Home
 /
Papers
 /
Biochemistry
 /
Mapping the mammalian dark metabolome by in vivo isotope tracing
Preprint
Open access
V1
Top 1% · Validated by QED

Mapping the mammalian dark metabolome by in vivo isotope tracing

Michael R. MacArthur, Justine Raeber, Wenyun Lu +22 more
April 2026
 ·
bioRxiv
 ·
DOI 
10.64898/2026.03.31.713900
94
%
Reproducible
QED Impressions
This paper passed independent validation.
QED's automated review checked the evidence supporting each claim, the statistical methods, and whether the results are reproducible from the data provided.

It ranks in the top 1% of preprints assessed in Biochemistry this quarter.
Run full QED analysis
Read paper
Save

Why this is interesting

The mammalian metabolome's 'dark matter'—thousands of uncharacterized signals—is illuminated here through systematic isotope tracing and a novel multimodal AI, revealing unprecedented chemical families and an aging-linked isoprenoid pathway rooted in impaired CoA biosynthesis.

QED claims analysis

Summary

Systematic in vivo isotope tracing of 26 labeled precursors across mouse tissues, combined with multimodal AI-based structure elucidation, reveals the biosynthetic origins of thousands of unidentified mammalian metabolites and discovers multiple previously unrecognized metabolite families—including cysteine-derived alkylthiazolidines, short-chain N-acyltaurines, and mevalonate-derived isoprenoids—with the latter markedly depleted in aging due to impaired coenzyme A synthesis, thereby establishing defective CoA biosynthesis as a fundamental hallmark of mammalian aging.

See full analysis
Main Claim 1 –

In vivo isotope tracing maps precursors of unknown mammalian metabolites

Main Claim 2 –

Multimodal AI links isotope labeling to metabolite structures

Main Claim 3 –

Isotope tracing discovers novel mammalian metabolite families and chemistries

Supporting evidence

  • Expanded taurine metabolism includes short-chain N-acyltaurines and N-oxidized taurines
  • New metabolites are conserved across mammals and detectable in humans
  • Newly discovered metabolites are dysregulated in human cancers
  • Most newly discovered metabolites originate from host, not microbiome
  • Several newly discovered metabolites show male-biased sexual dimorphism
Main Claim 4 –

Aging depletes mevalonate metabolites via impaired coenzyme A synthesis

Supporting evidence

  • Impaired pantothenate phosphorylation drives defective CoA synthesis in aging

Abstract

Despite decades of biochemical study, a comprehensive map of the mammalian metabolome remains elusive. Mass spectrometry-based metabolomics detects thousands of small molecule-associated signals in mammalian tissues, but it is currently unclear how many of these reflect products of endogenous metabolism. Here, we leverage systematic in vivo isotope tracing to infer the biosynthetic origins of unidentified metabolites. We administered 26 different isotopically labelled nutrients to mice, measured circulating and tissue metabolite labelling by mass spectrometry, and developed a statistical framework to infer the number of carbon atoms incorporated from each of these precursors into more than 4,000 putative metabolites. We show this information can be harnessed for biosynthesis-aware structure elucidation using a multimodal AI model that co-embeds isotopic labelling patterns with chemical structures. This approach revealed several previously unrecognized families of mammalian metabolites, including cysteine-derived alkylthiazolidines, dithioacetal mercapturic acid derivatives, short-chain N-acyltaurines, acylglycyltaurines, and N-oxidized taurines. It further uncovered a family of mevalonate-derived isoprenoid metabolites that includes 2,3-dihydrofarnesoic acid, which is markedly depleted in both mouse and human aging. Age-related depletion of these isoprenoids is driven by impaired coenzyme A synthesis. Our work establishes the biosynthetic precursors for thousands of unidentified metabolites and reveals multiple previously unrecognized branches of mammalian metabolism.

Related papers

How the QED Score works

QED Score is a validated AI-based quality metric that evaluates life science papers on two dimensions: originality and validity. Each manuscript is anonymized, broken down into its claims and supporting evidence, and examined by specialized AI agents for statistical rigor, consistency across figures, and fit with the existing literature. Scores are percentile ranks, so they're comparable across fields. In blinded tests, expert professors sided with QED Score over journal rank in 75% of decisive cases.
Read the methodology

Free access for academic researchers

Create your free QED account to validate your research, strengthen grant proposals, and uncover scientific insights.
We've sent you an access link.
Please check your inbox.

Didn't get your email? Check your spam folder or reach out to info@qedscience.com

Oops! Something went wrong while submitting the form.
Looking for QED for pharma, biotech or life science organizations?