Development of a Highly Sensitive Absolute Determination Method for Ultra-Trace Proteins Adsorbed on Medical Materials

2022 Fiscal Year Final Research Report

• Project/Area Number: 18K05196
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 34020:Analytical chemistry-related
• Research Institution: National Institute of Advanced Industrial Science and Technology
• Principal Investigator: Kato Megumi 国立研究開発法人産業技術総合研究所, 計量標準総合センター, 研究グループ長 (10415656)
• Co-Investigator(Kenkyū-buntansha): 柿木 佐知朗 関西大学, 化学生命工学部, 教授 (70421419)
• Project Period (FY): 2018-04-01 – 2023-03-31
• Keywords: タンパク質 / 吸着 / 定量 / アミノ酸分析

Outline of Final Research Achievements

In this study, in order to develop a highly sensitive and accurate determination method for the ultra-trace amount of proteins adsorbed on medical materials, we have conducted "Improvement of amino acid analysis using isotope dilution mass spectrometry (IDMS-AAA method) ", "Optimization of immobilization method of hydrophilic polymer fixed interface, which is one of versatile protein adsorption inhibitory interfaces", and "Development of an evaluation system suitable for quantifying the ultra-trace amount of adsorbed proteins". When a model protein was adsorbed on the hydrophilic polymer-immobilized cover glass, it was found that the trace amount of adsorbed protein could be quantified almost in the expected order, but there were issues with quantitative properties including absolute value and reproducibility. We plan to continue our research and development by improving the immobilization method and evaluation system protocols.

Free Research Field

分析化学

Academic Significance and Societal Importance of the Research Achievements

人工心臓や人工関節等の医療デバイスへのタンパク質成分の吸着は、移植後の感染、炎症などの引き金となると考えられており、タンパク質吸着抑制は医用材料開発における重要な課題の一つである。一方、従来の定量法では医用材料に吸着する超微量なタンパク質を高感度かつ正確に定量することが出来なかった。本研究では同位体希釈質量分析を利用したアミノ酸分析法を改良し、医用材料に吸着した超微量タンパク質の高感度・高精度な絶対定量を試みた。モデルタンパク質と独自の評価系を用いて定量を行ったところ、ほぼ期待通りのオーダーで定量可能であることが分かったが、定量性に課題があることから、引き続き改良に取り組む。