Metabolomic Profiles of Mouse Tissues Reveal an Interplay between Aging and Energy Metabolism

Abstract

Energy metabolism, including alterations in energy intake and expenditure, is closely related to aging and longevity. Metabolomics studies have recently unraveled changes in metabolite composition in plasma and tissues during aging and have provided critical information to elucidate the molecular basis of the aging process. However, the metabolic changes in tissues responsible for food intake and lipid storage have remained unexplored. In this study, we aimed to investigate aging-related metabolic alterations in these tissues. To fill this gap, we employed NMR-based metabolomics in several tissues, including different parts of the intestine (duodenum, jejunum, ileum) and brown/white adipose tissues (BAT, WAT), of young (9–10 weeks) and old (96–104 weeks) wild-type (mixed genetic background of 129/J and C57BL/6) mice. We, further, included plasma and skeletal muscle of the same mice to verify previous results. Strikingly, we found that duodenum, jejunum, ileum, and WAT do not metabolically age. In contrast, plasma, skeletal muscle, and BAT show a strong metabolic aging phenotype. Overall, we provide first insights into the metabolic changes of tissues essential for nutrient uptake and lipid storage and have identified biomarkers for metabolites that could be further explored, to study the molecular mechanisms of aging.

Oral Intake of L-Ornithine-L-Aspartate Is Associated with Distinct Microbiome and Metabolome Changes in Cirrhosis

“…Nuclear magnetic resonance (NMR) metabolomic profiling was performed for urine, serum and stool samples using a well-established pipeline (for details regarding the method, see Supplementary Methods) [18,19]. Metabolites were extracted using methanol, NMR spectra were recorded and processed in Matlab to obtain aligned and normalized datasets.…”

Phosphatidylethanolamine N-methyltransferase Knockout Modulates Metabolic Changes in Aging Mice

“…Metabolites with p < 0.05 are shown in panel B and panel D of supplementary Figure S1-S13. For each tissue, an additional 2D 1 H- 13 C HSQC spectra was recorded to highlight the presented metabolites and to validate the interpretations of 1D 1 H spectra either published previously (for WT [52]) or included in Supplementary Figure S16.…”

“…Alignment and a probabilistic quotient normalization were performed to the 1 H 1 D NMR spectra by Matlab2014b to generate normalized spectra and reduced spectra. Metabolite quantification was based on the signal integration of normalized spectra as described previously [52]. Signal integration was used to generate a volcano plot, orthogonal partial least squares discriminant analysis (O-PLS-DA), permutation analysis, sparse partial least squares discriminant analysis (S-PLS-DA), metabolite set enrichment analysis (MSEA, only over representation analysis (ORA) was performed here [57]), and a heat map using MetaboAnalyst 5.0 [58].…”

“…Plotting the four plasma groups on the S-PLS-DA plot resulted in a component 1 at 30.8% and a component 2 at 18.2% and yielded a distinct separation of WT young and old, as well as between old WT and KO mice (Figure 2G). The aging profile of WT and PEMT KO plasma has both 13 increased and decreased metabolites, 6 of which overlap, suggesting that PEMT affects the metabolic aging of plasma (Supplementary figure S14C, S14D [52]). ORA showed that metabolites with altered levels in the aged KO plasma were related to 5 metabolic pathways, including galactose metabolism, glucose-alanine cycle, Warburg effect, transfer of acetyl groups into mitochondria, and gluconeogenesis (Figure 2H).…”

“…Mouse models are well suited to study age-related metabolic changes due to their analogy to human metabolism [50][51][52]. Here, we investigated the role of PEMT in lipid metabolism and energy homeostasis in young (9-10 weeks) and old (96-104 weeks) wildtype (WT) and PEMT knockout (KO) mice.…”