A Self-Driven Microfluidic Chip for Ricin and Abrin Detection
<p>Illustration of the overall experimental strategy. (<b>a</b>) The principle of NC membrane action in conventional immunochromatographic test strips. Only the surface signal of the membrane can be measured. (<b>b</b>) A microfluidic chip based on nanoforest structure was designed for the detection of AT and RT. (<b>c</b>) Progress of the sample reaction. (<b>d</b>) The fluorescence signal value can be read after 15 min.</p> "> Figure 2
<p>Illustration of the preparation for nanoforest structure: (<b>a</b>) process of spin-coating polyimide photoresist; (<b>b</b>) O<sub>2</sub> plasma treatment for nanowire forests; (<b>c</b>) Ar plasma treatment for nanowire forests; (<b>d</b>) process of SiO<sub>2</sub> coating by PECVD; (<b>e</b>–<b>h</b>) SEM images of the PI layer, nanofiber forests, nanowire forests, and nanoforests.</p> "> Figure 3
<p>The principle of the saturated fluorescence experiments: (<b>a</b>,<b>b</b>) Scheme of the surface modification process for the chip. (<b>c</b>) The modified nanoforest structure with rabbit antibody added. (<b>d</b>) The antibody combined with the sheep anti-rabbit antibody labeled by AbFluor 680 or AbFluor 488.</p> "> Figure 4
<p>Design of microfluidic sensor based on the nanoforest structure. (<b>a</b>) Sample pad. (<b>b</b>) Conjugate pad. (<b>c</b>) Detection area containing the corresponding capture antibody with nanoforest. (<b>d</b>) Absorbent pad. (<b>e</b>) The backing plate.</p> "> Figure 5
<p>SEM photographs of nanoforest structures (1,2 are the same nanoforest at a different angle). (<b>A<sup>1</sup></b>) 2 μm, 45°. (<b>A<sup>2</sup></b>) 2 μm, 90°. (<b>B<sup>1</sup></b>) 5 μm, 45°. (<b>B<sup>2</sup></b>) 5 μm, 90°. (<b>C<sup>1</sup></b>) 10 μm, 45°. (<b>C<sup>2</sup></b>) 10 μm, 90°.</p> "> Figure 6
<p>Characterization of nanoforest structure. (<b>a</b>) Flow rate test of silicon nanoforest chip recorded in 1 s intervals. The flow speed of PBS was recorded by the distance traveled per second. (<b>b</b>) Reflectance for nanoforest structure on silicon substrate. (<b>c</b>) Scheme of the silicon nanoforest chip under fluorescence microscope: (1) silicon-based plane in 488 nm wavelength; (2) nanoforest structure in 488 nm wavelength; (3) silicon-based plane in 688 nm wavelength; (4) nanoforest structure in 688 nm wavelength.</p> "> Figure 7
<p>Physical assembly and flow process of the microfluidic chip sensors. (<b>a</b>,<b>d</b>) Sample pad. (<b>b</b>,<b>e</b>) Conjugate pad. (<b>c</b>,<b>f</b>) Detection area containing the corresponding capture antibody with nanoforest. (<b>g</b>) Speed-limiting membrane. (<b>h</b>) Absorbent pad.</p> "> Figure 8
<p>(<b>A</b>) Dose–response curve for the RT sample at different concentrations. The x-axis denotes the toxin concentration (pg/mL), and the y-axis denotes the fluorescence intensity at 700 nm. The red horizontal line represents the boundary between negative and positive. (<b>B</b>) Fluorescence response image at corresponding concentrations for RT. (<b>C</b>) Dose–response curve for the AT sample at different concentrations. (<b>D</b>) Fluorescence response image at corresponding concentrations for AT. (<b>E</b>) Detection of cross-reaction between RT and three other toxins. (<b>F</b>) Detection of cross-reaction between AT and three other toxins.</p> "> Figure 9
<p>Fluorescence detection curves of ricin and abrin in different food samples. (<b>A</b>) AT samples in juice. (<b>B</b>) AT samples in milk. (<b>C</b>) RT samples in juice. (<b>D</b>) RT samples in milk. The red horizontal line represents the boundary between negative and positive results.</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Preparation and Characterization of Nanoforest Structures
2.2. Surface Modification and Saturation Fluorescence Experiments on Silicon Nanoforest Structured Chips
2.3. Preparation of Microfluidic Chip Sensors
2.4. Microfluidic Chip Sensors Signal Measurement
3. Results and Discussions
3.1. Characterization of Nanoforest Structure Chip
3.2. Sensor Detection of Two Plant Toxins
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Photoresist Thickness (μm) | Density (Fibers/μm2) | Diameter (nm) | Height (μm) |
---|---|---|---|
2 | 10 | 100 | 0.2 |
5 | 15 | 50–100 | 1.8 |
10 | 20 | 200–400 | 5 |
Name | Detectable Toxin Agents | Sensitivity | Time | Cost of Equipment |
---|---|---|---|---|
ELISA | RT [38] | 0.093 ng/mL | 4–5 h | Expensive |
AT [39] | 1 ng/mL | |||
Immunochromatographic Test Strip | RT [40] | 0.5 ng/mL | 15 min | Cheap |
AT [41] | 3 ng/mL | |||
MALDI-TOF MS | RT [42] | 0.2 ng/mL | 3.5–7.5 h | Expensive |
AT [43] | 40 ng/mL | |||
Electrochemical Luminescence Method | RT [44] | 0.2 ng/mL | 5.5 h | Expensive |
AT [45] | 5 pg/mL | |||
This work | RT, AT | 10 pg/mL | 15 min | Cheap |
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Bai, X.; Hu, C.; Chen, L.; Wang, J.; Li, Y.; Wan, W.; Jin, Z.; Li, Y.; Xin, W.; Kang, L.; et al. A Self-Driven Microfluidic Chip for Ricin and Abrin Detection. Sensors 2022, 22, 3461. https://doi.org/10.3390/s22093461
Bai X, Hu C, Chen L, Wang J, Li Y, Wan W, Jin Z, Li Y, Xin W, Kang L, et al. A Self-Driven Microfluidic Chip for Ricin and Abrin Detection. Sensors. 2022; 22(9):3461. https://doi.org/10.3390/s22093461
Chicago/Turabian StyleBai, Xuexin, Chenyi Hu, Liang Chen, Jing Wang, Yanwei Li, Wei Wan, Zhiying Jin, Yue Li, Wenwen Xin, Lin Kang, and et al. 2022. "A Self-Driven Microfluidic Chip for Ricin and Abrin Detection" Sensors 22, no. 9: 3461. https://doi.org/10.3390/s22093461