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Bulletin of Chinese Academy of Sciences (Chinese Version)

Authors

Shuang LI, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China; Key Laboratory of Industrial Biocatalysts, Ministry of Education, Beijing 100084, ChinaFollow
Xiaojie GUO, TMAXTREE Biotechnology Co. Ltd., Luoyang 471023, China
Haibo CHEN, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China; Key Laboratory of Industrial Biocatalysts, Ministry of Education, Beijing 100084, China
Sisi CHEN, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China; Key Laboratory of Industrial Biocatalysts, Ministry of Education, Beijing 100084, China
Xin DA, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China; Key Laboratory of Industrial Biocatalysts, Ministry of Education, Beijing 100084, China
Zhenghui LI, Beijing Key Laboratory of Biomass Waste Resource Utilization, College of Biochemical Engineering, Beijing Union University, Beijing 100023, China
Qinxiu LIU, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China; Key Laboratory of Industrial Biocatalysts, Ministry of Education, Beijing 100084, China
Yi WANG, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China; Key Laboratory of Industrial Biocatalysts, Ministry of Education, Beijing 100084, China
Xinhui XING, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China; Key Laboratory of Industrial Biocatalysts, Ministry of Education, Beijing 100084, China; Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China; Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China
Chong ZHANG, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China; Key Laboratory of Industrial Biocatalysts, Ministry of Education, Beijing 100084, China; Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, ChinaFollow

Keywords

microfluidics; single-cell; high-throughput testing; synthetic biology; biomanufacturing

Document Type

Biomanufacturing: Retrospect and Prospects

Abstract

Engineering cells are a core component of green bio-manufacturing. The efficient testing and acquisition of engineering cells with the desired phenotype is a critical factor in the successful implementation of bio-manufacturing. In recent years, based on microfluidics technologies, non-culture type single-cell phenotype high-throughput test equipment and culture type phenotype high-throughput test equipment for the growth and metabolism of single cell in a bioreactor have been developed such as microdroplet and microchamber, realizing high-throughput, automated, miniaturized, and integrated testing of the phenotypes of engineering cells and providing a powerful tool for the breeding of engineering cells. This review systematically compiles the research progress of non-culture type single-cell phenotype testing technologies and equipment based on fluorescence signals, Raman signals, image signals, and magnetic signals, as well as the droplet and microchamber culture type single-cell test technologies and equipment based on picoliter, nanoliter, and microliter multi-scale microbioreactors, and explores the development trend of the creation of high-throughput testing instruments for engineering cells, providing a reference for the research of green bio-manufacturing engineering cells testing technologies.

First page

91

Last Page

106

Language

Chinese

Publisher

Bulletin of Chinese Academy of Sciences

References

1 Bashor C J, Hilton I B, Bandukwala H, et al. Engineering the next generation of cell-based therapeutics. Nature Reviews Drug Discovery, 2022, 21(9): 655-675.

2 Liu Y, Nielsen J. Recent trends in metabolic engineering of microbial chemical factories. Current Opinion in Biotechnology, 2019, 60: 188-197.

3 Opgenorth P, Costello Z, Okada T, et al. Lessons from two design-build-test-learn cycles of dodecanol production in Escherichia coli aided by machine learning. ACS Synthetic Biology, 2019, 8(6): 1337-1351.

4 Bhunia A K, Singh A K, Parker K, et al. Petri-plate, bacteria, and laser optical scattering sensor. Frontiers in Cellular and Infection Microbiology, 2022, doi: 10.3389/fcimb.2022.1087074.

5 Abatzoglou I, Zois C E, Pouliliou S, et al. Establishment and validation of a method for multi-dose irradiation of cells in 96-well microplates. Biochemical and Biophysical Research Communications, 2013, 431(3): 456-459.

6 Zeng W Z, Guo L K, Xu S, et al. High-throughput screening technology in industrial biotechnology. Trends in Biotechnology, 2020, 38(8): 888-906.

7 Huang Y M, Sheth R U, Zhao S J, et al. High-throughput microbial culturomics using automation and machine learning. Nature Biotechnology, 2023, 41(10): 1424-1433.

8 Manz A, Graber N, Widmer H M. Miniaturized total chemical analysis systems: A novel concept for chemical sensing. Sensors and Actuators B: Chemical, 1990, 1(6): 244-248.

9 Sciambi A, Abate A R. Accurate microfluidic sorting of droplets at 30 kHz. Lab on a Chip, 2015, 15(1): 47-51.

10 Whitesides G M. The origins and the future of microfluidics. Nature, 2006, 442: 368-373.

11 Zhang J, Ren L, Zhang L, et al. Single-cell rapid identification, in situ viability and vitality profiling, and genome-based source-tracking for probiotics products. iMeta, 2023, doi: 10.1002/imt2.117.

12 Nawar S, Stolaroff J K, Ye C W, et al. Parallelizable microfluidic dropmakers with multilayer geometry for the generation of double emulsions. Lab on a Chip, 2020, 20(1): 147-154.

13 Bhatia S N, Ingber D E. Microfluidic organs-on-chips. Nature Biotechnology, 2014, 32(8): 760-772.

14 Hodne K, Weltzien F A. Single-cell isolation and gene analysis: Pitfalls and possibilities. International Journal of Molecular Sciences, 2015, 16(11): 26832-26849.

15 Jakobsson O, Grenvall C, Nordin M, et al. Acoustic actuated fluorescence activated sorting of microparticles. Lab on a Chip, 2014, 14(11): 1943-1950.

16 Newell E W, Sigal N, Bendall S C, et al. Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes. Immunity, 2012, 36(1): 142-152.

17 Song Y Z, Kaster A K, Vollmers J, et al. Single-cell genomics based on Raman sorting reveals novel carotenoid-containing bacteria in the Red Sea. Microbial Biotechnology, 2017, 10(1): 125-137.

18 Hasle N, Cooke A, Srivatsan S, et al. High-throughput, microscope-based sorting to dissect cellular heterogeneity. Molecular Systems Biology, 2020, 16(6): e9442.

19 Kim U, Tom Soh H. Simultaneous sorting of multiple bacterial targets using integrated dielectrophoretic-magnetic activated cell sorter. Lab on a Chip, 2009, 9(16): 2313-2318.

20 Johansson L, Nikolajeff F, Johansson S, et al. On-chip fluorescence-activated cell sorting by an integrated miniaturized ultrasonic transducer. Analytical Chemistry, 2009, 81(13): 5188-5196.

21 Robinson J P, Ostafe R, Iyengar S N, et al. Flow cytometry: The next revolution. Cells, 2023, doi: 10.3390/cells12141875.

22 Grzeschik J, Yanakieva D, Roth L, et al. Yeast surface display in combination with fluorescence-activated cell sorting enables the rapid isolation of antibody fragments derived from immunized chickens. Biotechnology Journal, 2019, doi: 10.1002/biot.201800466.

23 Hewitt B M, Singhal N, Elliot R G, et al. Novel fiber optic detection method for in situ analysis of fluorescently labeled biosensor organisms. Environmental Science Technology, 2012, 46(10): 5414-5421.

24 Ostafe R, Prodanovic R, Commandeur U, et al. Flow cytometry-based ultra-high-throughput screening assay for cellulase activity. Analytical Biochemistry, 2013, 435(1): 93-98.

25 Gao J S, Du M H, Zhao J H, et al. Design of a genetically encoded biosensor to establish a high-throughput screening platform for L-cysteine overproduction. Metabolic Engineering, 2022, 73: 144-157.

26 Kortmann M, Mack C, Baumgart M, et al. Pyruvate carboxylase variants enabling improved lysine production from glucose identified by biosensor-based high-throughput fluorescence-activated cell sorting screening. ACS Synthetic Biology, 2019, 8(2): 274-281.

27 Wagner J M, Liu L Q, Yuan S F, et al. A comparative analysis of single cell and droplet-based FACS for improving production phenotypes: Riboflavin overproduction in Yarrowia lipolytica. Metabolic Engineering, 2018, 47: 346-356.

28 Ma C X, Tan Z L, Lin Y, et al. Gel microdroplet–based high-throughput screening for directed evolution of xylanase-producing Pichia pastoris. Journal of Bioscience and Bioengineering, 2019, 128(6): 662-668.

29 Song H K, Kim J M, Noh E M, et al. Role of NOX1 and NOX5 in protein kinase C/reactive oxygen species-mediated MMP-9 activation and invasion in MCF-7 breast cancer cells. Molecular Medicine Reports, 2024, 30(4): 188.

30 Song Y Z, Yin H B, Huang W E. Raman activated cell sorting. Current Opinion in Chemical Biology, 2016, 33: 1-8.

31 Wang Y, Ji Y T, Wharfe E S, et al. Raman activated cell ejection for isolation of single cells. Analytical Chemistry, 2013, 85(22): 10697-10701.

32 Xu T, Gong Y H, Su X L, et al. Phenome-genome profiling of single bacterial cell by Raman-activated gravity-driven encapsulation and sequencing. Small, 2020, doi: 10.1002/smll.202001172.

33 Wang X X, Ren L H, Su Y T, et al. Raman-activated droplet sorting (RADS) for label-free high-throughput screening of microalgal single-cells. Analytical Chemistry, 2017, 89(22): 12569-12577.

34 Wang X X, Xin Y, Ren L H, et al. Positive dielectrophoresis-based Raman-activated droplet sorting for culture-free and label-free screening of enzyme function in vivo. Science Advances, 2020, doi: 10.1126/sciadv.abb352.

35 Su X L, Gong Y H, Gou H L, et al. Rational optimization of Raman-activated cell ejection and sequencing for bacteria. Analytical Chemistry, 2020, 92(12): 8081-8089.

36 Vinay Kumar B N, Guo S X, Bocklitz T, et al. Demonstration of carbon catabolite repression in naphthalene degrading soil bacteria via Raman spectroscopy based stable isotope probing. Analytical Chemistry, 2016, 88(15): 7574-7582.

37 Kaczor A, Baranska M. Structural changes of carotenoid astaxanthin in a single algal cell monitored in situ by Raman spectroscopy. Analytical Chemistry, 2011, 83(20): 7763-7770.

38 Ji Y T, He Y H, Cui Y B, et al. Raman spectroscopy provides a rapid, non-invasive method for quantitation of starch in live, unicellular microalgae. Biotechnology Journal, 2014, 9(12): 1512-1518.

39 Yan S S, Wang S Y, Qiu J X, et al. Raman spectroscopy combined with machine learning for rapid detection of food-borne pathogens at the single-cell level. Talanta, 2021, 226: 122195.

40 Diao Z D, Kan L Y, Zhao Y L, et al. Artificial intelligence-assisted automatic and index-based microbial single-cell sorting system for One-Cell-One-Tube. mLife, 2022, 1(4): 448-459.

41 Nitta N, Sugimura T, Isozaki A, et al. Intelligent image-activated cell sorting. Cell, 2018, 175(1): 266-276.

42 Isozaki A, Mikami H, Hiramatsu K, et al. A practical guide to intelligent image-activated cell sorting. Nature Protocols, 2019, 14(8): 2370-2415.

43 Zhao Y Q, Isozaki A, Herbig M, et al. Intelligent sort-timing prediction for image-activated cell sorting. Cytometry Part A, 2023, 103(1): 88-97.

44 Headland S E, Jones H R, D’Sa A S V, et al. Cutting-edge analysis of extracellular microparticles using ImageStream(X) imaging flow cytometry. Scientific Reports, 2014, 4: 5237.

45 Zuba-Surma E, Kucia M, Ratajczak M. “Decoding the dots”: The ImageStream System (ISS) as a novel and powerful tool for flow cytometric analysis. Open Life Sciences, 2008, 3(1): 1-10.

46 Welzel G, Seitz D, Schuster S. Magnetic-activated cell sorting (MACS) can be used as a large-scale method for establishing zebrafish neuronal cell cultures. Scientific Reports, 2015, 5: 795.

47 Adams J D, Kim U, Tom Soh H. Multitarget magnetic activated cell sorter. PNAS, 2008, 105(47): 18165-18170.

48 Pan J, Wan J. Methodological comparison of FACS and MACS isolation of enriched microglia and astrocytes from mouse brain. Journal of Immunological Methods, 2020, 486: 112834.

49 Münz C, Steinman R M, Fujii S I. Dendritic cell maturation by innate lymphocytes: Coordinated stimulation of innate and adaptive immunity. Journal of Experimental Medicine, 2005, 202(2): 203-207.

50 Chavarria V, Ortiz-Islas E, Salazar A, et al. Lactate-loaded nanoparticles induce glioma cytotoxicity and increase the survival of rats bearing malignant glioma brain tumor. Pharmaceutics, 2022, 14(2): 327.

51 Kulis M, Merkel A, Heath S, et al. Whole-genome fingerprint of the DNA methylome during human B cell differentiation. Nature Genetics, 2015, 47(7): 746-756.

52 Laghmouchi A, Hoogstraten C, Frederik Falkenburg J H, et al. Long-term in vitro persistence of magnetic properties after magnetic bead-based cell separation of T cells. Scandinavian Journal of Immunology, 2020, doi: 10.1111/sji.12924.

53 Mazutis L, Gilbert J, Lloyd Ung W, et al. Single-cell analysis and sorting using droplet-based microfluidics. Nature Protocols, 2013, 8(5): 870-891.

54 Shembekar N, Hu H X, Eustace D, et al. Single-cell droplet microfluidic screening for antibodies specifically binding to target cells. Cell Reports, 2018, 22(8): 2206-2215.

55 Zhang C T, Wu X H, Song F Q, et al. Core-shell droplet-based microfluidic screening system for filamentous fungi. ACS Sensors, 2023, 8(9): 3468-3477.

56 Baret J C, Miller O J, Taly V, et al. Fluorescence-activated droplet sorting (FADS): Efficient microfluidic cell sorting based on enzymatic activity. Lab on a Chip, 2009, 9(13): 1850-1858.

57 Ma F Q, Chung M T, Yao Y, et al. Efficient molecular evolution to generate enantioselective enzymes using a dual-channel microfluidic droplet screening platform. Nature Communications, 2018, 9(1): 1030.

58 Jiang J J, Yang G Y, Ma F Q. Fluorescence coupling strategies in fluorescence-activated droplet sorting (FADS) for ultrahigh-throughput screening of enzymes, metabolites, and antibodies. Biotechnology Advances, 2023, doi: 10.1016/j.biotechadv.2023.108173.

59 Shi L X, Liu P, Tan Z J, et al. Complete depolymerization of PET wastes by an evolved PET hydrolase from directed evolution. Angewandte Chemie (International Ed), 2023, doi: 10.1002/anie.202218390.

60 Yuan H L, Tu R, Tong X W, et al. Ultrahigh-throughput screening of industrial enzyme-producing strains by droplet-based microfluidic system. Journal of Industrial Microbiology Biotechnology, 2022, doi: 10.1093/jimb/kuac007.

61 Abalde-Cela S, Gould A, Liu X, et al. High-throughput detection of ethanol-producing cyanobacteria in a microdroplet platform. Journal of the Royal Society, Interface, 2015, doi: 10.1098/rsif.2015.0216.

62 Wang B L, Ghaderi A, Zhou H, et al. Microfluidic high-throughput culturing of single cells for selection based on extracellular metabolite production or consumption. Nature Biotechnology, 2014, 32(5): 473-478.

63 Li S, Zhang Y, Li L, et al. Establishment of picodroplet-based co-culture system to improve erythritol production in Yarrowia lipolytica. Biochemical Engineering Journal, 2023, doi: 10.1016/j.bej.2023.109036.

64 Li S, Liao X H, Yu X Y, et al. Combining genetically encoded biosensors with droplet microfluidic system for enhanced glutaminase production by Bacillus amyloliquefaciens. Biochemical Engineering Journal, 2022, doi: 10.1016/j.bej.2022.108586.

65 Gielen F, Hours R, Emond S, et al. Ultrahigh-throughput-directed enzyme evolution by absorbance-activated droplet sorting (AADS). PNAS, 2016, 113(47): 7383-7389.

66 Holland-Moritz D A, Wismer M K, Mann B F, et al. Mass activated droplet sorting (MADS) enables high-throughput screening of enzymatic reactions at nanoliter scale. Angewandte Chemie (International Ed), 2020, 59(11): 4470-4477.

67 Zang E, Brandes S, Tovar M, et al. Real-time image processing for label-free enrichment of Actinobacteria cultivated in picolitre droplets. Lab on a Chip, 2013, 13(18): 3707-3713.

68 Yu X Y, Li S, Feng H B, et al. CRISPRi-microfluidics screening enables genome-scale target identification for high-titer protein production and secretion. Metabolic Engineering, 2023, 75: 192-204.

69 Meng Y J, Li S, Zhang C, et al. Strain-level profiling with picodroplet microfluidic cultivation reveals host-specific adaption of honeybee gut symbionts. Microbiome, 2022, 10(1): 140.

70 Wei L F, Li S, Pan H, et al. Ultrahigh-throughput screening of antagonistic bacteria against Erwinia carotovoraEcc15 based on droplet microfluidics. Food Science and Human Wellness, 2024, doi: 10.26599/FSHW.2024.9250263.

71 Gaa R, Menang-Ndi E, Pratapa S, et al. Versatile and rapid microfluidics-assisted antibody discovery. mAbs, 2021, 13(1): 1978130.

72 Yu T, Hull J, Ruiz A, et al. Expediting antibody discovery using Bioelectronica’s HypercellTM platform. The Journal of Immunology, 2020, 204(1_Supplement): 86.36.

73 Jian X J, Guo X J, Cai Z S, et al. Single-cell microliter-droplet screening system (MISS Cell): An integrated platform for automated high-throughput microbial monoclonal cultivation and picking. Biotechnology and Bioengineering, 2023, 120(3): 778-792.

74 Liu L, Zeng W Z, Yu S Q, et al. Rapid enabling of Gluconobacter oxydans resistance to high D-sorbitol concentration and high temperature by microdroplet-aided adaptive evolution. Frontiers in Bioengineering and Biotechnology, 2021, 9: 731247.

75 Jian X J, Guo X J, Wang J, et al. Microbial microdroplet culture system (MMC): An integrated platform for automated, high-throughput microbial cultivation and adaptive evolution. Biotechnology and Bioengineering, 2020, 117(6): 1724-1737.

76 Jiang L, Boitard L, Broyer P, et al. Digital antimicrobial susceptibility testing using the MilliDrop technology. European Journal of Clinical Microbiology Infectious Diseases, 2016, 35(3): 415-422.

77 Postek W, Garstecki P. Droplet microfluidics for high-throughput analysis of antibiotic susceptibility in bacterial cells and populations. Accounts of Chemical Research, 2022, 55(5): 605-615.

78 Villa M M, Bloom R J, Silverman J D, et al. Interindividual variation in dietary carbohydrate metabolism by gut bacteria revealed with droplet microfluidic culture. mSystems, 2020, 5(3): e00864-19.

79 Sun L L, Zhang L K, Yang X, et al. A simple and low-cost method for fabrication of polydimethylsiloxane microfludic chips. Journal of Nanoscience and Nanotechnology, 2021, 21(11): 5635-5641.

80 Gambardella G, Viscido G, Tumaini B, et al. A single-cell analysis of breast cancer cell lines to study tumour heterogeneity and drug response. Nature Communications, 2022, 13(1): 1714.

81 Park J Y, Morgan M, Sachs A N, et al. Single cell trapping in larger microwells capable of supporting cell spreading and proliferation. Microfluidics and Nanofluidics, 2010, 8(2): 263-268.

82 Lindström S, Andersson-Svahn H. Single-cell culture in microwells. Single-Cell Analysis. Totowa: Humana Press, 2012: 41-52.

83 Le K, Tan C, Le H, et al. Assuring clonality on the beacon digital cell line development platform. Biotechnology Journal, 2020, 15(1): e1900247.

84 Wang X X, Ren L H, Diao Z D, et al. Robust spontaneous Raman flow cytometry for single-cell metabolic phenome profiling via pDEP-DLD-RFC. Advanced Science, 2023, 10(16): e2207497.

85 Vallone V F, Telugu N S, Fischer I, et al. Methods for automated single cell isolation and sub-cloning of human pluripotent stem cells. Current Protocols in Stem Cell Biology, 2020, 55(1): e123.

86 Matochko W L, Nelep C, Chen W C, et al. CellCelector™ as a platform in isolating primary B cells for antibody discovery. Antibody Therapeutics, 2022, 5(1): 11-17.

87 Yoshimoto N, Kida A, Jie X, et al. An automated system for high-throughput single cell-based breeding. Scientific Reports, 2013, 3: 1191.

88 Berdy B, Spoering A L, Ling L L, et al. In situ cultivation of previously uncultivable microorganisms using the ichip. Nature Protocols, 2017, 12(10): 2232-2242.

89 Nichols D, Cahoon N, Trakhtenberg E M, et al. Use of ichip for high-throughput in situ cultivation of “uncultivable” microbial species. Applied and Environmental Microbiology, 2010, 76(8): 2445-2450.

90 Li M, Raza M, Song S, et al. Application of culturomics in fungal isolation from mangrove sediments. Microbiome, 2023, 11(1): 272.

91 Liu H Z, Xue R, Wang Y L, et al. FACS-iChip: A high-efficiency iChip system for microbial ‘dark matter’ mining. Marine Life Science Technology, 2020, 3(2): 162-168.

92 Lodhi A F, Zhang Y, Adil M, et al. Antibiotic discovery: Combining isolation chip (iChip) technology and co-culture technique. Applied Microbiology and Biotechnology, 2018, 102(17): 7333-7341.

93 Herzenberg L A, Parks D, Sahaf B, et al. The history and future of the fluorescence activated cell sorter and flow cytometry: A view from Stanford. Clinical Chemistry, 2002, 48(10): 1819-1827.

94 Uchinomiya S, Nagaura T, Weber M, et al. Fluorescence-based detection of fatty acid β-oxidation in cells and tissues using quinone methide-releasing probes. Journal of the American Chemical Society, 2023, 145(14): 8248-8260.

95 Tu R, Li L P, Yuan H L, et al. Biosensor-enabled droplet microfluidic system for the rapid screening of 3-dehydroshikimic acid produced in Escherichia coli. Journal of Industrial Microbiology Biotechnology, 2020, 47(12): 1155-1160.

96 He R L, Ding R H, Heyman J A, et al. Ultra-high-throughput picoliter-droplet microfluidics screening of the industrial cellulase-producing filamentous fungus Trichoderma reesei. Journal of Industrial Microbiology Biotechnology, 2019, 46(11): 1603-1610.

97 Qiao Y X, Zhao X Y, Zhu J, et al. Fluorescence-activated droplet sorting of lipolytic microorganisms using a compact optical system. Lab on a Chip, 2017, 18(1): 190-196.

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