Selective removal of deletion-bearing mitochondrial DNA in heteroplasmic Drosophila

http://www.nature.com/articles/ncomms13100

Nikolay P. Kandul, Ting Zhang, Bruce A. Hay & Ming Guo

Mitophagy is the process by which mitochondria are engulfed and degraded within the cell. It has long been thought that mitophagy has a role to play in quality control in the mitochondrial population, however it has remained unclear whether the effect can selectively degrade faulty organelles, or instead is an unbiased process, in vivo. A potential confounding effect is cell division where, simply by dividing, mutants can be driven to fixation through stochastic effects.

To address this question, the authors developed a Drosophila model which can inducibly generate a mitochondrial mutation which would otherwise be lethal if present at birth in the whole-body. This is done through the inducible expression of a mitochondrially-targetted restriction enzyme which cleaves mtDNA in Drosophila in two places, creating a 2584 bp deletion which disrupts or removes several important mitochondrial genes. The authors were able to induce expression of this restriction enzyme in a non-essential, energy-intense, post-mitotic tissue, namely the indirect flight muscle. This is an ideal tissue to study mitophagy, since its energy requirements imply the need for a healthy mitochondrial population, and is non-dividing so does not suffer from confounding effects from the stochastic nature of mtDNA dynamics.

Flies tended to accumulate ~76% heteroplasmy in the mitochondrial deletion by day 10 after hatching, stabilizing thereafter, with no large difference in mtDNA copy number. The flies had similar flight performances to wild-type animals, suggesting that the tissue may withstand high levels of heteroplasmy without phenotypic consequences.

The authors probed the effects of modulating the expression of genes which have been thought to play a role in mitophagy, and measured the resultant heteroplasmy. They investigated Atg1, Atg8a, Pink1 and Parkin, which all had the expected effects on heteroplasmy. Parkin overexpression caused ~71% reduction in heteroplasmy, and Atg1 caused ~72% reduction, these genes having the largest effect sizes. The authors found that inhibition of mitochondrial fusion through MFN silencing had a modest effect on heteroplasmy reduction (37%), which is expected if defective mitochondria are not allowed to re-enter the mitochondrial network. Interestingly, inhibiting ATP synthase from hydrolysing ATP and therefore maintaining mitochondrial membrane potential, through expression of ATPIF1, had a synergistic effect with MFN silencing, resulting in a 64% effect size.  This suggests that mitochondria with mutated mtDNAs may attempt to cheat the mitophagic system by consuming ATP to maintain their membrane potential and avoid detection.

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Thoughts:

These results show that mitophagy can be a selective process, and may be induced to have greater effect sizes. The key question is, if mitophagy is able to clear mitochondrial mutants, why do we see them at all in the wild-type case? What is the tradeoff that keeps mitophagy low? It would be interesting to see the lifespan of these flies upon induction of mitophagy. Are they more susceptible to other pathologies e.g. cancer or aging?

Evolution of Cell-to-Cell Variability in Stochastic, Controlled, Heteroplasmic mtDNA Populations

http://www.cell.com/ajhg/fulltext/S0002-9297(16)30397-4

Iain G. Johnston and Nick S. Jones
 
Mitochondrial DNA (mtDNA) contains instructions for building important cellular machines. We have populations of mtDNA inside each of our cells -- almost like a population of animals in an ecosystem. Indeed, mitochondria were originally independent organisms, that billions of years ago were engulfed by our ancestor's cells and survived -- so the picture of mtDNA as a population of critters living inside our cells has evolutionary precedent! MtDNA molecules replicate and degrade in our cells in response to signals passed back and forth between mitochondria and the nucleus (the cell's "control tower"). Describing the behaviour of these population given the random, noisy environment of the cell, the fact that cells divide, and the complicated nuclear signals governing mtDNA populations, is challenging. At the same time, experiments looking in detail at mtDNA inside cells are difficult -- so predictive theoretical descriptions of these populations are highly valuable.

Why should we care about these cellular populations? MtDNA can become mutated, wrecking the instructions for building machines. If a high enough proportion of mtDNAs in a cell are mutated, our cells struggle and we get diseases. It only takes a few cells exceeding this "threshold" to cause problems -- so understanding the cell-to-cell distribution of mtDNA is medically important (as well as biologically fascinating). Simple mathematical approaches typically describe only average behaviours -- we need to describe the variability in mtDNA populations too. And for that, we need to account for the random effects that influence them.  

​In our cells, signals from the "control tower" nucleus lead to the replication (orange) and degradation (purple) of mtDNA. These processes affect mtDNA populations that may contain normal (blue) and mutant (red) molecules. Our mathematical approach -- extending work addressing a similar but simpler system -- describes how the total number of machines, and the proportion of mutants, is likely to behave and change with time and as cells divide.

 
In the past, we have used a branch of maths called stochastic processes to answer questions about the random behaviour of mtDNA populations. But these previous approaches cannot account for the "control tower" -- the nucleus' control of mtDNA. To address this, we've developed a mathematical tradeoff -- we make a particular assumption (which we show not to be unreasonable) and in exchange are able to derive a wealth of results about mtDNA behaviour under all sorts of different nuclear control signals. Technically, we use a rather magical-sounding tool called "Van Kampen's system size expansion" to approximate mtDNA behaviour, then explore how the resulting equations behave as time progresses and cells divide.

Our approach shows that the cell-to-cell variability in heteroplasmy (the potentially damaging proportion of mutants in a cell) generally increases with time, and surprisingly does so in the same way regardless of how the control tower signals the population. We're able to update a decades-old and commonly-used expression (often called the Wright formula) for describing heteroplasmy variance, so that the formula, instead of being rather abstract and hard to interpret, is directly linked to real biological quantities. We also show that control tower attempts to decrease mutant mtDNA can induce more variability in the remaining "normal" mtDNA population. We link these and other results to biological applications, and show that our approach unifies and generalises many previous models and treatments of mtDNA -- providing a consistent and powerful theoretical platform with which to understand cellular mtDNA populations. The article is in the American Journal of Human Genetics here and a preprint version can be viewed here. (crossed from Evolution, Energetics & Noise)

Cellular Allometry of Mitochondrial Functionality Establishes the Optimal Cell Size

http://www.sciencedirect.com/science/article/pii/S1534580716306268

Teemu P. Miettinen and Mikael Björklund

Cells in a population, despite having the same genetic content, are often very different from each other due to the stochastic nature of biological processes. An example is cellular size: some cells are big, some are small and some have an intermediate size. How does the size of a cell affect its functionality? Is there an optimal cell size? This paper focusses on how mitochondrial functionality changes with cell size.

It is known that if a cell is twice as big, it will approximately have twice as many mitochondria, keeping the mitochondrial density roughly constant. However, the expression of mitochondrial genes becomes less than twice as high, meaning that bigger cells express relatively less mitochondrial genes. This may mean that there is a particular cell size corresponding to optimal mitochondrial functionality.

In the paper, they use single cell flow cytometry to measure the size of about 10^5-10^6 cells. Additionally, the mitochondrial membrane potential per unit cell size (ΔΨ) is measured. The relationship between cell size and ΔΨ can then be investigated.

Some of the findings are:

• Consistent with previous studied, mitochondrial mass increases linearly with cell size
• ΔΨ first increases as cells get larger, but then decreases again as cells get very large.
• Mitochondrial respiration is highest in intermediate-sized cells
• Intermediate-sized cells show the lowest variation in mitochondrial membrane potential
• A higher ΔΨ variation is correlated with a higher rate of apoptosis (cell death)
• Intermediate-sized cells showed (on average) the fastest growth

These results strongly indicate that mitochondrial functionality is largest in intermediate-sized cells in a population. Cells also seem to try to maintain the size at which mitochondrial functionality is largest, meaning that this is probably an optimal cell size.

Mitochondrial Dysfunction Prevents Repolarization of Inflammatory Macrophages

http://www.cell.com/cell-reports/supplemental/S2211-1247(16)31213-X

Jan Van den Bossche, Jeroen Baardman, Natasja A. Otto, Saskia van der Velden, Annette E. Neele, Susan M. van den Berg, Rosario Luque-Martin, Hung-Jen Chen, Marieke C.S. Boshuizen, Mohamed Ahmed, Marten A. Hoeksema, Alex F. de Vos, Menno P.J. de Winther

Macrophages are types of white blood cell. They engulf and digest bodies which do not possess the correct protein markers which mark healthy cells. Whilst these cells play a crucial role in immunity, their dysfunction is associated with a number of auto-immune diseases such as asthma and rheumatoid arthritis. Macrophages exist in a spectrum of states, ranging from pro-inflammatory (M1) to anti-inflammatory (M2). In this study, the authors wished to investigate the mechanisms which prevent the transition from M1 to M2, so that we may better understand the mechanisms of inflammation.

Previous studies have shown that M1 cells are reliant upon glycolysis whereas M2 cells use mitochondrial oxidative phosphorylation (OXPHOS). These modes of energy production have also been associated with promoting the activation of these macrophage states. The authors find here that when macrophages are induced (using LPS + IFN-γ) to become M1 (pro-inflammatory) cells, this process inhibits OXPHOS. The signal (IL-4) which induces M2 (anti-inflammatory) cells cannot reverse this suppression of OXPHOS, and so they remain trapped in the pro-inflammatory state. The authors found that nitric oxide production by M1 cells, which is used as an antimicrobial mechanism and inhibits mitochondrial function, prevents the ability of M1 macrophages to be reprogrammed as non-inflammatory M2 cells.

Loss of Dendritic Complexity Precedes Neurodegeneration in a Mouse Model with Disrupted Mitochondrial Distribution in Mature Dendrites

López-Doménech G, Higgs NF, Vaccaro V, Roš H, Arancibia-Cárcamo IL, MacAskill AF, Kittler JT

http://www.cell.com/cell-reports/abstract/S2211-1247(16)31208-6

Miro proteins link mitochondria to motor proteins, allowing them to be trafficked through neurons. In this study, the authors disrupted the expression of Miro proteins in neurons to understand the role of mitochondrial trafficking in neurodegeneration. The authors found that Miro1-KO caused the distribution of mitochondria in dendrites (the branched extensions of nerve cells which receive electrochemical signals from other neurons) to become more accumulated around the soma, and more sparse along dendrites. Miro1-KO cells also appeared smaller and less developed than wild-type neurons; this was also shown to be the case in an inducible Miro1-KO system in mature neurons of the forebrain of mice. The deletion of this gene was associated with neurodegeneration 12 months after induction of Miro1-KO.

Prediction of multidimensional drug dose responses based on measurements of drug pairs

Anat Zimmer, Itay Katzir, Erez Dekel, Avraham E. Mayo, and Uri Alon

http://www.pnas.org/content/113/37/10442.full

*Not mitochondrial, but very cool

Cocktail therapies are common to treatments of a diverse array of diseases, in order to combat effects such as: antibiotic resistance in bacterial infections; persister cells in tuberculosis; and chemotheraputic resistance in cancer. It is, however, incredibly difficult to optimize the dose of multiple theraputic agents because of combinatorial explosions. For instance, if we have 10 possible doses for 3 different drugs, then we must test 10x10x10 = 1000 different dose combinations to find the optimal treatment. This becomes 10,000 if we wish to use 4 drugs. What makes this problem even more difficult is that drugs often show antagonism: it is not simply the case that using higher and higher doses of each drug is more effective, the optimum is often found at intermediate doses.

Here, the authors use mathematics to try and approximate the optimal dose of a cocktail of three or more drugs (N in general) whilst avoiding the problem of combinatorial explosion. They model the survival of cells (g) versus drug concentration (Di), for each drug (i), using Hill curves. They approximate g(D1, ... ,DN) using information only from single-drug dose response curves g(Di) and two-drug data g(Di, Dj) for all pairs of drugs. Their computation therefore only scales quadratically with the number of drugs N, rather than exponentially if we were to brute-force compute the global optimum. The authors show that their method is able to well-describe dose-response curves for a case study of six triplet and two quadruplet combination therapies, with 0.85 < R^2 < 0.93 for all of the examples tested.

These methods not only allow us to find the most effective doses, but also has the potential to minimize side effects by optimizing with the assumption that side-effects increase with higher dose. More realistic predictions could be made with more accurate models for side-effects.

Lactate metabolism is associated with mammalian mitochondria

Ying-Jr Chen, Nathaniel G Mahieu, Xiaojing Huang, Manmilan Singh, Peter A Crawford, Stephen L Johnson, Richard W Gross, Jacob Schaefer, Gary J Patti

http://www.nature.com/nchembio/journal/vaop/ncurrent/full/nchembio.2172.html

Lactate is sometimes referred to as "metabolic waste" but this has been established as a misnomer for quite some time, with it being shown as early as the 1920s that lactate can be transformed back into glucose via gluconeogenesis in the liver. There are multiple other examples where shuttling of lactate between tissues allows it to be metabolised. However,  it remains controversial whether individual cells are able to metabolise this apparent metabolic by-product.

Here, the authors show that lactate is able to enter mitochondria and participate in mitochondrial energy metabolism. By culturing cells in radiolabelled lactate, the authors show that carbon from lactate can be found in intermediate metabolites of the TCA. They show that mitochondria are able to metabolize lactate, suggesting that they are able to import the metabolite, and that mitochondria possess the necessary enzyme (lactate dehydrogenase B) to convert lactate into the better-known mitochondrial substrate, pyruvate. The authors suggest this may be particularly relevant in cancer cells, which have particularly high glycolysis and lactate production.

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Thoughts: It seems like a pretty important follow-up question to ask how much lactate is used by mitochondria relative to secretion in vivo. If the effect is big, doesn't this mean extracellular acidification rate is not a good metric of glycolysis levels?

The repopulating cancer cells in melanoma are characterized by increased mitochondrial membrane potential

http://www.sciencedirect.com/science/article/pii/S0304383516305122

Don G. Lee, Beom K. Choi, Young H. Kim, Ho S. Oh, Sang H. Park, Young Soo Bae, Byoung S. Kwon

In this study, the authors investigate whether mitochondrial membrane potential (ΔΨ) serves as a biomarker of higher proliferative potential in melanoma cells. The authors found that tumour cells which survived stressors such as serum starvation and cisplatin treatment had substantially higher ΔΨ. Furthermore, upon sorting cells into categories of low and high ΔΨ, the authors found that high-ΔΨ cells tended to induce tumour growth whereas low-ΔΨ could not, for doses of 10^5 cells/mouse: this was demonstrated for cells grown in vitro as well as sorted tumour cells grown in vivo.

Homeostatic Responses Regulate Selfish Mitochondrial Genome Dynamics in C. elegans

Bryan L. Gitschlag, Cait S. Kirby, David C. Samuels, Rama D. Gangula, Simon A. Mallal, Maulik R. Patel

http://www.sciencedirect.com/science/article/pii/S1550413116302947

Why haven't deleterious mutations in mitochondrial DNA gone extinct? Naively, if a mutation has a negative impact on the fitness of an organism, then that organism may be less likely to reproduce and, in time, we expect to see fewer organisms with the mutation in nature. And yet deleterious mutations in mtDNA are still seen and passed down from generation to generation (albeit that this is often through carriers who bear such mutations at lower loads). 

The authors of this study explore this simple, but fundamental, question by establishing a slightly deleterious mtDNA variant in C. elegans, called uaDF5. This is a deletion mutation which removes four protein-coding genes and seven tRNAs. The authors show that worms are still viable with a mutant load as high as 80% (but lethal at 100%), and that mtDNA copy number tended to increase in individuals with large mutant load (suggesting expansion of the total mtDNA population so that there are enough wild-type mtDNA molecules to fulfil the metabolic needs of the animal). The authors also determined that it is unlikely that the mutation has a proliferative advantage by virtue of its smaller size, through comparison with another deletion mutant which was much smaller.

In addition to mtDNA copy number control, the authors suggest an additional mechanism whereby mutant mtDNAs may proliferate. The authors find that silencing of the mitochondrial unfolded protein response (mt-UPR) causes a substantial reduction in mutant load. The mt-UPR is thought to provide a protective role against adverse conditions for mitochondria; the authors suggest here that the process inadvertently allows mutants to proliferate as it suppresses mitophagy: the mechanism by which faulty mitochondria are recycled by the cell. They show this by blocking mt-UPR and parkin-mediated mitophagy to show a recovery in mutant load.

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Thoughts: A natural question to ask is, given that these heteroplasmic animals are less fit, why do cells not have a larger mitophagy rate if this allows quality control? Is there some tradeoff where wild-type mtDNAs are also consumed? Perhaps with a lower probability?

Selective Vulnerability of Cancer Cells by Inhibition of Ca2+ Transfer from Endoplasmic Reticulum to Mitochondria

http://www.sciencedirect.com/science/article/pii/S2211124716301334

César Cárdenas, Marioly Müller, Andrew McNeal, Alenka Lovy, Fabian Jaňa, Galdo Bustos, Felix Urra, Natalia Smith, Jordi Molgó, J. Alan Diehl, Todd W. Ridky, J. Kevin Foskett

Mitochondria are often found to be tethered to another organelle of the cell, called the endoplasmic reticulum (ER). The ER releases calcium into the mitochondria, which stimulates energy metabolism by increasing the rate of several catalysts in the metabolic network. A basal level of calcium release is necessary for mitochondrial ATP production in many cell types. Without this, cells tend to start recycling themselves through autophagy, as a survival mechanism.

In this study, the authors probe the difference in response to normal and cancer cells, to blocking calcium release (using the drug XeB, as well as genetic knockdown of the gene InsP3R) from the ER to mitochondria. The authors compared the cell death response of non-tumourigenic MCF10A cells to three tumorigenic cell lines (MCF7, T47D and HS578T). At 5uM XeB, the authors find that breast tumour cell lines experienced significant cell death (43, 53 and 22%) whereas normal cells were less sensitive to the drug (5% cell death). Similar effect sizes were seen in prostate cancer cells, at the same drug concentration. It was also the case that XeB did not induce large cell death in primary human fibroblasts, when compared to transformed cells.

The authors found that providing the tumour cells with additional pyruvate rescued their proliferation rate. Calcium stimulates the enzyme pyruvate dehydrogenase, which takes pyruvate from glycolysis and converts it into acetyl-coa, for use in mitochondrial metabolism. Therefore it is reasonable to conclude that providing additional pyruvate pushes flux through the network, to compensate for lower enzymatic activity (by mass-action kinetics).

The authors hypothesized that nucleoside supplementation may also rescue the effect of calcium import inhibition, since mitochondrial metabolism is intertwined with nucleoside synthesis (a necessity for DNA synthesis). Indeed, the authors found that nucleoside supplementation ameliorated cytotoxicity by ~50%. This indicates that nucleoside production of mitochondria is more important than their energy production, in this model. The authors show mechanistically that, when cancer cells are blocked in calcium uptake, they progress through the cell cycle normally, but their progression into mitosis results in necrotic cell death. In contrast, normal cells halt their cell cycle at G1 phase.

Segregation of naturally occurring mitochondrial DNA variants in a mini-pig model

http://genetics.org/content/early/2016/01/25/genetics.115.181321

 

Gael Cagnone, Te-Sha Tsai, Kanokwan Srirattana, Fernando Rossello, David R. Powell, Gary Rohrer, Lynsey Cree, Ian A. Trounce, Justin St. John

 

Recent work in mice has shown that different mitochondrial sequences (haplotypes) will tend to accumulate in different tissues, and this segregation depends on the sequence in question.

In this study, the authors study four mtDNA mutations, over three generations of mini-pigs. These mutations were: Del A376 affecting 12 rRNA; Del A1302 affecting 16s rRNA; Del A1394 affecting 16s rRNA; and Del A9725 affecting NADH3 (a protein of the electron transport chain). The authors investigated which tissues had variable mutant load, and found that mutant load is significantly reduced in diaphragm (4/4 mutants), muscle (3/4 mutants), brain (2/4 mutants) and fat (2/4 mutants). 

 

They then go on to correlate the variation with mtDNA copy number, across all tissues, and all generations. In one of the four cases, no correlation was observed. However, in Del A376 and Del 1302, variant load had a fairly strong negative correlation with mtDNA copy number; in Del 1394, the correlation was weaker and also negative.

 

The authors therefore suggest that mutant load is lowered in high-respiratory tissue, such as brain, diaphragm, muscle, liver, heart and fat.

 

 

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Thoughts: Are these mutants deleterious to respiratory activity? I imagine so, since they are all deletion mutations, so cause frameshifts. If that is the case, I wonder if the mutations could be ranked by how much they inhibit OXPHOS? I wonder whether the strongest inhibitors either have i) the strongest gradient with mtDNA copy number or ii) lowest overall abundance in all tissues?

I also find it pretty surprising that frameshift mutations can be found in healthy pig tissues, even 2-15%. I wonder whether there is a complementation effect happening here: several different mutants producing transcription products that the others cannot?

Accurate concentration control of mitochondria and nucleoids

 Rishi Jajoo, Yoonseok Jung, Dann Huh, Matheus P. Viana, Susanne M. Rafelski, Michael Springer, Johan Paulsson

http://classic.sciencemag.org/content/351/6269/169.long

When a cell divides, all components in the cell need to go into either one of the daughter cells. The cell has developed mechanisms to make sure that some components, for example chromosomes, are correctly segregated. How does this work for mitochondria? Does the cell have active mechanisms to push equal amounts of mitochondria in each daughter cell, or do the mitochondria randomly move into one of the daughters?

In this paper, they try to answer these questions in fission yeast S. Pombe.
It was shown before that mitochondria are pushed to both of the cell poles before cell division, which would suggest that this is a mechanism of segregating the mitochondria.

However, in this paper they show that in the last 15% of the cell cycle, mitochondria spatially re-equilibrate themselves throughout the cell. When the cell divides, the mitochondrial volume in a daughter cell tracks the cytoplasmic volume of that daughter cell. For example, if the two daughters get 60% and 40% of the cytoplasmic volume, they will on average also get 60% and 40% of the mitochondrial volume.
The same is true of mitochondrial nucleoids, which contain the mitochondrial DNA; they too segregate in proportion to the cytoplasmic volume.

However, the errors made in nucleoid segregation are smaller than you would expect from passive mechanisms. Using the example from above, passively one would expect that each nucleoid has a probability of 0.6 of ending up in the larger daughter (the one with 60% of the cytoplasm) and a probability of 0.4 of ending up in the other daughter. This is called binomial partitioning and has a certain error size associated with it. The actual errors that are made in S. Pombe (i.e. the deviations from perfect partitioning) are smaller than binomial errors.

A model that would explain these sub-binomial nucleoid segregation errors is to assume that the nucleoids are regularly spaced out within the mitochondria. It is not known how this regular spacing is accomplished by the cell.

The authors also find that the number of nucleoids that are produced from beginning to end of the cell cycle does not depend on the initial amount that was present. This suggests that S. Pombe does not not use feedback control to produce its nucleoids (or other mitochondrial proteins). Feedback control is energetically expensive. Rather, nucleoids are randomly added throughout the cell cycle, following a Poisson distribution.

TCA Cycle and Mitochondrial Membrane Potential Are Necessary for Diverse Biological Functions

http://www.sciencedirect.com/science/article/pii/S1097276515009363

Inmaculada Martínez-Reyes, Lauren P. Diebold, Hyewon Kong, Michael Schieber, He Huang, Christopher T. Hensley, Manan M. Mehta, Tianyuan Wang, Janine H. Santos, Richard Woychik, Eric Dufour, Johannes N. Spelbrink, Samuel E. Weinberg, Yingming Zhao, Ralph J. DeBerardinis, Navdeep S. Chandel

In this study, the authors investigate the effect of eliminating mtDNA from cells, on metabolism. This is often achieved by incubation with the chemical ethidium bromide, which prevents the protein responsible for mtDNA replication (POLG) from working. However, ethidium bromide is toxic and has potentially off-target effects. The authors engineered cells which, upon exposure to an antibiotic, express a dominant-negative form of POLG (DN-POLG), thereby removing potential off-target effects. Within 6 days of induction of DN-POLG, mtDNA transcription had ceased.

Cells had a greatly reduced proliferation rate (although still viable), despite having access to glucose and pyruvate: metabolites required to drive glycolysis and the TCA cycle respectively. As discussed in [1] (see here) mitochondria oxidise NADH to NAD+, the substrate of glycolysis. The authors introduced two non-mammalian proteins (NDl1 and AOX), which together carry electrons in a similar manner to the electron transport chain, but do not pump protons across the inner mitochondrial membrane. In this way, NAD+ can be restored, without generating mitochondrial ATP from oxidative phosphorylation. The authors show that these proteins are sufficient to drive flux through the TCA cycle, and increase the NAD+/NADH ratio. However, the authors find that these cells still have an impaired proliferation rate (at odds with the findings in [1]?)

The authors investigated an alternative reason for the impaired proliferation of these cells: mitochondrial membrane potential (ΔΨm). Cells without mtDNA cannot pump protons to maintain ΔΨm, but ATP synthase is still able to hydrolyse ATP from glycolysis, to maintain ΔΨm. An endogenous inhibitor of this function is the protein ATPIF1. The authors knocked out this gene, and showed that cells without mtDNA are able to maintain their ΔΨm at wild-type levels. These ATPIF1-KO cells had a, statistically significant, partial recovery in proliferation rate.

Interestingly, treating the ATPIF1-KO cells with an antioxidant, which mops up ROS (canonically considered to be the bad-guy of mitochondrial physiology, see here), reduced the proliferation rate. This shows that ROS, as well as ΔΨm, are necessary for cells to proliferate.

[1] Wiley, Christopher D., et al. "Mitochondrial Dysfunction Induces Senescence with a Distinct Secretory Phenotype." Cell metabolism (2015).

Mitochondrial Dysfunction Induces Senescence with a Distinct Secretory Phenotype

http://www.sciencedirect.com/science/article/pii/S1550413115005781

Wiley CD, Velarde MC, Lecot P, Liu S, Sarnoski EA, Freund A, Shirakawa K, Lim HW, Davis SS, Ramanathan A, Gerencser AA, Verdin E, Campisi J

Cellular senescence is the process by which dividing cells permanently lose their ability to replicate. This phenotype can inhibit the growth of cancerous cells, but it is also thought to occur in normal tissues during aging. It is known that mitochondrial dysfunction can induce senescence, however the mechanisms of this are unclear.

The authors show that several different kinds of mitochondrial dysfunction can induce senescence in the IMR-90 cell line: mtDNA depletion; drugs which inhibit the electron transport chain (rotenone and antimycin A); and inhibition of a particular mitochondrial chaperone (HSPA9) which aids in import of proteins into mitochondria.

Mitochondria oxidise NADH to NAD+ in a number of metabolic reactions involved in generating energy. NAD+ is a substrate of glycolysis, whereas NADH is a product, which can inhibit the pathway if it is not removed. As glycolysis provides pyruvate, the substrate of oxidative phosphorylation, a reduced NAD+/NADH ratio may be expected to slow down glycolysis and therefore oxidative phosphorylation.

The authors provide evidence that the mechanism of mitochondrially-induced senescence is lowered NAD+/NADH ratios, suggesting energetic collapse. This is supported by an increased ADP/ATP ratio in these cells. They find that supplementation of pyruvate to cells can partially rescue the senescent phenotype.

The authors further show the relevance of mitochondrially-induced senescence, by investigating the effect in POLG mutator mice (mice which accumulate mtDNA mutations in time and have a progerioid phenotype). The authors found that the progerioid mice had many more senescent cells in affected tissues, with lowered NAD+/NADH ratios compared to wild-type mice.

Mitochondrial Membrane Potential Identifies Cells with Enhanced Stemness for Cellular Therapy

http://www.sciencedirect.com/science/article/pii/S1550413115005690

Sukumar M, Liu J, Mehta GU, Patel SJ, Roychoudhuri R, Crompton JG, Klebanoff CA, Ji Y, Li P, Yu Z, Whitehill GD, Clever D, Eil RL, Palmer DC, Mitra S, Rao M, Keyvanfar K, Schrump DS, Wang E, Marincola FM, Gattinoni L, Leonard WJ, Muranski P, Finkel T, Restifo NP

Cancer immunotherapy involves using the immune system to target and eradicate tumours. One method is to isolate and transfer immune cells into the patient. There are a number of different kinds of immune cell, one of which is called the T cell. T cells themselves divide into a number of subtypes, two of which are: effector memory (EM) and stem-cell memory (SCM) T cells. It is known that SCM cells are able to persist for longer periods of time, and are more effective in attacking tumour cells than EM cells. It is therefore desirable to be able to enrich for SCM cells, in a mixed population of T cells, to deliver a more potent immunotherapy.

In this study, the authors stain a mixed population of T cells with a chemical which causes cells with a large mitochondrial membrane potential (ΔΨm) to fluoresce more strongly (using TMRM). They find that fractions with low membrane potential are enriched for SCM cells, whereas fractions with high membrane potential are enriched for EM cells. Indeed, the authors show in a variety of cell lines that low ΔΨm is associated with stem-like properties.

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Thoughts:
Curiously, low ΔΨm cells had a lower glycolysis rate, and higher spare respiratory capacity, and lower baseline respiratory rate, compared to high ΔΨm cells. Low ΔΨm cells tend to favour fatty acid oxidation, which provides an alternative substrate to glucose for energy production. However, fatty acid oxidation drives the Krebs cycle, which in turn can drive oxidative phosphorylation. So, given that these cells are not undergoing glycolysis, one might expect ΔΨm low cells to have a higher resting oxygen consumption rate? It would be interesting to know the ATP concentration of the ΔΨm low cells: my guess would be that they have a lower ATP concentration?