Project description:We characterized the global response of plants carrying a mitochondrial dysfunction induced by the expression of the unedited form of the ATP synthase 9 subunit. The u-ATP9 transgene driven by A9 and Apetala3 promoters induce mitochondrial dysfunction revealed by a decrease in both oxygen uptake and ATP levels, with an increase in ROS and a concomitant oxidative stress response. The transcriptome analysis of young Arabidopsis flowers, validated by RT-PCR and enzymatic or functional tests, show dramatic changes in u-ATP9 plants. Both lines present a modification in the expression of several genes involved in carbon, lipid and cell wall metabolism, suggesting that an important metabolic readjustment occurs in plants with a mitochondrial dysfunction. Interestingly, transcript levels involved in mitochondrial biogenesis, protein synthesis, and degradation are affected. Moreover, several mRNA levels for transcription factors and DNA binding proteins were also changed. Some of them are involved in stress and hormone response, suggesting that several signaling pathways overlap. Indeed, the transcriptome data reveal that the mitochondrial dysfunction dramatically alters genes involved in signaling pathways, including those involved in ethylene, absicic acid and auxin signal transduction. Our data suggest that the mitochondrial dysfunction model used in this rapport may be useful to uncover the retrograde signaling mechanism between the nucleus and mitochondria in plant cells. Arabidopsis oligonucleotide microarrays fabricated by the University of Arizona contain 26,000 oligonucleotides (http://www.ag.arizona.edu/microarray/). RNA was isolated from 6-week-old flowers from u-ATP9 and wt plants. The experimental (mutant) and reference (wild type) RNA samples were reverse-transcribed and directly labeled with either Cy5-dUTP or Cy3-dUTP fluorescent dye (GE Healthcare), using random hexamer primers (Invitrogen). Excess nucleotides and primers were removed using QIAquick PCR Purification Kit (Qiagen). Labeled samples were mixed and then hybridized to microarray for 15 h at 60°C. The slides were washed at room temperature in three wash steps: 2 x SSC, 0.5% SDS; 0.5 x SSC; and 0.05 x SSC for 5 min each with gentle shaking. The slides were scanned with a GenePix 4000B Scanner (Axon Instruments Inc., Union City, CA). Normalization between the Cy3 and Cy5 fluorescent dye emission channels was achieved by adjusting the levels of both image intensities. The experiments were repeated four times with samples from different experiments, as biological replicates. In dye swapping experiments, the RNA samples from different experiments were reciprocally labeled, both as a biological and technical repetition for comparing the reproducibility of the experiments. Hybridization intensities for each microarray element were measured using ScanAlyze 4.24 (available at http://genome-www4.stanford.edu/MicroArray/SMD/restech.html). The two channels were normalized in log space using the z-score normalization on a 95% trimmed data set. We removed unreliable spots according to the following criteria: spots flagged as having false intensity caused by dust or background on the array were removed; and spots for which intensity was less than three fold above background were also eliminated. Data from multiple experiments were normalized (Bolstad, 2003) and signals from spots from different experiments were statistically analyzed using Significance Analysis of Microarrays using the one class response (SAM, http://www-stat.stanford.edu/~tibs/SAM/), cut at a false discovery rate < 10% (Tusher, 2001).

Project description:DallePazze2014 - Cellular senescene-induced mitochondrial dysfunction This model is described in the article: Dynamic modelling of pathways to cellular senescence reveals strategies for targeted interventions. Dalle Pezze P, Nelson G, Otten EG, Korolchuk VI, Kirkwood TB, von Zglinicki T, Shanley DP. PLoS Comput. Biol. 2014 Aug; 10(8): e1003728 Abstract: Cellular senescence, a state of irreversible cell cycle arrest, is thought to help protect an organism from cancer, yet also contributes to ageing. The changes which occur in senescence are controlled by networks of multiple signalling and feedback pathways at the cellular level, and the interplay between these is difficult to predict and understand. To unravel the intrinsic challenges of understanding such a highly networked system, we have taken a systems biology approach to cellular senescence. We report a detailed analysis of senescence signalling via DNA damage, insulin-TOR, FoxO3a transcription factors, oxidative stress response, mitochondrial regulation and mitophagy. We show in silico and in vitro that inhibition of reactive oxygen species can prevent loss of mitochondrial membrane potential, whilst inhibition of mTOR shows a partial rescue of mitochondrial mass changes during establishment of senescence. Dual inhibition of ROS and mTOR in vitro confirmed computational model predictions that it was possible to further reduce senescence-induced mitochondrial dysfunction and DNA double-strand breaks. However, these interventions were unable to abrogate the senescence-induced mitochondrial dysfunction completely, and we identified decreased mitochondrial fission as the potential driving force for increased mitochondrial mass via prevention of mitophagy. Dynamic sensitivity analysis of the model showed the network stabilised at a new late state of cellular senescence. This was characterised by poor network sensitivity, high signalling noise, low cellular energy, high inflammation and permanent cell cycle arrest suggesting an unsatisfactory outcome for treatments aiming to delay or reverse cellular senescence at late time points. Combinatorial targeted interventions are therefore possible for intervening in the cellular pathway to senescence, but in the cases identified here, are only capable of delaying senescence onset. This model is hosted on BioModels Database and identified by: BIOMD0000000582. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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RNA-sequencing analysis reveals mitochondrial dysfunction in Akap1 Knockout mice exposed to hyperoxia

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