1932

Abstract

Microfluidics has proven to be a key tool in quantitative biological research. The research community in particular has developed a variety of microfluidic platforms to investigate sensory systems, development, aging, and physiology of the nematode. Critical for the growth of this field, however, has been the implementation of concurrent advanced microscopy, hardware, and software technologies that enable the discovery of novel biology. In this review, we highlight recent innovations in microfluidic platforms used for assaying and discuss the novel technological approaches and analytic strategies required for these systems. We conclude that platforms that provide analytical frameworks for assaying specific biological mechanisms and those that take full advantage of integrated technologies to extract high-value quantitative information from worm assays are most likely to move the field forward.

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2018-06-12
2024-04-27
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Literature Cited

  1. 1.  Whitesides GM 2006. The origins and the future of microfluidics. Nature 442:368–73
    [Google Scholar]
  2. 2.  Duffy DC, McDonald JC, Schueller OJA, Whitesides GM 1998. Rapid prototyping of microfluidic systems in poly(dimethylsiloxane). Anal. Chem. 70:4974–84
    [Google Scholar]
  3. 3.  McDonald JC, Duffy DC, Anderson JR, Chiu DT, Wu HK et al. 2000. Fabrication of microfluidic systems in poly(dimethylsiloxane). Electrophoresis 21:27–40
    [Google Scholar]
  4. 4.  Qin D, Xia Y, Whitesides GM 2010. Soft lithography for micro- and nanoscale patterning. Nat. Protoc. 5:491–502
    [Google Scholar]
  5. 5.  Beebe DJ, Mensing GA, Walker GM 2002. Physics and applications of microfluidics in biology. Annu. Rev. Biomed. Eng. 4:261–86
    [Google Scholar]
  6. 6.  Sackmann EK, Fulton AL, Beebe DJ 2014. The present and future role of microfluidics in biomedical research. Nature 507:181–89
    [Google Scholar]
  7. 7.  San-Miguel A, Lu H 2013. Microfluidics as a tool for C. elegans research. WormBook The C. elegans Research Community. WormBook. http://www.wormbook.org
    [Google Scholar]
  8. 8.  Corsi AK, Wightman B, Chalfie M 2015. A transparent window into biology: a primer on Caenorhabditis elegans. WormBook The C. elegans Research Community. WormBook. http://www.wormbook.org
    [Google Scholar]
  9. 9.  Brenner S 1974. The genetics of Caenorhabditis elegans. . Genetics 77:71–94
    [Google Scholar]
  10. 10.  Riddle DL, Blumenthal T, Meyer BJ, Priess JR 1997. Introduction to C. elegans. C. elegans II DL Riddle, T Blumenthal, BJ Meyer 1–23 Cold Spring Harbor, NY: JR Priess
    [Google Scholar]
  11. 11.  Stiernagle T 2006. Maintenance of C. elegans. WormBook The C. elegans Research Community. WormBook. http://www.wormbook.org
    [Google Scholar]
  12. 12.  Chung K, Crane MM, Lu H 2008. Automated on-chip rapid microscopy, phenotyping and sorting of C. . elegans. Nat. Methods 5:637–43
    [Google Scholar]
  13. 13.  Chronis N, Zimmer M, Bargmann CI 2007. Microfluidics for in vivo imaging of neuronal and behavioral activity in Caenorhabditis elegans. . Nat. Methods 4:727–31
    [Google Scholar]
  14. 14.  Zhang Y, Lu H, Bargmann CI 2005. Pathogenic bacteria induce aversive olfactory learning in Caenorhabditis elegans. . Nature 438:179–84
    [Google Scholar]
  15. 15.  Hulme SE, Shevkoplyas SS, Samuel A 2008. Microfluidics: streamlining discovery in worm biology. Nat. Methods 5:589–90
    [Google Scholar]
  16. 16.  Chronis N 2010. Worm chips: microtools for C. elegans biology. Lab Chip 10:432–37
    [Google Scholar]
  17. 17.  Bakhtina NA, Korvink JG 2014. Microfluidic laboratories for C. elegans enhance fundamental studies in biology. RSC Adv 4:4691–709
    [Google Scholar]
  18. 18.  Lockery SR, Lawton KJ, Doll JC, Faumont S, Coulthard SM et al. 2008. Artificial dirt: microfluidic substrates for nematode neurobiology and behavior. J. Neurophysiol. 99:3136–43
    [Google Scholar]
  19. 19.  Crane MM, Chung K, Stirman J, Lu H 2010. Microfluidics-enabled phenotyping, imaging, and screening of multicellular organisms. Lab Chip 10:1509–17
    [Google Scholar]
  20. 20.  McCormick KE, Gaertner BE, Sottile M, Phillips PC, Lockery SR 2011. Microfluidic devices for analysis of spatial orientation behaviors in semi-restrained Caenorhabditis elegans. . PLOS ONE 6:e25710
    [Google Scholar]
  21. 21.  Hwang H, Lu H 2013. Microfluidic tools for developmental studies of small model organisms—nematodes, fruit flies, and zebrafish. Biotechnol. J. 8:192–205
    [Google Scholar]
  22. 22.  Aubry G, Lu H 2014. A perspective on optical developments in microfluidic platforms for Caenorhabditis elegans research. Biomicrofluidics 8:011301
    [Google Scholar]
  23. 23.  O'Reilly LP, Luke CJ, Perlmutter DH, Silverman GA, Pak SC 2014. C. elegans in high-throughput drug discovery. Adv. Drug Deliv. Rev. 69–70:247–53
    [Google Scholar]
  24. 24.  Levario TJ, Lim B, Shvartsman SY, Lu H 2016. Microfluidics for high-throughput quantitative studies of early development. Annu. Rev. Biomed. Eng. 18:285–309
    [Google Scholar]
  25. 25.  Porto DA, Rouse TM, San-Miguel A, Lu H 2016. Microfluidic Platforms for Quantitative Biology Studies in Model Organisms C Lu, SS Verbridge 1–18 Cham, Switz.: Springer Intl.
  26. 26.  Gupta B, Rezai P 2016. Microfluidic approaches for manipulating, imaging, and screening C. . elegans. Micromachines 7:123–23
    [Google Scholar]
  27. 27.  Shanmugam MM, Santra TS 2016. Microfluidic devices in advanced Caenorhabditis elegans research. Molecules 21:1006
    [Google Scholar]
  28. 28.  Cornaglia M, Lehnert T, Gijs MAM 2017. Microfluidic systems for high-throughput and high-content screening using the nematode Caenorhabditis elegans. . Lab Chip 22:3736–59
    [Google Scholar]
  29. 29.  Erickson D, Li DQ 2004. Integrated microfluidic devices. Anal. Chim. Acta 507:11–26
    [Google Scholar]
  30. 30.  Kuswandi B, Nuriman, Huskens J, Verboom W 2007. Optical sensing systems for microfluidic devices: a review. Anal. Chim. Acta 601:141–55
    [Google Scholar]
  31. 31.  Megason SG, Fraser SE 2007. Imaging in systems biology. Cell 130:784–95
    [Google Scholar]
  32. 32.  Tarca AL, Carey VJ, Chen XW, Romero R, Draghici S 2007. Machine learning and its applications to biology. PLOS Comput. Biol. 3:e116
    [Google Scholar]
  33. 33.  Danuser G 2011. Computer vision in cell biology. Cell 147:973–78
    [Google Scholar]
  34. 34.  Wu J, Zheng G, Lee LM 2012. Optical imaging techniques in microfluidics and their applications. Lab Chip 12:3566–75
    [Google Scholar]
  35. 35.  Choi JR, Song H, Sung JH, Kim D, Kim K 2016. Microfluidic assay-based optical measurement techniques for cell analysis: a review of recent progress. Biosens. Bioelectron. 77:227–36
    [Google Scholar]
  36. 36.  White JG, Southgate E, Thomson JN, Brenner S 1986. The structure of the nervous system of the nematode Caenorhabditis elegans. . Philos. Trans. R. Soc. B 314:1–340
    [Google Scholar]
  37. 37.  Emmons SW 2015. The beginning of connectomics: a commentary on White et al. 1986 ‘The structure of the nervous system of the nematode Caenorhabditis elegans’. Philos. Trans. R. Soc. B 370:20140309
    [Google Scholar]
  38. 38.  Kerr R, Lev-Ram V, Baird G, Vincent P, Tsien RY, Schafer WR 2000. Optical imaging of calcium transients in neurons and pharyngeal muscle of C. . elegans. Neuron 26:583–94
    [Google Scholar]
  39. 39.  Tian L, Hires SA, Mao T, Huber D, Chiappe ME et al. 2009. Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators. Nat. Methods 6:875–81
    [Google Scholar]
  40. 40.  Akerboom J, Chen TW, Wardill TJ, Tian L, Marvin JS et al. 2012. Optimization of a GCaMP calcium indicator for neural activity imaging. J. Neurosci. 32:13819–40
    [Google Scholar]
  41. 41.  Bargmann CI 2006. Chemosensation in C. elegans. WormBook The C. elegans Research Community. WormBook. http://www.wormbook.org
    [Google Scholar]
  42. 42.  Goodman MB 2006. Mechanosensation. WormBook The C. elegans Research Community. WormBook. http://www.wormbook.org
    [Google Scholar]
  43. 43.  Chalasani SH, Chronis N, Tsunozaki M, Gray JM, Ramot D et al. 2007. Dissecting a circuit for olfactory behaviour in Caenorhabditis elegans. . Nature 450:63–70
    [Google Scholar]
  44. 44.  Chokshi TV, Bazopoulou D, Chronis N 2010. An automated microfluidic platform for calcium imaging of chemosensory neurons in Caenorhabditis elegans. . Lab Chip 10:2758–63
    [Google Scholar]
  45. 45.  Kato S, Xu Y, Cho CE, Abbott LF, Bargmann CI 2014. Temporal responses of C. elegans chemosensory neurons are preserved in behavioral dynamics. Neuron 81:616–28
    [Google Scholar]
  46. 46.  Bazopoulou D, Chaudhury AR, Pantazis A, Chronis N 2017. An automated compound screening for anti-aging effects on the function of C. elegans sensory neurons. Sci. Rep. 7:9403
    [Google Scholar]
  47. 47.  Albrecht DR, Bargmann CI 2011. High-content behavioral analysis of Caenorhabditis elegans in precise spatiotemporal chemical environments. Nat. Methods 8:599–605
    [Google Scholar]
  48. 48.  Larsch J, Ventimiglia D, Bargmann CI, Albrecht DR 2013. High-throughput imaging of neuronal activity in Caenorhabditis elegans. . PNAS 110:E4266–73
    [Google Scholar]
  49. 49.  Larsch J, Flavell SW, Liu Q, Gordus A, Albrecht DR, Bargmann CI 2015. A circuit for gradient climbing in C. elegans chemotaxis. Cell Rep 12:1748–60
    [Google Scholar]
  50. 50.  Zimmer M, Gray JM, Pokala N, Chang AJ, Karow DS et al. 2009. Neurons detect increases and decreases in oxygen levels using distinct guanylate cyclases. Neuron 61:865–79
    [Google Scholar]
  51. 51.  Schrödel T, Prevedel R, Aumayr K, Zimmer M, Vaziri A 2013. Brain-wide 3D imaging of neuronal activity in Caenorhabditis elegans with sculpted light. Nat. Methods 10:1013–20
    [Google Scholar]
  52. 52.  Kato S, Kaplan HS, Schrödel T, Skora S, Lindsay TH et al. 2015. Global brain dynamics embed the motor command sequence of Caenorhabditis elegans. . Cell 163:656–69
    [Google Scholar]
  53. 53.  Nichols ALA, Eichler T, Latham R, Zimmer M 2017. A global brain state underlies C. elegans sleep behavior. Science 356:eeam6851
    [Google Scholar]
  54. 54.  Sulston J, Dew M, Brenner S 1975. Dopaminergic neurons in the nematode Caenorhabditis elegans. . J. Comp. Neurol. 163:215–26
    [Google Scholar]
  55. 55.  Chalfie M, Sulston J 1981. Developmental genetics of the mechanosensory neurons of Caenorhabditis elegans. . Dev. Biol. 82:358–70
    [Google Scholar]
  56. 56.  Chalfie M, Sulston JE, White JG, Southgate E, Thomson JN, Brenner S 1985. The neural circuit for touch sensitivity in Caenorhabditis elegans. . J. Neurosci. 5:956–64
    [Google Scholar]
  57. 57.  Way JC, Chalfie M 1989. The mec-3 gene of Caenorhabditis elegans requires its own product for maintained expression and is expressed in three neuronal cell types. Genes Dev 3:1823–33
    [Google Scholar]
  58. 58.  Li W, Kang L, Piggott BJ, Feng Z, Xu XZ 2011. The neural circuits and sensory channels mediating harsh touch sensation in Caenorhabditis elegans. . Nat. Commun. 2:315
    [Google Scholar]
  59. 59.  Chalfie M, Sulston J 1981. Developmental genetics of the mechanosensory neurons of Caenorhabditis elegans. . Dev. Biol. 82:358–70
    [Google Scholar]
  60. 60.  Chalfie M, Hart AC, Rankin CH, Goodman MB 2014. Assaying mechanosensation. WormBook The C. elegans Research Community. WormBook. http://www.wormbook.org
    [Google Scholar]
  61. 61.  Park SJ, Goodman MB, Pruitt BL 2007. Analysis of nematode mechanics by piezoresistive displacement clamp. PNAS 104:17376–81
    [Google Scholar]
  62. 62.  Park SJ, Petzold BC, Goodman MB, Pruitt BL 2011. Piezoresistive cantilever force-clamp system. Rev. Sci. Instrum. 82:043703
    [Google Scholar]
  63. 63.  Petzold BC, Park SJ, Mazzochette EA, Goodman MB, Pruitt BL 2013. MEMS-based force-clamp analysis of the role of body stiffness in C. elegans touch sensation. Integr. Biol. 5:853–64
    [Google Scholar]
  64. 64.  Cho Y, Porto DA, Hwang H, Grundy LJ, Schafer WR, Lu H 2017. Automated and controlled mechanical stimulation and functional imaging in vivo in C. . elegans. Lab Chip 17:2609–18
    [Google Scholar]
  65. 65.  Nekimken AL, Fehlauer H, Kim AA, Manosalvas-Kjono SN, Ladpli P et al. 2017. Pneumatic stimulation of C. elegans mechanoreceptor neurons in a microfluidic trap. Lab Chip 17:1116–27
    [Google Scholar]
  66. 66.  Collins JJ, Huang C, Hughes S, Kornfeld K 2008. The measurement and analysis of age-related changes in Caenorhabditis elegans. WormBook The C. elegans Research Community. WormBook. http://www.wormbook.org
    [Google Scholar]
  67. 67.  Krajniak J, Lu H 2010. Long-term high-resolution and culture of C. elegans in chip-gel hybrid microfluidic device for developmental studies. Lab Chip 10:1862–68
    [Google Scholar]
  68. 68.  Chung K, Kim Y, Kanodia JS, Gong E, Shvartsman SY, Lu H 2011. A microfluidic array for large-scale ordering and orientation of embryos. Nat. Methods 8:171–76
    [Google Scholar]
  69. 69.  Cornaglia M, Mouchiroud L, Marette A, Narasimhan S, Lehnert T et al. 2015. An automated microfluidic platform for C. elegans embryo arraying, phenotyping, and long-term live imaging. Sci. Rep. 5:10192
    [Google Scholar]
  70. 70.  Uppaluri S, Brangwynne CP 2015. A size threshold governs Caenorhabditis elegans developmental progression. Proc. R. Soc. B 282:20151283
    [Google Scholar]
  71. 71.  Cornaglia M, Krishnamani G, Mouchiroud L, Sorrentino V, Lehnert T et al. 2016. Automated longitudinal monitoring of in vivo protein aggregation in neurodegenerative disease C. elegans models. Mol. Neurodegener. 11:17
    [Google Scholar]
  72. 72.  Gritti N, Kienle S, Filina O, van Zon JS 2016. Long-term time-lapse microscopy of C. elegans post-embryonic development. Nat. Commun. 7:12500
    [Google Scholar]
  73. 73.  Keil W, Kutscher LM, Shaham S, Siggia ED, Cooper RC et al. 2017. Long-term high-resolution imaging of developing C. elegans larvae with microfluidics. Dev. Cell 40:202–14
    [Google Scholar]
  74. 74.  Sutphin GL, Kaeberlein M 2009. Measuring Caenorhabditis elegans life span on solid media. J. Vis. Exp. 27:1152
    [Google Scholar]
  75. 75.  Solis GM, Petrascheck M 2011. Measuring Caenorhabditis elegans life span in 96 well microtiter plates. J. Vis. Exp. 49:2496
    [Google Scholar]
  76. 76.  Vanfleteren JR, Braeckman BP 1999. Mechanisms of life span determination in Caenorhabditis elegans. . Neurobiol. Aging 20:487–502
    [Google Scholar]
  77. 77.  Lithgow GJ, Driscoll M, Phillips P 2017. A long journey to reproducible results. Nature 548:387–88
    [Google Scholar]
  78. 78.  Lucanic M, Plummer WT, Chen E, Harke J, Foulger AC et al. 2017. Impact of genetic background and experimental reproducibility on identifying chemical compounds with robust longevity effects. Nat. Commun. 8:14256
    [Google Scholar]
  79. 79.  Hulme SE, Shevkoplyas SS, McGuigan AP, Apfeld J, Fontana W, Whitesides GM 2010. Life span-on-a-chip: microfluidic chambers for performing lifelong observation of C. . elegans. Lab Chip 10:589–97
    [Google Scholar]
  80. 80.  Dong L, Cornaglia M, Lehnert T, Gijs MAM 2016. On-chip microfluidic biocommunication assay for studying male-induced demise in C. elegans hermaphrodites. Lab Chip 16:4534–45
    [Google Scholar]
  81. 81.  Maures TJ, Booth LN, Benayoun BA, Izrayelit Y, Schroeder FC, Brunet A 2014. Males shorten the life span of C. elegans hermaphrodites via secreted compounds. Science 343:541–44
    [Google Scholar]
  82. 82.  Wen H, Shi W, Qin J 2012. Multiparameter evaluation of the longevity in C. elegans under stress using an integrated microfluidic device. Biomed. Microdevices 14:721–28
    [Google Scholar]
  83. 83.  Harada H, Kurauchi M, Hayashi R, Eki T 2007. Shortened life span of nematode Caenorhabditis elegans after prolonged exposure to heavy metals and detergents. Ecotoxicol. Environ. Safety 66:378–83
    [Google Scholar]
  84. 84.  Wen H, Gao X, Qin J 2014. Probing the anti-aging role of polydatin in Caenorhabditis elegans on a chip. Integr. Biol. 6:35–43
    [Google Scholar]
  85. 85.  Xian B, Shen J, Chen W, Sun N, Qiao N et al. 2013. WormFarm: a quantitative control and measurement device toward automated Caenorhabditis elegans aging analysis. Aging Cell 12:398–409
    [Google Scholar]
  86. 86.  Stroustrup N, Ulmschneider BE, Nash ZM, Lopez-Moyado IF, Apfeld J, Fontana W 2013. The Caenorhabditis elegans lifespan machine. Nat. Methods 10:665–70
    [Google Scholar]
  87. 87.  Zhang WB, Sinha DB, Pittman WE, Hvatum E, Stroustrup N, Pincus Z 2016. Extended twilight among isogenic C. elegans causes a disproportionate scaling between life span and health. Cell Syst 3:333–45.e4
    [Google Scholar]
  88. 88.  Churgin MA, Jung SK, Yu CC, Chen X, Raizen DM, Fang-Yen C 2017. Longitudinal imaging of Caenorhabditis elegans in a microfabricated device reveals variation in behavioral decline during aging. eLife 6:e26652
    [Google Scholar]
  89. 89.  Stroustrup N, Anthony WE, Nash ZM, Gowda V, Gomez A et al. 2016. The temporal scaling of Caenorhabditis elegans ageing. Nature 530:103–7
    [Google Scholar]
  90. 90.  Hughes SE, Evason K, Xiong C, Kornfeld K 2007. Genetic and pharmacological factors that influence reproductive aging in nematodes. PLOS Genet 3:e25
    [Google Scholar]
  91. 91.  Luo S, Murphy CT 2011. Caenorhabditis elegans reproductive aging: regulation and underlying mechanisms. Genesis 49:53–65
    [Google Scholar]
  92. 92.  Li S, Stone HA, Murphy CT 2015. A microfluidic device and automatic counting system for the study of C. elegans reproductive aging. Lab Chip 15:524–31
    [Google Scholar]
  93. 93.  San-Miguel A, Kurshan PT, Crane MM, Zhao Y, McGrath PT et al. 2016. Deep phenotyping unveils hidden traits and genetic relations in subtle mutants. Nat. Commun. 7:12990
    [Google Scholar]
  94. 94.  Stirman JN, Brauner M, Gottschalk A, Lu H 2010. High-throughput study of synaptic transmission at the neuromuscular junction enabled by optogenetics and microfluidics. J. Neurosci. Methods 191:90–93
    [Google Scholar]
  95. 95.  Hwang H, Barnes DE, Matsunaga Y, Benian GM, Ono S, Lu H 2016. Muscle contraction phenotypic analysis enabled by optogenetics reveals functional relationships of sarcomere components in Caenorhabditis elegans. . Sci. Rep. 6:19900
    [Google Scholar]
  96. 96.  Kopito RB, Levine E 2014. Durable spatiotemporal surveillance of Caenorhabditis elegans response to environmental cues. Lab Chip 14:764–70
    [Google Scholar]
  97. 97.  Lee KS, Iwanir S, Kopito RB, Scholz M, Calarco JA et al. 2017. Serotonin-dependent kinetics of feeding bursts underlie a graded response to food availability in C. . elegans. Nat. Commun. 8:14221
    [Google Scholar]
  98. 98.  Raizen DM, Avery L 1994. Electrical-activity and behavior in the pharynx of Caenorhabditis elegans. . Neuron 12:483–95
    [Google Scholar]
  99. 99.  Avery L, Raizen D, Lockery S 1995. Electrophysiological methods. Methods Cell Biol 48:251–69
    [Google Scholar]
  100. 100.  Lockery SR, Hulme SE, Roberts WM, Robinson KJ, Laromaine A et al. 2012. A microfluidic device for whole-animal drug screening using electrophysiological measures in the nematode C. . elegans. Lab Chip 12:2211–20
    [Google Scholar]
  101. 101.  Hu C, Dillon J, Kearn J, Murray C, O'Connor V et al. 2013. NeuroChip: a microfluidic electrophysiological device for genetic and chemical biology screening of Caenorhabditis elegans adult and larvae. PLOS ONE 8:e64297
    [Google Scholar]
  102. 102.  Markaki M, Tavernarakis N 2010. Modeling human diseases in Caenorhabditis elegans. . Biotechnol. J. 5:1261–76
    [Google Scholar]
  103. 103.  Mondal S, Hegarty E, Martin C, Gökçe SK, Ghorashian N, Ben-Yakar A 2016. Large-scale microfluidics providing high-resolution and high-throughput screening of Caenorhabditis elegans poly-glutamine aggregation model. Nat. Commun. 7:13023
    [Google Scholar]
  104. 104.  Hulme SE, Shevkoplyas SS, Apfeld J, Fontana W, Whitesides GM 2007. A microfabricated array of clamps for immobilizing and imaging C. . elegans. Lab Chip 7:1515–23
    [Google Scholar]
  105. 105.  Lee H, Kim SA, Coakley S, Mugno P, Hammarlund M et al. 2014. A multi-channel device for high-density target-selective stimulation and long-term monitoring of cells and subcellular features in C. . elegans. Lab Chip 14:4513–22
    [Google Scholar]
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