The development of selected reaction monitoring methods for targeted proteomics via empirical refinement

Software advancements in the last several years have had a significant impact on proteomics from method development to data analysis. Herein, we detail a method, which uses our in-house developed software tool termed Skyline, for empirical refinement of candidate peptides from targeted proteins. The method consists of four main steps from generation of a testable hypothesis, method development, peptide refinement, to peptide validation. The ultimate goal is to identify the best performing peptide in terms of ionization efficiency, reproducibility, specificity, and chromatographic characteristics to monitor as a proxy for protein abundance. It is important to emphasize that this method allows the user to perform this refinement procedure in the sample matrix and organism of interest with the instrumentation available. Finally, the method is demonstrated in a case study to determine the best peptide to monitor the abundance of surfactant protein B in lung aspirates.     

Development of a highly automated and multiplexed targeted proteome pipeline and assay for 112 rat brain synaptic proteins

We present a comprehensive workflow for large scale (>1000 transitions/run) label‐free LC‐MRM proteome assays. Innovations include automated MRM transition selection, intelligent retention time scheduling that improves S/N by twofold, and automatic peak modeling. Improvements to data analysis include a novel Q/C metric, normalized group area ratio, MLR normalization, weighted regression analysis, and data dissemination through the Yale protein expression database. As a proof of principle we developed a robust 90 min LC‐MRM assay for mouse/rat postsynaptic density fractions which resulted in the routine quantification of 337 peptides from 112 proteins based on 15 observations per protein. Parallel analyses with stable isotope dilution peptide standards (SIS), demonstrate very high correlation in retention time (1.0) and protein fold change (0.94) between the label‐free and SIS analyses. Overall, our method achieved a technical CV of 11.4% with >97.5% of the 1697 transitions being quantified without user intervention, resulting in a highly efficient, robust, and single injection LC‐MRM assay.     

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.     

Quantitative analysis of human centrosome architecture by targeted proteomics and fluorescence imaging

Centrioles are essential for the formation of centrosomes and cilia. While numerical and/or structural centrosomes aberrations are implicated in cancer, mutations in centriolar and centrosomal proteins are genetically linked to ciliopathies, microcephaly, and dwarfism. The evolutionarily conserved mechanisms underlying centrosome biogenesis are centered on a set of key proteins, including Plk4, Sas‐6, and STIL, whose exact levels are critical to ensure accurate reproduction of centrioles during cell cycle progression. However, neither the intracellular levels of centrosomal proteins nor their stoichiometry within centrosomes is presently known. Here, we have used two complementary approaches, targeted proteomics and EGFP‐tagging of centrosomal proteins at endogenous loci, to measure protein abundance in cultured human cells and purified centrosomes. Our results provide a first assessment of the absolute and relative amounts of major components of the human centrosome. Specifically, they predict that human centriolar cartwheels comprise up to 16 stacked hubs and 1 molecule of STIL for every dimer of Sas‐6. This type of quantitative information will help guide future studies of the molecular basis of centrosome assembly and function.     

蛋白质组学中色谱保留时间对齐算法的研究进展北大核心CSCD

色谱是目前蛋白质组学流程中的一个基本环节,而色谱的保留时间对齐是有效提高鉴定和定量准确性的重要步骤之一。经过多年的发展,目前已经产生了一系列保留时间对齐算法。文中主要从可用性角度对蛋白质组学分析中色谱保留时间对齐算法及工具进行了系统总结,并对其发展趋势及应用方向进行了展望。     

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.     

A targeted proteomics toolkit for high-throughput absolute quantification of Escherichia coli proteins

Transformation of engineered Escherichia coli into a robust microbial factory is contingent on precise control of metabolism. Yet, the throughput of omics technologies used to characterize cell components has lagged far behind our ability to engineer novel strains. To expand the utility of quantitative proteomics for metabolic engineering, we validated and optimized targeted proteomics methods for over 400 proteins from more than 20 major pathways in E. coli metabolism. Complementing these methods, we constructed a series of synthetic genes to produce concatenated peptides (QconCAT) for absolute quantification of the proteins and made them available through the Addgene plasmid repository (www.addgene.org). To facilitate high sample throughput, we developed a fast, analytical-flow chromatography method using a 5.5-min gradient (10 min total run time). Overall this toolkit provides an invaluable resource for metabolic engineering by increasing sample throughput, minimizing development time and providing peptide standards for absolute quantification of E. coli proteins.     

Protein identification by liquid chromatography-mass spectrometry using retention time prediction

Liquid chromatography has been coupled with mass spectrometry to improve the dynamic range and to reduce the complexity of sample introduced to the mass spectrometer at any given time. The chromatographic separation also provides information on the analytes, such as peptides in enzymatic digests of proteins; information that can be used when identifying the proteins by peptide mass fingerprinting. This paper discusses a recently introduced method based on retention time prediction to extract information from chromatographic separations and the applications of this method to protein identification in organisms with small and large genomes.     

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.     

Mass spectrometry-based targeted quantitative proteomics: achieving sensitive and reproducible detection of proteins

Traditional shotgun proteomics used to detect a mixture of hundreds to thousands of proteins through mass spectrometric analysis, has been the standard approach in research to profile protein content in a biological sample which could lead to the discovery of new (and all) protein candidates with diagnostic, prognostic, and therapeutic values. In practice, this approach requires significant resources and time, and does not necessarily represent the goal of the researcher who would rather study a subset of such discovered proteins (including their variations or posttranslational modifications) under different biological conditions. In this context, targeted proteomics is playing an increasingly important role in the accurate measurement of protein targets in biological samples in the hope of elucidating the molecular mechanism of cellular function via the understanding of intricate protein networks and pathways. One such (targeted) approach, selected reaction monitoring (or multiple reaction monitoring) mass spectrometry (MRM-MS), offers the capability of measuring multiple proteins with higher sensitivity and throughput than shotgun proteomics. Developing and validating MRM-MS-based assays, however, is an extensive and iterative process, requiring a coordinated and collaborative effort by the scientific community through the sharing of publicly accessible data and datasets, bioinformatic tools, standard operating procedures, and well characterized reagents.     

A novel targeted proteomics method for identification and relative quantitation of difference in nitration degree of OGDH between healthy and diabetic mouse

For analysis of nitration modification of α oxoglutarate dehydrogenase (α‐OGDH) induced by diabetes, a targeted proteomics strategy was developed through the use of Skyline. All peptides containing Y and W of the target proteins were nitrated in silico and output to produce parallel reaction monitoring (PRM) or SRM method for nitration analysis. A nitrated casein mixture was used as standard protein to assess the feasibility of this method. The results demonstrated the availability of this strategy for nitration identification, and subsequently this method was used to analyze the nitration of α‐OGDH from myocardial tissue extracts of diabetic mouse. The PRM method was primarily generated by Skyline for identification of the actual nitrated peptides from all possible nitrated peptides of α‐OGDH due to the complexity of α‐OGDH. The PRM‐based data were analyzed by SEQUEST, and transitions of the identified nitrated peptides were used to develop an SRM method for relative quantitation of nitration degree. The nitration degree of α‐OGDH for diabetic mouse is higher than that for control mouse, indicating that α‐OGDH of the diabetic mouse suffered from more intense oxidative damage. We believe that this approach for obtaining information regarding nitration will facilitate the study of other PTMs in complex mixtures.     

Generation of accurate peptide retention data for targeted and data independent quantitative LC‐MS analysis: Chromatographic lessons in proteomics

The emergence of data‐independent quantitative LC‐MS/MS analysis protocols further highlights the importance of high‐quality reproducible chromatographic procedures. Knowing, controlling and being able to predict the effect of multiple factors that alter peptide RP‐HPLC separation selectivity is critical for successful data collection for the construction of ion libraries. Proteomic researchers have often regarded RP‐HPLC as a “black box”, while vast amount of research on peptide separation is readily available. In addition to obvious parameters, such as the type of ion‐pairing modifier, stationary phase and column temperature, we describe the “mysterious” effects of gradient slope, column size and flow rate on peptide separation selectivity. Retention time variations due to these parameters are governed by the linear solvent strength (LSS) theory on a peptide level by the value of its slope S in the basic LSS equation—a parameter that can be accurately predicted. Thus, the application of shallower gradients, higher flow rates, or smaller columns will each increases the relative retention of peptides with higher S‐values (long species with multiple positively charged groups). Simultaneous changes to these parameters that each drive shifts in separation selectivity in the same direction should be avoided. The unification of terminology represents another pressing issue in this field of applied proteomics that should be addressed to facilitate further progress.     

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.     

Decoupling the retention time of easily degradable and persistent substances using ultrafiltration membranes increases biogas production yield

The decoupling of the retention time of easily degradable and persistent substances relieves the degradation process from inhibitors and increases the biogas yield. Anaerobic digestion of maize silage was investigated in a pilot‐scale plant with a coupled ultrafiltration membrane. The aim of the study was the evaluation of the influence of the membrane‐based relief of the degradation process and the increase of the retention time of persistent substances. For that purpose, the fermenter content was separated into solid and liquid fractions. The solid fraction was recirculated to the fermenter for longer retention time and higher substrate degradation rates. The fermentation process was improved by the removal of the liquid fraction and adding volatile fatty acids. The results showed an increase of the biogas yield by 7.2% in comparison to the anaerobic digestion without membrane filtration.     

Clinical applications of quantitative proteomics using targeted and untargeted data-independent acquisition techniques

Introduction: While selected/multiple-reaction monitoring (SRM or MRM) is considered the gold standard for quantitative protein measurement, emerging data-independent acquisition (DIA) using high-resolution scans have opened a new dimension of high-throughput, comprehensive quantitative proteomics. These newer methodologies are particularly well suited for discovery of biomarker candidates from human disease samples, and for investigating and understanding human disease pathways.

Areas covered: This article reviews the current state of targeted and untargeted DIA mass spectrometry-based proteomic workflows, including SRM, parallel-reaction monitoring (PRM) and untargeted DIA (e.g., SWATH). Corresponding bioinformatics strategies, as well as application in biological and clinical studies are presented.

Expert commentary: Nascent application of highly-multiplexed untargeted DIA, such as SWATH, for accurate protein quantification from clinically relevant and disease-related samples shows great potential to comprehensively investigate biomarker candidates and understand disease.     

Using iRT, a normalized retention time for more targeted measurement of peptides

Multiple reaction monitoring (MRM) has recently become the method of choice for targeted quantitative measurement of proteins using mass spectrometry. The method, however, is limited in the number of peptides that can be measured in one run. This number can be markedly increased by scheduling the acquisition if the accurate retention time (RT) of each peptide is known. Here we present iRT, an empirically derived dimensionless peptide-specific value that allows for highly accurate RT prediction. The iRT of a peptide is a fixed number relative to a standard set of reference iRT-peptides that can be transferred across laboratories and chromatographic systems. We show that iRT facilitates the setup of multiplexed experiments with acquisition windows more than four times smaller compared to in silico RT predictions resulting in improved quantification accuracy. iRTs can be determined by any laboratory and shared transparently. The iRT concept has been implemented in Skyline, the most widely used software for MRM experiments.     

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.     

Systematic research on the pretreatment of peptides for quantitative proteomics using a C18 microcolumn

Reversed phase microcolumns have been widely used for peptide pretreatment to desalt and remove interferences before tandem LC–MS in proteomics studies. However, few studies have characterized the effects of experimental parameters as well as column characteristics on the composition of identified peptides. In this study, several parameters including the concentration of ACN in washing buffer, the microcolumn's purification effect, the peptide recovery rate, and the dynamic‐binding capacity were characterized in detail, based upon stable isotope labeling by amino acids in a cell culture quantitative approach. The results showed that peptide losses can be reduced with low ACN concentration in washing buffers resulting in a recovery rate of approximately 82%. Furthermore, the effects of ACN concentration and loading amount on the properties of identified peptides were also evaluated. We found that the dynamic‐binding capacity of the column was approximately 26 μg. With increased loading amounts, more hydrophilic peptides were replaced by hydrophobic peptides.