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Kato K, Mukawa Y, Uemura S, Okayama M, Kadota Z, Hosozawa C, Kumamoto S, Furuta S, Iwaoka M, Araki T, Yamaguchi H. A protein identification method for proteomics using amino acid composition analysis with IoT-based remote control. Anal Biochem 2022; 657:114904. [PMID: 36152875 DOI: 10.1016/j.ab.2022.114904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 09/11/2022] [Accepted: 09/13/2022] [Indexed: 11/27/2022]
Abstract
In the present study, we developed a protein identification method using low-cost and easy-to-operate amino acid composition analysis. The identification program automatically compares the quantitative result for each amino acid concentration obtained from the amino acid analysis to the amino acid composition data retrieved from the UniProt protein database. We found that the accuracy of protein identification using amino acid composition analysis was comparable to that of mass spectrometry analysis. The method was able to distinguish and identify differences in amino acid substitutions of several residues between proteins with high sequence homology. The identification accuracy of proteins was also improved by correcting the concentrations in the program for Cys, Trp, and Ile residues, which cannot be quantified by general sample preparation for amino acid analysis. Moreover, the amino acid analyzer was remotely controlled in accordance with the growing demand for remote work. The measured amino acid data were automatically uploaded to the IoT portal within a few minutes of each measurement, allowing researchers to download data and analyze them using the identification program anywhere and at any time by connecting to a network. The results indicated that the present method is useful for protein identification.
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Affiliation(s)
- Kazuyuki Kato
- Hitachi High-Tech Fielding Corporation, 1-17-1 Toranomon, Minato-ku, Tokyo, 105-6410, Japan
| | - Yasutake Mukawa
- Hitachi High-Tech Fielding Corporation, 1-17-1 Toranomon, Minato-ku, Tokyo, 105-6410, Japan
| | - Shoichi Uemura
- Hitachi High-Tech Corporation, 1-17-1 Toranomon, Minato-ku, Tokyo, 105-6409, Japan
| | - Masataka Okayama
- Hitachi High-Tech Corporation, 1-17-1 Toranomon, Minato-ku, Tokyo, 105-6409, Japan
| | - Zentaro Kadota
- Hitachi High-Tech Fielding Corporation, 1-17-1 Toranomon, Minato-ku, Tokyo, 105-6410, Japan
| | - Chika Hosozawa
- Graduate School of Agriculture, Tokai University, 9-1-1 Toroku, Higashi-ku, Kumamoto, Kumamoto, 862-8652, Japan
| | - Sayaka Kumamoto
- Graduate School of Agriculture, Tokai University, 9-1-1 Toroku, Higashi-ku, Kumamoto, Kumamoto, 862-8652, Japan
| | - Shun Furuta
- Graduate School of Agriculture, Tokai University, 9-1-1 Toroku, Higashi-ku, Kumamoto, Kumamoto, 862-8652, Japan
| | - Michio Iwaoka
- Department of Chemistry, School of Science, Tokai University, 4-1-1 Kitakaname, Hiratsuka, Kanagawa, 259-1292, Japan; Institute of Advanced Biosciences, Tokai University, 4-1-1 Kitakaname, Hiratsuka, Kanagawa, 259-1292, Japan
| | - Tomohiro Araki
- Graduate School of Agriculture, Tokai University, 9-1-1 Toroku, Higashi-ku, Kumamoto, Kumamoto, 862-8652, Japan; Research Institute of Agriculture, Tokai University, 9-1-1 Toroku, Higashi-ku, Kumamoto, Kumamoto, 862-8652, Japan
| | - Hiroshi Yamaguchi
- Graduate School of Agriculture, Tokai University, 9-1-1 Toroku, Higashi-ku, Kumamoto, Kumamoto, 862-8652, Japan; Department of Food and Life Science, School of Agriculture, Tokai University, 9-1-1 Toroku, Higashi-ku, Kumamoto, Kumamoto, 862-8652, Japan.
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