研究目的
To develop a microfluidic device for the DXT method that controls microenvironments for KcsA channels, enabling the capture of conformational changes in response to chemical stimuli with improved signal-to-background ratio.
研究成果
The fabricated microfluidic device with SiN membrane windows and a photo-patternable adhesive material successfully reduces background noise, enabling the observation of diffraction spots from gold nanocrystals attached to KcsA channels. The optimal microchannel height for detectable diffraction spots is identified as 50 μm. This setup paves the way for future studies on conformational changes of KcsA channels in response to chemical stimuli.
研究不足
The study focuses on optimizing the microchannel height and adhesive material thickness for improved S/B ratio but does not extensively explore the effects of various chemical stimuli on KcsA channel conformational changes.
1：Experimental Design and Method Selection:
The study employs the DXT method to trace conformational changes of KcsA potassium ion channels by recording the position of a diffraction spot from a gold nanocrystal attached to the channel. A microfluidic device with SiN membrane windows bonded with a photo-patternable adhesive material is designed for high-resolution imaging under controlled microenvironments.
2：Sample Selection and Data Sources:
KcsA potassium ion channels are fixed on a chemically modified substrate surface inside the observation chamber.
3：List of Experimental Equipment and Materials:
The fabrication involves UV lithography, KOH etching, PECVD for SiO2 deposition, and a photo-patternable adhesive material for microchannel structuring. The device is evaluated at the synchrotron radiation facility (BL28B2, SPring-8).
4：8). Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: The fabrication process includes patterning SiN, releasing a SiN membrane, depositing SiO2, patterning the adhesive material, and bonding two SiN membrane windows. The device is assembled using a 3D-printed polymer holder.
5：Data Analysis Methods:
Background noise is evaluated by fitting multivariate normal distribution to images recorded with an X-ray camera.
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