Inoculum composition determines microbial community and function in an anaerobic sequential batch reactor.

The sustainable recovery of resources from wastewater streams can provide many social and environmental benefits. A common strategy to recover valuable resources from wastewater is to harness the products of fermentation by complex microbial communities. In these fermentation bioreactors high microbial community diversity within the inoculum source is commonly assumed as sufficient for the selection of a functional microbial community. However, variability of the product profile obtained from these bioreactors is a persistent challenge in this field. In an attempt to address this variability, the impact of inoculum on the microbial community structure and function within the bioreactor was evaluated using controlled laboratory experiments. In the course of this work, sequential batch reactors were inoculated with three complex microbial inocula and the chemical and microbial compositions were monitored by HPLC and 16S rRNA amplicon analysis, respectively. Microbial community dynamics and chemical profiles were found to be distinct to initial inoculate and highly reproducible. Additionally we found that the generation of a complex volatile fatty acid profile was not specific to the diversity of the initial microbial inoculum. Our results suggest that the composition of the original inoculum predictably contributes to bioreactor community structure and function.

Influence of pH Regulation Mode in Glucose Fermentation on Product Selection and Process Stability.

Mixed culture anaerobic fermentation generates a wide range of products from simple sugars, and is potentially an effective process for producing renewable commodity chemicals. However it is difficult to predict product spectrum, and to control the process. One of the key control handles is pH, but the response is commonly dependent on culture history. In this work, we assess the impact of pH regulation mode on the product spectrum. Two regulation modes were applied: in the first, pH was adjusted from 4.5 to 8.5 in progressive steps of 0.5 and in the second, covered the same pH range, but the pH was reset to 5.5 before each change. Acetate, butyrate, and ethanol were produced throughout all pH ranges, but there was a shift from butyrate at pH < 6.5 to ethanol at pH > 6.5, as well as a strong and consistent shift from hydrogen to formate as pH increased. Microbial analysis indicated that progressive pH resulted in dominance by Klebsiella, while reset pH resulted in a bias towards Clostridium spp., particularly at low pH, with higher variance in community between different pH levels. Reset pH was more responsive to changes in pH, and analysis of Gibbs free energy indicated that the reset pH experiments operated closer to thermodynamic equilibrium, particularly with respect to the formate/hydrogen balance. This may indicate that periodically resetting pH conforms better to thermodynamic expectations.

A Novel Analysis Method for Paired-Sample Microbial Ecology Experiments.

Many microbial ecology experiments use sequencing data to measure a community's response to an experimental treatment. In a common experimental design, two units, one control and one experimental, are sampled before and after the treatment is applied to the experimental unit. The four resulting samples contain information about the dynamics of organisms that respond to the treatment, but there are no analytical methods designed to extract exactly this type of information from this configuration of samples. Here we present an analytical method specifically designed to visualize and generate hypotheses about microbial community dynamics in experiments that have paired samples and few or no replicates. The method is based on the Poisson lognormal distribution, long studied in macroecology, which we found accurately models the abundance distribution of taxa counts from 16S rRNA surveys. To demonstrate the method's validity and potential, we analyzed an experiment that measured the effect of crude oil on ocean microbial communities in microcosm. Our method identified known oil degraders as well as two clades, Maricurvus and Rhodobacteraceae, that responded to amendment with oil but do not include known oil degraders. Our approach is sensitive to organisms that increased in abundance only in the experimental unit but less sensitive to organisms that increased in both control and experimental units, thus mitigating the role of "bottle effects".