(566d) Phylogenetic and Functional Profiling of the Microbiome Associated with a Phytoremediation System Targeting Air Quality in the Built Environment

We are spending majority of our time indoors, where we can be exposed to harmful chemicals and bacteria. The active modular phytoremediation system (AMPS) is a biowall where plants are grown aeroponically in a granular bulk media. Biowalls have strong potential for improving indoor air quality through bioremediation by both plants and their-associated microbes. Understanding whether the presence of soil affects the AMPS microbiome was targeted because the presence of soil in biowalls has been correlated to the presence of mold spores and increases in plant module replacement. We wanted to know if microbial community composition and function are maintained if soil is removed from the AMPS modules and plants are supported only by the granular bulk media. Microbiome samples were isolated from bulk media and roots from three modules without soil and bulk media, soil and roots from three modules containing both soil and bulk media. We determined the phylogenetic profile by sequencing the 16S rRNA gene. All microbiome samples were observed to contain diverse communities with many rare species, and were all dominated by members of the phyla Proteobacteria and Planctomycetes. These phyla are typical of plant-associated microbiomes. Small differences are observed in the number and diversity of species in roots from modules with and without soil. Samples were clustered based on abundant and rare community members by calculating pairwise Bray-Curtis and Canberra distances respectively. In both cases, root and soil samples from modules containing soil clustered separately from all other samples. Thus, the presence of soil does contribute to a minor increase in diversity and drives differences in community composition. We are exploring if genes capable of promoting plant growth or degrading pollutants such as volatile organics are present in the communities. These functions may be leveraged to enhance phytoremediation using AMPS-type systems. We are using a novel computational tool to query the presence of these target genes using the 16S rRNA data and available genomic and metabolic databases to make functional predictions. Predictions can be verified using PCR-based techniques. This study demonstrates that the microbiomes associated with plants grown with and without soil in the biowall are diverse. The results set the stage for forward engineering efforts to enhance the remediation capabilities of these microbiomes and improve indoor biodiversity.