Bayesian selection of continuous-time Markov chain evolutionary models.
We develop a reversible jump Markov chain Monte Carlo approach to estimating the posterior distribution of phylogenies based on aligned DNA/RNA sequences under several hierarchical evolutionary models. Using a proper, yet nontruncated and uninformative prior, we demonstrate the advantages of the Bayesian approach to hypothesis testing and estimation in phylogenetics by comparing different models for the infinitesimal rates of change among nucleotides, for the number of rate classes, and for the relationships among branch lengths. We compare the relative probabilities of these models and the appropriateness of a molecular clock using Bayes factors. Our most general model, first proposed by Tamura and Nei, parameterizes the infinitesimal change probabilities among nucleotides (A, G, C, T/U) into six parameters, consisting of three parameters for the nucleotide stationary distribution, two rate parameters for nucleotide transitions, and another parameter for nucleotide transversions. Nested models include the Hasegawa, Kishino, and Yano model with equal transition rates and the Kimura model with a uniform stationary distribution and equal transition rates. To illustrate our methods, we examine simulated data, 16S rRNA sequences from 15 contemporary eubacteria, halobacteria, eocytes, and eukaryotes, 9 primates, and the entire HIV genome of 11 isolates. We find that the Kimura model is too restrictive, that the Hasegawa, Kishino, and Yano model can be rejected for some data sets, that there is evidence for more than one rate class and a molecular clock among similar taxa, and that a molecular clock can be rejected for more distantly related taxa.
Community proteogenomics reveals insights into the physiology of phyllosphere bacteria
Aerial plant surfaces represent the largest biological interface on Earth and provide essential services as sites of carbon dioxide fixation, molecular oxygen release, and primary biomass production. Rather than existing as axenic organisms, plants are colonized by microorganisms that affect both their health and growth. To gain insight into the physiology of phyllosphere bacteria under in situ conditions, we performed a culture-independent analysis of the microbiota associated with leaves of soybean, clover, and Arabidopsis thaliana plants using a metaproteogenomic approach. We found a high consistency of the communities on the 3 different plant species, both with respect to the predominant community members (including the alphaproteobacterial genera Sphingomonas and Methylo bacterium) and with respect to their proteomes. Observed known proteins of Methylobacterium were to a large extent related to the ability of these bacteria to use methanol as a source of carbon and energy. A remarkably high expression of various TonB-dependent receptors was observed for Sphingomonas. Because these outer membrane proteins are involved in transport processes of various carbohydrates, a particularly large substrate utilization pattern for Sphingomonads can be assumed to occur in the phyllosphere. These adaptations at the genus level can be expected to contribute to the success and coexistence of these 2 taxa on plant leaves. We anticipate that our results will form the basis for the identification of unique traits of phyllosphere bacteria, and for uncovering previously unrecorded mechanisms of bacteria-plant and bacteria-bacteria relationships.
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