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How to count cells: the advantages and disadvantages of the isotropic fractionator compared with stereology

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Abstract

The number of cells comprising biological structures represents fundamental information in basic anatomy, development, aging, drug tests, pathology and genetic manipulations. Obtaining unbiased estimates of cell numbers, however, was until recently possible only through stereological techniques, which require specific training, equipment, histological processing and appropriate sampling strategies applied to structures with a homogeneous distribution of cell bodies. An alternative, the isotropic fractionator (IF), became available in 2005 as a fast and inexpensive method that requires little training, no specific software and only a few materials before it can be used to quantify total numbers of neuronal and non-neuronal cells in a whole organ such as the brain or any dissectible regions thereof. This method entails transforming a highly anisotropic tissue into a homogeneous suspension of free-floating nuclei that can then be counted under the microscope or by flow cytometry and identified morphologically and immunocytochemically as neuronal or non-neuronal. We compare the advantages and disadvantages of each method and provide researchers with guidelines for choosing the best method for their particular needs. IF is as accurate as unbiased stereology and faster than stereological techniques, as it requires no elaborate histological processing or sampling paradigms, providing reliable estimates in a few days rather than many weeks. Tissue shrinkage is also not an issue, since the estimates provided are independent of tissue volume. The main disadvantage of IF, however, is that it necessarily destroys the tissue analyzed and thus provides no spatial information on the cellular composition of biological regions of interest.

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References

  • Andersen BB, Korbo L, Pakkenberg BJ (1992)A quantitative study of the human cerebellum with unbiased stereological techniques.Comp Neurol 326:549–560

  • Andrade-Moraes CH, Oliveira-Pinto AV, Castro-Fonseca E, Silva CG da, Guimarães DM, Szczupak D, Parente-Bruno DR, Carvalho LR, Polichiso L, Gomes BV, Oliveira LM, Rodriguez RD, Leite RE, Ferretti-Rebustini RE, Jacob-Filho W, Pasqualucci CA, Grinberg LT, Lent R (2013) Cell number changes in Alzheimer’s disease relate to dementia, not to plaques and tangles. Brain 136:3738–3752

  • Azevedo FA, Carvalho LR, Grinberg LT, Farfel JM, Ferretti RE, Leite RE, Jacob Filho W, Lent R, Herculano-Houzel S (2009) Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. J Comp Neurol 513:532–541

    Article  PubMed  Google Scholar 

  • Bahney J, Bartheld CS von (2014) Validation of the isotropic fractionator: comparison with unbiased stereology and DNA extraction for quantification of glial cells. J Neurosci Methods 222:165–174

  • Bandeira F, Lent R, Herculano-Houzel S (2009) Changing numbers of neuronal and non-neuronal cells underlie postnatal brain growth in the rat. Proc Natl Acad Sci U S A 106:14108–14113

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Bartheld CS von (2001) Comparison of 2-D and 3-D counting: the need for calibration and common sense. Trends Neurosci 24:504–506

  • Bartheld C von (2002) Counting particles in tissue sections: choices of methods and importance of calibration to minimize biases. Histol Histopathol 17:639–648

  • Baryshnikova LM, Von Bohlen Und Halbach O, Kaplan S, Bartheld CS von (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

  • Brautigam H, Steele JW, Westaway D, Fraser PE, StGeorge-Hyslop PH, Gandy S, Hof PR, Dickstein DL (2012) The isotropic fractionator provides evidence for differential loss of hippocampal neurons in two mouse models of Alzheimer’s disease. Mol Neurodegener 7:58

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Calhoun ME, Kurth D, Phinney AL, Long JM, Hengemihle J, Mouton PR, Ingram DK, Jucker M (1998) Hippocampal neuron and synaptophysin-positive bouton number in aging C57BL/6 mice. Neurobiol Aging 19:599–606

    Article  CAS  PubMed  Google Scholar 

  • Carlo CN, Stevens CF (2013) Structural uniformity of neocortex, revisited. Proc Natl Acad Sci U S A 110:1488–1493

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Charvet CJ, Cahalane DJ, Finlay BL (2015) Systematic, cross-cortex variation in neuron numbers in rodents and primates. Cereb Cortex 25:147–160

    Article  PubMed  Google Scholar 

  • Coggeshall RE, Lekan HA (1996) Methods for determining numbers of cells and synapses: a case for more uniform standards of review. J Comp Neurol 364:6–15

    Article  CAS  PubMed  Google Scholar 

  • Coggeshall RE, Chung K, Greenwood D, Hulsebosch CE (1984) An empirical method for converting nucleolar counts to neuronal numbers. J Neurosci Methods 12:125–132

    Article  CAS  PubMed  Google Scholar 

  • Coggeshall RE, La Forte R, Klein CM (1990) Calibration of methods for determining numbers of dorsal root ganglion cells. J Neurosci Methods 35:187–194

    Article  CAS  PubMed  Google Scholar 

  • Collins CE, Airey DC, Young NA, Leitch DB, Kaas JH (2010a) Neuron densities vary across and within cortical areas in primates. Proc Natl Acad Sci U S A 107:15927–15932

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Collins CE, Young NA, Flaherty DK, Airey DC, Kaas JH (2010b) A rapid and reliable method of counting neurons and other cells in brain tissue: a comparison of flow cytometry and manual counting methods. Front Neuroanat 9:5

    Google Scholar 

  • Dobbing J, Sands J (1973) Quantitative growth and development of human brain. Arch Dis Child 48:757–767

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Dorph-Petersen KA, Pierri JN, Sun Z, Sampson AR, Lewis DA (2004) Stereological analysis of the mediodorsal thalamic nucleus in schizophrenia: volume, neuron number, and cell types. J Comp Neurol 472:449–462

    Article  PubMed  Google Scholar 

  • Dorph-Petersen KA, Caric D, Saghafi R, Zhang W, Sampson AR, Lewis DA (2009) Volume and neuron number of the lateral geniculate nucleus in schizophrenia and mood disorders. Acta Neuropathol 117:369–384

    Article  PubMed Central  PubMed  Google Scholar 

  • Geuna S, Herrera-Rincon (2015) Update on stereology for light microscopy. Cell Tissue Res [current issue]

  • Guillery RW (2002) On counting and counting errors. J Comp Neurol 447:1–7

    Article  CAS  PubMed  Google Scholar 

  • Guillery RW, Herrup K (1997) Quantification without pontification: choosing a method for counting objects in sectioned tissues. J Comp Neurol 386:2–7

    Article  CAS  PubMed  Google Scholar 

  • Gundersen HJ (1986) Stereology of arbitrary particles. A review of unbiased number and size estimators and the presentation of some new ones, in memory of William R. Thompson. J Microsc 143:3–45

    Article  CAS  PubMed  Google Scholar 

  • Gundersen HJ, Bendtsen TF, Korbo L, Marcussen N, Møller A, Nielsen K, Nyengaard JR, Pakkenberg B, Sørensen FB, Vesterby A, West MJ (1988) Some new, simple and efficient stereological methods and their use in pathological research and diagnosis. APMIS 96:379–394

  • Hall DH, Russell RL (1991) The posterior nervous system of the nematode Caenorhabditis elegans: serial reconstruction of identified neurons and complete pattern of synaptic interactions. J Neurosci 11:1–22

    CAS  PubMed  Google Scholar 

  • Hatton WJ, Bartheld CS von (1999) Analysis of cell death in the trochlear nucleus of the chick embryo: calibration of the optical disector counting method reveals systematic bias. J Comp Neurol 409:169–186

  • Heller IH, Elliott KA (1954) Desoxyribonucleic acid content and cell density in brain and human brain tumors. Can J Biochem Physiol 32:584–592

    Article  CAS  PubMed  Google Scholar 

  • Herculano-Houzel S (2012) The isotropic fractionator: a fast, reliable method to determine numbers of cells in the brain or other tissues. In: Fellin T, Halassa MM (eds) Springer neuromethods: neuronal network analysis: concepts and experimental approaches, vol 67. Humana, New York, pp 391–403

    Chapter  Google Scholar 

  • Herculano-Houzel S, Kaas JH (2011) Gorilla and orangutan brains conform to the primate cellular scaling rules: implications for human evolution. Brain Behav Evol 77:33–44

    Article  PubMed Central  PubMed  Google Scholar 

  • Herculano-Houzel S, Lent R (2005) Isotropic fractionator: a simple, rapid method for the quantification of total cell and neuron numbers in the brain. J Neurosci 25:2518–2521

    Article  CAS  PubMed  Google Scholar 

  • Herculano-Houzel S, Watson C, Paxinos G (2013) Distribution of neurons in functional areas of the mouse cerebral cortex reveals quantitatively different cortical zones. Front Neuroanat 7:35

    Article  PubMed Central  PubMed  Google Scholar 

  • Herculano-Houzel S, Avelino-de-Souza K, Neves K, Porfirio J, Messeder D, Mattos Feijó L, Maldonado J, Manger PR (2014) The elephant brain in numbers. Front Neuroanat 8:46

    PubMed Central  PubMed  Google Scholar 

  • Hess HH, Thalheimer C (1971) DNA and RNA and the cytoarchitecture of human frontal cortex. J Neurochem 18:1281–1290

    Article  CAS  PubMed  Google Scholar 

  • Insausti AM, Megías M, Crespo D, Cruz-Orive LM, Dierssen M, Vallina IF, Insausti R, Flórez J (1998) Hippocampal volume and neuronal number in Ts65Dn mice: a murine model of Down syndrome. Neurosci Lett 253:175–178

    Article  CAS  PubMed  Google Scholar 

  • Kaplan S, Geuna S, Ronchi G, Ulkay MB, Bartheld CS von (2010) Calibration of the stereological estimation of the number of myelinated axons in the rat sciatic nerve: a multicenter study. J Neurosci Methods 187:90–99

  • Korbo L, Andersen BB, Ladefoged O, Møller A (1993) Total numbers of various cell types in rat cerebellar cortex estimated using an unbiased stereological method. Brain Res 609:262–268

    Article  CAS  PubMed  Google Scholar 

  • Mayhew TM (1991) Accurate prediction of Purkinje cell number from cerebellar weight can be achieved with the fractionator. J Comp Neurol 308:162–168

    Article  CAS  PubMed  Google Scholar 

  • Miller DJ, Duka T, Stimpson CD, Schapiro SJ, Baze WB, McArthur MJ, Fobbs AJ, Sousa AMM, Sestan N, Wildman DE, Lipovich L, Kuzawa CW, Hof PR, Sherwood CC (2012) Prolonged myelination in human neocortical evolution. Proc Natl Acad Sci U S A 109:16480–16485

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Miller DJ, Lackey EP, Hackett TA, Kaas JH (2013) Development of myelination and cholinergic innervation in the central auditory system of a prosimian primate (Otolemur garnetti). J Comp Neurol 521:3804–3816

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Miller DJ, Balaram P, Young N, Kaas JH (2014) Three counting methods agree on cell and neuron number in chimpanzee primary visual cortex. Front Neuroanat 8:36. doi:10.3389/fnana.2014.00036

    Article  PubMed Central  PubMed  Google Scholar 

  • Mullen RJ, Buck CR, Smith AM (1992) NeuN, a neuronal specific nuclear protein in vertebrates. Development 116:201–211

    CAS  PubMed  Google Scholar 

  • Pakkenberg B, Gundersen HJ (1988) Total number of neurons and glial cells in human brain nuclei estimated by the disector and the fractionator. J Microsc 150:1–20

    Article  CAS  PubMed  Google Scholar 

  • Peters A, Morrison JH, Rosene DL, Hyman BT (1998) Feature article: are neurons lost from the primate cerebral cortex during normal aging? Cereb Cortex 8:295–300

    Article  CAS  PubMed  Google Scholar 

  • Popken GJ, Bunney WE Jr, Potkin SG, Jones EG (2000) Subnucleus-specific loss of neurons in medial thalamus of schizophrenics. Proc Natl Acad Sci U S A 97:9276–9280

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Rapp PR, Gallagher M (1996) Preserved neuron number in the hippocampus of aged rats with spatial learning deficits. Proc Natl Acad Sci U S A 93:9926–9930

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Rasmussen T, Schliemann T, Sørensen JC, Zimmer J, West MJ (1996) Memory impaired aged rats: no loss of principal hippocampal and subicular neurons. Neurobiol Aging 17:143–147

    Article  CAS  PubMed  Google Scholar 

  • Ribeiro PFM, Ventura-Antunes L, Gabi M, Mota B, Grinberg LT, Farfel JM, Ferretti REL, Leite REP, Jacob Filho W, Herculano-Houzel S (2013) The human cerebral cortex is neither one nor many: neuronal distribution reveals two quantitatively different zones in the grey matter, three in the white matter, and explains local variations in cortical folding. Front Neuroanat 7:28

    Article  PubMed Central  PubMed  Google Scholar 

  • Schmitz C, Hof PR (2000) Recommendations for straightforward and rigorous methods of counting neurons based on a computer simulation approach. J Chem Neuroanat 20:93–114

    Article  CAS  PubMed  Google Scholar 

  • Schmitz C, Hof PR (2005) Design-based stereology in neuroscience. Neuroscience 130:813–831

    Article  CAS  PubMed  Google Scholar 

  • Schmitz C, Korr H, Heinsen H (1999) Design-based counting techniques: the real problems. Trends Neurosci 22:345–346

    Article  CAS  PubMed  Google Scholar 

  • Selemon LD, Begovic A (2007) Stereologic analysis of the lateral geniculate nucleus of the thalamus in normal and schizophrenic subjects. Psychiatry Res 151:1–10

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Tsai PS, Kaufhold JP, Blinder P, Friedman B, Drew PJ, Karten HJ, Lyden PD, Kleinfeld D (2009) Correlations of neuronal and microvascular densities in murine cortex revealed by direct counting and colocalization of nuclei and vessels. J Neurosci 29:14553–14570

    Article  CAS  PubMed  Google Scholar 

  • Verkhratsky A, Butt A (2013) Glial physiology and pathophysiology. Wiley-Blackwell, Oxford

    Book  Google Scholar 

  • Ward S, Thomson N, White JG, Brenner S (1975) Electron microscopical reconstruction of the anterior sensory anatomy of the nematode Caenorhabditis elegans. J Comp Neurol 160:313–337

    Article  CAS  PubMed  Google Scholar 

  • West MJ (1999) Stereological methods for estimating the total number of neurons and synapses: issues of precision and bias. Trends Neurosci 22:51–61

    Article  CAS  PubMed  Google Scholar 

  • West MJ, Gundersen HJ (1990) Unbiased stereological estimation of the number of neurons in the human hippocampus. J Comp Neurol 296:1–22

    Article  CAS  PubMed  Google Scholar 

  • Williams RW, 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

    Article  CAS  PubMed  Google Scholar 

  • Williams RW, Bartheld CS von, Rosen GD (2003) Counting cells in sectioned material: a suite of techniques, tools, and tips. Curr Protoc Neurosci 24:1.11.1–1.11.29

  • Young NA, Flaherty DK, Airey DC, Varlan P, Aworunse F, Kaas JH (2012) Use of flow cytometry for high-throughput cell population estimates in brain tissue. Front Neuroanat 6:27. doi:10.3389/fnana.2012.00027

    Article  PubMed Central  PubMed  Google Scholar 

  • Young NA, Szabó CÁ, Phelix CF, Flaherty DK, Balaram P, Foust-Yeoman KB, Collins CE, Kaas JH (2013a) Epileptic baboons have lower numbers of neurons in specific areas of cortex. Proc Natl Acad Sci U S A 110:19107–19112

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Young NA, Collins CE, Kaas JH (2013b) Cell and neuron densitites in the primary motor cortex of primates. Front Neural Circuits 7:30

    Article  PubMed Central  PubMed  Google Scholar 

  • Zamenhof S, Bursztyn H, Rich K, Zamenhof PJ (1964) The determination of deoxyribonucleic acid and of cell number in brain. J Neurochem 11:505–509

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

Thanks to Roberto Lent for supporting the creation of the isotropic fractionator, to Nicole Young and Christine Collins for establishing the automated variation and to Paul Manger for insights on tissue storage. Flow cytometry experiments were conducted in the Vanderbilt Medical Center Flow Cytometry Shared Resource and aided by the expertise of David K. Flaherty.

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Authors and Affiliations

  1. Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil

    Suzana Herculano-Houzel

  2. Instituto Nacional de Neurociência Translacional, Ministério de Ciência e Tecnologia, Sao Paulo, Brazil

    Suzana Herculano-Houzel

  3. Department of Physiology and Cell Biology, University of Nevada School of Medicine, Reno, NV 89557, USA

    Christopher S. von Bartheld

  4. Department of Psychology, Vanderbilt University, Nashville, TN 37240, USA

    Daniel J. Miller & Jon H. Kaas

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  1. Suzana Herculano-Houzel
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  2. Christopher S. von Bartheld
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  3. Daniel J. Miller
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  4. Jon H. Kaas
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Corresponding author

Correspondence to Suzana Herculano-Houzel.

Additional information

The development and improvement of the isotropic fractionator was made possible by grants from CNPq and FAPERJ to Suzana Herculano-Houzel. Work comparing the isotropic fractionator with other methods was supported by NIH grants NS079884 and GM103554 (Center of Biomedical Research Excellence from the National Institute of General Medical Science) to Christopher von Bartheld and by a grant from the G. Harold and Leila Y. Mathers Foundation to Jon H. Kaas. Flow cytometry experiments were conducted in the Vanderbilt Medical Center Flow Cytometry Shared Resource, which is supported by the Vanderbilt Ingram Cancer Center (P30 CA68485) and the Vanderbilt Digestive Disease Research Center (DK058404).

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Herculano-Houzel, S., von Bartheld, C.S., Miller, D.J. et al. How to count cells: the advantages and disadvantages of the isotropic fractionator compared with stereology. Cell Tissue Res 360, 29–42 (2015). https://doi.org/10.1007/s00441-015-2127-6

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