(a) MALDI-TOF peptide profile obtained from human serum after sample workup using RPC18-functionalized magnetic beads. (b) Observed isotopic distributions of five peptides chosen for alignment of all serum peptide profiles. The horizontal lines at the top of the peaks represent the calculated values of the corresponding polyaveragine peptides. (c) Profile processing results in a QC value for each individual mass spectrum. First, the intensity of each isotope peak is determined using Xtractor. Then, after normalization, the observed intensities are compared with those estimated from the polyaveragine peptide. For a more accurate determination of the deviation, the random noise variance is taken into account. Finally, the sum of thus obtained deviations for all considered peptides represents the QC value of the MALDI-TOF peptide profile in (a). 

(a) MALDI-TOF peptide profile obtained from human serum after sample workup using RPC18-functionalized magnetic beads. (b) Observed isotopic distributions of five peptides chosen for alignment of all serum peptide profiles. The horizontal lines at the top of the peaks represent the calculated values of the corresponding polyaveragine peptides. (c) Profile processing results in a QC value for each individual mass spectrum. First, the intensity of each isotope peak is determined using Xtractor. Then, after normalization, the observed intensities are compared with those estimated from the polyaveragine peptide. For a more accurate determination of the deviation, the random noise variance is taken into account. Finally, the sum of thus obtained deviations for all considered peptides represents the QC value of the MALDI-TOF peptide profile in (a). 

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In this study, we have implemented a new quality control (QC) parameter for peptide profiling based on isotopic distributions. This QC parameter is an objective measure and facilitates automatic sorting of large numbers of peptide spectra. Peptides in human serum samples were enriched using reversed-phase C(18)-functionalized magnetic beads using a...

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... of the aims of this study was to demonstrate the use of peptide isotopic distri- butions of peptides for quality control parameter. For illustration, the isotopic patterns of the five ubiquitous peptides used for alignment are shown in Figure 2. While the selection of these five peptides was an arbitrary process, no software is available that yields a better result without the need of user-defined input parameters. ...
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... is sufficient for the estimation of isotopic distribution of unknown peptides since we are not searching for the best fit, but only need to discriminate between peptide and non- peptide (e.g., polymer, matrix cluster) distributions. The estimated values of the five peptides are depicted in Figure 2. These are obtained by first transferring a peptide m/z value into a neutral mass (i.e., [m/z value- proton-water]), then dividing this number by the exact mass of averagine (i.e., 111.0543 ...
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... to rounding of the indices, the m/z values of the observed peptide and the corresponding polyaveragine are not identical. It is clear from Figure 2 that the isotopic patterns of the five peptides used for alignment were in good agreement with the polyaver- agine distributions. A quantitative evaluation of these isotope distributions will be given in the next section. ...
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... intensities of the observed peaks in each peptide isotope distribution were determined using Xtractor (see the Materials and Methods section). As an example, for the peptide at m/z 1865.22 the intensity of the monoisotopic was determined as the sum of all mea- sured values at m/z 1865.22 0.49, the intensity of the second isotope was determined as the sum of all measured values at m/z 1866.22 0.49, and so forth (Figure 2). The window of 0.49 Da was chosen to ensure total quantification of each isotope. ...
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... and false-negative results. For a quantita- tive analysis, the normalized intensities estimated from the polyaveragine peptides, the average ratios of the isotopic distributions and their coefficients of variation were evaluated for the five peptides discussed earlier (see Figure 2) and the results are summarized in Table 1. In this evaluation, the 50 MALDI-TOF and the 50 MALDI-FTICR mass spectra with lowest QC values were selected from the results obtained from 192 pep- tide profiles in Figure 5. ...

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... One of the advantages of using ultrahigh-resolution MS is that measurements at isotopic resolution provide more spectra information compared to broad-peak detection in linear mode MALDI-TOF MS. Previously, we showed that the goodness of the observed isotopic distributions can be used as a quality control parameter for the selection of high-quality spectra generated from the analysis of a large cohort of samples (Nicolardi et al., 2010). This concept was then implemented in a more powerful software-namely, MassyTools-developed for the high-throughput processing of MALDI mass spectra (Jansen et al., 2015). ...
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... 39 Deviations from the theoretical isotopic distribution may be indicative of deviations in the elemental composition or the presence of overlapping ion species. 40 Fourier transform ion cyclotron resonance (FT-ICR) MS provides higher resolving power than TOF MS. 41 FT-ICR MS measurements of cesium iodide clusters [Cs(CsI) n ] + , up to about m/z 32,000, have been previously reported. 42,43 Ultrahigh-resolution MALDI FT-ICR MS has been used to analyze biomolecules at an isotopic resolution up to about m/z 24,000 44−47 and characterize complex biomolecules such as monoclonal antibodies. ...
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... The molecular isotopic distribution measured by mass spectrometry contains elemental composition, facilitating molecular composition determination [28]. It has been demonstrated that the quality of peptide profiling can be improved by the comparison between the measured isotope patterns and the calculated ones [29]. In Fig (4B-4E), we compared the observed isotopic patterns of molecules to the theoretical ones calculated by the IsotopePattern software. ...
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... In MALDI-TOF MS profiling, the major noise source is a chemical noise that originates mainly from the matrix and its cluster-derived signals. Baseline estimation and subtraction are based either on nonparametric heuristic methods or on algorithm approaches using top hat filter [27,89,90,94,96], local regression (LOESS) [91], asymmetric least squares algorithm, convex hull baseline [97,98], statisticssensitive non-linear iterative peak-clipping (SNIP) [99], and waveletbased method [100]. As systematic time shifts may be observed for separate MALDI-TOF MS measurements, recalibration of spectra is necessary. ...
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... For MALDI-TOF-MS TPNG glycan data, a window of m/z ±20 showed optimal results when comparing m/z ranges of ±50, 45,40,35,30,25,20,15,10,6, and 1 (data not shown). The difference in the optimum is likely due to the difference in sample complexity (TPNG contains far more signals than mAb1 spectra), and an m/z range of 20 for background determination is currently the default value for this definable setting. ...