Neuroscience Letters 404 (2006) 20–22
Lack of relationship between cellular density and either capillary density or metabolic rate in different regions of the brain Atik Baborie a,∗ , Wolfgang Kuschinsky b a
Department of Neuropathology, Newcastle General Hospital, Westgate Road, NE4 6BE, Newcastle upon Tyne, UK b Department of Physiology, University of Heidelberg, Germany Received 9 January 2006; received in revised form 11 April 2006; accepted 5 May 2006
Abstract Whereas a pronounced correlation exists between local cerebral glucose utilization (LCGU) and capillary density in different regions of the brain, it is not known whether these parameters also correlate with the overall density of nuclei (cellularity). Therefore, cellularity was determined by diamidino-phenylindol (DAPI) fluorescent staining of nuclei in acetone-fixed frozen sections of the rat brain. A comparison of the density of nuclei in different brain regions showed much less variation than that observed in LCGU and capillary density. No correlation was found between nuclear density and either LCGU or capillary densities. In conclusion the cellular density is not a determinant of variation in LCGU and capillary density. © 2006 Elsevier Ireland Ltd. All rights reserved. Keywords: Cellularity; Brain; Capillary; LCGU; LCBF; Metabolism
Previous studies have shown a regional heterogeneity of local cerebral glucose utilization (LCGU) and capillary density in the rat brain [6,10]. A comparison of different brain structures has demonstrated a clear correlation between LCGU and capillary density [10]. Structures of the white matter had low glucose utilization and a low capillary density whereas structures of high glucose utilization, like the inferior colliculus, had a high capillary density [5,10]. Whereas it is known that these parameters also correlate with the local cerebral blood flow [10], it has not been determined whether a local heterogeneity also exists for the density of cells in the brain. The purpose of this study was to determine the density of cells in different structures of the brain in the rat by measuring the density of the nuclear DNA. These results were then compared with functional parameters; local cerebral glucose utilization and capillary density. The values for LCGU and capillary density referred to are from previous work by our group [5,10]. Animal experiments were performed according to institutional guidelines and to the European Communities Council Directive of November 24, 1986. They were performed on eight male Sprague–Dawley rats weighing 320–390 g. After decap-
∗
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[email protected] (A. Baborie).
0304-3940/$ – see front matter © 2006 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2006.05.008
itation the brain was rapidly removed, frozen in isofluran and chilled to −40 ◦ C with dry ice. The brain was embedded (M-1 Embedding Matrix; Lipshaw., Detroit, MI, USA) and cut after maximally 13 days storage at −70 ◦ C into 6 m coronal sections in a cryomicrotome (Jung, Nussloch, Germany) at −21 ◦ C. The sections were transferred to slides and floated with acetone at room temperature. The 10 investigated brain structures were identified while cutting the brain in the microtome [9]. A DAPI [Serva recipe, data sheet no. 4: 4 ,6-Diamidino2-phenylindole.2 HCl (DAPI), catalog no. 18860] dilution 0.1 g/ml was prepared prior to cutting the brain. For this purpose the stock solution was diluted with PBS-buffer (NaCl 8.0 g/l, KCl 0.2 g/l, KH2 PO4 0.2 g/l and Na2 HPO4 water free 1.15 g/l, pH 7.4) at 1:1000. The acetone-fixed sections were stained with DAPI-dilution (50–75 l per slide) and kept in a wet chamber for 30 min. The slides were rinsed for 3× 5 min in PBS-buffer. The prepared sections were observed by fluorescent microscopy (Zeiss IV FL condensor) and a high-pressure mercury lamp (HBO 50; Zeiss) as a light source. DAPI could be visualized by use of a 365 nm primary filter, a 395 nm interference mirror and a 397 nm secondary filter. The brain sections were inspected and photographed using a 40× objective (neofluar) and a 10× eyepiece, a camera (Contax 139 quartz) and an AGFA Pan 400 film. The exposure time was 1 s. For each brain struc-
A. Baborie, W. Kuschinsky / Neuroscience Letters 404 (2006) 20–22
ture investigated, the number of visible nuclei per section was counted from at least 16 photographs taken from 5 brain sections (alternating sides) and calculated for an area of 1 mm2 . Each photograph permitted the analysis of an area of 0.08 mm2 per brain section. The minimum area analyzed for each brain structure in each animal was 1.2 mm2 . The developed films were analyzed with a computerized monitor screen (Signum company, Munich, screen memory of Imaging Technology, Woburn, MA, Hostcomputer DEC/PDP 11/73 with operation system RT-11). Each slide (black and white, 24 mm × 36 mm) was taken with a CCD-camera (HR600, aqua-tv, Kempten), digitized and stored in the monitor’s screen (512 × 512 × 8 bit). Each picture was binarized by setting threshold levels under visual control and the whole area of nuclei calculated in percentage of the whole picture. Furthermore, the number of nuclei per picture was counted and referred to 1 mm2 . The values of nuclear density/mm2 and area of nuclei were analyzed statistically with an IBM-PC. Using the Students’ t-test and the critical t-values corrected according to Bonferroni [11]. The level of significance was set at p < 0.05. Linear regression lines were calculated for the relationship between nuclear densities, areas of nuclei, LCGU and capillary densities. These parameters, LCGU and local cerebral capillary density, have been measured earlier and are described in previous publications (see [5] for capillary density and [10] for LCGU). Table 1 shows the values for nuclear density and area of nuclei in different brain structures. The variation of both parameters by a factor of two indicates minor differences in both parameters between different brain structures. Fig. 1 shows the relationship between the density of the nuclei and the local capillary density/mm2 . Fig. 2 shows the relationship between the density of nuclei and the local cerebral glucose utilization [mol/100 g/min]. Previous studies by our group have shown heterogeneities of the local distribution of cerebral capillary density, cerebral blood flow (LCBF) and cerebral glucose utilization in the rat
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Fig. 1. Relationship between capillary density and density of nuclei in different brain structures. For both parameters mean values and standard error of the mean (S.E.M.) have been calculated from sum of all local values measured in each structure. The linear regression equation was Y = 1615.17 − 1.14x. The correlation coefficient (−0.06) was not significantly different from zero (p < 0.05).
Fig. 2. Relationship between local cerebral glucose utilization and density of nuclei in different brain structures. For both parameters mean values and standard error of the mean (S.E.M.) have been calculated from the sum of all local values measured in each structure (6–8 rats) [9]. The linear regression equation was Y = 1646.65 − 0.91x. The correlation coefficient (−0.14) was not significantly different from zero (p < 0.05).
Table 1 Mean value of counted nuclei/mm2 and measured nuclear area (%) Brain structures Genu corporis callosi Superior colliculus Hippocampus Inferior colliculus Visual cortex Medial geniculate body Caudate nucleus Auditory cortex Frontal cortex Cerebellar peduncle
Nuclei (n/mm2 ) ±S.E.M. 2099 1856 1784 1700 1594 1494 1432 1359 1277 1100
± ± ± ± ± ± ± ± ± ±
61.7a1 99.9a2 47.5a3 88.5a4 53.0a5 21.0a6 16.9a6 25.2 40.6 58.6
Area of nuclei (%) ±S.E.M. 11.3 10.3 12.7 8.7 9.1 8.6 7.9 6.9 6.8 5.2
± ± ± ± ± ± ± ± ± ±
0.5b1 1.0b2 0.6b3 0.6b4 0.4b4 0.7b4 0.3b4 0.4 0.3 0.4
n
Investigated sections
8 8 6 8 8 7 8 8 7 8
40 40 30 40 40 35 40 40 35 40
The values for density of the nuclei have been ordered in decreasing order in different brain structures. n number of animals; significant differences in the density and area of the nuclei have been superscripted with a and b, respectively. For the density of the nuclei it follows: a1: significant difference to hippocampus and all following structures; a2: significant difference to visual cortex and all following structures; a3: significant difference to caudate nucleus and all following structures; a4: significant difference to auditory cortex and all following structures; a5: significant difference to frontal cortex and the following structure; a6: significant difference to cerebellar peduncle. For the area of nuclei it follows: b1: significant difference to inferior colliculus, medial geniculate body and all following structures; b2: significant difference to auditory cortex and all following structures; b3: significant difference to inferior colliculus and all following structures; b4: significant difference to cerebellar peduncle.
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A. Baborie, W. Kuschinsky / Neuroscience Letters 404 (2006) 20–22
brain; these local functional parameters were highly correlated with each other [5,6,10]. The heterogeneity of these parameters in different brain regions has been regarded as a reflection of differences in local brain activity [7,8]. However, the basis of this postulate is not understood. One possible explanation for this heterogeneity is a varying density of cells in different parts of the brain. Thus, a higher density of cells could correlate with a higher blood flow, capillary density or glucose metabolism in the present study. In order to test this hypothesis, in the present study ten brain structures were chosen for staining of nuclei to measure nuclear density. The brain structures selected for the present study had previously been analyzed with respect to their capillary density, LCGU and LCBF [5,6,10] by our group. We could show that both the area and the density of the nuclei are not homogeneously distributed in different brain areas. In addition, a linear relationship was observed between the density of nuclei/mm2 and the area of nuclei (percentage of area of nuclei per whole area in an image from one region). However, we did not observe a correlation between each of these morphological parameters and any of the functional parameters (LCGU, capillary density) in the structures analyzed (Figs. 1 and 2). To answer the question whether heterogeneities in capillary density, LCGU and LCBF are reflected in heterogeneities of cell nuclei, the fluorochrome DAPI has been used in the present study to determine the density of nuclei. It is known that DAPI stains all possible nuclei in the structures examined (i.e. endothelial cells, neurons, astrocytes and microglial cells). It is therefore impossible to draw any conclusion about relative differences, e.g. ratios neurons/glia from the present data. The new finding of the present study was a surprising constancy of nuclear counts in different brain structures in which major differences in capillary density, LCBF and LCGU were observed. At least two possibilities exist to explain these results. The first is that different brain structures contain cells of structure-dependent metabolic activity. Brain structures which contain preferentially cells of low metabolic activity may therefore show a lower metabolic activity, but not a low cell number and vice versa. Second, the state of functional activity varies between different brain structures resulting in an either high or low metabolic activity of a brain structure at a comparable nuclear density. Besides capillary densities, capillary diameters might vary between brain structures in relation to the density of nuclei. However, such a possibility could be excluded since capillary diameters do not vary between different brain structures [2]. What could be the cause of variations in capillary density and LCGU at a rather constant nuclear density? A positive correlation has been found between these parameters and oxidative enzyme activity in synaptic terminal fields [1]; in addition, neural electrical activity was related to mitochondrial density [12] or dendritic arborizations [3]. Whereas mitochondrial density
has not been quantified for the brain generally, the distribution of the key enzyme of the inner mitochondrial membrane, i.e. cytochrome c oxidase, has been intensely investigated. It could be shown that the enzyme levels are heterogeneously distributed and are directly related to the level of neuronal activity [12]. Cytochrome c oxidase was particularly enriched at synaptic structures, i.e. dendrites and axon terminals. Therefore, the density of synapses may be a decisive parameter for the uneven local distribution of LCGU and capillary density. Synaptogenesis involves neuronal and non-neuronal cells, mainly astrocytes [4]. In conclusion, the area and numerical density of nuclei are moderately heterogeneous in the brain. The density of these anatomical parameters, however, does not correlate with the regional capillary density or with LCGU. Parameters other than nuclear density may determine regional heterogeneities of capillary density or LCGU. Acknowledgments We thank Dr. Helmut Schr¨ock for statistical evaluation and Dr. Astrid Ensslin for editorial assistance. References [1] I.W. Borowsky, R.C. Collins, Metabolic anatomy of brain: a comparison of regional capillary density, glucose metabolism, and enzyme activities, J Comp. Neurol. 288 (1989) 401–413. [2] R. Duelli, W. Kuschinsky, Changes in brain capillary diameter during hypocapnia and hypercapnia, J. Cereb. Blood Flow Metabol. 13 (1993) 1025–1028. [3] M. Erecinska, S. Cherian, I.A. Silver, Energy metabolism in mammalian brain during development, Prog. Neurobiol. 73 (2004) 397– 445. [4] R.D. Fields, B. Stevens-Graham, New insights into neuron-glia communication, Science 298 (2002) 556–562. [5] U. G¨obel, H. Theilen, W. Kuschinsky, Congruence of total and perfused capillary network in rat brains, Circ. Res. 66 (1990) 271–281. [6] B. Klein, W. Kuschinsky, H. Schr¨ock, F. Vetterlein, Interpendency of local capillary density, blood flow and metabolism in rat brains, Am. J. Physiol. (1986) H1333–H1340. [7] D. Kleinfeld, P.P. Mitra, F. Helmchen, W. Denk, Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex, Proc. Natl. Acad. Sci. U.S.A. 95 (26) (1998) 15741–15746. [8] W. Kuschinsky, O.B. Paulson, Capillary circulation in the brain, Cerebrovasc. Brain Metab. Rev. 4 (1992) 261–286. [9] G. Paxinos, C. Watson, The Rat Brain in Stereotactic Coordinates, Academic Press, 1982. [10] H. Schr¨ock, W. Kuschinsky, Cerebral blood flow, glucose use and CSF ionic regulation in potasium depleted rats, Am. J. Physiol. (1988) H250–H257. [11] S. Wallenstein, C.L. Zucker, J.L. Fleiss, Some statistical methods useful in circulation research, Circ. Res. 47 (1980) 1–9. [12] M.T. Wong-Riley, Cytochrome oxidase: an endogenous metabolic marker for neuronal activity, Trends Neurosci. 12 (1989) 94–101.
