Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
, 14 (9), e0223014
eCollection

Mitochondrial Fragmentation and Network Architecture in Degenerative Diseases

Affiliations

Mitochondrial Fragmentation and Network Architecture in Degenerative Diseases

Syed I Shah et al. PLoS One.

Abstract

Fragmentation of mitochondrial network has been implicated in many neurodegenerative, renal, and metabolic diseases. However, a quantitative measure of the microscopic parameters resulting in the impaired balance between fission and fusion of mitochondria and consequently the fragmented networks in a wide range of pathological conditions does not exist. Here we present a comprehensive analysis of mitochondrial networks in cells with Alzheimer's disease (AD), Huntington's disease (HD), amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), optic neuropathy (OPA), diabetes/cancer, acute kidney injury, Ca2+ overload, and Down Syndrome (DS) pathologies that indicates significant network fragmentation in all these conditions. Furthermore, we found key differences in the way the microscopic rates of fission and fusion are affected in different conditions. The observed fragmentation in cells with AD, HD, DS, kidney injury, Ca2+ overload, and diabetes/cancer pathologies results from the imbalance between the fission and fusion through lateral interactions, whereas that in OPA, PD, and ALS results from impaired balance between fission and fusion arising from longitudinal interactions of mitochondria. Such microscopic difference leads to major disparities in the fine structure and topology of the network that could have significant implications for the way fragmentation affects various cell functions in different diseases.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Steps involved in the processing of the images and retrieval of various network features.
(a) Original image, (b) the grayscale image containing mitochondrial network only, (c) binary image, and (d) skeletonized image. Panel (e) shows a graph (partially shown) representation of the skeletonized image where red, green, and blue colors represent nodes with degree 1, 2 and 3 respectively. Size distribution of cyclic loops (f) and linear branch lengths (g), and cumulative probability distribution of cluster sizes (h) in mitochondrial network in striatal cells from wildtype (NL, red) and YAC128 HD (blue) transgenic mice. The image used for the mitochondrial network extraction in panel (a) was adopted from Ref. [78] with permission.
Fig 2
Fig 2. Experimentally observed mitochondrial network and the scheme to model it.
(a) Color coded mitochondrial network retrieved from experimental image of a striatal cell from a wildtype mice and (b) its zoomed in version. (c) Model scheme representing the tip-to-tip fusion of two X1 nodes into X2 and tip-to-side fusion of one X1 node with one X2 node to make one X3 node, and their corresponding fission processes. The image used for the mitochondrial network extraction in panel (a) was adopted from Ref. [78] with permission.
Fig 3
Fig 3
Model results at different C1 and C2 values. Mean degree (a1), Ng/N (a2), and Ng/N versus <k> (a3) as functions of C2 at a fixed value of C1. Inset in (a3) shows a zoomed in version of the main plot in (a3) with superimposed Ng/N versus <k> from experimental images of mitochondria in striatal cells (red cross) from wildtype (NL) and YAC128 HD transgenic mice [78]. Mitochondrial network changes from fragmented (b1) to physiologically viable, well-connected (b2) to a fully connected network making one giant cluster (b3) as we increase C2 (or C1). Distribution of loop sizes (c1), branch lengths (c2), and cluster sizes (c3) retrieved from simulated networks at two different C2 values corresponding to mitochondrial network in striatal cells from HD transgenic mice (representative of low C2) (black bars) and striatal cells from wildtype mice in the same experiments (representative of intermediate C2) (red bars). The insets in (c1) and (c2) and the blue bars in (c3) correspond to C2 value for the normal cells in ALS experiments (representative of high C2). The inset in (c3) shows the tail of the blue distribution indicating the formation of a giant cluster at high C2. At smaller cluster sizes, the black, red, and blue bars in panel (c1) are comparable and are skipped for clarity.
Fig 4
Fig 4
Two different types of microscopic changes in the fusion to fission processes leading to mitochondrial network fragmentation demonstrated with examples from HD (striatal cells from mouse embryos bearing a 111 polyglutamine repeat Q111/0 and Q111/1) versus control [78] for the first type (top row) and OPA (mouse embryonic fibroblasts with the pathogenic mutation R149W in human YME1L1) versus control [66] for the second type (bottom row) of microscopic changes. Distributions of (a1) loop sizes, (a2) branch lengths, and (a3) cluster sizes (cumulative probability) for NL (red) and diseased cells (blue) from experimental images. (a4) Fraction of X1 (NL: green, diseased: red), X2 (NL: magenta, diseased: blue) and X3 (NL: black, diseased: cyan) species from the model as functions of the number of iterations using C1 and C2 values for HD experiments. The model results show average of 100 runs. (b1-b4) shows the same mitochondrial network features as (a1-a4) for mouse embryonic fibroblasts with OPA pathology and their normal counterparts. Note that the curves for X3 species in cells with OPA pathology and NL overlap (b4).
Fig 5
Fig 5. The differences in the microscopic changes leading to mitochondrial network fragmentation lead to significantly differences in the way the fine structure and topology of the network is affected in different diseases.
The mean of size distribution of (a) cyclic loops, (b) branch lengths, and (c) clusters for normal (red) and diseased (blue) cells given by the model using the estimated C1 and C2 values from the experimental micrographs of mitochondrial networks with the condition modeled. Each data point is averaged over 100 runs with error bars showing the standard error of the mean. Simulation results for ALS are plotted separately in the insets for clarity.

Similar articles

See all similar articles

Cited by 1 PubMed Central articles

References

    1. Bakeeva L, Chentsov YS, Skulachev V. Mitochondrial framework (reticulum mitochondriale) in rat diaphragm muscle. Biochimica et Biophysica Acta (BBA)-Bioenergetics. 1978;501(3):349–69. - PubMed
    1. Amchenkova AA, Bakeeva LE, Chentsov YS, Skulachev VP, Zorov DB. Coupling membranes as energy-transmitting cables. I. Filamentous mitochondria in fibroblasts and mitochondrial clusters in cardiomyocytes. The Journal of cell biology. 1988;107(2):481–95. 10.1083/jcb.107.2.481 - DOI - PMC - PubMed
    1. Szabadkai G, Simoni AM, Rizzuto R. Mitochondrial Ca2+ uptake requires sustained Ca2+ release from the endoplasmic reticulum. Journal of Biological Chemistry. 2003;278(17):15153–61. 10.1074/jbc.M300180200 - DOI - PubMed
    1. Anesti V, Scorrano L. The relationship between mitochondrial shape and function and the cytoskeleton. Biochimica et Biophysica Acta (BBA)-Bioenergetics. 2006;1757(5–6):692–9. - PubMed
    1. Yang J-S, Kim J, Park S, Jeon J, Shin Y-E, Kim S. Spatial and functional organization of mitochondrial protein network. Scientific reports. 2013;3:1403 10.1038/srep01403 - DOI - PMC - PubMed
Feedback