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Record W4389338959 · doi:10.1038/s41467-023-43550-2

Early-adult methionine restriction reduces methionine sulfoxide and extends lifespan in Drosophila

2023· article· en· W4389338959 on OpenAlexfundno aff
Hina Kosakamoto, Fumiaki Obata, Junpei Kuraishi, Hide Aikawa, Rina Okada, Joshua N. Johnstone, Taro Onuma, Matthew D. W. Piper, Masayuki Miura

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceInstitute of GeneticsJapan Agency for Medical Research and Development
KeywordsMSRAMethionineLongevityMethionine sulfoxide reductaseBiologyDrosophila (subgenus)GeneticsGeneAmino acid

Abstract

fetched live from OpenAlex

Methionine restriction (MetR) extends lifespan in various organisms, but its mechanistic understanding remains incomplete. Whether MetR during a specific period of adulthood increases lifespan is not known. In Drosophila, MetR is reported to extend lifespan only when amino acid levels are low. Here, by using an exome-matched holidic medium, we show that decreasing Met levels to 10% extends Drosophila lifespan with or without decreasing total amino acid levels. MetR during the first four weeks of adult life only robustly extends lifespan. MetR in young flies induces the expression of many longevity-related genes, including Methionine sulfoxide reductase A (MsrA), which reduces oxidatively-damaged Met. MsrA induction is foxo-dependent and persists for two weeks after cessation of the MetR diet. Loss of MsrA attenuates lifespan extension by early-adulthood MetR. Our study highlights the age-dependency of the organismal response to specific nutrients and suggests that nutrient restriction during a particular period of life is sufficient for healthspan extension.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.836
Threshold uncertainty score0.663

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.302
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations44
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicGenetics, Aging, and Longevity in Model OrganismsFrench-language works237,207