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Accuracy and Reproducibility in Quantification of Plasma Protein Concentrations by Mass Spectrometry without the Use of Isotopic Standards.

ABSTRACT: Quantitative proteomic analysis with mass spectrometry holds great promise for simultaneously quantifying proteins in various biosamples, such as human plasma. Thus far, studies addressing the reproducible measurement of endogenous protein concentrations in human plasma have focussed on targeted analyses employing isotopically labelled standards. Non-targeted proteomics, on the other hand, has been less employed to this end, even though it has been instrumental in discovery proteomics, generating large datasets in multiple fields of research.Using a non-targeted mass spectrometric assay (LCMSE), we quantified abundant plasma proteins (43 mg/mL-40 ug/mL range) in human blood plasma specimens from 30 healthy volunteers and one blood serum sample (ProteomeXchange: PXD000347). Quantitative results were obtained by label-free mass spectrometry using a single internal standard to estimate protein concentrations. This approach resulted in quantitative results for 59 proteins (cut off ?11 samples quantified) of which 41 proteins were quantified in all 31 samples and 23 of these with an inter-assay variability of ? 20%. Results for 7 apolipoproteins were compared with those obtained using isotope-labelled standards, while 12 proteins were compared to routine immunoassays. Comparison of quantitative data obtained by LCMSE and immunoassays showed good to excellent correlations in relative protein abundance (r = 0.72-0.96) and comparable median concentrations for 8 out of 12 proteins tested. Plasma concentrations of 56 proteins determined by LCMSE were of similar accuracy as those reported by targeted studies and 7 apolipoproteins quantified by isotope-labelled standards, when compared to reference concentrations from literature.This study shows that LCMSE offers good quantification of relative abundance as well as reasonable estimations of concentrations of abundant plasma proteins.

SUBMITTER: Kramer G

PROVIDER: S-EPMC4608811 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Accuracy and Reproducibility in Quantification of Plasma Protein Concentrations by Mass Spectrometry without the Use of Isotopic Standards.

Kramer Gertjan G Woolerton Yvonne Y van Straalen Jan P JP Vissers Johannes P C JP Dekker Nick N Langridge James I JI Beynon Robert J RJ Speijer Dave D Sturk Auguste A Aerts Johannes M F G JM

PloS one 20151016 10

<h4>Background</h4>Quantitative proteomic analysis with mass spectrometry holds great promise for simultaneously quantifying proteins in various biosamples, such as human plasma. Thus far, studies addressing the reproducible measurement of endogenous protein concentrations in human plasma have focussed on targeted analyses employing isotopically labelled standards. Non-targeted proteomics, on the other hand, has been less employed to this end, even though it has been instrumental in discovery pr ...[more]

PMID: 26474480

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Project description:We applied a non targeted mass spectrometric assay (LCMSE), to quantify 55 abundant plasma proteins in specimens from 31 healthy volunteers. Quantitation was done by HI3 peptide measurement using a single internal standard to estimate protein concentrations. Results for 7 apolipoproteins were compared with those obtained using isotope labelled standards, while 12 proteins were compared to routine immunoassays. Blood samples were obtained from 31 healthy volunteers (17 males; 14 females) with a median age of 46 years and a range of 22-67 years. Total plasma protein concentration was assayed with a BCA-assay (20) according to the manufacturer’s protocol (Thermo). Samples were diluted tenfold in 0.1% Rapigest SF (Waters Corporation, Milford, MA), 50 mM ammonium bicarbonate and heated at 95° C for 15 min. Subsequently, plasma samples were reduced with 5 mM dithiothreitol (60° C, 30 min) and alkylated with 15 mM iodoacetamide (ambient temperature, dark, 30 min). Proteolytic digestion was performed with modified trypsin (gold grade, Promega, Madison WI) at 0.3 units/µg protein, (37° C, 20 hours) unless indicated otherwise. Following digestion, Rapigest SF was broken down by adding 1% trifluoroacetic acid (pH<2, 37 °C, 45 min). Peptide solutions were centrifuged (20,000 x g, 10 min) and supernatant was collected. Prior to analyses a MASSPREP protein digestion standard (Waters Corporation, ADH1 or ENO from Saccharomyces cerevisiae) was added for quantitation purposes. LC-MS analyses were performed using ~ 0.21 µg of the final plasma protein digest mixtures (384 times total dilution) unless indicated otherwise. LC separations of tryptic peptides were performed with a NanoAcquity system (Waters Corporation), coupled to a Synapt G2 quadrupole time of flight mass spectrometer (Waters Corporation, Manchester, UK). Accurate mass precursor and fragment ion LC-MS data were collected in data independent LCMSE mode of acquisition. Continuum LC-MS data were processed using ProteinLynx GlobalSERVER version 2.5 (PLGS 2.5, Waters Corporation). Parameter settings: digest reagent trypsin, allow 1 ‘missed cleavage’, search tolerances automatic, typically 5 ppm for precursor and 15 ppm for product ions, fixed modification cysteine carbamidomethylation, and variable modification methionine oxidation. Protein identifications were obtained searching the human SwissProt entries of an UniProt database (release 13.2). This database was modified to include N-terminal processing of proteins using protein maturation device software, with ADH1 and ENO1 of S. cerevisiae appended as internal standard to address technical variation and allow concentration determinations. Estimation of false-positive identification rates was done by searching a randomized version of the abovementioned human protein database generated within PLGS 2.5. Data were exported as csv-files for further, detailed analysis. Stringent criteria were applied for quantitation, protein identifications were only considered significant if reported in 14 or more samples. Protein false positive identification rates were estimated using the criteria mentioned above and no false positives were identified in these searches. DATASET: KC1-31: 31 healthy volunteers QC1-10: 10 times injection of a single sample to ascertain analytical variation over 9 days of measurements. 20120802_QC1-QC6: 6 pooled plasma samples worked up and analysed during a single day of measurements to ascertain Intra-assay variation. 20120427_S2,S4;20120525_S18,S19;20120626_S3,S4;20120802_QC7: 7 pooled plasma samples processed and analysed during 3 months of routine measurements to analyse Inter-assay variation 20130416_s1-s5: pooled plasma samples spiked with a QCONCATAMER for 11 apolipoproteins labelled by heavy Lysine and Arginine (+6.02 AMU) to quantify apolipoproteins by internal isotope labelled standard.

Project description:BackgroundAssessing the reproducibility of measurements is an important first step for improving the reliability of downstream analyses of high-throughput metabolomics experiments. We define a metabolite to be reproducible when it demonstrates consistency across replicate experiments. Similarly, metabolites which are not consistent across replicates can be labeled as irreproducible. In this work, we introduce and evaluate the use (Ma)ximum (R)ank (R)eproducibility (MaRR) to examine reproducibility in mass spectrometry-based metabolomics experiments. We examine reproducibility across technical or biological samples in three different mass spectrometry metabolomics (MS-Metabolomics) data sets.ResultsWe apply MaRR, a nonparametric approach that detects the change from reproducible to irreproducible signals using a maximal rank statistic. The advantage of using MaRR over model-based methods that it does not make parametric assumptions on the underlying distributions or dependence structures of reproducible metabolites. Using three MS Metabolomics data sets generated in the multi-center Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPD) study, we applied the MaRR procedure after data processing to explore reproducibility across technical or biological samples. Under realistic settings of MS-Metabolomics data, the MaRR procedure effectively controls the False Discovery Rate (FDR) when there was a gradual reduction in correlation between replicate pairs for less highly ranked signals. Simulation studies also show that the MaRR procedure tends to have high power for detecting reproducible metabolites in most situations except for smaller values of proportion of reproducible metabolites. Bias (i.e., the difference between the estimated and the true value of reproducible signal proportions) values for simulations are also close to zero. The results reported from the real data show a higher level of reproducibility for technical replicates compared to biological replicates across all the three different datasets. In summary, we demonstrate that the MaRR procedure application can be adapted to various experimental designs, and that the nonparametric approach performs consistently well.ConclusionsThis research was motivated by reproducibility, which has proven to be a major obstacle in the use of genomic findings to advance clinical practice. In this paper, we developed a data-driven approach to assess the reproducibility of MS-Metabolomics data sets. The methods described in this paper are implemented in the open-source R package marr, which is freely available from Bioconductor at http://bioconductor.org/packages/marr .

Dataset Information

Accuracy and Reproducibility in Quantification of Plasma Protein Concentrations by Mass Spectrometry without the Use of Isotopic Standards.

Publications

Accuracy and Reproducibility in Quantification of Plasma Protein Concentrations by Mass Spectrometry without the Use of Isotopic Standards.

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