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An improved sample preparation method for the sensitive detection of peptides by MALDI‐MS
Authors:Yusaku Hioki  Hiroki Kuyama  Chikako Hamana  Kohei Takeyama  Koichi Tanaka
Institution:Koichi Tanaka Laboratory of Advanced Science and Technology (KTLAST), Shimadzu Corporation, , Kyoto, 604‐8511 Japan
Abstract:We describe here an optimization study of the sample preparation conditions for sensitive detection of peptides by matrix‐assisted laser desorption/ionization mass spectrometry (MALDI‐MS). Among many factors in the conditions, we varied the percent acetonitrile in the peptide solution, the percent acetonitrile in the matrix solution and the α‐cyano‐4‐hydroxycinnamic acid (CHCA) concentration in the matrix solution. CHCA was chosen because it is the most frequently used matrix for analyzing peptides. The well‐established dried‐droplet method was employed for sample deposition. The examined range of the concentration of CHCA was from 0.01 to 10 mg/ml, and the MeCN content of the solvent for matrix/analyte was 10% to 50%. The indicator for the detection sensitivity was the S/N ratio of the peaks of peptides used. Highly increased sensitivity (100‐ to 1000‐fold) was observed for the optimal CHCA concentration of 0.1 mg/ml in 20% MeCN/0.1% aq. trifluoroacetic acid (TFA), as compared with the conventional concentration (10 mg/ml) in 50% MeCN/0.1% aq. TFA. For example, the limit of detection of human ACTH 18–39 was 10 amol/well for the optimal condition but 10 fmol/well for the conventional condition. The optimal condition (0.1 mg/ml CHCA in 20% MeCN/0.1% aq. TFA) was verified with five model peptides and provided significant improvement in sensitivity (by two to three orders of magnitude) compared with the conventional conditions. Optimizing the CHCA concentration and solvent composition significantly improved the detection sensitivity in the analysis of peptides by MALDI‐MS. Copyright © 2013 John Wiley & Sons, Ltd.
Keywords:MALDI mass spectrometry  sensitivity  peptide analysis  matrix concentration  acetonitrile content
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