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A robotic protocol for high-throughput processing of samples for selected reaction monitoring assays.

ABSTRACT: Selected reaction monitoring mass spectrometry (SRM-MS) is a sensitive and accurate method for the quantification of targeted proteins in biological specimens. However, the sample throughput and reliability of this technique is limited by the complexity of sample preparation, as well as instrumentation and data processing. Modern robotic equipment allows for rapid and accurate processing of large number of samples and makes SRM-MS assay applicable in epidemiological studies. Herein, we describe an automated sample processing platform developed in the context of an SRM-MS protocol for the assay of complement factor H protein and its variants in human plasma. We report detailed performance data on plasma digestion, sample cleanup and optimized robotic handling implemented on a Biomek® NXp Workstation. Method validation was assessed with isotopically labeled peptide standards and had high reproducibility of intra-day assay (CVs from 2.7 to 17.5% with median CV of 5.3%) and inter-day assay (CVs from 4.8 to 17.6 with median CV of 7.2%) for all peptides.

SUBMITTER: Zhu M

PROVIDER: S-EPMC5534325 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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A robotic protocol for high-throughput processing of samples for selected reaction monitoring assays.

Zhu Min M Zhang Pingbo P Geng-Spyropoulos Minghui M Moaddel Ruin R Semba Richard D RD Ferrucci Luigi L

Proteomics 20161223 6

Selected reaction monitoring mass spectrometry (SRM-MS) is a sensitive and accurate method for the quantification of targeted proteins in biological specimens. However, the sample throughput and reliability of this technique is limited by the complexity of sample preparation, as well as instrumentation and data processing. Modern robotic equipment allows for rapid and accurate processing of large number of samples and makes SRM-MS assay applicable in epidemiological studies. Herein, we describe ...[more]

PMID: 27862927

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Project description:BackgroundSince its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM) is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRM-based proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the discovery and validation of targets in hypothesis-driven studies in systems biology.ResultWe introduce a new open source software pipeline, ATAQS (Automated and Targeted Analysis with Quantitative SRM), which consists of a number of modules that collectively support the SRM assay development workflow for targeted proteomic experiments (project management and generation of protein, peptide and transitions and the validation of peptide detection by SRM). ATAQS provides a flexible pipeline for end-users by allowing the workflow to start or end at any point of the pipeline, and for computational biologists, by enabling the easy extension of java algorithm classes for their own algorithm plug-in or connection via an external web site.This integrated system supports all steps in a SRM-based experiment and provides a user-friendly GUI that can be run by any operating system that allows the installation of the Mozilla Firefox web browser.ConclusionsTargeted proteomics via SRM is a powerful new technique that enables the reproducible and accurate identification and quantification of sets of proteins of interest. ATAQS is the first open-source software that supports all steps of the targeted proteomics workflow. ATAQS also provides software API (Application Program Interface) documentation that enables the addition of new algorithms to each of the workflow steps. The software, installation guide and sample dataset can be found in http://tools.proteomecenter.org/ATAQS/ATAQS.html.

Project description:For many research questions in modern molecular and systems biology, information about absolute protein quantities is imperative. This information includes, for example, kinetic modeling of processes, protein turnover determinations, stoichiometric investigations of protein complexes, or quantitative comparisons of different proteins within one sample or across samples. To date, the vast majority of proteomic studies are limited to providing relative quantitative comparisons of protein levels between limited numbers of samples. Here we describe and demonstrate the utility of a targeting MS technique for the estimation of absolute protein abundance in unlabeled and nonfractionated cell lysates. The method is based on selected reaction monitoring (SRM) mass spectrometry and the "best flyer" hypothesis, which assumes that the specific MS signal intensity of the most intense tryptic peptides per protein is approximately constant throughout a whole proteome. SRM-targeted best flyer peptides were selected for each protein from the peptide precursor ion signal intensities from directed MS data. The most intense transitions per peptide were selected from full MS/MS scans of crude synthetic analogs. We used Monte Carlo cross-validation to systematically investigate the accuracy of the technique as a function of the number of measured best flyer peptides and the number of SRM transitions per peptide. We found that a linear model based on the two most intense transitions of the three best flying peptides per proteins (TopPep3/TopTra2) generated optimal results with a cross-correlated mean fold error of 1.8 and a squared Pearson coefficient R(2) of 0.88. Applying the optimized model to lysates of the microbe Leptospira interrogans, we detected significant protein abundance changes of 39 target proteins upon antibiotic treatment, which correlate well with literature values. The described method is generally applicable and exploits the inherent performance advantages of SRM, such as high sensitivity, selectivity, reproducibility, and dynamic range, and estimates absolute protein concentrations of selected proteins at minimized costs.

Dataset Information

A robotic protocol for high-throughput processing of samples for selected reaction monitoring assays.

Publications

A robotic protocol for high-throughput processing of samples for selected reaction monitoring assays.

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