Cellular and Molecular BioengineeringSystems BiologyPeer-reviewed journal article
Multiomic Integration Reveals Taxonomic Shifts Correlate to Serum Cytokines in an Antibiotics Model of Gut Microbiome Disruption
Abstract
The gut microbiome interacts with many systems throughout the human body. Microbiome disruption reduces bone tissue mechanics but paradoxically slows osteoarthritis progression. The microbiome also mediates inflammatory and immune responses, including serum cytokines. Towards our long-term goal of studying how the gut microbiome interacts with synovial joint health and disease, we examined how antibiotics-induced changes to microbial taxa abundance associated to serum cytokine levels. Mice (n = 5+) were provided ad libitum access to water containing antibiotics (1 g/L neomycin, 1 g/L ampicillin, or 1 g/L ampicillin with 0.5 g/L neomycin) or control water from 5- to 16-weeks old, corresponding in skeletal development to [~]10 to [~]25 years in humans. At humane euthanasia, we collected cecum contents for 16S metagenomics and blood for serum cytokine quantification for comparison to control and among antibiotic groups. We used dimensional reduction techniques, multiomic integration, and correlation to discriminate antibiotic groups and identify specific relationships between high-abundance taxa and serum cytokines. Antibiotic treatment significantly lowered diversity, altered phylum relative abundance, and resulted in significant association with specific taxa. Dimensional reduction techniques and multiomic integration revealed distinct antibiotic-associated clusters based on genera relative abundance and cytokine serum concentration. Cytokines IL-6, MIP-1B, and IL-10 significantly contributed to antibiotic discrimination, significantly different among antibiotic treatments, and had significant correlations with specific taxa. Antibiotic treatment resulted in heterogenous response in gut microbiome and serum cytokines, allowing significant microbe-cytokine links to emerge. The relationships identified here will enable further investigation of the gut microbiomes role in modifying joint health and disease.
- organism: mouse
- assay: metagenomics
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 1
- FWCI
- 0.30
- Field percentile
- 50th percentile
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