Detailed Method for Performing the ExSTA Approach in Quantitative Bottom-Up Plasma Proteomics.

ObjectiveTo quantify prostaglandin D synthase (PTGDS) in human cerebrospinal fluid (CSF) using multiple stable isotope peptides.MethodsEight tryptic peptides of PTGDS were synthesized containing stable isotopes ([13C]/[15N]) of amino acids. Experimental tandem mass spectrometry was used to obtain the best fragments and selective reaction monitoring (SRM) parameters were optimized using a triple quadrupole mass spectrometer. CSF or recombinant PTGDS was spiked with 50 pmol stable isotopes before digestion with trypsin. Liquid chromatography tandem mass spectrometry (LCMS) with SRM of multiple transitions and charged states for each peptide was used to quantify PTGDS in CSF.ResultsPeptide infusions reveal major b and y ions that can be used for experimental SRM. Standard curves are linear (0–100 pmol) with a peptide dependent on‐column limit of detection of 0.1–1 pmol. We detect all eight PTGDS peptides, and stable isotope SRM quantification reveals levels of PTGDS in CSF for normal subjects to be 15.2 ± 6.2 mg/L (n=14). CSF levels in subjects with migraine differ from those without, and average quantification using all peptides confirms a significant increase of PTGDS in migraine.ConclusionsExperimental SRM can be used to accurately quantify proteins in biological samples. This approach can be useful in discovering biomarkers of diseases when multiple peptides of biological pathways are monitored.

Proteomics addresses the important goal of determining the chemistry and composition of proteins in biological samples. Mass-spectrometry-based strategies have been highly successful in identifying and profiling proteins in complex mixtures; however, although depth of sampling continues to improve, a general recognition exists that no study has yet achieved complete protein coverage in any tissue, cell type, subcellular component, or fluid. The development of new approaches for comprehensively surveying highly complex protein mixtures, distinguishing protein isoforms, quantifying changes in protein abundance between different samples, and mapping post-translational modifications are areas of active research. These will be needed to achieve the "systems-wide" protein profiling goals of defining molecular responses to cell perturbations and obtaining biomarker information for disease detection, prognosis, and responses to therapy. We review recent progress in approaching these problems and present examples of successful applications and the outlook for the future.

Protein S-nitrosylation, the NO-dependent regulatory mechanism, is a posttranslational modification of reactive cysteine thiols to form S-nitrosothiols. The biotin-switch technique (BST) has become a mainstay method for detection of S-nitrosylated proteins in biological samples. On the basis of BST, we describe a surface plasmon resonance (SPR) spectroscopy method for detecting S-nitrosylated proteins. This method can be applied for the indirect determination of S-nitrosylated proteins in biological samples.

Multiple reaction monitoring (MRM) is one of the most powerful modes of analysis in liquid chromatographic tandem mass spectrometry for quantification of low-concentration metabolites in biological samples. The advances in mass spectrometry enabled the development of high-resolution multiple reaction monitoring (MRMHR ) and became suitable for the more specific analysis of target analytes. This is important for lipidomic studies and contributes in the medical and pharmaceutical fields, primarily in investigating alterations in cells or fluids relevant to various diseases. Therefore, this work proposes the development of the MRMHR method for quantification of circulating steroids. We focused on the determination of corticosterone, 11-dehydrocorticosterone (11-DHC), cortisol, cortisone, aldosterone, and progesterone concentration in serum, by using 129sv male mice exposed to chronic unpredictable stress to validate the quantification. The method was conducted according to the ANVISA normative, adopting a coefficient of variation, as well as relative standard deviation and relative error lower than 15% in linearity, intraday and interday precision, and accuracy. For cortisol, corticosterone, and their inert metabolites (cortisone and 11-DHC), the lower limit of quantification was 3.9ng·mL-1 , while that for progesterone and aldosterone was 7.8 and 15.6ng·mL-1 , respectively. MRMHR analysis showed that animals submitted to stressors have 4.5 times more corticosterone in their serum than nonstressed mice. However, 11-DHC concentration does not vary significantly in response to stress for these animals. The results indicate that the method can be applied for quantification of steroids in several biological samples, such as human plasma.

Background/AimsGlobal liquid chromatography mass spectrometry (LC-MS) profiling in a Thai population has previously identified a urinary metabolic signature in Opisthorchis viverrini-induced cholangiocarcinoma (CCA), primarily characterised by disturbance in acylcarnitine, bile acid, steroid, and purine metabolism. However, the detection of thousands of analytes by LC-MS in a biological sample in a single experiment potentially introduces false discovery errors. To verify these observed metabolic perturbations, a second validation dataset from the same population was profiled in a similar fashion.MethodsReverse-phase ultra-performance liquid-chromatography mass spectrometry was utilised to acquire the global spectral profile of 98 spot urine samples (from 46 healthy volunteers and 52 CCA patients) recruited from Khon Kaen, northeast Thailand (the highest incidence of CCA globally).ResultsMetabolites were differentially expressed in the urinary profiles from CCA patients. High urinary elimination of bile acids was affected by the presence of obstructive jaundice. The urine metabolome associated with non-jaundiced CCA patients showed a distinctive pattern, similar but not identical to published studies. A panel of 10 metabolites achieved a diagnostic accuracy of 93.4% and area under the curve value of 98.8% (CI = 96.3%–100%) for the presence of CCA.ConclusionsGlobal characterisation of the CCA urinary metabolome identified several metabolites of biological interest in this validation study. Analyses of the diagnostic utility of the discriminant metabolites showed excellent diagnostic potential. Further larger scale studies are required to confirm these findings internationally, particularly in comparison to sporadic CCA, not associated with liver fluke infestation.

Mass spectrometry has been widely applied in characterization and quantification of proteins from complex biological samples. Because the numbers of absolute amounts of proteins are needed in construction of mathematical models for molecular systems of various biological phenotypes and phenomena, a number of quantitative proteomic methods have been adopted to measure absolute quantities of proteins using mass spectrometry. The liquid chromatography-tandem mass spectrometry (LC-MS/MS) coupled with internal peptide standards, i.e., the stable isotope-coded peptide dilution series, which was originated from the field of analytical chemistry, becomes a widely applied method in absolute quantitative proteomics research. This approach provides more and more absolute protein quantitation results of high confidence. As quantitative study of posttranslational modification (PTM) that modulates the biological activity of proteins is crucial for biological science and each isoform may contribute a unique biological function, degradation, and/or subcellular location, the absolute quantitation of protein PTM isoforms has become more relevant to its biological significance. In order to obtain the absolute cellular amount of a PTM isoform of a protein accurately, impacts of protein fractionation, protein enrichment, and proteolytic digestion yield should be taken into consideration and those effects before differentially stable isotope-coded PTM peptide standards are spiked into sample peptides have to be corrected. Assisted with stable isotope-labeled peptide standards, the absolute quantitation of isoforms of posttranslationally modified protein (AQUIP) method takes all these factors into account and determines the absolute amount of a protein PTM isoform from the absolute amount of the protein of interest and the PTM occupancy at the site of the protein. The absolute amount of the protein of interest is inferred by quantifying both the absolute amounts of a few PTM-site-independent peptides in the total cellular protein and their peptide yields. The PTM occupancy determination is achieved by measuring the absolute amounts of both PTM and non-PTM peptides from the highly purified protein sample expressed in transgenic organisms or directly isolated from an organism using affinity purification. The absolute amount of each PTM isoform in the total cellular protein extract is finally calculated from these two variables. Following this approach, the ion intensities given by mass spectrometers are used to calculated the peptide amounts, from which the amounts of protein isoforms are then deduced. In this chapter, we describe the principles underlying the experimental design and procedures used in AQUIP method. This quantitation method basically employs stable isotope-labeled peptide standards and affinity purification from a tagged recombinant protein of interest. Other quantitation strategies and purification techniques related to this method are also discussed.

Ten systemic pesticides, comprising methomyl, thiamethoxam, acetamiprid, carbofuran, fosthiazate, metalaxyl, azoxystrobin, diethofencarb, propiconazole, and difenoconazole, were detected in 13 baby foods (cereals, boiled potatoes, fruit and milk) using QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) for sample preparation and liquid chromatography tandem mass spectrometry for analysis. The matrix-matched calibration curves showed good linearity with determination coefficients (R(2) ) >0.992. The limits of detection and quantitation were 0.0015-0.003 and 0.005-0.01 mg/kg, respectively. The mean recoveries of three different concentrations ranged from 69.2 to 127.1% with relative standard deviations <20%. The method was successfully applied to 13 actual samples collected from a local market, and none of the samples were found to contain pesticide residues. This method is suitable for the identification and quantification of systemic pesticides with matrix-matched standards in various baby foods.

Structural annotation of small molecules in biological samples remains a key bottleneck in untargeted metabolomics, despite rapid progress in predictive methods and tools during the past decade. Liquid chromatography–tandem mass spectrometry, one of the most widely used analysis platforms, can detect thousands of molecules in a sample, the vast majority of which remain unidentified even with best-of-class methods. Here we present LC-MS2Struct, a machine learning framework for structural annotation of small-molecule data arising from liquid chromatography–tandem mass spectrometry (LC-MS2) measurements. LC-MS2Struct jointly predicts the annotations for a set of mass spectrometry features in a sample, using a novel structured prediction model trained to optimally combine the output of state-of-the-art MS2 scorers and observed retention orders. We evaluate our method on a dataset covering all publicly available reversed-phase LC-MS2 data in the MassBank reference database, including 4,327 molecules measured using 18 different LC conditions from 16 contributors, greatly expanding the chemical analytical space covered in previous multi-MS2 scorer evaluations. LC-MS2Struct obtains significantly higher annotation accuracy than earlier methods and improves the annotation accuracy of state-of-the-art MS2 scorers by up to 106%. The use of stereochemistry-aware molecular fingerprints improves prediction performance, which highlights limitations in existing approaches and has strong implications for future computational LC-MS2 developments.

Preparation of multisample external calibration curves and dilution of study samples are critical steps in bioanalytical sample processing for quantitative liquid chromatography-tandem mass spectrometry (LC-MS/MS) based bioanalysis of small-molecule compounds, biotherapeutics, and biomarkers, but they can be time-consuming and prone to error. It is highly desired to simplify or eliminate these two steps in order to improve the assay throughput and robustness. While multisample external calibration curve preparation using authentic matrices can be eliminated with a previously reported in-sample calibration curve (ISCC) approach using multiple isotopologue reaction monitoring (MIRM) of a stable isotopically labeled (SIL) analyte, dilution of study samples is still inevitable due to limited LC-MS/MS assay ranges. In this work, a one-sample multipoint external calibration curve and isotope sample dilution, both using MIRM of an analyte, for quantitative LC-MS/MS based bioanalysis are proposed and demonstrated. By spiking a known amount of an analyte into one blank authentic matrix sample, a one-sample multipoint external calibration curve in an authentic matrix can be established on the basis of the relationship between the calculated theoretical isotopic abundances (analyte concentration equivalents) and the MS/MS responses in the corresponding MIRM channels. This one-sample multipoint external calibration curve can be used in the same way as the traditional multisample external calibration curve for quantitative LC-MS/MS-based bioanalysis. As isotopic abundance in each MIRM channel can be calculated and measured accurately, isotope sample dilution can be achieved by simply monitoring one or a few of the MIRM channels of the analyte in addition to the most abundant MIRM channel for study samples. While the most abundant MIRM channel (isotopic abundance of 100%) is used for the quantitation of samples having concentrations within the assay calibration curve range, less abundant MIRM channels (isotopic abundance of IA%) can be used for the quantitation of samples having concentrations beyond the assay upper limit of quantitation (ULOQ), resulting in isotope dilution factors (IDF) of 100%/IA%. The approaches of one-sample multipoint external calibration curve and isotope sample dilution were evaluated and demonstrated in this work with an example of the quantitation of daclatasvir in human plasma extracted with liquid-liquid extraction. Using these approaches together with the MIRM-ISCC methodology, accurate and reliable LC-MS/MS bioanalysis can be achieved without the need of preparation of multisample external calibration curve and dilution of study samples.

Targeted protein quantification using liquid chromatography-tandem mass spectrometry with stable isotope-labeled standards is recognized as the gold standard of practice for protein quantification. Such assays, however, can only cover a limited number of proteins, and developing targeted methods for larger numbers of proteins requires substantial investment. Alternatively, large-scale global proteomic experiments along with computational methods such as the "total protein approach" (TPA) have the potential to provide extensive protein quantification. In this study, we compared the TPA-based quantitation of seven major hepatic uptake transporters in four human liver tissue samples using global proteomic data obtained from two multiplexed tandem mass tag experiments (performed in two independent laboratories) to the quantitative data from targeted proteomic assays. The TPA-based quantitation of these hepatic transporters [sodium-taurocholate cotransporting polypeptide (NTCP/SLC10A1), organic anion transporter 2 (OAT2/SLC22A7), OAT7/SLC22A9, organic anion-transporting polypeptide 1B1 (OATP1B1/SLCO1B1), OATP1B3/SLCO1B3, OATP2B1/SLCO2B1, and organic cation transporter (OCT1/SLC22A1)] showed good-to-excellent correlations (Pearson r = 0.74-1.00) to the targeted data. In addition, the values were similar to those measured by targeted proteomics with 71% and 86% of the data sets falling within 3-fold of the targeted data. A comparison of the TPA-based quantifications of enzyme abundances to available literature data showed that the majority of the enzyme quantifications fell within the reference data intervals. In conclusion, these results demonstrate the capability of multiplexed global proteomic experiments to detect differences in protein expression between samples and provide reasonable estimations of protein expression levels.

We present the first large scale study characterizing both N- and O-linked glycosylation in a site-specific manner on hundreds of proteins. We demonstrate that a lectin-affinity fractionation step using wheat germ agglutinin enriches not only peptides carrying intracellular O-GlcNAc, but also those bearing ER/Golgi-derived N- and O-linked carbohydrate structures. Liquid chromatography-MS (LC/MS) analysis with high accuracy precursor mass measurements and high sensitivity ion trap electron-transfer dissociation (ETD) were utilized for structural characterization of glycopeptides. Our results reveal both the identity of the precise sites of glycosylation and information on the oligosaccharide structures possible on these proteins. We report a novel iterative approach that allowed us to interpret the ETD data set directly without making prior assumptions about the nature and distribution of oligosaccharides present in our glycopeptide mixture. Over 2500 unique N- and O-linked glycopeptides were identified on 453 proteins. The extent of microheterogeneity varied extensively, and up to 19 different oligosaccharides were attached at a given site. We describe the presence of the well-known mucin-type structures for O-glycosylation, an EGF-domain-specific fucosylation and a rare O-mannosylation on the transmembrane phosphatase Ptprz1. Finally, we identified three examples of O-glycosylation on tyrosine residues.

Mass spectrometry (MS)-based proteomics focuses on identifying and quantifying peptides and proteins in biological samples. Processing of MS-derived raw data, including deconvolution, alignment, and peptide-protein prediction, has been achieved through various software platforms. However, the downstream analysis, including quality control, visualizations, and interpretation of proteomics results, remains cumbersome due to the lack of integrated tools to facilitate the analyses. To address this challenge, we developed QuickProt, a series of Python-based Google Colab notebooks for analyzing data-independent acquisition (DIA) and parallel reaction monitoring (PRM) proteomics datasets. These pipelines are designed so that users with no coding expertise can utilize the tool. Furthermore, as open-source code, QuickProt notebooks can be customized and incorporated into existing workflows. As proof of concept, we applied QuickProt to analyze in-house DIA and stable isotope dilution (SID)-PRM MS proteomics datasets from a time-course study of human erythropoiesis. The analysis resulted in annotated tables and publication-ready figures revealing a dynamic rearrangement of the proteome during erythroid differentiation, with the abundance of proteins linked to gene regulation, metabolic, and chromatin remodeling pathways increasing early in erythropoiesis. Altogether, these tools aim to automate and streamline DIA and PRM-MS proteomics data analysis, making it more efficient and less time-consuming.

IntroductionHeart failure is a major health problem in western countries with high costs and poor outcome despite advances in therapy. 50% of patients die within 4 years of presentation, and...

The low levels of endogenous proteins in biological samples and the large dynamic range of the proteome complicate global analysis of gene expression at the protein level. The use of liquid chromatography (LC) in analytical chemistry is well established. However, the relatively low sensitivity associated with conventional LC makes it unsuitable for the analysis of certain biological samples. Furthermore, the flow rates at which it is operated are not compatible with the use of specific detectors, such as electrospray ionization mass spectrometers. Therefore, due to the analytical demands of biological samples, miniaturized LC techniques were developed to allow for the analysis of samples with greater sensitivity than that afforded by conventional LC. In nanoflow LC (nanoLC) chromatographic separations are performed using flow rates in the range of low nanoliter per minute, which result in high analytical sensitivity due to the large concentration efficiency afforded by this type of chromatography. NanoLC, in combination to tandem mass spectrometry, was first used to analyze peptides and as an alternative to other mass spectrometric methods to identify gel-separated proteins. More recently, gel-free analytical approaches based on LC and nanoLC separations have been developed, which are allowing proteomics to be performed in faster and more comprehensive manner than by using strategies based on the classical 2D gel electrophoresis approach.

Proteomic studies require efficient, robust, and practical methods of characterizing proteins present in biological samples. Here we describe an integrated strategy for systematic proteome analysis based on differential guanidination of C-terminal lysine residues on tryptic peptides followed by capillary liquid chromatography-electrospray tandem mass spectrometry. The approach, termed mass-coded abundance tagging (MCAT), facilitates the automated, large-scale, and comprehensive de novo determination of peptide sequence and relative quantitation of proteins in biological samples in a single analysis. MCAT offers marked advantages as compared with previously described methods and is simple, economic, and effective when applied to complex proteomic mixtures. MCAT is used to identify proteins, including polymorphic variants, from complex mixtures and measure variation in protein levels from diverse cell types.