563 research outputs found

    Can You Sequence Ecology? Metagenomics of Adaptive Diversification

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    Few areas of science have benefited more from the expansion in sequencing capability than the study of microbial communities. Can sequence data, besides providing hypotheses of the functions the members possess, detect the evolutionary and ecological processes that are occurring? For example, can we determine if a species is adapting to one niche, or if it is diversifying into multiple specialists that inhabit distinct niches? Fortunately, adaptation of populations in the laboratory can serve as a model to test our ability to make such inferences about evolution and ecology from sequencing. Even adaptation to a single niche can give rise to complex temporal dynamics due to the transient presence of multiple competing lineages. If there are multiple niches, this complexity is augmented by segmentation of the population into multiple specialists that can each continue to evolve within their own niche. For a known example of parallel diversification that occurred in the laboratory, sequencing data gave surprisingly few obvious, unambiguous signs of the ecological complexity present. Whereas experimental systems are open to direct experimentation to test hypotheses of selection or ecological interaction, the difficulty in “seeing ecology” from sequencing for even such a simple system suggests translation to communities like the human microbiome will be quite challenging. This will require both improved empirical methods to enhance the depth and time resolution for the relevant polymorphisms and novel statistical approaches to rigorously examine time-series data for signs of various evolutionary and ecological phenomena within and between species.Organismic and Evolutionary Biolog

    Development of a broad-host-range sacB-based vector for unmarked allelic exchange

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    <p>Abstract</p> <p>Background</p> <p>Although genome sequences are available for an ever-increasing number of bacterial species, the availability of facile genetic tools for physiological analysis have generally lagged substantially behind traditional genetic models.</p> <p>Results</p> <p>Here I describe the development of an improved, broad-host-range "in-out" allelic exchange vector, pCM433, which permits the generation of clean, marker-free genetic manipulations. Wild-type and mutant alleles were reciprocally exchanged at three loci in <it>Methylobacterium extorquens </it>AM1 in order to demonstrate the utility of pCM433.</p> <p>Conclusion</p> <p>The broad-host-range vector for marker-free allelic exchange described here, pCM433, has the advantages of a high copy, general <it>Escherichia coli </it>replicon for easy cloning, an IncP <it>oriT </it>enabling conjugal transfer, an extensive set of restriction sites in its polylinker, three antibiotic markers, and <it>sacB </it>(encoding levansucrase) for negative selection upon sucrose plates. These traits should permit pCM433 to be broadly applied across many bacterial taxa for marker-free allelic exchange, which is particularly important if multiple manipulations or more subtle genetic manipulations such as point mutations are desired.</p

    Genetic and Phenotypic Comparison of Facultative Methylotrophy between Methylobacterium extorquens Strains PA1 and AM1

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    Methylobacterium extorquens AM1, a strain serendipitously isolated half a century ago, has become the best-characterized model system for the study of aerobic methylotrophy (the ability to grow on reduced single-carbon compounds). However, with 5 replicons and 174 insertion sequence (IS) elements in the genome as well as a long history of domestication in the laboratory, genetic and genomic analysis of M. extorquens AM1 face several challenges. On the contrary, a recently isolated strain - M. extorquens PA1- is closely related to M. extorquens AM1 (100% 16S rRNA identity) and contains a streamlined genome with a single replicon and only 20 IS elements. With the exception of the methylamine dehydrogenase encoding gene cluster (mau), genes known to be involved in methylotrophy are well conserved between M. extorquens AM1 and M. extorquens PA1. In this paper we report four primary findings regarding methylotrophy in PA1. First, with a few notable exceptions, the repertoire of methylotrophy genes between PA1 and AM1 is extremely similar. Second, PA1 grows faster with higher yields compared to AM1 on C1 and multi-C substrates in minimal media, but AM1 grows faster in rich medium. Third, deletion mutants in PA1 throughout methylotrophy modules have the same C1 growth phenotypes observed in AM1. Finally, the precision of our growth assays revealed several unexpected growth phenotypes for various knockout mutants that serve as leads for future work in understanding their basis and generality across Methylobacterium strains
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