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Microfluidic Single-Cell Analytics

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Microfluidics in Biotechnology

Part of the book series: Advances in Biochemical Engineering/Biotechnology ((ABE,volume 179))

Abstract

What is the impact of cellular heterogeneity on process performance? How do individual cells contribute to averaged process productivity? Single-cell analysis is a key technology for answering such key questions of biotechnology, beyond bulky measurements with populations. The analysis of cellular individuality, its origins, and the dependency of process performance on cellular heterogeneity has tremendous potential for optimizing biotechnological processes in terms of metabolic, reaction, and process engineering. Microfluidics offer unmatched environmental control of the cellular environment and allow massively parallelized cultivation of single cells. However, the analytical accessibility to a cell’s physiology is of crucial importance for obtaining the desired information on the single-cell production phenotype. Highly sensitive analytics are required to detect and quantify the minute amounts of target analytes and small physiological changes in a single cell. For their application to biotechnological questions, single-cell analytics must evolve toward the measurement of kinetics and specific rates of the smallest catalytic unit, the single cell. In this chapter, we focus on an introduction to the latest single-cell analytics and their application for obtaining physiological parameters in a biotechnological context from single cells. We present and discuss recent advancements in single-cell analytics that enable the analysis of cell-specific growth, uptake, and production kinetics, as well as the gene expression and regulatory mechanisms at a single-cell level.

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References

  1. Schmid A, Dordick JS, Hauer B, Kiener A, Wubbolts M, Witholt B (2001) Industrial biocatalysis today and tomorrow. Nature 409(6817):258–268

    Article  CAS  PubMed  Google Scholar 

  2. Schrewe M, Julsing MK, Buhler B, Schmid A (2013) Whole-cell biocatalysis for selective and productive C-O functional group introduction and modification. Chem Soc Rev 42(15):6346–6377

    Article  CAS  PubMed  Google Scholar 

  3. Blank LM, Ebert BE, Buhler B, Schmid A (2008) Metabolic capacity estimation of Escherichia coli as a platform for redox biocatalysis: constraint-based modeling and experimental verification. Biotechnol Bioeng 100(6):1050–1065

    Article  CAS  PubMed  Google Scholar 

  4. Olaofe OA, Fenner CJ, Gudiminchi RK, Smit MS, Harrison ST (2013) The influence of microbial physiology on biocatalyst activity and efficiency in the terminal hydroxylation of n-octane using Escherichia coli expressing the alkane hydroxylase, CYP153A6. Microb Cell Factories 12:8

    Article  CAS  Google Scholar 

  5. Litsios A, Ortega AD, Wit EC, Heinemann M (2018) Metabolic-flux dependent regulation of microbial physiology. Curr Opin Microbiol 42:71–78

    Article  CAS  PubMed  Google Scholar 

  6. Davies J (2002) Re-birth of microbial physiology. Environ Microbiol 4(1):6

    Article  PubMed  Google Scholar 

  7. Royle K, Kontoravdi C (2013) A systems biology approach to optimising hosts for industrial protein production. Biotechnol Lett 35(12):1961–1969

    Article  CAS  PubMed  Google Scholar 

  8. Schuetz R, Zamboni N, Zampieri M, Heinemann M, Sauer U (2012) Multidimensional optimality of microbial metabolism. Science 336(6081):601–604

    Article  CAS  PubMed  Google Scholar 

  9. Lee SY, Lee DY, Kim TY (2005) Systems biotechnology for strain improvement. Trends Biotechnol 23(7):349–358

    Article  CAS  PubMed  Google Scholar 

  10. Fritzsch FS, Dusny C, Frick O, Schmid A (2012) Single-cell analysis in biotechnology, systems biology, and biocatalysis. Ann Rev Chem Biomol Eng 3(1):129–155

    Article  CAS  Google Scholar 

  11. Dusny C, Grunberger A (2019) Microfluidic single-cell analysis in biotechnology: from monitoring towards understanding. Curr Opin Biotechnol 63:26–33

    Article  CAS  PubMed  Google Scholar 

  12. Kortmann H, Blank LM, Schmid A (2011) Single cell analytics: an overview. Adv Biochem Eng Biotechnol 124:99–122

    PubMed  Google Scholar 

  13. Schmid A, Kortmann H, Dittrich PS, Blank LM (2010) Chemical and biological single cell analysis. Curr Opin Biotechnol 21(1):12–20

    Article  CAS  PubMed  Google Scholar 

  14. Reshes G, Vanounou S, Fishov I, Feingold M (2008) Cell shape dynamics in Escherichia coli. Biophys J 94(1):251–264

    Article  CAS  PubMed  Google Scholar 

  15. Boyd ES, Leavitt WD, Geesey GG (2009) CO2 uptake and fixation by a thermoacidophilic microbial community attached to precipitated sulfur in a geothermal spring. Appl Environ Microbiol 75(13):4289–4296

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Zakhartsev M, Reuss M (2018) Cell size and morphological properties of yeast Saccharomyces cerevisiae in relation to growth temperature. FEMS Yeast Res 18(6)

    Google Scholar 

  17. Zavrel T, Ocenasova P, Cerveny J (2017) Phenotypic characterization of Synechocystis sp. PCC 6803 substrains reveals differences in sensitivity to abiotic stress. PLoS One 12(12):e0189130

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Milo R, Jorgensen P, Moran U, Weber G, Springer M (2010) BioNumbers-the database of key numbers in molecular and cell biology. Nucleic Acids Res 38:D750–D753

    Article  CAS  PubMed  Google Scholar 

  19. Dittrich P, Jakubowski N (2014) Current trends in single cell analysis. Anal Bioanal Chem 406(27):6957–6961

    Article  CAS  PubMed  Google Scholar 

  20. Lubeck E, Cai L (2012) Single-cell systems biology by super-resolution imaging and combinatorial labeling. Nat Methods 9(7):743–748

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Altinoglu I, Merrifield CJ, Yamaichi Y (2019) Single molecule super-resolution imaging of bacterial cell pole proteins with high-throughput quantitative analysis pipeline. Sci Rep 9(1):6680

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Young JW, Locke JCW, Altinok A, Rosenfeld N, Bacarian T, Swain PS, Mjolsness E, Elowitz MB (2012) Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy. Nat Protoc 7(1):80–88

    Article  CAS  Google Scholar 

  23. Locke JC, Elowitz MB (2009) Using movies to analyse gene circuit dynamics in single cells. Nat Rev Microbiol 7(5):383–392

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Young JW, Locke JC, Elowitz MB (2013) Rate of environmental change determines stress response specificity. Proc Natl Acad Sci U S A 110(10):4140–4145

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Locke JCW, Young JW, Fontes M, Jimenez MJH, Elowitz MB (2011) Stochastic pulse regulation in bacterial stress response. Science 334(6054):366–369

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Unthan S, Gruenberger A, van Ooyen J, Gaetgens J, Heinrich J, Paczia N, Wiechert W, Kohlheyer D, Noack S (2014) Beyond growth rate 0.6: what drives Corynebacterium glutamicum to higher growth rates in defined medium. Biotechnol Bioeng 111(2):359–371

    Article  CAS  PubMed  Google Scholar 

  27. Dusny C, Grunberger A, Probst C, Wiechert W, Kohlheyer D, Schmid A (2015) Technical bias of microcultivation environments on single-cell physiology. Lab Chip 15(8):1822–1834

    Article  CAS  PubMed  Google Scholar 

  28. Dusny C, Schmid A (2015) Challenging biological limits with microfluidic single cell analysis. Microb Biotechnol 8(1):23–25

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Dusny C, Schmid A (2015) Microfluidic single-cell analysis links boundary environments and individual microbial phenotypes. Environ Microbiol 17(6):1839–1856

    Article  PubMed  Google Scholar 

  30. Klumpp S, Hwa T (2014) Bacterial growth: global effects on gene expression, growth feedback and proteome partition. Curr Opin Biotechnol 28:96–102

    Article  CAS  PubMed  Google Scholar 

  31. Klumpp S (2011) Growth-rate dependence reveals design principles of plasmid copy number control. PLoS One 6(5):e20403

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Ullman G, Wallden M, Marklund EG, Mahmutovic A, Razinkov I, Elf J (2013) High-throughput gene expression analysis at the level of single proteins using a microfluidic turbidostat and automated cell tracking. Philos Trans R Soc B 368(1611):20120025

    Article  CAS  Google Scholar 

  33. Klumpp S, Zhang ZG, Hwa T (2009) Growth rate-dependent global effects on gene expression in bacteria. Cell 139(7):1366–1375

    Article  PubMed  PubMed Central  Google Scholar 

  34. Moffitt JR, Lee JB, Cluzel P (2012) The single-cell chemostat: an agarose-based, microfluidic device for high-throughput, single-cell studies of bacteria and bacterial communities. Lab Chip 12(8):1487–1494

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Lee SS, Avalos Vizcarra I, Huberts DH, Lee LP, Heinemann M (2012) Whole lifespan microscopic observation of budding yeast aging through a microfluidic dissection platform. Proc Natl Acad Sci U S A 109(13):4916–4920

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Wang P, Robert L, Pelletier J, Dang WL, Taddei F, Wright A, Jun S (2010) Robust growth of Escherichia coli. Curr Biol 20(12):1099–1103

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Dusny C, Fritzsch FS, Frick O, Schmid A (2012) Isolated microbial single cells and resulting micropopulations grow faster in controlled environments. Appl Environ Microbiol 78(19):7132–7136

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Sweedler JV, Arriaga EA (2007) Single cell analysis. Anal Bioanal Chem 387(1):1–2

    Article  CAS  Google Scholar 

  39. Boulineau S, Tostevin F, Kiviet DJ, ten Wolde PR, Nghe P, Tans SJ (2013) Single-cell dynamics reveals sustained growth during diauxic shifts. PLoS One 8(4):1–9

    Article  CAS  Google Scholar 

  40. Mannik J, Wu F, Hol FJ, Bisicchia P, Sherratt DJ, Keymer JE, Dekker C (2012) Robustness and accuracy of cell division in Escherichia coli in diverse cell shapes. Proc Natl Acad Sci U S A 109(18):6957–6962

    Article  PubMed  PubMed Central  Google Scholar 

  41. Balaban NQ, Merrin J, Chait R, Kowalik L, Leibler S (2004) Bacterial persistence as a phenotypic switch. Science 305(5690):1622–1625

    Article  CAS  PubMed  Google Scholar 

  42. Evans SN, Ralph PL, Schreiber SJ, Sen A (2013) Stochastic population growth in spatially heterogeneous environments. J Math Biol 66(3):423–476

    Article  PubMed  Google Scholar 

  43. Gefen O, Balaban NQ (2009) The importance of being persistent: heterogeneity of bacterial populations under antibiotic stress. FEMS Microbiol Rev 33(4):704–717

    Article  CAS  PubMed  Google Scholar 

  44. Gefen O, Gabay C, Mumcuoglu M, Engel G, Balaban NQ (2008) Single-cell protein induction dynamics reveals a period of vulnerability to antibiotics in persister bacteria. Proc Natl Acad Sci U S A 105(16):6145–6149

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Li B, Qiu Y, Glidle A, Cooper J, Shi H, Yin H (2014) Single cell growth rate and morphological dynamics revealing an "opportunistic" persistence. Analyst 139(13):3305–3313

    Article  CAS  PubMed  Google Scholar 

  46. Lidstrom ME, Konopka MC (2010) The role of physiological heterogeneity in microbial population behavior. Nat Chem Biol 6(10):705–712

    Article  CAS  PubMed  Google Scholar 

  47. Dusny C, Gruenberger A, Probst C, Wiechert W, Kohlheyer D, Schmid A (2015) Technical bias of microcultivation environments on single-cell physiology. Lab Chip 15(8):1822–1834

    Article  CAS  PubMed  Google Scholar 

  48. Bryan AK, Hecht VC, Shen WJ, Payer K, Grover WH, Manalis SR (2014) Measuring single cell mass, volume, and density with dual suspended microchannel resonators. Lab Chip 14(3):569–576

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Bryan AK, Engler A, Gulati A, Manalis SR (2012) Continuous and long-term volume measurements with a commercial coulter counter. PLoS One 7(1):e29866

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Schaechter M (2015) A brief history of bacterial growth physiology. Front Microbiol 6:289

    Article  PubMed  PubMed Central  Google Scholar 

  51. Schaechter M, Williamson JP, Hood Jr JR, Koch AL (1962) Growth, cell and nuclear divisions in some bacteria. J Gen Microbiol 29:421–434

    Article  CAS  PubMed  Google Scholar 

  52. Schaechter M, Maaloe O, Kjeldgaard NO (1958) Dependency on medium and temperature of cell size and chemical composition during balanced growth of Salmonella typhimurium. J Gen Microbiol 19(3):592–606

    Article  CAS  PubMed  Google Scholar 

  53. Kjeldgaard NO, Maaloe O, Schaechter M (1958) The transition between different physiological states during balanced growth of Salmonella typhimurium. J Gen Microbiol 19(3):607–616

    Article  CAS  PubMed  Google Scholar 

  54. Dal Co A, van Vliet S, Ackermann M (2019) Emergent microscale gradients give rise to metabolic cross-feeding and antibiotic tolerance in clonal bacterial populations. Philos Trans R Soc Lond Ser B Biol Sci 374(1786):20190080

    Article  CAS  Google Scholar 

  55. Gruenberger A, Probst C, Heyer A, Wiechert W, Frunzke J, Kohlheyer D (2013) Microfluidic picoliter bioreactor for microbial single-cell analysis: fabrication, system setup, and operation. J Vis Exp JoVE 82:50560

    Google Scholar 

  56. Saeki T, Hosokawa M, Lim TK, Harada M, Matsunaga T, Tanaka T (2014) Digital cell counting device integrated with a single-cell array. PLoS One 9(2):e89011

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Lu H, Caen O, Vrignon J, Zonta E, El Harrak Z, Nizard P, Baret JC, Taly V (2017) High throughput single cell counting in droplet-based microfluidics. Sci Rep 7(1):1366

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Peitz I, van Leeuwen R (2010) Single-cell bacteria growth monitoring by automated DEP-facilitated image analysis. Lab Chip 10(21):2944–2951

    Article  CAS  PubMed  Google Scholar 

  59. Grunberger A, Paczia N, Probst C, Schendzielorz G, Eggeling L, Noack S, Wiechert W, Kohlheyer D (2012) A disposable picolitre bioreactor for cultivation and investigation of industrially relevant bacteria on the single cell level. Lab Chip 12(11):2060–2068

    Article  CAS  PubMed  Google Scholar 

  60. Grunberger A, van Ooyen J, Paczia N, Rohe P, Schiendzielorz G, Eggeling L, Wiechert W, Kohlheyer D, Noack S (2013) Beyond growth rate 0.6: Corynebacterium glutamicum cultivated in highly diluted environments. Biotechnol Bioeng 110(1):220–228

    Article  CAS  PubMed  Google Scholar 

  61. Hammar P, Angermayr SA, Sjostrom SL, van der Meer J, Hellingwerf KJ, Hudson EP, Joensson HN (2015) Single-cell screening of photosynthetic growth and lactate production by cyanobacteria. Biotechnol Biofuels 8:193

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Probst C, Grunberger A, Wiechert W, Kohlheyer D (2013) Microfluidic growth chambers with optical tweezers for full spatial single-cell control and analysis of evolving microbes. J Microbiol Method 95(3):470–476

    Article  Google Scholar 

  63. Probst C, Grunberger A, Wiechert W, Kohlheyer D (2013) Polydimethylsiloxane (PDMS) sub-micron traps for single-cell analysis of bacteria. Micromachines-Basel 4(4):357–369

    Article  Google Scholar 

  64. Harris LK, Theriot JA (2018) Surface area to volume ratio: a natural variable for bacterial morphogenesis. Trends Microbiol 26(10):815–832

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Rosenthal K, Falke F, Frick O, Dusny C, Schmid A (2015) An inert continuous microreactor for the isolation and analysis of a single microbial cell. Micromachines-Basel 6(12):1836–1855

    Article  Google Scholar 

  66. Taheri-Araghi S, Bradde S, Sauls JT, Hill NS, Levin PA, Paulsson J, Vergassola M, Jun S (2015) Cell-size control and homeostasis in bacteria. Curr Biol 25(3):385–391

    Article  CAS  PubMed  Google Scholar 

  67. Wang Z (2019) Cell segmentation for image cytometry: advances, insufficiencies, and challenges. Cytometry A 95(7):708–711

    Article  PubMed  Google Scholar 

  68. Leygeber M, Lindemann D, Sachs CC, Kaganovitch E, Wiechert W, Noh K, Kohlheyer D (2019) Analyzing microbial population heterogeneity-expanding the toolbox of microfluidic single-cell cultivations. J Mol Biol 431(23):4569–4588

    Article  CAS  PubMed  Google Scholar 

  69. Sliusarenko O, Heinritz J, Emonet T, Jacobs-Wagner C (2011) High-throughput, subpixel precision analysis of bacterial morphogenesis and intracellular spatio-temporal dynamics. Mol Microbiol 80(3):612–627

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Garner EC (2011) MicrobeTracker: quantitative image analysis designed for the smallest organisms. Mol Microbiol 80(3):577–579

    Article  CAS  PubMed  Google Scholar 

  71. Campos M, Surovtsev IV, Kato S, Paintdakhi A, Beltran B, Ebmeier SE, Jacobs-Wagner C (2014) A constant size extension drives bacterial cell size homeostasis. Cell 159(6):1433–1446

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Paintdakhi A, Parry B, Campos M, Irnov I, Elf J, Surovtsev I, Jacobs-Wagner C (2016) Oufti: an integrated software package for high-accuracy, high-throughput quantitative microscopy analysis. Mol Microbiol 99(4):767–777

    Article  CAS  PubMed  Google Scholar 

  73. Ducret A, Quardokus EM, Brun YV (2016) MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis. Nat Microbiol 1(7):16077

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Sachs CC, Grunberger A, Helfrich S, Probst C, Wiechert W, Kohlheyer D, Noh K (2016) Image-based single cell profiling: high-throughput processing of mother machine experiments. PLoS One 11(9):e0163453

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Popescu G, Park K, Mir M, Bashir R (2014) New technologies for measuring single cell mass. Lab Chip 14(4):646–652

    Article  CAS  PubMed  Google Scholar 

  76. Popescu G (2008) Quantitative phase imaging of nanoscale cell structure and dynamics. Methods Cell Biol 90:87–115

    Article  PubMed  Google Scholar 

  77. Popescu G, Park Y, Lue N, Best-Popescu C, Deflores L, Dasari RR, Feld MS, Badizadegan K (2008) Optical imaging of cell mass and growth dynamics. Am J Physiol Cell Physiol 295(2):C538–C544

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Phillips KG, Jacques SL, McCarty OJ (2012) Measurement of single cell refractive index, dry mass, volume, and density using a transillumination microscope. Phys Rev Lett 109(11):118105

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Zangle TA, Chun J, Zhang J, Reed J, Teitell MA (2013) Quantification of biomass and cell motion in human pluripotent stem cell colonies. Biophys J 105(3):593–601

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Chun J, Zangle TA, Kolarova T, Finn RS, Teitell MA, Reed J (2012) Rapidly quantifying drug sensitivity of dispersed and clumped breast cancer cells by mass profiling. Analyst 137(23):5495–5498

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Reed J, Troke JJ, Schmit J, Han S, Teitell MA, Gimzewski JK (2008) Live cell interferometry reveals cellular dynamism during force propagation. ACS Nano 2(5):841–846

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Mir M, Wang Z, Shen Z, Bednarz M, Bashir R, Golding I, Prasanth SG, Popescu G (2011) Optical measurement of cycle-dependent cell growth. Proc Natl Acad Sci U S A 108(32):13124–13129

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Cotte Y, Toy F, Jourdain P, Pavillon N, Boss D, Magistretti P, Marquet P, Depeursinge C (2013) Marker-free phase nanoscopy. Nat Photonics 7(2):113–117

    Article  CAS  Google Scholar 

  84. Mir M, Babacan SD, Bednarz M, Do MN, Golding I, Popescu G (2012) Visualizing Escherichia coli sub-cellular structure using sparse deconvolution spatial light interference tomography. PLoS One 7(6):e39816

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Johnson BN, Mutharasan R (2012) Biosensing using dynamic-mode cantilever sensors: a review. Biosens Bioelectron 32(1):1–18

    Article  CAS  PubMed  Google Scholar 

  86. Martinez-Martin D, Flaschner G, Gaub B, Martin S, Newton R, Beerli C, Mercer J, Gerber C, Muller DJ (2017) Inertial picobalance reveals fast mass fluctuations in mammalian cells. Nature 550(7677):500

    Article  CAS  PubMed  Google Scholar 

  87. Godin M, Delgado FF, Son SM, Grover WH, Bryan AK, Tzur A, Jorgensen P, Payer K, Grossman AD, Kirschner MW, Manalis SR (2010) Using buoyant mass to measure the growth of single cells. Nat Methods 7(5):387–390

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Godin M, Bryan AK, Burg TP, Babcock K, Manalis SR (2007) Measuring the mass, density, and size of particles and cells using a suspended microchannel resonator. Appl Phys Lett 91(12):123121

    Article  CAS  Google Scholar 

  89. Son S, Tzur A, Weng Y, Jorgensen P, Kim J, Kirschner MW, Manalis SR (2012) Direct observation of mammalian cell growth and size regulation. Nat Methods 9(9):910–912

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Ilic B, Czaplewski D, Zalalutdinov M, Craighead HG, Neuzil P, Campagnolo C, Batt C (2001) Single cell detection with micromechanical oscillators. J Vac Sci Technol B 19(6):2825–2828

    Article  CAS  Google Scholar 

  91. Weng Y, Delgado FF, Son S, Burg TP, Wasserman SC, Manalis SR (2011) Mass sensors with mechanical traps for weighing single cells in different fluids. Lab Chip 11(24):4174–4180

    Article  CAS  PubMed  Google Scholar 

  92. Zangle TA, Teitell MA (2014) Live-cell mass profiling: an emerging approach in quantitative biophysics. Nat Methods 11(12):1221–1228

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Bryan AK, Goranov A, Amon A, Manalis SR (2010) Measurement of mass, density, and volume during the cell cycle of yeast. Proc Natl Acad Sci U S A 107(3):999–1004

    Article  CAS  PubMed  Google Scholar 

  94. Lewis CL, Craig CC, Senecal AG (2014) Mass and density measurements of live and dead gram-negative and gram-positive bacterial populations. Appl Environ Microbiol 80(12):3622–3631

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Ackermann M (2015) A functional perspective on phenotypic heterogeneity in microorganisms. Nat Rev Microbiol 13(8):497–508

    Article  CAS  PubMed  Google Scholar 

  96. Baumann K, Maurer M, Dragosits M, Cos O, Ferrer P, Mattanovich D (2008) Hypoxic fed-batch cultivation of Pichia pastoris increases specific and volumetric productivity of recombinant proteins. Biotechnol Bioeng 100(1):177–183

    Article  CAS  PubMed  Google Scholar 

  97. Chen BY, You JW, Hsieh YT, Chang JS (2008) Feasibility study of exponential feeding strategy in fed-batch cultures for phenol degradation using Cupriavidus taiwanensis. Biochem Eng J 41(2):175–180

    Article  CAS  Google Scholar 

  98. d'Anjou MC, Daugulis AJ (2000) Mixed-feed exponential feeding for fed-batch culture of recombinant methylotrophic yeast. Biotechnol Lett 22(5):341–346

    Article  CAS  Google Scholar 

  99. Stryhanyuk H, Calabrese F, Kummel S, Musat F, Richnow HH, Musat N (2018) Calculation of single cell assimilation rates from SIP-NanoSIMS-derived isotope ratios: a comprehensive approach. Front Microbiol 9:2342

    Article  PubMed  PubMed Central  Google Scholar 

  100. Sengupta D, Mongersun A, Kim TJ, Mongersun K, von Eyben R, Abbyad P, Pratx G (2019) Multiplexed single-cell measurements of FDG uptake and lactate release using droplet microfluidics. Technol Cancer Res Trans 18

    Google Scholar 

  101. Hehemann JH, Reintjes G, Klassen L, Smith AD, Ndeh D, Arnosti C, Amann R, Abbott DW (2019) Single cell fluorescence imaging of glycan uptake by intestinal bacteria. ISME J 13(7):1883–1889

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Sung Y, Tetrault MA, Takahashi K, Ouyang J, Pratx G, Fakhri GE, Normandin MD (2020) Dependence of fluorodeoxyglucose (FDG) uptake on cell cycle and dry mass: a single-cell study using a multi-modal radiography platform. Sci Rep 10(1):4280

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Achilles J, Muller S, Bley T, Babel W (2004) Affinity of single S. cerevisiae cells to 2-NBDglucose under changing substrate concentrations. Cytom Part A 61A(1):88–98

    Article  CAS  Google Scholar 

  104. VanEngelenburg SB, Palmer AE (2008) Fluorescent biosensors of protein function. Curr Opin Chem Biol 12(1):60–65

    Article  CAS  PubMed  Google Scholar 

  105. Otten J, Tenhaef N, Jansen RP, Dobber J, Jungbluth L, Noack S, Oldiges M, Wiechert W, Pohl M (2019) A FRET-based biosensor for the quantification of glucose in culture supernatants of mL scale microbial cultivations. Microb Cell Factories 18(1)

    Google Scholar 

  106. Fehr M, Frommer WB, Lalonde S (2002) Visualization of maltose uptake in living yeast cells by fluorescent nanosensors. Proc Natl Acad Sci U S A 99(15):9846–9851

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Nikolic N, Barner T, Ackermann M (2013) Analysis of fluorescent reporters indicates heterogeneity in glucose uptake and utilization in clonal bacterial populations. BMC Microbiol 13:258

    Article  PubMed  PubMed Central  Google Scholar 

  108. Musat N, Foster R, Vagner T, Adam B, Kuypers MM (2012) Detecting metabolic activities in single cells, with emphasis on nanoSIMS. FEMS Microbiol Rev 36(2):486–511

    Article  CAS  PubMed  Google Scholar 

  109. Schoffelen NJ, Mohr W, Ferdelman TG, Littmann S, Duerschlag J, Zubkov MV, Ploug H, Kuypers MMM (2018) Single-cell imaging of phosphorus uptake shows that key harmful algae rely on different phosphorus sources for growth. Sci Rep 8

    Google Scholar 

  110. Straeuber H, Huebschmann T, Jehmlich N, Schmidt F, von Bergen M, Harms H, Mueller S (2010) NBDT (3-(N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-3-toluene) – a novel fluorescent dye for studying mechanisms of toluene uptake into vital bacteria. Cytometry A 77(2):113–120

    Google Scholar 

  111. Natarajan A, Srienc F (2000) Glucose uptake rates of single E. coli cells grown in glucose-limited chemostat cultures. J Microbiol Methods 42(1):87–96

    Article  CAS  PubMed  Google Scholar 

  112. Natarajan A, Srienc F (1999) Dynamics of glucose uptake by single Escherichia coli cells. Metab Eng 1(4):320–333

    Article  CAS  PubMed  Google Scholar 

  113. Heuker M, Sijbesma JWA, Suarez RA, de Jong JR, Boersma HH, Luurtsema G, Elsinga PH, Glaudemans AWJM, van Dam GM, van Dijl JM, Slart RHJA, van Oosten M (2017) In vitro imaging of bacteria using F-18-fluorodeoxyglucose micro positron emission tomography. Sci Rep 7:1–9

    Article  CAS  Google Scholar 

  114. Berg J, Hung YP, Yellen G (2009) A genetically encoded fluorescent reporter of ATP:ADP ratio. Nat Methods 6(2):161–166

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Yaginuma H, Kawai S, Tabata KV, Tomiyama K, Kakizuka A, Komatsuzaki T, Noji H, Imamura H (2014) Diversity in ATP concentrations in a single bacterial cell population revealed by quantitative single-cell imaging. Sci Rep 4:6522

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Boersma AJ, Zuhorn IS, Poolman B (2015) A sensor for quantification of macromolecular crowding in living cells. Nat Methods 12(3):227–229

    Article  CAS  PubMed  Google Scholar 

  117. Ha JS, Song JJ, Lee YM, Kim SJ, Sohn JH, Shin CS, Lee SG (2007) Design and application of highly responsive fluorescence resonance energy transfer biosensors for detection of sugar in living Saccharomyces cerevisiae cells. Appl Environ Microbiol 73(22):7408–7414

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Kaper T, Lager I, Looger LL, Chermak D, Frommer WB (2008) Fluorescence resonance energy transfer sensors for quantitative monitoring of pentose and disaccharide accumulation in bacteria. Biotechnol Biofuels 1(1):11

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Nikolic N, Schreiber F, Dal Co A, Kiviet DJ, Bergmiller T, Littmann S, Kuypers MMM, Ackermann M (2017) Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations. PLoS Genet 13(12):e1007122

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Worrich A, Stryhanyuk H, Musat N, Konig S, Banitz T, Centler F, Frank K, Thullner M, Harms H, Richnow HH, Miltner A, Kastner M, Wick LY (2017) Mycelium-mediated transfer of water and nutrients stimulates bacterial activity in dry and oligotrophic environments. Nat Commun 8:1–9

    Article  CAS  Google Scholar 

  121. Kopf SH, McGlynn SE, Green-Saxena A, Guan YB, Newman DK, Orphan VJ (2015) Heavy water and N-15 labelling with NanoSIMS analysis reveals growth rate-dependent metabolic heterogeneity in chemostats. Environ Microbiol 17(7):2542–2556

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Lindemann D, Westerwalbesloh C, Kohlheyer D, Grunberger A, von Lieres E (2019) Microbial single-cell growth response at defined carbon limiting conditions. RSC Adv 9(25):14040–14050

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Binder D, Drepper T, Jaeger KE, Delvigne F, Wiechert W, Kohlheyer D, Grunberger A (2017) Homogenizing bacterial cell factories: analysis and engineering of phenotypic heterogeneity. Metab Eng 42:145–156

    Article  CAS  PubMed  Google Scholar 

  124. Xiao Y, Bowen CH, Liu D, Zhang F (2016) Exploiting nongenetic cell-to-cell variation for enhanced biosynthesis. Nat Chem Biol 12(5):339–344

    Article  CAS  PubMed  Google Scholar 

  125. Manafi M, Kneifel W, Bascomb S (1991) Fluorogenic and chromogenic substrates used in bacterial diagnostics. Microbiol Rev 55(3):335–348

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Binder S, Schendzielorz G, Stabler N, Krumbach K, Hoffmann K, Bott M, Eggeling L (2012) A high-throughput approach to identify genomic variants of bacterial metabolite producers at the single-cell level. Genome Biol 13(5):R40

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Schendzielorz G, Dippong M, Grunberger A, Kohlheyer D, Yoshida A, Binder S, Nishiyama C, Nishiyama M, Bott M, Eggeling L (2013) Taking control over control: use of product sensing in single cells to remove flux control at key enzymes in biosynthesis pathways. ACS Synth Biol 3:21–29

    Article  CAS  PubMed  Google Scholar 

  128. Love KR, Panagiotou V, Jiang B, Stadheim TA, Love JC (2010) Integrated single-cell analysis shows Pichia pastoris secretes protein stochastically. Biotechnol Bioeng 106(2):319–325

    PubMed  Google Scholar 

  129. Love KR, Politano TJ, Panagiotou V, Jiang B, Stadheim TA, Love JC (2012) Systematic single-cell analysis of Pichia pastoris reveals secretory capacity limits productivity. PLoS One 7(6):e37915

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Mazutis L, Gilbert J, Ung WL, Weitz DA, Griffiths AD, Heyman JA (2013) Single-cell analysis and sorting using droplet-based microfluidics. Nat Protoc 8(5):870–891

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Wang BL, Ghaderi A, Zhou H, Agresti J, Weitz DA, Fink GR, Stephanopoulos G (2014) Microfluidic high-throughput culturing of single cells for selection based on extracellular metabolite production or consumption. Nat Biotechnol 32(5):473–478

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. El Debs B, Utharala R, Balyasnikova IV, Griffiths AD, Merten CA (2012) Functional single-cell hybridoma screening using droplet-based microfluidics. Proc Natl Acad Sci U S A 109(29):11570–11575

    Article  PubMed  PubMed Central  Google Scholar 

  133. Sjostrom SL, Bai Y, Huang M, Liu Z, Nielsen J, Joensson HN, Andersson Svahn H (2014) High-throughput screening for industrial enzyme production hosts by droplet microfluidics. Lab Chip 14(4):806–813

    Article  CAS  PubMed  Google Scholar 

  134. Prodanovic R, Ung WL, Durdic KI, Fischer R, Weitz DA, Ostafe R (2020) A high-throughput screening system based on droplet microfluidics for glucose oxidase gene libraries. Molecules 25(10):2418

    Article  CAS  PubMed Central  Google Scholar 

  135. Amantonico A, Urban PL, Zenobi R (2010) Analytical techniques for single-cell metabolomics: state of the art and trends. Anal Bioanal Chem 398:2493–2504

    Article  CAS  PubMed  Google Scholar 

  136. Heinemann M, Zenobi R (2011) Single cell metabolomics. Curr Opin Biotechnol 22(1):26–31

    Article  CAS  PubMed  Google Scholar 

  137. Zenobi R (2013) Single-cell metabolomics: analytical and biological perspectives. Science 342(6163):1201–1211

    Article  CAS  Google Scholar 

  138. Dusny C, Lohse M, Reemtsma T, Schmid A, Lechtenfeld OJ (2019) Quantifying a biocatalytic product from a few living microbial cells using microfluidic cultivation coupled to FT-ICR-MS. Anal Chem 91(11):7012–7018

    Article  CAS  PubMed  Google Scholar 

  139. Fritzsch FS, Rosenthal K, Kampert A, Howitz S, Dusny C, Blank LM, Schmid A (2013) Picoliter nDEP traps enable time-resolved contactless single bacterial cell analysis in controlled microenvironments. Lab Chip 13(3):397–408

    Article  CAS  PubMed  Google Scholar 

  140. Kortmann H, Chasanis P, Blank LM, Franzke J, Kenig E, Schmid A (2009) The envirostat – a new bioreactor concept. Lab Chip 9(4):576–585

    Article  CAS  PubMed  Google Scholar 

  141. Haidas D, Bachler S, Kohler M, Blank LM, Zenobi R, Dittrich PS (2019) Microfluidic platform for multimodal analysis of enzyme secretion in nanoliter droplet arrays. Anal Chem 91(3):2066–2073

    Article  CAS  PubMed  Google Scholar 

  142. Haidas D, Napiorkowska M, Schmitt S, Dittrich PS (2020) Parallel sampling of nanoliter droplet arrays for noninvasive protein analysis in discrete yeast cultivations by MALDI-MS. Anal Chem 92(5):3810–3818

    Article  CAS  PubMed  Google Scholar 

  143. Ibanez AJ, Fagerer SR, Schmidt AM, Urban PL, Jefimovs K, Geiger P, Dechant R, Heinemann M, Zenobi R (2013) Mass spectrometry-based metabolomics of single yeast cells. Proc Natl Acad Sci U S A 110(22):8790–8794

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. Urban PL, Schmidt AM, Fagerer SR, Amantonico A, Ibanez A, Jefimovs K, Heinemann M, Zenobi R (2011) Carbon13 labelling strategy for studying the ATP metabolism in individual yeast cells by micro-arrays for mass spectrometry. Mol BioSyst 7(10):2837–2840

    Article  CAS  PubMed  Google Scholar 

  145. Elowitz MB, Levine AJ, Siggia ED, Swain PS (2002) Stochastic gene expression in a single cell. Science 297(5584):1183–1186

    Article  CAS  PubMed  Google Scholar 

  146. Ozbudak EM, Thattai M, Kurtser I, Grossman AD, van Oudenaarden A (2002) Regulation of noise in the expression of a single gene. Nat Genet 31(1):69–73

    Article  CAS  PubMed  Google Scholar 

  147. Swain PS, Elowitz MB, Siggia ED (2002) Intrinsic and extrinsic contributions to stochasticity in gene expression. Proc Natl Acad Sci U S A 99(20):12795–12800

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Meng TC, Somani S, Dhar P (2004) Modeling and simulation of biological systems with stochasticity. In Silico Biol 4(3):293–309

    CAS  PubMed  Google Scholar 

  149. Thattai M, van Oudenaarden A (2004) Stochastic gene expression in fluctuating environments. Genetics 167(1):523–530

    Article  PubMed  PubMed Central  Google Scholar 

  150. Kaern M, Elston TC, Blake WJ, Collins JJ (2005) Stochasticity in gene expression: from theories to phenotypes. Nat Rev Genet 6(6):451–464

    Article  CAS  PubMed  Google Scholar 

  151. Kussell E, Leibler S (2005) Phenotypic diversity, population growth, and information in fluctuating environments. Science 309(5743):2075–2078

    Article  CAS  PubMed  Google Scholar 

  152. Raser JM, O'Shea EK (2005) Noise in gene expression: origins, consequences, and control. Science 309(5743):2010–2013

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  153. Yu J, Xiao J, Ren XJ, Lao KQ, Xie XS (2006) Probing gene expression in live cells, one protein molecule at a time. Science (New York, NY) 311(5767):1600–1603

    Article  CAS  Google Scholar 

  154. Lindmeyer M, Jahn M, Vorpahl C, Muller S, Schmid A, Buhler B (2015) Variability in subpopulation formation propagates into biocatalytic variability of engineered Pseudomonas putida strains. Front Microbiol 6:1042

    Article  PubMed  PubMed Central  Google Scholar 

  155. Nikel PI, Silva-Rocha R, Benedetti I, de Lorenzo V (2014) The private life of environmental bacteria: pollutant biodegradation at the single cell level. Environ Microbiol 16(3):628–642

    Article  CAS  PubMed  Google Scholar 

  156. Gefen O, Fridman O, Ronin I, Balaban NQ (2014) Direct observation of single stationary-phase bacteria reveals a surprisingly long period of constant protein production activity. Proc Natl Acad Sci U S A 111(1):556–561

    Article  CAS  PubMed  Google Scholar 

  157. Stricker J, Maddox P, Salmon ED, Erickson HP (2002) Rapid assembly dynamics of the Escherichia coli FtsZ-ring demonstrated by fluorescence recovery after photobleaching. Proc Natl Acad Sci U S A 99(5):3171–3175

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  158. Dai J, Yoon SH, Sim HY, Yang YS, Oh TK, Kim JF, Hong JW (2013) Charting microbial phenotypes in multiplex nanoliter batch bioreactors. Anal Chem 85(12):5892–5899

    Article  CAS  PubMed  Google Scholar 

  159. Sun YQ, Casella S, Fang Y, Huang F, Faulkner M, Barrett S, Liu LN (2016) Light modulates the biosynthesis and organization of cyanobacterial carbon fixation machinery through photosynthetic electron flow. Plant Physiol 171(1):530–541

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. Long ZC, Olliver A, Brambilla E, Sclavi B, Lagomarsino MC, Dorfman KD (2014) Measuring bacterial adaptation dynamics at the single-cell level using a microfluidic chemostat and time-lapse fluorescence microscopy. Analyst 139(20):5254–5262

    Article  CAS  PubMed  Google Scholar 

  161. Kimmerling RJ, Prakadan SM, Gupta AJ, Calistri NL, Stevens MM, Olcum S, Cermak N, Drake RS, Pelton K, De Smet F, Ligon KL, Shalek AK, Manalis SR (2018) Linking single-cell measurements of mass, growth rate, and gene expression. Genome Biol 19(1):207

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  162. Friedman N, Vardi S, Ronen M, Alon U, Stavans J (2005) Precise temporal modulation in the response of the SOS DNA repair network in individual bacteria. PLoS Biol 3(7):e238

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  163. Bennett MR, Hasty J (2009) Microfluidic devices for measuring gene network dynamics in single cells. Nat Rev Genet 10(9):628–638

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Ma Z, Chu PM, Su Y, Yu Y, Wen H, Fu X, Huang S (2019) Applications of single-cell technology on bacterial analysis. Quant Biol 7(3):171–181

    Article  CAS  Google Scholar 

  165. Stratz S, Eyer K, Kurth F, Dittrich PS (2014) On-chip enzyme quantification of single Escherichia coli bacteria by immunoassay-based analysis. Anal Chem 86(24):12375–12381

    Article  CAS  PubMed  Google Scholar 

  166. Dusny C, Schmid A (2016) The MOX promoter in Hansenula polymorpha is ultrasensitive to glucose-mediated carbon catabolite repression. FEMS Yeast Res 16(6):fow067

    Article  CAS  PubMed  Google Scholar 

  167. Taheri-Araghi S, Brown SD, Sauls JT, McIntosh DB, Jun S (2015) Single-cell physiology. Annu Rev Biophys 44:123–142

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  168. Langdahl BR, Ingvorsen K (1997) Temperature characteristics of bacterial iron solubilisation and C-14 assimilation in naturally exposed sulfide ore material at Citronen fjord, North Greenland (83 degrees N). FEMS Microbiol Ecol 23(4):275–283

    Article  CAS  Google Scholar 

  169. Zipfel WR, Williams RM, Webb WW (2003) Nonlinear magic: multiphoton microscopy in the biosciences. Nat Biotechnol 21(11):1369–1377

    Article  CAS  PubMed  Google Scholar 

  170. Davies MJ (2004) Reactive species formed on proteins exposed to singlet oxygen. Photochem Photobiol Sci 3(1):17–25

    Article  CAS  PubMed  Google Scholar 

  171. Merbt SN, Stahl DA, Casamayor EO, Marti E, Nicol GW, Prosser JI (2012) Differential photoinhibition of bacterial and archaeal ammonia oxidation. FEMS Microbiol Lett 327(1):41–46

    Article  CAS  PubMed  Google Scholar 

  172. Woodward JR, Cirillo VP, Edmunds LN (1978) Light effects in yeast – inhibition by visible light of growth and transport in Saccharomyces cerevisiae grown at low temperatures. J Bacteriol 133(2):692–698

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  173. Tinevez JY, Dragavon J, Baba-Aissa L, Roux P, Perret E, Canivet A, Galy V, Shorte S (2012) A quantitative method for measuring phototoxicity of a live cell imaging microscope. Method Enzymol 506:291–309

    Article  CAS  Google Scholar 

  174. Jun S, Taheri-Araghi S (2015) Cell-size maintenance: universal strategy revealed. Trends Microbiol 23(1):4–6

    Article  CAS  PubMed  Google Scholar 

  175. Frigault MM, Lacoste J, Swift JL, Brown CM (2009) Live-cell microscopy – tips and tools. J Cell Sci 122(Pt 6):753–767

    Article  CAS  PubMed  Google Scholar 

  176. Dixit R, Cyr R (2003) Cell damage and reactive oxygen species production induced by fluorescence microscopy: effect on mitosis and guidelines for non-invasive fluorescence microscopy. Plant J 36(2):280–290

    Article  CAS  PubMed  Google Scholar 

  177. Hebisch E, Knebel J, Landsberg J, Frey E, Leisner M (2013) High variation of fluorescence protein maturation times in closely related Escherichia coli strains. PLoS One 8(10):e75991

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  178. Andersen JB, Sternberg C, Poulsen LK, Bjorn SP, Givskov M, Molin S (1998) New unstable variants of green fluorescent protein for studies of transient gene expression in bacteria. Appl Environ Microbiol 64(6):2240–2246

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  179. McGinness KE, Baker TA, Sauer RT (2006) Engineering controllable protein degradation. Mol Cell 22(5):701–707

    Article  CAS  PubMed  Google Scholar 

  180. Terai T, Nagano T (2013) Small-molecule fluorophores and fluorescent probes for bioimaging. Pflugers Arch 465(3):347–359

    Article  CAS  PubMed  Google Scholar 

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Dusny, C. (2020). Microfluidic Single-Cell Analytics. In: Bahnemann, J., Grünberger, A. (eds) Microfluidics in Biotechnology. Advances in Biochemical Engineering/Biotechnology, vol 179. Springer, Cham. https://doi.org/10.1007/10_2020_134

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