| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MITOCHONDRIAL MODELING AND FUNCTION
1Faculty of Life Sciences, The University of Manchester, Manchester, United Kingdom; and 2Institute of Cybernetics, Tallinn University of Technology, Tallinn, Estonia
Submitted 3 May 2006 ; accepted in final form 29 June 2006
 |
ABSTRACT |
|---|
 TOP ABSTRACT MATERIALS AND METHODSRESULTSDISCUSSIONGRANTSREFERENCES |
|---|
1.8 µm and can be found in any transversal direction relative to each other. Neighboring strands exhibit the same mitochondrial periodicity. In contrast to the rat, trout ventricular myocytes (22 cells; 5,528 mitochondrial centers) exhibit a relatively chaotic mitochondrial pattern. Neighboring mitochondria can be found in any direction relative to each other. Thus, two potential subpopulations of mitochondria in trout are not distinguishable by their pattern. The developed method required minor interaction in the filtering of the mitochondrial centers. It is therefore a practical approach to describe intracellular organization and may also be used for analysis of time-dependent organizational changes. The obtained quantitative description of mitochondrial organization is a requisite for accurate mathematical analysis of mitochondrial systems biology. confocal microscopy; quantitative analysis; rat; rainbow trout; probability density function
The organization of mitochondria may have important functional consequences. Cardiomyocytes seem to be divided into functional compartments called intracellular energetic units (ICEUs), in which adenine nucleotides are channeled between ATPases and mitochondria without being released to the cytosolic bulk solution (14, 23, 24, 35). This compartmentation is expected from experiments showing that mitochondria in skinned fibers and cardiomyocytes have a low apparent affinity for exogenous ADP in the surrounding medium but not endogenous ADP produced by ATPases. Furthermore, a competitive exogenous ADP trapping system consisting of pyruvate kinase and phosphoenolpyruvate is not able to inhibit mitochondrial consumption of endogenous ADP by >40%, although it has a 100 times higher ADP consumption capacity (28). These experimental results can only be reproduced by mathematical models if they assume large and rather localized diffusion restriction that separates mitochondria and endogenous ATPases from the surrounding solution (35). The functional advantage of such a compartmentation should be to increase the coupling of energy production to energy consumption diminishing the risk of the cardiomyocytes experiencing energy deficit (25). However, disruption of the mitochondrial regular pattern with trypsin increases the apparent affinity for exogenous ADP without affecting the maximal respiration capacity of mitochondria (23, 34). This suggests that disruption of the mitochondrial crystal-like pattern diminishes intracellular compartmentation and hence channeling of adenine nucleotides. This may in turn reduce the coupling between energy consumption and energy production leading to a compromise of the energetic status.
The overall structure and mitochondrial distribution in cardiomyocytes seem to differ between species. As noted above, rat cardiomyocytes have several longitudinal rows of mitochondria interchanged with rows of myofibrils (26, 32). The situation seems to be different in cardiomyocytes from rainbow trout (Oncorhynchus mykiss). Trout cells have a much smaller diameter and one single cylinder-shaped layer of myofibrils situated immediately beneath the sarcolemma. According to electron microscope images, this layer surrounds a central core of mitochondria with no obvious pattern (38). Despite this difference, rainbow trout cardiomyocytes also seem to be divided into functional compartments with mitochondria and ATPases forming ICEUs (5, 6). However, the fixation and dehydration of cells during their preparation for electron microscopy may produce histological artifacts (21), and to our knowledge there is currently no quantitative description of the mitochondrial pattern in live trout cardiomyocytes. Interestingly, a closer look at the energetic data reveals that skinned trout cardiac fibers actually exhibit both a low and a high apparent ADP affinity, suggesting the existence of two mitochondrial subpopulations (4). In rat, a low apparent ADP affinity is reflecting, in the first approximation, the overall diffusion restriction between the solution surrounding the fiber and mitochondrial inner membrane (23). Assuming that in the rat a low apparent ADP affinity is related to the organization of the mitochondria (34), we speculated whether the two potential subpopulations in trout might be distinguishable by their pattern.
The aim of the present study was to quantitatively analyze and compare the relative positioning of mitochondria in live rat and trout cardiomyocytes. For this, the two-dimensional quantitative approach from a previous study (34) was elaborated to encompass three dimensions. Our quantitative analysis of mitochondrial organization in the three-dimensional (3D) space shows large differences in mitochondrial patterns in trout and rat. In rat, the intermyofibrillar mitochondria are highly ordered. In contrast to rat, the arrangement of mitochondria in trout is rather random, or chaotic.
|
MATERIALS AND METHODS |
|---|
|
TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONGRANTSREFERENCES |
|---|
Isolated cardiomyocytes. Isolated rat cardiomyocytes were kindly provided by Louise Miller and were prepared according to the procedure of Eisner et al. (12). They were kept at room temperature in a solution consisting of (in mM) 115 NaCl, 10 HEPES, 11.1 glucose, 1.2 NaH2PO4, 1.2 MgSO4, 4 KCl, 50 taurine, and 0.1 CaCl2, titrated to pH 7.34 with NaOH.
Rainbow trout were obtained from Chirk Trout Farm and kept in freshwater tanks at 15°C. They were kept at a 12:12-h light:dark cycle and regularly fed with commercial trout pellets. Rainbow trout cardiomyocytes were isolated, as described in Shiels et al. (29). Briefly, the fish were humanely killed by a Schedule 1 method according to the Animal Scientific Procedures Act 1986 published by the United Kingdom Home Office, and the heart was quickly excised and transferred to ice-cold isolation solution consisting of (in mM) 100 NaCl, 10 KCl, 12 KH2PO4, 4 MgSO4, 50 taurine, 20 glucose, and 10 HEPES (adjusted to pH 6.9 using KOH). A cannula was inserted into the ventricle through the bulbus arteriosus, and the heart was perfused in a retrograde manner with isolation solution bubbled with 99% O2. After the heart was perfused with Ca2+-free isolation solution for 10 min to clear the myocardium of blood and relax the myofibrils, the perfusion solution was changed to a digestion solution consisting of isolation solution containing trypsin, collagenase, and BSA. Perfusion with digestive enzymes lasted 14 min. The heart was then taken off the cannula, quickly dried on a piece of paper to remove any solution with digestive enzymes, and transferred to fresh, ice-cold isolation solution. The ventricle was cut into small pieces, which were triturated with a Pasteur pipette to obtain isolated ventricular myocytes. The trout cardiomyocytes were kept in isolation solution in a refrigerator until use.
Confocal imaging of mitochondria in cardiomyocytes. MitoTracker red CMXRos is a membrane-permeable derivative of the redox-sensitive dye X-rosamine. Visible dye therefore accumulates in the mitochondria in a potential-dependent manner. At least 15 min before the cardiomyocytes were used, 0.2 µM MitoTracker red CMXRos was added to trout cardiomyocytes in isolation solution and rat cardiomyocytes in Ringer solution, respectively. To visualize the sarcolemma in trout cardiomyocytes, 2 µM 4-{2-[6-(dioctylamino)-2-naphthalenyl]ethenyl}1-(3-sulfopropyl)-pyridinium (di-8-ANEPPS) at least 15 min before use.
A suspension of dye-loaded cells was put on a glass coverslip and the cells were visualized with the use of an inverted confocal microscope (Leica Microsystems, Heidelberg, Germany) with a x63 water-immersion objective (1.2 numerical aperture) at room temperature. MitoTracker red CMXRos was excited with a 543-nm laser and emission was recorded at 570–690 nm. Di-8-ANEPPS was excited with 488 nm and emission was recorded at 550–700 nm range. For each cell, a 3D image was generated by scanning several confocal planes (XY) at different depths (Z) of the cell (Fig. 1). This 3D image was used for further analysis. It should be noted that the z-resolution was lower than the x- and y-resolution, and that this is reflected in the results in as much as pixels are elongated in the z-direction.
|
8 pixels on the image in x- and y-directions and 2–3 images in the stack in z-direction. With the use of the blurred stack of images, local fluorescence maxima were found. Only the maxima that had a large fluorescence in ±0.25 µm (x- and y-directions) and ±0.32 µm (z-direction) were recorded for further analysis. Blurring and recording only local maxima that are largest in a relatively large box, allowed us to effectively remove stochastic fluorescence maxima that always occur during the recording of the images. The local fluorescence maxima were typically found in the mitochondrial center, although deviations may occur, and this may result in a higher spread of the data than is actually the case. However, the following calculations are based on the assumption that fluorescence maxima are found at the mitochondrial centers, and therefore, throughout the text, fluorescence maxima are referred to as mitochondrial centers. Second, for rat cardiomyocytes, subsarcolemmal mitochondria, and mitochondria around the nucleus (perinuclear mitochondria) were filtered out as judged by the eye. No filtering was applied for trout. Third, for each fluorescence maximum, the relative positions of other maxima, which were within a 6-µm radius from each other, were recorded. Fourth, the 3D probability density was computed describing the distribution of relative positions of mitochondrial centers. The density was found by dividing 3D space into 0.08 x 0.08 x 0.33 µm (x x y x z) boxes and counting the relative positions falling into each of the boxes. Fifth, the overall fiber orientation was found assuming that the two symmetrically distributed maxima of the probability density were along the fiber. The computed fiber orientation was similar to cell orientation, as judged visually. Next, the relative distances found in the third step were recalculated taking into account the fiber orientation and assuming that the y-axis was aligned along the fiber. The statistical analysis of relative positions of mitochondrial centers was performed by either calculating the probability densities (in 3D) for all mitochondria that were within a radius of 6 µm from each other or dividing the space around each of the mitochondria into the sectors and analyzing the distributions in each sector separately. Both methods were used here for analysis. The division of the space surrounding each mitochondrion is shown in Fig. 1. The sectors used in this study are based on two-dimensional analysis of mitochondrial arrangement in rat cardiomyocytes (34).
In addition to the probability densities, the relative distribution of mitochondrial centers was characterized by the cumulative distribution function. The distribution function shows the fraction of mitochondria as a function of the distance in a given direction. For this, the sectors were pooled according to the direction of their median: the two opposing sectors whose medians coincided with the x-, y-, and z-axes were termed X, Y, and Z, respectively, the four sectors whose medians coincided with y = x were termed XY, and the four sectors whose medians coincided with z = y were termed YZ (Fig. 1B). The pooling of opposing sectors is justified by the symmetry of the calculated probability density functions (see figures in RESULTS).
The programs developed for this analysis were written in Python and are available upon request. The positioning of mitochondrial centers on the image stacks was checked using IMOD [http://bio3d.colorado.edu/imod, The Boulder Laboratory for 3D Electron Microscopy of Cells Department of Molecular, Cellular, and Developmental Biology, University of Colorado (17)]. The 3D probability densities were visualized and examined using OpenDX (http://www.opendx.org).
|
RESULTS |
|---|
|
TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONGRANTSREFERENCES |
|---|
|
|
Probability density of all mitochondria within a distance of 6 µm. The probability density of all neighboring mitochondria within a radius of 6 µm is shown for rat and trout cardiomyocytes in Figs. 4 and 5, respectively. For each mitochondrial center, the relative position of neighboring mitochondrial centers within a radius of 6 µm was found and statistically analyzed. The 3D probability density found on the basis of these data is shown in Figs. 4 and 5. The six upper frames show XY-planes that cut the 3D space perpendicular to the z-axis at different z values. Since the probability density is symmetric with respect to the origin of the coordinate system (0,0,0), the planes cutting at positive z values are shown only. Likewise, the six lower frames show XZ-planes taken at different y-positions. Because local fluorescence maxima within a distance of 0.25 µm in each x- and y-direction, and within 0.32 µm in each z-direction were filtered out as described in MATERIALS AND METHODS, there is a central box of 0.50 x 0.50 x 0.64 µm (x x y x z) in which the probability density is zero.
|
|
In trout cardiomyocytes, the probability density distribution is more diffuse. As in the rat, the maximal probability density is found along the y-axis. However, in contrast to the rat, it is not delimited to the sides (Fig. 5, top). This continuity of the probability density is also observed cross-sectionally (Fig. 5, bottom). In contrast to rat, there is no ring of low probability density around the central maximum. Notably, the probability density decreases with distance from the center, but the decrease is much steeper vertically than horizontally (Fig. 5, bottom). This indicates that mitochondria are mainly distributed around a plane in trout. In contrast to rat, there is no distinguishable mitochondrial pattern: there are only two local fluorescence maxima, one on each side of the center along the y-axis.
Probability density of closest neighbors in sectors. On the basis of the regular pattern of intermyofibrillar mitochondria in rat cardiomyocytes, the considered sphere around each mitochondrial center was divided into sectors (Fig. 1). For each sector, the distribution of the closest neighboring mitochondria was described by the probability density. Figures 6 and 7 show the results from the rat and trout, respectively, and the top and bottom panels are as in Figs. 4 and 5 showing the values of the density at different planes cutting 3D space. When only the closest neighbors are considered (Figs. 6 and 7), the probability density is refined and the distances between mitochondrial centers can be identified with a greater accuracy.
|
|
In trout cardiomyocytes, despite the fact that sectors are considered separately, their probability density distributions fuse together so that the center is surrounded by an ellipsoid with a continuous, high probability density (Fig. 7, top and bottom). The probability is highest near the center and slowly decreases with distance.
Distance between mitochondrial centers. The sector-dependent distance between mitochondrial centers relative to each other (Fig. 8A) and the y-axis (Fig. 9A) was analyzed statistically using the same sectors as for Figs. 6 and 7. Opposing x-, y- and z-sectors, and diagonal sectors whose median had the same absolute angle to the XY-plane, and to the YZ-plane, were pooled because of the symmetrical mitochondrial arrangement. Here, the statistical analysis of the distances is presented using cumulative distribution functions, which show the fraction of mitochondria that are closer either to the origin (Fig. 8) or to the y-axis (Fig. 9) than a given distance.
|
|
1 µm, and a second step 1.8 µm. These two steps in the cumulative distribution function, while not very strong, are separated by a region where a smaller amount of mitochondrial centers are found leading to relatively small derivative of the distribution function 1.4 µm. The stepwise increase confirms the observation in Fig. 6 of at least two local maxima in each of the Y-sectors. Most of the mitochondria in X- and Z-sectors are slightly further away than in Y-sectors. The cumulative distribution curve rises smoothly and more steeply suggesting a lower spread of mitochondria in these directions. Not surprisingly, the mitochondria are further away in the diagonal sectors XY and YZ than in the longitudinal (Y) and transversal (X and Z) sectors. In trout cardiomyocytes, in contrast to the situation in rat, mitochondria in Y-sectors were furthest away (Fig. 8C). The cumulative distribution function for Y-sectors tended to group with the functions of the diagonal XY- and YZ-sectors at the smaller distances. The closest mitochondria were found in the transverse X- and Z-sectors. Calculating the cumulative distribution functions for the distance to the y-axis revealed a different pattern (Fig. 9). In rat, the Y-distribution function rose steeply, suggesting a small spread around the y-axis (Fig. 9B). The distribution functions for all the other sectors could be grouped together. This indicates that transverse spacing between longitudinal rows of mitochondria does not change in the longitudinal direction, i.e., the rows are parallel. In addition, this transverse spacing is the same in Y, Z, and diagonal directions.
In trout cardiomyocytes, the situation was different (Fig. 9C). The rise of the Y-distribution function was less steep suggesting a higher spread around the y-axis. Furthermore, the distance of diagonal mitochondria from the y-axis was lower than that of transversal mitochondria confirming the observations in Figs. 5 and 7 that in trout cardiomyocytes, there is no regular spacing between mitochondria.
|
DISCUSSION |
|---|
|
TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONGRANTSREFERENCES |
|---|
The mitochondrial arrangement, especially in rat cardiomyocytes, is related to the overall cell structure and myofibrillar arrangement. Rat cardiomyocytes have relatively large diameter (20 µm; Ref. 27), and electron microscope images show several rows of myofibrils interchanged with rows of mitochondria (32). Indeed, in the rat, the probability of finding a neighboring intermyofibrillar mitochondrial strand in the immediate vicinity of the central mitochondrial strand is very low (Figs. 4 and 6), and this is likely because each strand of mitochondria is surrounded by a ring of myofibrils. Outside this surrounding layer of myofibrils, parallel strands of mitochondria can be found in any direction as indicated by the cylinder of high probability density around the central strand (Figs. 4 and 6). The cumulative distribution function shows that the average distance between parallel rows of mitochondrial centers is 1.8 µm (Fig. 9). This value differs from that found in a previous study, in which the transversal distance was 1.43 µm (34). However, that study was carried out in two dimensions, and thus parallel mitochondrial rows in different planes were projected onto each other leading to underestimation of transversal distance between the mitochondrial centers.
In rat cardiomyocytes, intermyofibrillar mitochondria in parallel rows are arranged with more or less the same periodicity. Moreover, the periodicity in neighboring strands is in phase (Figs. 4 and 6), and this is what gives rise to the "crystal-like" pattern of rat mitochondria (34). While we have not determined the position of mitochondria relative to the sarcomere, this periodicity is consistent with the finding that intermyofibrillar mitochondria are mainly found at the level of the A-band of the myofilaments (18, 26, 31, 32). Thus mitochondrial periodicity is imposed by regular pattern of myofilaments in the cell. Our results differ from a previous study (34) in as much as the cumulative distribution function for the closest neighboring mitochondria in the longitudinal sectors seems to rise in several steps (Fig. 8, Y-sector). In accordance with this, the probability density in the Y-sectors seems to exhibit two local maxima: one at 1 µm and one at 1.8 µm (Fig. 6). This suggests that there are mainly two possible distances to the closest neighboring mitochondrial center. Indeed, Figs. 2A and 3A show that mitochondrial centers frequently occur in pairs. Thus the shorter distance is between paired centers and the longer distance is between single centers. This was not noted in a previous study, in which mitochondrial centers were consistently 2.0 µm apart (34). For comparison, the sarcomere length in relaxed cardiac muscle is 1.9 µm (32). The finding of paired centers may be due to differences between cardiomyocyte preparations or automatic rather than manual treatment of the data. It is uncertain whether paired centers represent two separate mitochondria or one single dog bone-shaped mitochondrion (Fig. 3A). In both cases two fluorescence maxima would be detected by the software.
The diameter of trout cardiomyocytes is relatively small (5–8 µm; Refs. 30 and 38). Figure 2B shows that in trout cardiomyocytes there is a gap between the sarcolemma and the central mitochondrial network. According to electron microscope images, this gap is due to a cylinder-shaped single layer of myofibrils that lies immediately beneath the sarcolemma and surrounds a central core of mitochondria (38). Therefore, in contrast to the rat, there is no regular transverse spacing between mitochondria. A longitudinal periodicity is lacking as well and the region with high probability density is ellipsoid shaped. This is confirmed by the cumulative distribution functions, which show that in the trout, mitochondria in the diagonal (XY and YZ) sectors compared with transverse (X and Z) sectors are closer to the y-axis (Fig. 9C). In the rat, these distributions are similar (Fig. 9B).
Skinned rat cardiomyocytes exhibit a low apparent mitochondrial ADP affinity because the intracellular environment is divided into functional compartments (ICEUs) in which adenosine nucleotides are locally channeled between ATPases and mitochondria (24). Tentatively, this compartmentation, which is specific to red muscle fibers (37), increases the coupling of energy consumption to energy production (25). In rat cardiomyocytes, a low apparent ADP affinity is related to the highly ordered organization of intermyofibrillar mitochondria (34). Intriguingly, despite the absence of an ordered mitochondrial pattern in trout cardiomyocytes, skinned fibers also exhibit a low apparent ADP affinity (4–6). Furthermore, recent evidence strongly suggests that this is due to their functional compartmentation into ICEUs (6). A closer look at skinned trout cardiac fibers reveals that they actually exhibit two apparent ADP affinities (4). This suggests the existence of two mitochondrial populations, possibly with different arrangements. However, from our present analysis, we were not able to determine the mitochondrial patterns that could be responsible for this. Thus the potential causes of two mitochondrial populations are still not clear and require further investigations.
The quantitative description of mitochondrial arrangements can be used to analyze intracellular energy fluxes and interactions between mitochondria in the cells. For example, mathematical models of oxygen transport in muscle cells, intracellular diffusion of metabolites, and propagation of mitochondrial oscillations require a geometric description of intracellular arrangement (2, 3, 36). In addition, the changes in mitochondrial organization in the heart muscle cells during ischemia (7, 15, 19) can be taken into account by the next generation of metabolic models. The quantitative approach developed by us and used to describe the organization of cardiac muscle cells gives not only the mean distances between mitochondrial centers, but the variability as well. The analysis of variability is expected to become an important aspect of intracellular modeling. Indeed, the nonlinear models used to analyze complex intracellular processes can be sensitive to small changes in parameter values indicating instability of some processes. The influence of mitochondrial arrangement and its variability can now be taken into account using the probability densities and cumulative distribution functions found in the present study for rat and trout cardiomyocytes.
In addition to the relative position of mitochondria determined in our work, several morphological aspects have to be taken into account for modeling of mitochondria in the cells. Mitochondrial morphology in many cells is not fixed but can change when the balance between fission and fusion is disturbed (22). For example, when the cardiac muscle cells are challenged by hypoxia, gigantic mitochondria, which are longer than several sarcomeres, can form (33). This is in contrast to mitochondrial morphology in normal conditions in adult rat cardiac muscle cells, where mitochondria are approximately the size of a sarcomere and are squarish and flattened in shape (26). In addition to the changes in size, depending on the cell type, the mitochondria can form an electrically continuous network (1, 13) or not (9). In adult rat cardiomyocytes, the mitochondria were found to be morphologically heterogeneous and not coupled electrically (8, 10). To our knowledge, the electric continuity has not been studied yet in trout cardiomyocytes. Another aspect of mitochondrial organization that is important for modeling oxygen fluxes in vivo is the regional intracellular differences in mitochondrial densities. For example, the mitochondrial volume density is higher near capillaries than in regions far from capillaries (16). Since we treated in our analysis all cell parts simultaneously, such gradients were ignored. Our method can be refined to take into account the regional differences in mitochondrial distribution by analyzing each region separately.
To summarize, we quantified 3D distribution of mitochondria in rat and rainbow trout cardiomyocytes by determining relative position of mitochondrial centers. While intermyofibrillar mitochondria were found to be highly ordered in the rat, mitochondria in trout are arranged in rather random pattern. The quantitative description of the arrangement can be used in the mathematical models of intracellular energy fluxes, diffusion of oxygen, and interactions between mitochondria in the cells.
|
GRANTS |
|---|
|
TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONGRANTSREFERENCES |
|---|
|
ACKNOWLEDGMENTS |
|---|
|
FOOTNOTES |
|---|
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
|
REFERENCES |
|---|
|
TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONGRANTSREFERENCES |
|---|
2. Aon MA, Cortassa S, and O'Rourke B. Percolation and criticality in a mitochondrial network. Proc Natl Acad Sci USA 101: 4447–4452, 2004.
3. Beard DA, Schenkman KA, and Feigl EO. Myocardial oxygenation in isolated hearts predicted by an anatomically realistic microvascular transport model. Am J Physiol Heart Circ Physiol 285: H1826–H1836, 2003.
4. Birkedal R and Gesser H. Creatine kinase and mitochondrial respiration in hearts of trout, cod and freshwater turtle. J Comp Physiol [B] 173: 493–499, 2003.[CrossRef][Medline]
5. Birkedal R and Gesser H. Regulation of mitochondrial energy production in cardiac cells of rainbow trout (oncorhynchus mykiss). J Comp Physiol [B] 174: 255–262, 2004.[CrossRef][Medline]
6. Birkedal R and Gesser H. Intracellular compartmentation of cardiac fibres from rainbow trout and Atlantic cod–a general design of heart cells. Biochim Biophys Acta 1757: 764–772, 2006.[Medline]
7. Boudina S, Laclau MN, Tariosse L, Daret D, Gouverneur G, Bonoron-Adele S, Saks VA, and Santos PD. Alteration of mitochondrial function in a model of chronic ischemia in vivo in rat heart. Am J Physiol Heart Circ Physiol 282: H821–H831, 2002.
8. Brady NR, Elmore SP, van Beek JJHGM, Krab K, Courtoy PJ, Hue L, and Westerhoff HV. Coordinated behavior of mitochondria in both space and time: a reactive oxygen species-activated wave of mitochondrial depolarization. Biophys J 87: 2022–2034, 2004.[CrossRef][Web of Science][Medline]
9. Collins TJ, Berridge MJ, Lipp P, and Bootman MD. Mitochondria are morphologically and functionally heterogeneous within cells. EMBO J 21: 1616–1627, 2002.[CrossRef][Web of Science][Medline]
10. Collins TJ and Bootman MD. Mitochondria are morphologically heterogeneous within cells. J Exp Biol 206: 1993–2000, 2003.
11. Duchen MR. Contributions of mitochondria to animal physiology: from homeostatic sensor to calcium signalling, and cell death. J Physiol 516: 1–17, 1999.
12. Eisner DA, Nichols CG, O'Neill SC, Smith GL, and Valdeolmillos M. The effects of metabolic inhibition on intracellular calcium and pH in isolated rat ventricular cells. J Physiol 411: 393–418, 1989.
13. Gerencser AA and Adam-Vizi V. Mitochondrial Ca2+ dynamics reveals limited intramitochondrial Ca2+ diffusion. Biophys J 88: 698–714, 2005.[CrossRef][Web of Science][Medline]
14. Kaasik A, Veksler V, Boehm E, Novotova M, Minajeva A, and Ventura-Clapier R. Energetic crosstalk between organelles: architectural integration of energy production and utilization. Circ Res 89: 153–159, 2001.
15. Kay L, Saks VA, and Rossi A. Early alteration of the control of mitochondrial function in myocardial ischemia. J Mol Cell Cardiol 29: 3399–3411, 1997.[CrossRef][Web of Science][Medline]
16. Kayar SR, Conley KE, Claassen H, and Hoppeler H. Capillarity and mitochondrial distribution in rat myocardium following exercise training. J Exp Biol 120: 189–199, 1986.
17. Kremer JR, Mastronarde DN, and McIntosh JR. Computer visualization of three-dimensional image data using imod. J Struct Biol 116: 71–76, 1996.[CrossRef][Web of Science][Medline]
18. Muir AR. The effects of divalent cations on the ultrastructure of the perfused rat heart. J Anat 101: 239–261, 1967.[Web of Science][Medline]
19. Pitts KR and Toombs CF. Coverslip hypoxia: a novel method for studying cardiac myocyte hypoxia and ischemia in vitro. Am J Physiol Heart Circ Physiol 287: H1801–H1812, 2004.
20. Romashko DN, Marban E, and O'Rourke B. Subcellular metabolic transients and mitochondrial redox waves in heart cells. Proc Natl Acad Sci USA 95: 1618–1623, 1998.
21. Roy RR, Pierotti DJ, and Edgerton VR. Skeletal muscle fiber cross-sectional area: effects of freezing procedures. Acta Anat (Basel) 155: 131–135, 1996.[Web of Science][Medline]
22. Rube DA and van der Bliek AM. Mitochondrial morphology is dynamic and varied. Mol Cell Biochem 256–257: 331–339, 2004.
23. Saks V, Kuznetsov A, Andrienko T, Usson Y, Appaix F, Guerrero K, Kaambre T, Sikk P, Lemba M, and Vendelin M. Heterogeneity of ADP diffusion and regulation of respiration in cardiac cells. Biophys J 84: 3436–3456, 2003.[Web of Science][Medline]
24. Saks VA, Kaambre T, Sikk P, Eimre M, Orlova E, Paju K, Piirsoo A, Appaix F, Kay L, Regitz-Zagrosek V, Fleck E, and Seppet E. Intracellular energetic units in red muscle cells. Biochem J 356: 643–657, 2001.[CrossRef][Web of Science][Medline]
25. Saks VA, Kuznetsov AV, Vendelin M, Guerrero K, Kay L, and Seppet EK. Functional coupling as a basic mechanism of feedback regulation of cardiac energy metabolism. Mol Cell Biochem 256/257: 185–199, 2004.
26. Segretain D, Rambourg A, and Clermont Y. Three dimensional arrangement of mitochondria and endoplasmic reticulum in the heart muscle fiber of the rat. Anat Rec 200: 139–151, 1981.[CrossRef][Medline]
27. Seppet EK, Eimre M, Andrienko T, Kaambre T, Sikk P, Kuznetsov AV, and Saks V. Studies of mitochondrial respiration in muscle cells in situ: use and misuse of experimental evidence in mathematical modelling. Mol Cell Biochem 256–257: 219–227, 2004.
28. Seppet EK, Kaambre T, Sikk P, Tiivel T, Vija H, Tonkonogi M, Sahlin K, Kay L, Appaix F, Braun U, Eimre M, and Saks VA. Functional complexes of mitochondria with ca,mgatpases of myofibrils and sarcoplasmic reticulum in muscle cells. Biochim Biophys Acta 1504: 379–395, 2001.[Medline]
29. Shiels HA, Vornanen M, and Farrell AP. Temperature-dependence of L-type Ca2+ channel current in atrial myocytes from rainbow trout. J Exp Biol 203: 2771–2780, 2000.[Abstract]
30. Shiels HA and White E. Temporal and spatial properties of cellular Ca2+ flux in trout ventricular myocytes. Am J Physiol Regul Integr Comp Physiol 288: R1756–R1766, 2005.
31. Shimada T, Horita K, Murakami M, and Ogura R. Morphological studies of different mitochondrial populations in monkey myocardial cells. Cell Tissue Res 238: 577–582, 1984.[Web of Science][Medline]
32. Sommer JR and Jennings RB. Ultrastructure of cardiac muscle. In: The Heart and Cardiovascular System, edited by Fozzard HA, Haber E, Jennings RB, Katz AM, and Morgan HE. New York: Raven, 1986, p. 61–100.
33. Sun CN, Dhalla NS, and Olson RE. Formation of gigantic mitochondria in hypoxic isolated perfused rat hearts. Experientia 25: 763–764, 1969.[Web of Science][Medline]
34. Vendelin M, Beraud N, Guerrero K, Andrienko T, Kuznetsov A, Olivares J, Kay L, and Saks VA. Mitochondrial regular arrangement in muscle cells: a "crystal-like" pattern. Am J Physiol Cell Physiol 288: C757–C767, 2005.
35. Vendelin M, Eimre M, Seppet E, Peet N, Andrienko T, Lemba M, Engelbrecht J, Seppet EK, and Saks VA. Intracellular diffusion of adenosine phosphates is locally restricted in cardiac muscle. Mol Cell Biochem 256/257: 229–241, 2004.
36. Vendelin M, Kongas O, and Saks V. Regulation of mitochondrial respiration in heart cells analyzed by reaction-diffusion model of energy transfer. Am J Physiol Cell Physiol 278: C747–C764, 2000.
37. Ventura-Clapier R, Kuznetsov A, Veksler V, Boehm E, and Anflous K. Functional coupling of creatine kinases in muscles: species and tissue specificity. Mol Cell Biochem 184: 231–247, 1998.[CrossRef][Web of Science][Medline]
38. Vornanen M. L-type Ca2+ current in fish cardiac myocytes: effects of thermal acclimation, and beta-adrenergic stimulation. J Exp Biol 201: 533–547, 1998.
This article has been cited by other articles:
|
|
 |
|
  M. Vendelin and R. Birkedal Anisotropic diffusion of fluorescently labeled ATP in rat cardiomyocytes determined by raster image correlation spectroscopy Am J Physiol Cell Physiol, November 1, 2008; 295(5): C1302 - C1315. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 E. Takahashi Anoxic cell core can promote necrotic cell death in cardiomyocytes at physiological extracellular PO2 Am J Physiol Heart Circ Physiol, June 1, 2008; 294(6): H2507 - H2515. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Visit Other APS Journals Online |
) and the closest mitochondrial center in each of the sectors is considered. This distance is statistically analyzed for the rat (B) and trout (C). The names of the sectors are indicated in the insets of the plots. B: in the rat, there are three groups of distributions corresponding to longitudinal (Y), transversal (X and Z) and diagonal (XY and YZ) directions. C: in the trout, only distributions of mitochondria in the transversal directions (X and Z) are relatively close to each other.