Precision enhancement of MALDI-TOF MS using high resolution peak detection and label-free alignment

• Published in: Proteomics (Weinheim) Vol. 8; no. 8; pp. 1530 - 1538
• Main Authors: Tracy, Maureen B, Chen, Haijian, Weaver, Dennis M, Malyarenko, Dariya I, Sasinowski, Maciek, Cazares, Lisa H, Drake, Richard R, Semmes, O. John, Tracy, Eugene R, Cooke, William E
• Format: Journal Article
• Language: English
• Published: Weinheim Wiley-VCH Verlag 01.04.2008; WILEY-VCH Verlag; WILEY‐VCH Verlag; Wiley-VCH
• Subjects: Algorithm; Algorithms; Analytical, structural and metabolic biochemistry; Biological and medical sciences; Blood Proteins - analysis; Fundamental and applied biological sciences. Psychology; Humans; Mass Spectra; Mass Spectrometry; Miscellaneous; Pattern Recognition, Automated; Peptide Mapping; Protein Array Analysis; Proteins; Proteome - analysis; Reproducibility; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization - methods; Detection; Reproducibility; Mass Spectra; Algorithm; Mass spectrometry; Proteomics
• ISSN: 1615-9853; 1615-9861; 1615-9861
• DOI: 10.1002/pmic.200701146

We have developed an automated procedure for aligning peaks in multiple TOF spectra that eliminates common timing errors and small variations in spectrometer output. Our method incorporates high-resolution peak detection, re-binning, and robust linear data fitting in the time domain. This procedure aligns label-free (uncalibrated) peaks to minimize the variation in each peak's location from one spectrum to the next, while maintaining a high number of degrees of freedom. We apply our method to replicate pooled-serum spectra from multiple laboratories and increase peak precision (t/σt) to values limited only by small random errors (with σt less than one time count in 89 out of 91 instances, 13 peaks in seven datasets). The resulting high precision allowed for an order of magnitude improvement in peak m/z reproducibility. We show that the CV for m/z is 0.01% (100 ppm) for 12 out of the 13 peaks that were observed in all datasets between 2995 and 9297 Da.