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Open-source tool for real-time and automated analysis of droplet-based microfluidic.

Authors :
Neto, Joana P.
Mota, Ana
Lopes, Gonçalo
Coelho, Beatriz J.
Frazão, João
Moura, André T.
Oliveira, Beatriz
Sieira, Bárbara
Fernandes, José
Fortunato, Elvira
Martins, Rodrigo
Igreja, Rui
Baptista, Pedro V.
Águas, Hugo
Source :
Lab on a Chip. 7/21/2023, Vol. 23 Issue 14, p3238-3244. 7p.
Publication Year :
2023

Abstract

Droplet-based microfluidic technology is a powerful tool for generating large numbers of monodispersed nanoliter-sized droplets for ultra-high throughput screening of molecules or single cells. Yet further progress in the development of methods for the real-time detection and measurement of passing droplets is needed for achieving fully automated systems and ultimately scalability. Existing droplet monitoring technologies are either difficult to implement by non-experts or require complex experimentation setups. Moreover, commercially available monitoring equipment is expensive and therefore limited to a few laboratories worldwide. In this work, we validated for the first time an easy-to-use, open-source Bonsai visual programming language to accurately measure in real-time droplets generated in a microfluidic device. With this method, droplets are found and characterized from bright-field images with high processing speed. We used off-the-shelf components to achieve an optical system that allows sensitive image-based, label-free, and cost-effective monitoring. As a test of its use we present the results, in terms of droplet radius, circulation speed and production frequency, of our method and compared its performance with that of the widely-used ImageJ software. Moreover, we show that similar results are obtained regardless of the degree of expertise. Finally, our goal is to provide a robust, simple to integrate, and user-friendly tool for monitoring droplets, capable of helping researchers to get started in the laboratory immediately, even without programming experience, enabling analysis and reporting of droplet data in real-time and closed-loop experiments. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14730197
Volume :
23
Issue :
14
Database :
Academic Search Index
Journal :
Lab on a Chip
Publication Type :
Academic Journal
Accession number :
164879391
Full Text :
https://doi.org/10.1039/d3lc00327b