This past Wednesday (March 21st) I had the privilege of presenting Chris and I’s research into how reactor influent composition (within HDBRs (but the concept is extensible to other reactor systems)) affects microbial community composition which, in turn, drives nutrient removal kinetics. I’m pleased with the positive feedback we have received and I’m very excited to say that we have two manuscripts in preparation from this dataset…

I’ll leave you guys with that teaser. :-P

Until we have the publications in the bag, I’ll leave you with the presentation document from the conference HERE.

If anyone has questions or are interested in discussing our results, please reach out to either Chris or I.

Our title and abstract can be found below….

Title:
Examining nutrient uptake and transformation within photosynthetic microbial communities using a high density bioreactor

Jacob R. Price and Christopher M. Sales

Abstract:
Anthropogenic nutrient sources such as wastewater treatment and untreated agricultural animal waste contribute to a large number of environmental and ecological disturbances, such as eutrophication. Applying engineered resource recovery systems, using photosynthetic microbial communities, provides a way to intercept high nutrient fluxes before their deleterious effects are realized, while also creating valuable byproducts (i.e., clean water and nutrient rich biomass). In this presentation we will describe the use of a unique reactor architecture, called a high density bioreactor (HDBR), which is capable of continuous production of bacterial-algal biomass grown on wastewater, to study the uptake and transformation of organic carbon, nitrogen, and phosphorous within an algae- and cyanobacteria-dominated photosynthetic microbial community, as well as how changes in influent composition affects microbial community composition and its impact on reactor kinetics. At the lab scale, the HDBR has been demonstrated to remove a significant proportion of nutrients while simultaneously cultivating high density biomass for use as feedstock for the potential production of biofuels or fertilizer. Reactors were sampled daily for kinetic performance and microbial community samples were subjected to amplicon sequencing, targeting 16S rDNA, for each experimental condition. We will present preliminary results demonstrating how analyzing this data using numerical ecology techniques including hierarchical clustering and ordination can be applied to explore both kinetic and molecular ecology datasets simultaneously and to garner useful information to better model, engineer, and operate these systems.