Ontology highlight
ABSTRACT:
PROVIDER: PRJNA823742 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18649700_1.fastq.gz | Fastqsanger.gz | |||
| SRR18649700_2.fastq.gz | Fastqsanger.gz | |||
| SRR18649701_1.fastq.gz | Fastqsanger.gz | |||
| SRR18649701_2.fastq.gz | Fastqsanger.gz | |||
| SRR18649702_1.fastq.gz | Fastqsanger.gz |
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Project description:Aging is the predominant cause of morbidity and mortality in industrialized countries, yet the molecular mechanisms driving aging and especially the contribution by the microbiome remain unclear. We combined multi-omics with metabolic modeling to comprehensively characterize host–microbiome interactions during aging in mice. Our findings reveal a complex dependency of host metabolism on known and novel microbial interactions. We observed a pronounced reduction in metabolic activity within the aging microbiome accompanied by reduced beneficial interactions between bacterial species. These microbial changes coincided with increased inflammaging as well as a corresponding downregulation of key host pathways, predicted by our model to be microbiome-dependent, 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 anti-aging therapies.
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Project description:The objective of this study was to characterize the major proteomes and metabolites present in beef exudate and determine their relationship with the color and oxidative quality of beef muscles. Beef loin (longissimus lumborum; LD) and tenderloin (psoas major; PM) muscles were cut into sections, individually vacuum-packaged, and aged for 9, 16 and 23 days. Following aging, the meat exudates were collected and analyzed for both proteomics and metabolomics profiles. Both analyses demonstrated that distinct proteins and metabolites clustered by different muscle types and aging times were detected from meat exudate, however, metabolomics profiling presented a greater capability in identifying different aging periods. The proteome profile of PM exudate exhibited a greater concentration of oxidative metabolism enzymes, while the LD exudate contained a higher abundance of glycolytic metabolism enzymes. Greater lipid, nucleotide, carnitine and glucoside metabolites were observed in LD and 23d exudates, further explaining potential postmortem energy metabolism. HSP70 and laminin proteins, together with glucosides metabolites identified in the exudates were correlated (P<0.1 and |r|>0.5) to muscle oxidative stability. The results indicated that meat exudate could be a viable analytical matrix to further understand postmortem metabolism and potentially generate unique biomarker combinations to predict meat quality attributes.
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Project description:In this study, we conducted an integrated analysis of skin measurements, clinical BSTI surveys, and the skin microbiome of 950 Korean subjects to examine the ideal skin microbiome-biophysical association. By utilizing four skin biophysical parameters, we identified four distinct Korean Skin Cutotypes (KSCs) and categorized the subjects into three aging groups based on their age distribution. We established strong connections between 15 core genera and the four KSC types within the three aging groups, revealing three prominent clusters of the facial skin microbiome. Together with skin microbiome variations, skin tone/elasticity distinguishes aging groups while oiliness/hydration distinguishes individual differences within aging groups. Our study provides prospective reality data for customized skin care based on the microbiome environment of each skin type.
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