In this study, we performed the first combined transcriptome, proteome, acetylome, and metabolome analyses of young and old mouse livers under physiological conditions. Transcriptome, proteome, and acetylome profiles revealed different expression patterns in old and young mice, in contrast to metabolomic profiles. Although many metabolic alterations were observed in all four omics, pyrimidine and glutathione metabolisms were clearly dysregulated during hepatic aging.
Aging is commonly accompanied by a progressive decline of cellular functions, but the aging liver appears to preserve its function relatively well [9, 18, 19]. In this study, the aging-related alterations in the four omics were generally mild, although fat accumulation was clearly observed in the liver. Transcriptome analysis identified changed levels of cytochrome P450 family members, whereas proteome analysis found alterations of both cytochrome P450 and cytochrome c family member levels. However, cytochromes are involved in many metabolic processes of endogenous or exogenous compounds [20, 21]. Although aging is a risk factor for NAFLD [9, 22], lipid metabolism may not be the critical pathway during hepatic aging. We, therefore, sought additional lines of evidence to further explore hepatic aging using acetylome and metabolome analyses.
Acetylation is a post-translational modification that integrates key physiological processes with gene regulation . Acetylation is sensitive to intracellular metabolic alterations because acetyl-CoA derived from nutrient metabolism, especially lipid-derived acetyl-CoA, is its major carbon source . The metabolome represents the collection of small molecules involved in metabolism, and improvements in the relevant analytical technologies provide significant information for biomarker and mechanism analyses [25, 26]. In this study, transcriptome, proteome, acetylome, and metabolome analyses each presented characteristic changes during aging. However, alterations in pyrimidine and glutathione metabolisms were especially notable because they were observed in all four omics results in the aging liver.
Down-regulation of nucleic acid metabolism occurs in Caenorhabditis elegans and mouse heart during aging [7, 27]. Intermediates of pyrimidine or purine metabolism, such as uridine, cytidine, and hypoxanthine, extend the lifespan of C. elegans [7, 28]. Our metabolome data identified increased levels of deoxycytidine, D-ribose 5-phosphate, AMP, and adenine, and decreased levels of dihydrofolate, dihydrouracil, deoxyuridine, uracil, cytidine, thymidine, xanthine, AICAR, IMP, and GMP in the aging mouse liver. Disruption of nucleic acid metabolism is associated with increased mutagenesis, genomic instability, and tumorigenesis. Alterations of intracellular deoxyribonucleoside triphosphate (dNTP) pools may impair DNA synthesis and DNA replication, causing cell cycle dysregulation and double-stranded DNA breaks [29–31]. During hepatic aging, we observed down-regulation of Cdk1, Cdkn2c, Ccnd2 (cyclin D2), Ccne2 (cyclin E2), Ccnl1 (cyclin L1), Ccnl2 (cyclin L2), and Ccnt2 (cyclin T2), and up-regulation of Inca1 (inhibitor of CDK, cyclin A1 interacting protein 1) in the transcriptome. In the proteome of the aging liver, we observed decreased levels of cyclin-dependent kinase inhibitor 1B (Cdkn1b). These changes in the levels of cell cycle-associated transcripts and proteins indicate that cell cycle dysregulation is likely to happen in the mouse liver during aging [32, 33], and may partially contribute to pyrimidine metabolism dysregulation. Moreover, down-regulation of histones, together with dysregulated pyrimidine metabolism, may exacerbate aging-associated genomic instability. Considering that the liver is the major organ for nucleic acid metabolism in mammals, a dysregulated pyrimidine metabolism in the liver is likely to change the levels of nucleic acids in the whole body and accelerate systemic aging.
The decrease in glutathione levels during aging was found decades ago [34, 35]. Glutathione deficiency increases the cellular risk for oxidative damage, and glutathione imbalance is observed in a wide range of pathological conditions . In this study, however, metabolome analysis only identified decreased levels of glutathione disulfide, 5-L-glutamyl-L-alanine, gamma-L-glutamyl-L-valine, and gamma-L-glutamyl-L-glutamic acid in the aging mouse liver. We expect that improvements in metabolome technology may help to identify more metabolites and detect variations in glutathione levels directly in future studies.
This study also revealed that immunological function is altered during hepatic aging. Previous studies reported broadly up-regulated interferon signaling with aging across tissues and species [13, 14]. In this multi-omics aging study, transcriptome analysis revealed up-regulated arachidonic acid metabolism, including prostamide/prostaglandin F synthase and leukotriene-B(4) omega-hydroxylase 2, during aging, and metabolome analysis confirmed increased arachidonic acid levels in the aging liver. In addition, the complement and coagulation cascades were decreased in both the transcriptome and proteome. Decreased complement may contribute to decreased hepatic protein synthesis ability and/or inflammation-associated complement consumption. As Xia et al. have summarized, aging-associated adaptive immunity decline is called immunosenescence, and an increase in the body’s proinflammatory status with advancing age is called inflamm-aging [37, 38]. Thus, inflamm-aging and immunosenescence may simultaneously occur during hepatic aging.
Mammalian aging is a highly complex process spanning gene expression to metabolism, and thus multi-omics analysis can strongly support aging research. However, although each omics analysis provided abundant information, integrated analysis among them is quite a challenge. In this study, we pooled the liver samples and performed proteome and acetylome analyses using an MS2-based TMT strategy and the Significance A algorithm. MS2-based TMT can identify peptides precisely but introduce ratio compression . We probably obtained a shortlist of differentially expressed proteins and excluded the interference of individual differences to some extent. We calculated Spearman correlation coefficients and found that the correlation between transcriptome and proteome and between proteome and acetylome were both low. Differences between each omics brought obstacles to reconstruct complete biological processes and signaling pathways but also prompted us to view aging from new perspectives. We expect technical and analytical improvements to increase identification accuracy and help future multi-omics analyses. We also hope that more omics methods can be applied and integrated for aging research. It is important to investigate other organs and both sexes in future studies to avoid biases  and obtain a comprehensive profile of liver aging and systematic aging.