The selected reaction monitoring/multiple reaction monitoring-based mass spectrometry approach for the accurate quantitation of proteins: clinical applications in the cardiovascular diseases

Selected reaction monitoring, also known as multiple reaction monitoring, is a powerful targeted mass spectrometry approach for a confident quantitation of proteins/peptides in complex biological samples. In recent years, its optimization and application have become pivotal and of great interest in clinical research to derive useful outcomes for patient care. Thus, selected reaction monitoring/multiple reaction monitoring is now used as a highly sensitive and selective method for the evaluation of protein abundances and biomarker verification with potential applications in medical screening. This review describes technical aspects for the development of a robust multiplex assay and discussing its recent applications in cardiovascular proteomics: verification of promising disease candidates to select only the highest quality peptides/proteins for a preclinical validation, as well as quantitation of protein isoforms and post-translational modifications.     

Post-translational quantitation by SRM/MRM: applications in cardiology

Introduction: Post-translational modifications (PTMs) have an important role in the regulation of protein function, localization, and interaction with other molecules. PTMs apply a dynamic control of proteins in both physiological and pathological conditions. The study of disease-specific PTMs allows identifying potential biomarkers and developing effective drugs. Enrichment techniques combined with high-resolution mass spectrometry (MS)/MS analysis provide attractive results on PTM characterization. Selected reaction monitoring/multiple reaction monitoring (SRM/MRM) is a powerful targeted assay for the quantitation and validation of PTMs in complex biological samples.

Areas covered: The most frequent PTMs are described in terms of biological role and analytical methods commonly used to detect them. The applications of SRM/MRM for the absolute quantitation of PTMs are reported, and a specific section is focused on PTM detection in proteins that are involved in the cardiovascular system and heart diseases.

Expert commentary: PTM characterization in relation to disease pathology is still in progress, but targeted proteomics by LC-MS/MS has significantly upgraded our knowledge in the last few years. Advances in enrichment strategies and software tools will facilitate the interpretation of high PTM complexity. Promising studies confirm the great potential of SRM/MRM to study PTMs in the cardiovascular field, and PTMomics could be very useful in the clinical perspective.     

基于质谱的选择反应监测技术相关策略和方法的研究进展

随着蛋白质组学研究的不断深入,基于质谱的选择反应监测技术(SRM)已经成为以发现生物标志物为代表的定向蛋白质组学研究的重要手段.SRM技术根据假设信息,特异性地获取符合假设条件的质谱信号,去除不符合条件的离子信号干扰,从而得到特定蛋白质的定量信息.SRM技术具有更高的灵敏度和精确性、更大的动态范围等优势.该技术可分为实验设计、数据获取和数据分析三个步骤.在这几个步骤中,最重要的是利用生物信息学手段总结当前实验数据的结果,并用机器学习方法和总结的经验规则进行SRM实验的母离子和子离子对的预测.针对数据质控和定量的生物信息学方法研究在提高SRM数据可靠性方面具有重要作用.此外,为方便SRM的研究,本文还收集、汇总了SRM技术相关的软件、工具和数据库资源.随着质谱仪器的不断发展,新的SRM实验策略以及分析方法、计算工具也应运而生.结合更优化的实验策略、方法,采用更精准的生物信息学算法和工具,SRM在未来蛋白质组学的发展中将发挥更加重要的作用.     

Mass spectrometry-based plasma proteomics: state of the art and future outlook

Mass spectrometry-based plasma proteomics is a field where intense research has been performed during the last decade. Being closely linked to biomarker discovery, the field has received a fair amount of criticism, mostly due to the low number of novel biomarkers reaching the clinic. However, plasma proteomics is under gradual development with improvements on fractionation methods, mass spectrometry instrumentation and analytical approaches. These recent developments have contributed to the revival of plasma proteomics. The goal of this review is to summarize these advances, focusing in particular on fractionation methods, both for targeted and global mass spectrometry-based plasma analysis.     

选择反应监测技术在蛋白质组学研究中的应用

基于三重四极杆质谱仪的选择反应监测(SRM)技术是一种根据已有信息或理论信息靶向进行质谱信号采集的技术,具有高选择性、高重复性、高灵敏度、宽动态范围等特点,已被广泛应用于蛋白质组学研究,用于生物样本中蛋白质的绝对定量分析.本文对SRM技术的特点、发展过程、在蛋白质组学中的应用现状以及发展前景进行了概述.     

A Targeted Mass Spectrometry Strategy for Developing Proteomic Biomarkers: A Case Study of Epithelial Ovarian Cancer

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Highlights

• •Rigorous experimental design and data analysis for large-scale SRM studies.
• •Plasma-based biomarker signature combined with CA125 for ovarian cancer detection.
• •Broadly applicable strategy for the development of diagnostic biomarker assays.

     

Advances in high-resolution quantitative proteomics: implications for clinical applications

The advances in high-resolution mass spectrometry instrumentation, capable of accurate mass measurement and fast acquisition, have enabled new approaches for targeted quantitative proteomics. More specifically, analyses performed on quadrupole-orbitrap mass spectrometers operated in parallel reaction monitoring (PRM) mode leverage the intrinsic high resolving power and trapping capabilities. The PRM technique offers unmatched degrees of selectivity and analytical sensitivity, typically required to analyze peptides in complex samples, such as those encountered in biomedical research or clinical studies. The features of PRM have provoked a paradigm change in targeted experiments, by decoupling acquisition and data processing. It has resulted in a new analytical workflow comprising distinct methods for each step, thus enabling much larger flexibility. The PRM technique was further enhanced by a new data acquisition scheme, allowing dynamic parameter settings. The potential of the technique may radically impact future quantitative proteomics studies.     

PeptideAtlas: a resource for target selection for emerging targeted proteomics workflows

A crucial part of a successful systems biology experiment is an assay that provides reliable, quantitative measurements for each of the components in the system being studied. For proteomics to be a key part of such studies, it must deliver accurate quantification of all the components in the system for each tested perturbation without any gaps in the data. This will require a new approach to proteomics that is based on emerging targeted quantitative mass spectrometry techniques. The PeptideAtlas Project comprises a growing, publicly accessible database of peptides identified in many tandem mass spectrometry proteomics studies and software tools that allow the building of PeptideAtlas, as well as its use by the research community. Here, we describe the PeptideAtlas Project, its contents and components, and show how together they provide a unique platform to select and validate mass spectrometry targets, thereby allowing the next revolution in proteomics.     

Selection of Features with Consistent Profiles Improves Relative Protein Quantification in Mass Spectrometry Experiments

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Highlights

• •Automated statistical approach for detecting uninformative features and outliers.
• •Improved performance on relative protein quantification.
• •An option in the open-source R-based software MSstats.

     

Profiling proteoforms: promising follow-up of proteomics for biomarker discovery

Today, proteomics usually compares clinical samples by use of bottom-up profiling with high resolution mass spectrometry, where all protein products of a single gene are considered as an integral whole. At the same time, proteomics of proteoforms, which considers the variety of protein species, offers the potential to discover valuable biomarkers. Proteoforms are protein species that arise as a consequence of genetic polymorphisms, alternative splicing, post-translational modifications and other less-explored molecular events. The comprehensive observation of proteoforms has been an exclusive privilege of top-down proteomics. Here, we review the possibilities of a bottom-up approach to address the microheterogeneity of the human proteome. Special focus is given to shotgun proteomics and structure-based bioinformatics as a source of hypothetical proteoforms, which can potentially be verified by targeted mass spectrometry to determine the relevance of proteoforms to diseases.     

Proteomics approaches to biomarker detection.

The development of mass spectrometry (MS) technologies has brought the ability to gather massive amounts of data characterising the proteomes of complex mixtures. A major focus in proteomics is to leverage this data-gathering capability to conduct comparative analyses of biofluids from healthy and disease-affected patients for the identification of highly specific biomarkers and/or the development of MS-based diagnostic platforms. Much effort has gone into optimising the biofluid proteome coverage that can be obtained using these technologies, leaving proteomics poised to make an important impact in disease diagnostics in the future.     

血浆蛋白质组——人类蛋白质组计划的“探路者”

概述了血浆蛋白的研究现状、难点和策略.血浆是血液中无形的液体成分,是一种十分复杂和多样化的基质,包含数百万种蛋白质和小分子多肽、盐、类脂、氨基酸和糖等.血浆蛋白参与机体免疫、凝血-抗凝血、物质运输、营养和对生长信号调节等多种重要的生理功能.人体器官的病理变化可导致血浆蛋白在结构和数量上的改变,这种特征性的变化对疾病诊断和疗效监测具有十分重要的意义.然而,迄今为止人类对血浆蛋白的了解还十分有限,只有很少一部分血浆蛋白被用于常规的临床诊断.全面而系统地认识健康和疾病状态下血液循环中血浆蛋白的性质,会极大地加速对具有疾病诊断和治疗监测作用的血浆标志蛋白的研发.国际人类蛋白质组组织于2002年首先选择了血浆蛋白质组作为人类蛋白质组首期执行计划之一,其初期目标是：a.比较各种蛋白质组分析技术平台的优点和局限性;b.用这些技术平台分析人类血浆和血清的参考样本;c.建立人类血浆蛋白质组知识库.     

Reactivation of Inactivated d-Glucose Dehydrogenase of a Bacillus Species by Pyridine and Adenine Nucleotides

d-Glucose dehydrogenase [β-d-glucosc: NAD(P) oxidoreductase (EC 1.1.1.47)] was synthesized derepressively in a mutant of a Bacillus species which was isolated as an improved strain for d-ribose production. The enzyme was very unstable and inactivated during storage or column chromatography. The inactivation was prevented in the presence of NAD⁺, NADP⁺ or certain salts. The inactive enzyme was reactivated by the addition of NAD⁺, NADH, NADP⁺, NADPH, AMP, ADP, ATP or certain salts. The molecular weights of the inactive and active form of the enzyme were estimated to be about 45,000 and 80,000, respectively, by Sephadex G–150 gel filtration. Thus, it seems that the enzyme activity is regulated by monomer-dimer interconversion of the enzyme molecule.     

Multiple marker abundance profiling: combining selected reaction monitoring and data‐dependent acquisition for rapid estimation of organelle abundance in subcellular samples

Measuring changes in protein or organelle abundance in the cell is an essential, but challenging aspect of cell biology. Frequently‐used methods for determining organelle abundance typically rely on detection of a very few marker proteins, so are unsatisfactory. In silico estimates of protein abundances from publicly available protein spectra can provide useful standard abundance values but contain only data from tissue proteomes, and are not coupled to organelle localization data. A new protein abundance score, the normalized protein abundance scale (NPAS), expands on the number of scored proteins and the scoring accuracy of lower‐abundance proteins in Arabidopsis. NPAS was combined with subcellular protein localization data, facilitating quantitative estimations of organelle abundance during routine experimental procedures. A suite of targeted proteomics markers for subcellular compartment markers was developed, enabling independent verification of in silico estimates for relative organelle abundance. Estimation of relative organelle abundance was found to be reproducible and consistent over a range of tissues and growth conditions. In silico abundance estimations and localization data have been combined into an online tool, multiple marker abundance profiling, available in the SUBA4 toolbox ( http://suba.live ).     

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC–MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC–MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC–MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.     

Using SRM-MS to quantify nuclear protein abundance differences between adipose tissue depots of insulin-resistant mice

Insulin resistance (IR) underlies metabolic disease. Visceral, but not subcutaneous, white adipose tissue (WAT) has been linked to the development of IR, potentially due to differences in regulatory protein abundance. Here we investigate how protein levels are changed in IR in different WAT depots by developing a targeted proteomics approach to quantitatively compare the abundance of 42 nuclear proteins in subcutaneous and visceral WAT from a commonly used insulin-resistant mouse model, Lepr(db/db), and from C57BL/6J control mice. The most differentially expressed proteins were important in adipogenesis, as confirmed by siRNA-mediated depletion experiments, suggesting a defect in adipogenesis in visceral, but not subcutaneous, insulin-resistant WAT. Furthermore, differentiation of visceral, but not subcutaneous, insulin-resistant stromal vascular cells (SVCs) was impaired. In an in vitro approach to understand the cause of this impaired differentiation, we compared insulin-resistant visceral SVCs to preadipocyte cell culture models made insulin resistant by different stimuli. The insulin-resistant visceral SVC protein abundance profile correlated most with preadipocyte cell culture cells treated with both palmitate and TNFα. Together, our study introduces a method to simultaneously measure and quantitatively compare nuclear protein expression patterns in primary adipose tissue and adipocyte cell cultures, which we show can reveal relationships between differentiation and disease states of different adipocyte tissue types.     

Analytical comparison of absolute quantification strategies to investigate the insulin signaling pathway in fat cells

So far, mass spectrometry-based targeted proteomics is the most sensitive approach to answer and address specific biological questions in an accurate and quantitative fashion. However, the data analysis design used for such quantification varies in the field leading to discrepancies in the reported values. In this study, different quantification strategies based on calibration curves were evaluated and compared. The best accuracy and coefficient of variation was achieved by ratio to ratio calibration curves. We applied the ratio to ratio quantification approach to analyze very low abundant insulin signaling proteins such as PIK3RA (0.10–0.93 fmol/μg), AKT1 (0.1–0.39 fmol/μg), and the insulin receptor (0.22–2.62 fmol/μg) in a fat cell model and demonstrated the adaptation of this pathway at different states of insulin sensitivity.