A Comprehensive Guide for Performing Sample Preparation and Top-Down Protein Analysis

Proteomics-The State of the Field: The Definition and Analysis of Proteomes Should Be Based in Reality, Not Convenience

With growing recognition and acknowledgement of the genuine complexity of proteomes, we are finally entering the post-proteogenomic era. Routine assessment of proteomes as inferred correlates of gene sequences (i.e., canonical 'proteins') cannot provide the necessary critical analysis of systems-level biology that is needed to understand underlying molecular mechanisms and pathways or identify the most selective biomarkers and therapeutic targets. These critical requirements demand the analysis of proteomes at the level of proteoforms/protein species, the actual active molecular players. Currently, only highly refined integrated or integrative top-down proteomics (iTDP) enables the analytical depth necessary to provide routine, comprehensive, and quantitative proteome assessments across the widest range of proteoforms inherent to native systems. Here we provide a broad perspective of the field, taking in historical and current realities, to establish a more balanced understanding of where the field has come from (in particular during the ten years since Proteomes was launched), current issues, and how things likely need to proceed if necessary deep proteome analyses are to succeed. We base this in our firm belief that the best proteomic analyses reflect, as closely as possible, the native sample at the moment of sampling. We also seek to emphasise that this and future analytical approaches are likely best based on the broad recognition and exploitation of the complementarity of currently successful approaches. This also emphasises the need to continuously evaluate and further optimize established approaches, to avoid complacency in thinking and expectations but also to promote the critical and careful development and introduction of new approaches, most notably those that address proteoforms. Above all, we wish to emphasise that a rigorous focus on analytical quality must override current thinking that largely values analytical speed; the latter would certainly be nice, if only proteoforms could thus be effectively, routinely, and quantitatively assessed. Alas, proteomes are composed of proteoforms, not molecular species that can be amplified or that directly mirror genes (i.e., 'canonical'). The problem is hard, and we must accept and address it as such, but the payoff in playing this longer game of rigorous deep proteome analyses is the promise of far more selective biomarkers, drug targets, and truly personalised or even individualised medicine.

Insight into carbohydrate metabolism, protein quantification and mineral regulation in wheat (Triticum aestivum L.) by the action of green synthesized silver nanoparticles (AgNPs) against heat stress

In the present investigation, the role of GS-AgNPs treatment in wheat plants was carried out in reducing heat stress with the aim of facilitating scientists on this topic. The effect of GS-AgNPs against heat stress has rarely been deliberated in wheat plants, and only a few studies have been established earlier in this scenario. This work illustrated the effect of GS-AgNPs on the regulation of carbohydrates metabolism, SOD, proteins, crude fibers, and minerals changes in wheat plants. Data were analysed using PCA analysis, correlation parameters, and normal probability distribution in PAST 3 software. The results indicated that heat stress alone caused severe changes in carbohydrates metabolism, SOD, proteins, crude fibers, and minerals immediately so that plants could not recover without foreign stabilizers such as GS-AgNPs. The application of GS-AgNPs increases the flux of carbohydrates metabolism, SOD, and proteins, including HSPs, crude fibers, and minerals, in wheat plants to reduce the effect of heat stress. The 50 mg/l concentration of GS-AgNPs has shown an increase in carbohydrates metabolism and SOD activity, while crude fibres have shown a significant enhancement at 100 mg/l of GS-AgNPs. The crude and true proteins were also shown pronounced increase in treatment to a concentration of 50 mg/l of GS-AgNPs. GS-AgNPs stimulated HSP production; most importantly, smHSP production was observed in the present results with other HSPs in wheat plants treated with a 50 mg/l concentration of GS-AgNPs. The mineral distribution was also regulated by the respective treatment of GS-AgNPs, and the highest amounts of Ca, P and Fe were found to be highest in wheat under heat stress. In general, we computed the expected model based on GS-AgNPs on the genes/factors that respond to heat stress and their potential role in mitigating heat stress in wheat. In addition, we discussed the prospective signalling pathway triggered by GS-AgNPs in wheat against heat stress. In the future, this work might be helpful in distinguishing the genetic variation due to GS-AgNPs in promoting tolerance in wheat against heat stress.Communicated by Ramaswamy H. Sarma.

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

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

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

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

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

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

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Proteomic Identification of Saliva Proteins as Noninvasive Diagnostic Biomarkers

Many biomedically relevant biomarkers are proteins with characteristic biochemical properties and a relatively restricted subcellular distribution. The comparative and mass spectrometry-based proteomic analysis of body fluids can be particularly instrumental for the targeted identification of novel protein biomarkers with pathological relevance. In this respect, new research efforts in biomarker discovery focus on the systematic mapping of the human saliva proteome, as well as the pathobiochemical identification of disease-related modifications or concentration changes in specific saliva proteins. As a product of exocrine secretion, saliva can be considered an ideal source for the biochemical identification of new disease indicators. Importantly, saliva represents a body fluid that is continuously available for diagnostic and prognostic assessments. This chapter gives an overview of saliva proteomics, including a discussion of the usefulness of both liquid chromatography and two-dimensional gel electrophoresis for efficient protein separation in saliva proteomics.

Top-Down Proteomics and Comparative 2D-DIGE Analysis

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

Bioinformatic Analysis of the Subproteomic Profile of Cardiomyopathic Tissue

Following large-scale protein separation by two-dimensional gel electrophoresis or liquid chromatography, mass spectrometry-based proteomics can be used for the swift identification and characterization of cardiac proteins and their various proteoforms. Comparative cardiac proteomics has been widely applied for the systematic analysis of heart disease and the establishment of novel diagnostic protein biomarkers. The X-linked neuromuscular disorder Duchenne muscular dystrophy is a multisystemic disease that is characterized by late-onset cardiomyopathy. This chapter outlines the bioinformatic analysis of the subproteomic profile of cardiac tissue from wild-type versus the dystrophic mdx-4cv mouse model of dystrophinopathy.

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

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

Proteomics in Inherited Metabolic Disorders

Inherited metabolic disorders (IMD) are rare medical conditions caused by genetic defects that interfere with the body's metabolism. The clinical phenotype is highly variable and can present at any age, although it more often manifests in childhood. The number of treatable IMDs has increased in recent years, making early diagnosis and a better understanding of the natural history of the disease more important than ever. In this review, we discuss the main challenges faced in applying proteomics to the study of IMDs, and the key advances achieved in this field using tandem mass spectrometry (MS/MS). This technology enables the analysis of large numbers of proteins in different body fluids (serum, plasma, urine, saliva, tears) with a single analysis of each sample, and can even be applied to dried samples. MS/MS has thus emerged as the tool of choice for proteome characterization and has provided new insights into many diseases and biological systems. In the last 10 years, sequential window acquisition of all theoretical fragmentation spectra mass spectrometry (SWATH-MS) has emerged as an accurate, high-resolution technique for the identification and quantification of proteins differentially expressed between healthy controls and IMD patients. Proteomics is a particularly promising approach to help obtain more information on rare genetic diseases, including identification of biomarkers to aid early diagnosis and better understanding of the underlying pathophysiology to guide the development of new therapies. Here, we summarize new and emerging proteomic technologies and discuss current uses and limitations of this approach to identify and quantify proteins. Moreover, we describe the use of proteomics to identify the mechanisms regulating complex IMD phenotypes; an area of research essential to better understand these rare disorders and many other human diseases.

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

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

Nano liquid chromatography, an updated review

Low flow chromatography has a rich history of innovation but has yet to reach widespread implementation in bioanalytical applications. Improvements in pump technology, microfluidic connections, and nano-electrospray sources for mass spectrometry have laid the groundwork for broader application, and innovation in this space has accelerated in recent years. This article reviews the instrumentation used for nano-flow liquid chromatography , the types of columns employed, and strategies for multi-dimensionality of separations, which is key to the future state of the technique to the high-throughput needs of modern bioanalysis. An update of the current applications where nano-LC is widely used, such as proteomics and metabolomics, is discussed. But the trend towards biopharmaceutical development of increasingly complex, targeted, and potent therapeutics for the safe treatment of disease drives the need for ultimate selectivity and sensitivity of our analytical platforms for targeted quantitation in a regulated space. The selectivity needs are best addressed by mass spectrometric detection, especially at high resolutions, and exquisite sensitivity is provided by nano-electrospray ionization as the technology continues to evolve into an accessible, robust, and easy to use platform.

Quantification of tumor heterogeneity: from data acquisition to metric generation

Tumors are unique and complex ecosystems, in which heterogeneous cell subpopulations with variable molecular profiles, aggressiveness, and proliferation potential coexist and interact. Understanding how heterogeneity influences tumor progression has important clinical implications for improving diagnosis, prognosis, and treatment response prediction. Several recent innovations in data acquisition methods and computational metrics have enabled the quantification of spatiotemporal heterogeneity across different scales of tumor organization. Here, we summarize the most promising efforts from a common experimental and computational perspective, discussing their advantages, shortcomings, and challenges. With personalized medicine entering a new era of unprecedented opportunities, our vision is that of future workflows integrating across modalities, scales, and dimensions to capture intricate aspects of the tumor ecosystem and to open new avenues for improved patient care.

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.

Quantitative proteomic and lipidomics analyses of high oil content GmDGAT1-2 transgenic soybean illustrate the regulatory mechanism of lipoxygenase and oleosin

KEY MESSAGE

Proteomic and lipidomics analyses of WT and GmDGAT1-2 transgenic soybeans showed that GmDGAT1-2 over-expression induced lipoxygenase down-regulatation and oleoin up-regulatation, which significantly changed the compositions and total fatty acid. The main goal of soybean breeding is to increase the oil content. Diacylglycerol acyltransferase (DGAT) is a key rate-limiting enzyme in fatty acid metabolism and may regulate oil content. Herein, 10 GmDGAT genes were isolated from soybean and transferred into wild-type (WT) Arabidopsis. The total fatty acid was 1.2 times higher in T3 GmDGAT1-2 transgenic Arabidopsis seeds than in WT. Therefore, GmDGAT1-2 was transferred into WT soybean (JACK), and four T3 transgenic soybean lines were obtained. The results of high-performance gas chromatography and Soxhlet extractor showed that, compared with those of JACK, oleic acid (18:1), and total fatty acid levels in transgenic soybean plants were much higher, but linoleic acid (18:2) was lower than WT. Palmitic acid (16:0), stearic acid (18:0), and linolenic acid (18:3) were not significantly different. For mechanistic studies, 436 differentially expressed proteins (DEPs) and 180 differentially expressed metabolites (DEMs) were identified between WT (JACK) and transgenic soybean pods using proteomic and lipidomics analyses. Four lipoxygenase proteins were down-regulated in linoleic acid metabolism while four oleosin proteins were up-regulated in the final oil formation. The results showed an increase in the total fatty acid and 18:1 composition, and a decrease in the 18:2 composition of fatty acid. Our study brings new insights into soybean genetic transformation and the deep study of molecular mechanism that changes the total fatty acid, 18:1, and 18:2 compositions in GmDGAT1-2 transgenic soybean.

Proteome analysis using machine learning approaches and its applications to diseases

With the tremendous developments in the fields of biological and medical technologies, huge amounts of data are generated in the form of genomic data, images in medical databases or as data on protein sequences, and so on. Analyzing this data through different tools sheds light on the particulars of the disease and our body's reactions to it, thus, aiding our understanding of the human health. Most useful of these tools is artificial intelligence and deep learning (DL). The artificially created neural networks in DL algorithms help extract viable data from the datasets, and further, to recognize patters in these complex datasets. Therefore, as a part of machine learning, DL helps us face all the various challenges that come forth during protein prediction, protein identification and their quantification. Proteomics is the study of such proteins, their structures, features, properties and so on. As a form of data science, Proteomics has helped us progress excellently in the field of genomics technologies. One of the major techniques used in proteomics studies is mass spectrometry (MS). However, MS is efficient with analysis of large datasets only with the added help of informatics approaches for data analysis and interpretation; these mainly include machine learning and deep learning algorithms. In this chapter, we will discuss in detail the applications of deep learning and various algorithms of machine learning in proteomics.

Fast in-line bottom-up analysis of monoclonal antibodies: Toward an electrophoretic fingerprinting approach

For their characterization and quality control, monoclonal antibodies are frequently analyzed at the bottom-up level to generate specific fingerprints that can be used to tackle post-translational modifications or ensure production consistency between lots. To circumvent time-consuming and labor-intensive off-line sample preparation steps, the implementation of integrated methodologies from sample preparation to separation and detection is highly valuable. In this perspective, capillary zone electrophoresis appears as a choice technique since the capillary can subsequently be used as a vessel for sample preparation and electrophoretic discrimination/detection of the reaction products. Here, a fast in-line methodology for the routine quality control of mAbs at the bottom-up level is reported. Simultaneous denaturation and reduction (pretreatment step) were conducted with RapiGest® surfactant and dithiothreitol before in-line tryptic digestion. Reactant mixing was realized by transverse diffusion of laminar flow profile under controlled temperature. In-line digestion was carried out with a resistant trypsin to autolysis. The main parameters affecting the digestion efficiency (trypsin concentration and incubation conditions) were optimized to generate mAb electrophoretic profiles free from trypsin interferences. An acidic MS-compatible BGE was used to obtain high resolution separation of released peptides and in-line surfactant cleavage. The whole methodology was performed in less than two hours with good repeatability of migration times (RSD = 0.91%, n = 5) and corrected peak areas (RSD = 9.6%, n = 5). CE-fingerprints were successfully established for different mAbs and an antibody-drug conjugate.

Optimization of cysteine residue alkylation using an on-line LC-MS strategy: Benefits of using a cocktail of haloacetamide reagents

Several common reagents for the alkylation of cysteine residues of model intact proteins were evaluated for reaction speed, yield of alkylated product and degree of over-alkylation using an online LC-MS platform. The efficiency of the alkylation reaction is found to be dependent on the (1) reagent, (2) peptide/protein, (3) reagent concentration and (4) reaction time. At high reagent concentrations, iodoacetic acid was found to produce significant levels of over-alkylation products wherein methionine residues become modified. For optimal performance of the alkylation reaction, we found the use of a cocktail of chloroacetamide, bromoacetamide and iodoacetamide worked best. The alkylating efficiency of each haloacetamide is a balance between the characteristics of the halogen leaving group and the steric hindrance of the alkylation site on the peptide or protein. A key aspect of using a cocktail of haloacetamides is that they all produce the same modification (+57.0209 Da) to the cysteine residues of the protein while the alkylation efficiency of each site may differ for each of the three reagents. Over-alkylation effects appear to be lower with the cocktail due to a lower concentration of each reagent. The haloacetamide cocktail could be useful when considering complex mixtures of proteins.

Biological Applications for LC-MS-Based Proteomics

Since its inception, liquid chromatography-mass spectrometry (LC-MS) has been continuously improved upon in many aspects, including instrument capabilities, sensitivity, and resolution. Moreover, the costs to purchase and operate mass spectrometers and liquid chromatography systems have decreased, thus increasing affordability and availability in sectors outside of academic and industrial research. Processing power has also grown immensely, cutting the time required to analyze samples, allowing more data to be feasibly processed, and allowing for standardized processing pipelines. As a result, proteomics via LC-MS has become popular in many areas of biological sciences, forging an important seat for itself in targeted and untargeted assays, pure and applied science, the laboratory, and the clinic. In this chapter, many of these applications of LC-MS-based proteomics and an outline of how they can be executed will be covered. Since the field of personalized medicine has matured alongside proteomics, it has also come to rely on various mass spectrometry methods and will be elaborated upon as well. As time goes on and mass spectrometry evolves, there is no doubt that its presence in these areas, and others, will only continue to grow.

Proteomic Analysis of Proteins Responsive to Drought and Low Temperature Stress in a Hard Red Spring Wheat Cultivar

Drought stress is becoming more prevalent with global warming, and has been shown to have large effects on gluten proteins linked to wheat bread making quality. Likewise, low temperature stress can detrimentally affect proteins in wheat. This study was done to determine the differential abundance of high molecular weight (HMW) glutenin proteins in a drought and low temperature stressed high quality hard red spring wheat cultivar (PAN3478), against a control. The treatments were applied in the greenhouse at the soft dough stage. HMW glutenin proteins were extracted from the flour, and were separated by using two-dimensional gel electrophoresis. Protein spots that had p values lower than 0.05 and fold values equal to or greater than 1.2 were considered to be significantly differentially abundant. These proteins were further analyzed by using tandem mass spectrometry. There was a 1.3 to 1.8 fold change in 17 protein spots due to the cold treatment. The drought treatment caused a 1.3 to 3.8 fold change in 19 protein spots. These spots matched either HMW or low molecular weight (LMW) glutenin subunits. In the latter case, the C subunits of LMW glutenins were notably found to be up-regulated under both stress conditions. All the proteins that have been identified can directly influence dough characteristics. Data are available via ProteomeXchange with the identifier PXD017578.

Effect of difluoroacetic acid and biological matrices on the development of a liquid chromatography-triple quadrupole mass spectrometry method for determination of intact growth factor proteins

In biological systems, variable protein expression is a crucial marker for numerous diseases, including cancer. The vast majority of liquid chromatography-triple quadrupole mass spectrometry-based quantitative protein assays use bottom-up methodologies, where proteins are subjected to proteolytic cleavage prior to analysis. Here, the effect of difluoroacetic acid and biological matrices on the developement of a multiple reaction monitoring based top-down reversed-phase liquid chromatography-triple quadrupole mass spectrometry method for analysis of cancer-related intact proteins was evaluated. Seven growth factors (5.5-26.5 kDa; isoelectric points: 4.6-9.9) were analyzed on a wide-pore C4 column. The optimized method was performed at 30°C, using a 0.2 mL/min flow rate, a 10 %B/min gradient slope, and 0.05% v/v difluoroacetic acid as a mobile phase modifier. The increase of mass spectrometry sensitivity due to the difluoroacetic acid (estimated limits of detection in biological matrices 1-500 ng/mL) significantly varied for proteins with lower and higher charge state distributions. Matrix effects, as well as the specificity of the method were assessed for variable biological samples and pretreatment methods. This work demonstrates method development to improve the ability to target intact proteins directly by more affordable triple quadrupole mass spectrometry instrumentation, which could be beneficial in many application fields.

Development of a Novel Platform of Proteome Profiling Based on an Easy-to-Handle and Informative 2D-DIGE System

Proteome profiling based on two-dimensional (2D)-DIGE might be a useful tool for investigating drug-like compounds and the mode of action of drugs. However, obtaining data for profiling requires high labor costs, and it is difficult to control the reproducibility of spot positions because 2D-DIGE usually requires large-size glass plates and spot alignments are greatly affected by the quality of DryStrips and polyacrylamide gels (PAGs). Therefore, we have developed a novel platform by employing small size DryStrips and PAGs, and an image analysis strategy based on dual correction of spot alignment and volume. Our system can automatically detect a large number of consistent spots through all images. Cytosol fractions of HeLa cells treated with dimethyl sulfoxide (DMSO) or bortezomib were analyzed, 1697 consistent spots were detected, and 775 of them were significantly changed with the treatment. Deviations between different days and lot sets of DryStrips and PAGs were investigated by calculating the correlation coefficients. The mean values of the correlation between days and lot sets were 0.96 and 0.94, respectively. Clustering analysis of all the treatment data clearly separated the DMSO or bortezomib treated groups beyond day deviations. Thus, we have succeeded in developing an easy-to-handle 2D-DIGE system that can be a novel proteome profiling platform.

Unbiased Thiol-Labeling and Top-Down Proteomic Analyses Implicate Multiple Proteins in the Late Steps of Regulated Secretion

Regulated exocytosis enables temporal and spatial control over the secretion of biologically active compounds; however, the mechanism by which Ca²⁺ modulates different stages of exocytosis is still poorly understood. For an unbiased, top-down proteomic approach, select thiol- reactive reagents were used to investigate this process in release-ready native secretory vesicles. We previously characterized a biphasic effect of these reagents on Ca²⁺-triggered exocytosis: low doses potentiated Ca²⁺ sensitivity, whereas high doses inhibited Ca²⁺ sensitivity and extent of vesicle fusion. Capitalizing on this novel potentiating effect, we have now identified fluorescent thiol- reactive reagents producing the same effects: Lucifer yellow iodoacetamide, monobromobimane, and dibromobimane. Top-down proteomic analyses of fluorescently labeled proteins from total and cholesterol-enriched vesicle membrane fractions using two-dimensional gel electrophoresis coupled with mass spectrometry identified several candidate targets, some of which have been previously linked to the late steps of regulated exocytosis and some of which are novel. Initial validation studies indicate that Rab proteins are involved in the modulation of Ca²⁺ sensitivity, and thus the efficiency of membrane fusion, which may, in part, be linked to their previously identified upstream roles in vesicle docking.

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.

Reducing Complexity? Cysteine Reduction and S-Alkylation in Proteomic Workflows: Practical Considerations

Reduction and alkylation are common processing steps in sample preparation for qualitative and quantitative proteomic analyses. In principle, these steps mitigate the limitations resulting from the presence of disulfide bridges. There has been recurring debate in the proteomics community around their use, with concern over negative impacts that result from overalkylation (off-target, non-thiol sites) or incomplete reduction and/or S-alkylation of cysteine. This chapter integrates findings from a number of studies on different reduction and alkylation strategies, to guide users in experimental design for their optimal use in proteomic workflows.

Electrophoretic cytometry of adherent cells

Cell-matrix and cell-cell interactions influence intracellular signalling and play an important role in physiologic and pathologic processes. Detachment of cells from the surrounding microenvironment alters intracellular signalling. Here, we demonstrate and characterise an integrated microfluidic device to culture single and clustered cells in tuneable microenvironments and then directly analyse the lysate of each cell in situ, thereby eliminating the need to detach cells prior to analysis. First, we utilise microcontact printing to pattern cells in confined geometries. We then utilise a microscale isoelectric focusing (IEF) module to separate, detect, and analyse lamin A/C from substrate-adhered cells seeded and cultured at varying (500, 2000, and 9000 cells per cm2) densities. We report separation performance (minimum resolvable pI difference of 0.11) that is on par with capillary IEF and independent of cell density. Moreover, we map lamin A/C and β-tubulin protein expression to morphometric information (cell area, circumference, eccentricity, form factor, and cell area factor) of single cells and observe poor correlation with each of these parameters. By eliminating the need for cell detachment from substrates, we enhance detection of cell receptor proteins (CD44 and β-integrin) and dynamic phosphorylation events (pMLCS19) that are rendered undetectable or disrupted by enzymatic treatments. Finally, we optimise protein solubilisation and separation performance by tuning lysis and electrofocusing (EF) durations. We observe enhanced separation performance (decreased peak width) with longer EF durations by 25.1% and improved protein solubilisation with longer lysis durations. Overall, the combination of morphometric analyses of substrate-adhered cells, with minimised handling, will yield important insights into our understanding of adhesion-mediated signalling processes.