Improved signal processing and normalization for biomarker protein detection in broad-mass-range TOF mass spectra from clinical samples.

PURPOSE: To demonstrate robust detection of biomarkers in broad-mass-range TOF-MS data. EXPERIMENTAL DESIGN: Spectra were obtained for two serum protein profiling studies: (i) 2-200 kDa for 132 patients, 67 healthy and 65 diagnosed as having adult T-cell leukemia and (ii) 2-100 kDa for 140 patients, 70 pairs, each with matched prostate-specific antigen (PSA) levels and biopsy-confirmed diagnoses of one benign and one prostate cancer. Signal processing was performed on raw spectra and peak data were normalized using four methods. Feature selection was performed using Bayesian Network Analysis and a classifier was tested on withheld data. Identification of candidate biomarkers was pursued. RESULTS: Integrated peak intensities were resolved over full spectra. Normalization using local noise values was superior to global methods in reducing peak correlations, reducing replicate variability and improving feature selection stability. For the leukemia data set, potential disease biomarkers were detected and were found to be predictive for withheld data. Preliminary assignments of protein IDs were consistent with published results and LC-MS/MS identification. No prostate-specific-antigen-independent biomarkers were detected in the prostate cancer data set. CONCLUSIONS AND CLINICAL RELEVANCE: Signal processing, local signal-to-noise (SNR) normalization and Bayesian Network Analysis feature selection facilitate robust detection and identification of biomarker proteins in broad-mass-range clinical TOF-MS data.

Automated assignment of ionization states in broad-mass matrix-assisted laser desorption/ionization spectra of protein mixtures.

A computational technique is presented for the automated assignment of the multiple charge and multimer states (ionization states) in the time-of-flight (TOF) domain for matrix-assisted laser desorption/ionization (MALDI) spectra. Examples of the application of this technique include an improved, automatic calibration over the 2 to 70 kDa mass range and a reduced data redundancy after reconstruction of the molecular spectrum of only singly charged monomers. This method builds on our previously reported enhancement of broad-mass signal detection, and includes two steps: (1) an automated correction of the instrumental acquisition initial time delay, and (2) a recursive TOF detection of multiple charge states and singly charged multimers of molecular [MH](+) ions over the entire record range, based on MALDI methods. The technique is tested using calibration mixtures and pooled serum quality control samples acquired along with clinical study data. The described automated procedure improves the analysis and dimension reduction of MS data for comparative proteomics applications.

Deconvolution filters to enhance resolution of dense time-of-flight survey spectra in the time-lag optimization range.

By applying time-domain filters to time-of-flight (TOF) mass spectrometry signals, we have simultaneously smoothed and narrowed spectra resulting in improved resolution and increased signal-to-noise ratios. This filtering procedure has an advantage over detailed curve fitting of spectra in the case of large dense spectra, when neither the location nor the number of mass peaks is known a priori. This time series method is directly applicable in the time lag optimization range, where point density per peak is constant. We present a systematic methodology to optimize the filters according to any desired figure of merit, illustrating the procedure by optimizing the signal-to-noise per unit bandwidth of matrix-assisted laser desorption/ionization (MALDI) data. We also introduce a nonlinear filter that reduces the spurious structure that often accompanies deconvolution filters. The net result of the application of these filters is that we can identify new structures in dense MALDI-TOF data, clearly showing small adducts to heavy biomolecules.

Resampling and deconvolution of linear time-of-flight records for enhanced protein profiling.

We have developed a peak deconvolution strategy that is applicable to the full mass range of a time-of-flight (TOF) spectrum. This strategy involves resampling a spectrum to create a time series that has equal peak widths (in time) across the entire spectrum, and then using the deconvolution filters we have previously described. We use this technique to deconvolve the protein mass spectra for blood serum and cell lysates acquired on three separate TOF instruments. Following deconvolution, we resolve spectral structures consistent with expected events such as multiply charged ions, matrix adducts and post-translational protein modifications. The deconvolution procedure produces a 40% improvement in the resolution and enhanced experimental sensitivity over the full length of the linear TOF record, up to m/z 150 000. This approach is particularly appropriate for automated data analysis and peak detection in dense TOF spectra.

Enhancement of sensitivity and resolution of surface-enhanced laser desorption/ionization time-of-flight mass spectrometric records for serum peptides using time-series analysis techniques.

BACKGROUND: Measurement of peptide/protein concentrations in biological samples for biomarker discovery commonly uses high-sensitivity mass spectrometers with a surface-processing procedure to concentrate the important peptides. These time-of-flight (TOF) instruments typically have low mass resolution and considerable electronic noise associated with their detectors. The net result is unnecessary overlapping of peaks, apparent mass jitter, and difficulty in distinguishing mass peaks from background noise. Many of these effects can be reduced by processing the signal using standard time-series background subtraction, calibration, and filtering techniques. METHODS: Surface-enhanced laser desorption/ionization (SELDI) spectra were acquired on a PBS II instrument from blank, hydrophobic, and IMAC-Cu ProteinChip arrays (Ciphergen Biosystems, Inc.) incubated with calibration peptide mixtures or pooled serum. TOF data were recorded after single and multiple laser shots at different positions. Correlative analysis was used for time-series calibration. Target filters were used to suppress noise and enhance resolution after baseline removal and noise rescaling. RESULTS: The developed algorithms compensated for the electronic noise attributable to detector overload, removed the baseline caused by charge accumulation, detected and corrected mass peak jitter, enhanced signal amplitude at higher masses, and improved the resolution by using a deconvolution filter. CONCLUSIONS: These time-series techniques, when applied to SELDI-TOF data before any peak identification procedure, can improve the data to make the peak identification process simpler and more robust. These improvements may be applicable to most TOF instrumentation that uses analog (rather than counting) detectors.

Theory of wave propagation along a waveguide filled with moving magnetized plasma.

Making use of the transformation of constitutive relations for electromagnetic waves and the transformation of the wave vector in Minkowski space, we have worked out the theory of wave propagation along a waveguide filled with moving magnetized plasma (MMPW). The dispersion equations of the wave propagation in a circular MMPW are given in this paper, along with a detailed discussion of their behaviors. Numerical calculations show that there are many interesting and important features of the wave propagation along an MMPW compared with that in a stationary magnetized plasma-filled waveguide (MPW).