Evidence map›Paper›PMID 30399141›Full record

ReviewPLoS genetics2018

Genotype to phenotype: Diet-by-mitochondrial DNA haplotype interactions drive metabolic flexibility and organismal fitness.

Wen C Aw, Samuel G Towarnicki, Richard G Melvin, Neil A Youngson, Michael R Garvin, Yifang Hu, Shaun Nielsen, Torsten Thomas, Russell Pickford, Sonia Bustamante and 3 more

Open access · goldAbstract readReview
In one paragraph

Review in PLoS genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 1 synthesis or guideline pooled it, 93 citations in OpenAlex.

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  8. Biomolecules · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 6 institutions in 3 countries.

Wen C AwSchool of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, NSW, Australia.ORCID 0000-0002-9910-3688
Samuel G TowarnickiSchool of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, NSW, Australia.ORCID 0000-0001-6591-6376
Richard G MelvinSchool of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, NSW, Australia.ORCID 0000-0001-6428-6763
Neil A YoungsonSchool of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, NSW, Australia.ORCID 0000-0003-0690-4580
Michael R GarvinSchool of Biological Sciences, Washington State University, Pullman, Washington, United States of America.ORCID 0000-0002-2204-7569
Yifang HuThe Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia.
Shaun NielsenCentre for Marine Bio-Innovation and School of Biological, Earth and Environmental Sciences, The University of New South Wales, Sydney, NSW, Australia.ORCID 0000-0001-6855-4227
Torsten ThomasCentre for Marine Bio-Innovation and School of Biological, Earth and Environmental Sciences, The University of New South Wales, Sydney, NSW, Australia.ORCID 0000-0001-9557-3001
Russell PickfordBioanalytical Mass Spectrometry Facility, Mark Wainwright Analytical Center, The University of New South Wales, Sydney, NSW, Australia.ORCID 0000-0001-8982-7618
Sonia BustamanteBioanalytical Mass Spectrometry Facility, Mark Wainwright Analytical Center, The University of New South Wales, Sydney, NSW, Australia.ORCID 0000-0002-5411-2919
Antón Vila-SanjurjoGrupo GIBE, Bioloxía Celular e Molecular, Facultade de Ciencias, Universidade da Coruña (UDC), Campus Zapateira s/n, A Coruña, Spain.ORCID 0000-0001-7820-1644
Gordon K SmythThe Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia.ORCID 0000-0001-9221-2892
J William O BallardSchool of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, NSW, Australia.ORCID 0000-0002-2358-6003
UNSW Sydney · AUThe University of Sydney · AUThe University of Melbourne · AUUniversidade da Coruña · ESWalter and Eliza Hall Institute of Medical Research · AUWashington State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diet may be modified seasonally or by biogeographic, demographic or cultural shifts. It can differentially influence mitochondrial bioenergetics, retrograde signalling to the nuclear genome, and anterograde signalling to mitochondria. All these interactions have the potential to alter the frequencies of mtDNA haplotypes (mitotypes) in nature and may impact human health. In a model laboratory system, we fed four diets varying in Protein: Carbohydrate (P:C) ratio (1:2, 1:4, 1:8 and 1:16 P:C) to four homoplasmic Drosophila melanogaster mitotypes (nuclear genome standardised) and assayed their frequency in population cages. When fed a high protein 1:2 P:C diet, the frequency of flies harbouring Alstonville mtDNA increased. In contrast, when fed the high carbohydrate 1:16 P:C food the incidence of flies harbouring Dahomey mtDNA increased. This result, driven by differences in larval development, was generalisable to the replacement of the laboratory diet with fruits having high and low P:C ratios, perturbation of the nuclear genome and changes to the microbiome. Structural modelling and cellular assays suggested a V161L mutation in the ND4 subunit of complex I of Dahomey mtDNA was mildly deleterious, reduced mitochondrial functions, increased oxidative stress and resulted in an increase in larval development time on the 1:2 P:C diet. The 1:16 P:C diet triggered a cascade of changes in both mitotypes. In Dahomey larvae, increased feeding fuelled increased β-oxidation and the partial bypass of the complex I mutation. Conversely, Alstonville larvae upregulated genes involved with oxidative phosphorylation, increased glycogen metabolism and they were more physically active. We hypothesise that the increased physical activity diverted energy from growth and cell division and thereby slowed development. These data further question the use of mtDNA as an assumed neutral marker in evolutionary and population genetic studies. Moreover, if humans respond similarly, we posit that individuals with specific mtDNA variations may differentially metabolise carbohydrates, which has implications for a variety of diseases including cardiovascular disease, obesity, and perhaps Parkinson's Disease.

Indexed as

Genetic Association StudiesGenotypePhenotypeAnimalsDietDNA, MitochondrialElectron Transport Complex IEnergy MetabolismGenetic FitnessHaplotypesHumansMembrane ProteinsMetabolomeMitochondriaModels, BiologicalModels, MolecularDNA, MitochondrialElectron Transport Complex IMembrane Proteins

Identifiers

PMID30399141
PMCPMC6219761
OpenAlexW2900027369

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.