Mechanism of Docosahexaenoic Acid in the Enhancement of Neuronal Signalling

  • Md Ahsan Ul BariEmail author
  • Julie Gaburro
  • Agnes Michalczyk
  • M. Leigh Ackland
  • Catherine Williams
  • Asim Bhatti
Part of the Series in BioEngineering book series (SERBIOENG)


Microelectrode array (MEA) has attracted paramount attention from neuroscientific community to explore and understand the working principle of nervous systems and the effect of drugs on the behaviour of neurons. In this work, we attempt to explore the effect of docosahexaenoic acid (DHA) on the overall neuronal spike activity as well as the spontaneous activity patterns of primary cortical neurons employing MEA technology. Neocortex neurons of C57BL/6 mice were cultured on MEA for 2 weeks until maturation and then treated with 10 µg/ml DHA for 48 h. Our results demonstrated that DHA supplementation enhanced the overall spike activity (454.35 spikes/s) of the neurons compared to the non-treated control (297.01 spikes/s). This is a preliminary study to explore the changes in the electrophysiological properties of neurons in response to DHA. Our results indicated the potential use of DHA in improving neuronal signalling indicating it could be helpful in improving the diseased condition of neuronal disorders particularly in Alzheimer’s disease (AD).


Docosahexaenoic acid (DHA) Microelectrode array (MEA) Alzheimer’s disease (AD) Neuronal spike Neuronal signalling 



This work was jointly supported by Centre for Cellular and Molecular Biology (CCMB), Deakin University, Australia, Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Australia and Australian Animal Health Laboratory (AAHL), CSIRO, Australia. We would also like to thank Steve Cheung’s lab for providing facilities for the immunocytochemistry work for the manuscript.


  1. 1.
    Yurko-Mauro, K., et al.: Beneficial effects of docosahexaenoic acid on cognition in age-related cognitive decline. Alzheimers Dement 6(6), 456–464 (2010)CrossRefGoogle Scholar
  2. 2.
    Collins, F.D., et al.: Plasma lipids in human linoleic acid deficiency. Nutr. Metab. 13(3), 150–167 (1971)CrossRefGoogle Scholar
  3. 3.
    Connor, W.E., Neuringer, M., Lin, D.S.: Dietary effects on brain fatty acid composition: the reversibility of n-3 fatty acid deficiency and turnover of docosahexaenoic acid in the brain, erythrocytes, and plasma of rhesus monkeys. J. Lipid Res. 31(2), 237–247 (1990)Google Scholar
  4. 4.
    McNamara, R.K.: DHA deficiency and prefrontal cortex neuropathology in recurrent affective disorders. J. Nutr. 140(4), 864–868 (2010)CrossRefGoogle Scholar
  5. 5.
    Tully, A.M., et al.: Low serum cholesteryl ester-docosahexaenoic acid levels in Alzheimer’s disease: a case-control study. Br. J. Nutr. 89(4), 483–489 (2003)CrossRefGoogle Scholar
  6. 6.
    Crawford, M.A., Bazinet, R.P., Sinclair, A.J.: Fat intake and CNS functioning: ageing and disease. Ann. Nutr. Metab. 55(1–3), 202–228 (2009)CrossRefGoogle Scholar
  7. 7.
    DeMar Jr., J.C., et al.: One generation of n-3 polyunsaturated fatty acid deprivation increases depression and aggression test scores in rats. J. Lipid Res. 47(1), 172–180 (2006)CrossRefGoogle Scholar
  8. 8.
    Lukiw, W.J., et al.: A role for docosahexaenoic acid-derived neuroprotectin D1 in neural cell survival and Alzheimer disease. J. Clin. Invest. 115(10), 2774–2783 (2005)CrossRefGoogle Scholar
  9. 9.
    Stephan, B.C., et al.: The neuropathological profile of mild cognitive impairment (MCI): a systematic review. Mol Psychiatry 17(11), 1056–1076 (2012)CrossRefGoogle Scholar
  10. 10.
    Shankar, G.M., Walsh, D.M.: Alzheimer’s disease: synaptic dysfunction and Abeta. Mol. Neurodegener. 4, 48 (2009)CrossRefGoogle Scholar
  11. 11.
    Masliah, E.: Mechanisms of synaptic dysfunction in Alzheimer’s disease. Histol. Histopathol. 10(2), 509–519 (1995)Google Scholar
  12. 12.
    Gomez-Pinilla, F.: Brain foods: the effects of nutrients on brain function. Nat. Rev. Neurosci. 9(7), 568–578 (2008)CrossRefGoogle Scholar
  13. 13.
    Connor, K.M., et al.: Increased dietary intake of omega-3-polyunsaturated fatty acids reduces pathological retinal angiogenesis. Nat. Med. 13(7), 868–873 (2007)CrossRefGoogle Scholar
  14. 14.
    Bazan, N.G.: Cell survival matters: docosahexaenoic acid signaling, neuroprotection and photoreceptors. Trends Neurosci. 29(5), 263–271 (2006)CrossRefGoogle Scholar
  15. 15.
    Horrocks, L.A., Farooqui, A.A.: Docosahexaenoic acid in the diet: its importance in maintenance and restoration of neural membrane function. Prostaglandins Leukot. Essent. Fat. Acids 70(4), 361–372 (2004)CrossRefGoogle Scholar
  16. 16.
    Jeffrey, B.G., et al.: The role of docosahexaenoic acid in retinal function. Lipids 36(9), 859–871 (2001)CrossRefGoogle Scholar
  17. 17.
    Kim, H.Y., Spector, A.A., Xiong, Z.M.: A synaptogenic amide N-docosahexaenoyl ethanolamide promotes hippocampal development. Prostaglandins Lipid Mediat. 96(1–4), 114–120 (2011)CrossRefGoogle Scholar
  18. 18.
    Su, H.M., et al.: Bioequivalence of dietary alpha-linolenic and docosahexaenoic acids as sources of docosahexaenoate accretion in brain and associated organs of neonatal baboons. Pediatr. Res. 45(1), 87–93 (1999)CrossRefGoogle Scholar
  19. 19.
    Martin, R.E., Bazan, N.G.: Changing fatty acid content of growth cone lipids prior to synaptogenesis. J. Neurochem. 59(1), 318–325 (1992)CrossRefGoogle Scholar
  20. 20.
    Poulos, A., Darin-Bennett, A., White, I.G.: The phospholipid-bound fatty acids and aldehydes of mammalian spermatozoa. Comp. Biochem. Physiol. B 46(3), 541–549 (1973)Google Scholar
  21. 21.
    Suzuki, H., et al.: Rapid incorporation of docosahexaenoic acid from dietary sources into brain microsomal, synaptosomal and mitochondrial membranes in adult mice. Int. J. Vitam. Nutr. Res. 67(4), 272–278 (1997)Google Scholar
  22. 22.
    Crawford, M.A., Casperd, N.M., Sinclair, A.J.: The long chain metabolites of linoleic avid linolenic acids in liver and brain in herbivores and carnivores. Comp. Biochem. Physiol. B 54(3), 395–401 (1976)Google Scholar
  23. 23.
    Bazinet, R.P., Laye, S.: Polyunsaturated fatty acids and their metabolites in brain function and disease. Nat. Rev. Neurosci. 15(12), 771–785 (2014)CrossRefGoogle Scholar
  24. 24.
    Carrie, I., et al.: Specific phospholipid fatty acid composition of brain regions in mice. Effects of n-3 polyunsaturated fatty acid deficiency and phospholipid supplementation. J. Lipid Res. 41(3), 465–472 (2000)Google Scholar
  25. 25.
    Calon, F., et al.: Docosahexaenoic acid protects from dendritic pathology in an Alzheimer’s disease mouse model. Neuron 43(5), 633–645 (2004)CrossRefGoogle Scholar
  26. 26.
    Zhao, Y., et al.: Docosahexaenoic acid-derived neuroprotectin D1 induces neuronal survival via secretase—and PPARgamma-mediated mechanisms in Alzheimer’s disease models. PLoS ONE 6(1), e15816 (2011)CrossRefGoogle Scholar
  27. 27.
    Yoshida, S., et al.: Synaptic vesicle ultrastructural changes in the rat hippocampus induced by a combination of alpha-linolenate deficiency and a learning task. J. Neurochem. 68(3), 1261–1268 (1997)CrossRefGoogle Scholar
  28. 28.
    Morin, C., et al.: Effect of docosahexaenoic acid monoacylglyceride on systemic hypertension and cardiovascular dysfunction. Am. J. Physiol. Heart Circ. Physiol. 309(1), H93–H102 (2015)MathSciNetCrossRefGoogle Scholar
  29. 29.
    Kim, H.Y., Akbar, M., Kim, Y.S.: Phosphatidylserine-dependent neuroprotective signaling promoted by docosahexaenoic acid. Prostaglandins Leukot. Essent. Fat. Acids 82(4–6), 165–172 (2010)CrossRefGoogle Scholar
  30. 30.
    Kim, H.Y.: Novel metabolism of docosahexaenoic acid in neural cells. J. Biol. Chem. 282(26), 18661–18665 (2007)CrossRefGoogle Scholar
  31. 31.
    Akbar, M., et al.: Docosahexaenoic acid: a positive modulator of Akt signaling in neuronal survival. Proc. Natl. Acad. Sci. USA 102(31), 10858–10863 (2005)CrossRefGoogle Scholar
  32. 32.
    Kim, H.-Y., et al.: Inhibition of neuronal apoptosis by docosahexaenoic acid (22: 6n-3) role of phosphatidylserine in antiapoptotic effect. J. Biol. Chem. 275(45), 35215–35223 (2000)CrossRefGoogle Scholar
  33. 33.
    Kim, H.Y., Akbar, M., Kim, K.Y.: Inhibition of neuronal apoptosis by polyunsaturated fatty acids. J. Mol. Neurosci. 16(2–3), 223–227 (2001) discussion 279-84Google Scholar
  34. 34.
    Akbar, M., Kim, H.Y.: Protective effects of docosahexaenoic acid in staurosporine-induced apoptosis: involvement of phosphatidylinositol-3 kinase pathway. J. Neurochem. 82(3), 655–665 (2002)CrossRefGoogle Scholar
  35. 35.
    Cao, D., et al.: Effects of docosahexaenoic acid on the survival and neurite outgrowth of rat cortical neurons in primary cultures. J. Nutr. Biochem. 16(9), 538–546 (2005)CrossRefGoogle Scholar
  36. 36.
    Suphioglu, C., et al.: The omega-3 fatty acid, DHA, decreases neuronal cell death in association with altered zinc transport. FEBS Lett. 584(3), 612–618 (2010)CrossRefGoogle Scholar
  37. 37.
    Koh, J.Y., et al.: Staurosporine-induced neuronal apoptosis. Exp. Neurol. 135(2), 153–159 (1995)CrossRefGoogle Scholar
  38. 38.
    Yang, X.P., et al.: Potential protection of 2, 3, 5, 4’-tetrahydroxystilbene-2-O-beta-D-glucoside against staurosporine-induced toxicity on cultured rat hippocampus neurons. Neurosci. Lett. 576, 79–83 (2014)CrossRefGoogle Scholar
  39. 39.
    Chen, L., et al.: Hydrogen peroxide-induced neuronal apoptosis is associated with inhibition of protein phosphatase 2A and 5, leading to activation of MAPK pathway. Int. J. Biochem. Cell Biol. 41(6), 1284–1295 (2009)CrossRefGoogle Scholar
  40. 40.
    Snyder, A.C., et al.: Global network influences on local functional connectivity. Nat. Neurosci. 18(5), 736–743 (2015)CrossRefGoogle Scholar
  41. 41.
    Spira, M.E., Hai, A.: Multi-electrode array technologies for neuroscience and cardiology. Nat. Nanotechnol. 8(2), 83–94 (2013)CrossRefGoogle Scholar
  42. 42.
    Hochberg, L.R., et al.: Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 442(7099), 164–171 (2006)CrossRefGoogle Scholar
  43. 43.
    Hai, A., Shappir, J., Spira, M.E.: In-cell recordings by extracellular microelectrodes. Nat. Methods 7(3), 200–202 (2010)CrossRefGoogle Scholar
  44. 44.
    Hales, C.M., Rolston, J.D., Potter, S.M.: How to culture, record and stimulate neuronal networks on micro-electrode arrays (MEAs). J. Vis. Exp. (39) (2010)Google Scholar
  45. 45.
    Nam, Y., Wheeler, B.C.: In vitro microelectrode array technology and neural recordings. Crit. Rev. Biomed. Eng. 39(1), 45–61 (2011)CrossRefGoogle Scholar
  46. 46.
    Johnstone, A.F., et al.: Microelectrode arrays: a physiologically based neurotoxicity testing platform for the 21st century. Neurotoxicology 31(4), 331–350 (2010)CrossRefGoogle Scholar
  47. 47.
    Makarova, J., et al.: Parallel readout of pathway-specific inputs to laminated brain structures. Fr. Syst. Neurosci. 5, 77 (2011)Google Scholar
  48. 48.
    Biffi, E., et al.: Development and validation of a spike detection and classification algorithm aimed at implementation on hardware devices. Comput. Intell. Neurosci. 659050 (2010)Google Scholar
  49. 49.
    Liu, M.G., et al.: Use of multi-electrode array recordings in studies of network synaptic plasticity in both time and space. Neurosci. Bull. 28(4), 409–422 (2012)CrossRefGoogle Scholar
  50. 50.
    Thomas Jr., C.A., et al.: A miniature microelectrode array to monitor the bioelectric activity of cultured cells. Exp. Cell Res. 74(1), 61–66 (1972)CrossRefGoogle Scholar
  51. 51.
    Gross, G.W., et al.: A new fixed-array multi-microelectrode system designed for long-term monitoring of extracellular single unit neuronal activity in vitro. Neurosci. Lett. 6(2–3), 101–105 (1977)CrossRefGoogle Scholar
  52. 52.
    Gross, G.W.: Simultaneous single unit recording in vitro with a photoetched laser deinsulated gold multimicroelectrode surface. IEEE Trans. Biomed. Eng. 26(5), 273–279 (1979)CrossRefGoogle Scholar
  53. 53.
    Pine, J.: Recording action potentials from cultured neurons with extracellular microcircuit electrodes. J. Neurosci. Methods 2(1), 19–31 (1980)CrossRefGoogle Scholar
  54. 54.
    McConnell, E.R., et al.: Evaluation of multi-well microelectrode arrays for neurotoxicity screening using a chemical training set. Neurotoxicology 33(5), 1048–1057 (2012)CrossRefGoogle Scholar
  55. 55.
    Israel, D.A., et al.: An array of microelectrodes to stimulate and record from cardiac cells in culture. Am. J. Physiol. 247(4 Pt 2), H669–H674 (1984)Google Scholar
  56. 56.
    Novak, J.L., Wheeler, B.C.: Recording from the Aplysia abdominal ganglion with a planar microelectrode array. IEEE Trans. Biomed. Eng. 33(2), 196–202 (1986)CrossRefGoogle Scholar
  57. 57.
    Novak, J.L., Wheeler, B.C.: Multisite hippocampal slice recording and stimulation using a 32 element microelectrode array. J. Neurosci. Methods 23(2), 149–159 (1988)CrossRefGoogle Scholar
  58. 58.
    Regehr, W.G., et al.: Sealing cultured invertebrate neurons to embedded dish electrodes facilitates long-term stimulation and recording. J. Neurosci. Methods 30(2), 91–106 (1989)CrossRefGoogle Scholar
  59. 59.
    Connolly, P., et al.: An extracellular microelectrode array for monitoring electrogenic cells in culture. Biosens. Bioelectron. 5(3), 223–234 (1990)CrossRefGoogle Scholar
  60. 60.
    Martinoia, S., et al.: A general-purpose system for long-term recording from a microelectrode array coupled to excitable cells. J. Neurosci. Methods 48(1–2), 115–121 (1993)CrossRefGoogle Scholar
  61. 61.
    Nisch, W., et al.: A thin film microelectrode array for monitoring extracellular neuronal activity in vitro. Biosens. Bioelectron. 9(9–10), 737–741 (1994)CrossRefGoogle Scholar
  62. 62.
    Lewicki, M.S.: A review of methods for spike sorting: the detection and classification of neural action potentials. Network 9(4), R53–R78 (1998)CrossRefzbMATHGoogle Scholar
  63. 63.
    Pleasure, S.J., Lee, V.M.: NTera 2 cells: a human cell line which displays characteristics expected of a human committed neuronal progenitor cell. J. Neurosci. Res. 35(6), 585–602 (1993)CrossRefGoogle Scholar
  64. 64.
    Nick, C., et al.: DrCell—a software tool for the analysis of cell signals recorded with extracellular microelectrodes. Signal Process. Int. J. 7, 96–109 (2013)Google Scholar
  65. 65.
    Kuebler, E.S., et al.: Burst predicting neurons survive an in vitro glutamate injury model of cerebral ischemia. Sci. Rep. 5, 17718 (2015)CrossRefGoogle Scholar
  66. 66.
    Mack, C.M., et al.: Burst and principal components analyses of MEA data for 16 chemicals describe at least three effects classes. Neurotoxicology 40, 75–85 (2014)CrossRefGoogle Scholar
  67. 67.
    Pimashkin, A., et al.: Spiking signatures of spontaneous activity bursts in hippocampal cultures. Fr. Comput. Neurosci. 5, 46 (2011)Google Scholar
  68. 68.
    Wagenaar, D.A., Pine, J., Potter, S.M.: An extremely rich repertoire of bursting patterns during the development of cortical cultures. BMC Neurosci. 7, 11 (2006)CrossRefGoogle Scholar
  69. 69.
    Cooper, D.C.: The significance of action potential bursting in the brain reward circuit. Neurochem. Int. 41(5), 333–340 (2002)CrossRefGoogle Scholar
  70. 70.
    Sakoe, H., Chiba, S.: Dynamic programming algorithm optimization for spoken word recognition. Acoust. Speech Signal Process. IEEE Trans. 26(1), 43–49 (1978)CrossRefzbMATHGoogle Scholar
  71. 71.
    Ahmed, R., et al.: Dynamic time warping based neonatal seizure detection system. In: Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE. IEEE (2012)Google Scholar
  72. 72.
    Smith, V.A., et al.: Computational inference of neural information flow networks. PLoS Comput. Biol. 2(11), e161 (2006)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • Md Ahsan Ul Bari
    • 1
    Email author
  • Julie Gaburro
    • 2
    • 3
  • Agnes Michalczyk
    • 1
  • M. Leigh Ackland
    • 1
  • Catherine Williams
    • 3
  • Asim Bhatti
    • 2
  1. 1.Centre for Cellular and Molecular Biology (CCMB)Deakin UniversityVictoriaAustralia
  2. 2.Institute for Intelligent Systems Research and Innovation (IISRI)Deakin UniversityVictoriaAustralia
  3. 3.Australian Animal Health Laboratory (AAHL)CSIROVictoriaAustralia

Personalised recommendations