SNIC
SUPR
SNIC SUPR
Ostrich microbiome
Dnr:

SNIC 2018/8-181

Type:

SNAC Small

Principal Investigator:

Charlie Cornwallis

Affiliation:

Lunds universitet

Start Date:

2018-05-10

End Date:

2019-06-01

Primary Classification:

10606: Microbiology (medical to be 30109 and agricultural to be 40302)

Allocation

Abstract

The community of bacteria harboured within the gastrointestinal tract of animals – ‘the gut microbiome’ – has been established as an important determinant of host health and physiology (Sekirov et al. 2010). Although research has largely focused on humans and model organisms, it is becoming increasingly recognised that the gut microbiome may play an important role in a variety of ecological and evolutionary processes, as it has been associated with disease resistance, behaviour, mate selection, longevity, and adaptation (Sharon et al. 2010; Koch & Schmid-Hempel 2011; Muegge et al. 2011; Ezenwa et al. 2012; Brooks et al. 2016; Smith et al. 2017). Over the past four years we have been studying the role of the gut microbiome in a non-model organism, the ostrich, which has highly variable growth and known to suffer from episodes of severe mortality associated with outbreaks of gut bacteria. We have developed a system for reliably monitoring gut microbiomes and characterised the bacteria associated host health (Videvall et al. 2017 msystems; Videvall et al. 2018 Mol. Ecol. Res; Videvall et al. Biorxiv). However, we known very little in ostriches and other species about how beneficial and harmful bacteria spread within populations. To address this problem we conducted an experiment over the past two years that manipulated genetic diversity within developing groups of offspring and in half the groups seeded their microbiomes with adult faeces, while in the other half gave them a control diet. We collected repeated faecal samples from 150 individuals (5 samples per individual) throughout development and used illumina miseq sequencing. The sequence data is now available and we request resources on uppmax to analyse this data.