EMBO reports - Peer Review Process File - EMBOR-2014-39757
Manuscript EMBOR-2014-39757
Single muscle fiber proteomics reveals unexpected
mitochondrial specialization
Marta Murgia, Nagarjuna Nagaraj, Atul Deshmukh, Marlis Zeiler, Pasqua Cancellara, Irene Moretti,
Carlo Reggiani, Stefano Schiaffino and Matthias Mann
Corresponding author: Marta Murgia, Matthias Mann, Max-Planck Institute of Biochemistry,
Stefano Schiaffino, Venetian Institute of Molecular Medicine
Review timeline:
Submission date:
Editorial Decision:
Revision received:
Accepted:
20 October 2014
26 November 2014
23 December 2014
09 January 2015
Transaction Report:
(Note: With the exception of the correction of typographical or spelling errors that could be a source of ambiguity,
letters and reports are not edited. The original formatting of letters and referee reports may not be reflected in this
compilation.)
Editor: Barbara Pauly
1st Editorial Decision
26 November 2014
Thank you very much for the submission of your research manuscript to our editorial office and for
your patience while we were waiting to hear back from the referees. We have now received the full
set of reviews on your manuscript and I am pasting them below for your information.
You will see that all reviewers appreciate the interest of your findings and are, in principle,
supportive of publication of your study in our journal. However, they also raise some points that
need further clarifications and/or discussions. In particular, referee 2 also feels that in some cases,
additional controls and experiments would be required to strengthen the data at hand.
Overall, and given the reviewers' constructive comments, I would like to give you the opportunity to
revise your manuscript, with the understanding that the main concerns of the reviewers should be
addressed. Acceptance of the manuscript will depend on a positive outcome of a second round of
review and I should also remind you that it is EMBO reports policy to allow a single round of
revision only and that therefore, acceptance or rejection of the manuscript will depend on the
completeness of your responses included in the next, final version of the manuscript.
I look forward to seeing a revised form of your manuscript when it is ready. Should you in the
meantime have any questions, please do not hesitate to contact me.
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REFEREE REPORTS:
Referee #1:
The manuscript by Murgia et al reports the characterization of the proteome of single muscle fibers
(over 7000 proteins). This is an important technical achievement since, to my knowledge, it is a first
example of single cell MS proteomics ... albeit of a very atypical multinucleate cell type. As a
consequence proteome heterogeneity between and within fiber types can be addressed. This is
achieved by a state of the art technological pipeline for sample preparation and analysis. The
manuscript is clearly written and the results dense of potentially interesting information.
The main conclusions are
- Cell proteomics can correctly classify fiber types, not only by looking at Myh isoforms, but also by
clustering the whole proteome profile.
- fibers show a regional heterogeneity in their proteome (As outlined below this is a conclusion that
I find weak)
- Analysis of fiber type specific patterns allows to convincingly speculate on specialization in
substrate utilization.
In my opinion this warrants publication in EMBO reports.
Major remark.
Interestingly the authors note regional differences in fibers that are mechanically split into two parts.
However these data are not completely convincing. If I understand the experiments correctly this
was only observed in one out three fibers. I am not an expert in single fiber purification, but how can
one be sure that the observed differences are not due to cross contamination between two different
fiber types.
Typos and minor observations.
second line in the introduction: if =>it
page 3 fifth line from the botton Fig S1 and B=> Fig S1 A and B
page 6 "...on the basis of expression values of for an OXPHOS marker, cytochrome c, as an
indicator of mitochondrial quantity in different tissues ..." Something wrong in this sentence.
Some interesting questions are not dealt with
- Do members of the same fiber type, but isolated from different muscles, show a different
proteomic profile?
- How does the fiber proteome change when the muscle is perturbed by exercise by a chemical
challenge or a genetic defect?
Referee #2:
In this work, Murgia et al. analyze the proteomic profiling of single muscle fibers, using a high
sensitivity workflow. They first analyzed the whole muscle proteome by a linear quadrupole
Orbitrap mass analyzer, and then each specific muscle fiber type. Combining both techniques, they
identify more than 7000 proteins and different protein categories in each fiber type. Analysis of
these proteins allowed them to group each fiber type, differentiating each subtype and identifying
several variations in mitochondrial proteins in each fiber.
This study is technically well-done and shows different approaches in the analysis, which in general,
makes it reliable. A few additional control experiments are, however, still required. Furthermore, the
biological significance of the observed changes is not well discussed and needs some clarification.
Major Points:
1. Why does the analyses of half fibers show different Myh phenotype? How can you ascertain that
2X and 2B fibers are not mixed in the proteome analysis? In this regard, and seeing the overlap of
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proteins observed in the PCA analysis between 2B-2X and 2A-1, how can it be proven that the final
mitochondrial protein assignments are correct?
2. Why have you selected different percentages of Myh to assign each fiber type?
3. The differential distribution of mitochondrial proteins in each fiber suggests different functions or
different use of energy sources. However, as argued in my point 1, some differences are not clear
between subtypes 2B-2X and 1-2A. In addition, fibers of type 2A, assigned classically as fast and
glycolytic, show an increase in OXPHOS proteins. How can this be explained? Is the classical
classification obsolete? Are there any mitochondrial differences between subtypes 2B and 2X?
More discussion about the biochemical function of each fiber type/subtype is therefore required.
4. Could you please justify why only cytochrome c is used as the protein to normalize for
mitochondrial number? It seems strange to use only one protein for normalization, since you show
later that even TCA cycle enzymes can vary a lot from one fiber type to the other. Thus, cytochrome
c might also vary and it might introduce a bias (similarly, cyt c being in the membrane, it could vary
a lot if the surface/volume ratio changes). I would suggest using at least two mitochondrial proteins
for normalization, with the second one being a matrix protein.
5. It could be good to confirm the proteomics data by at least one enzyme activity assay for an
enzyme that varies between fiber types (e.g. Idh2 types).
Minor Points:
1. EDL - acronym should be clarified.
2. In Figure 2B, legends of Myh2 and Myh4 in the WB do not correspond with the LC-MS analysis.
Referee #3:
This is an interesting paper which is technically innovative and which contributes to our
understanding on muscle fiber specialization and phenotype.
Major;
1. The innovation lies in the methodology. However, there should be some discussion of how the
data fit relative to data that have been acquired years earlier on single fiber enzyme levels. I note
that Pette and Lowry are given token references, but these authors significantly advanced the field in
this area, using techniques that6 were very advanced at those times. Some discussion of how the
results compare should be made (at least a paragraph of discussion, I would think, is warranted). For
example, how do the current data improve our understanding of metabolic pathways compared to
what we knew before?
2. Page 6: gives the impression that TCA cycle enzymes and activity is highest in type IIx fibers.
This is surely not the case.
Minor:
1. Page 5: reference by Park could not be found;
2. Page 2: Not clear what is meant by the statement at the bottom of page 2 that "fibers contain very
limited amounts of protein" and that they have a "highly unfavourable dynamic range". This runs
counter to all that we know about muscle plasticity. Please re-think.
3. Page 5: bottom: Muscle does not have a very high mitochondrial content compared to other
tissues. Please see any work by H. Hoppeler on the Volume density of mitochondria in muscle.
1st Revision - authors' response
23 December 2014
Point-by-point answer to reviewers
We thank the reviewers for their thorough and helpful comments on our manuscript. Generally, all
three reviewers were positive but they recommended a number of minor changes as well as a few
more experiments. We addressed the textual changes as explained below and have also done more
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experiments, mainly on split single fibers as well as some additional independent validation. We
hope that the revised manuscript is now acceptable for publication.
Referee #1:
The manuscript by Murgia et al reports the characterization of the proteome of single muscle fibers
(over 7000 proteins). This is an important technical achievement since, to my knowledge, it is a first
example of single cell MS proteomics ... albeit of a very atypical multinucleate cell type. As a
consequence proteome heterogeneity between and within fiber types can be addressed. This is
achieved by a state of the art technological pipeline for sample preparation and analysis. The
manuscript is clearly written and the results dense of potentially interesting information.
The main conclusions are
- Cell proteomics can correctly classify fiber types, not only by looking at Myh isoforms, but also by
clustering the whole proteome profile.
- fibers show a regional heterogeneity in their proteome (As outlined below this is a conclusion that
I find weak)
- Analysis of fiber type specific patterns allows to convincingly speculate on specialization in
substrate utilization.
In my opinion this warrants publication in EMBO reports.
We thank the reviewer for his or her positive evaluation of our work.
Major remark.
Interestingly the authors note regional differences in fibers that are mechanically split into two parts.
However these data are not completely convincing. If I understand the experiments correctly this
was only observed in one out three fibers. I am not an expert in single fiber purification, but how can
one be sure that the observed differences are not due to cross contamination between two different
fiber types.
We have prepared a new set of half-fiber pairs, to address Referee#1’s concerns. We have taken
additional care during fiber isolation to avoid carry-over/cross-contamination from neighboring
fibers and debris, which might artificially cause any two samples to differ. All fiber pairs have been
isolated from EDL. Scissors and tweezers were cleaned before and after isolating each fiber. As part
of our standard protocol, individual fiber morphology has been thoroughly monitored during
isolation, to exclude the presence of additional fibers and fiber segments. Our analysis now includes
a total of 9 half fiber pairs, with 3 of them showing a difference above 20 % in the distribution of the
major Myh between the two parts. The new results strengthen our observation that different
segments of the same fiber may show detectable differences at the proteome level. This variability
along the longitudinal fiber axis is not a novel concept (see also Response to Referee#2, point 1a).
At the same time, we would like to point out that the majority of fibers is actually very similar in
terms of Myh isoforms. If there had been systematic contamination, this would not be expected.
In the revised version of the manuscript, Figure 2D and E show Myh isoform distribution and
Principal Component Analysis of six fiber pairs instead of three. The Myh composition of all fiber
pairs analyzed is now shown in supplementary figure S3D. The new dataset has been deposited in
the PRIDE repository.
Typos and minor observations second line in the introduction: if =>it
page 3 fifth line from the botton Fig S1 and B=> Fig S1 A and B
page 6 "...on the basis of expression values of for an OXPHOS marker, cytochrome c, as an
indicator of mitochondrial quantity in different tissues ..." Something wrong in this sentence.
We have made these changes.
Some interesting questions are not dealt with
- Do members of the same fiber type, but isolated from different muscles, show a different
proteomic profile?
This question is of great interest and we thank the Referee for highlighting this topic. To address this
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point, we focused on type 2X fibers, which are present in both soleus and EDL (see figure S2). Type
2A can also be found in both muscles, however they are much smaller in EDL and are, therefore,
more rarely sampled. Type 1 and 2B are, conversely, prevalent in soleus and EDL, respectively. To
address the Referee’s comment, we have analyzed a biological replicate of 2X fibers isolated from
the same mouse, prepared and analysed as a single experiment. These fibers are not included in the
main dataset due to differences in the sample preparation procedure. These experimental conditions
should avoid that other sources of variability perturb the comparison, which is based on the muscle
of origin. Using principal component analysis, we indeed obtained a separation of the two fibers
originated from soleus from the other three originated from EDL. However, the difference is
distributed along component 2, which amounts to less than 20% of observed variability. This
suggests that the muscle of origin is not a prevalent source of variability among type 2X fibers in
our experimental model. Due to the small number of fibers, we decided to not include these data in
the revised version of the paper. We provide a figure for the Referee (Referee 1, figure R1).
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Figure for Referee 1. Principal component analysis (PCA) of type 2X fibers from soleus and EDL,
originating from the same mouse and prepared and processed together. The table at bottom shows
corresponding fiber type assignments.
- How does the fiber proteome change when the muscle is perturbed by exercise by a chemical
challenge or a genetic defect?
This is also a question of great interest, which we think could be addressed as a follow-up of this
study. Indeed, we have performed preliminary experiments in a model of induced atrophy and the
reviewer’s comment encourages us to pursue this issue further. However, a strength of EMBO
Reports and a stated mission is that it publishes papers that basically address a single point and we
believe adding follow up experiments to this manuscript would detract from this.
Referee #2:
In this work, Murgia et al. analyze the proteomic profiling of single muscle fibers, using a high
sensitivity workflow. They first analyzed the whole muscle proteome by a linear quadrupole
Orbitrap mass analyzer, and then each specific muscle fiber type. Combining both techniques, they
identify more than 7000 proteins and different protein categories in each fiber type. Analysis of
these proteins allowed them to group each fiber type, differentiating each subtype and identifying
several variations in mitochondrial proteins in each fiber.
This study is technically well-done and shows different approaches in the analysis, which in general,
makes it reliable. A few additional control experiments are, however, still required. Furthermore, the
biological significance of the observed changes is not well discussed and needs some clarification.
We thank the reviewer for the positive evaluation of our work.
Major Points:
1. Why does the analyses of half fibers show different Myh phenotype? How can you ascertain that
2X and 2B fibers are not mixed in the proteome analysis? In this regard, and seeing the overlap of
proteins observed in the PCA analysis between 2B-2X and 2A-1, how can it be proven that the final
mitochondrial protein assignments are correct?
Regarding the different phenotype of half fibers, we have now extended the analysis of half-fiber
pairs, performing new experiments to strengthen our observation that two half fibers can show
detectable differences at the proteome level. Figure 2D and E and supplementary figure S3E in the
revised version address this point, which was also a concern of Referee #1.
The observation that two segments of the same fiber may express a different subset of Myh isoforms
is not novel. It is a common finding in human and rodent extraocular muscles and has been reported
by Staron and Pette in rabbit limb muscles (Staron and Pette, Pfluegers Archives 1987). These
authors have proposed that it might be associated with the reprogramming of myosin expression that
occurs upon local injury or in response to activity. As muscle fibers originate from the fusion of
individual myoblasts, segmental differences have been attributed to the existence of nuclear domains
dictating the properties of a certain adjacent fiber volume (See Pavlath et al Nature 1987).
Segmental differences in the velocity of contraction along single frog fibers (Edman et al J Physiol
1985) and human fiber segments have also been observed (Wilkins et al Muscle and nerve 2001),
indicating that the observed differences may have a physiological correlate. Here, we show these
differences for the first time on a proteomic scale.
We have added a brief discussion of this point on page 5 in the revised manuscript.
Regarding the mixing of 2X and 2B fibers, we have verified the Myh isoforms composition of the
individual fibers that were used to obtain a fiber type-resolved proteome. The expression of specific
Myh isoforms is the traditional criterion used so far for defining muscle fiber types. We show in
figure 2B that our MS-based method assigns the same fiber type as the traditional method based on
electrophoretic separation of Myh isoforms. The figures also shows that MS-5
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based proteomics is more sensitive in detecting isoform coexpression, as it detects a minor (20%)
presence of Myh2 the fiber typified as pure Myh1 by electrophoresis.
The fiber subsets we have selected to obtain a fiber type-resolved proteome have the property of
being “pure” according to the established criteria that have defined fiber types so far. This is also
shown in figure 2F, which reports the relative enrichment Myh isoforms of each fiber type subset
and thus allows an estimate of the degree of mixing. Concerning type 2X and 2B fibers in particular,
median expression of Myh4 for the 2B subset amounts to 92% with negligible coexpression of other
isoforms. This gives us confidence that the final mitochondrial protein assignment for type 2B is
devoid of contamination by other types. Type 2X fibers have a median expression of Myh 1 of 69%,
with partial coexpression of Myh4 (13%) and Myh2 (14%) respectively, so we rely on a five-fold
enrichment for this fiber type.
In our view, the PCA analysis shown in figure 2C substantially confirms the existence of distinct
groups based on Myh isoforms while at the same time enlarging the view on the phenotype of
individual fibers. By this method we are comparing whole fiber proteomes, therefore differences and
similarities extend to many subcellular system, including other sarcomeric proteins, ion channels
and calcium signaling components, which may show a continuous spectrum rather than four distinct
fiber phenotypes. We think that occasional overlap between fibers with different Myh composition
is revealing potentially novel common features that cannot be accounted for by looking at Myh
alone.
Concerning the specific issue of the final mitochondrial protein assignments, see under point 3
below.
2. Why have you selected different percentages of Myh to assign each fiber type?
The Referee raises an important point, which we indeed did not describe in the necessary detail in
the original manuscript. The reason for the different cut-offs is the different purities of the fiber
types. The different percentages that we used to assign fiber types are approximated on the observed
distribution relative abundances of Myh. We have now added a section in the Supplementary
Experimental Procedures of the revised manuscript, describing Myh isoform quantification and the
definition of pure and mixed fiber. This section provides the observed values (average and standard
deviation of Myh isoform expression) that we used to approximate the cut-offs. We have added a
panel showing the analysis underlying fiber type assignment (Figure S1c).
3. The differential distribution of mitochondrial proteins in each fiber suggests different functions or
different use of energy sources. However, as argued in my point 1, some differences are not clear
between subtypes 2B-2X and 1-2A. In addition, fibers of type 2A, assigned classically as fast and
glycolytic, show an increase in OXPHOS proteins. How can this be explained? Is the classical
classification obsolete? Are there any mitochondrial differences between subtypes 2B and 2X?
More discussion about the biochemical function of each fiber type/subtype is therefore required.
Type 2A fibers have traditionally been classified as fast-oxidative-glycolytic (FOG), because of
their high relative abundance of mitochondria. We show by immunohistochemistry in
supplementary figure S6 that type 2A fibers have a higher succinate dehydrogenase activity, and
thus more mitochondria, than type 1 fibers, in agreement with previous electron microscopy studies
(see Schiaffino and Reggiani, Physiol Rev 2011). We have now extended the description of each
fiber type and its biochemical function in the introduction.
We do observe mitochondrial differences between type 2X and 2B fibers. When we compare
normalized protein expression of mitochondrial proteins in the two subsets, there are 153
significantly different proteins. Invariably, they are higher in 2X than in 2B fibers, reflecting
mitochondrial abundance. However, when we normalize for the amount of mitochondria using
either cytochrome C or succinate dehydrogenase (see point 4), 2B fibers have a significantly higher
content of a subset of mitochondrial proteins, among these glycerol-3 phosphate dehydrogenase 2
(Gpd2), which demonstrates this point (see discussion of figure 3 in the manuscript).
We have now assembled these data into a supplemental table (Table S4). A similar comparison
between type 1 and 2A fibers, which was originally presented in Table 1 is now in table S3, due to
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space constraints. The new experiment in figure 3B also confirms a difference between 2X and 2B
fibers in the expression of IDH3a (see point 5).
Our finding of significant fiber type differences in some mitochondrial proteins, e. g. that IDH3a is
high in 2X and low in 2B, are now independently confirmed with antibody staining (new Fig. 3B),
indicate that these differences are correct and may even be underestimated.
4. Could you please justify why only cytochrome c is used as the protein to normalize for
mitochondrial number? It seems strange to use only one protein for normalization, since you show
later that even TCA cycle enzymes can vary a lot from one fiber type to the other. Thus, cytochrome
c might also vary and it might introduce a bias (similarly, cyt c being in the membrane, it could vary
a lot if the surface/volume ratio changes). I would suggest using at least two mitochondrial proteins
for normalization, with the second one being a matrix protein.
We have followed the Referee’s suggestion to use more than one mitochondrial protein for
normalization. We now use both cytochrome C and succinate dehydrogenase (SDHA) to normalize
for mitochondrial content; this latter enzyme is located on the matrix side of the inner mitochondrial
membrane and can be quantified in all fibers, a requirement that forced us to exclude a number of
other candidate normalizer proteins. The results of this analysis are now presented next to each other
in supplementary table S3 and S4.
5. It could be good to confirm the proteomics data by at least one enzyme activity assay for an
enzyme that varies between fiber types (e.g. Idh2 types).
Following the reviewers’ suggestion, we have used an independent approach,
immunohistochemistry, to validate our quantitative proteomics data indicating that Idh2 expression
is essentially restricted to type 1 and 2A fibers. Furthermore, we have also addressed by the same
method the expression of Idh3, which we had reported as being highly abundant in 2X fibers. These
experiments, now shown in figure 3B, are an important validation of our proteomics data.
Minor Points:
1. EDL - acronym should be clarified
It is now clarified in the second line of results.2. In Figure 2B, legends of Myh2 and Myh4 in the WB do not correspond with the LC-MS analysis.
This has been corrected.
Referee #3:
This is an interesting paper which is technically innovative and which contributes to our
understanding on muscle fiber specialization and phenotype. Major; 1. The innovation lies in the
methodology. However, there should be some discussion of how the data fit relative to data that
have been acquired years earlier on single fiber enzyme levels. I note that Pette and Lowry are given
token references, but these authors significantly advanced the field in this area, using techniques
that6 were very advanced at those times. Some discussion of how the results compare should be
made (at least a paragraph of discussion, I would think, is warranted). For example, how do the
current data improve our understanding of metabolic pathways compared to what we knew before?
This was indeed missing. We have now added a paragraph to the discussion (page 8).
2. Page 6: gives the impression that TCA cycle enzymes and activity is highest in type IIx fibers.
This is surely not the case.
There are 3 types of mitochondria-rich fibers in mouse muscles, type 1, 2A and 2X. In our single
fibers dataset we did find a significantly higher expression of TCA cycle enzymes in type 2X
compared to type 1 fibers (Fig. 3A and Table S3). On the other hand, the differences between type 1
and 2A, as well as the difference between 2X and 2A are not statistically significant. Using an
independent approach, i. e. immunohistochemistry, we now show (Fig. 3B) that type 2X and 2A
fibers are more reactive with an antibody specific for a subunit of a TCA cycle enzyme, IDH3a,
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compared type 1 fibers. We have also analyzed our data focusing on proteins annotated as “TCA
cycle” using GOBP and Keyword annotations and calculated their median expression in 2A and 2X
fibers. As shown in the figure below (Referee#3 figure R3), we find higher values for 2X compared
to type 2A fibers.
Figure for Referee 3. Median abundance of proteins annotated as related to the TCA cycle (Uniprot
Keywords annotations) in type 2A and 2X fibers. The analysis was performed using the 1D
annotation enrichment algorithm (Cox et al, 2012).
Minor:
1. Page 5: reference by Park could not be found;
We have corrected this mistake and modified the references accordingly
2. Page 2: Not clear what is meant by the statement at the bottom of page 2 that "fibers contain very
limited amounts of protein" and that they have a "highly unfavourable dynamic range". This runs
counter to all that we know about muscle plasticity. Please re-think.
These statements emphasize the main difficulties encountered in analyzing single fibers by MSbased quantitatively proteomics and are not related to their function. The total amount of protein we
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can measure from a single mouse muscle fiber in our preparations is extremely low, especially
compared to other proteomics studies that almost without exception start with easily visible amounts
of material. The dynamic range of the muscle proteome is unfavorable for proteomics because the
peptides originating from highly abundant sarcomeric proteins decrease the probability of observing,
fragmenting and thus identifying peptides from less abundant proteins. Therefore, to reach large
numbers of identified proteins in skeletal muscle is much more difficult compared to other tissue
and to cell lines. We have rewritten the sentence to make the technical point more clearly.
3. Page 5: bottom: Muscle does not have a very high mitochondrial content compared to other
tissues. Please see any work by H. Hoppeler on the Volume density of mitochondria in muscle.
There are species differences in mitochondrial content of skeletal muscles. The studies of Hoppeler
are focused on mitochondria density in human skeletal muscles, which contain much lower amount
of mitochondria compared to mouse muscle (see Schiaffino, Acta Physiologica 2010, for a
discussion of the differences between human and mouse skeletal muscle in this respect). Given these
species differences, we have modified the sentence in the revised version of the paper by deleting
any mention to mitochondrial content in muscle compared to other tissues. We now simply refer to
the importance of mitochondria in muscle energy metabolism and the frequent involvement of
skeletal muscle in human mitochondrial diseases.
2nd Editorial Decision
09 January 2015
I am very pleased to accept your manuscript for publication in the next available issue of EMBO
reports.
Thank you for your contribution to EMBO reports and congratulations on a successful publication.
Please consider us again in the future for your most exciting work.
REFEREE REPORT:
Referee #2:
The authors replied adequately to my critiques. The manuscript can be published as such.
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