Scrambled Internal Standard Method for High-Throughput Protein Quantification by Matrix-Assisted Laser Desorption Ionization Tandem Mass Spectrometry.
Toshihiro YoneyamaSumio OhtsukiMasanori TachikawaYasuo UchidaTetsuya TerasakiPublished in: Journal of proteome research (2017)
Matrix-assisted laser desorption ionization (MALDI) could be advantageous for high-throughput MS acquisition but suffers from low signal reproducibility. The purpose of this study was to establish a reliable MALDI-tandem mass spectrometry (MS/MS)-based high-throughput quantification of tryptic peptides using our newly developed scrambled internal standard (sIS) method. The standard curves obtained with sIS peptides showed good linearity over a wide concentration range (5-1000 fmol/μL) compared to that with the IS-free method, and the coefficient of variation of data points at each concentration (5-1000 fmol/μL) was significantly reduced. Furthermore, the ion suppression effect of digested serum could be normalized with the sIS peptides. Differences of quantitative values obtained by MALDI-MS/MS and liquid chromatography-MS/MS with selected reaction monitoring were within 20% in the presence of 0.1-5 μL of immunoprecipitated model plasma. Furthermore, the effect of amino acid composition on peptide sensitivity was examined, and we found that sensitivity was significantly decreased if an aromatic amino acid was replaced with a nonaromatic amino acid. Thus, high sensitivity required the use of sIS peptides containing an aromatic amino acid. Finally, the sIS method enabled high-throughput quantification of tryptic peptides with high accuracy and a wide dynamic range.
Keyphrases
- amino acid
- high throughput
- tandem mass spectrometry
- liquid chromatography
- mass spectrometry
- ultra high performance liquid chromatography
- ms ms
- high performance liquid chromatography
- gas chromatography
- high resolution mass spectrometry
- simultaneous determination
- high resolution
- solid phase extraction
- liquid chromatography tandem mass spectrometry
- single cell
- multiple sclerosis
- electronic health record
- risk assessment
- magnetic resonance
- artificial intelligence