Quantifying Peptide Signal in MALDI-TOF Mass Spectrometry Data

Abstract

This study addressed the question of which properties in MALDI-TOF spectra are relevant to the task of identifying mass and abundance of a peptide species in human serum. Data of this type are common to biomarker studies, but significant within- and between-spectrum variabilities make quantifying biologically induced features difficult. We investigated this signal content and quantified the existence, or lack, of peptide-induced signal (as manifest in a multiresolution decomposition) by generating spectra from human serum in which the abundance of peptides of specific masses is controlled by a sequence of dilutions. The intensities of the corresponding features were directly proportional to peptide concentration. The primary goal was to exhibit some quantifiable properties of raw spectra from this application of MALDI-TOF mass spectrometry. Although no recommendations are given regarding the best method for processing these data, the results confirm the utility of a simple method, based on wavelets, for defining and quantifying features related to low abundance peptide species in a heterogeneous set of complex spectra. Estimates on lower limits of detectable peptide abundance (in the 20-nmol range) and on the number of features present in a spectrum are made possible by the controlled experimental design, the use of a large external reference data set, and dependence on relatively few modeling assumptions.