Quality control of mitochondria during aging: Is there a good and a bad side of mitochondrial dynamics?


  • Marc Thilo Figge,

    Corresponding author
    1. Applied Systems Biology, HKI-Center for Systems Biology of Infection, Leibniz-Institute for Natural Product Research and Infection Biology – Hans-Knöll-Institute and Friedrich Schiller University, Jena, Germany
    • Applied Systems Biology, HKI-Center for Systems Biology of Infection, Leibniz-Institute for Natural Product Research and Infection Biology – Hans-Knöll-Institute and Friedrich Schiller University, Jena, Germany
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  • Heinz D. Osiewacz,

    Corresponding author
    1. Faculty for Biosciences, Molecular Developmental Biology, Cluster of Excellence Macromolecular Complexes, Goethe University, Frankfurt am Main, Germany
    • Applied Systems Biology, HKI-Center for Systems Biology of Infection, Leibniz-Institute for Natural Product Research and Infection Biology – Hans-Knöll-Institute and Friedrich Schiller University, Jena, Germany
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  • Andreas S. Reichert

    Corresponding author
    1. Mitochondrial Biology, Buchmann Institute for Molecular Life Sciences, Goethe University, Frankfurt am Main, Germany
    2. Mitochondriale Biologie, Zentrum für Molekulare Medizin, Goethe Universität, Frankfurt am Main, Germany
    • Applied Systems Biology, HKI-Center for Systems Biology of Infection, Leibniz-Institute for Natural Product Research and Infection Biology – Hans-Knöll-Institute and Friedrich Schiller University, Jena, Germany
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Maintenance of functional mitochondria is essential in order to prevent degenerative processes leading to disease and aging. Mitochondrial dynamics plays a crucial role in ensuring mitochondrial quality but may also generate and spread molecular damage through a population of mitochondria. Computational simulations suggest that this dynamics is advantageous when mitochondria are not or only marginally damaged. In contrast, at a higher degree of damage, mitochondrial dynamics may be disadvantageous. Deceleration of fusion-fission cycles could be one way to adapt to this situation and to delay a further decline in mitochondrial quality. However, this adaptive response makes the mitochondrial network more vulnerable to additional molecular damage. The “mitochondrial infectious damage adaptation” (MIDA) model explains a number of inconsistent and counterintuitive data such as the “clonal expansion” of mutant mitochondrial DNA. We propose that mitochondrial dynamics is a double-edged sword and suggest ways to test this experimentally.


MFRTA, mitochondrial free radical theory of aging; MIDA, mitochondrial infectious damage adaptation; MQC, mitochondrial quality control; ROS, reactive oxygen species.


Biological aging is the time-dependent decline of physiological functions in biological systems leading to increased morbidity and mortality. The process is complex and under the control of genetic traits, environmental conditions and stochastic processes. Mitochondria, the eukaryotic “power plants” generating most of the adenosine triphosphate (ATP) needed to drive the energy-consuming processes in a cell, have been recognized for quite some time as a cellular “Achilles heel”. Mitochondrial dysfunction is known to be associated with various diseases and aging 1–4. The latter has first been conceptualized in the “mitochondrial free radical theory of aging” (MFRTA) which explains aging as the result of molecular damage accumulation in mitochondria generated by free radicals (or reactive oxygen species [ROS]) during cellular respiration 5. Although this hypothesis is still controversially discussed it is generally accepted that minimizing mitochondrial dysfunction is of central importance in maintaining cellular and organismal fitness and also in counteracting aging. Several mitochondrial quality control (MQC) pathways have been described in recent years all acting in a coordinated manner at different levels (Fig. 1).

Figure 1.

Mitochondrial function and quality control. Mitochondria are involved in a variety of essential functions including the generation of ATP and reactive oxygen species (ROS), the synthesis of Fe/S clusters, the regulation of apoptosis and others (e.g. thermogenesis, biosynthesis of lipids). ROS are not only efficient damaging agents, but also indispensable signals for controlled gene expression. The outer circle summarizes different pathways which control a “healthy” population of mitochondria in a cell. Among these, ROS scavenging is involved in keeping ROS levels low. Protein quality control pathways lead to repair and refolding of impaired proteins. If proteins are severely damaged or cannot be repaired they may be degraded by proteases and subsequently replaced after the expression of nuclear or mitochondrial encoded genes. DNA repair systems in mitochondria (but also in the nucleus) are controlling the integrity of the corresponding genes and regulatory sequences. Mitochondrial fission and fusion is also part of the quality control system. Damaged parts of the mitochondrial network are separated by fission and can be delivered to the mitophagy system for degradation.

Mitochondrial quality control pathways help to prevent mitochondrial dysfunction

At a molecular and largely intraorganellar level, controlling the amount of ROS is one significant aspect of MQC. A reduction in superoxide anion generation at the mitochondrial electron transport chain can slow down the process of damaging 6. The regulation of individual components of the ROS scavenging system is more complex and depending on the coordinated regulation of different components. Consequently the increase of just one component may not be beneficial but rather increase oxidative stress leading to adverse consequences 7, 8. In any case, if ROS scavenging systems become overwhelmed in their capacity, essential biomolecules such as nucleic acids, proteins or lipids can be damaged. DNA damage leads to mutations and heteroplasmy, the simultaneous presence of wild type and mutated mtDNA molecules in one cell. Since mitochondrial homeostasis is dependent on a well-coordinated expression of both nuclear and mitochondrial genes, mitochondrial mutations may lead to suboptimal fitting of the different components of the respiratory chain. This “mitonuclear mismatch” may lead to reduced ATP generation, an increase in ROS production and increased damage 9. Once molecular damage has occurred, different components are activated to repair it, counteract the consequence of damage, or remove damaged components by degradation. In particular, effective protein degradation systems are active in MQC. Several proteases involved in MQC are known for each mitochondrial sub-compartment. For instance, Lon and Clp proteases are located in the mitochondrial matrix, iAAA, and mAAA proteases are bound to the inner mitochondrial membrane. Emerging experimental data confirm the impact of these systems on mitochondrial quality, aging, and lifespan control 10, 11. Furthermore, recent data show that the ubiquitin proteasome system (UPS) located in the cytoplasm is also part of the MQC system. Proteins from the outer membrane or those from other sub-compartments which are retro-translocated to the outer membrane become ubiquitinated and delivered to the proteasome where they are degraded 12, 13. Although not demonstrated so far, this system, termed “mitochondrial associated degradation” (MAD), is likely to be relevant to aging and lifespan control in higher organisms.

At an organellar level, another emerging pathway is the recently reported mitochondria-derived vesicle (MDV) transfer of mitochondrial lipids and proteins from the outer membrane to lysosomes, which is independent from mitophagy 14. Furthermore, the interplay between mitochondrial dynamics, mitophagy, and biogenesis is intensively discussed to ensure MQC. This pathway has recently been implicated in the pathogenesis of Parkinson's disease 15–19. Here we focus on the latter MQC pathway and primarily discuss the implications derived from recent simulations for this particular MQC pathway on aging.

Although it is clear that various MQC pathways exist, the relative importance of these pathways has not been elucidated until recently. All pathways are limited in their capacity of dealing with different types of mitochondrial damage and thus, after passing certain thresholds, pathways of a higher order become activated 11, 20–26. The precise regulation mechanisms of the corresponding links and interactions remain to be established.

In a previous systems biology approach we modeled different available data on MQC mediated by mitochondrial dynamics, mitophagy, and biogenesis. We came to the hypothesis that mitochondrial fusion-fission cycles, in addition to their beneficial effects on mitochondrial function, can contribute to the spread of molecular damage and that the deceleration of such cycles could be an effective way to postpone the time-point at which a system passes a critical threshold leading to adverse effects 27. Here we describe the “mitochondrial infectious damage adaptation” (MIDA) model in general, discuss consequences arising from this model, make suggestions with regard to its experimental validation and address perspectives to integrate other pathways involved in MQC into a model of increased complexity.

Aging hypothesis: Deceleration of fusion-fission cycles improves mitochondrial quality control

Microscopic investigations revealed that mitochondria are organized within a highly dynamic network that is governed by mitochondria undergoing cycles of fusion and fission that result in the mixing of their molecular content 28–32. Mitochondrial dynamics and consequently changes in mitochondrial morphology are regulated at multiple levels including limited proteolysis, ubiquitinylation, phosphorylation, sumoylation, and disulfide formation of critical fusion and/or fission factors 20, 33–44.

In this context it is important to note that it was shown in yeast as well as in mammalian cells that the bioenergetic state of mitochondria is linked to the mitochondrial morphology 41, 42, 45, 46. When mitochondrial function is impaired, the fusion machinery is inactivated, e.g. via stress-induced proteolytic processing of the fusion factor OPA1 and/or by ubiquitinylation and proteasome-dependent degradation of Mfn2 in mammals 41–44. In this way dysfunctional mitochondria become spatially separated from the intact network and, importantly, distinguishable from intact mitochondria. This is needed to prime them for their selective degradation by autophagy (mitophagy) and several reports have confirmed that mitochondrial fission is indeed required for the selective removal of mitochondria in mammals 37, 38, 47–50. Damaged mitochondria are subsequently marked by stabilization of PINK1 at the outer membrane and by recruitment of PARKIN 17, 18 which represent early steps in mitophagy. Based on these observations the life cycle of single mitochondria within the network was inferred and it was proposed that it ensures quality control and maintenance of the mitochondrial network as a whole 15, 46, 51–53.

Recently, we have implemented this MQC pathway (see Fig. 2) in a computer-based model 27 whereby mitochondria actively take part in the network via fusion-fission cycles accompanied by biogenesis of mitochondrial mass as well as gradual loss of their functional quality via the natural decline of the molecular integrity of active mitochondria. According to this model, mitochondria that gradually fall below a minimal level of functional quality will become non-active, i.e. they do not undergo fusion-fission cycles anymore, fragment from the network, and await mitophagy 26. In this way mitochondria of low quality are negatively selected to preserve the overall quality of the mitochondrial network. In such a scenario mitochondrial dynamics is clearly an efficient way to keep a “healthy” population of mitochondria.

Figure 2.

Quality control by cycles of fusion and fission at the heart of the mitochondrial life cycle. The functional quality of the mitochondrial network as a whole is maintained by cycles of fusion and fission. Mixing of the mitochondrial content gives rise to low-quality mitochondria that are negatively selected to become non-active. These mitochondria become fragmented and are removed from the network by mitophagy for the benefit of the network as a whole.

However, the efficiency of this and other MQC systems appears to be limited since they are not able to prevent the accumulation of impaired mitochondria over the lifetime of an organism. In fact, based on our simulations we hypothesize that mitochondrial fission and fusion can even be disadvantageous giving rise to the introduction of “infectious damage” and that aging cells may benefit from the deceleration of fusion-fission cycles. At first glance, this hypothesis is counter-intuitive, in particular, if we think of molecular damage as being randomly induced by ROS. In turn, it could be argued that quality control should rather be performed with accelerated cycles of fusion and fission. However, this expectation is only reasonable if the origin of molecular damage would be merely random, could be viewed as being independent of fusion-fission cycles, and does not show any dominant-negative effect when mixed with non-damaged mitochondrial content. The fusion-fission process itself could, however, impose a kind of damage. This is indeed supported by the notion that instantly after single mitochondrial fission events the mitochondrial membrane potential was reduced in a subset of daughter mitochondria 47. The consideration of this type of damage led us to assume a type of “infectious molecular damage” and to evaluate its consequences. This general term can, for example, represent loss of mitochondrial ion homeostasis or a propagation of dominant-negative properties (e.g. spreading of mutant mtDNA with a replicative advantage over wild type mtDNA) by ongoing content mixing.

Our MIDA model challenges the currently existing view as it suggests that important parts of the MQC itself pose harmful effects. Rather than being driven by randomness, molecular damage may accumulate and spread in the mitochondrial network of aging cells by ongoing molecular content mixing during fusion-fission events. While this aging hypothesis assigns a major role to infectious molecular damage, the initial spark of damage occurrence may still be induced by random events such as the reaction of any biomolecule with ROS. Initially, cycles of fusion and fission guarantee a mitochondrial network of sufficiently high quality (Fig. 3A). In Fig. 3B, mitochondria that acquired ROS-induced molecular damage are indicated in red color. Even though they are of reduced functional quality, these mitochondria may still undergo fusion-fission events. However, by these processes the corresponding partner mitochondria (green) become infected (Fig. 3C) and subsequently contribute to the spreading of molecular damage throughout the mitochondrial network (Fig. 3D). It is obvious that, since the accumulation of infectious molecular damage depends on the mitochondrial dynamics itself, the imminent infection of the whole mitochondrial network can only be prevented by the deceleration of fusion-fission cycles. Thus, under these circumstances, deceleration of fusion-fission cycles is a means to improve MQC.

Figure 3.

Snapshot of molecular damage in the mitochondrial network of aging cells. A: Mitochondrial network in the absence of molecular damage. B: Random molecular damage became manifested in two mitochondria (red) that are subsequently undergoing cycles of fusion and fission. C: Infectious molecular damage occurs in mitochondria (green) as the result of fusion-fission events with mitochondria that were previously acquiring molecular damage (red). D: Molecular damage spreads throughout the whole mitochondrial network by on-going fusion-fission events giving rise to infectious molecular damage.

However, it can be expected that this is a double-edged sword, since it will bring the mitochondrial network into a more vulnerable position with regard to newly acquired random molecular damage. Therefore, deceleration of fusion-fission cycles is no cure-all but delays the fate of the cell to die young by facing the consequences to grow old. The role and adaptive responses of other MQC pathways remain to be investigated in future studies as one certainly cannot exclude that in parallel other MQC pathways are dynamically regulated in order to compensate for increased mitochondrial dysfunction.

Theoretical hypothesis testing

We recently tested the aging hypothesis on theoretical grounds by computer simulations of a mathematical model that describes the dynamics of MQC 27. The model was based on a master equation approach that describes the cellular network of mitochondria in the state space of their functional quality, i.e. the ensemble of mitochondria in the network was represented by a distribution that is spread over discrete levels ranging from low to high quality. Depending on the current state of quality, mitochondria in this model are actively taking part in the dynamic processes summarized in Fig. 2, e.g. fusion-fission events, quality decay by molecular degradation, mitophagy and biogenesis of mitochondrial mass under homeostatic conditions. These processes give rise to dynamic changes in the mitochondrial distribution, whereby mitochondria of high quality undergo fusion-fission events with high probability and are unlikely to undergo mitophagy, while this is the other way round for mitochondria of low quality. In particular, the lowest state of functional quality in the model refers to mitochondria that are non-active and contribute to the fragmentation of the dynamic network, i.e. these mitochondria are non-fusogenic, become isolated from the mitochondrial network and await mitophagy.

Classification of the mitochondrial network by computer simulations

Computer simulations allowed the characterization of emergent properties of the mitochondrial network by the number of active versus non-active mitochondria and also by the average quality of mitochondria in the network. In the absence of molecular damage, the mathematical model predicted, in agreement with conclusions derived from previous experimental investigations 47, 53, that MQC can be achieved by cycles of fusion and fission. As seen from the mitochondrial equilibrium distribution in Fig. 4A, the dynamic network was characterized by two classes of mitochondria: a large fraction of active mitochondria in states of high quality and a small fraction of non-active mitochondria in low-quality states. This distribution supports a highly dynamic network with only a small fraction of mitochondria that are fragmented from the network and await mitophagy. Of note, the accumulation of mitochondria in high-quality states is due to cycles of fusion and fission. This can be seen in Fig. 4B, whereby we plot the mitochondrial equilibrium distribution in the absence of fusion-fission cycles for otherwise identical conditions as in Fig. 4A.

Figure 4.

Results of computer simulations for the mitochondrial equilibrium distribution Peq(q) with active (green) and non-active (red) mitochondria in the state space of functional quality. A: Reference model of mitochondrial quality control in the presence of fusion-fission cycles, molecular degradation, mitophagy, and biogenesis. All model parameters are chosen as in 27. B: Reference model in the absence of fusion-fission cycles. C: Reference model with random molecular damage. D: Reference model with infectious molecular damage.

The high-quality distribution of mitochondria was challenged by molecular damage and its effect was observed to be comparable for both random (Fig. 4C) and infectious (Fig. 4D) molecular damage. In both cases a modest decrease of the average quality for active mitochondria was observed to be accompanied by a significant decrease in the fraction of active mitochondria. Furthermore, the two classes of mitochondria in the dynamic network developed a comparable size: mitochondria were either actively undergoing cycles of fusion and fission or becoming non-active by accumulating in the lowest state of functional quality. These distributions support mitochondrial networks with significant fragmentation caused by ongoing generation of non-fusogenic mitochondria making up 50% of all mitochondria in the flow-equilibrium. Since the proper functioning of cells requires mitochondria of sufficiently high quality to be present at sufficiently high quantities, this deterioration of the initial mitochondrial distribution may already have severe consequences for cellular survival.

Simulations with decelerated fusion-fission cycles

We subsequently tested the aging hypothesis by using a dynamical reduction in the rate of fusion-fission events in order to model the experimentally observed deceleration of mitochondrial dynamics during aging 54. As seen in Fig. 5, the impact of this reduction was strikingly different for random and infectious molecular damage. In the case of random molecular damage, a reduction of the fusion-fission rate hardly affected the comparable class sizes of active and non-active mitochondria, while the average quality of active mitochondria was clearly decreased due to reduced MQC (see Fig. 5A). In contrast, in the case of infectious molecular damage, the reduction in the fusion-fission rate had a minimal effect on the average quality of active mitochondria and the initial mitochondrial distribution, with the two classes having different sizes and supporting a dynamic network with only a small fraction of fragmented mitochondria (see Fig. 5B).

Figure 5.

Results of computer simulations for the mitochondrial equilibrium distribution Peq(q) with active (green) and non-active (red) mitochondria in the state space of functional quality. A: Reference model with random molecular damage and with deceleration of fusion-fission cycles by 80%. B: Reference model with infectious molecular damage and with deceleration of fusion-fission cylces by 80%. C: Reference model with combined random and infectious molecular damage. D: Reference model with combined random and infectious molecular damage and with deceleration of fusion-fission cycles by 80%.

The restoration of the mitochondrial quality by the deceleration of fusion-fission events supports the hypothesis that MQC in aging cells with accumulating molecular damage can be improved in this way. Indeed, computer simulations in which the occurrence of random molecular damage was combined with infectious molecular damage revealed that the distribution deteriorated further. This can be seen in Fig. 5C, whereby the class of non-active mitochondria reaches values of 60% compared to 50% in Fig. 4C and D. However, adaptation of the fusion-fission rate by a reduction of 80% revealed a significant restoration of the mitochondrial distribution. As can be seen in Fig. 5D, the class of non-active mitochondria was reduced to values well below 30% while the class of active mitochondria consisted mainly of high-quality mitochondria.

Implications of the MIDA model

The MIDA model could well have major implications for biological systems as it (i) allows us to explain a number of findings that have been reported during the last decades, and (ii) enables us to make predictions that can be tested experimentally. Before discussing these points in more detail one needs to emphasize that there are major limitations in the field; limitations that certainly have contributed to the fact that the main conclusions derived from the MIDA model have not been recognized earlier.

More data on mitochondrial dynamics from non-tumor cell lines are needed

So far, virtually all studies on mitochondrial dynamics and mitophagy in mammalian cells have been performed in tumor cell lines. These cell lines have undergone numerous genetic alterations and are metabolically distinct from primary cells or tissues. Furthermore, the physiological fusion-fission rates present in distinct cell types such as young, healthy, or aged organisms have not yet been determined.

Recent advances in this area however, enabled several studies on fusion and fission processes to be carried out using primary tissues 37, 55. In the latter study a mouse model expressing photo-activatable mito-Dendra-2 was generated that could help quantify mitochondrial dynamics in a gene-, tissue-, and age-dependent manner in vivo. Also, in vitro mammalian cell fusion assays have become available, which could be used to detect redox-, cell-type-, and tissue-specific differences regulating mitochondrial fusion 56–58. However, quantitative data concerning fission rates, particularly for the in vivo situation, are lacking. Another limitation in the field is the lack of suitable model systems of mitochondrial dysfunction in which mitophagy is induced in a physiological manner. Commonly the protonophore CCCP and concomitant overexpression of E3-ubiquitin-ligase PARKIN are being used. These conditions are very instrumental in order to decipher the role of PARKIN and PINK1, two genes linked to Parkinson's disease, in the removal of damaged mitochondria 17–19. However, it remains questionable to which extent this reflects the situation in vivo and during aging. One should keep in mind that with the addition of CCCP the fusion of all mitochondria becomes artificially blocked and thus any selectivity of fusion and degradation is lost.

Thus, MQC under these conditions is expected to be random and not directed towards the specific removal of damaged mitochondria. In this extreme example mitophagy is even cytotoxic as cells loose viability in about 48 hours. Interestingly, it was shown recently in yeast that α-synuclein induced cytotoxicity and reduction in chronological lifespan depends on mitophagy, indicating that mitophagy could also have detrimental effects 59. To our knowledge only when applying mild and transient oxidative stress conditions mitophagy is specifically induced in mammalian cells without concomitant induction of bulk autophagy 50.

Mitochondrial hyperfusion helps to ensure mitochondrial quality control

The concern that data from tumor cells cannot be transferred to primary cells is further strengthened by recent studies showing that the cell cycle and also the metabolic state are coupled to mitochondrial dynamics and morphology. Progression from G1 to S phase during the cell cycle was shown to depend on hyperfusion of mitochondria. Also, mitochondrial fission was increased during mitosis 60–62. These results further strengthen the general view that mitochondrial dynamics is strictly regulated at several levels (for a review see 63). Hyperfusion of mitochondria was further observed under numerous stress conditions and after starvation 37, 38, 50, 57, 64. One mechanism mediating this dynamic change in mitochondrial morphology is linked to protein kinase A dependent phosphorylation of DRP1, resulting in the inhibition of mitochondrial fission which was shown to reduce the extent of mitophagy 37, 38, 50. It should be noted that mitochondrial hyperfusion after starvation was not only shown in several tumor cell lines but also in primary mouse hepatocytes 37 and thus represents one of the very few examples where primary tissues have been investigated. Interestingly, hyperfusion of mitochondria was also demonstrated to be promoted by oxidized glutathione via disulfide-mediated oligomerization of Mfn2 57. What could be the physiological explanation for the observed cytoprotective role of mitochondrial hyperfusion in light of the MIDA model? We hypothesize that three major factors come into play and secure MQC: (i) cells that undergo any type of stress or that are up to enter S phase in the cell cycle are likely to actively aim to get rid of any possibly damaged mitochondria. “Forcing” mitochondria to hyperfuse does only work for functional mitochondria and thus results in the exclusion of all damaged mitochondria from the mitochondrial network. (ii) This allows the degradation machinery to “concentrate” on the latter for removing them. (iii) By inactivating the fission machinery it is ensured that healthy mitochondria remain in the network (at least temporarily) and thus are not degraded accidentally. This hypothesis can be abbreviated also as follows: (i) “coming-home” (of all mitochondria capable of doing so); (ii) “getting-rid-of-the-bad-ones-only”; and (iii) “securing-the-good-ones”.

Furthermore, inactivating the fission machinery is equivalent to the deceleration of both fusion and fission rates in the long run, which are central to the MIDA model, as fusion of mitochondria can only proceed to a limited degree. This presumably is due to sterical reasons, and consequently results after a relative short time period in a deceleration of both fusion and fission rates. Thus, the proposed adaptation of decelerating mitochondrial dynamics during aging has already been observed in another biological system which, however, represents a rapid adaptation to various cellular stresses. It will be interesting to see whether similar regulatory mechanisms that were described for rapid stress responses and for regulation during the cell cycle also apply for adaptations that occur over the entire life-time of an organism. We suggest that the MIDA model cannot only be applied to the aging process itself but possibly also to the general stress response in vivo.

Why a high degree of mitochondrial dynamics is not necessarily beneficial for mitochondrial quality control

There are a number of observations (for details see also 27) that appear counterintuitive considering the prevailing view that a high degree of mitochondrial dynamics is beneficial for MQC. First, ablation of mitochondrial fission in two fungal systems led to a considerable increase in lifespan and not, as one might have expected, to a reduction in lifespan 65. Second, clonal expansion of mtDNA alterations in fungi and humans during aging or during the pathogenesis of certain mitochondriopathies is a widely observed phenomenon that is not well understood 3, 66–77. Mitochondrial content mixing might well promote clonal expansion of mutated mtDNA molecules and thus has potentially rather harmful consequences. Thirdly, the observed reduction of fusion-fission rates in postmitotic/aged cells 54 is unexpected at first sight. However, in the light of the MIDA model this reduction does not necessarily accelerate aging, as one might intuitively assume, but rather delays harmful effects of content mixing. Also the transfer of mitochondrial genetic traits (i.e. the “infectious principle”) from one individual fungal culture to another one 25 or the spread of mtDNA with a deletion leading to “clonal expansion” can be explained by the dynamic behavior of mitochondria which constantly are in the process of fusion and fission.

Experimental hypothesis testing

To test the MIDA hypothesis experimentally one could, for example, down-regulate fusion and fission factors in a cellular or even a mouse model system. These could include model systems for aging such as the “mutator” mouse 78, 79 or models of mitochondriopathies or neurodegenerative disorders. The “mutator” mouse harbors a mitochondrial γ-DNA polymerase lacking a 3′–5′ exonuclease proofreading activity which results in elevated levels of mtDNA mutations, a number of age-related phenotypes, and in a drastic shortening of lifespan. The reduction of mitochondrial dynamics in this or other specific genetic backgrounds can be expected to rescue the adverse effects of mitochondrial dysfunction. Furthermore, we would predict that the degree of heteroplasmy in mammalian cells is influenced by altering mitochondrial fission and/or fusion rates. We propose to generate a cytoplasmic hybrid (cybrid) cell line harboring wild type and mutant mtDNA molecules (e.g. a MERRF or MELAS cybrid cell line) and follow the percentage of mutated mtDNA over time when mitochondrial dynamics is reduced or not.

The prediction is that the observed accumulation of mutated mtDNA over time is delayed when fusion-fission rates are reduced. Alternatively, one could think about preventing the age-dependent deceleration of fusion-fission cycles. This may be achieved by stable (or inducible) overexpression in vivo of a variant of DRP1 that cannot be phosphorylated by protein kinase A (thus remaining fission competent) and/or of a variant of Mfn2 that cannot form disulphide bonds preventing fusion enhancement (see 40, 44, 57). We would predict that both alterations result in increased cytotoxicity and a reduced lifespan.

Next, various forms of external stress (oxidative stress or physical training or drug induced mitochondrial dysfunction) should be applied and the effect of preventing mitochondrial hyperfusion should be assessed in greater detail as has been done so far. Overall, we feel that the next goals in the field will be (i) to obtain more quantitative data from primary tissues in an age-dependent manner and (ii) to test the MIDA model experimentally.


The evaluation of available experimental data, some of which appear to be counterintuitive or even inconsistent, and the computer simulation of mitochondrial dynamics, mitophagy, and the biogenesis of mitochondrial mass uncovered the importance of a flexible regulation of mitochondrial fusion-fission cycles in cells during aging. In general, mitochondrial dynamics in combination with mitophagy is a beneficial process especially when the extent of molecular damage is low. However, when a certain threshold of damage is reached (during aging or under pathological conditions) it is counterproductive to further propagate or mix this damage. In the latter situation it is more beneficial to keep healthy mitochondria apart from the damaged ones. A deceleration of fusion-fission cycles delays reaching thresholds of damage that lead to the degeneration of the system. This reduction of fusion-fission cycles, however, make mitochondria more vulnerable to newly acquired random molecular damage.

Our conclusions imply that a more moderate role is attributed to random molecular damage than is the case in the standard view of MFRTA. The latter aging theory requires a significant impact of random molecular damage by ROS production. The MIDA model, however, calls this view into question as a consequence of extending the traditional view of MRFTA by the recent experimental observations that the mitochondrial network is highly dynamic and involves molecular exchange between interacting mitochondria for quality control. The elucidation of the details concerning the “good” and the “bad” sides of mitochondrial dynamics requires further extensive experimental investigations. In addition to mitochondrial dynamics, mitophagy and biogenesis, other pathways of MQC are active. Unravelling the precise regulation of the involved mechanisms and their interactions is a key for understanding the complex mechanisms involved in aging and lifespan control. Computational simulation of the relevant surveillance pathways and their integration into mathematical models of higher complexity can be a significant part in this strategy.


This work was supported by the BMBF, Germany, GerontoMitoSys project (M.T.F., H.D.O., and A.R.), the DFG grant RE1575-1/1 (A.R.), and the Cluster of Excellence Frankfurt Macromolecular Complexes at the Goethe University Frankfurt DFG project EXC 115 (H.D.O. and A.R.).