chemical cytometry
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ACS Nano ◽  
2021 ◽  
Author(s):  
Soo-Yeon Cho ◽  
Volodymyr B. Koman ◽  
Xun Gong ◽  
Sun Jin Moon ◽  
Pavlo Gordiichuk ◽  
...  

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Soo-Yeon Cho ◽  
Xun Gong ◽  
Volodymyr B. Koman ◽  
Matthias Kuehne ◽  
Sun Jin Moon ◽  
...  

AbstractNanosensors have proven to be powerful tools to monitor single cells, achieving spatiotemporal precision even at molecular level. However, there has not been way of extending this approach to statistically relevant numbers of living cells. Herein, we design and fabricate nanosensor array in microfluidics that addresses this limitation, creating a Nanosensor Chemical Cytometry (NCC). nIR fluorescent carbon nanotube array is integrated along microfluidic channel through which flowing cells is guided. We can utilize the flowing cell itself as highly informative Gaussian lenses projecting nIR profiles and extract rich information. This unique biophotonic waveguide allows for quantified cross-correlation of biomolecular information with various physical properties and creates label-free chemical cytometer for cellular heterogeneity measurement. As an example, the NCC can profile the immune heterogeneities of human monocyte populations at attomolar sensitivity in completely non-destructive and real-time manner with rate of ~600 cells/hr, highest range demonstrated to date for state-of-the-art chemical cytometry.


2020 ◽  
Author(s):  
Soo-Yeon Cho ◽  
Xun Gong ◽  
Volodymyr Koman ◽  
Matthias Kuehne ◽  
Sun Jin Moon ◽  
...  

Abstract Nanosensor have proven to be powerful tools to monitor single biological cells and organisms, achieving spatial and temporal precision even at the single molecule level. However, there has not been a way of extending this approach to statistically relevant numbers of living cells and organisms. Herein, we design and fabricate a high throughput nanosensor array in a microfluidic channel that addresses this limitation, creating a Nanosensor Chemical Cytometry (NCC). An array of nIR fluorescent single walled carbon nanotube (SWNT) nanosensors is integrated along a microfluidic channel through which a population of flowing cells is guided. We show that one can utilize the flowing cell itself as highly informative Gaussian lenses projecting nIR emission profiles and extract rich information on a per cell basis at high throughput. This unique biophotonic waveguide allows for quantified cross-correlation of the biomolecular information with physical properties such as cellular diameter, refractive index (RI), and eccentricity and creates a label-free chemical cytometer for the measurement of cellular heterogeneity with unprecedented precision. As an example, the NCC can profile the immune response heterogeneities of distinct human monocyte populations at attomolar (10-18 moles) sensitivity in a completely non-destructive and real-time manner with a rate of ~100 cells/frame, highest range demonstrated to date for state of the art chemical cytometry. We demonstrate distinct H2O2 efflux heterogeneities between 330 and 624 attomole/cell·min with cell projected areas between 271 and 263 µm2, eccentricity values between 0.405 and 0.363 and RI values between 1.383 and 1.377 for non-activated and activated human monocytes, respectively. Hence, we show that our nanotechnology based biophotonic cytometer has significant potential and versatility to answer important questions and provide new insight in immunology, cell manufacturing and biopharmaceutical research.


2018 ◽  
Vol 13 (7) ◽  
pp. 1741-1751 ◽  
Author(s):  
Brianna M. Vickerman ◽  
Matthew M. Anttila ◽  
Brae V. Petersen ◽  
Nancy L. Allbritton ◽  
David S. Lawrence

The Analyst ◽  
2018 ◽  
Vol 143 (15) ◽  
pp. 3643-3650 ◽  
Author(s):  
Kathy Rodogiannis ◽  
Jessica T. Duong ◽  
Michelle L. Kovarik

Microfluidic chemical cytometry is a powerful technique for examining chemical contents of individual cells. Here, it is applied to study unicellular organisms for the first time.


2017 ◽  
Vol 1523 ◽  
pp. 97-106 ◽  
Author(s):  
Angela Proctor ◽  
Christopher E. Sims ◽  
Nancy L. Allbritton

2016 ◽  
Vol 128 (42) ◽  
pp. 13289-13292 ◽  
Author(s):  
Emilie R. Mainz ◽  
Qunzhao Wang ◽  
David S. Lawrence ◽  
Nancy L. Allbritton

2016 ◽  
Vol 55 (42) ◽  
pp. 13095-13098 ◽  
Author(s):  
Emilie R. Mainz ◽  
Qunzhao Wang ◽  
David S. Lawrence ◽  
Nancy L. Allbritton

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