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

Albalat, A. et al. (2013) Improving peptide relative quantification in MALDI-TOF MS for biomarker assessment. Proteomics, 13(20), pp. 2967-2975. (doi: 10.1002/pmic.201300100)

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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).

Item Type:Articles
Glasgow Author(s) Enlighten ID:Stalmach, Dr Angelique and Albalat, Dr Amaya and Husi, Dr Holger and Mischak, Professor Harald
Authors: Albalat, A., Stalmach, A., Bitsika, V., Siwy, J., Schanstra, J.P., Petropoulos, A.D., Vlahou, A., Jankowski, J., Persson, F., Rossing, P., Jaskolla, T., Mischak, H., and Husi, H.
Subjects:Q Science > QH Natural history > QH301 Biology
Q Science > QH Natural history > QH345 Biochemistry
R Medicine > R Medicine (General)
College/School:College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
Journal Name:Proteomics
ISSN (Online):1615-9861
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
546181Development of an efficient, robust MS-based platform for early detection of acute kidney injuryHarald MischakMedical Research Council (MRC)G1000791RI CARDIOVASCULAR & MEDICAL SCIENCES