Zhu, Z.-J. | bioRxiv Science

bioRxiv2018

Metabolic Reaction Network-based Recursive Metabolite Identification for Untargeted Metabolomics

Metabolite identification is a long-standing challenge in untargeted metabolomics and a major hurdle for functional metabolomics studies. Here, we developed a metabolic reaction network-based recursive algorithm and webserver called MetDNA for the large-scale and unambiguous identification of metabolites (available at http://metdna.zhulab.cn). We showcased the versatility of our workflow using different instrument platforms, data acquisition methods, and biological sample types and demonstrated that over 2,000 metabolites could be identified from one experiment.

bioinformatics↗

bioRxiv2018

Epigenetic Drift of H3K27me3 in Aging Links Glycolysis to Healthy Longevity

Epigenetic alteration has been implicated in aging. However, the mechanism by which epigenetic change impacts aging is unclear. H3K27me3, a highly conserved histone modification signifying transcriptional repression, is marked and maintained by Polycomb Repressive Complexes (PRCs). Here, we explore the mechanism by which age-modulated increase of H3K27me3 impacts adult lifespan. Using Drosophila, we reveal that aging leads to loss of fidelity in epigenetic marking and drift of H3K27me3 and consequential reduction in the expression of glycolytic genes with negative effects on energy production and redox state. Moreover, we show that a reduction of H3K27me3 by PRCs-deficiency promotes glycolysis and healthy lifespan. While perturbing glycolysis by gene mutation diminishes the pro-lifespan benefits mediated by PRCs-deficiency, transgenic increase of glycolytic genes in wild-type animals extends longevity. Together, we propose that epigenetic drift of H3K27me3 defines a new aging mechanism and that stimulation of glycolysis promotes metabolic health and longevity.

molecular biology↗