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Verbist W, Breukers J, Sharma S, Rutten I, Gerstmans H, Coelmont L, Dal Dosso F, Dallmeier K, Lammertyn J. SeParate: multiway fluorescence-activated droplet sorting based on integration of serial and parallel triaging concepts. LAB ON A CHIP 2024; 24:2107-2121. [PMID: 38450543 DOI: 10.1039/d3lc01075a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Fluorescence-activated droplet sorting (FADS) has emerged as a versatile high-throughput sorting tool that is, unlike most fluorescence-activated cell sorting (FACS) platforms, capable of sorting droplet-compartmentalized cells, cell secretions, entire enzymatic reactions and more. Recently, multiplex FADS platforms have been developed for the sorting of multi-fluorophore populations towards different outlets in addition to the standard, more commonly used, 2-way FADS platform. These multiplex FADS platforms consist of either multiple 2-way junctions one after the other (i.e. serial sorters) or of one junction sorting droplets in more than 2 outlets (i.e. parallel sorters). In this work, we present SeParate, a novel platform based on integrating s̲e̲rial and p̲a̲r̲allel sorting principles for accura̲t̲e̲ multiplex droplet sorting that is able to mitigate limitations of current multiplex sorters. We show the SeParate platform and its capability in highly accurate 4-way sorting of a multi-fluorophore population into four subpopulations with the potential to expand to more. More specifically, the SeParate platform was thoroughly validated using mixed populations of fluorescent beads and picoinjected droplets, yielding sorting accuracies up to 100% and 99.9%, respectively. Finally, transfected HEK-293T cells were sorted employing two different optical setups, resulting in an accuracy up to 99.5%. SeParate's high accuracy for a diverse set of samples, including highly variable biological specimens, together with its scalability beyond the demonstrated 4-way sorting, warrants a broad applicability for multi-fluorophore studies in life sciences, environmental sciences and others.
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Affiliation(s)
- Wannes Verbist
- Department of Biosystems - Biosensors Group, KU Leuven, Willem de Croylaan 42, Box 2428, 3001 Leuven, Belgium.
| | - Jolien Breukers
- Department of Biosystems - Biosensors Group, KU Leuven, Willem de Croylaan 42, Box 2428, 3001 Leuven, Belgium.
| | - Sapna Sharma
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology and Chemotherapy, Molecular Vaccinology and Vaccine Discovery, KU Leuven, 3000 Leuven, Belgium
| | - Iene Rutten
- Department of Biosystems - Biosensors Group, KU Leuven, Willem de Croylaan 42, Box 2428, 3001 Leuven, Belgium.
| | - Hans Gerstmans
- Department of Biosystems - Biosensors Group, KU Leuven, Willem de Croylaan 42, Box 2428, 3001 Leuven, Belgium.
| | - Lotte Coelmont
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology and Chemotherapy, Molecular Vaccinology and Vaccine Discovery, KU Leuven, 3000 Leuven, Belgium
| | - Francesco Dal Dosso
- Department of Biosystems - Biosensors Group, KU Leuven, Willem de Croylaan 42, Box 2428, 3001 Leuven, Belgium.
| | - Kai Dallmeier
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology and Chemotherapy, Molecular Vaccinology and Vaccine Discovery, KU Leuven, 3000 Leuven, Belgium
| | - Jeroen Lammertyn
- Department of Biosystems - Biosensors Group, KU Leuven, Willem de Croylaan 42, Box 2428, 3001 Leuven, Belgium.
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He Y, Qiao Y, Ding L, Cheng T, Tu J. Recent advances in droplet sequential monitoring methods for droplet sorting. BIOMICROFLUIDICS 2023; 17:061501. [PMID: 37969470 PMCID: PMC10645479 DOI: 10.1063/5.0173340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 10/23/2023] [Indexed: 11/17/2023]
Abstract
Droplet microfluidics is an attractive technology to run parallel experiments with high throughput and scalability while maintaining the heterogeneous features of individual samples or reactions. Droplet sorting is utilized to collect the desired droplets based on droplet characterization and in-droplet content evaluation. A proper monitoring method is critical in this process, which governs the accuracy and maximum frequency of droplet handling. Until now, numerous monitoring methods have been integrated in the microfluidic devices for identifying droplets, such as optical spectroscopy, mass spectroscopy, electrochemical monitoring, and nuclear magnetic resonance spectroscopy. In this review, we summarize the features of various monitoring methods integrated into droplet sorting workflow and discuss their suitable condition and potential obstacles in use. We aim to provide a systematic introduction and an application guide for choosing and building a droplet monitoring platform.
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Affiliation(s)
- Yukun He
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
| | - Yi Qiao
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
| | - Lu Ding
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
| | - Tianguang Cheng
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
| | - Jing Tu
- State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
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Yasuura M, Tan ZL, Horiguchi Y, Ashiba H, Fukuda T. Improvement of Sensitivity and Speed of Virus Sensing Technologies Using nm- and μm-Scale Components. SENSORS (BASEL, SWITZERLAND) 2023; 23:6830. [PMID: 37571612 PMCID: PMC10422600 DOI: 10.3390/s23156830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 07/20/2023] [Accepted: 07/27/2023] [Indexed: 08/13/2023]
Abstract
Various viral diseases can be widespread and cause severe disruption to global society. Highly sensitive virus detection methods are needed to take effective measures to prevent the spread of viral infection. This required the development of rapid virus detection technology to detect viruses at low concentrations, even in the biological fluid of patients in the early stages of the disease or environmental samples. This review describes an overview of various virus detection technologies and then refers to typical technologies such as beads-based assay, digital assay, and pore-based sensing, which are the three modern approaches to improve the performance of viral sensing in terms of speed and sensitivity.
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Affiliation(s)
- Masato Yasuura
- Sensing System Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Central 5, 1-1-1 Higashi, Tsukuba 305-8565, Ibaraki, Japan; (Z.L.T.); (Y.H.); (H.A.); (T.F.)
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Gantz M, Neun S, Medcalf EJ, van Vliet LD, Hollfelder F. Ultrahigh-Throughput Enzyme Engineering and Discovery in In Vitro Compartments. Chem Rev 2023; 123:5571-5611. [PMID: 37126602 PMCID: PMC10176489 DOI: 10.1021/acs.chemrev.2c00910] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Novel and improved biocatalysts are increasingly sourced from libraries via experimental screening. The success of such campaigns is crucially dependent on the number of candidates tested. Water-in-oil emulsion droplets can replace the classical test tube, to provide in vitro compartments as an alternative screening format, containing genotype and phenotype and enabling a readout of function. The scale-down to micrometer droplet diameters and picoliter volumes brings about a >107-fold volume reduction compared to 96-well-plate screening. Droplets made in automated microfluidic devices can be integrated into modular workflows to set up multistep screening protocols involving various detection modes to sort >107 variants a day with kHz frequencies. The repertoire of assays available for droplet screening covers all seven enzyme commission (EC) number classes, setting the stage for widespread use of droplet microfluidics in everyday biochemical experiments. We review the practicalities of adapting droplet screening for enzyme discovery and for detailed kinetic characterization. These new ways of working will not just accelerate discovery experiments currently limited by screening capacity but profoundly change the paradigms we can probe. By interfacing the results of ultrahigh-throughput droplet screening with next-generation sequencing and deep learning, strategies for directed evolution can be implemented, examined, and evaluated.
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Affiliation(s)
- Maximilian Gantz
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Rd, Cambridge CB2 1GA, U.K
| | - Stefanie Neun
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Rd, Cambridge CB2 1GA, U.K
| | - Elliot J Medcalf
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Rd, Cambridge CB2 1GA, U.K
| | - Liisa D van Vliet
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Rd, Cambridge CB2 1GA, U.K
| | - Florian Hollfelder
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Rd, Cambridge CB2 1GA, U.K
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Sun G, Qu L, Azi F, Liu Y, Li J, Lv X, Du G, Chen J, Chen CH, Liu L. Recent progress in high-throughput droplet screening and sorting for bioanalysis. Biosens Bioelectron 2023; 225:115107. [PMID: 36731396 DOI: 10.1016/j.bios.2023.115107] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 01/09/2023] [Accepted: 01/25/2023] [Indexed: 01/31/2023]
Abstract
Owing to its ability to isolate single cells and perform high-throughput sorting, droplet sorting has been widely applied in several research fields. Compared with flow cytometry, droplet allows the encapsulation of single cells for cell secretion or lysate analysis. With the rapid development of this technology in the past decade, various droplet sorting devices with high throughput and accuracy have been developed. A droplet sorter with the highest sorting throughput of 30,000 droplets per second was developed in 2015. Since then, increased attention has been paid to expanding the possibilities of droplet sorting technology and strengthening its advantages over flow cytometry. This review aimed to summarize the recent progress in droplet sorting technology from the perspectives of device design, detection signal, actuating force, and applications. Technical details for improving droplet sorting through various approaches are introduced and discussed. Finally, we discuss the current limitations of droplet sorting for single-cell studies along with the existing gap between the laboratory and industry and provide our insights for future development of droplet sorters.
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Affiliation(s)
- Guoyun Sun
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Lisha Qu
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Fidelis Azi
- Department of Chemical Engineering, Guangdong Technion-Israel Institute of Technology GTIIT, Shantou, Guangdong, 515063, China
| | - Yanfeng Liu
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Jianghua Li
- Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Xueqin Lv
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Guocheng Du
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Jian Chen
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China
| | - Chia-Hung Chen
- Department of Biomedical Engineering, College of Engineering, City University of Hong Kong, Hong Kong, China.
| | - Long Liu
- Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China.
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