A Microfluidic Sensing System with a Multichannel Surface Plasmon Resonance Chip: Damage-free Characterization of Cells by Pattern Recognition

Author(s):  
Hiroka Sugai ◽  
Shunsuke Tomita ◽  
Sayaka Ishihara ◽  
Kyoko Yoshioka ◽  
Ryoji Kurita

<p>The development of a versatile sensing strategy for the damage-free characterization of cultured cells is of great importance for both fundamental biological research and industrial applications. Here, we present a pattern-recognition-based cell-sensing approach using a multichannel surface plasmon resonance (SPR) chip. The chip, in which five cysteine derivatives with different structures are immobilized on Au films, is capable of generating five unique SPR sensorgrams for the cell-secreted molecules that are contained in cell culture media. An automatic statistical program was built to acquire kinetic parameters from the SPR sensorgrams and to select optimal parameters as “pattern information” for subsequent multivariate analysis. Our system rapidly (~ 10 min) provides the complex information by merely depositing a small amount of cell culture media (~ 25 µL) onto the chip, and the amount of information obtained is comparable to that furnished by a combination of conventional laborious biochemical assays. This non-invasive pattern-recognition-based cell-sensing approach could potentially be employed as a versatile tool for characterizing cells. </p>

2020 ◽  
Author(s):  
Hiroka Sugai ◽  
Shunsuke Tomita ◽  
Sayaka Ishihara ◽  
Kyoko Yoshioka ◽  
Ryoji Kurita

<p>The development of a versatile sensing strategy for the damage-free characterization of cultured cells is of great importance for both fundamental biological research and industrial applications. Here, we present a pattern-recognition-based cell-sensing approach using a multichannel surface plasmon resonance (SPR) chip. The chip, in which five cysteine derivatives with different structures are immobilized on Au films, is capable of generating five unique SPR sensorgrams for the cell-secreted molecules that are contained in cell culture media. An automatic statistical program was built to acquire kinetic parameters from the SPR sensorgrams and to select optimal parameters as “pattern information” for subsequent multivariate analysis. Our system rapidly (~ 10 min) provides the complex information by merely depositing a small amount of cell culture media (~ 25 µL) onto the chip, and the amount of information obtained is comparable to that furnished by a combination of conventional laborious biochemical assays. This non-invasive pattern-recognition-based cell-sensing approach could potentially be employed as a versatile tool for characterizing cells. </p>


2020 ◽  
Vol 92 (22) ◽  
pp. 14939-14946
Author(s):  
Hiroka Sugai ◽  
Shunsuke Tomita ◽  
Sayaka Ishihara ◽  
Kyoko Yoshioka ◽  
Ryoji Kurita

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