4.7 Article

Variation in the Microbiota Associated with Daphnia magna Across Genotypes, Populations, and Temperature

Journal

MICROBIAL ECOLOGY
Volume 79, Issue 3, Pages 731-742

Publisher

SPRINGER
DOI: 10.1007/s00248-019-01412-9

Keywords

Microbiome; Cladocera; Water fleas; Climate change; Reproducibility

Funding

  1. National Science Foundation [MCB-1150213] Funding Source: Medline
  2. M.J. Murdock Charitable Trust [none] Funding Source: Medline

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Studies of how the microbiome varies among individuals, populations, and abiotic conditions are critical for understanding this key component of an organism's biology and ecology. In the case of Daphnia, aquatic microcrustaceans widely used in population/community ecology and environmental science studies, understanding factors that influence microbiome shifts among individuals is useful for both basic and applied research contexts. In this study, we assess differences in the microbiome among genotypes of D. magna collected from three regions along a large latitudinal gradient (Finland, Germany, and Israel). After being reared in the lab for many years, we sought to characterize any differences in genotype- or population-specific microbial communities, and to assess whether the microbiota varied among temperatures. Our study is similar to a recent comparison of the microbial communities among D. magna genotypes raised in different temperatures published by Sullam et al. (Microb Ecol 76(2):506-517, 2017), and as such represents one of the first examples of a reproducible result in microbiome research. Like the previous study, we find evidence for a strong effect of temperature on the microbiome of D. magna, although across a much smaller temperature range representing potential near-future climates. In addition, we find evidence that the microbiomes of D. magna genotypes from different regions are distinct, even years after being brought into the laboratory. Finally, our results highlight a potentially common finding in the expanding area of microbiome research-differences among treatments are not necessarily observed in the most abundant taxonomic groups. This highlights the importance of considering sampling scheme and depth of coverage when characterizing the microbiome, as different experimental designs can significantly impact taxon-specific results, even when large-scale effects are reproduced.

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