Nature MicrobiologySystems BiologyPeer-reviewed journal article
Metabolic modeling reveals the aging-associated decline of host-microbiome metabolic interactions in mice
Lena BestiD, Thomas DostiD, Daniela Esser, Stefano FloriD, Andy Mercado GamarraiD, Madlen Haase, A. Samer KadibalbaniD, Γεώργιος ΜαρίνοςiD, Alesia WalkeriD, Johannes ZimmermanniD, Rowena SimoniD, Silvio SchmidtiD, Jan TaubenheimiD, Sven KünzeliD, Robert HäsleriD, Sören FranzenburgiD, Marco GrothiD, Silvio WaschinaiD, Philip C RosenstieliD, Felix SommeriD, Otto Wilhelm WitteiD, Philippe Schmitt‐KoppliniD, John F. BainesiD, Christiane FrahmiD, Christoph KaletaiD
- Citations
- 65
- FWCI
- 19.43
- Field percentile
- top 1%
Abstract
Aging is the predominant cause of morbidity and mortality in industrialized countries. The specific molecular mechanisms that drive aging are poorly understood, especially the contribution of the microbiota in these processes. Here, we combined multi-omics with metabolic modeling in mice to comprehensively characterize host-microbiome interactions and how they are affected by aging. Our findings reveal a complex dependency of host metabolism on microbial functions, including previously known as well as novel interactions. We observed a pronounced reduction in metabolic activity within the aging microbiome, which we attribute to reduced beneficial interactions in the microbial community and a reduction in its metabolic output. These microbial changes coincided with a corresponding downregulation of key host pathways predicted by our model to be dependent on the microbiome that are crucial for maintaining intestinal barrier function, cellular replication, and homeostasis. Our results elucidate microbiome-host interactions that potentially influence host aging processes, focusing on microbial nucleotide metabolism as a pivotal factor in aging dynamics. These pathways could serve as future targets for the development of microbiome-based therapies against aging. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/587009v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@a8e7faorg.highwire.dtl.DTLVardef@115f35aorg.highwire.dtl.DTLVardef@1bbf32org.highwire.dtl.DTLVardef@1a58c7f_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: mouse
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- approach: statistical model
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