towards future clinical application., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Post-translational control of proteins through covalent attachment of ubiquitin plays important roles in all eukaryotic cell functions. The ubiquitin system in humans consists of 2 E1, 35 E2 and >600 E3 ubiquitin ligases as well as hundreds of deubiquitylases, which reverse ubiquitin attachment. Moreover, there are hundreds of proteins with ubiquitin-binding domains that bind one of the eight possible polyubiquitin chains. Dysfunction of the ubiquitin system is associated with many diseases such as cancer, autoimmunity and neurodegeneration, demonstrating the importance of ubiquitylation. Therefore, enzymes of the ubiquitin system are considered highly attractive drug targets. In recent years, mass spectrometry (MS)-based techniques have become increasingly important in the deciphering of the ubiquitin system. This short review addresses the state-of-the-art MS techniques for the identification of ubiquitylated proteins and their ubiquitylation sites. We also discuss the identification and quantitation of ubiquitin chain topologies and highlight how the activity of enzymes in the ubiquitin pathway can be measured. Finally, we present current MS tools that can be used for drug discovery in the ubiquitin space., (© 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.)

Introduction: In several biomedical research fields, the cross-linking of peptides and proteins has an important impact on health and wellbeing. It is therefore of crucial importance to study this class of post-translational modifications in detail. The huge potential of mass spectrometric technologies in the mapping of these protein-protein cross-links is however overshadowed by the challenges that the field has to overcome. Areas covered: In this review, we summarize the different pitfalls and challenges that the protein-protein cross-linking field is confronted with when using mass spectrometry approaches. We additionally focus on native disulfide bridges as an example and provide some examples of cross-links that are important in the biomedical field. Expert commentary: The current flow of methodological improvements, mainly from the chemical cross-linking field, has delivered a significant contribution to deciphering native and insult-induced cross-links. Although an automated data analysis of proteome-wide peptide cross-linking is currently only possible in chemical cross-linking experiments, the field is well on the way towards a more automated analysis of native and insult-induced cross-links in raw mass spectrometry data that will boost its potential in biomedical applications.

Glycoproteomics involves the study of glycosylation events on protein sequences ranging from purified proteins to whole proteome scales. Understanding these complex post-translational modification (PTM) events requires elucidation of the glycan moieties (monosaccharide sequences and glycosidic linkages between residues), protein sequences, as well as site-specific attachment of glycan moieties onto protein sequences, in a spatial and temporal manner in a variety of biological contexts. Compared with proteomics, bioinformatics for glycoproteomics is immature and many researchers still rely on tedious manual interpretation of glycoproteomics data. As sample preparation protocols and analysis techniques have matured, the number of publications on glycoproteomics and bioinformatics has increased substantially; however, the lack of consensus on tool development and code reuse limits the dissemination of bioinformatics tools because it requires significant effort to migrate a computational tool tailored for one method design to alternative methods. This review discusses algorithms and methods in glycoproteomics, and refers to the general proteomics field for potential solutions. It also introduces general strategies for tool integration and pipeline construction in order to better serve the glycoproteomics community. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:475-498, 2017., (© 2016 Wiley Periodicals, Inc.)

The redox conditions that reign inside a cell have a determining effect on a number of biological processes. Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are key redox players and have been linked to a number of pathologies. They have also been shown to play an important regulating role in cell signaling events. On the proteome level, thiol groups of cysteinyl side chains constitute the major targets of ROS and RNS. A number of analytical techniques based on mass spectrometry have been developed to characterize the cysteine redoxome, often facing a number of technical challenges, mostly related to the lability, heterogeneity, and low abundance of the oxidized forms. Furthermore, any posttranslational modification (PTM) quantification method needs to take the parent protein's expression level into account. While taking all these limitations into consideration, we have developed a quantitative analytical strategy named OxiTMT, based on chemical labeling with iodoacetyl isobaric tandem mass tags (iodoTMT). OxiTMT allowed the generation of quantitative redox data that could be normalized by the protein's expression profile in up to three different conditions. The method was tested on Escherichia coli with or without an oxidative treatment. Results showed the method to be adequate for the analysis of cysteine PTMs with a good coverage of the cysteine redoxome, especially for the low abundant oxidized species. Some of the challenges that face reporter ion quantification of PTMs by mass spectrometry were also assessed. This study serves as a proof of concept of the established protocol and consequent data treatment step. The use of tandem mass tags opens the ways towards the application of the method to the study of tissues and sera. Graphical abstract OxiTMT workflow.

Recently, "superbinder" SH2 domain variants with three amino acid substitutions (sSH2) were reported to have 100-fold or greater affinity for protein-phosphotyrosine (pY) than natural SH2 domains. Here we report a protocol in which His-tagged Src sSH2 efficiently captures pY-peptides from protease-digested HeLa cell total protein extracts. Affinity purification of pY-peptides by this method shows little bias for pY-proximal amino acid sequences, comparable to that achieved by using antibodies to pY, but with equal or higher yield. Superbinder-SH2 affinity purification mass spectrometry (sSH2-AP-MS) therefore provides an efficient and economical approach for unbiased pY-directed phospho-proteome profiling without the use of antibodies., (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Proteomics involves the applications of technologies for the identification and quantification of overall proteins present content of a cell, tissue or an organism. It supplements the other "omics" technologies such as genomic and transcriptomics to expound the identity of proteins of an organism, and to cognize the structure and functions of a particular protein. Proteomics-based technologies are utilized in various capacities for different research settings such as detection of various diagnostic markers, candidates for vaccine production, understanding pathogenicity mechanisms, alteration of expression patterns in response to different signals and interpretation of functional protein pathways in different diseases. Proteomics is practically intricate because it includes the analysis and categorization of overall protein signatures of a genome. Mass spectrometry with LC-MS-MS and MALDI-TOF/TOF being widely used equipment is the central among current proteomics. However, utilization of proteomics facilities including the software for equipment, databases and the requirement of skilled personnel substantially increase the costs, therefore limit their wider use especially in the developing world. Furthermore, the proteome is highly dynamic because of complex regulatory systems that control the expression levels of proteins. This review efforts to describe the various proteomics approaches, the recent developments and their application in research and analysis., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Rationale: In quantitative analysis of protein biomarkers and therapeutic proteins by liquid chromatography/mass spectrometry (LC/MS), it is a preferred and well-established approach to digest with proteolytic enzymes to produce smaller peptide fragments which are more suitable for LC/MS analysis than the intact protein. In-solution digestion is one widely used method for protein digestion. Proteolytically resistant proteins often require digestion times that extend beyond normal working hours and prohibit same day analysis. We evaluated the performance of an immobilized enzyme reactor (IMER) to determine if this technology could reduce method development time, digestion time and increase throughput., Methods: We digested human plasma samples using a commercially available IMER, Flash Digest, and compared it to an in-solution digestion method for analysis of three different apolipoprotein biomarkers APOE, APOC2, and APOC3. The plasma digests were analyzed via LC/MS using electrospray ionization (ESI) and multiple reaction monitoring (MRM). Value assigned calibrators were selected over a relevant physiological concentration range for each protein of interest. Quality control samples (QCs) and 'unknown' human plasma samples were analyzed with both methods., Results: Flash Digest significantly reduced digestion time for APOC3, the most proteolytically resistant of the three proteins, to 30 min compared with overnight used with in-solution digestion. The Flash Digest achieved comparable digestion efficiency with minimal method development and reduced sample preparation time. Both methods showed linearity over a physiologically relevant concentration range. Precision was evaluated and a percentage coefficient of variance (% CV) less than 8% was obtained during intra-day reproducibility evaluation for all three apolipoproteins with Flash Digest. Concentrations observed for QCs and unknown samples using Flash Digest were comparable to the in-solution method., Conclusions: An IMER such as Flash Digest may be a potential alternative to in-solution digestion to accelerate digestion of proteolytically resistant proteins in a quantitative proteomics experiments, reduce method development time and increase throughput. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

Protein folding is an intricate and precise process in living cells. Most exported proteins evade cytoplasmic folding, become targeted to the membrane, and then trafficked into/across membranes. Their targeting and translocation-competent states are nonnatively folded. However, once they reach the appropriate cellular compartment, they can fold to their native states. The nonnative states of preproteins remain structurally poorly characterized since increased disorder, protein sizes, aggregation propensity, and the observation timescale are often limiting factors for typical structural approaches such as X-ray crystallography and NMR. Here, we present an alternative approach for the in vitro analysis of nonfolded translocation-competent protein states and their comparison with their native states. We make use of hydrogen/deuterium exchange coupled with mass spectrometry (HDX-MS), a method based on differentiated isotope exchange rates in structured vs unstructured protein states/regions, and highly dynamic vs more rigid regions. We present a complete structural characterization pipeline, starting from the preparation of the polypeptides to data analysis and interpretation. Proteolysis and mass spectrometric conditions for the analysis of the labeled proteins are discussed, followed by the analysis and interpretation of HDX-MS data. We highlight the suitability of HDX-MS for identifying short structured regions within otherwise highly flexible protein states, as illustrated by an exported protein example, experimentally tested in our lab. Finally, we discuss statistical analysis in comparative HDX-MS. The protocol is applicable to any protein and protein size, exhibiting slow or fast loss of translocation competence. It could be easily adapted to more complex assemblies, such as the interaction of chaperones with nonnative protein states., (© 2017 Elsevier Inc. All rights reserved.)

Every data-rich community research effort requires a clear plan for ensuring the quality of the data interpretation and comparability of analyses. To address this need within the Human Proteome Project (HPP) of the Human Proteome Organization (HUPO), we have developed through broad consultation a set of mass spectrometry data interpretation guidelines that should be applied to all HPP data contributions. For submission of manuscripts reporting HPP protein identification results, the guidelines are presented as a one-page checklist containing 15 essential points followed by two pages of expanded description of each. Here we present an overview of the guidelines and provide an in-depth description of each of the 15 elements to facilitate understanding of the intentions and rationale behind the guidelines, for both authors and reviewers. Broadly, these guidelines provide specific directions regarding how HPP data are to be submitted to mass spectrometry data repositories, how error analysis should be presented, and how detection of novel proteins should be supported with additional confirmatory evidence. These guidelines, developed by the HPP community, are presented to the broader scientific community for further discussion.

Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test data sets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation-window setups. For consistent evaluation, we developed LFQbench, an R package, to calculate metrics of precision and accuracy in label-free quantitative MS and report the identification performance, robustness and specificity of each software tool. Our reference data sets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics., Competing Interests: The authors declare the following competing financial interests: S.A.T. is employed by SCIEX, O.M.B. and L.R. are employed by Biognosys AG.

Numerous biological processes are concurrently and coordinately active in every living cell. Each of them encompasses synthetic, catalytic and regulatory functions that are, almost always, carried out by proteins organized further into higher-order structures and networks. For decades, the structures and functions of selected proteins have been studied using biochemical and biophysical methods. However, the properties and behaviour of the proteome as an integrated system have largely remained elusive. Powerful mass-spectrometry-based technologies now provide unprecedented insights into the composition, structure, function and control of the proteome, shedding light on complex biological processes and phenotypes.

Background: Cancer research often focuses on protein quantification in model cancer cell lines and cancer tissues. SWATH (sequential windowed acquisition of all theoretical fragment ion spectra), the state of the art method, enables the quantification of all proteins included in spectral library. Spectral library contains fragmentation patterns of each detectable protein in a sample. Thorough spectral library preparation will improve quantitation of low abundant proteins which usually play an important role in cancer., Aim: Our research is focused on the optimization of spectral library preparation aimed at maximizing the number of identified proteins in MCF-7 breast cancer cell line. First, we optimized the sample preparation prior entering the mass spectrometer. We examined the effects of lysis buffer composition, peptide dissolution protocol and the material of sample vial on the number of proteins identified in spectral library. Next, we optimized mass spectrometry (MS) method for spectral library data acquisition., Conclusion: Our thorough optimized protocol for spectral library building enabled the identification of 1,653 proteins (FDR < 1%) in 1 µg of MCF-7 lysate. This work contributed to the enhancement of protein coverage in SWATH digital biobanks which enable quantification of arbitrary protein from physically unavailable samples. In future, high quality spectral libraries could play a key role in preparing of patient proteome digital fingerprints.Key words: biomarker - mass spectrometry - proteomics - digital biobanking - SWATH - protein quantificationThis work was supported by the project MEYS - NPS I - LO1413.The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study.The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers.Submitted: 7. 5. 2016Accepted: 9. 6. 2016.

A combination of (atomic force microscopy)-based fishing (AFM-fishing) and mass spectrometry allows to capture protein molecules from solutions, concentrate and visualize them on an atomically flat surface of the AFM chip and identify by subsequent mass spectrometric analysis. In order to increase the AFM-fishing efficiency we have applied pulsed voltage with the rise time of the front of about 1 ns to the AFM chip. The AFM-chip was made using a conductive material, highly oriented pyrolytic graphite (HOPG). The increased efficiency of AFM-fishing has been demonstrated using detection of cytochrome b5 protein. Selection of the stimulating pulse with a rise time of 1 ns, corresponding to the GHz frequency range, by the effect of intrinsic emission from water observed in this frequency range during water injection into the cell.

The significance of non-histone lysine methylation in cell biology and human disease is an emerging area of research exploration. The development of small molecule inhibitors that selectively and potently target enzymes that catalyze the addition of methyl-groups to lysine residues, such as the protein lysine mono-methyltransferase SMYD2, is an active area of drug discovery. Critical to the accurate assessment of biological function is the ability to identify target enzyme substrates and to define enzyme substrate specificity within the context of the cell. Here, using stable isotopic labeling with amino acids in cell culture (SILAC) coupled with immunoaffinity enrichment of mono-methyl-lysine (Kme1) peptides and mass spectrometry, we report a comprehensive, large-scale proteomic study of lysine mono-methylation, comprising a total of 1032 Kme1 sites in esophageal squamous cell carcinoma (ESCC) cells and 1861 Kme1 sites in ESCC cells overexpressing SMYD2. Among these Kme1 sites is a subset of 35 found to be potently down-regulated by both shRNA-mediated knockdown of SMYD2 and LLY-507, a selective small molecule inhibitor of SMYD2. In addition, we report specific protein sequence motifs enriched in Kme1 sites that are directly regulated by endogenous SMYD2 activity, revealing that SMYD2 substrate specificity is more diverse than expected. We further show direct activity of SMYD2 toward BTF3-K2, PDAP1-K126 as well as numerous sites within the repetitive units of two unique and exceptionally large proteins, AHNAK and AHNAK2. Collectively, our findings provide quantitative insights into the cellular activity and substrate recognition of SMYD2 as well as the global landscape and regulation of protein mono-methylation., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Proteomic and RNomic approaches have identified many components of different ribonucleoprotein particles (RNPs), yet still little is known about the organization and protein proximities within these heterogeneous and highly dynamic complexes. Here we describe a targeted cross-linking approach, which combines cross-linking from a known anchor site with affinity purification and mass spectrometry (MS) to identify the changing vicinity interactomes along RNP maturation pathways. Our method confines the reaction radius of a heterobifunctional cross-linker to a specific interaction surface, increasing the probability to capture low abundance conformations and transient vicinal interactors too infrequent for identification by traditional cross-linking-MS approaches, and determine protein proximities within RNPs. Applying the method to two conserved RNA-associated complexes in Saccharomyces cerevisae, the mRNA export receptor Mex67:Mtr2 and the pre-ribosomal Nop7 subcomplex, we identified dynamic vicinal interactomes within those complexes and along their changing pathway milieu. Our results therefore show that this method provides a new tool to study the changing spatial organization of heterogeneous dynamic RNP complexes., (© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The production of structurally significant product ions during the dissociation of phosphopeptides is a key to the successful determination of phosphorylation sites. These diagnostic ions can be generated using the widely adopted MS/MS approach, MS3 (Data Dependent Neutral Loss - DDNL), or by multistage activation (MSA). The main purpose of this work is to introduce a false-localization rate (FLR) probabilistic model to enable unbiased phosphoproteomics studies. Briefly, our algorithm infers a probabilistic function from the distribution of the identified phosphopeptides' XCorr Delta scores (XD-Scores) in the current experiment. Our module infers p-values by relying on Gaussian mixture models and a logistic function. We demonstrate the usefulness of our probabilistic model by revisiting the "to MSA, or not to MSA" dilemma. For this, we use human leukemia-derived cells (K562) as a study model and enriched for phosphopeptides using the hydroxyapatite (HAP) chromatography. The aliquots were analyzed with and without MSA on an Orbitrap-XL. Our XD-Scoring analysis revealed that the MS/MS approach provides more identifications because of its faster scan rate, but that for the same given scan rate higher-confidence spectra can be achieved with MSA. Our software is integrated into the PatternLab for proteomics freely available for academic community at http://www.patternlabforproteomics.org. Biological significance Assigning statistical confidence to phosphorylation sites is necessary for proper phosphoproteomic assessment. Here we present a rigorous statistical model, based on Gaussian mixture models and a logistic function, which overcomes shortcomings of previous tools. The algorithm described herein is made readily available to the scientific community by integrating it into the widely adopted PatternLab for proteomics. This article is part of a Special Issue entitled: Computational Proteomics., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Unlabelled: Data independent acquisition (DIA) mass spectrometry is an emerging technique that offers more complete detection and quantification of peptides and proteins across multiple samples. DIA allows fragment-level quantification, which can be considered as repeated measurements of the abundance of the corresponding peptides and proteins in the downstream statistical analysis. However, few statistical approaches are available for aggregating these complex fragment-level data into peptide- or protein-level statistical summaries. In this work, we describe a software package, mapDIA, for statistical analysis of differential protein expression using DIA fragment-level intensities. The workflow consists of three major steps: intensity normalization, peptide/fragment selection, and statistical analysis. First, mapDIA offers normalization of fragment-level intensities by total intensity sums as well as a novel alternative normalization by local intensity sums in retention time space. Second, mapDIA removes outlier observations and selects peptides/fragments that preserve the major quantitative patterns across all samples for each protein. Last, using the selected fragments and peptides, mapDIA performs model-based statistical significance analysis of protein-level differential expression between specified groups of samples. Using a comprehensive set of simulation datasets, we show that mapDIA detects differentially expressed proteins with accurate control of the false discovery rates. We also describe the analysis procedure in detail using two recently published DIA datasets generated for 14-3-3β dynamic interaction network and prostate cancer glycoproteome., Availability: The software was written in C++ language and the source code is available for free through SourceForge website http://sourceforge.net/projects/mapdia/.This article is part of a Special Issue entitled: Computational Proteomics., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Unlabelled: Label-free LC-MS/MS proteomics has proven itself to be a powerful method for evaluating protein identification and quantification from complex samples. For comparative proteomics, several methods have been used to detect the differential expression of proteins from such data. We have assessed seven methods used across the literature for detecting differential expression from spectral count quantification: Student's t-test, significance analysis of microarrays (SAM), normalised spectral abundance factor (NSAF), normalised spectral abundance factor-power law global error model (NSAF-PLGEM), spectral index (SpI), DESeq and QSpec. We used 2000 simulated datasets as well as publicly available data from a proteomic standards study to assess the ability of these methods to detect differential expression in varying effect sizes and proportions of differentially expressed proteins. At two false discovery rate (FDR) levels, we find that several of the methods detect differential expression within the data with reasonable precision, others detect differential expression at the expense of low precision, and finally, others which fail to identify any differentially expressed proteins. The inability of these seven methods to fully capture the differential landscape, even at the largest effect size, illustrates some of the limitations of the existing technologies and the statistical methodologies., Significance: In label-free mass spectrometry experiments, protein identification and quantification have always been important, but there is now a growing focus on comparative proteomics. Detecting differential expression in protein levels can inform on important biological mechanisms and provide direction for further study. Given the high cost and labour intensive nature of validation experiments, statistical methods are important for prioritising proteins of interest. Here, we have performed a comparative analysis to investigate the statistical methodologies for detecting differential expression and provide a reference for future experimental designs. This article is part of a Special Issue entitled: Computational Proteomics., (Copyright © 2015 Elsevier B.V. All rights reserved.)