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Published November 1, 1999 | public
Journal Article Open

Molecular Characterization of Functional and Phylogenetic Genes from Natural Populations of Methanotrophs in Lake Sediments

Abstract

The 16S rRNA and pmoA genes from natural populations of methane-oxidizing bacteria (methanotrophs) were PCR amplified from total community DNA extracted from Lake Washington sediments obtained from the area where peak methane oxidation occurred. Clone libraries were constructed for each of the genes, and approximately 200 clones from each library were analyzed by using restriction fragment length polymorphism (RFLP) and the tetrameric restriction enzymes MspI, HaeIII, and HhaI. The PCR products were grouped based on their RFLP patterns, and representatives of each group were sequenced and analyzed. Studies of the 16S rRNA data obtained indicated that the existing primers did not reveal the total methanotrophic diversity present when these data were compared with pure-culture data obtained from the same environment. New primers specific for methanotrophs belonging to the genera Methylomonas, Methylosinus, and Methylocystis were developed and used to construct more complete clone libraries. Furthermore, a new primer was designed for one of the genes of the particulate methane monooxygenase in methanotrophs, pmoA. Phylogenetic analyses of both the 16S rRNA and pmoA gene sequences indicated that the new primers should detect these genes over the known diversity in methanotrophs. In addition to these findings, 16S rRNA data obtained in this study were combined with previously described phylogenetic data in order to identify operational taxonomic units that can be used to identify methanotrophs at the genus level.

Additional Information

Copyright © 1999, American Society for Microbiology. Received 12 April 1999/Accepted 23 August 1999 This work was supported by a subcontract to DOE grant DE-AC05-960R22464 with Oak Ridge National Laboratory, managed by Lockheed Martin Energy Research Corp. A.M.C. was supported in part by a National Science Foundation graduate fellowship. We thank John Murray, University of Washington, and Michaeleen Callahan, California Institute of Technology, for their assistance during this study.

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August 22, 2023
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