Many studies have shown that biological fluids contain an important number of biomarkers associated with various pathologies. For instance, there has been extensive research to identify effective biomarkers as prognostic indicators of breast cancer [1]. An effective approach for biomarker discovery is to utilize affinity-based mass spectrometry to separate proteins based on their intrinsic properties [2] using Surface Enhanced Laser Desorption/Ionization Time of Flight Mass Spectrometry (SELDI-TOF MS), where the surface of arrays attract proteins based on their affinity to chemical (hydrophobic, anionic, normal-phase, weak cation exchange, etc.) or biochemical (antibodies, enzymes, etc.) entities. Biomarkers can be discovered by comparing protein profiles for control and experimental samples to elucidate statistically significant differences in protein expression. However, the subsequent separation and identification these protein biomarkers remains a challenge.

A recent study has focused on the identification of biomarkers regarding fish species that could serve as surrogates for environmental and human health comparative studies [3]. In this work, two fish species were treated with estrogen and their plasma proteins examined for biomarkers using SEDLI-TOF-MS. The analysis revealed 13 biomarkers in a mass range of 2950 to 13000 Daltons, however, they were only able to identify one of the biomarker proteins (at 3027 Da). Some of the complications associated with the identification of these biomarkers are: (1) there exists limited sequence information for the species being studied (thus requiring de novo analysis), (2) the proteins are large in size and therefore might not fragment well using collision-induced dissocation (CID), and (3) these biomarkers must be separated from the other plasma proteins and detected in the mass spectrometer.

In this work, we present the experimental and computational techniques used to identify these protein biomarkers. Several methods for sample cleanup were applied to the plasma proteins to recover the greatest fraction of target peptides. These samples were analyzed using OrbiTrap mass spectrometry to obtain the highest accuracy data. The biomarker proteins present in the fractionated samples were analyzed in a top-down fashion, where we performed MS-N framentations using collision-induced dissociation (CID) [4] and electron-transfer dissociation (ETD) [5,6]. We present the results using both methods and highlight how these techniques can be used in a complementary fashion.

[1] Laronga C, Becker S, Watson P, Gregory B, Cazares L, Lynch H, Perry RR, Wright GL, Drake RR, Semmes OJ. SELDI-TOP serum profiling for prognostic and diagnostic classification of breast cancers. Disease Markers. 19: 229-238, 2003.

[2] Miguet L, Bogumil R, Decloquement P, Herbrecht R, Potier N, Mauvieux L, Dorsselaer AV. Discovery and identification of potential biomarkers in a prospective study of chronic lymphoid malignancies using SELDI-TOF MS. J. Proteome Res. 5: 2258-2269, 2006.

[3] Walker CC, Salinas KA, Harris PS, Wilkinson SS, Watts JD, and Hemmer MJ. A proteomic (SELDI-TOF-MS) approach to estrogen agonist screening. Toxicological Sci., 95(1):74-81, 2007.

[4] Macek B, Waanders LF, Olsen JV, and Mann M. Top-down protein sequencing and MS3 on a hybrid linear quadrupole ion trap-orbitrap mass spectrometer. Mol. Cell Proteomics, 5:949-958, 2006.

[5] Syka JEP, Coon JJ, Schroeder MJ, Shabanowitz J, Hunt DF. Peptide and protein sequence analysis by electron transfer dissociation mass spectrometry. Proc. Nat. Acad. Sci. 101(26):9528-9533, 2004.

[6] Mikesh LM, Ueberheide B, Chi A, Coon JJ, Syka JEP, Shabanowitz J, Hunt DF. The utility of ETD mass spectrometry in proteomic analysis. Biochimica. et Biophysica Acta. 1764:1811-1822, 2006.