Dominique de Costa

Publications (3)9.54 Total impact

• Article: Mass spectrometry analyses of κ and λ fractions result in increased number of complementarity-determining region identifications.

  Ingrid Broodman, Dominique de Costa, Christoph Stingl, Lennard J M Dekker, Martijn M VanDuijn, Jan Lindemans, Rob J van Klaveren, Theo M Luider
  [show abstract] [hide abstract]
  ABSTRACT: Sera from lung cancer patients contain antibodies against tumor-associated antigens. Specific amino acid sequences of the complementarity-determining regions (CDRs) in the antigen-binding fragment (Fab) of these antibodies have potential as lung cancer biomarkers. Detection and identification of CDRs by mass spectrometry can significantly be improved by reduction of the complexity of the immunoglobulin molecule. Our aim was to molecular dissect IgG into κ and λ fragments to reduce the complexity and thereby identify substantially more CDRs than by just total Fab isolation. We purified Fab, Fab-κ, Fab-λ, κ and λ light chains from serum from 10 stage I lung adenocarcinoma patients and 10 matched controls from the current and former smokers. After purification, the immunoglobulin fragments were enzymatically digested and measured by high-resolution mass spectrometry. Finally, we compared the number of CDRs identified in these immunoglobulin fragments with that in the Fab fragments. Twice as many CDRs were identified when Fab-κ, Fab-λ, κ and λ (3330) were combined than in the Fab fraction (1663) alone. The number of CDRs and κ:λ ratio was statistically similar in both cases and controls. Molecular dissection of IgG identifies significantly more CDRs, which increases the likelihood of finding lung cancer-related CDR sequences.
  Proteomics 11/2011; 12(2):183-91. · 4.43 Impact Factor
• Source

  Available from: Mark K Titulaer

  Article: Label-free peptide profiling of Orbitrap™ full mass spectra.

  Mark K Titulaer, Dominique de Costa, Christoph Stingl, Lennard J Dekker, Peter Ae Sillevis Smitt, Theo M Luider
  [show abstract] [hide abstract]
  ABSTRACT: We developed a new version of the open source software package Peptrix that can yet compare large numbers of Orbitrap™ LC-MS data. The peptide profiling results for Peptrix on MS1 spectra were compared with those obtained from a small selection of open source and commercial software packages: msInspect, Sieve™ and Progenesis™. The properties compared in these packages were speed, total number of detected masses, redundancy of masses, reproducibility in numbers and CV of intensity, overlap of masses, and differences in peptide peak intensities. Reproducibility measurements were taken for the different MS1 software applications by measuring in triplicate a complex peptide mixture of immunoglobulin on the Orbitrap™ mass spectrometer. Values of peptide masses detected from the high intensity peaks of the MS1 spectra by peptide profiling were verified with values of the MS2 fragmented and sequenced masses that resulted in protein identifications with a significant score. Peptrix finds about the same number of peptide features as the other packages, but peptide masses are in some cases approximately 5 to 10 times less redundant present in the peptide profile matrix. The Peptrix profile matrix displays the largest overlap when comparing the number of masses in a pair between two software applications. The overlap of peptide masses between software packages of low intensity peaks in the spectra is remarkably low with about 50% of the detected masses in the individual packages. Peptrix does not differ from the other packages in detecting 96% of the masses that relate to highly abundant sequenced proteins. MS1 peak intensities vary between the applications in a non linear way as they are not processed using the same method. Peptrix is capable of peptide profiling using Orbitrap™ files and finding differential expressed peptides in body fluid and tissue samples. The number of peptide masses detected in Orbitrap™ files can be increased by using more MS1 peptide profiling applications, including Peptrix, since it appears from the comparison of Peptrix with the other applications that all software packages have likely a high false negative rate of low intensity peptide peaks (missing peptides).
  BMC Research Notes 01/2011; 4:21.
• Article: Sequencing and quantifying IgG fragments and antigen-binding regions by mass spectrometry.

  Dominique de Costa, Ingrid Broodman, Martijn M Vanduijn, Christoph Stingl, Lennard J M Dekker, Peter C Burgers, Henk C Hoogsteden, Peter A E Sillevis Smitt, Rob J van Klaveren, Theo M Luider
  [show abstract] [hide abstract]
  ABSTRACT: In cancer and autoimmune diseases, immunoglobulins with a specific molecular signature that could potentially be used as diagnostic or prognostic markers are released into body fluids. An immunomics approach based on this phenomenon relies on the ability to identify the specific amino acid sequences of the complementarity-determining regions (CDR) of these immunoglobulins, which in turn depends on the level of accuracy, resolution, and sensitivity that can be achieved by advanced mass spectrometry. Reproducible isolation and sequencing of antibody fragments (e.g., Fab) by high-resolution mass spectrometry (MS) from seven healthy donors revealed 43 217 MS signals: 225 could be associated with CDR1 peptides, 513 with CDR2 peptides, and 19 with CDR3 peptides. Seventeen percent of the 43 217 MS signals did not overlap between the seven donors. The Fab isolation method used is reproducible and fast, with a high yield. It provides only one Fab sample fraction for subsequent characterization by high-resolution MS. In 17% and 4% of these seven healthy donors, qualitative (presence/absence) and quantitative (intensity) differences in Fab fragments could be demonstrated, respectively. From these results, we conclude that the identification of a CDR signature as biomarker for autoimmune diseases and cancer without prior knowledge of the antigen is feasible.
  Journal of Proteome Research 04/2010; 9(6):2937-45. · 5.11 Impact Factor