Research article

Calibration of mass spectrometric peptide mass fingerprint data without specific external or internal calibrants

Witold E Wolski^1,2,5 , Maciej Lalowski³ , Peter Jungblut⁴ and Knut Reinert²

¹  Max Planck Institute for Molecular Genetics, Ihnestraße 63–73, D-14195 Berlin, Germany

²  Institute for Computer Science, Free University Berlin, Takustr. 9, 14195 Berlin, Germany

³  Max Delbrück Center for Molecular Medicine, Robert-Roessle-Str. 10, D-13125 Berlin-Buch, Germany

⁴  Max Planck Institute for Infection Biology, Schumannstr. 21–22, D-10117 Berlin, Germany

⁵  School of Mathematics and Statistics, Merz Court, University of Newcastle upon Tyne, NE1 7RU, UK

author email corresponding author email

BMC Bioinformatics 2005, 6:203doi:10.1186/1471-2105-6-203

Published:	15 August 2005

Abstract

Background

Peptide Mass Fingerprinting (PMF) is a widely used mass spectrometry (MS) method of analysis of proteins and peptides. It relies on the comparison between experimentally determined and theoretical mass spectra. The PMF process requires calibration, usually performed with external or internal calibrants of known molecular masses.

Results

We have introduced two novel MS calibration methods. The first method utilises the local similarity of peptide maps generated after separation of complex protein samples by two-dimensional gel electrophoresis. It computes a multiple peak-list alignment of the data set using a modified Minimum Spanning Tree (MST) algorithm. The second method exploits the idea that hundreds of MS samples are measured in parallel on one sample support. It improves the calibration coefficients by applying a two-dimensional Thin Plate Splines (TPS) smoothing algorithm. We studied the novel calibration methods utilising data generated by three different MALDI-TOF-MS instruments. We demonstrate that a PMF data set can be calibrated without resorting to external or relying on widely occurring internal calibrants. The methods developed here were implemented in R and are part of the BioConductor package mscalib available from http://www.bioconductor.org webcite.

Conclusion

The MST calibration algorithm is well suited to calibrate MS spectra of protein samples resulting from two-dimensional gel electrophoretic separation. The TPS based calibration algorithm might be used to correct systematic mass measurement errors observed for large MS sample supports. As compared to other methods, our combined MS spectra calibration strategy increases the peptide/protein identification rate by an additional 5 – 15%.