GeneGeneticsPeer-reviewed journal article
Gut Microbiome-Driven Metabolites Influence Skin Pigmentation in TYRP1 Mutant Oujiang Color Common Carp
Roland Nathan MandaliD, Jing Ke, Nusrat Hasan KanikaiD, Xin HouiD, Zhiyi ZhangiD, Penghui Zhang, Huifan Chen, Chunxiao Zeng, Xiaowen CheniD, Jun WangiD, Chenghui WangiD
Abstract
The gut microbiome is one of the major regulators of the gut-skin axis and is partly regulated by host genetics. In the present study, using comparative high-throughput omics data on CRISPR/Cas9-mediated TYRP1 mutant and wild-color common carp populations, we quantified the proportion of inter-individual variation in the skin transcriptome and blood metabolome by genetic architecture and gut microbiomes. We found 525 differential metabolites (DMs) and 45 differential gut microbial genera in TYRP1 mutant fishes relative to the wild type. Through interaction analysis and causal mediation analyses, we revealed that the TYRP1-mutant derived genetic background may exert an inflammatory Acinetobacter - Leukotrience-C4 and - Spermine metabolic pathway under the regulation of an anti-inflammatory cardio-vascular genetic network underlying the upregulating expression of COMT, PLG, C2, C3, F10, TDO2, MHC1, and SERPINF2 gene for evolving unusual coffee-like color phenotype. This unique network appears to underlie the "coffee-like" color phenotype. We propose that the COMT-mediated causal effect of the unusual gut microbiome on the atypical skin gene expression patterns through the gut-skin metabolic pathway. Article SummaryR.N. Mandal et al. report on the causal effect of gut microbiome-driven metabolites on the expression pattern of regulatory genes underlying an unusual color phenotype. It suggests that TYRP1 Mutation may rise an unusual inflammatory gut microbiome-skin metabolic pathway that may be balanced by an anti-inflammatory cardio-vascular genetic network leading to unique coloration in Oujiang Color Common Carp.
- organism: multiple species
- assay: metagenomics
- assay: metabolomics
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
- approach: experimental assay
- Citations
- 8
- FWCI
- 1.79
- Field percentile
- top 17%
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