Low-level mitochondrial heteroplasmy modulates dna replication, glucose metabolism and lifespan in mice

Low-level mitochondrial heteroplasmy modulates dna replication, glucose metabolism and lifespan in mice

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ABSTRACT Mutations in mitochondrial DNA (mtDNA) lead to heteroplasmy, i.e., the intracellular coexistence of wild-type and mutant mtDNA strands, which impact a wide spectrum of diseases but


also physiological processes, including endurance exercise performance in athletes. However, the phenotypic consequences of limited levels of naturally arising heteroplasmy have not been


experimentally studied to date. We hence generated a conplastic mouse strain carrying the mitochondrial genome of an _AKR/J_ mouse strain (B6-mtAKR) in a _C57BL/6 J_ nuclear genomic


background, leading to >20% heteroplasmy in the origin of light-strand DNA replication (OriL). These conplastic mice demonstrate a shorter lifespan as well as dysregulation of multiple


metabolic pathways, culminating in impaired glucose metabolism, compared to that of wild-type _C57BL/6 J_ mice carrying lower levels of heteroplasmy. Our results indicate that


physiologically relevant differences in mtDNA heteroplasmy levels at a single, functionally important site impair the metabolic health and lifespan in mice. SIMILAR CONTENT BEING VIEWED BY


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Mitochondria play a critical role in maintaining cellular activities by generating energy in the form of adenosine triphosphate (ATP)1. Additionally, mitochondria function as a signaling


platform, e.g., mitochondrial reactive oxygen species control a wide range of biological processes, including epigenetics, autophagy, and immune responses2. Since mitochondria are involved


in such critical cellular activities, mitochondrial dysfunction has been linked to various degenerative and metabolic conditions (e.g., Alzheimer’s disease and diabetes), cancer, and aging


in humans, as has been supported by experimental evidence3,4,5,6. Mitochondria carry their own mitochondrial DNA (mtDNA), which encodes codes 13 OXPHOS complex genes, two ribosomal RNA


genes, and 22 transfer RNA genes7. The mode of inheritance of mtDNA is maternal, and hundreds to thousands of mtDNA copies exist in a cell1. Mutations in mtDNA have been categorized into


three groups: deleterious mutations, somatic mutations and adaptive polymorphisms1. Deleterious mutations result in severe mitochondrial dysfunction and are causal for maternally inherited


mitochondrial disease such as Leber’s hereditary optic neuropathy (LHON)8 and mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS)9. Somatic mtDNA mutations


accumulate within various tissues with age, and it has been experimentally shown that increased somatic mtDNA mutations exhibit aging phenotypes in mice10,11. In contrast, adaptive


polymorphisms may be associated with survival under different climatic conditions or nutritional availability1. Conplastic mouse strains are a unique and powerful tool to investigate the


impact of mutations in mtDNA under a wide spectrum of physiological and pathological alterations12, including aging13,14,15. Of note, the study by Kauppila _et al_. investigating the impact


of heteroplasmy on lifespan reported that higher levels of maternally inherited _de novo_ mutations/heteroplasmy lead to severe pathological consequences13. Higher levels of


mutations/heteroplasmy rarely occur naturally, apart from cancers16,17. In contrast, lower levels of maternally inherited heteroplasmy commonly exist18,19, while their phenotypic


consequences have not been experimentally studied to date. We previously generated a series of conplastic mouse strains, which carry distinct and stable mutations over generations in mtDNA


on a _C57BL/6 J_ nuclear genomic background20 and provide a unique opportunity to study the impact of natural variation of mtDNA on various biological and pathological processes. Since the


mtDNA of those strains was previously sequenced using Sanger sequencing, which did not allow us to accurately determine their levels of heteroplasmy, we here performed next-generation


sequencing of the mtDNA of all of our previously constructed conplastic strains and discovered a stable, maternally inherited, and low-level heteroplasmic mutation at nt5172 in the origin of


L-strand replication (Supplementary Table S1). Moreover, the levels of the heteroplasmy varied between the _C57BL/6 J_ and _C57BL/6J-mt__AKR/J_ strains. Using this unique resource, we


studied the impact of natural low-level heteroplasmy on aging, and demonstrated its consequences, including an impact on mtDNA copy number ratio and the regulation of metabolic processes,


which may be causative for a shorter lifespan. RESULTS DEEP-SEQUENCING OF MTDNA PREPARED FROM B6-MTAKR REVEALS THE PRESENCE OF LOW LEVELS OF A HETEROPLASMIC MUTATION AT POSITION 5172 IN THE


ORIL First, we deep-sequenced the mtDNA of a series of conplastic strains that we previously generated20, and identified a strain carrying low levels of heteroplasmy at position 5172 in OriL


(Supplementary Table S1). This particular strain carries the mtDNA of _AKR/J_ (_C57BL/6J-mt__AKR/J_; B6-mtAKR) on a _C57BL/6 J_ (B6) background. Consistent with previously published


data21,22, the adenine-repeat number varies among individuals at this position. Specifically, the majority of mtDNA (approximately 60–70%) carries eleven adenines (“11 A”), while the


remaining percentage exhibits either 9, 10 or more than 11 adenines (9 A, 10 A, 12 A, 13 A). B6-mtAKR mice have higher levels of >11 A heteroplasmy compared to B6 (Fig. 1a, 12 A and 13 A;


_P_ < _0_._0001_ for both, two-way ANOVA). While the levels of the 12 A heteroplasmy at OriL vary individually, overall B6-mtAKR exhibits >20% heteroplasmy in comparison to B6, which


carries approximately 10% heteroplasmy at the same position in different organs and at different ages (Fig. 1b). Interestingly, the heteroplasmy at 5172 is also observed in free-living house


mice (_Mus musculus domesticus_) caught on farms (n = 215, Fig. 1c), and the pattern of heteroplasmy resembles that of B6 (Fig. 1a). This indicates that the patterns observed in inbred


laboratory mice are also present in nature, where they may represent a consequence of mutation pressure and possibly be subject to natural selection. LEVELS OF 12 A HETEROPLASMY AT 5172 IN


THE ORIL NEGATIVELY CORRELATE WITH LIFESPAN To investigate the impact of heteroplasmy at the OriL on murine lifespan and aging-related phenotypes, we conducted a longevity study using a


large cohort of this strain, and B6 control mice. Female B6-mtAKR live significantly shorter than B6 mice (approx. 50 days, _P_ = _0_._0305_, log-rank test), while the lifespan of males does


not differ between strains (Fig. 1d–f, Supplementary Tables S1a–d, and Supplementary Fig. S1a–c). Neither the aging score (i.e., the presence of alopecia, graying hair, body mass reduction,


and kyphosis, as previously described23), the tumor incidence, nor the incidence of ulcerative dermatitis is significantly different between the strains (Supplementary Fig. S1d–f).


Sequencing of genomic DNA derived from blood obtained from moribund female mice (B6; n = 84, B6-mtAKR; n = 61) reveals an inverse correlation between lifespan and higher levels of


heteroplasmy (Fig. 1g, ρ = −0.1881, _P_ = 0.0235, Spearman test). HIGHER 12 A HETEROPLASMY AT 5172 IN THE ORIL REDUCES THE MTDNA/NDNA RATIO, WHILE THE EXPRESSION LEVEL OF THE MTDNA-ENCODED


GENES IS INCREASED Next, we aimed to determine the functional consequence(s) of 12 A heteroplasmy. Since the OriL is essential for mtDNA replication22, the ratio of mtDNA to nuclear genome


copies was investigated by quantifying _mt-Co1_ and _Vdac1_ copies, respectively. We observe an inverse correlation with levels of 12 A heteroplasmy (_ρ_ = −0.4264, _P_ = 0.0025, Spearman


test, Fig. 2a), while the overall ratio is unaltered between B6-mtAKR and B6 at different ages (Fig. 2b). This is likely due to the high variability of 12 A heteroplasmy in individual mice


within each strain. This 12A-correlated phenomenon is also observed for another mitochondrially encoded gene, _mt-Nd5_, again normalized to nuclear _Vdac1_ (Fig. 2c,d). Thus, higher levels


of 12 A heteroplasmy at 5172 correlate with lower mtDNA copy number. On the other hand, the expression of mitochondrial _mt-Co1_ positively correlates with 12 A heteroplasmy (_ρ_ = 0.5646,


_P_ = 0.0033, Spearman test, Fig. 2e), while no significant difference is observed between strains (Fig. 2f). Consistent with the latter observation, the levels of several OXPHOS proteins as


well as those of the nuclear-encoded beta-actin protein are similar between strains (Fig. 2g,h). These findings suggest that while higher levels of 12 A heteroplasmy in the OriL lead to a


reduction of mtDNA copy number, the cells are capable of a compensatory increase in the expression of genes encoded by mtDNA despite its decreased copy number. MITOCHONDRIAL FUNCTION IN


YOUNG MICE CORRELATES TO 12 A HETEROPLASMY IN THE ORIL WHEN NORMALIZED TO MTDNA COPY NUMBER Mitochondrial functional analysis including OXPHOS complex activity and hydrogen peroxide


measurement assays display no significant correlation with 12 A heteroplasmy in the OriL (Supplementary Fig. S2a,b). However, when normalized to the ratio of mtDNA to nDNA copy number, 12 A


heteroplasmy significantly correlates with mitochondrial OXPHOS complex I, IV and V activity (the values of each complex activity were normalized to the individual values of citrate synthase


(CS); complex I (CI/CS) ρ = 0.6214, _P_ = 0.0134; complex IV (CIV/CS) ρ = 0.7321, _P_ = 0.0019; and complex V (CV/CS) ρ = 0.5668, _P_ = 0.0276, Spearman test, Fig. 3a) as well as ROS levels


(ρ = 0.575, _P_ = 0.0249, Spearman test, Fig. 3b). This phenomenon is observed only in young mice (three to six months of age; Fig. 3a,b), while an aged population maintains the trend of


this correlation (approximately 18–20 months of age; Supplementary Fig. S3a,b). IMPAIRED GLUCOSE AND LIPID METABOLISM MAY DETERMINE THE HEALTHSPAN IN B6-MTAKR MICE Mitochondrial metabolism


has a well-defined impact on glucose metabolism24,25, and conversely, increased glucose levels promote systemic aging26. We thus lastly evaluated the putative impact of 12 A heteroplasmy in


the OriL on the metabolic phenotype of both B6-mtAKR and B6 mice. Random-fed plasma glucose levels are higher in 12 A heteroplasmy B6-mtAKR mice than in B6 controls (Fig. 4a). Consistently,


plasma fructosamine concentrations, which reflect the glucose levels over a 2–3 week period prior to measurement, are also increased in states of high 12 A heteroplasmy (Fig. 4a), indicating


a long-term elevation of plasma-glucose in these mice. Moreover, B6-mtAKR consistently display elevated levels in oral glucose tolerance tests (Fig. 4b). Interestingly, no difference was


observed in glucose levels upon fasting or in i.p. glucose tolerance tests (Supplementary Fig. S4a). Since insulin levels in both fasted- and random-fed plasma samples are unaltered, as are


lactate, cholesterol and fasted glucose levels (Supplementary Fig. S4b,c), these data suggest enhanced intestinal glucose uptake, but no insulin resistance in our study. Furthermore,


comparable levels of glycogen storage contrasted by higher activity of pyruvate kinase (PK, indicative for glycolysis) and phosphoenolpyruvate carboxykinase (PEPCK, indicative for


gluconeogenesis) (Fig. 4c) indicate an increase in glucose consumption in B6-mtAKR mice. Higher levels of free fatty acids are also present in B6-mtAKR (Fig. 4c), suggesting a global


reduction of beta-oxidation in these mice. This is supported by our findings of elevated long-chain fatty acids in liver samples of B6-mtAKR (Fig. 4d and Supplementary Fig. S4d), being


consistent with an impaired capacity for mitochondrial metabolism, and in particular beta-oxidation. Thus, mice with higher 12 A heteroplasmy (B6-mtAKR) exhibit skewed glucose and lipid


metabolism, and that may be considered causal for the impaired lifespan of B6-mtAKR mice in comparison to low-heteroplasmy B6 control mice. This is consistent with long-standing published


evidence that mitochondrial mutations, such as the m.3243 A>G mutation that is causal for so-called mitochondrial diabetes mellitus, play a role not only in mitochondrial function, but


also in glucose metabolism, as reviewed elsewhere24,25. THE GENE EXPRESSION PATTERN IN MICE WITH HIGH LEVELS OF 12 A HETEROPLASMY AT THE ORIL IS SIMILAR TO THAT IN ADVANCED AGE MICE Next, to


elucidate the pathways involved in heteroplasmy-related phenotypes, RNA-seq was performed on liver tissue from 3–4 and 19–20-month-old B6 and B6-mtAKR mice. Of 14,031 expressed genes, 103


are differentially expressed between young B6-mtAKR and B6 mice (_p_ < _0_._01_, Fig. 5a, Supplementary Data S1). Genes highly expressed in mice with higher heteroplasmy include _Mtor_


and _Fbxo32_, suggesting that heteroplasmy exhibits a mild, but significant impact on the mTOR pathway. Interestingly, _Fbxo32_ (Atrogin-1; Mafbx) has been shown to be upregulated in


sarcopenia. Pathways leading to sarcopenia include the down regulation of the PI3K/AKT pathway and activation of the FOXO transcription factor27. Gene set enrichment analysis (GSEA) reveals


that up-regulated genes include those involved in metabolic processes and cellular responses (mainly to hormones), while down-regulated genes include those involved in the respiratory chain,


ribosomes and translation (e.g., mitochondrial translation) (Supplementary Data S2, Fig. 5b). We also evaluated whether aging and heteroplasmy play complementary roles in driving gene


expression. The overlap between GSEA according to heteroplasmy versus age (Fig. 5c) results in 23 common highly expressed gene ontology (GO) terms and 16 down-regulated terms (Fig. 5d).


Glucose metabolism and cell adhesion were prevalent in mice with higher heteroplasmy (B6-mtAKR) and aged mice, while mitochondrial processes were prevalent in those with lower heteroplasmy


(B6) and young mice (Supplementary Data S3). These transcriptomics data are in agreement with the findings of mtDNA copy number and gene expression (i.e., less mtDNA copy number and higher


mtDNA-gene expression in B6-mtAKR; Fig. 2a,d,e), as well as the metabolic phenotype data, i.e. genes involved in metabolic processes are up-regulated, presumably in order to control glucose


metabolism in mice with higher levels of 12 A heteroplasmy (Fig. 4 and Supplementary Fig. S4). THE IMPACT OF LOW-LEVEL HETEROPLASMIC MUTATIONS DEPENDS ON THE LOCATION Lastly, we evaluated


whether another heteroplasmic mutation present in the mice has an impact on lifespan. Sequencing data revealed that both the B6 and B6-mtAKR strain carry a heteroplasmic mutation at nt9821,


in the tRNA-arginine gene (_mt-Tr_). Almost all B6 samples are 8-adenine repeat (8 A) homoplasmic, while 9 A is the major genotype in B6-mtAKR with a very low copy number of 8 A


(Supplementary Fig. S5a). However, the level of heteroplasmy in _mt-Tr_ does not correlate to lifespan in our study (Supplementary Fig. S5b), indicating that the impact of lower heteroplasmy


on lifespan is highly dependent on the location. DISCUSSION Individual mammalian cells, including oocytes, carry thousands of individual copies of mitochondrial DNA. These copies may differ


in regards to individual bases or entire regions. This so-called heteroplasmy of mitochondrial DNA has been described many years ago28,29,30 and is known to cause mitochondrial dysfunction


if it affects a high percentage of mtDNA copies, i.e., over 70–80%31,32. Here, we observed “low-level” heteroplasmy at nt5172 in the OriL (>20%) in the B6-mtAKR mouse line, which is more


pronounced than the degree of heteroplasmy observed in the B6 background (namely, ~10%). This is the first report demonstrating the impact of naturally occurring low-level heteroplasmic


mutations, and specifically in the OriL locus, on mammalian aging. Interestingly, the effect of heteroplasmic mutation in the OriL on the lifespan was limited to females. This is in contrast


to the well-described “mother’s curse”, i.e. the consequence of mtDNA mutations are often thought to be higher in males33. The “mother’s curse” is defined by the fact that numerous


male-harming mutations accumulate in mitochondrial genome when those are neutral, beneficial or only slightly deleterious in their effects in females, i.e. a sex-specific selective sieve34.


In all our conplastic mouse strains, we do not see any mtDNA mutations that specifically affect males. Similar observations were previously reported by a study in fruit flies35. In that


study, an _ND2_ gene mutation, causing a Leigh syndrome-like neurological phenotype, was observed only in females, and the impact of the mutation on the lifespan was greater in females than


males35. Another example of a mtDNA mutation with a stronger impact in females was described in our previous study, which showed that females, but not males, carrying a single mutation in


complex V gain more weight when fed a western-type diet compared to the wild-type mice36. The OriL is indispensable for mtDNA maintenance in mice22. The OriL sequence forms a stable


stem-loop structure when mtDNA is single-stranded during replication, and mtDNA-directed RNA polymerase (POLRMT) initiates primer synthesis from the polyA stretch of the loop37. Since the


region is critical for mtDNA replication and maintenance, the OriL appears to be well protected from the incidence of mutations22. Our transcriptome data demonstrates that the lower the


level of 12 A heteroplasmy in the OriL, the higher the up-regulation of mitochondrial translation, supporting a functional link between the level of 12 A heteroplasmy in the OriL and mtDNA


copy number. The levels of the 12 A heteroplasmy at the OriL correlate to, mitochondrial functions, i.e., the levels of OXPHOS activities (normalized to each individual CS value) and


hydrogen peroxide (H2O2) levels when values are normalized with the mtDNA/nDNA copy number ratio. This correlation was stronger in young mice than in aged mice. This could be likely because


aging differentially affects OXPHOS activities and H2O2 levels in both strains. We also observed an impact of the different levels of the heteroplasmic mutation at the OriL on glucose


metabolism in mice. To the best our knowledge no variations in OriL have been reported to be associated with mitochondrial diabetes. This is in agreement with previous reports of mtDNA


mutations, e.g., the m.3243 A>G mutation in the mitochondrial DNA-encoded tRNA (_Leu_, _UUR_) gene is causal for mitochondrial diabetes38. The precise functional consequence of the m.3243


 A>G mutation in tRNA-Leu (UUR) on mitochondrial function, leading to mitochondrial diabetes, is a matter of debate, but it is likely to involve 1) alteration in the ATP/ADP ratio, which


is a critical determinant of insulin secretion in pancreatic beta cells, 2) functional impairment of the respiratory chain, and 3) an imbalance in the mtDNA-encoded protein amount24.


Additionally, it was shown that the gene expression patterns in cells carrying the m.3243 A>G mutation were quite similar to those in cells with reduced mtDNA copy numbers, indicating the


relevance of the mutation and the mtDNA copy number24. Interestingly, experimental evidence demonstrated that the reduced mtDNA copy number induced by beta-cell specific disruption of the


nuclear genome-encoded mitochondrial transcription factor A gene (_Tfam_), which controls mtDNA copy number and transcription, impaired glucose-induced insulin responses, consequently


resulted in mitochondrial diabetes39. Another report showed that mutations at the H-strand replication origins (OriH) of mtDNA are also linked to the levels of the mitochondrial DNA copy


number and diabetes40. Similarly, mutations in mitochondrially encoded genes, or mitochondrially active nuclear encoded genes, frequently associated with glucose intolerance, cause


neurodegenerative disorders41. One example of such disorders is Friedreich Ataxia (FA), which is resulted by the impaired expression of the nuclear genome encoded frataxin protein that


affect OXPHOS function42 by mediating mitochondrial iron-sulphur-cluster biosynthesis43. FA patients develop diabetes and exhibited decreased lifespan41, and experimental evidence using


different models showed that a frataxin knock-out cause diabetes in mice44, and knocking down of the frataxin gene resulted in shorter lifespan in worms45. To date, only a few studies have


addressed the functional and pathological consequences of mutations in the OriL in humans. One study identified a rare mutation in OriL (m.5747 A>G mutation, i.e., the starting point of


poly-A in the loop structure, which is similar to the 5172 mutation in mice) in 2 of 133 bipolar disease patients, while none of 186 healthy control carried the mutation46. Another study


reported a rare mutation in OriL (m.5752insA, which is in the poly-A loop structure) in one female with hypertension47. Since the position is evolutionally conserved46, the mutation is


likely pathologically relevant, though its relevance to the mtDNA copy number and disease phenotypes have not been fully investigated48. Our findings indicate that the correlation of the


higher levels of the 12 A heteroplasmy at the OriL to the mitochondrial DNA copy number and glucose metabolism, may result in a shorter lifespan in mice. As a proof of this concept and to


identify the pathways involved, generation of cell lines (eventually mice) with different levels of the heteroplasmy at OriL using gene-editing technology, e.g., mitochondrial genome-target


CRISPR-Cas system49 or TALEN50,51, and an investigation on the aging and metabolic phenotypes of the cells carrying different levels of the heteroplasmy should be performed. Additionally,


this particular region in the OriL seems to be a specific target of the nematodal CLK-1 protein52. The same study demonstrated that its mouse homologue also displays binding activity


specific to the OriL loop, suggesting a regulatory function of CLK-1 in mtDNA replication in addition to its known ubiquinone biosynthesis function52. Mutations in the _clk-1_ gene result in


an extension of lifespan in nematodes53, and a partial inactivation of the mouse homologue _Mclk-1_ also extends lifespan in mice54. Global deletion of _Mclk-1_ in adult mice results in


decreased levels of fasting glucose and triglycerides6, suggesting the potential role of the OriL in metabolic control. This experimental evidence supports our observation regarding the


correlation between heteroplasmic mutations in OriL and lifespan in mice. To determine whether the interaction between CLK-1 and OriL is dependent on the levels of 12 A heteroplasmy at the


OriL, experiments such as DNA binding activity of CLK-1 protein using probe containing 11 A or 12 A at 5172 at the OriL as previously described52 will be considered. Additionally, since the


loss of CLK-1 extends the lifespan in worms and mice, it seems that disrupting of the binding CLK-1 and OriL may negatively regulate of mtDNA replication, which consequently leads to a


shorter lifespan. Thus, analyzing the effect of Mclk-1 knockout or overexpression on the B6-mtAKR and B6 backgrounds, may elucidate the impact of the _Mclk-1_ gene on different levels of the


12 A heteroplasmy and lifespan _in vivo_. An additional low-level heteroplasmy at position 9821 is present in our data, in B6-mtAKR mice. This position is located in the tRNA-arginine gene


(_mt-Tr_), which is known to be polymorphic in common inbred strains21,55,56. No correlation is observed between the heteroplasmic mutation in _mt-T_r and any of the phenotypes we


investigated. Interestingly, a previous study investigating the functional consequences of varying length polymorphisms of adenines at nt9821 in the DHU loop of _mt-Tr_ reported that cybrids


carrying 8 A and 9 A polymorphisms did not differ the levels of H2O2, and a copy number ratio of mtDNA to nDNA, while those levels were significantly higher in cybrids with 10A57. B6-mtAKR


mice exhibited low levels of the heteroplasmy, i.e. 8 A or 10 A at 9821 in _mt-Tr_, 5% and 0.56% respectively, while all B6 mice carry homoplasmic 8 A variant. Those very low levels of


heteroplasmy are unlikely to cause the observed phenotypes in the B6-mtAKR mice. Also, the 10 A heteroplasmy, which is reportedly a causal variant for OXPHOS functional differences, occurred


in only 7 of 32 B6-mtAKR mice, thus, supporting our conclusion that the impact of low-level heteroplasmy is dependent on the location within the mtDNA, i.e. OriL in this study. In summary,


we present experimental evidence linking the degree of mtDNA heteroplasmy to murine lifespan. Specifically, higher levels of 12 A heteroplasmy at position 5172 in the OriL correlate with


shorter lifespan and impaired glucose metabolism in female mice. Furthermore, this heteroplasmy influences mtDNA copy number. In young mice, such a reduction of mtDNA copy number can be


compensated for by increased expression of the affected genes. In contrast, this compensatory mechanism is missing in aged mice. The heteroplasmic mutation investigated in this study is


natural, low-level and stable over generations. We demonstrate that such quiescent variation in mtDNA influences healthspan even under normal housing condition, suggesting that additional


environmental triggers such as metabolic stress could amplify the phenotypic consequences. Further studies to elucidate the involved mechanisms, particularly the interaction between mtDNA


variants and environmental stress factors, are warranted. Given the established role of mtDNA variations in human exercise performance, the current findings may likely translate into a


co-determining function of human aging. METHODS MICE ANIMALS AND HUSBANDRY The conplastic mouse strain _C57BL/6J-mt__AKR/J_ (B6-mtAKR) was previously generated20. _C57BL/6 J_ (B6) mice


(stock number 000664) were purchased from Jackson laboratory (Bar Harbor, ME, USA) and were inbred, supplying new breeders every 12 months. B6-mtAKR mice with a backcross of 25 to 28


generations were used for the survival study. Nuclear genomes of both B6 and B6-mtAKR were genotyped using the MegaMUGA Mouse Universal Genotyping Array (77,800 SNPs) as described below, and


greater than 99.9% of SNPs were identical between the strains (Supplementary Table S2). The entire mitochondrial genome was deep-sequenced using Illumina MiSeq as described below. Mice had


_ad libitum_ access to filtered water and autoclaved pellet diet (1314, Altromin, Lippe, Germany). The animal facility was maintained at 21 °C on a 12-h light-dark cycle. Mice were allocated


into two study groups: a longitudinal study group to evaluate lifespan and a cross sectional study group to evaluate the mice at different ages. Animal use and all methods were approved by


the Animal Care and Use Committee (V242–7224. 122–5, Kiel, Germany), and were performed in accordance with the relevant guidelines and regulations by certified personnel. NEXT GENERATION


SEQUENCING OF THE ENTIRE MITOCHONDRIAL GENOME Total DNA was isolated from liver, heart and brain tissues from mice at 3 and 22 months of age and was obtained using the DNeasy Blood and


Tissue kit (Qiagen, Hilden, Germany). Two primer sets [6551 forward (AGCAAAAGCCCACTTCGCCA) and 15169 reverse (GGTTGGCCCCCAATTCAGGT); 15150 forward (ACCTGAATTGGGGGCCAACC) and 6573 reverse


(TGGCGAAGTGGGCTTTTGCT)] were used to amplify the mtDNA by long-range PCR58. The 15169 reverse primer and the 15150 forward primer overlap. The library preparation was performed using a


Nextera XT DNA Library Preparation Kit (Illumina Inc., CA, USA), and the 10 pM library was sequenced using the Illumina MiSeq sequencing platform (2 × 150 bp) (Illumina Inc.). Trimmed


paired-end fastq files were obtained from MiSeq platform. Quality of the paired-end reads was evaluated using the FastQC v0.11.5 software59. Reads missing either ends or with an average


quality score of <30 or a read length of <30 bp were discarded from subsequent analysis. The remaining reads were mapped to the C57BL/6 J mouse mtDNA reference sequence (EF08336) using


Burrows-Wheeler Aligner bwa version 0.70560, and bam files were generated. Duplicated reads generated due to PCR were removed using Markdupliates (Picard tools version 1.9261), and indels


were realigned using IndelRealigner (Genome analysis tool kit version 3.3)62. The processed bam files were assessed for the frequency and base quality (≥30) for each reference and alternate


base in mouse mtDNA using pysamstat (version 0.24.3)63. When the frequency of the alternate allele compared with the reference allele was greater than 90%, it was considered as homoplasmic


mutation, whereas 40 to 90% was considered as heteroplasmy. Additionally, bam files were manually inspected for mutations and indels using IGV software64. To count the GA+ at nucleotide 5171


and 5172 and the TA+ at nucleotide 9821, the CIGAR strings from the bam files were parsed using an in-house-written perl script. In brief, samtools were used to identify the mapped


paired-end read at this position. Thereafter, these reads were search for motif G+ poly A (reference, 11A) and occurrence of every motif was counted in each sample. The quality of each motif


was also parsed, where average base pair quality <20 was discarded. To the targeted re-sequencing the above procedure was applied as same, while aligning the reads to the targeted region


spanned by the primer sequences. NUCLEAR GENOME SNP GENOTYPING DNA samples were genotyped for 77,808 SNP markers in the nuclear genome using the Mouse Universal Genotyping Array (MegaMUGA,


GeneSeek Europe, Scotland, UK). Array processing and genotype calling were performed using GeneSeek as previously described65. WHOLE TRANSCRIPTOME STUDY Total RNA was prepared from liver


tissue using innuPREP RNA Mini Kit (Analytik Jena AG, Jena, Germany). Library preparation was performed employing the TruSeq stranded Total RNA kit (Illumina Inc.), starting from 0.6 µg of


total RNA of each sample, and sequenced on an Illumina HiSeq. 4000 platform (75-nucleotide paired-end reads). Aiming for high transcriptome coverage, sequencing runs were performed by


combining four samples per lane (corresponding to approximately 50 million reads per sample). Fastq reads were pseudo-aligned to the mm10 genome assembly using Kallisto66 and transcript read


counts were aggregated to Ensembl Gene IDs for further analysis. RNAseq data has been uploaded to Gene Expression Omnibus (GEO) with the ID GSE94315. The reviewer can access the data under


the private link: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=orcniykedvejjox&acc=GSE94315. Differential gene expression analysis was performed via the R library sleuth67 using


a linear model that accounted for mouse age, heteroplasmy and batch effects. Significance and effect sizes of differential gene regulation were calculated from the likelihood ratio and the


Wald test, respectively, as implemented in the sleuth package. GO term and pathway enrichment analyses were performed based on the effect size between the different mouse strains or age


using the generally applicable Gen Set Enrichment Analysis (GSEA), GAGE, which determines whether a set of genes is systematically up- or down-regulated as a whole68. For gene set


definitions, we used the Molecular Signatures Database (MSigDB) collections v.5.2 that were mapped to mouse ortholog Entrez IDs via the HGNC Comparison of Orthology Predictions (HCOP)


(provided by the Walter and Eliza Hall Institute; http://bioinf.wehi.edu.au/software/MSigDB/). Gene sets with less than 10 or those with more than 500 members were discarded for statistical


robustness and biological interpretation. To assess the significance of differential regulation, a gene rank-based nonparametric Kolmogorov-Smirnoff test was used. SURVIVAL STUDY LIFESPAN


STUDY AND DETERMINING AGE AT DEATH Sixty-four mice per group were calculated using G*Power69 to allow the detection of a 10% difference in lifespan at a two-sided 0.05 significance level and


a power of 0.8. Therefore, we used 155 B6 mice (87 females and 68 males) and 131 B6-mtAKR mice (85 females and 79 males) to evaluate lifespan. Mice were inspected daily. As previously


described70, a mouse was determined as moribund when demonstrating more than one of the following clinical signs: inability to eat or drink; abnormally low body temperature; severe lethargy


(reluctant to move when gently prodded with forceps); severe balance or gait disturbance; rapid body mass loss; an ulcerated or bleeding tumor; enlarged abdomen; panting; or severe


ulcerative dermatitis that covers greater than 20% of the body surface. The age at which a moribund mouse was sacrificed was taken as the best available estimate of its natural lifespan. At


the autopsy, the aging phenotype (presence of alopecia, graying hair, body mass reduction, and kyphosis) was scored as previously described23. Moribund mice were autopsied by a veterinarian,


and clinical and macroscopic observations were recorded. Blood samples were stored at −20 °C, and organ samples were stored in 4% paraformaldehyde solution in phosphate buffered saline.


STATISTICAL ANALYSIS FOR THE SURVIVAL STUDY Survival curves were drawn using the Kaplan-Meier method, and median lifespans with 95% confidence intervals were calculated. Censored mice are


displayed as a cross (×) in the survival curves. The differences of longevity between the strains were analyzed using both the log-rank method and the Gehan test. In addition, mouse survival


data in females were fitted by a skew Gaussian distribution using the R library sn071. MITOCHONDRIAL FUNCTIONAL STUDIES MITOCHONDRIAL DNA COPY NUMBER RATIO The copy number ratio of


mitochondrial DNA and nuclear DNA was determined using a droplet digital PCR system with DNA-binding dye (Bio-Rad Laboratories, Munich, Germany). Genomic DNA isolated from liver samples was


digested with HindIII (New England BioLabs Inc. MA, USA). Droplets were generated using 20 µl PCR reaction components (digested genomic DNA, _mt-Co1_ [forward (ACATGAAACCCCCAGCCATA) and


reverse (TTGTGTTTAGGTTGCGGTCTG)], _mt-Nd5_ [forward (TGCCTAGTAATCGGAAGCCTCGC and reverse (TCAGGCGTTGGTGTTGCAGG)] or _Vdac1_ [forward (CTCCCACATACGCCGATCTT) and reverse (GCCGTAGCCCTTGGTGAAG)]


primers at a final concentration of 1 nM, and 10 µl of 2 × QX200 EvaGreen ddPCR supermix (Bio-Rad Laboratories)) with 70 µl of Droplet Generator Oil for EvaGreen (Bio-Rad Laboratories)


using QX200 droplet generator (Bio-Rad Laboratories), followed by PCR reaction using thermal cycler (Bioer, Zhejiang, China). The PCR reaction and the droplet quantification were performed


as previously described72. MITOCHONDRIAL GENE EXPRESSION The mitochondrial gene expression was determined using a droplet digital PCR system. Total RNA isolated from liver samples were


prepared for cDNA using First Strand cDNA Synthesis Kit (Thermo Fischer Scientific, Pinneberg, Germany). The following procedure is the same as the method for mitochondrial DNA copy number


ratio determination. MITOCHONDRIAL PREPARATION Freshly removed liver was minced and homogenized on ice in ice-cold isolation buffer [0.2 mM EDTA, 250 mM sucrose, 10 mM Tris-HCl pH 7.8, and


protease and phosphatase inhibitor (Thermo Fisher Scientific)] using a Potter-Elvehjem glass homogenizer. The liver homogenates were centrifuged at 1000 × _g_ for 10 minutes at +4 °C, and


the resulting supernatants were centrifuged for 10,000 × _g_ for 15 minutes at +4 °C. Pellets were resuspended in a small volume of isolation buffer and immediately used for the measurement


of mitochondrial hydrogen peroxide. For the mitochondrial OXPHOS complex activity measurement, mitochondria samples were frozen at −80 °C until analysis. MITOCHONDRIAL RESPIRATORY CHAIN


COMPLEX ACTIVITY ASSAY Mitochondrial respiratory chain complex activities were measured as previously reported73,74 with slight modifications15. In brief, assays were performed in 200 


µl/well in a 96-well plate at 37 °C (except citrate synthase, which was performed at 30 °C) using a Tecan Infinite 200 PRO series spectrophotometer (Tecan Group Ltd., Crailsheim, Germany).


Frozen mitochondria samples were disrupted by two cycles of freezing in liquid nitrogen and thawing at room temperature. Complex I activity was measured at 340 nm as the rotenone-sensitive


rate of NADH oxidation and complex I-dependent electron transfer to decylubiquinone. Complex III activity was assayed at 550 nm as the antimycin A-sensitive rate of reduction of cytochrome c


by electron transfer from decylubiquinol through complex III. Complex IV activity was measured at 550 nm as the cyanide-sensitive oxidation of cytochrome c. Complex V activity was assayed


at 340 nm as oligomycin-sensitive ATP hydrolysis by complex V coupled to pyruvate kinase and lactate dehydrogenase activities and the corresponding oxidation of NADH. Citrate synthase


activity was measured as the condensation reaction of oxaloacetic acid and acetyl-CoA to citrate and the subsequent reduction of DTNB (5,5′-dithiobis (2-nitrobenzoic acid)) by coenzyme A as


detected at 412 nm. MEASUREMENT OF MITOCHONDRIAL HYDROGEN PEROXIDE Hydrogen peroxide content in liver mitochondria and skin fibroblast cell lines was assessed using the Amplex Red H2O2 kit


(Thermo Fisher Scientific) following the manufacturer’s protocol. WESTERN BLOTTING Frozen liver tissue was lysed in RIPA buffer and the supernatant was used for Western blotting. Antibodies


against OXPHOS proteins (MitoProfile Total OXPHOS Rodent WB Antibody Cocktail; Abcam, Cambridge, UK) and beta-actin (Cell Signaling Technology), as well as secondary antibodies (polyclonal


goat anti-rabbit immunoglobulins-HRP and polyclonal rabbit anti-mouse immunoglobulins-HRP; both from Dako, Glostrup, Denmark) were used. Antibody binding was visualized using the Clarity


Western ECL Substrate (Bio-Rad Laboratories) to detect HRP-induced luminescence, Signals were detected using a CCD camera documentation system (FUSION Fx7, Vilber Lourmat Deutschland GmbH,


Eberhardzell, Germany) applying variable exposure times. Images were evaluated using ImageJ v1.50b. METABOLIC PHENOTYPING ORAL GLUCOSE TOLERANCE TEST (OGTT) Female mice were fasted for 6 


hours and then glucose (2 g/kg) was orally administrated. Glucose was determined from a tail vein blood before and 30, 60 and 120 min after glucose administration using a glucometer


(ACCU-CHEK® Performa, Roche Diagnositcs GmbH, Mannheim, Germany). PLASMA PARAMETER ASSAY Determination of glucose, fructosamine, lactate, free fatty acids and total cholesterol in plasma was


performed using an automated analyzer (Cobas Mira S, Hoffmann-La Roche, Basel, Switzerland) with the appropriate commercially available reagent kits (glucose HK, fructosamine, lactate FS,


cholesterol PAP, Diatools, Villmergen, Switzerland; and NEFA HR, Wako, Neuss, Germany. Plasma insulin levels were measured using an immunoassay-based Mouse/Rat Insulin Kit on a Sector Imager


(Meso Scale Discovery, Gaithersburg, MD) according to the manufacturer’s instructions. ENZYME ACTIVITY AND GLYCOGEN CONTENT DETERMINATION Activities of pyruvate kinase (PK) and


phosphoenolpyruvate carboxylkinase (PEPCK) as well as glycogen content in the liver were determined as previously described75. In brief, PEPCK activity was determined using cytosolic


fraction of frozen liver tissue homogenates (female, n = 7 per strain) in a sample buffer containing 65 mM Tris (pH8.0), 6 mM MgCl2, 15 µM MnCl2. 0.875 mg/ml BSA. 4.65 mM ATP and ADP, 0.6 mM


reduced nicotinamide adenine dinucleotide, 5U/ml PK and lactate dehydeogenase. Oxyloacetate was added as substrate in a final concentration of 0.5 mM, and the conversion of reduced


nicotinamide adenine dinucleotide was monitored at 340 nm. Sample without substrate and samples with water were used to determine background activity. The same cytosolic fractions and sample


buffers, and substrates without MnCl2, ATP and PK, and 0.5 mM phosphoenolpyruvate were used to measure PK activity. Glycogen content in the liver was precipitated homogenate using 5%


trichloroacetic acid, and dissolved in Lugol´s reagent (Sigma-Aldrich GmbH, Munich, Germany) in 25% (wt/vol) potassium chloride containing 30 mm hydrochloric acid, followed by the


measurement at 600 nm and normalized to the tissue weight. METABOLOMICS STUDY Plasma and liver samples were obtained from B6 and B6-mtAKR mice (n = 5 per strain; female). Snap frozen samples


were sent to Helmholz Center Munich for the targeted metabolites detection (163 metabolites) using Biocrate assays (Biocrates life Sciences AG, Innsbruck, Austria). STATISTICAL ANALYSIS


Statistical tests used for analysis are indicated in the figure legends. P-values were not adjusted for multiple testing. WILD HOUSE MOUSE SAMPLES 217 mice were captured in 34 farms around


Espelette, France in September 2013, of which 216 were confirmed to belong to _Mus musculus domesticus_. The sampling procedure was organized over a two days period: the traps were placed at


day 1 and trapped live mice were collected in the morning of day 2. Mice were sacrificed and ear samples for analysis were collected and frozen at −20 °C. After shipment of the samples to


the laboratory, genomic DNA was extracted from the ear samples using the DNeasy Blood & Tissue Kit (Qiagen) and used for the next generation sequencing of the whole mitochondrial genome,


as described for the laboratory mice. Samples from 215 mice were successfully sequenced and used for the analysis. DATA AVAILABILITY RNAseq data has been uploaded to Gene Expression Omnibus


(GEO) with the ID GSE94315. REFERENCES * Wallace, D. C. A mitochondrial paradigm of metabolic and degenerative diseases, aging, and cancer: a dawn for evolutionary medicine. _Annu. Rev.


Genet._ 39, 359–407 (2005). Article  CAS  PubMed  PubMed Central  Google Scholar  * Chandel, N. S. Mitochondria as signaling organelles. _BMC Biol._ 12, 34 (2014). Article  MathSciNet 


PubMed  PubMed Central  Google Scholar  * Dillin, A. _et al_. Rates of Behavior and Aging Specified by Mitochondrial Function During Development. _Science_ 298, 2398–2401 (2002). Article 


ADS  CAS  PubMed  Google Scholar  * Feng, J., Bussière, F. & Hekimi, S. Mitochondrial electron transport is a key determinant of life span in Caenorhabditis elegans. _Dev. Cell_ 1,


633–644 (2001). Article  CAS  PubMed  Google Scholar  * Lin, M. T. & Beal, M. F. Mitochondrial dysfunction and oxidative stress in neurodegenerative diseases. _Nature_ 443, 787–795


(2006). Article  ADS  CAS  PubMed  Google Scholar  * Wang, Y., Oxer, D. & Hekimi, S. Mitochondrial function and lifespan of mice with controlled ubiquinone biosynthesis. _Nat. Commun._


6, 6393 (2015). Article  ADS  CAS  PubMed  PubMed Central  Google Scholar  * Anderson, S. _et al_. Sequence and organization of the human mitochondrial genome. _Nature_ 290, 457–465 (1981).


Article  ADS  CAS  PubMed  Google Scholar  * Wallace, D. C. _et al_. Mitochondrial DNA mutation associated with Leber’s hereditary optic neuropathy. _Science_ 242, 1427–1430 (1988). Article


  ADS  CAS  PubMed  Google Scholar  * Wallace, D. C. _et al_. Familial mitochondrial encephalomyopathy (MERRF): genetic, pathophysiological, and biochemical characterization of a


mitochondrial DNA disease. _Cell_ 55, 601–610 (1988). Article  CAS  PubMed  Google Scholar  * Kujoth, G. C. _et al_. Mitochondrial DNA mutations, oxidative stress, and apoptosis in mammalian


aging. _Science_ 309, 481–484 (2005). Article  ADS  CAS  PubMed  Google Scholar  * Trifunovic, A. _et al_. Premature ageing in mice expressing defective mitochondrial DNA polymerase.


_Nature_ 429, 417–423 (2004). Article  ADS  CAS  PubMed  Google Scholar  * Sharpley, M. S. _et al_. Heteroplasmy of mouse mtDNA is genetically unstable and results in altered behavior and


cognition. _Cell_ 151, 333–343 (2012). Article  CAS  PubMed  PubMed Central  Google Scholar  * Kauppila, J. H. K. _et al_. A Phenotype-Driven Approach to Generate Mouse Models with


Pathogenic mtDNA Mutations Causing Mitochondrial Disease. _Cell Rep._ 16, 2980–2990 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  * Latorre-Pellicer, A. _et al_.


Mitochondrial and nuclear DNA matching shapes metabolism and healthy ageing. _Nature_, https://doi.org/10.1038/nature18618 (2016). * Hirose, M. _et al_. Lifespan effects of mitochondrial


mutations. _Nature_ 540, E13–E14 (2016). Article  CAS  PubMed  Google Scholar  * Polyak, K. _et al_. Somatic mutations of the mitochondrial genome in human colorectal tumours. _Nat. Genet._


20, 291–293 (1998). Article  CAS  PubMed  Google Scholar  * He, Y. _et al_. Heteroplasmic mitochondrial DNA mutations in normal and tumour cells. _Nature_ 464, 610–614 (2010). Article  ADS 


CAS  PubMed  PubMed Central  Google Scholar  * Li, M. _et al_. Detecting heteroplasmy from high-throughput sequencing of complete human mitochondrial DNA genomes. _Am. J. Hum. Genet._ 87,


237–249 (2010). Article  CAS  PubMed  PubMed Central  Google Scholar  * Payne, B. A. I. _et al_. Universal heteroplasmy of human mitochondrial DNA. _Hum. Mol. Genet._ 22, 384–390 (2013).


Article  CAS  PubMed  Google Scholar  * Yu, X. _et al_. Dissecting the effects of mtDNA variations on complex traits using mouse conplastic strains. _Genome Res._ 19, 159–165 (2009). Article


  CAS  PubMed  PubMed Central  Google Scholar  * Bayona-Bafaluy, M. P. _et al_. Revisiting the mouse mitochondrial DNA sequence. _Nucleic Acids Res._ 31, 5349–5355 (2003). Article  CAS 


PubMed  PubMed Central  Google Scholar  * Wanrooij, S. _et al_. _In vivo_ mutagenesis reveals that OriL is essential for mitochondrial DNA replication. _EMBO Rep._ 13, 1130–1137 (2012).


Article  CAS  PubMed  PubMed Central  Google Scholar  * Ross, J. M. _et al_. Germline mitochondrial DNA mutations aggravate ageing and can impair brain development. _Nature_ 501, 412–415


(2013). Article  ADS  CAS  PubMed  PubMed Central  Google Scholar  * Maassen, J. A. _et al_. Mitochondrial diabetes: molecular mechanisms and clinical presentation. _Diabetes_ 53(Suppl 1),


S103–109 (2004). Article  CAS  PubMed  Google Scholar  * Wiederkehr, A. & Wollheim, C. B. Minireview: implication of mitochondria in insulin secretion and action. _Endocrinology_ 147,


2643–2649 (2006). Article  CAS  PubMed  Google Scholar  * Yin, F., Sancheti, H., Liu, Z. & Cadenas, E. Mitochondrial function in ageing: coordination with signalling and transcriptional


pathways. _J. Physiol._ 594, 2025–2042 (2016). Article  CAS  PubMed  Google Scholar  * Sandri, M. _et al_. Foxo transcription factors induce the atrophy-related ubiquitin ligase atrogin-1


and cause skeletal muscle atrophy. _Cell_ 117, 399–412 (2004). Article  CAS  PubMed  PubMed Central  Google Scholar  * Solignac, M., Monnerot, M. & Mounolou, J. C. Mitochondrial DNA


heteroplasmy in Drosophila mauritiana. _Proc. Natl. Acad. Sci. USA_ 80, 6942–6946 (1983). Article  ADS  CAS  PubMed  PubMed Central  Google Scholar  * Hauswirth, W. W., V de Walle, M. J.,


Laipis, P. J. & Olivo, P. D. Heterogeneous mitochondrial DNA D-loop sequences in bovine tissue. _Cell_ 37, 1001–1007 (1984). Article  CAS  PubMed  Google Scholar  * Boursot, P.,


Yonekawa, H. & Bonhomme, F. Heteroplasmy in mice with deletion of a large coding region of mitochondrial DNA. _Mol. Biol. Evol._ 4, 46–55 (1987). CAS  PubMed  Google Scholar  * Larsson,


N.-G. Somatic mitochondrial DNA mutations in mammalian aging. _Annu. Rev. Biochem._ 79, 683–706 (2010). Article  CAS  PubMed  Google Scholar  * Stewart, J. B. & Chinnery, P. F. The


dynamics of mitochondrial DNA heteroplasmy: implications for human health and disease. _Nat. Rev. Genet._ 16, 530–542 (2015). Article  CAS  PubMed  Google Scholar  * Frank, S. A. &


Hurst, L. D. Mitochondria and male disease. _Nature_ 383, 224 (1996). Article  ADS  CAS  PubMed  Google Scholar  * Innocenti, P., Morrow, E. H. & Dowling, D. K. Experimental evidence


supports a sex-specific selective sieve in mitochondrial genome evolution. _Science_ 332, 845–848 (2011). Article  ADS  CAS  PubMed  Google Scholar  * Burman, J. L. _et al_. A Drosophila


model of mitochondrial disease caused by a complex I mutation that uncouples proton pumping from electron transfer. _Dis. Model. Mech._ 7, 1165–1174 (2014). Article  PubMed  PubMed Central 


Google Scholar  * Schröder, T. _et al_. Mitochondrial gene polymorphisms alter hepatic cellular energy metabolism and aggravate diet-induced non-alcoholic steatohepatitis. _Mol. Metab._ 5,


283–295 (2016). Article  PubMed  PubMed Central  Google Scholar  * Fusté, J. M. _et al_. Mitochondrial RNA polymerase is needed for activation of the origin of light-strand DNA replication.


_Mol. Cell_ 37, 67–78 (2010). Article  PubMed  Google Scholar  * van den Ouweland, J. M. _et al_. Mutation in mitochondrial tRNA(Leu)(UUR) gene in a large pedigree with maternally


transmitted type II diabetes mellitus and deafness. _Nat. Genet._ 1, 368–371 (1992). Article  PubMed  Google Scholar  * Silva, J. P. _et al_. Impaired insulin secretion and beta-cell loss in


tissue-specific knockout mice with mitochondrial diabetes. _Nat. Genet._ 26, 336–340 (2000). Article  CAS  PubMed  Google Scholar  * Cormio, A. _et al_. Variations at the H-strand


replication origins of mitochondrial DNA and mitochondrial DNA content in the blood of type 2 diabetes patients. _Biochim. Biophys. Acta_ 1787, 547–552 (2009). Article  CAS  PubMed  Google


Scholar  * Ristow, M. Neurodegenerative disorders associated with diabetes mellitus. _J. Mol. Med. Berl. Ger._ 82, 510–529 (2004). Google Scholar  * Ristow, M. _et al_. Frataxin activates


mitochondrial energy conversion and oxidative phosphorylation. _Proc. Natl. Acad. Sci. USA_ 97, 12239–12243 (2000). Article  ADS  CAS  PubMed  PubMed Central  Google Scholar  * Mühlenhoff,


U., Richhardt, N., Ristow, M., Kispal, G. & Lill, R. The yeast frataxin homolog Yfh1p plays a specific role in the maturation of cellular Fe/S proteins. _Hum. Mol. Genet._ 11, 2025–2036


(2002). Article  PubMed  Google Scholar  * Ristow, M. _et al_. Frataxin deficiency in pancreatic islets causes diabetes due to loss of beta cell mass. _J. Clin. Invest._ 112, 527–534 (2003).


Article  CAS  PubMed  PubMed Central  Google Scholar  * Zarse, K., Schulz, T. J., Birringer, M. & Ristow, M. Impaired respiration is positively correlated with decreased life span in


Caenorhabditis elegans models of Friedreich Ataxia. _FASEB J. Off. Publ. Fed. Am. Soc. Exp. Biol._ 21, 1271–1275 (2007). CAS  Google Scholar  * Kato, T., Kunugi, H., Nanko, S. & Kato, N.


Mitochondrial DNA polymorphisms in bipolar disorder. _J. Affect. Disord._ 62, 151–164 (2001). Article  CAS  PubMed  Google Scholar  * Mostafaie, N. _et al_. Mitochondrial genotype and risk


for Alzheimer’s disease: cross-sectional data from the Vienna-Transdanube-Aging ‘VITA’ study. _J. Neural Transm. Vienna Austria 1996_ 111, 1155–1165 (2004). CAS  Google Scholar  * Anglin, R.


E. S., Mazurek, M. F., Tarnopolsky, M. A. & Rosebush, P. I. The mitochondrial genome and psychiatric illness. _Am. J. Med. Genet. Part B Neuropsychiatr. Genet. Off. Publ. Int. Soc.


Psychiatr. Genet._ 159B, 749–759 (2012). Article  Google Scholar  * Jo, A. _et al_. Efficient Mitochondrial Genome Editing by CRISPR/Cas9. _BioMed Res. Int._ 2015, 305716 (2015). Article 


PubMed  PubMed Central  Google Scholar  * Bacman, S. R., Williams, S. L., Pinto, M., Peralta, S. & Moraes, C. T. Specific elimination of mutant mitochondrial genomes in patient-derived


cells by mitoTALENs. _Nat. Med._ 19, 1111–1113 (2013). Article  CAS  PubMed  PubMed Central  Google Scholar  * Reddy, P. _et al_. Selective elimination of mitochondrial mutations in the


germline by genome editing. _Cell_ 161, 459–469 (2015). Article  CAS  PubMed  PubMed Central  Google Scholar  * Gorbunova, V. & Seluanov, A. CLK-1 protein has DNA binding activity


specific to O(L) region of mitochondrial DNA. _FEBS Lett._ 516, 279–284 (2002). Article  CAS  PubMed  Google Scholar  * Lakowski, B. & Hekimi, S. Determination of life-span in


Caenorhabditis elegans by four clock genes. _Science_ 272, 1010–1013 (1996). Article  ADS  CAS  PubMed  Google Scholar  * Liu, X. _et al_. Evolutionary conservation of the clk-1-dependent


mechanism of longevity: loss of mclk1 increases cellular fitness and lifespan in mice. _Genes Dev._ 19, 2424–2434 (2005). Article  CAS  PubMed  PubMed Central  Google Scholar  * Johnson, K.


R., Zheng, Q. Y., Bykhovskaya, Y., Spirina, O. & Fischel-Ghodsian, N. A nuclear-mitochondrial DNA interaction affecting hearing impairment in mice. _Nat. Genet._ 27, 191–194 (2001).


Article  CAS  PubMed  PubMed Central  Google Scholar  * Sachadyn, P., Zhang, X.-M., Clark, L. D., Naviaux, R. K. & Heber-Katz, E. Naturally occurring mitochondrial DNA heteroplasmy in


the MRL mouse. _Mitochondrion_ 8, 358–366 (2008). Article  CAS  PubMed  PubMed Central  Google Scholar  * Moreno-Loshuertos, R. _et al_. Differences in reactive oxygen species production


explain the phenotypes associated with common mouse mitochondrial DNA variants. _Nat. Genet._ 38, 1261–1268 (2006). Article  CAS  PubMed  Google Scholar  * Quispe-Tintaya, W., White, R. R.,


Popov, V. N., Vijg, J. & Maslov, A. Y. Fast mitochondrial DNA isolation from mammalian cells for next-generation sequencing. _BioTechniques_ 55, 133–136 (2013). Article  CAS  PubMed 


PubMed Central  Google Scholar  * Babraham Bioinformatics - FastQC A Quality Control tool for High Throughput Sequence Data. Available at:


http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (Accessed: 18th July 2016). * Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform.


_Bioinforma. Oxf. Engl._ 25, 1754–1760 (2009). Article  CAS  Google Scholar  * Picard Tools - By Broad Institute. Available at: http://broadinstitute.github.io/picard/ (Accessed: 18th July


2016). * McKenna, A. _et al_. The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. _Genome Res._ 20, 1297–1303 (2010). Article  CAS  PubMed 


PubMed Central  Google Scholar  * alimanfoo/pysamstats. _GitHub_ Available at: https://github.com/alimanfoo/pysamstats (Accessed: 18th July 2016). * Robinson, J. T. _et al_. Integrative


genomics viewer. _Nat. Biotechnol._ 29, 24–26 (2011). Article  CAS  PubMed  PubMed Central  Google Scholar  * Collaborative Cross Consortium. The genome architecture of the Collaborative


Cross mouse genetic reference population. _Genetics_ 190, 389–401 (2012). * Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. _Nat.


Biotechnol._ 34, 525–527 (2016). Article  CAS  PubMed  Google Scholar  * Pimentel, H., Bray, N. L., Puente, S., Melsted, P. & Pachter, L. Differential analysis of RNA-Seq incorporating


quantification uncertainty. _bioRxiv_, https://doi.org/10.1101/058164 (2016). * Luo, W., Friedman, M. S., Shedden, K., Hankenson, K. D. & Woolf, P. J. GAGE: generally applicable gene set


enrichment for pathway analysis. _BMC Bioinformatics_ 10, 161 (2009). Article  PubMed  PubMed Central  Google Scholar  * Faul, F., Erdfelder, E., Lang, A.-G. & Buchner, A. G*Power 3: a


flexible statistical power analysis program for the social, behavioral, and biomedical sciences. _Behav. Res. Methods_ 39, 175–191 (2007). Article  PubMed  Google Scholar  * Yuan, R. _et


al_. Aging in inbred strains of mice: study design and interim report on median lifespans and circulating IGF1 levels. _Aging Cell_ 8, 277–287 (2009). Article  CAS  PubMed  PubMed Central 


Google Scholar  * Azzalini, A. _The Skew-Normal Probability Distribution_ (2013). * McDermott, G. P. _et al_. Multiplexed target detection using DNA-binding dye chemistry in droplet digital


PCR. _Anal. Chem._ 85, 11619–11627 (2013). Article  CAS  PubMed  Google Scholar  * Spinazzi, M., Casarin, A., Pertegato, V., Salviati, L. & Angelini, C. Assessment of mitochondrial


respiratory chain enzymatic activities on tissues and cultured cells. _Nat. Protoc._ 7, 1235–1246 (2012). Article  CAS  PubMed  Google Scholar  * Barrientos, A., Fontanesi, F. & Díaz, F.


Evaluation of the mitochondrial respiratory chain and oxidative phosphorylation system using polarography and spectrophotometric enzyme assays. _Curr_. _Protoc_. _Hum_. _Genet_. _Editor_.


_Board Jonathan Haines A_l Chapter 19, Unit19.3 (2009). * Vujovic, M. _et al_. Interference of a Mutant Thyroid Hormone Receptor α1 with Hepatic Glucose Metabolism. _Endocrinology_ 150,


2940–2947 (2009). Article  CAS  PubMed  Google Scholar  Download references ACKNOWLEDGEMENTS The authors thank Miriam Daumann, Miriam Freitag, Beate Laube, Doris Pöhlmann, Melanie Vollstedt,


and Nicole Thomsen for excellent technical assistance. We thank Stephanie Derer and Christian Sina for valuable discussion. This work was supported by grants from the Bundesministerium für


Bildung und Forschung (BMBF, 0315892B), DFG (EXC 306 and CRC 1182), University of Lübeck (P01-2012), the Swiss National Science Foundation (Schweizerischer Nationalfonds, SNF 31003A_156031),


and the European Union’s Horizon 2020 research and innovation program (633589). AUTHOR INFORMATION Author notes * Marvin N. Wright Present address: Leibniz Institute for Prevention Research


and Epidemiology, BIPS GmbH, Department Biometry and Data Management, Unit Statistical Methods in Genetics and Live-Course Epidemiology, Bremen, Germany AUTHORS AND AFFILIATIONS * Lübeck


Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany Misa Hirose, Paul Schilf, Yask Gupta, Junping Yin & Saleh M. Ibrahim * Energy Metabolism Laboratory,


Institute of Translational Medicine, Swiss Federal Institute of Technology (ETH) Zurich, Schwerzenbach, Switzerland Kim Zarse & Michael Ristow * Medical Systems Biology Group, Lübeck


Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany Axel Künstner, Anke Fähnrich & Hauke Busch * Institute for Cardiogenetics, University of Lübeck, Lübeck,


Germany Axel Künstner, Anke Fähnrich & Hauke Busch * Institute of Medical Biometry and Statistics, University of Lübeck, University Medical Center Schleswig-Holstein, Campus Lübeck,


Lübeck, Germany Marvin N. Wright * StatSol, Lübeck, Germany Andreas Ziegler * Max Planck Institute for Evolutionary Biology, Evolutionary Genomics, Plön, Germany Marie Vallier, Meriem


Belheouane, John F Baines & Diethard Tautz * Institute for Experimental Medicine, Section of Evolutionary Medicine, Christian-Albrechts-University of Kiel, Kiel, Germany John F Baines *


Center of Brain Behavior & Metabolism, Molecular Endocrinology, University of Lübeck, Lübeck, Germany Kornelia Johann, Rebecca Oelkrug & Jens Mittag * Center of Brain Behavior &


Metabolism, Clinical Endocrinology and Metabolism, University of Lübeck, Lübeck, Germany Hendrik Lehnert * Institute for Experimental and Clinical Pharmacology and Toxicology, University of


Lübeck, Lübeck, Germany Alaa Othman & Olaf Jöhren * Center of Brain, Behavior & Metabolism, University of Lübeck, Lübeck, Germany Alaa Othman & Markus Schwaninger * Helmholtz


Center, German Research Center for Environmental Health, Institute of Experimental Genetics, Genome Analysis Center, Neuherberg, Germany Cornelia Prehn & Jerzy Adamski * Department of


Infectious Disease and Microbiology, University of Lübeck, Lübeck, Germany Kensuke Shima & Jan Rupp * Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, Kiel,


Germany Robert Häsler * Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany Georg Fuellen *


Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock University, Rostock, Germany Rüdiger Köhling * College of Medicine and Sharjah Institute for Medical


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Scholar * Saleh M. Ibrahim View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS M.H. and S.M.I. designed the study. M.H., P.S. and J.Y.


performed the lifespan study, mitochondrial functional study as well as mitochondrial genome sequencing experiments and analyzed the data. M.N.W. and A.Z. conducted the statistical analysis


of the survival data together with A.K. and H.B.; Y.G. and A.F. analyzed the mitochondrial sequencing data. R.H. performed RNA-seq. A.K. and H.B. analyzed transcriptome data together with


G.F.; M.V., M.B., and J.F.B. collected wild mice samples and analyzed the data with D.T.; K.Z., K.J., R.O., and C.P. performed metabolic phenotyping experiment and analyzed the data. J.M.,


A.O., O.J., H.L., M.S., M.R., J.A., and R.K. contributed to interpretation of the metabolic phenotype data. K.S. and J.R. contributed to interpretation of the mitochondrial phenotype data.


M.H., J.F.B., M.R. and S.M.I. wrote the manuscript with contributions from all other authors. S.M.I. directed the study. CORRESPONDING AUTHORS Correspondence to Michael Ristow or Saleh M.


Ibrahim. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION PUBLISHER'S NOTE: Springer Nature remains neutral with regard to


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_et al._ Low-level mitochondrial heteroplasmy modulates DNA replication, glucose metabolism and lifespan in mice. _Sci Rep_ 8, 5872 (2018). https://doi.org/10.1038/s41598-018-24290-6


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