Short ArticleRegulation of Mother-to-Offspring Transmission of
mtDNA HeteroplasmyGraphical AbstractHighlightsd Wild-type mtDNA heteroplasmy is sensed in oocyte
maturation and embryo development
d Random versus selective mtDNA segregation is driven by the
nuclear genetic context
d Haplotype-derived OXPHOS differences and ROS signaling
define the preferred mtDNA
d Efficiency of iPSC generation strongly depends on themtDNA
haplotypeLatorre-Pellicer et al., 2019, Cell Metabolism 30, 1120–1130
December 3, 2019 Crown Copyright ª 2019 Published by Elsevi
https://doi.org/10.1016/j.cmet.2019.09.007Authors
Ana Latorre-Pellicer,
Ana Victoria Lechuga-Vieco,
Iain G. Johnston, ..., Nick S. Jones,
Jesu´s Ruı´z-Cabello,
Jose´ Antonio Enrı´quez
Correspondence
jaenriquez@cnic.es
In Brief
The dynamics of heteroplasmic mtDNA
populations and the factors that promote
mtDNA homogeneity remain poorly
understood. Latorre-Pellicer et al. have
discovered that heteroplasmy is checked
at oocyte maturation and in the early
embryo. mtDNA segregation can occur
on a spectrum from randomdrift to strong
selection of one of the haplotypes,
through mechanisms dependent upon
mito-nuclear interactions affecting
embryo metabolism and cell fitness.er Inc.
Cell Metabolism
Short ArticleRegulation of Mother-to-Offspring
Transmission of mtDNA Heteroplasmy
Ana Latorre-Pellicer,1,2,12 Ana Victoria Lechuga-Vieco,1,3,12 Iain G. Johnston,4 Riikka H. H€am€al€ainen,5,6 Juan Pellico,1,3
Raquel Justo-Me´ndez,1 Jose Marı´a Ferna´ndez-Toro,1 Cristina Claverı´a,1 Adela Guaras,1 Rocı´o Sierra,1 Jordi Llop,7,8
Miguel Torres,1 Luis Miguel Criado,1 Anu Suomalainen,6 Nick S. Jones,9 Jesu´s Ruı´z-Cabello,3,7,8,10
and Jose´ Antonio Enrı´quez1,11,13,*
1Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid, Spain
2Unit of Clinical Genetics and Functional Genomics, Department of Pharmacology-Physiology, School of Medicine, University of Zaragoza,
ISS-Aragon, 50009 Zaragoza, Spain
3CIBERES: C/ Melchor Ferna´ndez-Almagro 3, 28029 Madrid, Spain
4School of Biosciences, University of Birmingham, Birmingham, UK
5Department of Neurobiology, A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
6Research Program of Molecular Neurology, Biomedicum, University of Helsinki, Helsinki, Finland
7CIC biomaGUNE, Paseo Miramo´n No 182, San Sebastia´n, 20014 Guipu´zcoa, Spain
8IKERBASQUE, Basque Foundation for Science, Bilbao, Spain
9Department of Mathematics, Imperial College London, London SW7 2BB, UK
10Universidad Complutense de Madrid, Madrid 28606, Spain
11CIBERFES: C/ Melchor Ferna´ndez-Almagro 3, 28029 Madrid, Spain
12These authors contributed equally
13Lead Contact
*Correspondence: jaenriquez@cnic.es
https://doi.org/10.1016/j.cmet.2019.09.007SUMMARY
mtDNA is present in multiple copies in each cell
derived from the expansions of those in the oocyte.
Heteroplasmy, more than one mtDNA variant, may
be generated by mutagenesis, paternal mtDNA
leakage, and novel medical technologies aiming to
prevent inheritance of mtDNA-linked diseases. Het-
eroplasmy phenotypic impact remains poorly under-
stood. Mouse studies led to contradictory models of
random drift or haplotype selection for mother-to-
offspring transmission of mtDNA heteroplasmy.
Here, we show that mtDNA heteroplasmy affects em-
bryo metabolism, cell fitness, and induced pluripo-
tent stem cell (iPSC) generation. Thus, genetic and
pharmacological interventions affecting oxidative
phosphorylation (OXPHOS) modify competition
among mtDNA haplotypes during oocyte develop-
ment and/or at early embryonic stages. We showContext and Significance
Normally, one single version of mtDNA is present in a cell. Rec
would be present in the same cell (heteroplasmy). Latorre-Pell
ations in mice harboring two versions of mtDNA. During early
mtDNA variants and selectively expand one of them until it beco
specific nuclear-encoded genes and their interaction with mito
oplasmymay be used to prevent the transmission of mtDNA-lin
involve mitochondrial transfer from a donor.
1120 Cell Metabolism 30, 1120–1130, December 3, 2019 Crown Cop
This is an open access article under the CC BY-NC-ND license (http://that heteroplasmy behavior can fall on a spectrum
from random drift to strong selection, depending on
mito-nuclear interactions and metabolic factors.
Understanding heteroplasmy dynamics and its
mechanisms provide novel knowledge of a funda-
mental biological process and enhance our ability
to mitigate risks in clinical applications affecting
mtDNA transmission.
INTRODUCTION
Mitochondrial DNA (mtDNA) exists in populations within eukary-
otic cells and encodes genes that are vital for cellular energetics
and metabolism. Cellular populations of mtDNA may be geneti-
cally identical (homoplasmy) or consist of a genetic admixture
(heteroplasmy) arising from mutation, inheritance, or gene thera-
pies. The interaction between different variants of mtDNA within
the samecytoplasm is a fascinating biological problemwith evolu-
tionary, physiological, pathological, and ethical implications. It hasent observations indicate that more than one mtDNA variant
icer et al. have investigated this phenomenon across gener-
embryo development and oogenesis, the cell can detect the
mes predominant. The selection process is dependent upon
chondrial genes. This information on the regulation of heter-
ked diseases and to better designmedical technologies that
yright ª 2019 Published by Elsevier Inc.
creativecommons.org/licenses/by-nc-nd/4.0/).
come to the forefront of public awareness due to debate concern-
ing the use of mitochondrial replacement therapy in human
oocytes to prevent transmission of mtDNA-linked diseases
(Tachibana et al., 2009; Craven et al., 2010), and the proposal to
improve fertility by injecting young donor oocyte cytoplasm and
mtDNA to oocytes of sub-fertile women (Woods and Tilly, 2015).
However, the dynamics of heteroplasmic mtDNA populations
and the factors that affect these dynamics remain poorly
understood.
In mammals, mtDNA encodes a reduced number of genes: 13
mRNAs, 22 tRNAs, and 2 rRNAs. All proteins encoded in the
mtDNA are structural components of the multiprotein mitochon-
drial respiratory complexes. It is critical that these mtDNA-en-
coded proteins match physically and functionally with up to 70
nDNA-encoded structural proteins of the same complexes to
build a functional oxidative phosphorylation (OXPHOS) system.
Animal models with identical nuclear genomes but with different
mtDNA haplotypes (conplastic mice) generate functionally
different OXPHOS systems that shape organismal metabolism
(Latorre-Pellicer et al., 2016), supporting the conclusion that
different wild-type mtDNA variants have phenotypically impor-
tant consequences.
Selection between non-pathological mtDNA haplotypes in the
female germline of heteroplasmic engineered mice was first
thought not to exist (Jenuth et al., 1996), but this conclusion
has been recently questioned (Burgstaller et al., 2014; Sharpley
et al., 2012). Solving this dispute is ofmajor interest in addressing
the potential medical implications of mixed mtDNA populations.
The analysis of mtDNA heteroplasmy progression in genetically
manipulated monkey heteroplasmic oocytes revealed that, dur-
ing embryo development, one of the mtDNA variants may
become predominant (Lee et al., 2012). In human embryonic
stem cells (ESCs) derived from embryos cultured in vivo after
nuclear transfer to exchange mtDNA complements, similar
expansion of the residual mtDNA haplotype has been observed
(Kang et al., 2016; Yamada et al., 2016). Very recently, expansion
of the minority copies of paternal mtDNA (70 versus 200,000)
was documented in human families where the active elimination
of the sperm mitochondria failed (Luo et al., 2018). The driving
forces responsible for the selective advantage of mtDNA during
embryo development is still unknown.
Here, we address these questions by elucidating mtDNA
behavior between non-pathological mtDNA variants in unprece-
dented detail in a set of novel model organisms. We identify
stages at which mtDNA haplotype selection occurs during early
embryo development and a set of metabolic and nuclear genetic
factors that drive this selection.
RESULTS
mtDNA Competition at Early Embryonic Stages
We generated heteroplasmic mice by electro-fusion of an em-
bryo and an enucleated embryo. The nuclear genome from
C57BL/6JOlaHsd strain was combined with mtDNA either of
NZB/OlaHsd (BL/6NZB) or of C57BL/6JOlaHsd (BL/6C57). The
heteroplasmic offspring (named BL/6C57-NZB) were mated with
C57BL/6JOlaHsd males to prevent nuclear genetic drift in our
particular mice strains. We did not observe any adverse effect
of the heteroplasmy in ovary, embryo development, or fertility(Figures S1A and S1B). Only the offsprings of the established
heteroplasmic mice were used.
During female germline maturation, mtDNA undergoes a ge-
netic bottleneck where random drift and positive selection may
both act to strongly reduce heteroplasmy in cells (Johnston
et al., 2015). A parallel assessment of heteroplasmy in gonads
(ovary and testis) and in germline cells revealed that both oo-
cytes and spermatozoa progressively select for C57 mtDNA
with age despite their rather dissimilar differentiation process
(Figures 1A and 1B). Oocytes are the cells with the highest
mtDNA content, up to 200,000 copies per cell (Piko´ and Taylor,
1987), while sperm mtDNA content is among the lowest
(70 copies per cell) (Dı´ez-Sa´nchez et al., 2003). Whole-ovary
analysis also showed a significant tendency to accumulate
C57 mtDNA while testes accumulated NZB mtDNA (Figures 1A
and 1B). Therefore, the mtDNA extracted from ovaries is a
good proxy of the behavior of the oocyte mtDNA heteroplasmy,
whereas the analysis of testis cannot inform us about the sperm
mtDNA heteroplasmy.
How does this selection of C57 mtDNA in ovaries occur? In
fetal stage, during early oogenesis, there is a substantial in-
crease in mtDNA copy number (10 to 20 times [Wai et al.,
2008]). Post-natal maturation of the oocytes for ovulation re-
quires a further mtDNA replication activity with a burst in mtDNA
copy number (Johnston et al., 2015; Wai et al., 2008). Analysis of
the ovary at different ages of the mother showed that the mtDNA
haplotype (C57 or NZB) modifies the proportion of follicles at
different stages of maturation, with a better maintenance of the
ovary function with NZB mtDNA. In particular, the proportion of
primordial follicles at early age is increased in the presence of
NZB mtDNA with respect to that shown in homoplasmic C57
mtDNA (Figure S1C). Heteroplasmy induces an accelerated
loss of primary oocytes (Figure S1C). This loss may suggest
either a selection against subpopulations of follicles with higher
proportion of NZB mtDNA or, alternatively, an earlier maturation
of oocytes with higher content of NZB mtDNA. However, addi-
tional mtDNA intracellular selection within oocytes with age
can also occur. Either scenario could explain the shift in hetero-
plasmy towardmore C57mtDNAwith the age of themother. Wai
and Shoubridge (Wai et al., 2008) reported a significant increase
in NZB mtDNA in more mature oocytes when studying hetero-
plasmy dynamics (Balb/c versus NZB mtDNA haplotypes) be-
tween primary follicles and secondary follicles (between post-
natal day 1 and post-natal day 29), but this observation cannot
rule out the alternative explanations. Moreover, the analysis
of over 900 pups reveal that the C57 mtDNA is significantly
favored, with a 45:1 proportion of homoplasmic C57 versus
NZB (Figure 1C).
Based on these heteroplasmy changes observed in ovaries,
the intergenerational heteroplasmy shift between mother and
offspring (measured by comparing tail measurements at day
21) was predicted to increase with the mother’s age at pup birth.
Our observations indeed indicate a selective segregation in favor
of C57 mtDNA haplotype from heteroplasmic mothers to pups
(Figure 1C). However, the female germline segregation inferred
through ovary mtDNA dynamics cannot account in full for the
observed mother-to-pup shift in mtDNA heteroplasmy (Fig-
ure 1C), suggesting that additional selection in favor of C57
mtDNA haplotype takes place during gestation.Cell Metabolism 30, 1120–1130, December 3, 2019 1121
A B
D
F
C
E
Figure 1. Heteroplasmy Is Sensed and
mtDNA Segregated Prenatally
(A) Convergence in heteroplasmic proportions
between ovary (red, p = 1.2 3 10
4 against zero
segregation) and oocytes (blue, p = 3.7 3 10
4
against zero segregation) (n = 110 oocytes and n =
13 ovaries from 13 BL/6C57-NZB females).
(B) Divergence in the heteroplasmic proportion
between testis (red, p = 7.6 3 10
6 against zero
segregation) and spermatozoa (blue, p = 1.53 10
4
against zero segregation) (n = 18).
In (A) and (B), the candlesticks show heteroplasmy
statistics amalgamated over time, compared to a
zero-change null hypothesis.
(C) Heteroplasmy shift between mother’s tail
sampled at 21 days old and pup’s tail sampled
at 21 days old (vertical axis), as a function of the
mother’s age when the pup was born (horizontal
axis). Red lines show a fit, with 95% CI, to a
linear decrease in transformed heteroplasmy
(STAR Methods) with mother’s age. Black line
shows the predicted trend from the inferred
developmental shift and ovarian segregation;
alone, it cannot explain the observed shift
in heteroplasmy between mothers and their
offspring (pups = 819 from 43 BL/6C57-NZB
females, ovary = 73 from BL/6C57-NZB females).
(D) Shifts in heteroplasmy, relative to ovary het-
eroplasmy, observed upon a change into each
pluripotency class. The classes are 0 (ovary, n =
73), I (oocyte, n = 110), II (2.5 dpc embryos, n =
101), III (5.5 dpc embryos, n = 21, p = 1.03 10
13
against zero segregation, p = 4.7 3 10
6 against
identity to II), and IV (13.5 dpc embryos, n = 161,
p = 3.0 3 10
9 against zero segregation). Pink
dots represent heteroplasmy level in the indi-
cated embryo class samples, and blue dots
represent heteroplasmy in iPSCs derived from
MEF lines stablished from class IV embryos.
Heteroplasmy changes are tested against
a zero-change null hypothesis, and between
classes.
(E and F) Variability in heteroplasmy between embryos of the same litter at 13.5 (n = 9) (E) or 17.5 dpc (n = 10) (F) and between the indicated tissues.
In (A)–(C), (E), and (F), transformed heteroplasmy shift using tail as the reference tissue. In (E) and (F), comparisons assessed by Mann-Whitney test and one-
way ANOVA; Tukey’s range test correction for multiple comparison (*p < 0.05; **p < 0.01; ***p < 0.001).Pursuing this observation, we found that a very fast shift in het-
eroplasmy happened during early development between 2.5 and
5.5 days post-coitum (dpc), which includes the implantation and
pre-gastrula post-implantation stages (Figure 1D). No evidence
of selection could be observed between 5.5 and 13.5 dpc
embryos (Figures 1D, 1E, and S1D). At 17.5 dpc, heart and brown
adipose tissue (BAT) revealed selection in favor of C57 and NZB
mtDNAs respectively (Figures 1F and S1D). Interestingly, placenta
did not show any mtDNA haplotype preference at any stage.
In summary, mother-to-pup development of heteroplasmy has
dual contributions, both from positive selection for C57 in devel-
oping oocytes and additional positive selection in early embryo-
genesis. This dual selection mirrors the dynamics observed in
another heteroplasmic mouse model (Burgstaller et al., 2018).
Heteroplasmy Alters Metabolism of Mouse Embryonic
Fibroblast and of the Embryo
We next asked whether metabolic factors may be responsible for
these mtDNA selection patterns. Recently, we demonstrated that1122 Cell Metabolism 30, 1120–1130, December 3, 2019the two mtDNA variants (NZB or C57) determine qualitatively
different OXPHOS performance in mice (Latorre-Pellicer et al.,
2016), confirming our previous observations in cybrid cell lines
(Moreno-Loshuertos et al., 2006). To investigatewhether suchvar-
iations in OXPHOS function influence mtDNA haplotype segrega-
tion, we isolated mouse embryonic fibroblasts (MEFs) from post-
implantation embryos of the homoplasmic strains, BL/6C57 and
BL/6NZB, and from heteroplasmic mice, BL/6C57-NZB, with three
different proportions of heteroplasmy (Figure 2). To guarantee
that they were true heteroplasmic cells and not a mix of cells
withdifferentmtDNAs, heteroplasmywasassessedusingpadlock
probes to detect in situ each mitochondrial DNA haplotype by
confocal fluorescencemicroscopy. In thisway,wecould conclude
that heteroplasmy is intracellular and not intercellular (Figure 2A),
as both mtDNA variants co-exist in the same cytoplasm.
Interestingly, heteroplasmic MEFs showed a consistent
reduction in basal andmaximum respiration capacity, regardless
of the proportion of heteroplasmy and the carbon source (Fig-
ures 2B and 2C). The presence of any level of heteroplasmy
BD E F
C
G
J K
H I
A
(legend on next page)
Cell Metabolism 30, 1120–1130, December 3, 2019 1123
induced elevatedmitochondrial membrane potential (MMP) (Fig-
ure 2D) and higher reactive oxygen species (ROS) production
(Figure 2E), one order of magnitude higher than the homoplasmic
MEFs when normalized by the maximum respiration rate (MRR)
(Figure 2F). We further observed that these functional conse-
quences feed back onto the dynamics of mtDNA populations.
MEFs maintained heteroplasmy levels when grown in glucose
over-rich medium, whereas they favored NZB mtDNA at physio-
logical concentrations of glucose and shifted towardC57mtDNA
in amedium promoting OXPHOS, when glucose was substituted
by galactose (Figures 2G and S1E).
Following these observations, we asked whether these meta-
bolic impacts of heteroplasmy in cultured MEFs reflected similar
impacts in vivo. We investigated the metabolic poise of 12.5 dpc
embryos by determining their ability to uptake 18F-Fluorodeoxy-
glucose ([18F]-FDG) or 18F-Fluoromisonidazole ([18F]-FMISO) us-
ing positron emission tomography and computed tomography
(PET-CT). In addition, we quantified the uptake of the probes
by gamma counter in isolated embryos. In this way, we could
estimate the embryo glucose demands ([18F]-FDG) and oxygen
utilization in correlation with their heteroplasmy proportion.
Notice that the ([18F]-FMISO) is an inverse indicator of oxygen
consumption since the signal increase in hypoxic status (Grimes
et al., 2017; Corroyer-Dulmont et al., 2015; Warren and Par-
tridge, 2016). We found that glucose uptake is decreased (Fig-
ures 2H and S1F) and oxygen level higher (Figures 2I, S1G,
and S1H) when NZB mtDNA predominates (Figure S1H; 100%
NZB mtDNA). This observation in the embryo is reminiscent of
our previous results showing that NZB and C57 mtDNAs pro-
mote differential organismal metabolism (Latorre-Pellicer et al.,
2016). The PET-CT analysis indicates that the energetic meta-
bolism of the embryos, with high glycolytic predominance, can
be modulated between more oxidative versus more glycolytic
metabolism (Figures 2H, 2I, and S1H).
We next sought to characterize the influence of mtDNA popu-
lation structure on metabolic poise at a finer-grained, molecular
scale. To this end, we isolated 12.5 dpc embryos from the homo-
plasmic and heteroplasmic strains and analyzed the organization
of the mitochondrial electron transport chain by blue native elec-
trophoresis (BNE). We found that the CI + CIII2/CI ratio is
decreased in homoplasmic NZB animals with respect to homo-
plasmic C57 (Figure 2J). We described elsewhere that in mostFigure 2. Heteroplasmy Modulates MEF and Embryonic Metabolism
(A) Identification of C57 and NZB mtDNA haplotypes in MEFs by in situ fluoresce
(B–F) Metabolic performance of MEFs derived from 12.5 dpc embryos of hom
Oxygen consumption rate (OCR) of intact cells estimated by SeaHorse at (B) 5mM
H2O2 production per cell or (F) per maximum respiration (OCR) capacity.
(G) Dynamics of mtDNA segregation in MEFs under different nutritional conditions
segregation (left); galactose shows significant support for a model where there i
21 days (center, likelihood ratio test, p < 0.05) (n = 3BL/6C57-NZB immortalizedMEF
and 47% of NZB mtDNA respectively).
(H and I) Determination of [18F]-FDG (H) or [18F]-FMISO (I) uptake measured by gam
dot represents an individual embryo; colors indicate embryos from the same litte
(J) BNE showing the assembly and superassembly status of respiratory comple
perassembly status (right) (n = 3 homoplasmic embryos and n = 4 heteroplasmic
(K) Western blot (top) and metabolic BEC index (ATPB/GADPH) quantification (b
indicated embryo strains (n = 5 homoplasmic embryos and n = 8 heteroplasmic e
****p < 0.0001).
See Tables S1 and S2 for antibodies utilized in western blot and padlock probes
1124 Cell Metabolism 30, 1120–1130, December 3, 2019C57BL/6 tissues, respiratory complex I is mainly distributed be-
tween the free monomer CI and the super-assembled CI + CIII2
(Cogliati et al., 2016). We also showed that the relative ratio of
CI + CIII2/CI is adapted by the mitochondria according to avail-
able fuel, being higher when glutamate or pyruvate is the main
source of electrons and reduced when fatty acids are the pre-
dominant source (Guara´s et al., 2016). The substitution of C57
by NZB haplotype in homoplasmic animals induced a shift in
the fuel use by mitochondria in adult liver and also reduces the
CI + CIII2/CI ratio (Latorre-Pellicer et al., 2016). In heteroplasmic
embryos, we observed an exacerbated decrease in the CI +
CIII2/CI compared to homoplasmic NZB embryos (Figure 2J).
Looking at another molecular-scale readout of metabolic
poise, we next assessed the relative contribution of glycolytic
versus oxidative ATP production in the embryos by determining
the bioenergetic cellular (BEC) index (Cuezva et al., 2004). The
BEC index is calculated by the estimation of the ratio of expres-
sion between the beta subunit of the mitochondrial H+-ATP syn-
thase and a critical protein of the glycolysis (GAPDH) by western
blot. This index was decreased in heteroplasmic versus homo-
plasmic embryos suggesting, as it was observed in MEFs, that
heteroplasmy impacts on the mitochondrial OXPHOS efficiency
(Figure 2K).
Thus, once more, we find that the presence of heteroplasmy
has a qualitatively different effect on the metabolic poise of
MEFs and embryos than would be expected as a simple combi-
nation of homoplasmic contributions.
Embryonic mtDNA Segregation Is Associated with
Pluripotency
Despite the metabolic impact of mtDNA heteroplasmy on MEFs
and embryos during gestation, dynamic changes in hetero-
plasmy seem largely restricted to a short period in early develop-
ment. Since the observed stages of the segregation coincide
with the appearance of pluripotency in the embryo epiblast, we
decided to study the relationship between mtDNA heteroplasmy
and pluripotency. We generated induced pluripotent stem cells
(iPSCs) from BL/6C57, BL/6NZB, and heteroplasmic BL/6C57-NZB
MEFs in order to reprogram their differentiation status toward
pluripotency. Interestingly, cultured BL/6C57-NZB iPSCs strongly
selected against NZB mtDNA (Figure 3A). Unexpectedly, we
noticed a significant decrease in the reprogramming efficiencynce. In blue is labeled the nucleus; in green, mtDNA C57; in red, mtDNA NZB.
oplasmic or heteroplasmic mice. Heteroplasmy indicates % of NZB mtDNA.
glucose and (C) 5mMgalactose. (D) Mitochondrial membrane potential and (E)
: 25 mM glucose displays no segregation (right); 5 mM glucose displays linear
s no heteroplasmy change in early treatment, followed by fast decrease after
lines per treatment during 62 days of culture. Initial heteroplasmy levels: 43, 46,
ma counter in 12.5 dpc embryos with different degrees of heteroplasmy. Each
r.
xes in the indicated 12.5 dpc embryos (left) and the proportion of the CI su-
embryos).
ottom) of the relative proportion of glycolytic versus oxidative capacity in the
mbryos) (mean ± SD, one-way ANOVA test, *p < 0.05; **p < 0.01; ***p < 0.001;
, respectively.
D E
BA C
Figure 3. Heteroplasmy Modulates Pluripotency
(A) Left: heteroplasmy shift between themean of the MEF set and individual derived iPSCs, showing a significant departure from zero (n = 80 iPSCs clones from 4
different MEFs BL/6C57-NZB lines, p = 1.43 10
11 against zero segregation). Heteroplasmy change with iPSC passage, with the heteroplasmy of the first passage
as the reference value, and the x axis labeling subsequent passages (n = 8 iPSCs BL/6C57-NZB lines); lines show mean linear fit and 95% CI.
(B) iPSC reprogramming efficiency of BL/6C57, BL/6NZB, and BL/6C57-NZB MEFs under 21%O2 (n = 7 per genotype), 21%O2 (n = 4 per genotype) plus 1 mMNAC,
and 4% O2 (n = 4 per genotype) (mean ± SD, two-tailed t test, *p < 0.05; **p < 0.01; ***p < 0.001).
(C) Alkaline phosphatase (AP) staining of iPSC colonies 14 days after transposon-mediated gene transfer.
(D) Heteroplasmy shift between themean of the MEFs set and individual MEFs, individual iPSCs reprogrammed under 21%O2 (n = 50 iPSC clones), 21%O2 plus
1 mM NAC (n = 45 iPSC clones), and 4% O2 (n = 9 iPSC clones) (mean ± SD, ANOVA test, *p < 0.05; **p < 0.01).
(E) Heteroplasmy shift betweenmother and pups for mice treated with NAC. Red lines show the fit to a linear decrease in transformed heteroplasmywithmother’s
age from untreated animals (control mean andCI obtained from Figure 1C data points). Blue lines show a fit with 95%CI to the heteroplasmy shift betweenmother
tail at 21 dpc and pups at 21 dpc with NAC administration in drinking water to mother during gestation (n = 52 pups from 9 BL/6C57-NZB females treated with NAC).of MEFs obtained from conplastic BL/6NZB and heteroplasmic
BL/6C57-NZB animals when compared with MEFs from BL/6C57
mice (Figures 3B and 3C). These results are in agreement with
a theoretical study elucidating the dependence of pluripotency
on mitochondrial status (Johnston et al., 2012) and resemble
what was reported for mutator mice that carry a load of mtDNA
heteroplasmy (H€am€al€ainen et al., 2015). Moreover, we observed
that NZB mtDNA was preferentially lost upon reprogramming of
BL/6C57-NZB MEFs (Figure 3D). Using culture conditions with 4%
oxygen, the reprogramming efficiency increased in MEFs
regardless of their mtDNA content, but oxygen concentration
did not prevent the heteroplasmic shift (Figures 3B and 3D).
We demonstrated elsewhere that the primary difference
induced by the interchange of the mtDNA haplotypes NZB and
C57 is the higher ROS signaling generated by NZB mtDNA (La-
torre-Pellicer et al., 2016; Moreno-Loshuertos et al., 2006).
Here, we found that heteroplasmic MEFs generate high levels
of ROS (Figures 2E and 2F). To pursue the potential role of
ROS in reprogramming, we generated iPSCs in the presence
of 1 mM N-acetyl-L-cysteine (NAC), an antioxidant and reduc-tant. We found that reprogramming efficiency increased signifi-
cantly in MEFs derived from BL/6NZB and BL/6C57-NZB embryos
without affecting that of BL/6C57 MEFs (Figures 3B and 3C).
Moreover, the presence of NAC eliminated the heteroplasmic
shift during MEFs to iPSCs reprogramming (Figure 3D). Overall,
this behavior is reminiscent of the observed reduction in iPSCs
reprogramming efficiency associated with elevated mitochon-
drial ROS and the demonstration of negative selection against
mutant mtDNA by pluripotent stem cells (H€am€al€ainen et al.,
2015). Remarkably, per-oral NAC treatment provided to the
BL/6C57-NZB pregnant females in their drinking water abolished
the observed early embryonic shift in heteroplasmy (Figure 3E).
In the presence of NAC, the mtDNA selection during oocyte
maturation can account in full for the heteroplasmic shift
between the mother and pups (Figure 3E).
These results suggest that mtDNA haplotype has a substantial
effect on reprogramming efficiency and pluripotency of cells,
which likely manifest at least in part by levels of ROS production,
and reminiscent of the above feedback loops, the differentiation
process places selective pressure on cellular mtDNA populations.Cell Metabolism 30, 1120–1130, December 3, 2019 1125
AC D
B
Figure 4. MtDNA Haplotype Competition in Oocyte Biogenesis and Embryo Development Are Determined by Nuclear Context
(A) Mother-to-pup heteroplasmic shift in the inbred (homozygote) C57BL/6 nuclear background (data from Figure 1C), compared with the F1 of BL/6C57-NZB
females with NZBNZB males to generate a non-inbred (heterozygote) background. Each dot corresponds to a different individual.
(B) Evaluation of ovary heteroplasmywith the age of themother in heteroplasmic femaleswith alterations in the indicated nuclear geneswith respect to the original
heteroplasmic animal (see Figure 1A). Each dot represents the heteroplasmy shift of the ovary from a different female.
(C) Comparative behavior of the mother-to-pup heteroplasmic shift with the age of the mother in heteroplasmic strains, with alterations in the indicated nuclear
genes. Each dot corresponds to a different individual.
(A–C) Significant non-zero slope, linear regression, *p < 0.05, **p < 0.01, ***p < 0.001.
(D) Heteroplasmy development between pluripotent classes 0 (ovary) and III (5.5–6.5 dpc embryos) in heteroplasmic lines with alterations in the indicated nuclear
genes (mean ± SD, two-tailed t test, *p < 0.05). Eye and tail were used as the reference tissues to calculate the heteroplasmy shift.Embryonic mtDNA Segregation Is Determined by
Nuclear-Mitochondrial Interaction
All the studies on mtDNA segregation performed in mouse
models use inbred strains that are homozygotic for most of their
nuclear genes. This situation is rather unnatural: in every
generation, maternally transmitted mtDNA is confronted with
new nuclear alleles that offer novel variability in nuclear-encoded
mitochondrial genes from the father. To translate our observa-
tions into a more realistic situation, we bred heteroplasmic
females with NZB/OlaHsd males to induce heterozygosity in
the first generation of heteroplasmic animals. Strikingly, the
induction of heterozygosity markedly reduces the observed
embryonic selection toward C57 mtDNA (Figure 4A).
To investigate the mechanism behind this mito-nuclear inter-
action, we next focused on specific genes known tomildly influ-
ence mitochondrial performance that can differ between
NZB/OlaHsd and C57BL/6 strains: supercomplex assembly
factor 1 (SCAF1 or Cox7a2l) and the nicotinamide nucleotide
transhydrogenase (NNT). SCAF1 is required for the superas-
sembly between complexes III and IV of the mitochondrial elec-
tron transport chain (Cogliati et al., 2016), and it is mutated in all
C57BL/6 sub-strains, which have lost this capacity without ma-
jor effects on health or fertility (Lapuente-Brun et al., 2013). NNT
is an integral mitochondrial inner membrane enzyme that1126 Cell Metabolism 30, 1120–1130, December 3, 2019couples the hydride transfer between NAD(H) and NADP(+) to
proton translocation across the inner membrane to produce
NADPH in the mitochondrial matrix. NNT is needed for biosyn-
thetic processes and free radical detoxification. The C57BL/6J
sub-strain naturally lacks functional NNT. Despite this, the an-
imals are healthy and fertile but lose versatility in the proper
adaptation of OXPHOS to environmental changes and may
develop some minor impairments (Picard et al., 2015). The
NZB/OlaHsd strains harbor the wild-type version of both genes,
while our heteroplasmic animals harbor the mutant version of
SCAF1 and the wild-type version of the NNT. Finally, we also
considered nuclear factors controllingmitochondrial dynamics.
Mitochondrial fission is related to autophagy and removal of
mitochondria via mitophagy and hence can shape the genetic
structure of cellular mtDNA populations (Shirihai et al., 2015).
Tissue-specific response to mtDNA segregation in heteroplas-
mic mice with mutated dynamin-related protein 1 (DRP)
involved in mitochondrial fission has been reported (Jokinen
et al., 2016). Other fusion proteins (i.e., MFN1, MFN2, and
OPA1) may play a crucial role in mtDNA nucleoids segregation
(Carelli et al., 2015). It is possible that functional variations
in these (and/or other) genes could impact mitochondrial func-
tion and influence mtDNA segregation during germline
transmission.
To explore the interplay between these processes and mtDNA
population structure, we generated three novel heteroplasmic
mousemodels to assess the relative relevance formtDNA segre-
gation of (1) the relevance of ROS signaling/detoxification
(NNTKOmice), (2) the role of the superassembly of the respiratory
complexes (SCAF1113 mice), or (3) the mechanism of fragmenta-
tion and removal of damaged mitochondria under stress
(OMA1KO mice).
First, we evaluated whether variability in these nuclear genes
impacts on the previously observed segregation of mtDNA in
ovary with the age of the mother. Comparison between each ge-
notype with the control heteroplasmic group showed that the
three different nuclear modifications alter the original segrega-
tion toward C57 mtDNA in ovaries with age (compare
Figure 1A with Figure 4B). Thus, BL/6C57-NZB:NNTKO and
BL/6C57-NZB:OMA1KO showed no segregation preference, while
BL/6C57-NZB:SCAF1113 shifted their preference from C57 toward
NZB mtDNA. Next, we evaluated if variability in these nuclear
genes impacts themother-to-pup transmission of heteroplasmy.
For that, tail heteroplasmic levels of the mothers from different
strains were measured at the time of weaning. In agreement
with the lack of preferences in ovary (Figure 4B), the ablation of
NNT or OMA1 erased the preference toward C57 mtDNA during
mother-to-pup transmission observed in the control heteroplas-
mic animals (compare Figure 1C with Figure 4C). Surprisingly,
the tendency to favor NZB in ovaries induced by the re-expres-
sion of SCAF1 was fully reverted in mother-to-pup transmission,
which again showed a preference in favor of C57 mtDNA (Fig-
ure 4C). The coherence between the lack of preferential segrega-
tion in ovary and mother-to-pup strongly suggests that the
observed phenomenon of embryonic segregation was also lost
when NNT or OMA1 genes are ablated. In fact, no changes in
the heteroplasmic proportions between ovary and 6.5 dpc em-
bryos could be detected (Figure 4D).
On the other hand, the change in preferred mtDNA in ovary
(NZB instead of C57) in mother-to-pup shown in SCAF1113
animals predicts that the embryo-stage segregation in favor of
C57 mtDNA should be strong. In agreement with this prediction,
we found that the heteroplasmic proportion between mother
ovary and 6.5 days embryos in SCAF113 animals experiences a
drastic shift toward C57 mtDNA haplotype, indicative of a strong
mtDNA selection during early embryo development.
DISCUSSION
We have shown here that intergenerational wild-type mtDNA
haplotype selection is common and depends on the impact of
the mtDNA haplotype on the performance of the OXPHOS sys-
tem.We described that in addition to themtDNA selection during
female germline maturation, a second step of mtDNA selection
happened at early embryonic stages. Fuel preference, mito-
chondrial dynamics regulation, and differential mitochondrial
ROS handling all play a substantial role in the driving force of
the selection. This dependence helps to resolve one of the his-
toric debates on the topic of mtDNA selection: under a variety
of different circumstances, which we reveal and quantify,
different degrees of mtDNA selection (including none) may be
observed. Together, these observations reflect that the commu-
nication between mtDNA and the nuclear genome determinesthe dynamics of cellular mtDNA populations: selection of one
or other of the haplotypes or no selection at all. Our data provide
an explanation for apparently conflicting conclusions resulting
from the diverse nuclear genotypes of the inbred mouse strains
used (Jenuth et al., 1996; Sharpley et al., 2012).
If wild-type mtDNA haplotype variability can cause sufficient
functional differences to trigger segregation, it is expected that
overtly pathological haplotypes would exert a stronger impact.
In this sense, the only two available examples in mice concluded
that pathological mutations are selectively eliminated through
germline transmission (Fan et al., 2008; Stewart et al., 2008). In
both mouse models a similar, but not identical, nuclear back-
ground was used. The report from Wallace’s laboratory (Fan
et al., 2008) used mouse female ESC line CC9.3.1 isolated from
129SvEv-Gpilc embryo (129 mice are wild type for NNT and
SCAF1113). ESCs harboring the mutant mtDNA were injected in
C57BL/6NHsd female blastocysts and transferred into pseudo-
pregnant females. After that, female chimeras were identified
and mated with C57BL6/J males (NNTKO, SCAF1111). Therefore,
although the genotype for these two genes is uncertain, they
should shift to NNTKO, SCAF1111 with subsequent crosses, a ge-
netic context that may enhance mother-to-offspring segregation.
Interestingly, they reported that the severe mutation that they fol-
lowed in heteroplasmy (ND6 frameshift) completely disappears in
subsequent litters of the same female and in along two or three
generations (Fan et al., 2008). The report from Stewart and co-
workers investigated the fate of mtDNA mutations generated in
the mtDNA-mutator mice were the functional gamma-pol was
restored (Stewart et al., 2008). All the studies were performed in
the C57BL/6N background (NNTWT and SCAF1111) the nuclear
context in which we found themore efficient segregation between
mother-to-offspring mtDNA transmission. It is in this context
where Stewart and co-workers found a very strong selection
against missense mutations.
In contrast to the studies in mice, selective elimination of the
defective mtDNA in humans does not always operate. An array
of behaviors from random drift to positive or negative selection
for the mutated mtDNA was documented (Otten et al., 2018).
We propose that differences in nuclear background may be
responsible for this discrepancy between mice and humans
and that further studies in mouse models should be performed
to evaluate this issue.
The relationship between mitochondrial ROS and hetero-
plasmy has been previously highlighted (H€am€al€ainen et al.,
2013). Thus, elevated levels of H2O2 production by mitochondria
caused by elevated mtDNA mutagenesis, disrupted cellular
redox signaling and, as a consequence of that, reduced pluripo-
tent stem cell reprogramming efficiency and self-renewal capac-
ity (H€am€al€ainen et al., 2015). On the other hand, iPSC generation
from human patients harboring elevated levels of the 3,243 com-
mon MELAS mutation induced a drastic selective response
against heteroplasmy (H€am€al€ainen et al., 2013). Both observa-
tions are consistent with those reported here and reinforce the
relevance of mitochondrial mediated ROS signaling and its
sensitivity to mtDNA variations or mutations. Thus, the use of an-
tioxidants (NAC) or a genetic nuclear background were mito-
chondrial ROS handling is impaired (lack of NNT), obliterate
the specific ROS signal that drives the differentiation between
NZB and C57 mtDNA haplotypes. In the same line of thought,Cell Metabolism 30, 1120–1130, December 3, 2019 1127
part of the effects induced by the recovery of the wild-type
version of SCAF1 may be related to its effects in ROS handling,
although it has also implication in the adaptation to cell stress
(Balsa et al., 2019). The improved understanding of the molecu-
lar link between ROS and mtDNA haplotype selection may open
an unexplored way to prevent the transmission of mtDNA-linked
diseases. By the same token, understanding how mitochondrial
quality control and the regulation of OXPHOS dynamics is trans-
duced into the molecular mechanisms that drive non-random
mtDNA segregation will open the possibility to prevent the
maternal transmission of mtDNA-linked diseases.
Mitochondria from the sperm enter the oocyte upon fertilization
(Cummins, 2000). Two concurrent mechanism guarantee unipa-
rental transmission, the active elimination of the paternal mito-
chondria (Sato and Sato, 2011; Zhou et al., 2016) and the enor-
mous dilution of the paternal mtDNA (100 copies among
200,000 copies). The mechanism of elimination of the sperm
mitochondria may ‘‘leak,’’ generating heteroplasmy in mammals
(Gyllensten et al., 1991; Zhao et al., 2004), flies (Dokianakis and
Ladoukakis, 2014), and also in humans (Luo et al., 2018; Schwartz
and Vissing, 2002), but these are considered very rare cases.
However, this possibility, together with the potential artificial gen-
eration of mtDNA heteroplasmy by novel medical technologies,
highlights the relevance to understand the implications and dy-
namics of confronting different pairs of human mtDNA variants.
Limitations of Study
Our study assessed the behavior of two defined mtDNA haplo-
types under one homozygote nuclear genetic background. The
question of at which extension our observations can be consid-
ered frequent within the mtDNA and nDNA genetic context in
mammals in general and in humans in particular, may require
further confirmation. In this sense, a very recent publication
from the group of Chinnery in Cambridge, UK, documented the
existence of selective segregation of mtDNA in the human germ-
line driven by the nuclear background. They found that this
impact is so strong that it can be observed in just one generation
(Wei et al., 2019). Therefore, in accordance with this report, the
observed nDNA/mtDNA interaction may not be a peculiarity of
a given genetic context inmice (C57BL/6) but a general phenom-
enon occurring also in human populations.
STAR+METHODS
Detailed methods are provided in the online version of this paper
and include the following:
d KEY RESOURCES TABLE
d LEAD CONTACT AND MATERIALS AVAILABILITY
d EXPERIMENTAL MODEL AND SUBJECT DETAILS112B Animal Models
B Cellular Models
d METHOD DETAILS
B Molecular Confirmation and Quantification of Hetero-
plasmy
B Padlock Probes
B Oocyte Collection
B Embryo Collection
B Sperm Collection8 Cell Metabolism 30, 1120–1130, December 3, 2019B In Vitro mtDNA Segregation Studies
B SeaHorse Analysis
B Histological Analysis of the Ovary
B Mitochondrial Membrane Potential (MMP) and ROS
Assessment in MEFs
B Blue Native Gel Electrophoresis
B Western Blot
B PET-CT in Embryos
d QUANTIFICATION AND STATISTICAL ANALYSIS
B Heteroplasmy Statistical Analysis
B General Statistical Analysis
d DATA AND CODE AVAILABILITY
SUPPLEMENTAL INFORMATION
Supplemental Information can be found online at https://doi.org/10.1016/j.
cmet.2019.09.007.
ACKNOWLEDGMENTS
We thank Dr. C. Lo´pez-Otin for the OMA1KO mice; Dra. R. Martı´nez-de-
Mena, I. Martinez-Carrascoso, M.M. Mun˜oz-Hernandez, A. Gonzalez-
Guerra, E.R. Martı´nez-Jime´nez, and Dr. Concepcio´n Jimenez for technical
assistance; M. Cueva and R. A´lvarez for mouse work; and A. Molina-Iracheta
and R. Doohan for histology. A.V.L.-V. was supported by fellowship SVP-
2013-068089 from MCIU. I.G.J. thanks ERC StG EvoConBiO, and a Turing
fellowship from the Alan Turing Institute. N.J. thanks EP/N014529/1.
SAF2017-84494-C2-R and Programa Red Guipuzcoana de Ciencia, Tecno-
logı´a e Informacio´n 2018-CIEN-000058-01, and the Basque Government un-
der its ELKARTEK research program (ref: KK-2019/00015) to J.R.-C. The
work at CIC biomaGUNE was performed under the Maria de Maeztu Units
of Excellence Program from the Spanish State Research Agency – Grant
No. MDM-2017-0720. This study was supported by grants from the MCNU
(SAF2015-65633-R), the EU (UE0/MCA317433), the Biomedical Research
Networking Center on Frailty and Healthy Ageing (CIBERFES-ISCiii), and
the HFSP agency (RGP0016/2018) to J.A.E. The CNIC is supported by the
Instituto de Salud Carlos III (ISCIII), the Ministerio de Ciencia, Innovacio´n y
Universidades (MCNU), and the Pro CNIC Foundation, and is a Severo
Ochoa Center of Excellence (SEV-2015-0505).
AUTHOR CONTRIBUTIONS
A.L.-P. and A.V.L.-V. performed most of the mouse and experimental work
with the help of R.J.-M. I.G.J. and N.S.J. performed the data analysis and
mathematical modeling. J.M.F.-T. and L.M.C. generated the heteroplasmic
animals. A.V.L.-V., J.P., and J.R.-C. performed and analyzed the in vivo imag-
ing data. J.L. provided the radiotracers. R.H.H. and A.S. contributed to the
generation and analysis of the iPSC and commented on the manuscript.
A.G., C.C., R.S., and M.T. contributed to the embryo manipulation and anal-
ysis. J.A.E., A.L.-P., and A.V.L.-V. participated in the design of the experi-
mental work, the integrated analysis of the results, and the writing of themanu-
script. J.A.E. directed and designed the research.
DECLARATION OF INTERESTS
The authors declare no competing interests.
Received: January 22, 2019
Revised: June 12, 2019
Accepted: September 10, 2019
Published: October 3, 2019
REFERENCES
Balsa, E., Soustek, M.S., Thomas, A., Cogliati, S., Garcı´a-Poyatos, C., Martı´n-
Garcı´a, E., Jedrychowski, M., Gygi, S.P., Enriquez, J.A., and Puigserver, P.
(2019). ER and nutrient stress promote assembly of respiratory chain super-
complexes through the PERK-eIF2a axis. Mol. Cell 74, 877–890.e6.
Burgstaller, J.P., Johnston, I.G., Jones, N.S., Albrechtova´, J., Kolbe, T., Vogl,
C., Futschik, A., Mayrhofer, C., Klein, D., Sabitzer, S., et al. (2014). MtDNA
segregation in heteroplasmic tissues is common in vivo and modulated by
haplotype differences and developmental stage. Cell Rep. 7, 2031–2041.
Burgstaller, J.P., Kolbe, T., Havlicek, V., Hembach, S., Poulton, J., Pia´lek, J.,
Steinborn, R., R€ulicke, T., Brem, G., Jones, N.S., et al. (2018). Large-scale ge-
netic analysis reveals mammalian mtDNA heteroplasmy dynamics and vari-
ance increase through lifetimes and generations. Nat. Commun. 9, 2488.
Carelli, V., Maresca, A., Caporali, L., Trifunov, S., Zanna, C., and Rugolo, M.
(2015). Mitochondria: biogenesis and mitophagy balance in segregation and
clonal expansion of mitochondrial DNA mutations. Int. J. Biochem. Cell Biol.
63, 21–24.
Cogliati, S., Calvo, E., Loureiro, M., Guaras, A.M., Nieto-Arellano, R., Garcia-
Poyatos, C., Ezkurdia, I., Mercader, N., Va´zquez, J., and Enriquez, J.A.
(2016). Mechanism of super-assembly of respiratory complexes III and IV.
Nature 539, 579–582.
Corroyer-Dulmont, A., Chakhoyan, A., Collet, S., Durand, L., MacKenzie, E.T.,
Petit, E., Bernaudin,M., Touzani, O., and Valable, S. (2015). Imagingmodalities
to assess oxygen status in glioblastoma. Front. Med. (Lausanne) 2, 57.
Craven, L., Tuppen, H.A., Greggains, G.D., Harbottle, S.J., Murphy, J.L., Cree,
L.M., Murdoch, A.P., Chinnery, P.F., Taylor, R.W., Lightowlers, R.N., et al.
(2010). Pronuclear transfer in human embryos to prevent transmission of mito-
chondrial DNA disease. Nature 465, 82–85.
Cuezva, J.M., Chen, G., Alonso, A.M., Isidoro, A., Misek, D.E., Hanash, S.M.,
and Beer, D.G. (2004). The bioenergetic signature of lung adenocarcinomas is
a molecular marker of cancer diagnosis and prognosis. Carcinogenesis 25,
1157–1163.
Cummins, J.M. (2000). Fertilization and elimination of the paternal mitochon-
drial genome. Hum. Reprod. 15, 92–101.
Dı´ez-Sa´nchez, C., Ruiz-Pesini, E., Montoya, J., Pe´rez-Martos, A., Enrı´quez,
J.A., and Lo´pez-Pe´rez, M.J. (2003). Mitochondria from ejaculated human sper-
matozoa do not synthesize proteins. FEBS Lett. 553, 205–208.
Dokianakis, E., and Ladoukakis, E.D. (2014). Different degree of paternal
mtDNA leakage between male and female progeny in interspecific
Drosophila crosses. Ecol. Evol. 4, 2633–2641.
Fan, W., Waymire, K.G., Narula, N., Li, P., Rocher, C., Coskun, P.E., Vannan,
M.A., Narula, J., Macgregor, G.R., and Wallace, D.C. (2008). A mouse model
of mitochondrial disease reveals germline selection against severe mtDNA
mutations. Science 319, 958–962.
Grimes, D.R., Warren, D.R., andWarren, S. (2017). Hypoxia imaging and radio-
therapy: bridging the resolution gap. Br. J. Radiol. 90, 20160939.
Guara´s, A., Perales-Clemente, E., Calvo, E., Acı´n-Pere´z, R., Loureiro-Lopez,
M., Pujol, C., Martı´nez-Carrascoso, I., Nun˜ez, E., Garcı´a-Marque´s, F.,
Rodrı´guez-Herna´ndez, M.A., et al. (2016). The CoQH2/CoQ ratio serves as a
sensor of respiratory chain efficiency. Cell Rep. 15, 197–209.
Gyllensten, U., Wharton, D., Josefsson, A., and Wilson, A.C. (1991). Paternal
inheritance of mitochondrial DNA in mice. Nature 352, 255–257.
H€am€al€ainen, R.H., Manninen, T., Koivum€aki, H., Kislin, M., Otonkoski, T., and
Suomalainen, A. (2013). Tissue- and cell-type-specificmanifestations of heter-
oplasmic mtDNA 3243A>G mutation in human induced pluripotent stem cell-
derived disease model. Proc. Natl. Acad. Sci. U S A 110, E3622–E3630.
H€am€al€ainen, R.H., Ahlqvist, K.J., Ellonen, P., Lepisto¨, M., Logan, A.,
Otonkoski, T., Murphy, M.P., and Suomalainen, A. (2015). mtDNA mutagen-
esis disrupts pluripotent stem cell function by altering redox signaling. Cell
Rep. 11, 1614–1624.
Jenuth, J.P., Peterson, A.C., Fu, K., and Shoubridge, E.A. (1996). Random ge-
netic drift in the female germline explains the rapid segregation of mammalian
mitochondrial DNA. Nat. Genet. 14, 146–151.
Johnston, I.G., Burgstaller, J.P., Havlicek, V., Kolbe, T., R€ulicke, T., Brem, G.,
Poulton, J., and Jones, N.S. (2015). Stochastic modelling, Bayesian inference,
and new in vivo measurements elucidate the debated mtDNA bottleneck
mechanism. eLife 4, e07464.Johnston, I.G., and Jones, N.S. (2016). Evolution of cell-to-cell variability in
stochastic, controlled, heteroplasmic mtDNA populations. Am. J. Hum.
Genet. 99, 1150–1162.
Johnston, I.G., Gaal, B., Neves, R.P.D., Enver, T., Iborra, F.J., and Jones, N.S.
(2012). Mitochondrial variability as a source of extrinsic cellular noise. PLoS
Comput. Biol. 8, e1002416.
Jokinen, R., Marttinen, P., Stewart, J.B., Neil Dear, T., and Battersby, B.J.
(2016). Tissue-specific modulation of mitochondrial DNA segregation by a
defect in mitochondrial division. Hum. Mol. Genet. 25, 706–714.
Kang, E., Wu, J., Gutierrez, N.M., Koski, A., Tippner-Hedges, R., Agaronyan,
K., Platero-Luengo, A., Martinez-Redondo, P., Ma, H., Lee, Y., et al. (2016).
Mitochondrial replacement in human oocytes carrying pathogenic mitochon-
drial DNA mutations. Nature 540, 270–275.
Lapuente-Brun, E., Moreno-Loshuertos, R., Acı´n-Pe´rez, R., Latorre-Pellicer,
A., Cola´s, C., Balsa, E., Perales-Clemente, E., Quiro´s, P.M., Calvo, E.,
Rodrı´guez-Herna´ndez, M.A., et al. (2013). Supercomplex assembly deter-
mines electron flux in the mitochondrial electron transport chain. Science
340, 1567–1570.
Latorre-Pellicer, A., Moreno-Loshuertos, R., Lechuga-Vieco, A.V., Sa´nchez-
Cabo, F., Torroja, C., Acı´n-Pe´rez, R., Calvo, E., Aix, E., Gonza´lez-Guerra, A.,
Logan, A., et al. (2016). Mitochondrial and nuclear DNA matching shapes
metabolism and healthy ageing. Nature 535, 561–565.
Lee, H.S., Ma, H., Juanes, R.C., Tachibana, M., Sparman, M., Woodward, J.,
Ramsey, C., Xu, J., Kang, E.J., Amato, P., et al. (2012). Rapid mitochondrial
DNA segregation in primate preimplantation embryos precedes somatic and
germline bottleneck. Cell Rep. 1, 506–515.
Luo, S., Valencia, C.A., Zhang, J., Lee, N.C., Slone, J., Gui, B., Wang, X., Li, Z.,
Dell, S., Brown, J., et al. (2018). Biparental inheritance of mitochondrial DNA in
humans. Proc. Natl. Acad. Sci. U S A 115, 13039–13044.
Moreno-Loshuertos, R., Acı´n-Pere´z, R., Ferna´ndez-Silva, P., Movilla, N.,
Pe´rez-Martos, A., Rodrı´guez de Co´rdoba, S., Gallardo, M.E., and Enrı´quez,
J.A. (2006). Differences in reactive oxygen species production explain the phe-
notypes associated with common mouse mitochondrial DNA variants. Nat.
Genet. 38, 1261–1268.
Otten, A.B.C., Sallevelt, S.C.E.H., Carling, P.J., Dreesen, J.C.F.M., Dr€usedau,
M., Spierts, S., Paulussen, A.D.C., de Die-Smulders, C.E.M., Herbert, M.,
Chinnery, P.F., et al. (2018). Mutation-specific effects in germline transmission
of pathogenic mtDNA variants. Hum. Reprod. 33, 1331–1341.
Picard, M., McManus, M.J., Gray, J.D., Nasca, C., Moffat, C., Kopinski, P.K.,
Seifert, E.L., McEwen, B.S., and Wallace, D.C. (2015). Mitochondrial functions
modulate neuroendocrine, metabolic, inflammatory, and transcriptional re-
sponses to acute psychological stress. Proc. Natl. Acad. Sci. U S A 112,
E6614–E6623.
Piko´, L., and Taylor, K.D. (1987). Amounts of mitochondrial DNA and abun-
dance of some mitochondrial gene transcripts in early mouse embryos. Dev.
Biol. 123, 364–374.
Quiro´s, P.M., Ramsay, A.J., Sala, D., Ferna´ndez-Vizarra, E., Rodrı´guez, F.,
Peinado, J.R., Ferna´ndez-Garcı´a, M.S., Vega, J.A., Enrı´quez, J.A., Zorzano,
A., et al. (2012). Loss of mitochondrial protease OMA1 alters processing of
the GTPase OPA1 and causes obesity and defective thermogenesis in mice.
EMBO J. 31, 2117–2133.
Ronchi, J.A., Figueira, T.R., Ravagnani, F.G., Oliveira, H.C.F., Vercesi, A.E.,
and Castilho, R.F. (2013). A spontaneous mutation in the nicotinamide nucle-
otide transhydrogenase gene of C57BL/6Jmice results in mitochondrial redox
abnormalities. Free Radic. Biol. Med. 63, 446–456.
Sato, M., and Sato, K. (2011). Degradation of paternal mitochondria by fertil-
ization-triggered autophagy in C. elegans embryos. Science 334, 1141–1144.
Schwartz, M., and Vissing, J. (2002). Paternal inheritance of mitochondrial
DNA. N. Engl. J. Med. 347, 576–580.
Sharpley, M.S., Marciniak, C., Eckel-Mahan, K., McManus, M., Crimi, M.,
Waymire, K., Lin, C.S., Masubuchi, S., Friend, N., Koike, M., et al. (2012).
Heteroplasmy of mouse mtDNA is genetically unstable and results in altered
behavior and cognition. Cell 151, 333–343.Cell Metabolism 30, 1120–1130, December 3, 2019 1129
Shirihai, O.S., Song, M., and Dorn, G.W. (2015). Howmitochondrial dynamism
orchestrates mitophagy. Circ. Res. 116, 1835–1849.
Stewart, J.B., Freyer, C., Elson, J.L., Wredenberg, A., Cansu, Z., Trifunovic, A.,
and Larsson, N.G. (2008). Strong purifying selection in transmission of
mammalian mitochondrial DNA. PLoS Biol. 6, e10.
Tachibana, M., Sparman, M., Sritanaudomchai, H., Ma, H., Clepper, L.,
Woodward, J., Li, Y., Ramsey, C., Kolotushkina, O., and Mitalipov, S. (2009).
Mitochondrial gene replacement in primate offspring and embryonic stem
cells. Nature 461, 367–372.
Treuting, P.M., Dintzis, S.M., and Montine, K.S. (2017). Comparative Anatomy
and Histology (Academic Press).
Wai, T., Teoli, D., and Shoubridge, E.A. (2008). The mitochondrial DNA genetic
bottleneck results from replication of a subpopulation of genomes. Nat. Genet.
40, 1484–1488.
Warren, D.R., and Partridge, M. (2016). The role of necrosis, acute hypoxia and
chronic hypoxia in 18F-FMISOPET image contrast: a computational modelling
study. Phys. Med. Biol. 61, 8596–8624.
Wartiovaara, A., and Syv€anen, A.C. (2002). Analysis of nucleotide sequence
variations by solid-phase minisequencing. Methods Mol. Biol. 187, 57–63.
Wei, W., Tuna, S., Keogh, M.J., Smith, K.R., Aitman, T.J., Beales, P.L.,
Bennett, D.L., Gale, D.P., Bitner-Glindzicz, M.A.K., Black, G.C., et al. (2019).1130 Cell Metabolism 30, 1120–1130, December 3, 2019Germline selection shapes human mitochondrial DNA diversity. Science 364,
eaau6520.
Wittig, I., Braun, H.P., and Sch€agger, H. (2006). Blue native PAGE. Nat. Protoc.
1, 418–428.
Woltjen, K., H€am€al€ainen, R., Kibschull, M., Mileikovsky, M., and Nagy, A.
(2011). Transgene-free production of pluripotent stem cells using piggyBac
transposons. Methods Mol. Biol. 767, 87–103.
Woods, D.C., and Tilly, J.L. (2015). Autologous germline mitochondrial energy
transfer (AUGMENT) in human assisted reproduction. Semin. Reprod. Med.
33, 410–421.
Yamada, M., Emmanuele, V., Sanchez-Quintero, M.J., Sun, B., Lallos, G.,
Paull, D., Zimmer, M., Pagett, S., Prosser, R.W., Sauer, M.V., et al. (2016).
Genetic drift can compromise mitochondrial replacement by nuclear transfer
in human oocytes. Cell Stem Cell 18, 749–754.
Zhao, X., Li, N., Guo, W., Hu, X., Liu, Z., Gong, G., Wang, A., Feng, J., and Wu,
C. (2004). Further evidence for paternal inheritance ofmitochondrial DNA in the
sheep (Ovis aries). Heredity (Edinb) 93, 399–403.
Zhou, Q., Li, H., Li, H., Nakagawa, A., Lin, J.L.J., Lee, E.S., Harry, B.L., Skeen-
Gaar, R.R., Suehiro, Y., William, D., et al. (2016). Mitochondrial endonuclease
G mediates breakdown of paternal mitochondria upon fertilization. Science
353, 394–399.
STAR+METHODSKEY RESOURCES TABLEREAGENT or RESOURCE SOURCE IDENTIFIER
Antibodies
NDUFA9 Abcam Ab14713
COI Invitrogen 459600
UQCRC2 (Core2) ProteinTech 14742-I-AP
SDHA ThermoFisher 459200
GAPDH Abcam Ab8245
ATPB Abcam Ab14730
Mouse IgG (H+L) DyLight 800 Rockland 610-145-002
Mouse IgG (H+L) Alexa Fluor 680 Invitrogen A21057
Rabbit IgG (H+L) DyLight 800 Rockland 611-145-122
Chemicals, Peptides, and Recombinant Proteins
F29 DNA polymerase New England Biolabs M0269L
BamH1 New England Biolabs R0136M
SspI New England Biolabs R0132S
Lambda Exonuclease. New England Biolabs M0262S
T4 DNA ligase New England Biolabs M0202M
TMRM ThermoFisher T668
H2DCFDA ThermoFisher D399
Digitonin Sigma-Aldrich D5628
[18F]-FMISO This Paper N/A
[18F]-FDG This Paper N/A
N-Acetyl-L-cysteine Sigma-Aldrich A7250
Critical Commercial Assays
kit 5Prime Master Mix 5Prime 2200200
DNeasy Blood &Tissue kit Qiagen 69506
Dulbecco’s modified Eagle’s medium Gibco 41966029
Seahorse XFe96 FluxPaks Agilent 102416-100
CyQUANT NF Cell Proliferation Assay Kit ThermoFisher C35006
PVDF transfer membrane Immobilon-FL Merck Millipore IPFL00010
SEA BLOCK Blocking buffer ThermoFisher 37527
Neon Trasfection System 100ml kit Invitrogen MPK10025
Vector Red Alkaline Phosphatase (Red AP) Substrate Kit Vector Laboratories SK-5100
Experimental Models: Organisms/Strains
C57BL/6JOlaHsd Envigo N/A
CD1 Charles River Laboratories N/A
C57BL/6J The Jackson Laboratories 000664
Oligonucleotides
Mouse 3862-3884 (Fw) 5’-AAGCTATCGGG
CCCATACCCCG-3’
This Paper N/A
Mouse 4503-4525 (Rv) 5’-GTTGAGTAGAGT
GAGGGATGGG-3’
This Paper N/A
ppC57 probe -P- ATTACTCTCTTCTGG TTCCTTTTACGA
CCTCAATGCTGCTGCTGTACTACTCTTC ACAGTGTACA
GGTTA -3’
This Paper N/A
(Continued on next page)
Cell Metabolism 30, 1120–1130.e1–e5, December 3, 2019 e1
Continued
REAGENT or RESOURCE SOURCE IDENTIFIER
ppNZB probe 5’-P- ATTACTCTCTTCTGGCCTTTCC
TACGACCTCAATGCACATGTTTGGCTCCTCTTCAC
AGTGTACAGGTTC -3’
This Paper N/A
Lin33 (ppC57) 5’-Cy3-CCTCAATGCTGCTGCTGTACTAC-3’ This Paper N/A
Lin16 (ppNZB) 5’-FITC-CCTCAATGCACATGTTTGGCTCC-3’;
5’-Cy5-CCTCAATGCACATGTTTGGCTCC-3’
This Paper N/A
Software and Algorithms
GraphPad Prism Version 6 GraphPad Software N/A
ImageJ v.1.6.0 NIH N/A
NDP view2 Software Hamamatsu Photonics U12388-01
FACSDiva Software BD Biosciences N/A
FlowJo FlowJo LLC, BD Biosciences N/ALEAD CONTACT AND MATERIALS AVAILABILITY
Request of information and material should be made to Jose´ Antonio Enriquez. Mouse and cell lines generated in this study are
available upon request for a non-commercial use under a Material Transfer agreement.
EXPERIMENTAL MODEL AND SUBJECT DETAILS
This study used mouse and cellular models which were generated from the animals.
Animal Models
Mice were kept in standard housing conditions in a specific pathogen free (SPF) status facility on a 12-hour light/dark cycle at 20-24C
and relative humidity at 45-65%. Themaintenance conditions are checked and registered daily. All animal procedures conformed to EU
Directive 86/609/EEC and Recommendation 2007/526/EC regarding the protection of animals used for experimental and other scien-
tific purposes, enforced in Spanish law under RD 1201/2005 and RD 53/2013. Approval of the different experimental protocols requires
the estimation of adequate sample sizes aswell as the definition of the randomization and blinding criteria.Mice received ad libitum food
and water (5K67 LabDiet) and the number of mice per cage is limited and adapted to RD 53/2013. Experiments were carried out with
males and females indistinctively, and the details of the age of themice can be found in the figure legends and results. C57BL/6JOlaHsd
andCD-1wild-typemicewerepurchased fromEnvigo andCharlesRiver Laboratories respectively, and themicewithC57BL/6J nuclear
background were from The Jackson Laboratory. The conplastic mouse strain with C57BL/6 nuclear genome and the NZB/OlaHsd
mtDNA was described before (Latorre-Pellicer et al., 2016). OMA1KO mice on the C57BL/6JOlaHsd background, were generated as
described in Quiro´s et al. (2012). Heteroplasmic mice were generated by electro-fusing cytoplasts from conplastic BL/6NZB zygotes
to recipient C57BL/6JOlaHsd (BL/6C57) one-cell embryos, cultured overnight and transplanted as two-cell embryos into pseudo preg-
nant Hsd:ICR (CD-1) females to complete development to term as previously described (Jenuth et al., 1996). To the best of our knowl-
edge, no consensus rule to name heteroplasmic mouse strains exists. Here, we propose the following designation to name heteroplas-
mic mouse strains: NUCLEAR GENOME- - mtCYTOPLASMIC GENOME #1 + CYTOPLASMIC GENOME #2 [i.e., C57BL/6-mtC57BL/
6+NZB, a strain with the nuclear genome of C57BL/6JOlaHsd and the cytoplasmic (mitochondrial) genome of C57BL/6JOlaHsd and
NZB/B1NJ]. For simplicity, we label this BL/6C57-NZB throughout this report. Heteroplasmic females (BL/6C57-NZB) were outcrossed
with males BL/6C57. Only females with an initial level of mtDNA NZB heteroplasmy above 20% were used for colony maintenance.
To produce heteroplasmic mice OMA1KO, BL/6C57-NZB female were outcrossed to male OMA1KO (C57BL/6JOlaHsd background) to
generate an F1 heterozygote mice, which were then intercrossed to obtain a F2 OMA1KO heteroplasmic mice. Oma1 was genotyped
as described (Quiro´s et al., 2012). To produce heteroplasmic mice NNTKO, BL/6C57-NZB females were outcrossed with NNTKO males
(C57BL/6J background) to generate the F1 heterozygote mice, which were then intercrossed to obtain the F2 NNTKO heteroplasmic
mice. Heteroplasmic strains were maintained by outcrossing heteroplasmic females (BL/6C57-NZB NNTKO) with BL/6C57 NNTKO males.
Nnt was genotyped as described in Ronchi et al. (2013). To produce heteroplasmic mice SCAF1113, BL/6C57-NZB females were out-
crossed to SCAF1113 males (C57BL/6JOlaHsd nuclear background) to generate the F1 heterozygote mice, which were then inter-
crossed to obtain the F2 SCAF1113 heteroplasmic mice. Heteroplasmic strains were maintained by outcrossing heteroplasmic females
(BL/6C57-NZB SCAF1113) with BL/6C57 SCAF1113 males. Scaf1 was genotyped as described in Cogliati et al. (2016).e2 Cell Metabolism 30, 1120–1130.e1–e5, December 3, 2019
Cellular Models
Mouse embryo fibroblast (MEF) cell lines were isolated from 13.5 dpc from both sexes of embryos using standard protocol. Each
embryo was dissected into 10ml of sterile PBS, voided of its internal organs, head, and legs. After 30 min incubation with gentle
shaking at 37C with 5ml 0,1% trypsin, cells were plated in two 100 mm dishes and incubated for 24-48h. All MEFs used for iPSCs
studies were within the first three passages. To establish the immortalized MEF lines, early passage MEFs were seeded in 60 mm
plates and infected with 105 IU/ml packaged retrovirus E6/E7. Selection was performed with 400 mg/ml of G418 during 10 days.
IPSCs were generated using transposon-mediated gene transfer (Woltjen et al., 2011). The transfections were done using a Neon
electroporator (Invitrogen; one pulse; 30 mS; 1,300 V) and Neon Trasfection System 100ml kit (Invitrogen) with 2 mg of DNA and
2.5 x 105 cells per electroporation. The culture media was supplemented with 1.5 mg/ml of doxycycline on the next day. For reprog-
ramming in different oxygen tensions, electroporations were split into two separate plates: one cultured in 4%O2 (Biospherix ExVivo
chamber) and the other cultured in a standard room-air incubator of around 21% O2. For reprogramming in different medium con-
ditions in 21% O2, the electroporations were split into two separate plates: one cultured with standard medium, and the other sup-
plemented with 1mMNAC (Sigma). To assess the reprogramming efficiency, plates were stained on day 14 for alkaline phosphatase
(AP) activity (Vector Red Alkaline Phosphate substrate kit). The relative reprograming efficiencywas defined as the proportion of num-
ber of iPSC clones generated from identical MEFs number, compared to a reference of 100 defined as the proportion obtained with
BL/6C57 MEFs under 21% Oxygen concentration.
METHOD DETAILS
Molecular Confirmation and Quantification of Heteroplasmy
To determine the heteroplasmy levels of each tissue or cell culture, total genomic DNA was isolated using DNeasy Blood &Tissue kit
(Qiagen). The polymorphic G4276A nucleotide was used to genotype individual animals and tissues. This polymorphism in C57
mtDNA forms part of a BamH1 restriction site, which is absent in NZBmtDNA. Total genomic DNAwas PCR amplified using standard
conditions with the kit 5Prime Master Mix (5Prime) and the following primers: 5’-AAGCTATCGGGCCCATACCCCG-3’ (3862-3884)
and 5’-GTTGAGTAGAGTGAGGGATGGG-3’ (4503-4525), as follow: 95C, 30s; 58C, 30s; 72C, 45s for 30 cycles. A 15 ml aliquot
of PCR was digested with 20 units of BamH1 (New England Biolabs), at 37C for 2 hours. After agarose gel electrophoresis, DNA
was visualized using the Gel Doc XR+System (Bio-Rad), and band intensities were quantified with Quantity One 1-D Analysis
Software. The proportion of C57 mtDNA was calculated by adding the intensities of the 414bp and 250bp BamH1-digested frag-
ments and was divided by the sum of the intensities of the undigested 664bp fragments and the 414bp and 250bp BamH1-digested
fragments. Wemonitored it by PCR amplification followed by BamHI digestion to differentiate the twomtDNAs (C57 uncut, NZB cut).
normal room air of around 21%O2 To correct for potential bias in the estimation of the heteroplasmy, we used standard curves gener-
ated by mixing pure mutant and wildtype DNAs. We confirm the accuracy of our heteroplasmy estimation by PCR and solid-phase
minisequencing (Wartiovaara and Syv€anen, 2002).
Padlock Probes
Cells were seeded in Superfrost plus slides (Thermo Scientific) using complete DMEM media lacking phenol-red (10% FBS,
290 mg/mL L-glutamine, 50 mg/mL uridine, 5 mM glucose) and allowed to attach. When the cells reached 80% of confluency they
were fixed in 4% (w/v) paraformaldehyde (Sigma) in DMEMmedia for 15minutes at 37C. Cell permeabilization was performed using
95%EtOH and 5%acetic acid for 10minutes at RT. Slides were thenwashedwith PBS. Enzymatic target preparation was performed
with SspI (New Engalnd Biolabs R0132S) for 30 minutes at 37C. Two washes were done with Buffer A (0.1M Tris-HCl pH 7.5, 0.15 M
NaCl and 0.05%Tween-20). 0.2 U/mL of Lambda-exonuclease (New England BiolabsM0262S) was used for 15minutes at 37C add-
ing 10% glycerol to the corresponding enzyme buffer. The slides were washed twice with Buffer A. Oligonucleotide sequences were
designed (Table S2). Padlock probes (ppC57 and ppNZB) were incubated in a specific hybridization buffer (2X saline-sodium citrate
(SSC) buffer, 20% formamide, 0.5 mg/mL salmon sperm DNA) for 15minutes at 37C. To remove excess probe, Buffer B was used (2X
SSC, 0.05% Tween-20) for 5 minutes at 37C. DNA padlock probes were circularized by T4 DNA ligase (New England Biolabs
M0202M) for 15 minutes at 42C in Buffer B supplemented with 20% formamide and 1 mM EDTA. Slides were then washed in Buffer
A and dehydrated in ethanol. RCA was performed using 1U/ mL ofF29 DNA polymerase (New England Biolabs M0269L) for 1 hour at
37C in a shaking platform. Slides were washed three times with Buffer A and Lin16 and Lin33 fluorescence-labelled oligonucleotide
(100 nM) hybridization was performed in the hybridization buffer for 30 minutes at 37C. Slides were then washed with Buffer A fol-
lowed by PBS-0.01% Tween-20 and dehydrated in ethanol. Vectashield with DAPI mounting media were used for nuclei staining.
Specificity of the probes and staining were confirmed by using homoplasmic cell cultures (100% NZB and 100%C57mtDNA). Leica
SP5 confocal and ImageJ v.1.6.0 software was used for image acquisition and data analysis respectively.
Oocyte Collection
Heteroplasmic female mice were superovulated by intraperitoneal administration of 5 IU PMSG (Sigma) to stimulate follicle growth.
A single intraperitoneal injection of 5 IU hCG (Sigma) was followed 48 hr later. 16 hr after the hCG injection, mice were euthanized by
cervical dislocation and the oviducts dissected out. Ovulated oocytes were collected from the ampullae of the oviducts and placed
individually in a 0,2ml sterile tube for genotyping. Ovaries were collected to quantify heteroplasmy.Cell Metabolism 30, 1120–1130.e1–e5, December 3, 2019 e3
Embryo Collection
Heteroplasmic females werematedwith BL/6C57males. The presence of a vaginal plugwas taken as evidence of pregnancy, and 2.5,
5.5, 6.5, 13.5 and 17.5 dpc embryos were collected for genotyping. When indicated, females were treated with 1% NAC in drinking
water since vaginal plug was detected.
Sperm Collection
Male mice that had not been mated for more than 2 weeks were euthanized and sperm was collected from the epididymis.
In Vitro mtDNA Segregation Studies
Immortalized MEFS were grown in Dulbecco’s modified Eagle’s medium (DMEM; Gibco without glucose) supplemented with 10%
fetal bovine serum (FBS; Sigma), 1% Penicillin-Streptomycin (Lonza) and 1mM sodium pyruvate (Sigma). Where indicated, the
carbon source was: 4.5g/l of glucose (Sigma), 0.9g/l of glucose or 0.9g/l of galactose (Sigma).
SeaHorse Analysis
Oxygen consumption was measured using the XF96 MitoStress Test (Seahorse Bioscience). Oxygen consumption rates were
normalized to cell number using CyQuant (ThermoFisher Scientific).
Histological Analysis of the Ovary
Ovaries were collected from homoplasmic and heteroplasmic females, fixed with 4% PFA for 24 hours and sectioned at 5 mm. Four
sections from each ovary at three different levels of the tissue (40 mm between each section was discarded) were processed,
mounted on a glass slide, stained with H&E and digitalized using NDP view2 Software. Ovaries from females of 3, 6, 9, and 12months
of age were analyzed using ImageJ v.1.6.0 Software (NIH) to assess the percentage of lipofuscin in ovaries. Classification of primor-
dial follicle, primary follicle and growing follicle was done according to Treuting P. and Dintzis S (Treuting et al., 2017).
Mitochondrial Membrane Potential (MMP) and ROS Assessment in MEFs
ROS and MMP were measured in MEFs using 20-70dichlorofluorescein diacetate (H2DCFDA, ThermoFisher, 0.4mM final concentra-
tion), and tetramethylrhodamine methyl ester perchlorate (TMRM, Sigma, 100 nM final concentration). A total of 10.000 events were
recorded for each sample using the FACSCanto II system (BD Biosciences). All experiments were performed in triplicate. Samples
were analyzed with BD FACSDiva Software and an average of the means and standard deviations were calculated using FlowJo
Software (v10).
Blue Native Gel Electrophoresis
Supercomplex levels and compositions were analyzed in isolatedmitochondria from 12.5 dpc embryos using blue native electropho-
resis (BNE) as described previously (Wittig et al., 2006). Mitochondrial proteins were solubilized with 10% digitonin (4g/g) (Sigma
D5628) and run on a 3%–13% gradient gel. The gradient gel was prepared in 1.5 mm glass plates using a gradient former connected
to a peristaltic pump. Proteins were electroblotted onto PVDF transfer membrane (Immobilon-FL, 0.45 mm, Merck millipore,
IPFL00010) for 1 h at 100 V in transfer buffer (48 mM Tris, 39 mM glycine, 20 % EtOH). A Mini Trans- Blot Cell system (BioRad)
was used. SEA BLOCK Blocking buffer (ThermoFisher 37527) or PBS with 5 % BSA was used for 1 hour at room temperature
(RT) to avoid non-specific binding of antibodies. For protein detection, antibodies were incubated with the membrane for 2 hours
at RT. Secondary antibodies were incubated for 45 minutes at RT. The membrane was washed with PBS 0.1 % Tween-20 for 5 mi-
nutes three times between primary and secondary antibodies and after secondary antibodies. To study supercomplex assembly, the
PVDFmembranewas sequentially probedwith antibodies against Complex I (anti-NDUFA9), Complex III (anti-UQCRC2), Complex IV
(anti-COI), Complex V (anti-ATPB) and Complex II (anti-SDHA) (Table S1).
Western Blot
Proteins in whole embryo lysates were separated using SDS/PAGE and transferred to PVDF membranes (Immobilon-FL, 0.45 mm,
Merck millipore, IPFL00010), which were then blocked with 5% (vol/vol) BSA in 0.1 % Tween 20 in PBS for 1 h at room temperature.
The membranes were then probed using anti-GAPDH (mouse monoclonal, Abcam, Ab8245), and anti-ATPB (mouse monoclonal
Abcam, Ab14730). The secondary antibody was anti-mouse dylight 800 (Rockland, 610145002) and the images were acquired using
the ODYSSEY Infrared Imaging System (LI-COR). Protein quantification was performed using ImageJ v.1.6.0 software.
PET-CT in Embryos
In vivo positron emission tomography–computed tomography (PET/CT) imaging was performed with a nanoPET/CT small-animal im-
aging system (Mediso Medical Imaging Systems, Budapest, Hungary). List-mode PET data acquisition commenced 30 min post intra-
venous injection of 18MBq [18F]- FDG or 30MBq [18F]-fluoromisonidazole ([18F]-FMISO) in 12.5 dpc embryo imaging, and continued for
20 minutes of PET acquisition. At the end of PET acquisitions, scan microCT was performed for attenuation correction and anatomical
references. The resulting dynamic PET images were reconstructed in a 105 x 105matrix (frame rates: 3 x 10min, 1 x 30min, 1 x 60min)
using a Tera-Tomo 3D iterative algorithm. Acquisition and reconstruction were performed with proprietary Nucline software (Mediso,
Budapest, Hungary) and saved in Dicom format. The images were imported into OsiriX software (Pixmeo, Switzerland v.8.0.1).e4 Cell Metabolism 30, 1120–1130.e1–e5, December 3, 2019
Biodistribution studieswere performed in aWizard 1470GammaCounter (Perkin Elmer). The pregnant femaleswere sacrificed in a CO2
chamber. Embryoswere extracted and counted for 1min in the gammacounter. Decay correctionwas performed and data represented
as relative %ID/ g.
QUANTIFICATION AND STATISTICAL ANALYSIS
Heteroplasmy Statistical Analysis
Themagnitude of heteroplasmy shifts under constant selective pressure depends on heteroplasmy levels, so percentage-point shifts
observed in mice with different initial heteroplasmies cannot be directly compared. For example, for the same selective pressure,
smaller percentage-point shifts are expected as the limits of 0% and 100% are approached. To allow comparison of heteroplasmy
shifts across diverse samples, we use a transformation that accounts for the heterogeneity in expected shift magnitude from a given
selective pressure. This transformation (Burgstaller et al., 2014; Johnston and Jones, 2016) is Dh = ln ((h (h0 – 1)) / (h0 (h – 1))),
comparing a heteroplasmy observation h to a reference value h0. Depending on scientific context, h0 may be a sample taken earlier
in time, or from a reference tissue: we specify the source of the corresponding reference value in the main text. Dh, the transformed
heteroplasmy shift, then reports a normalised magnitude of heteroplasmy shift that is comparable across samples with differing h0
values. Dh = 0 corresponds to a null hypothesis of no selective difference between mtDNA types. Cross-sample distributions of Dh
values for nonzero and zero selection are typically well approximated by Gaussian distributions (Burgstaller et al., 2018).
General Statistical Analysis
Unless specified, statistical analyses and graphics were produced with GraphPad Prism 6 software. Data sets were compared by
ANOVA or non-parametric analysis when corresponded. Differences were considered statistically significant at P values below
0.05. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. All statistical analyses are presented as n, mean ± s.d. or mean ± s.e.m.
in the figure legends.
DATA AND CODE AVAILABILITY
Some of the datasets supporting the current study have not been deposited in a public repository yet, but will be donewhen possible,
meanwhile they are available from the corresponding author upon request.Cell Metabolism 30, 1120–1130.e1–e5, December 3, 2019 e5