Data from: Microbial solutions to dietary stress: Experimental evolution reveals host-microbiome interplay in Drosophila melanogaster
Data files
Jan 16, 2025 version files 586.43 KB
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2536_aceto_ovidata.csv
50 KB
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acetos_uricacid_210713b.csv
2.13 KB
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ancom_donor_flygeno.csv
1.99 KB
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chs_fecund_variance_adds.csv
651 B
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chs_nowolb_donors_obj_sp_SHARE.rds
19.30 KB
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CHScomp_table.csv
509.32 KB
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README.md
3.03 KB
Abstract
Can the microbiome serve as a reservoir of adaptive potential for hosts? To address this question, we leveraged ~150 generations of experimental evolution in Drosophila melanogaster in a stressful, high-sugar (HS) diet. We performed a fully reciprocal transplant experiment using the control and HS bacteria. If the microbiome confers benefits to hosts, then transplant recipients should gain fitness benefits compared to controls. Interestingly, we found that such benefits exist, but their magnitude depends on evolutionary history—mismatches between fly evolution and microbiome reduced fecundity and potentially exerted fitness costs, especially in the stressful HS diet. The dominant HS bacteria (Acetobacter pasteurianus) uniquely encoded several genes to enable uric acid degradation, mediating the toxic effects of uric acid accumulation due to the HS diet for flies. Our study demonstrates that host genotype x microbiome x environment interactions have substantial effects on host phenotype, highlighting how host evolution and ecological context together shape the adaptive potential of the microbiome.
README: Data from: Microbial solutions to dietary stress: Experimental evolution reveals host-microbiome interplay in Drosophila melanogaster
https://doi.org/10.5061/dryad.0vt4b8h7z
Description of the data and file structure
data was collected following ~150 generations of adaptation to HS diet selection
fully reciprocal host x microbiome x diet transplant
Files and variables
File: acetos_uricacid_210713b.csv
Description: uric acid degradation by C or HS Acetobacter on fly food
Variables
- sample: sample ID
- abs: absorbance value
- um.ua: conversion to micromolar uric acid
- treatment: full treatment code (diet x uric acid x microbe)
- diet: C or HS diet
- ua: how much uric acid added (0 or 200)
- microbe: sterile, C Aceto, or HS Aceto
File: 2536_aceto_ovidata.csv
Description: egg lay data for recipients of microbiome transplant
Variables
- plate.no: egg lay plate number
- date: date of egg lay
- well: which well in 24-well plate
- ovi.plate treat: C or HS ovipostion media
- fly.treat: total treatment (fly, microbiome, diet manipulation)
- fly.geno: control or high sugar fly genotype
- fly.micro: sterile, control Acetobacter, or high sugar Acetobacter
- fly.food: control or high sugar diet
- fly.ID: fly rearing tube
- egg.no: number of eggs produced by female
File: ancom_donor_flygeno.csv
Description:
Variables
- ASV ID: differentially expressed ASV ID
- clr: centered log transformed abundance of ASV
- W: test stat
- sig: significance for differentially abundant between C or HS fly
- taxonomy: taxonomic assignment of ASV
File: chs_nowolb_donors_obj_sp_SHARE.rds
Description: phyloseq object for microbiome analysis. Please download the package "phyloseq" to use this Rds object.
File: CHScomp_table.csv
Description: RAST assignments for function between C and HS Acetobacter strains
Variables
- Presence: A= HS acetobacter, B= C Acetobacter, A&B = shared between both strains
- Category: broad scale functional assignment
- Subcategory: subcategory functional assignment
- Subsystem: subsystem functional assignment
- Role: specific function
- Organism A: annotation in HS Acetobacter
- SS active A: present in HS Acetobacter
- Organism B: annotation in C Acetobacter
SS active B: present in C Acetobacter
File: chs_fecund_variance_adds.csv
Description: Marginal R2 values for each model to assess the relative contribution of host genotype, microbiome, and diet to fecundity. Models were zero-inflated poisson generalized mixed linear models. Marginal R2 was estimated using MuMIN r.squaredGLMM.
Variables
- Model = terms included in statistical model
- delta r2 = marginal R2 calculated using delta method (only this data is plotted in the supplement)
- lognormal r2 = marginal R2 calculated using lognormal method
- trigamma r2 = marginal R2 calculated using trigamma method