Ecological and evolutionary inferences from aphid microbiome analyses depend on methods and experimental design

Author:

Wolfgang Adrian1ORCID,Tack Ayco J. M.2ORCID,Berg Gabriele134ORCID,Abdelfattah Ahmed13ORCID

Affiliation:

1. Institute of Environmental Biotechnology Graz University of Technology Graz Austria

2. Department of Ecology, Environment and Plant Sciences Stockholm University Stockholm Sweden

3. Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB) Potsdam Germany

4. Institute for Biochemistry and Biology University of Potsdam Potsdam Germany

Abstract

AbstractIntroductionAphids play an important role in agroecological contexts as pests and vectors of plant diseases. Aphid performance is closely connected to microbial endosymbionts that provide different benefits or costs to both the aphids and their hosts plants. Furthermore, the microbiome of aphids is connected to soil microbiomes via the plant. Aphid microbiome experiments usually include a pooling step, where several individuals are sequenced together to obtain sufficient DNA concentrations but pooling may blur intraspecific variations.Materials and MethodsTo investigate the effects of sequencing single versus pooled aphids on the results of microbiome analyses, we compared 16S rRNA/ITS amplicon libraries from pooled and single oak aphids (Tuberculatus annulatus HARTIG) under three different soil treatments. We tested whether results quantitatively or qualitatively depend on pooling aphids, prevalence‐based in silico filtering or removal of the primary endosymbiont (Buchnera aphidicola). Buchnera phylogeny, prevalence and abundance of secondary endosymbionts and effects of soil microbiota were investigated.ResultsPooling leads to quantitative differences in bacteria and qualitative differences in fungal species richness, bacterial community composition and partially fungal community composition. Filtering‐dependent results were obtained for bacterial evenness. Buchnera phylogeny supports the hypothesis of cospeciation of primary endosymbionts in oak aphids. We detected Arsenophonus, Hamiltonella, Rickettsia, Rickettsiella, Serratia and Sphingopyxis in oak aphids, with their prevalence and abundance partially affected by pooling. Pooling leads to overestimating the frequency of multispecies endosymbiont infections, while underestimating their relative abundance.ConclusionWe hereby extend our view on non‐model aphid microbiomes and identify pitfalls in experimental design in aphid microbiome research.

Publisher

Wiley

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