Methanogenic bioreactor communities were used as model ecosystems to evaluate the relationship between functional stability and community structure. Replicated methanogenic bioreactor communities with two different community structures were established. The effect of a substrate loading shock on population dynamics in each microbial community was examined by using morphological analysis, small-subunit (SSU) rRNA oligonucleotide probes, amplified ribosomal DNA (rDNA) restriction analysis (ARDRA), and partial sequencing of SSU rDNA clones. One set of replicated communities, designated the high-spirochete (HS) set, was characterized by good replicability, a high proportion of spiral and short thin rod morphotypes, a dominance of spirochete-related SSU rDNA genes, and a high percentage of Methanosarcina-related SSU rRNA. The second set of communities, designated the low-spirochete (LS) set, was characterized by incomplete replicability, higher morphotype diversity dominated by cocci, a predominance of Streptococcus-related and deeply branching Spirochaetales-related SSU rDNA genes, and a high percentage of Methanosaeta-related SSU rRNA. In the HS communities, glucose perturbation caused a dramatic shift in the relative abundance of fermentative bacteria, with temporary displacement of spirochete-related ribotypes by Eubacterium-related ribotypes, followed by a return to the preperturbation community structure. The LS communities were less perturbed, with Streptococcus-related organisms remaining prevalent after the glucose shock, although changes in the relative abundance of minor members were detected by morphotype analysis. A companion paper demonstrates that the more stable LS communities were less functionally stable than the HS communities

A B S T R A C TAnow possible. An interactive edit feature was added to address the main sources of error in automatic shape classification, enabling the operator to inspect the assigned morphotype of each bacterium based on visual recognition of its distinctive pseudocolor, reassign it to another morphotype class if necessary, and add up to five other morphotypes to the classification scheme. The shape classifier reports on the number and types of different morphotypes present and the abundance among each of them, thus providing the data needed to compute the morphological diversity within the microbial community. An example of how CMEIAS can augment the analysis of microbial community structure is illustrated by studies of morphological diversity as an indicator of dynamic ecological succession following a nutrient shift-up perturbation in two continuously fed, anaerobic bioreactors with morphologically distinct start communities. Various steps to minimize the limitations of computer-assisted microscopy to classify bacterial morphotypes using CMEIAS are described. In summary, CMEIAS is an accurate, robust, flexible semiautomatic computing tool that can significantly enhance the ability to quantitate bacterial morphotype diversity and should serve as a useful adjunct to the analysis of microbial community structure. This first version of CMEIAS will be released as free, downloadable plug-ins so it can provide wide application in studies of microbial ecology.

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