Hostname: page-component-8448b6f56d-wq2xx Total loading time: 0 Render date: 2024-04-19T23:49:23.074Z Has data issue: false hasContentIssue false
  • English
  • Français

Cryostat Slice Irregularities May Introduce Bias in Tissue Thickness Estimation: Relevance for Cell Counting Methods

Published online by Cambridge University Press:  15 July 2015

Anna Puigdellívol-Sánchez ,
Albert Giralt ,
Anna Casanovas ,
Jordi Alberch  and
Alberto Prats-Galino
Anna Puigdellívol-Sánchez*
Affiliation:
Human Anatomy and Embryology Unit, Facultat de Medicina, Universitat de Barcelona, c/Casanova 143, 08036 Barcelona, Spain CAP Anton de Borja, Consorci Sanitari de Terrassa, c/Edison-cantonada Marconi, 08091 Rubí, Barcelona, Spain
Albert Giralt
Affiliation:
Departament de Biologia Cellular, Immunologia i Neurociències, Facultat de Medicina, Universitat de Barcelona, c/Casanova 143, 08036 Barcelona, Spain. Barcelona, Spain Institut d’ Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, c/Casanova 143, 08036 Barcelona, Spain Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, c/Casanova 143, 08036 Barcelona, Spain
Anna Casanovas
Affiliation:
Unit of Cellular Neurobioloy, Departament de Medicina Experimental, Facultat de Medicina, Universitat de Lleida, c/Montserrat Roig 2, 25008 Lleida, Spain
Jordi Alberch
Affiliation:
Departament de Biologia Cellular, Immunologia i Neurociències, Facultat de Medicina, Universitat de Barcelona, c/Casanova 143, 08036 Barcelona, Spain. Barcelona, Spain Institut d’ Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, c/Casanova 143, 08036 Barcelona, Spain Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, c/Casanova 143, 08036 Barcelona, Spain
Alberto Prats-Galino
Affiliation:
Human Anatomy and Embryology Unit, Facultat de Medicina, Universitat de Barcelona, c/Casanova 143, 08036 Barcelona, Spain
*
*Corresponding author.apuigdellivol@ub.edu
Get access

Abstract

Stereological techniques using the optical disectors require estimation of final section thickness, but frozen tissue irregularities may interfere with this estimation. Cryostat slices from rodent nerve tissues (dorsal root ganglia, spinal cord, and brain), cut at 16, 40, and 50 μm, were digitized with a confocal microscope and visualized through 3D software. Geometric section thickness of tissue (Tgeom) was defined as tissue volume/area. Maximal section thicknesses (Tmax), from the top to the bottom of the section, were measured in a random sample of vertical ZX planes. Irregularities were mostly related to blood vessels traversing the tissue and neuronal somas protruding over the cut surfaces, with other neuron profiles showing a fragmented appearance. Irregularities contributed to increasing the distance between the tops and bottoms of slices sectioned in different laboratories. Significant differences were found between Tmax and Tgeom for all thickness studies and counting frames (p<0.01). The Tgeom/Tmax average rate was 68.4–85.7% in volumes around cell profiles (∼600–1,200 μm2) and 83.3–91.8% in subcellular samples (∼25–160 μm2). Confocal microscopy may help to assess tissue irregularities, which might lead to an overestimation of tissue volume if section thickness is estimated by focusing on the top and bottom of the sections.

Keywords

quantitative microscopyfrozen sectionsconfocal microscopy3D analysis
Type
Biological Applications and Techniques
Information
Microscopy and Microanalysis , Volume 21 , Issue 4 , August 2015 , pp. 893 - 901
Copyright
© Microscopy Society of America 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Andersen, B.B. & Gundersen, J.G. (1999). Pronounced loss of cell nuclei and anisotropic deformation of thick sections. J Microsc 196, 69–73.Google Scholar
Baryshnikova, L.M., Von Bohlen Und Halbach, O., Kaplan, S. & Von Bartheld, C.S. (2006). Two distinct events, section compression and loss of particles (“lost caps”), contribute to z-axis distortion and bias in optical disector counting. Microsc Res Tech 69, 738–756.CrossRefGoogle ScholarPubMed
Bergman, E. & Ulfhake, B. (1998). Loss of primary sensory neurons in the very old rat: neuron number estimates using the disector method and confocal optical sectioning. J Comp Neurol 396, 211–222.Google Scholar
Bermejo, P.E., Jiménez, C.E., Torres, C.V. & Avendaño, A. (2003). Quantitative stereological evaluation of the gracile and cuneate nuclei and their projection neurons in the rat. J Comp Neurol 463, 419–433.Google Scholar
Bonthius, D.J., Mc Kim, R., Koele, L., Harb, H., Karacay, B., Mahoney, J. & Pantazis, N.J. (2004). Use of frozen sections to determine neuronal number in the murine hippocampus and neocortex using the optical disector and optical fractionator. Brain Res Protocols 14, 45–47.Google Scholar
Carlo, C.N. & Stevens, C.F. (2011). Analysis of differential shrinkage in frozen brain sections and its implications for the use of guard zones in stereology. J Comp Neurol 519, 2803–2810.Google Scholar
Casanovas, A., Hernández, S., Tarabal, O., Rosselló, J. & Esquerda, J.E. (2008). Strong P2×4 purinergic receptor-like immunoreactivity is selectively associated with degenerating neurons in transgenic rodent models of amyotrophic lateral sclerosis. J Comp Neurol 506, 75–92.Google Scholar
Christensen, J.R., Larsen, K.B., Lisanby, S.H., Scalia, J., Arango, V., Dwork, A.J. & Pakkenberg, B. (2007). Neocortical and hippocampal neuron and glial cell numbers in the rhesus monkeys. Anat Rec 290, 330–340.Google Scholar
Coggeshall, R.E., La Forte, R. & Klein, C.M. (1990). Calibration of methods for determining numbers of dorsal root ganglion cells. J Neurosci Methods 35, 187–194.CrossRefGoogle ScholarPubMed
Dorph-Petersen, K.A., Neurosci Methods, J. & Lewis, D.A. (2011). Stereological approaches to identifying neuropathology in psychosis. Biol Psychiatry 69, 113–116.Google Scholar
Dorph-Petersen, K.A., Nyengaard, J.R. & Gundersen, H.J.G. (2001). Tissue shrinkage and unbiased stereological estimation of particle number and size. J Microsc 204, 232–246.Google Scholar
Dwork, A.J., Christensen, J.R., Larsen, K.B., Scalia, J., Underwood, M.D., Arango, V., Pakkenberg, B. & Lisanby, S.H. (2009). Unaltered neuronal and glial counts in animal models of magnetic seizure therapy and electroconvulsive therapy. Neuroscience 164, 1557–1564.Google Scholar
Floderus, S. (1944). Untersuchungen über den Bau der menschlichen hypophyse mit besonderer Berücksichtigung der quantitativen mikromorphologischen Verhältnisse. Acta Pathol Microbiol Scan Suppl 53, 1–276.Google Scholar
Franze, K., Grosche, J., Skatchkov, S.N., Schinkinger, S., Foja, C., Schild, D., Uckermann, O., Travis, K., Reichenbach, A. & Guck, J. (2007). Müller cells are living optical fibers in the vertebrate retina. Proc Natl Acad USA 104, 8287–8292.Google Scholar
Gardella, D., Hatton, W.J., Rind, H.B., Rosen, G.D. & Von Bartheld, C.S. (2003). Differential tissue shrinkage and compression in the z-axis: Implications for optical disector counting in vibratome-, plastic-, and cryosections. J Neurosci Methods 124, 45–59.Google Scholar
Gardi, J.E., Nyengaard, J.R. & Gundersen, H.J.G. (2008). Automatic sampling for unbiased and efficient stereological estimation using the proportionator in biological studies. J Microscopy 230, 108–120.Google Scholar
Giralt, A., Friedman, H.C., Caneda-Ferrón, B., Urbán, N., Moreno, E., Rubio, N., Blanco, J., Peterson, A., Canals, J.M. & Alberch, J. (2010). BDNF regulation under GFAP promoter provides engineered astrocytes as a new approach for long-term protection in Huntington’s disease. Gene Ther 17, 1294–1308.Google Scholar
Guillery, R.W. (2002). On counting and counting errors. J Neurosci Methods 447, 1–7.Google Scholar
Gundersen, H.J.G., Bagger, P., Bendtsen, T.F., Evans, S.M., Korbo, L., Marcussen, N., Møller, A., Nielsen, K., Nyengaard, J.R., Pakkenberg, B., Sørensen, F.B., Vesterby, A. & West, M.J. (1988). The new stereological tools: Disector, fractionator, nucleator and point sampled intercepts and their use in pathological research and diagnosis. APMIS 96, 857–881.Google Scholar
Haug, H. (1986). History of neuromorphometry. J Neurosci Methods 18, 1–17.Google Scholar
Hatton, W.J. & Von Bartheld, C.S. (1999). Analysis of cell death in the trochlear nucleus of the chick embryo: Calibration of the disector counting method reveals systematic bias. J Comp Neurol 409, 169–186.Google Scholar
Hedreen, J.C. (1998). Lost caps in histological counting methods. Anat Rec 250, 366–372.Google Scholar
Helander, K.G. (1983). Thickness variations within individual paraffin and glycol methacrylate sections. J Microsc 132, 223–227.Google Scholar
Hell, S., Reiner, G., Cremer, C. & Stelzer, E.H.Z. (1993). Aberrations in confocal fluorescence microscopy induced by mismatches in refractive index. J Microsc 169, 391–405.Google Scholar
Heller, B., Schwingruber, F., Guvenc, D. & Heller, A. (2001). Computer experiments to determine whether over-or under-counting necessarily affects the determination of difference in cell number between experimental groups. J Neurosci Methods 91, 91–99.Google Scholar
Howard, V., Reid, S., Baddeley, A. & Boyde, A. (1985). Unbiased estimation of particle density in the tandem scanning reflected light microscope. J Microsc 138, 203–212.Google Scholar
Ibáñez-Sandoval, O., Tecaupetla, F., Unal, B., Shah, F., Koós, T. & Tepper, J.M. (2010). Electrophysiological and morphological characteristics and synaptic connectivity of tyrosine hydroxylase-expressing neurons in adult mouse striatum. J Neurosci 30, 6999–7016.Google Scholar
Janáček, J., Kreft, M., Cebašek, V. & Eržen, I. (2012). Correcting the axial shrinkage of skeletal muscle thick sections visualized by confocal microscopy. J Microsc 246, 107–112.Google Scholar
Konigsmark, B.W. (1970). Methods for the counting of neurons. In Contemporary Research Methods in Neuroanatomy, Nauta, W.J.H. & Ebbesson, S.O.E. (Eds.), pp. 315–338. Berlin: Springer-Verlag.Google Scholar
Kuypers, L.C., Decraemer, W.F., Dirckwx, J.J. & Timmermans, J.P. (2005). A procedure to determine the correct thickness of an object with confocal microscopy in case of refractive index mismatch. J Microsc 218, 68–78.Google Scholar
Matthews, C. & Cordelieres, F.P. (2010). MetroloJ: An ImageJ plugin to help monitor microscopes' health. ImageJ User and Developer Conference. MetroloJ website. Available at http://imagejdocu.tudor.lu/doku.php?id=plugin:analysis:metroloj:start. retrieved July 1, 2014.Google Scholar
Messina, A., Sangter, C.L., Morrison, W.A. & Galea, M.P. (2000). Requirements for obtaining unbiased estimates of neuronal numbers in frozen sections. J Neurosci Methods 97, 133–137.Google Scholar
Negredo, P., Castro, J., Lago, N., Navarro, X. & Avendaño, C. (2004). Differential growth of axons from sensory and motor neurons through a regenerative electrode: A stereological, retrograde tracer, and functional study in the rat. Neuroscience 128, 605–615.Google Scholar
Puigdellívol-Sánchez, A., Prats-Galino, A. & Molander, C. (2006). Estimations of topographically correct regeneration to nerve branches and skin after peripheral nerve injury and repair. Brain Res 1098, 49–60.CrossRefGoogle ScholarPubMed
Rafati, A., Noorafshan, A. & Torabi, N. (2013). Stereological study of the effects of morphine consumption and abstinence on the number of neurons and oligodendrocytes in medial prefrontal cortex of rats. Anat Cell Biol 46, 191–197.Google Scholar
Ruiter, G.C., Spinner, R.J., Verhhagen, J. & Malessy, M.J. (2014). Misdirection and guidance of regenerating axons after experimental nerve injury and repair. J Neurosurg 120, 493–501.Google Scholar
Schneider, C.A., Rasband, W.S. & Eliceiri, K.W. (2012). NIH Image to ImageJ: 25 years of image analysis. Nat Methods 9, 671–675.Google Scholar
Swett, J.E., Wikholm, R.P., Blanks, R.H.I., Swett, A.L. & Conley, L.C. (1986). Motoneurons of the rat sciatic nerve. Exp Neurol 93, 227–252.Google Scholar
Swett, J.E., Torigoew, Y., Elie, V.R., Bourassa, C.M & Miller, P.,G. (1991). Sensory neurons of the rat sciatic nerve. Exp Neurol 114, 82–103.Google Scholar
Van de Berg, W.D.J., Schmitz, C., Steinbusch, H.W.M. & Blanco, C.E. (2002). Perinatal asphyxia induced neuronal loss by apoptosis in the neonatal rat striatum: A combined TUNEL and stereological study. Exp Neurol 174, 29–36.CrossRefGoogle ScholarPubMed
Ward, T.S., Rosen, G.D. & Von Bartheld, C.S. (2008). Optical disector counting in cryosections and vibratome sections underestimates particle numbers: Effects of tissue quality. Microsc Res Tech 71, 60–68.Google Scholar
Williams, R.W. & Rakic, P. (1988). Three-dimensional counting: an accurate and direct method to estimate numbers of cells in sectioned material. J Comp Neurol 278, 344–352. Erratum in 1989, 281: 355.Google Scholar
Zhao, Y.Y., Shi, X.Y., Zhang, L., Wu, H., Chao, F.L., Huang, C.S., Gao, Y., Qiu, X., Chen, L., Lu, W. & Tang, Y. (2013). Enriched environment induces higher CNPase positive cells in aged rat hippocampus. Neurosci Lett 555, 177–181.Google Scholar