Integration of Droplet Microfluidic Tools for Single-Cell Functional Metagenomics: An Engineering Head Start.

David CONCHOUSO; Amani AL-MA'ABADI; Hayedeh BEHZAD; Mohammed ALARAWI; Masahito HOSOKAWA; Yohei NISHIKAWA; Haruko TAKEYAMA; Katsuhiko MINETA; Takashi GOJOBORI

Return

Integration of Droplet Microfluidic Tools for Single-Cell Functional Metagenomics: An Engineering Head Start.

Author: David CONCHOUSO ¹ ; Amani AL-MA'ABADI ² ; Hayedeh BEHZAD ² ; Mohammed ALARAWI ² ; Masahito HOSOKAWA ³ ; Yohei NISHIKAWA ⁴ ; Haruko TAKEYAMA ⁵ ; Katsuhiko MINETA ⁶ ; Takashi GOJOBORI ⁷
Author Information

1. Department of Industrial and Mechanical Engineering, Universidad de las Américas Puebla, Puebla 72810, Mexico; Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia; Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia.
2. Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia; Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia.
3. Research Organization for Nano & Life Innovation, Waseda University, Tokyo 162-0041, Japan; Department of Life Science and Medical Bioscience, Waseda University, Tokyo 162-8480, Japan; Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Waseda University, Tokyo 169-8555, Japan.
4. Research Organization for Nano & Life Innovation, Waseda University, Tokyo 162-0041, Japan; Computational Bio Big-Data Open Innovation Laboratory, AIST-Waseda University, Tokyo 169-0072, Japan.
5. Research Organization for Nano & Life Innovation, Waseda University, Tokyo 162-0041, Japan; Department of Life Science and Medical Bioscience, Waseda University, Tokyo 162-8480, Japan; Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Waseda University, Tokyo 169-8555, Japan; Computational Bio Big-Data Open Innovation Laboratory, AIST-Waseda University, Tokyo 169-0072, Japan.
6. Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia; Computer, Electrical, and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia. Electronic address: katsuhiko.mineta@kaust.edu.sa.
7. Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia; Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia. Electronic address: takashi.gojobori@kaust.edu.sa.
Publication Type:Journal Article
Keywords: Biotechnology; Droplet microfluidics; Droplet sorter; Metagenomics; Single cell
From: Genomics, Proteomics & Bioinformatics 2021;19(3):504-518
CountryChina
Language:English
Abstract: Droplet microfluidic techniques have shown promising outcome to study single cells at high throughput. However, their adoption in laboratories studying "-omics" sciences is still irrelevant due to the complex and multidisciplinary nature of the field. To facilitate their use, here we provide engineering details and organized protocols for integrating three droplet-based microfluidic technologies into the metagenomic pipeline to enable functional screening of bioproducts at high throughput. First, a device encapsulating single cells in droplets at a rate of ∼250 Hz is described considering droplet size and cell growth. Then, we expand on previously reported fluorescence-activated droplet sorting systems to integrate the use of 4 independent fluorescence-exciting lasers (i.e., 405, 488, 561, and 637 nm) in a single platform to make it compatible with different fluorescence-emitting biosensors. For this sorter, both hardware and software are provided and optimized for effortlessly sorting droplets at 60 Hz. Then, a passive droplet merger is also integrated into our pipeline to enable adding new reagents to already-made droplets at a rate of 200 Hz. Finally, we provide an optimized recipe for manufacturing these chips using silicon dry-etching tools. Because of the overall integration and the technical details presented here, our approach allows biologists to quickly use microfluidic technologies and achieve both single-cell resolution and high-throughput capability (>50,000 cells/day) for mining and bioprospecting metagenomic data.