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?