Advances in quantitative proteomics via stable isotope tagging and mass spectrometry

Research Progress in Isotope Labeling/Tags-Based Protein Quantification and Metrology Technologies

Advanced liquid chromatogram-mass spectrometry (LC-MS) and automated large-scale data processing have made MS-based quantitative analysis increasingly useful for research in fields such as biology, medicine, food safety, and beyond. This is because MS-based quantitative analysis can accurately and sensitively analyze thousands of proteins and peptides in a single experiment. However, the precision, coverage, complexity, and resilience of conventional quantification methods vary as a result of the modifications to the analytic environment and the physicochemical characteristics of analytes. Therefore, specially designed approaches are necessary for sample preparation. Dozens of methods have been developed and adapted for these needs based on stable isotopic labeling or isobaric tagging, each with distinct characteristics. In this review, we will summarize the leading strategies and techniques used thus far for MS-based protein quantification as well as analyze the advantages and shortcomings of different approaches. Additionally, we provide an overview of protein metrology development.

Mass spectrometry as a lens into molecular human nutrition and health

Mass spectrometry (MS) has developed over the last decades into the most informative and versatile analytical technology in molecular and structural biology (). The platform enables discovery, identification, and characterisation of non-volatile biomolecules, such as proteins, peptides, DNA, RNA, nutrients, metabolites, and lipids at both speed and scale and can elucidate their interactions and effects. The versatility, robustness, and throughput have rendered MS a major research and development platform in molecular human health and biomedical science. More recently, MS has also been established as the central tool for 'Molecular Nutrition', enabling comprehensive and rapid identification and characterisation of macro- and micronutrients, bioactives, and other food compounds. 'Molecular Nutrition' thereby helps understand bioaccessibility, bioavailability, and bioefficacy of macro- and micronutrients and related health effects. Hence, MS provides a lens through which the fate of nutrients can be monitored along digestion via absorption to metabolism. This in turn provides the bioanalytical foundation for 'Personalised Nutrition' or 'Precision Nutrition' in which design and development of diets and nutritional products is tailored towards consumer and patient groups sharing similar genetic and environmental predisposition, health/disease conditions and lifestyles, and/or objectives of performance and wellbeing. The next level of integrated nutrition science is now being built as 'Systems Nutrition' where public and personal health data are correlated with life condition and lifestyle factors, to establish directional relationships between nutrition, lifestyle, environment, and health, eventually translating into science-based public and personal heath recommendations and actions. This account provides a condensed summary of the contributions of MS to a precise, quantitative, and comprehensive nutrition and health science and sketches an outlook on its future role in this fascinating and relevant field.

Prediction, Discovery, and Characterization of Plant- and Food-Derived Health-Beneficial Bioactive Peptides

Nature may have the answer to many of our questions about human, animal, and environmental health. Natural bioactives, especially when harvested from sustainable plant and food sources, provide a plethora of molecular solutions to nutritionally actionable, chronic conditions. The spectrum of these conditions, such as metabolic, immune, and gastrointestinal disorders, has changed with prolonged human life span, which should be matched with an appropriately extended health span, which would in turn favour more sustainable health care: "adding years to life and adding life to years". To date, bioactive peptides have been undervalued and underexploited as food ingredients and drugs. The future of translational science on bioactive peptides-and natural bioactives in general-is being built on (a) systems-level rather than reductionist strategies for understanding their interdependent, and at times synergistic, functions; and (b) the leverage of artificial intelligence for prediction and discovery, thereby significantly reducing the time from idea and concept to finished solutions for consumers and patients. This new strategy follows the path from benefit definition via design to prediction and, eventually, validation and production.

18 O/16 O-Encoding Strategy for Microscale Stereochemical Determination of Peptidic Natural Products

The demand for more efficient methods of establishing the undetermined stereochemistries of peptidic natural products continues unabated. A new method for microscale stereochemical determination was devised by integrating solid-phase synthesis, split-and-mix randomization, ¹⁸ O/¹⁶ O-encoding of d/l-configurations, tandem mass spectrometry, and biological evaluation. Here we applied gramicidin A as the molecule for a blind test. Gramicidin A and its 31 diastereomers were randomly prepared in microgram scale with ¹⁸ O/¹⁶ O-stereochemical encoding and subjected to MS/MS-structural determination and cytotoxicity assay. Only the parent gramicidin A was selected from among the 32 stereoisomers, validating the high reliability of the present strategy.

Mouse Quantitative Proteomics Knowledgebase: reference protein concentration ranges in 20 mouse tissues using 5000 quantitative proteomics assays

Laboratory mouse is the most used animal model in biological research, largely due to its high conserved synteny with human. Researchers use mice to answer various questions ranging from determining a pathological effect of knocked out/in gene to understanding drug metabolism. Our group developed >5000 quantitative targeted proteomics assays for 20 mouse tissues and determined the concentration ranges of a total of more than 1600 proteins using heavy labelled internal standards. We describe here MouseQuaPro; a knowledgebase that hosts this collection of carefully curated experimental data. The Web-based application includes protein concentrations from >700 mouse tissue samples from three common research strains, corresponding to more than 200k experimentally determined concentrations. The knowledgebase integrates the assay and protein concentration information with their human orthologs, functional and molecular annotations, biological pathways, related human diseases, and known gene expressions. At its core are the protein concentration ranges, which provide insights into (dis)similarities between tissues, strains, and sexes. MouseQuaPro implements advanced search as well as filtering functionalities with a simple interface and interactive visualization. This information-rich resource provides an initial map of protein absolute concentration in mouse tissues and allows guided design of proteomics phenotyping experiments. The knowledgebase is available at mousequapro.proteincentre.com. (Reviewer access username and password: mousequapro_reviewer1234567).

Quantitative Mass Spectrometry-Based Proteomics: An Overview

In recent decades, mass spectrometry has moved more than ever before into the front line of protein-centered research. After being established at the qualitative level, the more challenging question of quantification of proteins and peptides using mass spectrometry has become a focus for further development. In this chapter, we discuss and review actual strategies and problems of the methods for the quantitative analysis of peptides, proteins, and finally proteomes by mass spectrometry. The common themes, the differences, and the potential pitfalls of the main approaches are presented in order to provide a survey of the emerging field of quantitative, mass spectrometry-based proteomics.

Proteomic approaches to investigate gammaherpesvirus biology and associated tumorigenesis

The DNA viruses, Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV), are members of the gammaherpesvirus subfamily, a group of viruses whose infection is associated with multiple malignancies, including cancer. The primary host for these viruses is humans and, like all herpesviruses, infection with these pathogens is lifelong. Due to the persistence of gammaherpesvirus infection and the potential for cancer formation in infected individuals, there is a driving need to understand not only the biology of these viruses and how they remain undetected in host cells but also the mechanism(s) by which tumorigenesis occurs. One of the methods that has provided much insight into these processes is proteomics. Proteomics is the study of all the proteins that are encoded by a genome and allows for (i) identification of existing and novel proteins derived from a given genome, (ii) interrogation of protein-protein interactions within a system, and (iii) discovery of druggable targets for the treatment of malignancies. In this chapter, we explore how proteomics has contributed to our current understanding of gammaherpesvirus biology and their oncogenic processes, as well as the clinical applications of proteomics for the detection and treatment of gammaherpesvirus-associated cancers.

Recent Technological Advances in the Mass Spectrometry-based Nanomedicine Studies: An Insight from Nanoproteomics

Nanoscience becomes one of the most cutting-edge research directions in recent years since it is gradually matured from basic to applied science. Nanoparticles (NPs) and nanomaterials (NMs) play important roles in various aspects of biomedicine science, and their influences on the environment have caused a whole range of uncertainties which require extensive attention. Due to the quantitative and dynamic information provided for human proteome, mass spectrometry (MS)-based quantitative proteomic technique has been a powerful tool for nanomedicine study. In this article, recent trends of progress and development in the nanomedicine of proteomics were discussed from quantification techniques and publicly available resources or tools. First, a variety of popular protein quantification techniques including labeling and label-free strategies applied to nanomedicine studies are overviewed and systematically discussed. Then, numerous protein profiling tools for data processing and postbiological statistical analysis and publicly available data repositories for providing enrichment MS raw data information sources are also discussed.

A New Quantification Method Using Electrochemical Mass Spectrometry

Mass spectrometry-based quantification method has advanced rapidly. In general, the methods for accurate quantification rely on the use of authentic target compounds or isotope-labeled compounds as standards, which might be not available or difficult to synthesize. To tackle this grand challenge, this paper presents a novel approach, based on electrochemistry (EC) combined with mass spectrometry (MS). In this approach, a target compound is allowed to undergo electrochemical oxidation and then subject to MS analysis. The oxidation current recorded from electrochemistry (EC) measurement provides information about the amount of the oxidized analyte, based on the Faraday's Law. On the other hand, the oxidation reaction yield can be determined from the analyte MS signal changes upon electrolysis. Therefore, the total amount of analyte can be determined. In combination with liquid chromatography (LC), the method can be applicable to mixture analysis. The striking strength of such a method for quantitation is that neither standard compound nor calibration curve is required. Various analyte molecules such as dopamine, norepinephrine, and rutin as well as peptide glutathione in low quantity were successfully quantified using our method with the quantification error ranging from - 2.6 to + 4.6%. Analyte in a complicated matrix (e.g., uric acid in urine) was also accurately measured. Graphical Abstract.

Quantitative proteomic analysis of mitochondrial proteins differentially expressed between small cell lung cancer cells and normal human bronchial epithelial cells

BACKGROUND

Small cell lung cancer (SCLC) is highly aggressive and is associated with a dismal prognosis. However, there are no clinically recognized biomarkers for early diagnosis. In this study, we used quantitative proteomics to build differential mitochondrial protein profiles that may be used for early diagnosis and investigated the pathogenesis of lung cancer.

METHODS

We cultured SCLC cells (NCI-H446) and normal human bronchial epithelial cells (16-HBE); mitochondria were extracted and purified using differential and Percoll density gradient centrifugation. Subsequently, we used Western blot analysis to validate mitochondrial purity and labeled proteins/peptides from NCI-H446 and 16-HBE cells using relative and absolute quantification of ectopic tags. We then analyzed mixed samples and identified proteins using two-dimensional liquid chromatography-tandem mass spectrometry. Additionally, we performed subsequent bioinformatic proteome analyses using the programs ExPASy, GOA, and STRING. Finally, the relationship between ornithine aminotransferase expression and clinicopathological features in lung cancer patients was evaluated using immunohistochemistry.

RESULTS

One hundred and fifty-three mitochondrial proteins were differentially expressed between 16-HBE and NCI-H446 cells. The expression of 30 proteins between 16-HBE and NCI-H446 cells increased more than 1.3-fold. The upregulation of ornithine aminotransferase was associated with pathological grade and clinical tumor node metastasis stage.

CONCLUSION

Our experiment represented a promising method for building differential mitochondrial protein profiles between NCI-H446 and 16-HBE cells. Such analysis may also help to identify novel biomarkers of lung cancer.

Relative and Absolute Quantitation in Mass Spectrometry-Based Proteomics

Mass spectrometry-based quantitative proteomics is a powerful tool for gaining insights into function and dynamics of biological systems. However, peptides with different sequences have different ionization efficiencies, and their intensities in a mass spectrum are not correlated with their abundances. Therefore, various label-free or stable isotope label-based quantitation methods have emerged to assist mass spectrometry to perform comparative proteomic experiments, thus enabling nonbiased identification of thousands of proteins differentially expressed in healthy versus diseased cells. Here, we discuss the most widely used label-free and metabolic-, enzymatic-, and chemical labeling-based proteomic strategies for relative and absolute quantitation. We summarize the specific strengths and weaknesses of each technique in terms of quantification accuracy, proteome coverage, multiplexing capability, and robustness. Applications of each strategy for solving specific biological complexities are also presented.

Quaternary ammonium isobaric tag for a relative and absolute quantification of peptides

Isobaric labeling quantification of peptides has become a method of choice for mass spectrometry-based proteomics studies. However, despite of wide variety of commercially available isobaric tags, none of the currently available methods offers significant improvement of sensitivity of detection during MS experiment. Recently, many strategies were applied to increase the ionization efficiency of peptides involving chemical modifications introducing quaternary ammonium fixed charge. Here, we present a novel quaternary ammonium-based isobaric tag for relative and absolute quantification of peptides (QAS-iTRAQ 2-plex). Upon collisional activation, the new stable benzylic-type cationic reporter ion is liberated from the tag. Deuterium atoms were used to offset the differential masses of a reporter group. We tested the applicability of QAS-iTRAQ 2-plex reagent on a series of model peptides as well as bovine serum albumin tryptic digest. Obtained results suggest usefulness of this isobaric ionization tag for relative and absolute quantification of peptides.

Deuterium- and Tritium-Labelled Compounds: Applications in the Life Sciences

Hydrogen isotopes are unique tools for identifying and understanding biological and chemical processes. Hydrogen isotope labelling allows for the traceless and direct incorporation of an additional mass or radioactive tag into an organic molecule with almost no changes in its chemical structure, physical properties, or biological activity. Using deuterium-labelled isotopologues to study the unique mass-spectrometric patterns generated from mixtures of biologically relevant molecules drastically simplifies analysis. Such methods are now providing unprecedented levels of insight in a wide and continuously growing range of applications in the life sciences and beyond. Tritium (³ H), in particular, has seen an increase in utilization, especially in pharmaceutical drug discovery. The efforts and costs associated with the synthesis of labelled compounds are more than compensated for by the enhanced molecular sensitivity during analysis and the high reliability of the data obtained. In this Review, advances in the application of hydrogen isotopes in the life sciences are described.

Application of Proteomics in Lung Research

Proteomics has enabled researchers to evaluate global protein changes in a relatively rapid and comprehensive manner. Applications of these technologies in lung research include biomarker and drug discovery, elucidating disease mechanisms, and quantitative clinical assays. Two common workflows exist for quantitative proteomics studies that are aimed at determining differences in protein levels: label-free and labeling methods. Here we describe specific techniques involved in both quantitative workflows; these include extensive sample preparation methods for several lung-specific sample types. Methods are also included for mass spectrometry-based sample analysis and data analysis. While the focus is on quantitative, clinical proteomics, these strategies are appropriate for a wide array of sample types and applications.

Application of mass spectrometry to elucidate the pathophysiology of Encephalitozoon cuniculi infection in rabbits

Encephalitozoon cuniculi is a microsporidian species which can induce subclinical to serious disease in mammals including rabbits, a definitive natural host. The pathophysiology of infection has not been comprehensively elucidated. In this exploratory study, we utilized two mass spectrometry approaches: first, the analysis of the humoral response by profiling the microsporidian antigens as revealed by Western blot screening, and second, implementing the iTRAQ®-labeling protocol to focus on the changes within the host proteome during infection. Seven E. cuniculi proteins were identified at one-dimensional gel regions where specific seropositive reaction was observed by Western blot, including polar tube protein 3, polar tube protein 2, and for the first time reported: heat shock related 70kDa protein, polysaccharide deacetylase domain-containing protein, zinc finger protein, spore wall and anchoring disk complex protein EnP1, and translation elongation factor 1 alpha. In addition, there was a significant increase of nine host proteins in blood samples from E. cuniculi-diseased rabbits in comparison with non-diseased control subjects undergoing various inflammatory processes. This included serum paraoxonase, alpha-1-antiproteinase F precursor and alpha-1-antiproteinase S-1 which have presumptive catalytic activity likely related to infection control, and cystatin fetuin-B-type, an enzyme regulator that has been poorly studied to date. Notably, 11 proteins were found to be statistically increased in rabbits with neurological versus renal clinical presentation of E. cuniculi infection. Overall, this novel analysis based on mass spectrometry has provided new insights on the inflammatory and humoral responses during E. cuniculi infection in rabbits.

Technological advances and proteomic applications in drug discovery and target deconvolution: identification of the pleiotropic effects of statins

Proteomic-based techniques provide a powerful tool for identifying the full spectrum of protein targets of a drug, elucidating its mechanism(s) of action, and identifying biomarkers of its efficacy and safety. Herein, we outline the technological advancements in the field, and illustrate the contribution of proteomics to the definition of the pharmacological profile of statins, which represent the cornerstone of the prevention and treatment of cardiovascular diseases (CVDs). Statins act by inhibiting 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase, thus reducing cholesterol biosynthesis and consequently enhancing the clearance of low-density lipoproteins from the blood; however, HMG-CoA reductase inhibition can result in a multitude of additional effects beyond lipid lowering, known as 'pleiotropic effects'. The case of statins highlights the unique contribution of proteomics to the target profiling of a drug molecule.

Stable isotope dimethyl labelling for quantitative proteomics and beyond

Stable-isotope reductive dimethylation, a cost-effective, simple, robust, reliable and easy-to- multiplex labelling method, is widely applied to quantitative proteomics using liquid chromatography-mass spectrometry. This review focuses on biological applications of stable-isotope dimethyl labelling for a large-scale comparative analysis of protein expression and post-translational modifications based on its unique properties of the labelling chemistry. Some other applications of the labelling method for sample preparation and mass spectrometry-based protein identification and characterization are also summarized.This article is part of the themed issue 'Quantitative mass spectrometry'.

Intact Protein Quantitation Using Pseudoisobaric Dimethyl Labeling

Protein structural and functional studies rely on complete qualitative and quantitative information on protein species (proteoforms); thus, it is important to quantify differentially expressed proteins at their molecular level. Here we report our development of universal pseudoisobaric dimethyl labeling (pIDL) of amino groups at both the N-terminal and lysine residues for relative quantitation of intact proteins. Initial proof-of-principle study was conducted on standard protein myoglobin and hepatocellular proteomes (HepG2 vs LO2). The amino groups from both the N-terminal and lysine were dimethylated with HXHO (X = (13)C or C) and NaBY3CN (Y = H or D). At the standard protein level, labeling efficiency, effect of product ion size, and mass resolution on quantitation accuracy were explored; and a good linear quantitation dynamic range up to 50-fold was obtained. For the hepatocellular proteome samples, 33 proteins were quantified with RSD ≤ 10% from one-dimensional reversed phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS) analysis of the 1:1 mixed samples. The method in this study can be extended to quantitation of other intact proteome systems. The universal "one-pot" dimethyl labeling of all the amino groups in a protein without the need of preblocking of those on the lysine residues is made possible by protein identification and quantitation analysis using ProteinGoggle 2.0 with customized databases of both precursor and product ions containing heavy isotopes.

Isotope-Encoded Carboxyl Group Footprinting for Mass Spectrometry-Based Protein Conformational Studies

We report an isotope-encoding method coupled with carboxyl-group footprinting to monitor protein conformational changes. The carboxyl groups of aspartic/glutamic acids and of the C-terminus of proteins can serve as reporters for protein conformational changes when labeled with glycine ethyl ester (GEE) mediated by carbodiimide. In the new development, isotope-encoded "heavy" and "light" GEE are used to label separately the two states of the orange carotenoid protein (OCP) from cyanobacteria. Two samples are mixed (1:1 ratio) and analyzed by a single LC-MS/MS experiment. The differences in labeling extent between the two states are represented by the ratio of the "heavy" and "light" peptides, providing information about protein conformational changes. Combining isotope-encoded MS quantitative analysis and carboxyl-group footprinting reduces the time of MS analysis and improves the sensitivity of GEE and other footprinting.

Chemoenzymatic method for glycomics: Isolation, identification, and quantitation

Over the past decade, considerable progress has been made with respect to the analytical methods for analysis of glycans from biological sources. Regardless of the specific methods that are used, glycan analysis includes isolation, identification, and quantitation. Derivatization is indispensable to increase their identification. Derivatization of glycans can be performed by permethylation or carbodiimide coupling/esterification. By introducing a fluorophore or chromophore at their reducing end, glycans can be separated by electrophoresis or chromatography. The fluorogenically labeled glycans can be quantitated using fluorescent detection. The recently developed approaches using solid-phase such as glycoprotein immobilization for glycan extraction and on-tissue glycan mass spectrometry imaging demonstrate advantages over methods performed in solution. Derivatization of sialic acids is favorably implemented on the solid support using carbodiimide coupling, and the released glycans can be further modified at the reducing end or permethylated for quantitative analysis. In this review, methods for glycan isolation, identification, and quantitation are discussed.

Stable isotope imaging of biological samples with high resolution secondary ion mass spectrometry and complementary techniques

Stable isotopes are ideal labels for studying biological processes because they have little or no effect on the biochemical properties of target molecules. The NanoSIMS is a tool that can image the distribution of stable isotope labels with up to 50 nm spatial resolution and with good quantitation. This combination of features has enabled several groups to undertake significant experiments on biological problems in the last decade. Combining the NanoSIMS with other imaging techniques also enables us to obtain not only chemical information but also the structural information needed to understand biological processes. This article describes the methodologies that we have developed to correlate atomic force microscopy and backscattered electron imaging with NanoSIMS experiments to illustrate the imaging of stable isotopes at molecular, cellular, and tissue scales. Our studies make it possible to address 3 biological problems: (1) the interaction of antimicrobial peptides with membranes; (2) glutamine metabolism in cancer cells; and (3) lipoprotein interactions in different tissues.

The beauty of being (label)-free: sample preparation methods for SWATH-MS and next-generation targeted proteomics

The combination of qualitative analysis with label-free quantification has greatly facilitated the throughput and flexibility of novel proteomic techniques. However, such methods rely heavily on robust and reproducible sample preparation procedures. Here, we benchmark a selection of in gel, on filter, and in solution digestion workflows for their application in label-free proteomics. Each procedure was associated with differing advantages and disadvantages. The in gel methods interrogated were cost effective, but were limited in throughput and digest efficiency. Filter-aided sample preparations facilitated reasonable processing times and yielded a balanced representation of membrane proteins, but led to a high signal variation in quantification experiments. Two in solution digest protocols, however, gave optimal performance for label-free proteomics. A protocol based on the detergent RapiGest led to the highest number of detected proteins at second-best signal stability, while a protocol based on acetonitrile-digestion, RapidACN, scored best in throughput and signal stability but came second in protein identification. In addition, we compared label-free data dependent (DDA) and data independent (SWATH) acquisition on a TripleTOF 5600 instrument. While largely similar in protein detection, SWATH outperformed DDA in quantification, reducing signal variation and markedly increasing the number of precisely quantified peptides.

The beauty of being (label)-free: sample preparation methods for SWATH-MS and next-generation targeted proteomics

The combination of qualitative analysis with label-free quantification has greatly facilitated the throughput and flexibility of novel proteomic techniques. However, such methods rely heavily on robust and reproducible sample preparation procedures. Here, we benchmark a selection of in gel, on filter, and in solution digestion workflows for their application in label-free proteomics. Each procedure was associated with differing advantages and disadvantages. The in gel methods interrogated were cost effective, but were limited in throughput and digest efficiency. Filter-aided sample preparations facilitated reasonable processing times and yielded a balanced representation of membrane proteins, but led to a high signal variation in quantification experiments. Two in solution digest protocols, however, gave optimal performance for label-free proteomics. A protocol based on the detergent RapiGest led to the highest number of detected proteins at second-best signal stability, while a protocol based on acetonitrile-digestion, RapidACN, scored best in throughput and signal stability but came second in protein identification. In addition, we compared label-free data dependent (DDA) and data independent (SWATH) acquisition on a TripleTOF 5600 instrument. While largely similar in protein detection, SWATH outperformed DDA in quantification, reducing signal variation and markedly increasing the number of precisely quantified peptides.

Differential mitochondrial proteome analysis of human lung adenocarcinoma and normal bronchial epithelium cell lines using quantitative mass spectrometry

BACKGROUND

Lung cancer is one of the higher incidences of malignant tumors around the world. At present, tumor markers CEA, CA19-9, and CA-125 in serum are used for the diagnosis of lung cancer, however, fewer studies have shown tumor markers for early diagnosis. Therefore, using quantitative mass spectrometry, differential mitochondrial proteome analysis was performed, comparing human lung adenocarcinoma and normal bronchial epithelium cells.

METHODS

A human lung adenocarcinoma cell line A549 and a normal human bronchial epithelial cell line 16HBE were cultured in vitro. The cell mitochondria of the two cell lines were extracted and purified by differential centrifugation and percoll density gradient centrifugation. The integrity and purity of mitochondria were validated by electron microscopy and Western-blot. The proteins/peptides from lung cancer cells and normal cells were marked by the same amount of relative and absolute quantification of ectopic tags (iTRAQ). The mixed samples were analyzed and identified by two-dimensional liquid chromatography - tandem mass spectrometry (2D-LC-MS/MS). The proteome was analyzed with different bioinformatic tools.

RESULTS

One hundred and sixty-one mitochondrial proteins were identified. One hundred and fifty-three mitochondrial proteins, which were expressed differently between 16HBE cells and A549 cells, were identified. Sixty-seven proteins were high expression, while 86 proteins were lower expression. Expression of three proteins: ornithine aminotransferase (OAT), heat shock protein beta90 (HSP90), and vimentin (VIM), was increased more than twice. Our results, in combination with the literature review, suggest that HSP90 and Vimentin may be the new tumor markers of lung cancer.

Quantitative protein analysis using (13)C7-labeled iodoacetanilide and d5-labeled N-ethylmaleimide by nano liquid chromatography/nanoelectrospray ionization ion trap mass spectrometry

We have developed a methodology for quantitative analysis and concurrent identification of proteins by the modification of cysteine residues with a combination of iodoacetanilide (IAA, 1) and (13)C7-labeled iodoacetanilide ((13)C7-IAA, 2), or N-ethylmaleimide (NEM, 3) and d5-labeled N-ethylmaleimide (d5-NEM, 4), followed by mass spectrometric analysis using nano liquid chromatography/nanoelectrospray ionization ion trap mass spectrometry (nano LC/nano-ESI-IT-MS). The combinations of these stable isotope-labeled and unlabeled modifiers coupled with LC separation and ESI mass spectrometric analysis allow accurate quantitative analysis and identification of proteins, and therefore are expected to be a useful tool for proteomics research.

Quantitative analysis of glycoprotein glycans

The ability to quantitatively determine changes in the N- and O-linked glycans is an essential component of comparative glycomics. Multiple strategies are available to by which this can be accomplished, including; both label free approaches and isotopic labeling strategies. The focus of this chapter is to describe each of these approaches while providing insight into their strengths and weaknesses, so that glycomic investigators can make an educated choice of the strategy that is best suited for their particular application.

Improved identification of wheat gluten proteins through alkylation of cysteine residues and peptide-based mass spectrometry

The concentration and composition of wheat gluten proteins and the presence, concentration and location of cysteine residues therein are important for wheat flour quality. However, it is difficult to identify gluten proteins, as they are an extremely polymorphic mixture of prolamins. We here present methods for cysteine labeling of wheat prolamins with 4-vinylpyridine (4-VP) and iodoacetamide (IDAM) which, as compared to label-free analysis, substantially improve identification of cysteine-containing peptides in enzymic prolamin digests by electrospray ionization--tandem mass spectrometry. Both chymotrypsin and thermolysin yielded cysteine-containing peptides from different gluten proteins, but more proteins could be identified after chymotryptic digestion. In addition, to the best of our knowledge, we were the first to label prolamins with isotope coded affinity tags (ICAT), which are commonly used for quantitative proteomics. However, more peptides were detected after labeling gluten proteins with 4-VP and IDAM than with ICAT.

Peptide peak intensities enhanced by cysteine modifiers and MALDI TOF MS

Two cysteine-specific modifiers we reported previously, N-ethyl maleimide (NEM) and iodoacetanilide (IAA), have been applied to the labeling of cysteine residues of peptides for the purpose of examining the enhancement of ionization efficiencies in combination with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF MS). The peak intensities of the peptides as a result of modification with these modifiers were compared with the peak intensities of peptides modified with a commercially available cysteine-specific modifier, iodoacetamide (IA). Our experiments show significant enhancement in the peak intensities of three cysteine-containing synthetic peptides modified with IAA compared to those modified with IA. The results showed a 4.5-6-fold increase as a result of modification with IAA compared to modification with IA. Furthermore, it was found that IAA modification also significantly enhanced the peak intensities of many peptides of a commercially available proteins, bovine serum albumin (BSA), compared to those modified with IA. This significant enhancement helped identify a greater number of peptides of these proteins, leading to a higher sequence coverage with greater confidence scores in identification of proteins with the use of IAA.

Detection of structural and metabolic changes in traumatically injured hippocampus by quantitative differential proteomics

Traumatic brain injury (TBI) is a complex and common problem resulting in the loss of cognitive function. In order to build a comprehensive knowledge base of the proteins that underlie these cognitive deficits, we employed unbiased quantitative mass spectrometry, proteomics, and bioinformatics to identify and quantify dysregulated proteins in the CA3 subregion of the hippocampus in the fluid percussion model of TBI in rats. Using stable isotope 18O-water differential labeling and multidimensional tandem liquid chromatography (LC)-MS/MS with high stringency statistical analyses and filtering, we identified and quantified 1002 common proteins, with 124 increased and 76 decreased. The ingenuity pathway analysis (IPA) bioinformatics tool identified that TBI had profound effects on downregulating global energy metabolism, including glycolysis, the Krebs cycle, and oxidative phosphorylation, as well as cellular structure and function. Widespread upregulation of actin-related cytoskeletal dynamics was also found. IPA indicated a common integrative signaling node, calcineurin B1 (CANB1, CaNBα, or PPP3R1), which was downregulated by TBI. Western blotting confirmed that the calcineurin regulatory subunit, CANB1, and its catalytic binding partner PP2BA, were decreased without changes in other calcineurin subunits. CANB1 plays a critical role in downregulated networks of calcium signaling and homeostasis through calmodulin and calmodulin-dependent kinase II to highly interconnected structural networks dominated by tubulins. This large-scale knowledge base lays the foundation for the identification of novel therapeutic targets for cognitive rescue in TBI.

Proteomics and systems biology for understanding diabetic nephropathy

Like many diseases, diabetic nephropathy is defined in a histopathological context and studied using reductionist approaches that attempt to ameliorate structural changes. Novel technologies in mass spectrometry-based proteomics have the ability to provide a deeper understanding of the disease beyond classical histopathology, redefine the characteristics of the disease state, and identify novel approaches to reduce renal failure. The goal is to translate these new definitions into improved patient outcomes through diagnostic, prognostic, and therapeutic tools. Here, we review progress made in studying the proteomics of diabetic nephropathy and provide an introduction to the informatics tools used in the analysis of systems biology data, while pointing out statistical issues for consideration. Novel bioinformatics methods may increase biomarker identification, and other tools, including selective reaction monitoring, may hasten clinical validation.

Encoding substrates with mass tags to resolve stereospecific reactions using Nimzyme

RATIONALE

The nanostructure-initiator mass spectrometry based enzyme assay (Nimzyme) provides a rapid method for screening glycan modifying reactions. However, this approach cannot resolve stereospecific reactions which are common in glycobiology and are typically assayed using lower-throughput methods (gas chromatography/mass spectrometry (GC/MS) or liquid chromatography/tandem mass spectrometry (LC/MS/MS) analysis) often in conjunction with stable isotopically labeled reactants. However, in many applications, library size necessitates the development of higher-throughput screening approaches of stereospecific reactions from crude sample preparations. Therefore, here we test the approach of utilizing Nimzyme linkers with unique masses to encode substrate identity such that this assay can resolve stereospecific reactions.

METHODS

We utilize the nanostructure-initiator mass spectrometry (NIMS) enzyme assay in conjuction with an accurate mass tagging approach where each reactant is tagged with a unique perfluoronated tail. Mass spectrometric analysis was conducted using conventional MALDI-TOF instrumentation.

RESULTS

Stereospecific reaction pathways of three stereoisomers (maltose, lactose and cellobiose) to afford the same product glucose were resolved simutaneously due to the presence of unique fluorous tags on both reactants and products. Not only purified enzymes, but also crude cell lysates can be used in this assay.

CONCLUSIONS

The Nimzyme assay with accurate mass tagging provides a rapid method for screening for targeted stereospecific reactions using mass spectrometry and may be useful for high-throughput screening and functional annotation of a wide range of glycan-modifying enzymes.

After genomics, what proteomics tools could help us understand the antimicrobial resistance of Escherichia coli?

Proteomic approaches have been considerably improved during the past decade and have been used to investigate the differences in protein expression profiles of cells grown under a broad spectrum of growth conditions and with different stress factors including antibiotics. In Europe, the most significant disease threat remains the presence of microorganisms that have become resistant to antimicrobials and so it is important that different scientific tools are combined to achieve the largest amount of knowledge in this area of expertise. The emergence and spread of the antibiotic-resistant Gram-negative pathogens, such as Escherichia coli, can lead to serious problem public health in humans. E. coli, a very well described prokaryote, has served as a model organism for several biological and biotechnological studies increasingly so since the completion of the E. coli genome-sequencing project. The purpose of this review is to present an overview of the different proteomic approaches to antimicrobial-resistant E. coli that will be helpful to obtain a better knowledge of the antibiotic-resistant mechanism(s). This can also aid to understand the molecular determinants involved with pathogenesis, which is essential for the development of effective strategies to combat infection and to reveal new therapeutic targets. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Mass spectrometry for protein quantification in biomarker discovery

Major technological advances have made proteomics an extremely active field for biomarker discovery in recent years due primarily to the development of newer mass spectrometric technologies and the explosion in genomic and protein bioinformatics. This leads to an increased emphasis on larger scale, faster, and more efficient methods for detecting protein biomarkers in human tissues, cells, and biofluids. Most current proteomic methodologies for biomarker discovery, however, are not highly automated and are generally labor-intensive and expensive. More automation and improved software programs capable of handling a large amount of data are essential to reduce the cost of discovery and to increase throughput. In this chapter, we discuss and describe mass spectrometry-based proteomic methods for quantitative protein analysis.

Enhancement of the capabilities of liquid chromatography-mass spectrometry with derivatization: general principles and applications

The integration of liquid chromatography-mass spectrometry (LC-MS) with derivatization is a relatively new and unique strategy that could add value and could enhance the capabilities of LC-MS-based technologies. The derivatization process could be carried out in various analytical steps, for example, sampling, storage, sample preparation, HPLC separation, and MS detection. This review presents an overview of derivatization-based LC-MS strategy over the past 10 years and covers both the general principles and applications in the fields of pharmaceutical and biomedical analysis, biomarker and metabolomic research, environmental analysis, and food-safety evaluation. The underlying mechanisms and theories for derivative reagent selection are summarized and highlighted to guide future studies.

Software for quantitative proteomic analysis using stable isotope labeling and data independent acquisition

Many software tools have been developed for analyzing stable isotope labeling (SIL)-based quantitative proteomic data using data dependent acquisition (DDA). However, programs for analyzing SIL-based quantitative proteomics data obtained with data independent acquisition (DIA) have yet to be reported. Here, we demonstrated the development of a new software for analyzing SIL data using the DIA method. Performance of the DIA on SYNAPT G2MS was evaluated using SIL-labeled complex proteome mixtures with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10) and compared with the DDA on linear ion trap (LTQ)-Orbitrap MS. The DIA displays relatively high quantitation accuracy for peptides cross all intensity regions, while the DDA shows an intensity dependent distribution of H/L ratios. For the three proteome mixtures, the number of detected SIL-peptide pairs and dynamic range of protein intensities using DIA drop stepwise, whereas no significant changes in these aspects using DDA were observed. The new software was applied to investigate the proteome difference between mouse embryonic fibroblasts (MEFs) and MEF-derived induced pluripotent stem cells (iPSCs) using (16)O/(18)O labeling. Our study expanded the capacities of our UNiquant software pipeline and provided valuable insight into the performance of the two cutting-edge MS platforms for SIL-based quantitative proteomic analysis today.

Monitoring processivity and length control of a carbohydrate polymerase

Carbohydrate polymerases are abundant in nature. Although they play vital physiological roles, the molecular mechanisms that they use for the controlled assembly of polymers are largely unknown. One fundamental issue is whether an enzyme utilizes a processive or distributive mechanism for chain elongation. The shortage of mechanistic information on polysaccharide-generating glycosyltransferases became apparent when we sought to carry out investigations of GlfT2, a glycosyltransferase essential for cell wall biosynthesis in Mycobacterium tuberculosis. GlfT2 catalyzes the formation of the cell wall galactan, which is a linear polysaccharide consisting of 20-40 repeating d-galactofuranose (Galf) residues. Recombinant GlfT2 can act on synthetic acceptors to produce polymers with lengths similar to those of endogenous galactan, indicating that GlfT2 has an intrinsic ability to control polymer length. To address whether GlfT2 utilizes a processive or distributive mechanism, we developed a mass spectrometry assay. Our approach, which relies on acceptors labeled with stable isotopes, provides direct evidence that GlfT2 is a processive polymerase that maintains contact with the glycan substrate through successive monomer additions. Given this finding, we probed further the catalytic mechanism of GlfT2 to address the basis of an observed kinetic lag phase. These studies suggest that GlfT2 possesses subsites for Galf residue binding and that substrates that can fill these subsites undergo efficient processive polymerization. The presence of these subsites and the kinetic lag phase are common features of processive enzymes. We anticipate that the strategies described herein can be applied to mechanistic studies of other carbohydrate polymerization reactions.

Relative quantitation of glycans using stable isotopic labels 1-(d0/d5) phenyl-3-methyl-5-pyrazolone by mass spectrometry

A deuterium reagent, 1-(d5) phenyl-3-methyl-5-pyrazolone (d5-PMP), has been synthesized and used for relative quantitative analysis of oligosaccharides by mass spectrometry (MS) using d0/d5-PMP stable isotopic labeling. Previously reported permethylation-based isotopic labels generate variable mass differences, and reductive amination-based isotopic labels cause a loss of some acid-labile groups in carbohydrates. In contrast, d0/d5-PMP stable isotopic labeling is performed at the reducing end of glycans under basic conditions without desialylation, and the mass difference (Δm=10 Da) between the heavy form (d5-PMP derivative) and light form (d0-PMP derivative) of each glycan is invariable. When the two derivative forms of a glycan are mixed in equimolar amounts, a pair of peaks with a 10-Da mass differences is observed in the MS profile. The difference at relative intensity between the d0- and d5-PMP derivatives reflects the difference in quantity of glycans in two samples, making it possible to carry out both qualitative and relative quantitative analyses of glycans in glycomic studies. Application of this method on DP(2) to DP(6) maltodextrin oligosaccharides and N-linked glycans released from ribonuclease B and bovine fetuin demonstrates a 10-fold relative quantitative dynamic range, a satisfying reproducibility (coefficient of variation [CV] ≤ 8.34%), and good accuracy (relative error [RE] ≤ 5.1%) of the method. The suggested technique has been successfully applied for comparative quantitative analysis of free oligosaccharides in human and bovine milk.