Skip to main content

Advertisement

SpringerLink
Log in

Quantifying Filopodia in Cultured Astrocytes by an Algorithm

  • Original Paper
  • Published:
Neurochemical Research Aims and scope Submit manuscript

Abstract

Astrocytes in vivo extend thin processes termed peripheral astrocyte processes (PAPs), in particular around synapses where they can mediate glia-neuronal communication. The relation of PAPs to synapses is not based on coincidence, but it is not clear which stimuli and mechanisms lead to their formation and are active during process extension/ retraction in response to neuronal activity. Also, the molecular basis of the extremely fine PAP morphology (often 50 to 100 nm) is not understood. These open questions can be best investigated under in vitro conditions studying glial filopodia. We have previously analyzed filopodial mechanisms (Lavialle et al. PNAS 108:12915) applying an automated method for filopodia morphometry, which is now described in greater detail. The Filopodia Specific Shape Factor (FSSF) developed integrates number and length of filopodia. It quantifies filopodia independent of overall astrocytic shape or size, which can be intricate in itself. The algorithm supplied here permits automated image processing and measurements using ImageJ. Cells have to be sampled in higher numbers to obtain significant results. We validate the FSSF, and characterize the systematic influence of thresholding and camera pixel grid on measurements. We provide exemplary results of substance-induced filopodia dynamics (glutamate, mGluR agonists, EGF), and show that filopodia formation is highly sensitive to medium pH (CO2) and duration of cell culture. Although the FSSF was developed to study astrocyte filopodia with focus on the perisynaptic glial sheath, we expect that this parameter can also be applied to neuronal growth cones, non-neural cell types, or cell lines.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Reichenbach A, Derouiche A, Kirchhoff F (2010) Morphology and dynamics of perisynaptic glia. Brain Res Rev 63:11–25

    Article  PubMed  Google Scholar 

  2. Cornell-Bell AH, Prem GT, Smith SJ (1990) The excitatory neurotransmitter glutamate causes filopodia formation in cultured hippocampal astrocytes. Glia 3:322–334

    Article  CAS  PubMed  Google Scholar 

  3. Derouiche A, Frotscher M (2001) Peripheral astrocyte processes: Monitoring by selective immunostaining for the actin-binding ERM-proteins. Glia 36:330–341

    Article  CAS  PubMed  Google Scholar 

  4. Wolff JR, Chao I. Cytoarchitechtonics of non-neural cells in the central nervous system (2004) In: Hertz L (ed) Non-neuronal cells in the nervous system: function and dysfunction. Elsevier: Adv Mol Cell Bio 31 (Vol 1), p 1–51

  5. Peters A, Palay SL, Webster Hd (1991) The fine structure of the nervous system: the neurons and supporting cells, 3rd edn. Oxford Univ. Press, Oxford

    Google Scholar 

  6. Araque A, Carmignoto G, Haydon PG, Oliet SH, Robitaille R, Volterra A (2014) Gliotransmitters travel in time and space. Neuron 81:728–739

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Grosche J, Matyash V, Moller T, Verkhratsky A, Reichenbach A, Kettenmann H (1999) Microdomains for neuron-glia interaction: parallel fiber signaling to Bergmann glial cells. Nat Neurosci 2:139–143

    Article  CAS  PubMed  Google Scholar 

  8. Derouiche A, Rauen T (1995) Coincidence of glutamate-aspartate-transporter-(GLAST) and glutamine synthetase-(GS) immunoreactions in retinal glia: Evidence for coupling of GLAST and GS in transmitter clearance. J Neurosci Res 42:131–143

    Article  CAS  PubMed  Google Scholar 

  9. Rothstein JD, Martin L, Levey AI, Dykes-Hoberg M, Jin L, Wu D et al (1994) Localization of neuronal and glial glutamate transporters. Neuron 13:713–725

    Article  CAS  PubMed  Google Scholar 

  10. Derouiche A, Frotscher M (1991) Astroglial processes around identified glutamatergic synapses contain glutamine synthetase: evidence for transmitter degradation. Brain Res 552:346–350

    Article  CAS  PubMed  Google Scholar 

  11. Norenberg MD, Martinez-Hernandez A (1979) Fine structural localization of glutamine synthetase in astrocytes of rat brain. Brain Res 161:303–310

    Article  CAS  PubMed  Google Scholar 

  12. García-Segura LM, Chowen JA, Párducz A, Naftolin F (1994) Gonadal hormones as promoters of structural synaptic plasticity: cellular mechanisms. Prog Neurobiol 44:279–307

    Article  PubMed  Google Scholar 

  13. Theodosis DT, Poulain DA, Oliet SH (2008) Activity-dependent structural and functional plasticity of astrocyte-neuron interactions. Physiol Rev 88:983–1008

    Article  CAS  PubMed  Google Scholar 

  14. Lavialle M, Aumann G, Anlauf E, Pröls F, Arpin M, Derouiche A (2011) Structural plasticity of perisynaptic astrocyte processes involves ezrin and metabotropic glutamate receptors. Proc Natl Acad Sci USA 108:12915–12919

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. McCarthy KD, de Vellis J (1980) Preparation of separate astroglia and oligodendroglial cell cultures from rat cerebral tissue. J Cell Biol 85:890–902

    Article  CAS  PubMed  Google Scholar 

  16. Goldman JE, Abramson B (1990) Cyclic AMP-induced shape changes of astrocytes are accompanied by rapid depolymerization of actin. Brain Res 528:189–196

    Article  CAS  PubMed  Google Scholar 

  17. Almeida-Prieto S, Blanco-Méndez J, Otero-Espinar FJ (2007) Microscopic image analysis techniques for the morphological characterization of pharmaceutical particles: influence of the software, and the factor algorithms used in the shape factor estimation. Eur J Pharm Biopharm 67:766–776

    Article  CAS  PubMed  Google Scholar 

  18. Rasband WS. (1997–2015) ImageJ. U. S. National Institutes of Health, Bethesda, Maryland, USA. http://imagej.nih.gov/ij/. Accessed 2 Oct 2016

  19. Matsutani S, Yamamoto N (1997) Neuronal regulation of astrocyte morphology in vitro is mediated by GABAergic signaling. Glia 20:1–9

    Article  CAS  PubMed  Google Scholar 

  20. Kapur J, Sahoo P, Wong A (1985) A new method for gray-level picture thresholding using the entropy of the histogramm. Comput Vis Gr Image Process 29:273–285

    Article  Google Scholar 

  21. Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T et al (2012) Fiji: an open-source platform for biological-image analysis. Nat Methods 9:676–682

    Article  CAS  PubMed  Google Scholar 

  22. Fisher R, Perinks S, Walker A, Wolfart E (2003) Adaptive thresholding. http://homepages.inf.ed.ac.uk/rbf/HIPR2/adpthrsh.htm. Accessed 2 Oct 2016

  23. Miller S, Romano C, Cotman CW (1995) Growth factor upregulation of a phosphoinositide-coupled metabotropic glutamate receptor in cortical astrocytes. J Neurosci 15:6103–6109

    CAS  PubMed  Google Scholar 

  24. Bretscher A (1989) Rapid phosphorylation and reorganizationof ezrin and spectrin accompany morphological changes induced in A-431 cells by epidermal growth factor. J Cell Biol 108:921–930

    Article  CAS  PubMed  Google Scholar 

  25. Argiro V, Bunge MB, Johnson MI (1985) A quantitative study of growth cone filopodial extension. J Neurosci Res 13:149–162

    Article  CAS  PubMed  Google Scholar 

  26. Bray D, Chapman K (1985) Analysis of microspike movements on the neuronal growth cone. J Neurosci 5:3204–3213

    CAS  PubMed  Google Scholar 

  27. Buettner HM, Pittman RN, Ivins JK (1993) A model of neurite extension across regions of non-permissive substrate: simulations based on experimental measurement of growth cone motility and filopodia dynamics. Dev Biol 163:407–422

    Article  Google Scholar 

  28. Buettner HM (1994) Nerve growth dynamics. Quantitative models for nerve development and regeneration. Ann N Y Acad Sci 745:210–221

    Article  CAS  PubMed  Google Scholar 

  29. Davenport RW, Dou P, Mills LR, Kater SB (1996) Distinct calcium signaling within neuronal growth cones and filopodia. J Neurobiol 31:1–15

    Article  CAS  PubMed  Google Scholar 

  30. Sydor AM, Su AL, Wang FS, Xu A, Jay DG (1996) Talin and vinculin play distinct roles in filopodial motility in the neuronal growth cone. J Cell Biol 134:1197–1207

    Article  CAS  PubMed  Google Scholar 

  31. Husainy AN, Morrow AA, Perkins TJ, Lee JM (2010) Robust patterns in the stochastic organization of filopodia. BMC Cell Biol 11:86

    Article  PubMed  PubMed Central  Google Scholar 

  32. Fanti Z, Martinez-Perez ME, De-Miguel FF (2011) NeuronGrowth, a software for automatic quantification of neurite and filopodial dynamics from time-lapse sequences of digital images. Dev Neurobiol 71:870–881

    Article  PubMed  Google Scholar 

  33. Costantino S, Kent CB, Godin AG, Kennedy TE, Wiseman PW, Fournier AE (2008) Semi-automated quantification of filopodial dynamics. J Neurosci Methods 171:165–173

    Article  PubMed  Google Scholar 

  34. Nilufar S, Morrow AA, Lee JM, Perkins TJ (2013) FiloDetect: automatic detection of filopodia from fluorescence microscopy images. BMC Syst Biol 7:66

    Article  PubMed  PubMed Central  Google Scholar 

  35. Saha T, Rathmann I, Viplav A, Panzade S, Begemann I, Rasch C, Klingauf J, Matis M, Galic M (2016) Automated analysis of filopodial length and spatially resolved protein concentration via adaptive shape tracking. Mol Biol Cell 27:3616–3626

    Article  PubMed  PubMed Central  Google Scholar 

  36. Derouiche A, Anlauf E, Aumann G, Mühlstädt B, Lavialle M (2002) Anatomical aspects of glia-synapse interaction: the perisynaptic glial sheath consists of a specialized astrocyte compartment. J Physiol (Paris) 96:177–182

    Article  CAS  Google Scholar 

  37. Derouiche A, Pannicke T, Haseleu J, Blaess S, Grosche J, Reichenbach A (2012) Beyond polarity: functional membrane domains in astrocytes and Müller cells. Neurochem Res 37:2513–2523

    Article  CAS  PubMed  Google Scholar 

  38. Thomsen R, Lade Nielsen A (2011) A Boyden chamber-based method for characterization of astrocyte protrusion localized RNA and protein. Glia 59:1782–1792

    Article  PubMed  Google Scholar 

  39. Perea G, Navarrete M, Araque A (2009) Tripartite synapses: astrocytes process and control synaptic information. Trends Neurosci 32:421–431

    Article  CAS  PubMed  Google Scholar 

  40. Cechin SR, Gottfried C, Prestes CC, Andrighetti L, Wofchuk ST, Rodnight R (2002) Astrocyte stellation in saline media lacking bicarbonate: possible relation to intracellular pH and tyrosine phosphorylation. Brain Res 946:12–23

    Article  CAS  PubMed  Google Scholar 

  41. Hirao M, Sato N, Kondo T, Yonemura S, Monden M, Sasaki T, Takai Y, Tsukita S, Tsukita S (1996) Regulation mechanism of ERM (Ezrin/Radixin/Moesin) protein/plasma membrane association: possible involvement of phasphatidylinositol turnover and Rho-dependent signaling pathway. J Biol Chem 135:37–51

    CAS  Google Scholar 

  42. Machesky LM, Hall A (1996) Rho: a connection between membrane receptor signalling and the cytoskeleton. Cell Biology 6:304–310

    Article  CAS  Google Scholar 

  43. Suidan HS, Nobes CD, Hall A, Monard D (1997) Astrocyte spreading in response to thrombin and lysophosphatidic acid is dependent on the Rho GTPase. Glia 21:244–252

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors wish to thank Brigitte Rost and Torsten Schwalm for technical assistance, and Ingrid Beck for graphic artwork. This work was supported by the Deutsche Forschungsgemeinschaft (DFG 676/2-1, to AD), the Frankfurter Promotionsförderung of the Medical Faculty of the Goethe-University Frankfurt (Stipend to FK), and the Dr. Senckenbergische Stiftung Frankfurt am Main (to HWK).

Author information

Author notes

  1. Georg Aumann

    Present address: Hospital of Günzburg, Günzburg, Germany

Authors and Affiliations

  1. Institute of Anatomy, University of Dresden, Dresden, Germany

    Georg Aumann

  2. Department of Neurology, University Hospital Frankfurt, Goethe-University Frankfurt, Frankfurt am Main, Germany

    Felix Friedländer & Robert Brunkhorst

  3. Department of Medical Physics and Biomedical Engineering, University of Dresden, Dresden, Germany

    Matthias Thümmler

  4. Institute of Anatomy II, Goethe-University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany

    Fabian Keil, Horst-Werner Korf & Amin Derouiche

  5. Dr. Senckenbergisches Chronomedizinisches Institut, University of Frankfurt, Frankfurt am Main, Germany

    Horst-Werner Korf & Amin Derouiche

Authors
  1. Georg Aumann
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Felix Friedländer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Matthias Thümmler
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fabian Keil
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Robert Brunkhorst
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Horst-Werner Korf
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Amin Derouiche
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amin Derouiche.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Appendix: Installation and Data Organization for the FSSF-ImageJ Macro

Appendix: Installation and Data Organization for the FSSF-ImageJ Macro

To install the analysis programme given below as a macro (not as a plugin) in Fiji (ImageJ does not contain the thresholding algorithms required), copy-paste the macro lines first into the Fiji Menu dialogue which opens under—Plugins/New/Macro. When saving it, make sure to use the file extension ‘.ijm’. Secondly, to make it easily accessible from the ImageJ menu bar, select the saved file from the file list opening under—Plugins/ Macros/Install. After that it can be readily selected from ‘Plugins/ Macros’. The macro version of this file has the advantage of easily customizing it using the Macro/Edit function. Alternatively, with an underscore (“_”) in the macro name and .txt as file extension, the macro can be moved to the Plugins folder, and thus be made available in the Plugins menu.

All images to be analysed should be in a single directory, not in subdirectories. They should be numbered at the beginning of the file name using leading zeros. An empty subdirectory named ‘FSSF’ should be contained in this directory. Open the first image of the series ‘manually’ in ImageJ/Fiji before starting the macro, the macro automatically reads out the file path for all subsequent images. All interim images and the results table (compatible with Excel) generated are automatically saved in the ‘FSSF’ subdirectory.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aumann, G., Friedländer, F., Thümmler, M. et al. Quantifying Filopodia in Cultured Astrocytes by an Algorithm. Neurochem Res 42, 1795–1809 (2017). https://doi.org/10.1007/s11064-017-2193-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11064-017-2193-0

Keywords

Search

Navigation