DOI: 10.5061/dryad.xd2547dj3
title: Post-association barrier to host switching maintained despite strong selection in a novel mutualism

description: Following a host shift, repeated co-passaging of a mutualistic pair is
 expected to increase fitness over time in one or both species. 
 Without adaptation, a novel association may be evolutionarily short-lived
 as it is likely to be outcompeted by native pairings.  Here we
 test whether experimental evolution can rescue a low-fitness novel pairing
 between two sympatric species of Steinernema nematodes and their symbiotic
 Xenorhabdus bacteria.  Despite low mean fitness in the novel
 association, considerable variation in nematode reproduction was observed
 across replicate populations.  We selected the most productive
 infections, co-passaging this novel mutualism nine times to determine
 whether selection could improve fitness of either or both
 partners.  We found that neither partner showed increased fitness
 over time.  Our results suggest that the variation in association
 success was not heritable and that mutational input was insufficient to
 allow evolution to facilitate this host shift.  Thus,
 post-association costs of host switching may represent a formidable
 barrier to novel partnerships among sympatric mutualists.
description: <strong>Data
 Collection</strong> We infected each <em>Galleria
 mellonella</em> caterpillar by pipetting 100 nematodes (carrying
 bacteria) in 500uL of ddH2O on to the dorsum of the caterpillar. Infection
 success (Infection_Success) was measured as the proportion of infected
 caterpillars with any nematode emergence.  Mean nematode emergence
 (Estimated_IJ_Count) was estimated by volumetric subsampling.  We
 estimated bacterial carriage (CFUs) by crushing a sample of 1000 IJs for
 at least 5 collections per treatment group per generation.  If no colonies
 grew from the crushing, we used the detection limit of 0.003 CFU/IJ as the
 estimated carriage the in statistical analyses.  
 <strong>Data Description and
 file format</strong> The data file “Dinges et al. 2022
 Ecology & Evolution” contains 7 columns:
 A. Passage: numeric description
 (1-9) of the co-passage infection.<br>B. Treatment: factor
 (Experimental, Bacteria, Nematode) describing the nematode-bacteria
 pairing used for each infection.  Experimental is made up of S. kraussei
 nematodes paired with bacteria from S. affine.  Bacteria is the native
 bacteria pairing – S. affine nematodes carrying their native bacteria.
  Nematode is the native nematode pairing – S. kraussei nematodes carrying
 their native bacteria.<br>C. Host_Mass: numeric (0.11-0.313) mass of
 infected caterpillar in grams.  Host Mass was not recorded for Passages
 5-9, instead "NA" is entered.<br>D. Estimated_IJ_Count:
 numeric number of juvenile nematodes which emerged from successful
 infections.  Where these estimates were not calculated, NA is
 used.<br>E. Infection_Success: binary – 1 indicates an infection had
 nematode emergence, 0 indicates no nematodes emerged from the
 infection<br>F. CFUs: numeric (0.003 – 16.32) bacterial carriage
 calculated as the number of colony forming units (CFUs) divided by the
 number of nematodes crushed in the sample, adjusted for dilution.  If no
 colonies grew, the detection limit, defined as the fewest cells detectable
 in our study was used instead.  If no sample was crushed, NA is
 recorded.<br>G. LogCFUs: numeric, calculated as log(CFUs).  If no
 sample was crushed, NA is recorded. 
 <strong>Software and data
 processing description</strong>
 All statistical
 analyses were performed in R version 3.6.3.  Differences in infection
 success (i.e. the proportion of caterpillars with nematode emergence)
 between the experimental and native-control pairings were analyzed as a
 binomial response variable using a generalized linear model including the
 interaction between pairing treatment and passage number.  Differences in
 nematode emergence, defined as the mean number of nematodes that emerged
 per caterpillar, were analyzed using a generalized linear model assuming
 normal distribution with pairing treatment, passage number, and their
 interaction as main effects, with caterpillar mass as a covariate. 
 Differences in the average number of bacterial cells carried per IJ were
 analyzed using a linear mixed model with the pairing treatment, passage
 number, and their interaction as main effects.  For each model, we
 computed the estimated marginal means (EMMs) and 95% confidence intervals
 for each pairing treatment using the emmeans package. 
description: <strong>License and
 Restriction statement</strong>
 There are no
 licenses or restrictions placed on access to the dataset or any associated
 files. <strong>Code
 Description</strong> The statistical analyses were
 performed in R using the file “Dinges et al. 2022 Ecology &
 Evolution.Rmd” in R Studio.  The first chunk of code loads
 libraries and set up options for the run.  This file uses libraries
 ggplot2 (to generate plots), dplyr (to filter and process data), emmeans
 (to calculate estimated marginal means), and rstatix (to calculate type 3
 fixed effects).  To simplify the output, I set scipen = 999, to prevent
 scientific notation of p-values.  I also set contrasts to “contr.sum” or
 “contr.poly” to accurately calculate the type 3 fixed effects. 
 The second chunk reads in the .csv
 data file, sets “Passage” as a factor (instead of a numeric), replaces
 missing data in “Estimated_IJ_Count” with 0, creates a data frame, “IJ”
 excluding unsuccessful infections, and creates a data frame, “X” excluding
 samples with no bacterial carriage data.
 The third chunk
 creates objects for plot aesthetics: PlotTheme, fill and color for
 points.  The fourth chunk analyses infection
 success for the experimental and nematode treatments (excluding bacteria
 treatment because it is introduced in passage 7).  It also analyzes all
 treatments for Passages 7-9.  Finally, it creates Figure
 2A. The fifth chunk analyzes nematode
 emergence with the data subset “IJ”, and creates Figure
 2B. The sixth chunk analyzes bacterial
 carriage, with the data subset “X” and creates Figure
 2C.