A zebrafish model to elucidate the impact of host genes on the microbiota

Author:

Thormar Eiríkur Andri1,Rasmussen Jacob Agerbo1ORCID,Mathiessen Heidi2,Marana Moonika Haahr2,Clausen Cecilie Grønlund1,Hansen Martin3,Kodama Miyako1,von Gersdorff Jørgensen Louise2,Limborg Morten Tønsberg1ORCID

Affiliation:

1. Center for Evolutionary Hologenomics GLOBE Institute, University of Copenhagen Copenhagen K Denmark

2. Section for Parasitology and Aquatic Pathobiology, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences University of Copenhagen Frederiksberg C Denmark

3. Department of Environmental Science, Environmental Metabolomics Lab Aarhus University Roskilde Denmark

Abstract

AbstractEvery host species and organism provides a unique environmental niche contributing to the overall diversity of microbial ecosystems from the intestine of an animal to the oceans and forests of our planet. The study of host–microbiota interactions has long focused on the well‐established effects the microbiota has on its host. In contrast, little focus has been allocated to the role of the host in these intricate interactions. However, understanding the role of the host may well be an essential key to understanding the complexity of the relationship between the host and its microbiota. In this study, we present a model in which the effects of host genes on the microbiota can be elucidated and how such genetic effects may shape host‐associated microbiota. We demonstrate a hologenomic approach implementing the CRISPR/Cas system in the zebrafish model to combine the effects of a host gene with 16S metabarcoding and metabolomics data. We show that knocking out the gene coding for the rate‐limiting enzyme in melanogenesis, tyrosinase (tyr), correlates with changes in the intestinal microbiota of zebrafish and differences in the abundance of specific metabolites illustrating the value of our model for studying the impact of host genes on the composition and function of the intestinal microbiota.

Funder

Danmarks Grundforskningsfond

Aarhus Universitets Forskningsfond

Publisher

Wiley

Reference117 articles.

1. Alberdi A. &Gilbert M. T. P.(2019).Hilldiv: An R package for the integral analysis of diversity based on Hill numbers.bioRxiv.https://doi.org/10.1101/545665

2. Andrews S.(2010).FastQC a quality control tool for high throughput sequence data.https://www.bioinformatics.babraham.ac.uk/projects/fastqc/

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