Current metagenomic approaches to the study of complex microbial consortia provide a glimpse into the community metabolism and occasionally allow genomic assemblies for the most abundant organisms. However, little information is gained for the members of the community present at low frequencies, especially those representing yet-uncultured taxa, which include the bulk of the diversity present in most environments. Here we used phylogenetically directed cell separation by fluorescence in situ hybridization and flow cytometry, followed by amplification and sequencing of a fraction of the genomic DNA of several bacterial cells that belong to the TM7 phylum. Partial genomic assembly allowed, for the first time, a look into the evolution and potential metabolism of a soil representative from this group of organisms for which there are no species in stable laboratory cultures. Genomic reconstruction from targeted cells of uncultured organisms isolated directly from the environment represents a powerful approach to access any specific members of a community and an alternative way to assess the community's metabolic potential.Over the last several years, there has been an unprecedented surge in the number and diversity of genomic approaches used to study microbial communities (24, 45). While sequencebased methods and functional screening have been used successfully over the past decade to discover specific genes and gene products from the environment (42), most of the research was focused on a few metabolic markers or was aimed primarily at biotechnological applications (29). A number of approaches have been developed to better understand the structure of microbial communities and to establish links between specific organisms and the metabolic potential encoded in their genes. Among these, fluorescence in situ hybridization (FISH)

Low-biomass samples from nitrate and heavy metal contaminated soils yield DNA amounts that have limited use for direct, native analysis and screening. Multiple displacement amplification (MDA) using 29 DNA polymerase was used to amplify whole genomes from environmental, contaminated, subsurface sediments. By first amplifying the genomic DNA (gDNA), biodiversity analysis and gDNA library construction of microbes found in contaminated soils were made possible. The MDA method was validated by analyzing amplified genome coverage from approximately five Escherichia coli cells, resulting in 99.2% genome coverage. The method was further validated by confirming overall representative species coverage and also an amplification bias when amplifying from a mix of eight known bacterial strains. We extracted DNA from samples with extremely low cell densities from a U.S. Department of Energy contaminated site. After amplification, smallsubunit rRNA analysis revealed relatively even distribution of species across several major phyla. Clone libraries were constructed from the amplified gDNA, and a small subset of clones was used for shotgun sequencing. BLAST analysis of the library clone sequences showed that 64.9% of the sequences had significant similarities to known proteins, and "clusters of orthologous groups" (COG) analysis revealed that more than half of the sequences from each library contained sequence similarity to known proteins. The libraries can be readily screened for native genes or any target of interest. Whole-genome amplification of metagenomic DNA from very minute microbial sources, while introducing an amplification bias, will allow access to genomic information that was not previously accessible.Recent studies have demonstrated that natural attenuation and bioremediation of metals, radionuclides, and organic contaminants cannot be effectively applied at many sites until we have a better understanding of the physiology, ecology, and phylogeny of microbial communities at contaminated sites (12,38,57). However, the success of many monitored natural attenuation and bioremediation approaches depends largely on our understanding of regulatory mechanisms and cellular responses to different environmental factors affecting the contaminant degradation or metal reduction activity in situ. Microorganisms are often exposed to multiple stress conditions in situ, and the microbial community structure is most likely affected by many different abiotic and biotic variables in a nonlinear fashion (58).

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