Nuclear genomic control of naturally occurring variation in mitochondrial function in Drosophila melanogaster
- Patricia Jumbo-Lucioni†1, 4,
- Su Bu†1,
- Susan T Harbison†2,
- Juanita C Slaughter1,
- Trudy FC Mackay3,
- Douglas R Moellering1Email author and
- Maria De Luca1Email author
© Jumbo-Lucioni et al.; licensee BioMed Central Ltd. 2012
Received: 8 June 2012
Accepted: 16 November 2012
Published: 22 November 2012
Mitochondria are organelles found in nearly all eukaryotic cells that play a crucial role in cellular survival and function. Mitochondrial function is under the control of nuclear and mitochondrial genomes. While the latter has been the focus of most genetic research, we remain largely ignorant about the nuclear-encoded genomic control of inter-individual variability in mitochondrial function. Here, we used Drosophila melanogaster as our model organism to address this question.
We quantified mitochondrial state 3 and state 4 respiration rates and P:O ratio in mitochondria isolated from the thoraces of 40 sequenced inbred lines of the Drosophila Genetic Reference Panel. We found significant within-population genetic variability for all mitochondrial traits. Hence, we performed genome-wide association mapping and identified 141 single nucleotide polymorphisms (SNPs) associated with differences in mitochondrial respiration and efficiency (P ≤1 × 10-5). Gene-centered regression models showed that 2–3 SNPs can explain 31, 13, and 18% of the phenotypic variation in state 3, state 4, and P:O ratio, respectively. Most of the genes tagged by the SNPs are involved in organ development, second messenger-mediated signaling pathways, and cytoskeleton remodeling. One of these genes, sallimus (sls), encodes a component of the muscle sarcomere. We confirmed the direct effect of sls on mitochondrial respiration using two viable mutants and their coisogenic wild-type strain. Furthermore, correlation network analysis revealed that sls functions as a transcriptional hub in a co-regulated module associated with mitochondrial respiration and is connected to CG7834, which is predicted to encode a protein with mitochondrial electron transfer flavoprotein activity. This latter finding was also verified in the sls mutants.
Our results provide novel insights into the genetic factors regulating natural variation in mitochondrial function in D. melanogaster. The integrative genomic approach used in our study allowed us to identify sls as a novel hub gene responsible for the regulation of mitochondrial respiration in muscle sarcomere and to provide evidence that sls might act via the electron transfer flavoprotein/ubiquinone oxidoreductase complex.
Mitochondria are organelles found in nearly all eukaryotic cells that participate in many fundamental cellular processes. A primary role of mitochondria is to utilize oxygen and nutrients to form adenosine triphosphate (ATP) via a process called oxidative phosphorylation (OxPhos) . In addition, mitochondria are important in cellular Ca2+ signaling, the regulation of apoptosis, and as a main source of reactive oxygen species (ROS) . ROS are generated and coordinated by redox-coupled reactions in multiple sites within the mitochondrial electron transport chain (ETC) and play critical roles in retrograde signaling  and physiological cell signaling and transduction . However, if produced in excess, ROS can oxidize and damage various cellular components, including mitochondrial proteins, membranes, lipids, and nuclear and mitochondrial genomes . Thus, mitochondrial dysfunction and ROS formation can have widespread adverse effects on many cellular processes and have been implicated in pathological conditions as diverse as heart failure, hypoxia, diabetes, neurodegenerative diseases, and the physiological process of aging .
The OxPhos system consists of five large multi-protein complexes, four of which (complexes I-IV) make up the ETC . During OxPhos, electrons from reduced substrates, such as nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FADH2), which are generated in the Krebs cycle, are fuelled into complexes I (NADH dehydrogenase) and II (succinate dehydrogenase) of the ETC. The electrons are then transferred through the complexes III (cytochrome bc1 oxidoreductase) and IV (cytochrome c oxidase) ultimately reducing oxygen to water, with protons concurrently pumped across the mitochondrial inner membrane in complexes I, III, and IV. This establishes an electrochemical potential difference across the inner membrane and a motive force for protons to re-enter through ATP synthase (complex V). ATP synthase captures the potential energy released upon protons re-entry by converting adenosine diphosphate (ADP) and inorganic phosphate to ATP. In this manner, electron transport is coupled to OxPhos . The efficiency with which mitochondria convert oxygen into ATP to perform useful work is known as mitochondrial energy coupling efficiency or P:O ratio . In a perfectly coupled system, protons would only re-enter the mitochondrial matrix through ATPsynthase in the presence of ADP. In isolated mitochondrial suspensions, this form of respiration is classified as ‘state 3’ (i.e. the O2 is consumed in the presence of saturating amounts of respiratory substrate and ADP). However, it has been known for several decades that under normal conditions protons leak back through the mitochondrial membrane into the matrix via a mechanism that does not involve ATP synthase . This uncouples respiration from OxPhos. Proton leak increases exponentially with the membrane potential (“non-Ohmic” pattern)  and is greatest under non-phosphorylating conditions, such as ‘state 4’ respiration (i.e. O2 is consumed in the presence of respiratory substrate and absence of ADP) in isolated mitochondria. Thus, mitochondria in the intact cell would normally respire at a rate somewhere between state 3 and state 4 respiration rates depending on the energy demand, substrate availability, oxygen, ADP availability, and proton leak back into the matrix. The mechanisms that account for proton leak are poorly understood, but phospholipids and fatty acid composition of the mitochondrial inner membrane and the expression and activation of uncoupling proteins (UCPs) are proposed contributors to the leak [9, 10].
In all Metazoa, the large OxPhos complexes are encoded mainly by nuclear genes and, to a small extent, by mitochondrial genes. The only exception is represented by complex II subunits that are entirely encoded by nuclear genes . Given the impact mitochondria have for cellular survival and function, numerous mutations in both mitochondrial- and nuclear-encoded OxPhos genes have been reported to be responsible for rare pathological disorders . Genetic studies have also provided evidence of associations between mitochondrial DNA (mtDNA) polymorphisms and aging  as well as age-related metabolic disorders, such as type-2 diabetes and cardiovascular disease . However, despite substantial progress in the field, we remain largely ignorant about the genomic regulation of natural variation in mitochondrial respiration. This is important for understanding the evolution of these traits in natural populations and also essential for the development of mitochondria-specific therapeutic strategies for the treatment and prevention of disorders related to mitochondrial dysfunction. To address this critical gap in our knowledge of mitochondrial biology, in this study we used Drosophila melanogaster as our model organism. We chose D. melanogaster for several reasons. First, this organism has emerged in recent years as a powerful model to elucidate the genomic basis that controls naturally occurring variation in quantitative traits, such as mitochondrial respiration traits . Second, the OxPhos system of insect mitochondria resembles that of mammalian mitochondria [16–18], with the mitochondrial respiration being affected by the same inhibitors and uncouplers that affect the mammalian system [19, 20]. Third, D. melanogaster possesses four genes coding for close relatives of the UCPs. One of the four fly genes (Bmcp) has been shown to be a Drosophila mitochondrial uncoupler of OxPhos . Finally, several genetic mechanisms controlling energy metabolism and homeostasis are shared between invertebrates and mammals [22–25]. Thus, insights gained from genomic studies in Drosophila are likely to apply to mammals.
First, we investigated whether there is variability in mitochondrial respiration and coupling efficiency among 40 inbred, sequenced lines of the Drosophila Genetic Reference Panel (DGRP), a newly established D. melanogaster genomics resource . This was accomplished by quantifying state 3 and state 4 respiration rates and the P:O ratios in mitochondria isolated from the thoraces (mainly composed of flight muscles) of young flies using NADH-linked respiratory substrates. Our study revealed significant genetic variation in mitochondrial function. As such, we next sought to identify the genomic architecture underlying such variability. Mitochondrial OxPhos is under dual genetic control, therefore genetic variation in both mitochondrial and nuclear genes and/or genetic interactions between nuclear and mitochondrial alleles (intergenomic epistasis) could be responsible for the observed variability in mitochondrial function . Previous studies by Ballard and co-workers have provided empirical evidence that variation in the mitochondrial genome influence multiple aspects of respiration in wild-caught D. simulans flies [28, 29]. However, much less is known about the effects of variation in nuclear genes on mitochondrial respiration, despite the fact that mostly nuclear genes are involved in mitochondrial metabolism. For example, while both nuclear and mitochondrial genes encode the respiration subunits, their transcription rely on nuclear-encoded factors. Some of these factors are directed to the mitochondria, where they control the transcription of mitochondrial DNA (mtDNA). Others act on nuclear genes required for the assembly and function of the respiratory chain . Also, it is well established that to adjust the rate of ATP production to both short term and long term changes in cellular energy demand, mitochondrial respiration is subject to complex regulation via reversible phosphorylation of OxPhos enzyme complexes . Additionally, a growing body of evidence points to a critical role for second messenger-mediated signal transduction mechanisms in the regulation of mitochondrial OxPhos . Hence, it is plausible that allelic differences in genes involved in these mechanisms may affect mitochondrial function. D. melanogaster is also particularly amenable for studying the nuclear-encoded genomic control of naturally occurring variation in mitochondrial function since previous population studies have shown that the level of naturally occurring variation in the mtDNA of D. melanogaster is low compared to other Drosophila species [33, 34]. Western hemisphere populations of D. melanogaster have been reported to be the least diverse with a single dominant haplogroup , suggesting that nuclear-encoded genes might explain some of the variation for mitochondrial respiration traits among the DGRP lines.
The 40 DGRP lines were previously quantified for transcript abundance  and their nuclear genomes have been sequenced . This provided us with the opportunity to perform genome-wide association (GWA) and quantitative trait transcript (QTT) mappings to identify nuclear-encoded genes and molecular networks responsible for the control of naturally occurring variation in mitochondrial respiration. Using these approaches, we identified sls as a transcription regulator of mitochondrial respiration in D. melanogaster. The product of sls is a protein with homology to the NH2-terminal half of vertebrate titin . As in mammals, Drosophila titin is a component of the muscle sarcomere and is required for both muscle and chromosome structure and elasticity . Our results thus implicate a structural protein as a novel factor contributing to variation in individual mitochondrial respiration.
Results and discussion
Natural variation in mitochondrial respiration and efficiency among D. melanogaster lines
Analysis of Variance of the mitochondrial traits for the 40 DGRP core lines
σ 2 c
State 3 respiration rate
Line × Sex
State 4 respiration rate
Line × Sex
Line × Sex
The sex-related differences in mitochondrial function observed in our study are consistent with the well-recognized differences between males and females in the control of substrate metabolism and energy homeostasis that occur across different species . Also consistent with previous work is our finding that females have greater mitochondrial function than males. For example, Ballard et al.  showed higher mitochondrial efficiency in female D. simulans flies under similar mitochondrial respiration conditions used in our study. Furthermore, studies in mammalian models reported that female rodents had higher mitochondrial oxidative capacity and efficiency for substrate oxidation across several tissues [39–43]. The mechanisms underlying the sexual dimorphism in mitochondrial bioenergetic traits are not known, but the way evolution selects and optimizes certain genes for each sex has been indicated as a potential explanation . Throughout evolution, genes from the mitochondrial genome and the X chromosome spend relatively more time under selection in females due to their asymmetric inheritance [44–46] and are therefore expected to be better optimized to function in females than in males . Since females usually engage in more energetically demanding behaviors than males to attain reproductive success, it has been proposed that sexual differences may have arisen as an evolutionary adaptation to such differences in energetic demands .
Variation in mitochondrial respiration can be influenced by differences in mitochondrial density. To address this issue, we measured the activity of the marker enzyme citrate synthase (CS) in a panel of eight of the 40 inbred wild-type lines. The eight lines were selected to represent the range of variability in mitochondrial respiration rates and coupling efficiency seen in our sample. We measured CS activity in whole-fly homogenates and isolated mitochondria and calculated the mitochondrial protein density from the ratio between the CS activity of the whole-fly homogenates and that of the isolated mitochondria as described in . Only one line was significantly different from the others in mitochondrial density (see Additional file 1). Also, there was no correlation between mitochondrial density and respiration rates or P:O ratio (Additional file 1), indicating that the variability in mitochondrial function among the DGRP lines is likely independent of the number of mitochondria.
Phenotypic correlations between energy metabolism and life-history traits
Phenotypic correlations between energy metabolism and life-history traits averaged across sexes (A), for females (B), and for males (C)
GWA analysis of mitochondrial respiration and efficiency traits
Multiple regression predictive models (A) and analyses of variance of haplotypes (B)
r2 = 0.666
r2 = 0.686
r2 = 0.744
Source of Variation
σ 2 c
Intracellular cAMP production and signaling are regulated by G-protein coupled receptors (GPCRs), which represent the largest group of integral membrane proteins involved in signal transduction and exert a wide variety of biological functions, including neurotransmission, photoreception, chemoreception, metabolism, and cell differentiation and migration [63, 64]. GPCRs predominantly exert their effects through interaction of their intracellular domains with heterotrimeric G- proteins . Additionally, evidence has emerged in recent years indicating that GPCR signaling involves a complex network of interacting targeting and regulatory proteins that leads to cross-communication between separate signaling units . For example, many GPCRs engage in crosstalk with receptor tyrosine kinases , the most relevant of which is the transactivation of the epidermal growth factor (EGF) receptor that allows GPCRs to initiate the Ras/Raf/MEK/ERK signaling pathway controlling cell proliferation, differentiation, and survival . Interestingly, we found that the majority of the genes associated with state 3 and P:O ratio encode proteins involved in these signaling pathways. These include dopamine receptor 2, tyramine β hydroxylase (which encodes an enzyme catalyzing the last step in the synthesis of the invertebrate neurotransmitter octopamine ), locomotion defects (which encodes a protein that physically binds to the Gα subunit of the heterotrimeric G- proteins ), star (which encodes a transmembrane protein that is a member of the EGFR signaling ), alphabet (which encodes a serine/threonine phosphatase that acts as a negative regulator of the Ras/ERK pathway ), still life (which encodes a protein with Rho guanyl-nucleotide exchange factor activity ), and RhoGEF (see Additional file 2).
Another intriguing finding is the association between an intronic variant in the SNF4/AMP-activated protein kinase gamma subunit and variation in mitochondrial state 4 respiration rates (Additional file 2A). As mentioned above, state 4 in isolated mitochondria is strongly influenced by proton leak. AMP-activated protein kinase (AMPK) is a central sensor of cellular energy status and allocation . As in mammals, Drosophila AMPK is an heterotrimer, with an alpha catalytic, a gamma regulatory, and a beta scaffolding subunits . Drosophila AMPK is also activated by AMP and shares many of the same targets with mammalian AMPK . Interestingly, recent work showed that flies deficient in AMPK are sensitive to starvation, a trait we have shown to be correlated to mitochondrial state 4 . Previous in vitro studies also reported that loss of mitochondrial function and reduced ATP (highly correlated to mitochondrial proton leak) causes AMPK activation in flies . Furthermore, AMPK increases the expression of uncoupling proteins in mammals [71, 72]. Overall these observations suggest that population variation at the SNF4/AMP-activated protein kinase gamma subunit locus may be maintained as part of a mechanism controlling the production of ROS and therefore their signaling activities . Additional data, however, will be needed to confirm this hypothesis.
Together, the above observations indicate that there is great utility in using the DGRP as a primary screen for follow-up testing of mutants of focal genes. Also, a notable result of our GWA study is that none of the nuclear genes encoding the subunits of the ETC enzyme complexes or the components required for the assembly and function of the respiratory chain was depicted by the SNPs that showed statistically significant association with the mitochondrial phenotypes. A growing body of evidence indicates that epistatic interactions between natural genetic variants in the mitochondrial and nuclear genomes affect mitochondrial function per se, as well as fitness and several life-history traits within and across populations [27, 29, 74–77]. Although these previous studies have made a significant contribution towards our understanding of the adaptive evolution of these complex traits, little is still known about the molecular nature of the nuclear-mitochondrial gene combinations. To this end, our results provide a new direction for future research seeking to identify the set of genetic variants involved in these mitonuclear epistatic interactions.
Variation in sls has a mtDNA-independent effect on mitochondrial respiration
Gene expression networks underlying variation in mitochondrial respiration
Based on our results from the correlation network analysis, we hypothesized that the sls d00134 and sls d07587 mutations perturbed the same underlying transcriptional network as the natural variants. To test this idea, we compared the transcript abundance of four of the module 4 QTTs (CG12050, CG2656, CG7834, Bteb2, and CG14291) in homozygous mutant and control flies. Given that sls d07587 is a mutant generated by the insertion of a P-element in the intron 2 of the sls gene (Figure 3A), we also examined the effects of this P-element insertion on two of the sls transcript isoform variants (sls-RA and sls-RP). We found that the expression of both sls isoforms was significantly reduced in the sls d07587 flies (Figure 4C). In addition, consistent with the positive correlation observed in our network analysis, we observed that CG12050, CG2656, and CG7834 had significantly lower expression in both sls d07587 (Figure 4C) and sls d00134 flies (Figure 4D) compared to controls. The molecular function of CG12050 and CG2656 is unknown; however, as mentioned above, CG7834 is predicted to encode a protein with mitochondrial electron transfer flavoprotein (ETF) activity. Across different species, ETFs accept electrons from the FADH2 produced in the first step of the fatty acid β-oxidation and transfer them to the mitochondrial membrane-bound ETF ubiquinone oxidoreductase complex . Thus, our finding suggest that sls might control mitochondrial respiration rates by affecting the respiratory chain .
The present study demonstrates that natural populations of D. melanogaster exhibit genetic variation in mitochondrial respiration and efficiency. The GWA data also suggest that natural variation regulating long-term adaptation of D. melanogaster flight muscle mitochondrial function occurs in nuclear-encoded genes involved in a network of interconnected signaling pathways induced by extracellular stimuli, such as neurotransmitters, to maintain cellular homeostasis. Finally, the integrative genomic approach used in our study allowed us to identify sls, with homology to the human Titin (TTN) gene, as a novel hub gene responsible for the regulation of mitochondrial respiration in muscle sarcomere and to provide evidence that sls might act via the ETF ubiquinone oxidoreductase complex.
The 40 unrelated wild-derived D. melanogaster inbred lines used in this study are a subset of the sequenced DGRP lines, which were established from a sample of isofemale lines collected in the Raleigh Farmer’s Market (North Carolina) and inbred to near-homozygosity by 20 generations of full-sib mating . The sls d00134 and sls d07587 stocks were obtained from the Harvard Exelixis Stock collection (https://drosophila.med.harvard.edu/) and the w 1118 (stock no: 6326) co-isogenic control line from the Bloomington Stock Center (http://flystocks.bio.indiana.edu). Each stock was maintained at constant parental density for at least two generations to minimize environmental effects. To control for larval density, we allowed the parents of the experimental flies to mate for 3 hours to generate egg collections on apple juice/agar medium in laying plates. After 24 hours, groups of 100 first-instar larvae were picked from the surface of the medium and put into replicate vials. To minimize the influence of genetic variation in reproduction on energy metabolism, all the phenotypic assays were performed on virgin flies that were randomly collected from the replicate vials for each line under brief CO2 exposure. For mitochondrial function assays, seven replicate vials per line were used, with each vial containing 20 single-sexed individuals aged 3–5 days. All lines were tested over a 2-year period and the lines and replicate vials were assayed in random order. Flies were reared in vials containing 10 ml of standard cornmeal, agar, molasses, and yeast medium, at a constant temperature of 25°C, relative humidity, and 12hr/12hr light/dark cycle.
Mitochondrial respiration rate assay
Mitochondria were isolated from the thorax of the flies as described previously , with minor modification. All mitochondrial isolation steps were performed on ice. Live flies were chilled briefly on ice and thoraces were separated from the heads and abdomens. Isolated thoraces were placed into 200μl of ice-cold isolation buffer [250 mM sucrose, 5 mM Tris–HCl, 2 mM EDTA, 1% (w/v) bovine serum albumin (BSA), pH 7.4 at 4°C; ) supplemented with protease inhibitors (leupeptin 1mg/ml, aprotinin 1mg/ml and pepstatin 1mg/ml) in a 1.5 ml Eppendorf tube. The samples were pounded gently 126 times over a 2 minute period, using a motorized micromortar. Mashed flies were filtered through a 5 micron nylon mesh, and the volume was raised to 400μl by washing the nylon membrane with additional isolation buffer. After a cycle of low-speed centrifugation followed by centrifugation of the filtered solution for 10 min at 3000 g at 4°C, the pellet was re-suspended in 100μl of isolation buffer. Protein concentrations in the mitochondrial fractions were determined using a Lowry assay.
Using freshly isolated mitochondria, mitochondrial respiration assays were performed using a polarographic oxygen sensor (Oroboros oxygraph, OROBOROS® INSTRUMENTS, Innsbruck, Austria) with 0.2 mg/ml of freshly isolated mitochondria incubated in respiration medium (120mM KCl, 5mM KH2PO4, 3mM Hepes, 1mM EDTA, 1mM MgCl2, and 0.2% BSA, pH 7.2; ). Oxygen consumption rates were measured at 25°C . As implemented by , we measured state 3 and state 4 respiration rates using the NAD+-linked substrates pyruvate 5mM/proline 5mM to deliver electrons into mitochondrial complex I. NAD+-linked substrates were added to the chamber and allowed to equilibrate for 1 min, followed by the addition of ADP at a concentration of 400μM to elicit ADP-dependent state 3. This was followed by the determination of the state 4 respiration rate, once all the added ADP had been exhausted and a steady state is reached . P:O ratio, e.g. the relationship between ATP synthesis and oxygen consumption, was calculated as the amount of ADP consumed per oxygen being reduced during state 3.
All assays were performed within three hours of mitochondrial isolation. Data was analyzed using the software DatLab Version 126.96.36.199.
Quantitative genetic analyses
All statistical analyses were performed using SAS version 9.1. We used a mixed model ANOVA to partition variation in each trait among the inbred lines according to the model, y = Âµ + L + S + LxS + ε, where μ is the overall mean, L and S are the main effects of Line (Random) and Sex (Fixed), LxS is the random effect of sex-by-line interaction, and ε is the within-vial error variance. Pearson phenotypic correlations among traits were calculated by SAS PROC CORR using pooled data and data stratified by sex.
The line mean of each mitochondrial parameter was associated with all segregating sites in the DGRP present in four or more DGRP lines, and having sequence coverage levels greater than two and less than thirty . We used the ANOVA model y = Âµ + M + S + M × S + L(M) + ε to evaluate each segregating site, where M is the effect of SNP (marker) genotype, L is line, and S is sex. Genotype-phenotype associations were also performed for males and females separately using the reduced model y = Âµ + M + ε. We calculated the standardized effect size (a/σ G ) as one-half the difference between marker classes divided by the overall genotypic standard deviation . We used the r2 measure to compute linkage disequilibrium among significant markers .
To estimate the amount of genetic variance explained by the SNPs, we applied multiple regression models using gene-centered forward selection. We chose SNPs for the model that were highly significant and not in strong LD with each other (i.e., P < 10-8 for r2 between SNPs). We imputed SNP genotypes for markers with missing data. We fitted SNPs to the model, beginning with the most significant marker, until the r2 for variance was maximal. We identified haplotypes among replicate line means and analyzed the data for sexes combined and sexes separate using the model y = Âµ + H + L(H) + ε, where H is haplotype and L is line. We estimated the phenotypic variance explained as σH2/(σH2 + σL2 + σE2), where σH2 is the among-haplotype variance component, σL2 is the among-line variance component, and σE2 is the error component.
Transcript-phenotype associations and transcriptional networks
The gene expression analysis in the 40 DGRP lines has been described previously . Associations between genetically variable transcripts with each mitochondrial respiration trait were assessed by regression analysis as previously described . Briefly, regression models of the form y = Âµ + S + T + S × T + ε, where S is sex, T is the mitochondrial trait, and ε is the error term, were computed for each probe set.
The genetic correlations between all QTTs associated with each trait at P < 0.01 were computed after removing the correlation between these transcripts and the trait. This was achieved by fitting the model y = μ + E + S + E × S + ε (Y is the trait, E is the covariate median log2 expression level, S is the sex effect and ε the residual error) and extracting the residuals to compute pair-wise transcript correlations for module construction . Modules of transcripts associated with each trait with coordinated patterns of expression across the 40 lines were then quantified as described previously .
We isolated total RNA using the TriPure RNA isolation kit (Roche). Isolated RNA was then used to make cDNA, using the First Strand Synthesis kit (Invitrogen). We performed RT-qPCR using a SYBR Green Master mix and 50 ng total of cDNA per reaction and run in a Stratagene Mx3000P® qPCR machine. The primers used for qRT-PCR are listed in Additional file 5. Statistical significance was determined by the two-tailed Student’s t test.
Drosophila Genetic Reference Panel
Quantitative Trait Transcript
Electron Transport Chain
Reactive Oxygen Species
Nicotinamide Adenine Dinucleotide
Flavin Adenine Dinucleotide
CAMP-Dependent Protein Kinase
G-Protein Coupled Receptors
Epidermal Growth Factor
AMP-Activated Protein Kinase
Electron Transfer Flavoprotein.
We thank Michelle Moses Chambers for help with Drosophila husbandry procedures. We also thank Dr. David Rand and an anonymous reviewer for proving insightful comments on the manuscript. We are enormously grateful to Dr. Carlos Krumdieck for designing and making available the motorized micro-mortar used for the mitochondrial assays. This study was supported by a BARB Core/Diabetes Research Training Center NIDDK Grant P60 DK079626, Diabetes Research Training Center Pilot Feasibility grant to DRM, and NIH Grants R01 GM45146 to TFCM and R01 DK084219 to MD.
- Saraste M: Oxidative phosphorylation at the fin de siecle. Science. 1999, 283: 1488-1493. 10.1126/science.283.5407.1488.View ArticlePubMed
- Duchen MR: Contributions of mitochondria to animal physiology, from homeostatic sensor to calcium signalling and cell death. J Physiol. 1999, 516 (Pt 1): 1-17.PubMed CentralView ArticlePubMed
- Butow RA, Avadhani NG: Mitochondrial signaling, the retrograde response. Mol Cell. 2004, 14: 1-15. 10.1016/S1097-2765(04)00179-0.View ArticlePubMed
- Thannickal VJ, Fanburg BL: Reactive oxygen species in cell signaling. Am J Physiol Lung Cell Mol Physiol. 2000, 279: L1005-L1028.PubMed
- Gao L, Laude K, Cai H: Mitochondrial pathophysiology, reactive oxygen species, and cardiovascular diseases. Vet Clin North Am Small Anim Pract. 2008, 38: 137-155. 10.1016/j.cvsm.2007.10.004. viPubMed CentralView ArticlePubMed
- Harper ME, Green K, Brand MD: The efficiency of cellular energy transduction and its implications for obesity. Annu Rev Nutr. 2008, 28: 13-33. 10.1146/annurev.nutr.28.061807.155357.View ArticlePubMed
- Loomis W, Lipmann F: Reversible inhibition of the coupling between phosphorylation and oxidation. J Biol Chem. 1948, 173: 807-PubMed
- Nobes CD, Brown GC, Olive PN, Brand MD: Non-ohmic proton conductance of the mitochondrial inner membrane in hepatocytes. J Biol Chem. 1990, 265: 12903-12909.PubMed
- Skulachev VP: Uncoupling, new approaches to an old problem of bioenergetics. Biochim Biophys Acta. 1998, 1363: 100-124. 10.1016/S0005-2728(97)00091-1.View ArticlePubMed
- Brand MD, Turner N, Ocloo A, Else PL, Hulbert AJ: Proton conductance and fatty acyl composition of liver mitochondria correlates with body mass in birds. Biochem J. 2003, 376: 741-748. 10.1042/BJ20030984.PubMed CentralView ArticlePubMed
- Saccone C, Lanave C, De GA: Metazoan OXPHOS gene families, evolutionary forces at the level of mitochondrial and nuclear genomes. Biochim Biophys Acta. 2006, 1757: 1171-1178. 10.1016/j.bbabio.2006.04.021.View ArticlePubMed
- Wallace DC, Fan W: The pathophysiology of mitochondrial disease as modeled in the mouse. Genes Dev. 2009, 23: 1714-1736. 10.1101/gad.1784909.PubMed CentralView ArticlePubMed
- Passarino G, Rose G, Bellizzi D: Mitochondrial function, mitochondrial DNA and ageing, a reappraisal. Biogerontology. 2010, 11: 575-588. 10.1007/s10522-010-9294-3.View ArticlePubMed
- Raule N, Sevini F, Santoro A, Altilia S, Franceschi C: Association studies on human mitochondrial DNA, methodological aspects and results in the most common age-related diseases. Mitochondrion. 2007, 7: 29-38. 10.1016/j.mito.2006.11.013.View ArticlePubMed
- Mackay TF, Stone EA, Ayroles JF: The genetics of quantitative traits, challenges and prospects. Nat Rev Genet. 2009, 10: 565-577.View ArticlePubMed
- Clary DO, Wolstenholme DR: The mitochondrial DNA molecular of Drosophila yakuba, nucleotide sequence, gene organization, and genetic code. J Mol Evol. 1985, 22: 252-271. 10.1007/BF02099755.View ArticlePubMed
- Watanabe MI, Williams CM: Mitochondria in the flight muscles of insects. I. Chemical composition and enzymatic content. J Gen Physiol. 1951, 34: 675-689. 10.1085/jgp.34.5.675.PubMed CentralView ArticlePubMed
- Gregg CT, Heisler CR, Remmert LF: Oxidative phosphorylation and respiratory control in housefly mitochondria. Biochim Biophys Acta. 1960, 45: 561-570.View ArticlePubMed
- Van den Bergh S: Insect mitochondria. Methods in enzymology. Edited by: Estabrook RW, Pullman ME. 1967, Academic, New York, 117-122.
- Miwa S, St-Pierre J, Partridge L, Brand MD: Superoxide and hydrogen peroxide production by Drosophila mitochondria. Free Radic Biol Med. 2003, 35: 938-948. 10.1016/S0891-5849(03)00464-7.View ArticlePubMed
- Fridell YW, Sanchez-Blanco A, Silvia BA, Helfand SL: Functional characterization of a Drosophila mitochondrial uncoupling protein. J Bioenerg Biomembr. 2004, 36: 219-228.View ArticlePubMed
- Leopold P, Perrimon N: Drosophila and the genetics of the internal milieu. Nature. 2007, 450: 186-188. 10.1038/nature06286.View ArticlePubMed
- Schlegel A, Stainier DY: Lessons from "lower" organisms, what worms, flies, and zebrafish can teach us about human energy metabolism. PLoS Genet. 2007, 3: e199-10.1371/journal.pgen.0030199.PubMed CentralView ArticlePubMed
- De Luca M, Chambers MM, Casazza K, Lok KH, Hunter GR, Gower BA, et al: Genetic variation in a member of the laminin gene family affects variation in body composition in Drosophila and humans. BMC Genet. 2008, 9: 52-PubMed CentralView ArticlePubMed
- De Luca M, Klimentidis YC, Casazza K, Chambers MM, Cho R, Harbison ST, et al: A conserved role for syndecan family members in the regulation of whole-body energy metabolism. PLoS One. 2010, 5: e11286-10.1371/journal.pone.0011286.PubMed CentralView ArticlePubMed
- Mackay TF, Richards S, Stone EA, Barbadilla A, Ayroles JF, Zhu D, et al: The Drosophila melanogaster genetic reference panel. Nature. 2012, 482: 173-178. 10.1038/nature10811.PubMed CentralView ArticlePubMed
- Dowling DK, Friberg U, Lindell J: Evolutionary implications of non-neutral mitochondrial genetic variation. Trends Ecol Evol. 2008, 23: 546-554. 10.1016/j.tree.2008.05.011.View ArticlePubMed
- Katewa SD, Ballard JW: Sympatric Drosophila simulans flies with distinct mtDNA show difference in mitochondrial respiration and electron transport. Insect Biochem Mol Biol. 2007, 37: 213-222. 10.1016/j.ibmb.2006.11.002.View ArticlePubMed
- Ballard JW, Melvin RG, Katewa SD, Maas K: Mitochondrial DNA variation is associated with measurable differences in life-history traits and mitochondrial metabolism in Drosophila simulans. Evolution. 2007, 61: 1735-1747. 10.1111/j.1558-5646.2007.00133.x.View ArticlePubMed
- Goffart S, Wiesner RJ: Regulation and co-ordination of nuclear gene expression during mitochondrial biogenesis. Exp Physiol. 2003, 88: 33-40. 10.1113/eph8802500.View ArticlePubMed
- Pagliarini DJ, Dixon JE: Mitochondrial modulation, reversible phosphorylation takes center stage?. Trends Biochem Sci. 2006, 31: 26-34. 10.1016/j.tibs.2005.11.005.View ArticlePubMed
- Boneh A: Regulation of mitochondrial oxidative phosphorylation by second messenger-mediated signal transduction mechanisms. Cell Mol Life Sci. 2006, 63: 1236-1248. 10.1007/s00018-005-5585-2.View ArticlePubMed
- Ballard JW, Kreitman M: Unraveling selection in the mitochondrial genome of Drosophila. Genetics. 1994, 138: 757-772.PubMed CentralPubMed
- Solignac M: Mitochondrial DNA in the Drosophila melanogaster complex. Genetica. 2004, 120: 41-50.View ArticlePubMed
- Ayroles JF, Carbone MA, Stone EA, Jordan KW, Lyman RF, Magwire MM, et al: Systems genetics of complex traits in Drosophila melanogaster. Nat Genet. 2009, 41: 299-307. 10.1038/ng.332.PubMed CentralView ArticlePubMed
- Machado C, Andrew DJ: D-Titin, a giant protein with dual roles in chromosomes and muscles. J Cell Biol. 2000, 151: 639-652. 10.1083/jcb.151.3.639.PubMed CentralView ArticlePubMed
- Cortright RN, Koves TR: Sex differences in substrate metabolism and energy homeostasis. Can J Appl Physiol. 2000, 25: 288-311. 10.1139/h00-023.View ArticlePubMed
- Ballard JW, Melvin RG, Miller JT, Katewa SD: Sex differences in survival and mitochondrial bioenergetics during aging in Drosophila. Aging Cell. 2007, 6: 699-708. 10.1111/j.1474-9726.2007.00331.x.View ArticlePubMed
- Valle A, Guevara R, Garcia-Palmer FJ, Roca P, Oliver J: Sexual dimorphism in liver mitochondrial oxidative capacity is conserved under caloric restriction conditions. Am J Physiol Cell Physiol. 2007, 293: C1302-C1308. 10.1152/ajpcell.00203.2007.View ArticlePubMed
- Justo R, Boada J, Frontera M, Oliver J, Bermudez J, Gianotti M: Gender dimorphism in rat liver mitochondrial oxidative metabolism and biogenesis. Am J Physiol Cell Physiol. 2005, 289: C372-C378. 10.1152/ajpcell.00035.2005.View ArticlePubMed
- Justo R, Frontera M, Pujol E, Rodriguez-Cuenca S, Llado I, Garcia-Palmer FJ, et al: Gender-related differences in morphology and thermogenic capacity of brown adipose tissue mitochondrial subpopulations. Life Sci. 2005, 76: 1147-1158. 10.1016/j.lfs.2004.08.019.View ArticlePubMed
- Rodriguez-Cuenca S, Pujol E, Justo R, Frontera M, Oliver J, Gianotti M, et al: Sex-dependent thermogenesis, differences in mitochondrial morphology and function, and adrenergic response in brown adipose tissue. J Biol Chem. 2002, 277: 42958-42963. 10.1074/jbc.M207229200.View ArticlePubMed
- Guevara R, Santandreu FM, Valle A, Gianotti M, Oliver J, Roca P: Sex-dependent differences in aged rat brain mitochondrial function and oxidative stress. Free Radic Biol Med. 2009, 46: 169-175. 10.1016/j.freeradbiomed.2008.09.035.View ArticlePubMed
- Tower J: Sex-specific regulation of aging and apoptosis. Mech Ageing Dev. 2006, 127: 705-718. 10.1016/j.mad.2006.05.001.View ArticlePubMed
- Giles RE, Blanc H, Cann HM, Wallace DC: Maternal inheritance of human mitochondrial DNA. Proc Natl Acad Sci USA. 1980, 77: 6715-6719. 10.1073/pnas.77.11.6715.PubMed CentralView ArticlePubMed
- Driver C, Tawadros N: Cytoplasmic genomes that confer additional longevity in Drosophila melanogaster. Biogerontology. 2000, 1: 255-260. 10.1023/A:1010038314910.View ArticlePubMed
- Rogowitz GL, Chappell MA: Energy metabolism of eucalyptus-boring beetles at rest and during locomotion, gender makes a difference. J Exp Biol. 2000, 203: 1131-1139.PubMed
- Magwere T, Pamplona R, Miwa S, Martinez-Diaz P, Portero-Otin M, Brand MD, et al: Flight activity, mortality rates, and lipoxidative damage in Drosophila. J Gerontol A Biol Sci Med Sci. 2006, 61: 136-145. 10.1093/gerona/61.2.136.View ArticlePubMed
- Mogensen M, Sahlin K: Mitochondrial efficiency in rat skeletal muscle, influence of respiration rate, substrate and muscle type. Acta Physiol Scand. 2005, 185: 229-236. 10.1111/j.1365-201X.2005.01488.x.View ArticlePubMed
- Jumbo-Lucioni P, Ayroles JF, Chambers MM, Jordan KW, Leips J, Mackay TF, et al: Systems genetics analysis of body weight and energy metabolism traits in Drosophila melanogaster. BMC Genomics. 2010, 11: 297-10.1186/1471-2164-11-297.PubMed CentralView ArticlePubMed
- Ockner R: Integration of metabolism, energetics, and signal transduction, unifying foundations in cell growth and death, cancer, atherosclerosis, and Alzheimer disease. 2004, Klumer Academic/Plenum Publishers, New York
- Dubessay P, Garreau-Balandier I, Jarrousse AS, Fleuriet A, Sion B, Debise R, et al: Aging impact on biochemical activities and gene expression of Drosophila melanogaster mitochondria. Biochimie. 2007, 89: 988-1001. 10.1016/j.biochi.2007.03.018.View ArticlePubMed
- Brown GC: Control of respiration and ATP synthesis in mammalian mitochondria and cells. Biochem J. 1992, 284 (Pt 1): 1-13.PubMed CentralView ArticlePubMed
- Brookes PS: Mitochondrial H(+) leak and ROS generation, an odd couple. Free Radic Biol Med. 2005, 38: 12-23. 10.1016/j.freeradbiomed.2004.10.016.View ArticlePubMed
- Hoehn KL, Salmon AB, Hohnen-Behrens C, Turner N, Hoy AJ, Maghzal GJ, et al: Insulin resistance is a cellular antioxidant defense mechanism. Proc Natl Acad Sci USA. 2009, 106: 17787-17792. 10.1073/pnas.0902380106.PubMed CentralView ArticlePubMed
- Anderson EJ, Lustig ME, Boyle KE, Woodlief TL, Kane DA, Lin CT, et al: Mitochondrial H2O2 emission and cellular redox state link excess fat intake to insulin resistance in both rodents and humans. J Clin Invest. 2009, 119: 573-581. 10.1172/JCI37048.PubMed CentralView ArticlePubMed
- Krause C, Wolf C, Hemphala J, Samakovlis C, Schuh R: Distinct functions of the leucine-rich repeat transmembrane proteins capricious and tartan in the Drosophila tracheal morphogenesis. Dev Biol. 2006, 296: 253-264. 10.1016/j.ydbio.2006.04.462.View ArticlePubMed
- Drysdale RA, Crosby MA: FlyBase, genes and gene models. Nucleic Acids Res. 2005, 33: D390-D395.PubMed CentralView ArticlePubMed
- Day JP, Dow JA, Houslay MD, Davies SA: Cyclic nucleotide phosphodiesterases in Drosophila melanogaster. Biochem J. 2005, 388: 333-342. 10.1042/BJ20050057.PubMed CentralView ArticlePubMed
- Huttemann M, Lee I, Samavati L, Yu H, Doan JW: Regulation of mitochondrial oxidative phosphorylation through cell signaling. Biochim Biophys Acta. 2007, 1773: 1701-1720. 10.1016/j.bbamcr.2007.10.001.View ArticlePubMed
- Leadsham JE, Gourlay CW: cAMP/PKA signaling balances respiratory activity with mitochondria dependent apoptosis via transcriptional regulation. BMC Cell Biol. 2010, 11: 92-10.1186/1471-2121-11-92.PubMed CentralView ArticlePubMed
- Acin-Perez R, Salazar E, Kamenetsky M, Buck J, Levin LR, Manfredi G: Cyclic AMP produced inside mitochondria regulates oxidative phosphorylation. Cell Metab. 2009, 9: 265-276. 10.1016/j.cmet.2009.01.012.PubMed CentralView ArticlePubMed
- Vassilatis DK, Hohmann JG, Zeng H, Li F, Ranchalis JE, Mortrud MT, et al: The G protein-coupled receptor repertoires of human and mouse. Proc Natl Acad Sci USA. 2003, 100: 4903-4908. 10.1073/pnas.0230374100.PubMed CentralView ArticlePubMed
- Broeck JV: Insect G protein-coupled receptors and signal transduction. Arch Insect Biochem Physiol. 2001, 48: 1-12. 10.1002/arch.1054.View ArticlePubMed
- Kristiansen K: Molecular mechanisms of ligand binding, signaling, and regulation within the superfamily of G-protein-coupled receptors, molecular modeling and mutagenesis approaches to receptor structure and function. Pharmacol Ther. 2004, 103: 21-80. 10.1016/j.pharmthera.2004.05.002.View ArticlePubMed
- Dumaz N, Marais R: Integrating signals between cAMP and the RAS/RAF/MEK/ERK signalling pathways. Based on the anniversary prize of the Gesellschaft fur Biochemie und Molekularbiologie Lecture delivered on 5 July 2003 at the Special FEBS Meeting in Brussels. FEBS J. 2005, 272: 3491-3504. 10.1111/j.1742-4658.2005.04763.x.View ArticlePubMed
- Luttrell DK, Luttrell LM: Not so strange bedfellows, G-protein-coupled receptors and Src family kinases. Oncogene. 2004, 23: 7969-7978. 10.1038/sj.onc.1208162.View ArticlePubMed
- Johnson EC, Kazgan N, Bretz CA, Forsberg LJ, Hector CE, Worthen RJ, et al: Altered metabolism and persistent starvation behaviors caused by reduced AMPK function in Drosophila. PLoS One. 2010, 5: e12799-10.1371/journal.pone.0012799.PubMed CentralView ArticlePubMed
- Pan DA, Hardie DG: A homologue of AMP-activated protein kinase in Drosophila melanogaster is sensitive to AMP and is activated by ATP depletion. Biochem J. 2002, 367: 179-186. 10.1042/BJ20020703.PubMed CentralView ArticlePubMed
- Mandal S, Guptan P, Owusu-Ansah E, Banerjee U: Mitochondrial regulation of cell cycle progression during development as revealed by the tenured mutation in Drosophila. Dev Cell. 2005, 9: 843-854. 10.1016/j.devcel.2005.11.006.View ArticlePubMed
- Foretz M, Ancellin N, Andreelli F, Saintillan Y, Grondin P, Kahn A, et al: Short-term overexpression of a constitutively active form of AMP-activated protein kinase in the liver leads to mild hypoglycemia and fatty liver. Diabetes. 2005, 54: 1331-1339. 10.2337/diabetes.54.5.1331.View ArticlePubMed
- Xie Z, Zhang J, Wu J, Viollet B, Zou MH: Upregulation of mitochondrial uncoupling protein-2 by the AMP-activated protein kinase in endothelial cells attenuates oxidative stress in diabetes. Diabetes. 2008, 57: 3222-3230. 10.2337/db08-0610.PubMed CentralView ArticlePubMed
- Mittler R, Vanderauwera S, Suzuki N, Miller G, Tognetti VB, Vandepoele K, et al: ROS signaling, the new wave?. Trends Plant Sci. 2011, 16: 300-309. 10.1016/j.tplants.2011.03.007.View ArticlePubMed
- Rand DM, Clark AG, Kann LM: Sexually antagonistic cytonuclear fitness interactions in Drosophila melanogaster. Genetics. 2001, 159: 173-187.PubMed CentralPubMed
- Montooth KL, Meiklejohn CD, Abt DN, Rand DM: Mitochondrial-nuclear epistasis affects fitness within species but does not contribute to fixed incompatibilities between species of Drosophila. Evolution. 2010, 64: 3364-3379. 10.1111/j.1558-5646.2010.01077.x.PubMed CentralView ArticlePubMed
- Arnqvist G, Dowling DK, Eady P, Gay L, Tregenza T, Tuda M, et al: Genetic architecture of metabolic rate, environment specific epistasis between mitochondrial and nuclear genes in an insect. Evolution. 2010, 64: 3354-3363. 10.1111/j.1558-5646.2010.01135.x.View ArticlePubMed
- Ellison CK, Burton RS: Disruption of mitochondrial function in interpopulation hybrids of Tigriopus californicus. Evolution. 2006, 60: 1382-1391.View ArticlePubMed
- Burkart C, Qiu F, Brendel S, Benes V, Haag P, Labeit S, et al: Modular proteins from the Drosophila sallimus (sls) gene and their expression in muscles with different extensibility. J Mol Biol. 2007, 367: 953-969. 10.1016/j.jmb.2007.01.059.View ArticlePubMed
- Thibault ST, Singer MA, Miyazaki WY, Milash B, Dompe NA, Singh CM, et al: A complementary transposon tool kit for Drosophila melanogaster using P and piggyBac. Nat Genet. 2004, 36: 283-287. 10.1038/ng1314.View ArticlePubMed
- Voy BH: Systems genetics, a powerful approach for gene-environment interactions. J Nutr. 2011, 141: 515-519. 10.3945/jn.110.130401.View ArticlePubMed
- Takahashi M, Chesley A, Freyssenet D, Hood DA: Contractile activity-induced adaptations in the mitochondrial protein import system. Am J Physiol. 1998, 274: C1380-C1387.PubMed
- Schonbauer C, Distler J, Jahrling N, Radolf M, Dodt HU, Frasch M, et al: Spalt mediates an evolutionarily conserved switch to fibrillar muscle fate in insects. Nature. 2011, 479: 406-409. 10.1038/nature10559.View ArticlePubMed
- Watmough NJ, Frerman FE: The electron transfer flavoprotein, ubiquinone oxidoreductases. Biochim Biophys Acta. 2010, 1797: 1910-1916. 10.1016/j.bbabio.2010.10.007.View ArticlePubMed
- Brand MD, Hafner RP, Brown GC: Control of respiration in non-phosphorylating mitochondria is shared between the proton leak and the respiratory chain. Biochem J. 1988, 255: 535-539.PubMed CentralPubMed
- Ferguson M, Mockett RJ, Shen Y, Orr WC, Sohal RS: Age-associated decline in mitochondrial respiration and electron transport in Drosophila melanogaster. Biochem J. 2005, 390: 501-511. 10.1042/BJ20042130.PubMed CentralView ArticlePubMed
- Sacktor B, Sanborn R: The effect of temperature on oxidative phosphorylation with insect flight muscle mitochondria. J Biophys Biochem Cytol. 1956, 2: 105-107.PubMed CentralView ArticlePubMed
- Affourtit C, Quinlan CL, Brand MD: Measurement of proton leak and electron leak in isolated mitochondria. Methods Mol Biol. 2012, 810: 165-182. 10.1007/978-1-61779-382-0_11.View ArticlePubMed
- Falconer DS, Mackay TFC: Introduction to quantitative genetics. 1996, Pearson Education Group (Longman Group Ltd.), Essex, England, 4
- Hill WG, Robertson A: The effects of inbreeding at loci with heterozygote advantage. Genetics. 1968, 60: 615-628.PubMed CentralPubMed
- Stone EA, Ayroles JF: Modulated modularity clustering as an exploratory tool for functional genomic inference. PLoS Genet. 2009, 5: e1000479-10.1371/journal.pgen.1000479.PubMed CentralView ArticlePubMed
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.