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Wang C, Qiu J, Liu M, Wang Y, Yu Y, Liu H, Zhang Y, Han L. Microfluidic Biochips for Single-Cell Isolation and Single-Cell Analysis of Multiomics and Exosomes. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2401263. [PMID: 38767182 DOI: 10.1002/advs.202401263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 04/26/2024] [Indexed: 05/22/2024]
Abstract
Single-cell multiomic and exosome analyses are potent tools in various fields, such as cancer research, immunology, neuroscience, microbiology, and drug development. They facilitate the in-depth exploration of biological systems, providing insights into disease mechanisms and aiding in treatment. Single-cell isolation, which is crucial for single-cell analysis, ensures reliable cell isolation and quality control for further downstream analyses. Microfluidic chips are small lightweight systems that facilitate efficient and high-throughput single-cell isolation and real-time single-cell analysis on- or off-chip. Therefore, most current single-cell isolation and analysis technologies are based on the single-cell microfluidic technology. This review offers comprehensive guidance to researchers across different fields on the selection of appropriate microfluidic chip technologies for single-cell isolation and analysis. This review describes the design principles, separation mechanisms, chip characteristics, and cellular effects of various microfluidic chips available for single-cell isolation. Moreover, this review highlights the implications of using this technology for subsequent analyses, including single-cell multiomic and exosome analyses. Finally, the current challenges and future prospects of microfluidic chip technology are outlined for multiplex single-cell isolation and multiomic and exosome analyses.
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Affiliation(s)
- Chao Wang
- Institute of Marine Science and Technology, Shandong University, Qingdao, 266237, China
| | - Jiaoyan Qiu
- Institute of Marine Science and Technology, Shandong University, Qingdao, 266237, China
| | - Mengqi Liu
- Institute of Marine Science and Technology, Shandong University, Qingdao, 266237, China
| | - Yihe Wang
- Institute of Marine Science and Technology, Shandong University, Qingdao, 266237, China
| | - Yang Yu
- Department of Periodontology, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University, Jinan, 250100, China
| | - Hong Liu
- State Key Laboratory of Crystal Materials, Shandong University, Jinan, 250100, China
| | - Yu Zhang
- Institute of Marine Science and Technology, Shandong University, Qingdao, 266237, China
| | - Lin Han
- Institute of Marine Science and Technology, Shandong University, Qingdao, 266237, China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, Jinan, 250100, China
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Ma J, Sun H, Li B, Wu B, Zhang X, Ye L. Horizontal transfer potential of antibiotic resistance genes in wastewater treatment plants unraveled by microfluidic-based mini-metagenomics. JOURNAL OF HAZARDOUS MATERIALS 2024; 465:133493. [PMID: 38228000 DOI: 10.1016/j.jhazmat.2024.133493] [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: 09/11/2023] [Revised: 12/30/2023] [Accepted: 01/08/2024] [Indexed: 01/18/2024]
Abstract
Wastewater treatment plants (WWTPs) are known to harbor antibiotic resistance genes (ARGs), which can potentially spread to the environment and human populations. However, the extent and mechanisms of ARG transfer in WWTPs are not well understood due to the high microbial diversity and limitations of molecular techniques. In this study, we used a microfluidic-based mini-metagenomics approach to investigate the transfer potential and mechanisms of ARGs in activated sludge from WWTPs. Our results show that while diverse ARGs are present in activated sludge, only a few highly similar ARGs are observed across different taxa, indicating limited transfer potential. We identified two ARGs, ermF and tla-1, which occur in a variety of bacterial taxa and may have high transfer potential facilitated by mobile genetic elements. Interestingly, genes that are highly similar to the sequences of these two ARGs, as identified in this study, display varying patterns of abundance across geographic regions. Genes similar to ermF found are widely found in Asia and the Americas, while genes resembling tla-1 are primarily detected in Asia. Genes similar to both genes are barely detected in European WWTPs. These findings shed light on the limited horizontal transfer potential of ARGs in WWTPs and highlight the importance of monitoring specific ARGs in different regions to mitigate the spread of antibiotic resistance.
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Affiliation(s)
- Jiachen Ma
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Haohao Sun
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China; School of Environmental Science and Engineering, Changzhou University, Changzhou 213164, China
| | - Bing Li
- State Environmental Protection Key Laboratory of Microorganism Application and Risk Control, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - Bing Wu
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Xuxiang Zhang
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Lin Ye
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China.
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Alma'abadi A, Behzad H, Alarawi M, Conchouso D, Saito Y, Hosokawa M, Nishikawa Y, Kogawa M, Takeyama H, Mineta K, Gojobori T. Identification of Lipolytic Enzymes Using High-Throughput Single-cell Screening and Sorting of a Metagenomic Library. N Biotechnol 2022; 70:102-108. [PMID: 35636700 DOI: 10.1016/j.nbt.2022.05.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 05/19/2022] [Accepted: 05/24/2022] [Indexed: 11/19/2022]
Abstract
The demand for novel, robust microbial biocatalysts for use in industrial and pharmaceutical applications continues to increase rapidly. As a result, there is a need to develop advanced tools and technologies to exploit the vast metabolic potential of unculturable microorganisms found in various environments. Single-cell and functional metagenomics studies can explore the enzymatic potential of entire microbial communities in a given environment without the need to culture the microorganisms. This approach has contributed substantially to the discovery of unique microbial genes for industrial and medical applications. Functional metagenomics involves the extraction of microbial DNA directly from environmental samples, constructing expression libraries comprising the entire microbial genome, and screening of the libraries for the presence of desired phenotypes. In this study, lipolytic enzymes from the Red Sea were targeted. A high-throughput single-cell microfluidic platform combined with a laser-based fluorescent screening bioassay was employed to discover new genes encoding lipolytic enzymes. Analysis of the metagenomic library led to the identification of three microbial genes encoding lipases based on their functional similarity and sequence homology to known lipases. The results demonstrated that microfluidics is a robust technology that can be used for screening in functional metagenomics. The results also indicate that the Red Sea is a promising, under-investigated source of new genes and gene products.
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Affiliation(s)
- Amani Alma'abadi
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia; Biological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia; Life Science and Environment Research Institute, King Abdulaziz City for Science and Technology, National Center of Biotechnology, P.O Box 6086, Riyadh 11442, Saudi Arabia
| | - Hayedeh Behzad
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia; Biological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia
| | - Mohammed Alarawi
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia; Biological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia
| | - David Conchouso
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia; Biological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia; Tecnológico de Monterrey, Escuela de Ingeniería y Ciencias, Puebla 72453, Mexico
| | - Yoshimoto Saito
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia; Biological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia; Marine Open Innovation (MaOI) Institute, 9-25, Hinodecho, Shimizu-ku, Shizuoka 424-0922, Japan
| | - Masahito Hosokawa
- Research Organization for Nano & Life Innovation, Waseda University, 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan; Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan; Department of Life Science and Medical Bioscience, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo 162-8480, Japan; Computational Bio Big-Data Open Innovation Laboratory, AIST-Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-0072, Japan
| | - Yohei Nishikawa
- Research Organization for Nano & Life Innovation, Waseda University, 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan; Computational Bio Big-Data Open Innovation Laboratory, AIST-Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-0072, Japan
| | - Masato Kogawa
- Research Organization for Nano & Life Innovation, Waseda University, 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan
| | - Haruko Takeyama
- Research Organization for Nano & Life Innovation, Waseda University, 513 Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan; Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan; Department of Life Science and Medical Bioscience, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo 162-8480, Japan; Computational Bio Big-Data Open Innovation Laboratory, AIST-Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-0072, Japan
| | - Katsuhiko Mineta
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia; Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
| | - Takashi Gojobori
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia; Biological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia; Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
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Chen L, Fan R, Tang F. Advanced Single-cell Omics Technologies and Informatics Tools for Genomics, Proteomics, and Bioinformatics Analysis. GENOMICS, PROTEOMICS & BIOINFORMATICS 2021; 19:343-345. [PMID: 34923125 PMCID: PMC8864189 DOI: 10.1016/j.gpb.2021.12.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 11/06/2021] [Accepted: 12/09/2021] [Indexed: 11/20/2022]
Affiliation(s)
- Luonan Chen
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China; Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study, Chinese Academy of Sciences, Hangzhou 310024, China.
| | - Rong Fan
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA.
| | - Fuchou Tang
- Beijing Advanced Innovation Center for Genomics, Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China.
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