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Evaluation of matrix‐assisted laser desorption/ionization‐time of flight mass spectrometry proteomic profiling: identification of alpha 2‐HS glycoprotein B‐chain as a biomarker of diet
Author(s) -
Mitchell Breeana L.,
Yasui Yutaka,
Lampe Johanna W.,
Gafken Philip R.,
Lampe Paul D.
Publication year - 2005
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200401099
Subject(s) - matrix assisted laser desorption/ionization , mass spectrometry , proteomics , time of flight mass spectrometry , biomarker , chemistry , biomarker discovery , chromatography , computational biology , bioinformatics , biology , biochemistry , desorption , ionization , ion , organic chemistry , adsorption , gene
Biomarkers have the potential to impact a wide range of public health concerns, including early detection of diseases, drug discovery, and improved accuracy of monitoring effects of interventions. Given new technological developments, broad‐based screening approaches will likely advance biomarker discovery at an accelerated pace. Matrix‐assisted laser desorption/ionization‐time of flight mass spectrometry (MALDI‐TOF MS) allows for the elucidation of individual protein masses from a complex mixture with high throughput. We have developed a method for identifying serum biomarkers using MALDI‐TOF and statistical analysis. However, before applying this approach to screening of complex diseases, we evaluated the approach in a controlled dietary intervention study. In this study, MALDI‐TOF spectra were generated using samples from a randomized controlled trial. During separate feeding periods, 38 participants ate a basal diet devoid of fruits and vegetables and a basal diet supplemented with cruciferous (broccoli) family vegetables. Serum samples were obtained at the end of each 7‐day feeding period and treated to remove large, abundant proteins. MALDI‐TOF spectra were analyzed using peak picking algorithms and logistic regression models. Our bioinformatics methods identified two significant peaks at m / z values of 2740 and 1847 that could classify participants based on diet (basal vs. cruciferous) with 76% accuracy. The 2740 m / z peak was identified as the B‐chain of alpha 2‐HS glycoprotein, a serum protein previously found to vary with diet and be involved in insulin resistance and immune function.