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

Min Zhu, Pingbo Zhang, Minghui Geng-Spyropoulos, Ruin Moaddel, Richard David Semba, Luigi Ferrucci

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
JournalProteomics
DOIs
StateAccepted/In press - 2016

Fingerprint

Robotics
Assays
Mass Spectrometry
Throughput
Mass spectrometry
Monitoring
Processing
Complement Factor H
Peptides
Plasma (human)
Epidemiologic Studies
Digestion
Proteins
Equipment and Supplies
Plasmas

Keywords

  • Absolute quantification
  • Automated sample preparation
  • Heavy isotope-labeled peptides
  • Reproducibility
  • SRM
  • Technology

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology

Cite this

A robotic protocol for high-throughput processing of samples for selected reaction monitoring assays. / Zhu, Min; Zhang, Pingbo; Geng-Spyropoulos, Minghui; Moaddel, Ruin; Semba, Richard David; Ferrucci, Luigi.

In: Proteomics, 2016.

Research output: Contribution to journalArticle

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