Literature DB >> 23943474

Improving peptide relative quantification in MALDI-TOF MS for biomarker assessment.

Amaya Albalat1, Angelique Stalmach, Vasiliki Bitsika, Justyna Siwy, Joost P Schanstra, Alexandros D Petropoulos, Antonia Vlahou, Joachim Jankowski, Frederik Persson, Peter Rossing, Thorsten W Jaskolla, Harald Mischak, Holger Husi.   

Abstract

Proteomic profiling by MALDI-TOF MS presents various advantages (speed of analysis, ease of use, relatively low cost, sensitivity, tolerance against detergents and contaminants, and possibility of automation) and is being currently used in many applications (e.g. peptide/protein identification and quantification, biomarker discovery, and imaging MS). Earlier studies by many groups indicated that moderate reproducibility in relative peptide quantification is a major limitation of MALDI-TOF MS. In the present work, we examined and demonstrate a clear effect, in cases apparently random, of sample dilution in complex samples (urine) on the relative quantification of peptides by MALDI-TOF MS. Results indicate that in urine relative abundance of peptides cannot be assessed with confidence based on a single MALDI-TOF MS spectrum. To account for this issue, we developed and propose a novel method of determining the relative abundance of peptides, taking into account that peptides have individual linear quantification ranges in relation to sample dilution. We developed an algorithm that calculates the range of dilutions at which each peptide responds in a linear manner and normalizes the received peptide intensity values accordingly. This concept was successfully applied to a set of urine samples from patients diagnosed with diabetes presenting normoalbuminuria (controls) and macroalbuminuria (cases).
© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Biomarker; MALDI-TOF MS; Proteomic profiling; Relative quantification; Technology; Urine

Mesh:

Substances:

Year:  2013        PMID: 23943474     DOI: 10.1002/pmic.201300100

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  5 in total

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Journal:  Proteomics Clin Appl       Date:  2016-05-17       Impact factor: 3.494

  5 in total

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