Abstract: We have identified an environmental bacterium in the Candidate Division TM7 with ≥98.5% 16S rDNA gene homology to a group of TM7 bacteria associated with the human oral cavity and skin. The environmental TM7 bacterium (referred to as TM7a-like) was readily detectable in wastewater with molecular techniques over two years of sampling. We present the first images of TM7a-like cells through FISH technique and the first images of any TM7 as viable cells through the STARFISH technique. In situ quantification showed TM7 concentration in wastewater up to five times greater than in human oral sites. We speculate that upon further characterization of the physiology and genetics of the TM7a-like bacterium from environmental sources and confirmation of its genomic identity to human-associated counterparts it will serve as model organisms to better understand its role in human health. The approach proposed circumvents difficulties imposed by sampling humans, provides an alternative strategy to characterizing some diseases of unknown etiology, and renders a much needed understanding of the ecophysiological role hundreds of unique Bacteria and Archaea strains play in mixed microbial communities.
Abstract: Comparative sequence analysis of the 16S rRNA gene is frequently used to characterize the microbial diversity of environmental samples. However, sequence similarities do not always imply functional or evolutionary relatedness due to many factors, including unequal rates of change and convergence. Thus, relying on top BLASTN hits for phylogenetic studies may misrepresent the diversity of these constituents. Furthermore, attempts to circumvent this issue by including a large number of BLASTN hits per sequence in one tree to explore their relatedness presents other problems. For instance, the multiple sequence alignment will be poor and computationally costly if not relying on manual alignment, and it may be difficult to derive meaningful relationships from the resulting tree. Analyzing sequence relationship networks within collective BLASTN results, however, reveal sequences that are closely related despite low rank. We have developed a web application, Phylometrics, that relies on networks of collective BLASTN results (rather than single BLASTN hits) to facilitate the process of building phylogenetic trees in an automated, high-throughput fashion while offering novel tools to find sequences that are of significant phylogenetic interest with minimal human involvement. The application, which can be installed locally in a laboratory or hosted remotely, utilizes a simple wizard-style format to guide the user through the pipeline without necessitating a background in programming. Furthermore, Phylometrics implements an independent job queuing system that enables users to continue to use the system while jobs are run with little or no degradation in performance. Phylometrics provides a novel data mining method to screen supplied DNA sequences and to identify sequences that are of significant phylogenetic interest using powerful analytical tools. Sequences that are identified as being similar to a number of supplied sequences may provide key insights into their functional or evolutionary relatedness. Users require the same basic computer skills as for navigating most internet applications.
Abstract: We have developed a microfluidic device that allows the isolation and genome amplification of individual microbial cells, thereby enabling organism-level genomic analysis of complex microbial ecosystems without the need for culture. This device was used to perform a directed survey of the human subgingival crevice and to isolate bacteria having rod-like morphology. Several isolated microbes had a 16S rRNA sequence that placed them in candidate phylum TM7, which has no cultivated or sequenced members. Genome amplification from individual TM7 cells allowed us to sequence and assemble >1,000 genes, providing insight into the physiology of members of this phylum. This approach enables single-cell genetic analysis of any uncultivated minority member of a microbial community.