Phylosymbiosis is defined as the relationship in which the microbiome recapitulates the phylogeny of the host and has been demonstrated in a variety of terrestrial organisms, although it has been understudied in fish, the most phylogenetically diverse vertebrate. Given that the species-specificity of fish microbiomes was detected in multiple body parts and differed by body parts, we assumed that the phylogenetic reflection of the microbiome would differ across body parts. Thus, we analyze the difference of phylosymbiotic relationships in the microbial communities found in three body parts (skin, gills, and intestine) of seven wild fish species from four families (Labridae, Sebastidae, Sparidae, and Rajidae) via 16S rRNA gene amplicon sequencing. Fishes were purchased at Docheon port market in Tongyeong City, Korea and were transported to nearby research institutes for aliveness. Mantel tests using dissimilarity values of microbiomes and hosts' divergence times showed that the differences in microbial communities in all three body parts were related to the hosts' divergence time. This pattern was the most pronounced in the skin. Furthermore, fishes from the same family showed similar bacterial compositions on their skins and gills, with clear differences depending on the family, with the exception of Labridae. These results suggest that the skin microbiome is particularly vulnerable to evolutionary pressures. We hypothesized that the evolution of the fish immune system and the difference in feeding habits induced the stronger phylosymbiotic signal in the skin. Collectively, this dataset will be useful for understanding the fish microbiome and give insights into phylosymbiosis of aquatic animals across body parts.
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http://dx.doi.org/10.1007/s00248-024-02467-z | DOI Listing |
Pol J Vet Sci
June 2024
Faculty of Mechanical Engineering, Wrocław University of Science and Technology, Łukasiewicza 5/7, 50-367 Wroclaw, Poland.
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View Article and Find Full Text PDFFront Biosci (Schol Ed)
December 2024
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View Article and Find Full Text PDFFront Biosci (Landmark Ed)
December 2024
Center for Immunology and Cellular Biotechnology, Institute of Medicine and Life Sciences, Immanuel Kant Baltic Federal University, 236001 Kaliningrad, Russia.
Background: Epidermal growth factor receptor 4 (ERBB4) and neuregulin 4 (NRG4) have been shown to reduce steatosis and prevent the development of non-alcoholic steatohepatitis in mouse models, but little to nothing is known about their role in non-alcoholic fatty liver disease (NAFLD) in humans. This study is the first to investigate the expression of and mRNAs and their role in lipid metabolism in the livers of individuals with obesity, type 2 diabetes and biopsy-proven NAFLD.
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Bioinform Adv
December 2024
Computer Science Department, Indiana University, Bloomington, IN 47408, United States.
Motivation: Microbial signatures in the human microbiome are closely associated with various human diseases, driving the development of machine learning models for microbiome-based disease prediction. Despite progress, challenges remain in enhancing prediction accuracy, generalizability, and interpretability. Confounding factors, such as host's gender, age, and body mass index, significantly influence the human microbiome, complicating microbiome-based predictions.
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