(652a) Capillary Electrophoresis Single-Strand Conformation Polymorphism (Ce-Sscp) For Active Community Profiling Of Complex Microbial Communities

Current community profiling techniques, such as T-RFLP, DGGE, and TGGE, fail to distinguish active from inactive microbial species in a mixed community. The purpose of this study was to validate the use of active community profiling (ACP) for characterizing the active microbial populations of constructed laboratory mixed cultures and a field-scale bioreactor treating acid mine drainage (AMD). ACP involves monitoring the composition and activity of a mixed microbial culture via comparative measurements of 16S rRNA and rDNA using capillary electrophoresis single-strand conformational polymorphism (CE-SSCP). The cellular ratio of total RNA to DNA is known to be proportional to growth rate in a variety of organisms. CE-SSCP involves denaturing of double-stranded PCR products that are rapidly cooled to form unique single-stranded conformations based on their nucleic acid sequences. Capillary electrophoresis is then used to separate the conformations based on electrophoretic mobility, resulting in an electropherogram with a series of peaks representing dominant members of the microbial community. Species identification is then determined by comparing the electrophoretic mobilities of individuals from a clone library to the individual peaks of the community profile.

The first stage of the study demonstrated that the rRNA:rDNA ratio obtained from CE-SSCP analysis can differentiate between different growth phases of a model organism, E. coli K12. Additionally, the ability to differentiate between different species was established. For the pure culture studies, E. coli was harvested from a chemostat at four different growth rates (µ. The rRNA:rDNA for each µ value was calculated using three independent methods: (1) CE-SSCP, (2) quantitative DNA marker using traditional slab gel electrophoresis, and (3) spectrophotometrically. For each analytical method, increased growth rate was found to correlate with a larger rRNA:rDNA.

Pure cultures of four species, Desulfovibrio salexigens, Desulfotomaculum ruminis, E. coli K12, and Pseudomonas putida F1, were combined to create simple mixed cultures. The mixed communities were exposed to perturbations known to inhibit the growth of selected species. The perturbations included oxygen content, salt concentration, and the addition of chlorhexidine. For each disturbance to the community, a quantifiable decrease in the rRNA:rDNA of the species targeted for inhibition was detected using CE-SSCP, while the rRNA:rDNA of the non-targeted species remained relatively constant. These studies validated the use of CE-SSCP as an appropriate means of characterizing the active members of a mixed microbial culture.

When applied to a field-scale bioreactor treating AMD, a more complex and diverse microbial community was observed in the rDNA profiles than in the rRNA profiles, indicating that many of the species present in the system are not active. Species representative of the three main groups of microorganisms associated with sulfate-reducing bioreactors (cellulose degraders, fermenters, and sulfate reducers) were more dominant in the rRNA profiles, verifying their active role in the remediation process. In addition to the three main groups, several species with unknown function were also prevalent in the rRNA profiles. These species may be actively involved in AMD remediation, or may be particularly suited to the environment of the bioreactor.

The results of this study validate the use of ACP as a tool to characterizing the active members of mixed microbial cultures. The method gives additional information regarding a community beyond that obtained from standard 16S rDNA community profiling techniques. The differences observed between standard 16S rDNA profiling and the newly developed rRNA-based ACP indicate that conclusions based on DNA measurements alone may not accurately depict the microbial community. By identifying the active species, ACP is an important step forward in fully understanding complex microbial communities.