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Data from: Weak phylogenetic signal in physiological traits of methane-oxidizing bacteria

Cite this dataset

Krause, Sascha; van Bodegom, Peter M.; Cornwell, Will K.; Bodelier, Paul L. E. (2014). Data from: Weak phylogenetic signal in physiological traits of methane-oxidizing bacteria [Dataset]. Dryad.


The presence of phylogenetic signal is assumed to be ubiquitous. However, for microorganisms, this may not be true given that they display high physiological flexibility and have fast regeneration. This may result in fundamentally different patterns of resemblance, that is, in variable strength of phylogenetic signal. However, in microbiological inferences, trait similarities and therewith microbial interactions with its environment are mostly assumed to follow evolutionary relatedness. Here, we tested whether indeed a straightforward relationship between relatedness and physiological traits exists for aerobic methane-oxidizing bacteria (MOB). We generated a comprehensive data set that included 30 MOB strains with quantitative physiological trait information. Phylogenetic trees were built from the 16S rRNA gene, a common phylogenetic marker, and the pmoA gene which encodes a subunit of the key enzyme involved in the first step of methane oxidation. We used a Blomberg's K from comparative biology to quantify the strength of phylogenetic signal of physiological traits. Phylogenetic signal was strongest for physiological traits associated with optimal growth pH and temperature indicating that adaptations to habitat are very strongly conserved in MOB. However, those physiological traits that are associated with kinetics of methane oxidation had only weak phylogenetic signals and were more pronounced with the pmoA than with the 16S rRNA gene phylogeny. In conclusion, our results give evidence that approaches based solely on taxonomical information will not yield further advancement on microbial eco-evolutionary interactions with its environment. This is a novel insight on the connection between function and phylogeny within microbes and adds new understanding on the evolution of physiological traits across microbes, plants and animals.

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