PLoS ONE (Jan 2022)

Genetic variation and microbiota in bumble bees cross-infected by different strains of C. bombi.

  • Seth M Barribeau,
  • Paul Schmid-Hempel,
  • Jean-Claude Walser,
  • Stefan Zoller,
  • Martina Berchtold,
  • Regula Schmid-Hempel,
  • Niklaus Zemp

DOI
https://doi.org/10.1371/journal.pone.0277041
Journal volume & issue
Vol. 17, no. 11
p. e0277041

Abstract

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The bumblebee Bombus terrestris is commonly infected by a trypanosomatid gut parasite Crithidia bombi. This system shows a striking degree of genetic specificity where host genotypes are susceptible to different genotypes of parasite. To a degree, variation in host gene expression underlies these differences, however, the effects of standing genetic variation has not yet been explored. Here we report on an extensive experiment where workers of twenty colonies of B. terrestris were each infected by one of twenty strains of C. bombi. To elucidate the host's genetic bases of susceptibility to infection (measured as infection intensity), we used a low-coverage (~2 x) genome-wide association study (GWAS), based on angsd, and a standard high-coverage (~15x) GWAS (with a reduced set from a 8 x 8 interaction matrix, selected from the full set of twenty). The results from the low-coverage approach remained ambiguous. The high-coverage approach suggested potentially relevant genetic variation in cell surface and adhesion processes. In particular, mucin, a surface mucoglycoprotein, potentially affecting parasite binding to the host gut epithelia, emerged as a candidate. Sequencing the gut microbial community of the same bees showed that the abundance of bacterial taxa, such as Gilliamella, Snodgrassella, or Lactobacillus, differed between 'susceptible' and 'resistant' microbiota, in line with earlier studies. Our study suggests that the constitutive microbiota and binding processes at the cell surface are candidates to affect infection intensity after the first response (captured by gene expression) has run its course. We also note that a low-coverage approach may not be powerful enough to analyse such complex traits. Furthermore, testing large interactions matrices (as with the full 20 x 20 combinations) for the effect of interaction terms on infection intensity seems to blur the specific host x parasite interaction effects, likely because the outcome of an infection is a highly non-linear process dominated by variation in individually different pathways of host defence (immune) responses.