title: Quantitative accuracy in mass spectrometry based proteomics of complex samples: the impact of labeling and precursor interference.
abstract: Knowing the limit of quantification is important to accurately judge the results from proteomics studies. In order to investigate isobaric labels in combination with peptide pre-fractionation by high resolution isoelectric focusing in terms of limit of detection, quantitative accuracy and how to improve it, we used a human cell lysate spiked with 57 protein standards providing reference points across a wide concentration range. Specifically, the impact of precursor mixing (isolation interference and reporter ion interference) on quantitative accuracy was investigated by co-analyzing iTRAQ (8-plex) and TMT (6-plex) labeled peptides. A label-free analysis was also performed. Peptides, labeled or label-free, were analyzed by LC-MS/MS (Orbitrap Velos). We identified 3386 proteins by the label-free approach, 4466 with iTRAQ and 5961 with TMT. A linear range of quantification down to 1fmol was indicated for both isobaric and label-free analysis workflows, with an upper limit exceeding 60fmol. Our results indicate that 6-plex TMT is more sensitive than 8-plex iTRAQ. For isobaric labels, quantitative accuracy was affected by precursor mixing. Based on our evaluation on precursor mixing and accuracy of isobaric label quantification, we propose a cut off of <30% isolation interference for peptide spectrum matches (PSMs) used in the quantification.
  
  
  CONCLUSIONS
  Quantitative proteome analysis by mass spectrometry offers opportunities for biological research. However, knowing the limit of quantification in biological samples is important to accurately judge the results. By using a high-complexity sample spiked with protein standards of known concentrations, we investigated the quantification limits of label-free and label-based peptide quantification, including an evaluation of precursor mixing and its impact on quantification accuracy by isobaric labels. We suggest limits of allowed precursor interference and believe that this study contributes with information useful in proteome quantification by mass spectrometry.
authors.affiliation: Science for Life Laboratory Stockholm and Cancer Proteomics, Department of Oncology-Pathology, Karolinska Institutet, Sweden.
authors.forename: AnnSofi
authors.initials: A
authors.lastname: Sandberg
authors.affiliation: Science for Life Laboratory Stockholm and Cancer Proteomics, Department of Oncology-Pathology, Karolinska Institutet, Sweden.
authors.forename: Rui M M
authors.initials: RM
authors.lastname: Branca
authors.affiliation: Science for Life Laboratory Stockholm and Cancer Proteomics, Department of Oncology-Pathology, Karolinska Institutet, Sweden.
authors.forename: Janne
authors.initials: J
authors.lastname: Lehtiö
authors.affiliation: Science for Life Laboratory Stockholm and Cancer Proteomics, Department of Oncology-Pathology, Karolinska Institutet, Sweden. Electronic address: jenny.forshed@ki.se.
authors.forename: Jenny
authors.initials: J
authors.lastname: Forshed
mesh_terms: D045744:Cell Line, Tumor; D005260:Female; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods*; D020543:Proteome / Q000378:metabolism*; D040901:Proteomics / Q000379:methods*
chemical_list: D020543:Proteome
keywords: Label-free; Precursor mixing; Quantification; TMT; iTRAQ