Conference Agenda

Microbial encapsulation is an emerging technology for various environmental applications ranging from removal of nutrients to remediation of contaminants. Encapsulation technology has advanced in the last decades with recent findings in new encapsulation materials, pure and enrichment culture studies, and improved mathematical models and molecular tools. Nevertheless, complex interactions between encapsulated microorganisms and between microorganisms and their surrounding matrices remain unclear. This hinders the predictive application of microbial encapsulation within and beyond the field of environmental engineering. Our recent studies developed a one-dimensional mathematical model that simulates the encapsulated growth and verified with a defined system of encapsulated Nitrosomonas europaea. The model successfully predicted the concentrations gradients of chemical species as well as the spatial distribution of cell growth. In addition, we developed a new method to track microbial colony formations during encapsulated growth. With the combination of microtome and fluorescence in situ hybridization techniques, differential growth of multiple groups of microorganisms were measured with temporal and spatial resolutions. This presentation will summarize major findings from the development of novel mathematical and microscopic tools, which helped advance the understanding of microorganism–encapsulant interactions and thus facilitate future predictive applications of microbial encapsulation in resource recovery, contaminant removal, and environmental remediation.

The World Health Organization lists the ever-increasing rise of antibiotic resistant pathogens as one of the greatest worldwide threats to human health. Environmental bacteria, such as wastewater microbes, represent reservoirs of antibiotic resistance genes (ARGs) that pathogens can acquire through horizontal gene transfer. Although the presence of ARGs in wastewater systems is well documented, there is a dearth of information on the diversity of which bacteria participate in ARG transfer. As the persistent threat of antibiotic resistance pathogens worsens, there is a need to understand the bacterial networks that facilitate conjugative transfer of ARG housing plasmids. To address this, we developed a novel RNA-based method to track conjugation in situ, called RNA addressable memory (RAM).

We built a plasmid-encoded catalytic RNA system that records which microbial community members receive an engineered plasmid via conjugation. A trans-splicing reaction cleaves the 16S rRNA and attaches a synthetic barcode onto the freshly made edge of the rRNA, forming a chimeric RNA that contains species-specific information (16S) and evidence of horizontal gene transfer (barcode). The identity of said transconjugants can easily be read-out using high-throughput amplicon sequencing. In demonstration, we showed conjugation from a donor E. coli species into 42% of a wastewater microbial community. Furthermore, we compute conjugation efficiencies for individual taxa as the ratio of barcoded-RNA to total RNA abundance, and show differences among taxa both within and across taxonomic orders. We show RAM can be applied to understand the propagation of different ARG-carrying plasmids and their hosts within real environments.

Biofilms are microbial communities that are distinct from planktonic cells and more resilient to external stressors. The role of biofilms in water and wastewater treatment may be advantageous or detrimental depending on the treatment processes employed. Controlling formation of detrimental biofilm is important when biofouling hinders the successful operation of treatment systems as well as in distribution systems, where the biofouling of tanks or pipelines may expose the treated water to pathogenic microorganisms. However biofilms may also be beneficial when they are used for treatment applications that benefit from the retention of high cell densities on surfaces or carrier media. This work investigated the influence of the water chemistry of growth media, specifically carbon/nitrogen (C/N) molar ratios, on the characteristics and development of biofilms of the model microorganism Pseudomonas aeruginosa. The ratio C/N=9 had a unique effect on biofilm composition as well as quorum sensing pathways, leading to higher concentrations of proteins and carbohydrates in the biofilm and significant upregulation of genes involved in biofilm formation, such as lasI. Principal component analysis revealed that there was a differential behavior of most measured outputs at C/N=9, and pointed to correlations between biofilm formation characteristics and steady-state distribution of cellular and extracellular components. Dual-species biofilm development by P. aeruginosa and N. winogradskyi was also influenced by C/N, with changes in the relative abundance related to C/N=9. Overall, results suggested that alternating operating parameters related to C/N can be relevant for promoting or controlling biofilm formation depending on the desired treatment configuration.

Treated wastewater contains residual bioactivity, which is a growing concern for both environmental and human health. Bioactive chemicals are removed through advanced treatment technologies, which are cost prohibitive for many municipalities. One possible solution to increase treatment is to optimize the microbial community in biological wastewater treatment processes. Some studies have reported on the removal of targeted compounds during biological treatment, but there is limited knowledge on the microbial communities driving chemical change. Herein, we examined the change in the non-target chemical composition as a function of microbial community composition and biological treatment type (i.e., activated sludge, facultative lagoons, and biological nutrient removal). Samples were collected before and after conventional biological treatment processes from 12 wastewater treatment utilities in Oregon. The non-target chemical composition was quantified using liquid chromatography high-resolution time-of-flight mass spectrometry. Microbial community composition was determined using 16S rRNA Illumina sequencing. The chemical composition of biologically treated wastewater was compared across each treatment type, and through treatment train using dissimilarity analysis and multivariate analysis methods. Using network analysis, the associations between chemical transformation and microbial communities were revealed. Results demonstrated changes in the holistic chemical composition after biological treatment with a reduction in the number of chemical features and abundances. The associations identified between microbial community and chemicals identify potential microorganisms responsible for major chemical transformation. The results from this study will help engineers select microbial communities to seed into wastewater treatment facilities to help increase treatment efficiencies and to reduce their impact on receiving ecosystems.

Anaerobic organic carbon competition in enhanced biological phosphorus removal water resource recovery facilities (WRRFs) is believed to be a primary cause of process breakdowns leading to phosphorus (P) discharges that contribute to eutrophication of natural waters. Saturation kinetics have typically been applied to organic carbon uptake competition, but WRRFs typically have saturating concentrations of most nutrients suggesting that an energy-based model may be more appropriate. Our objective was to demonstrate a thermodynamic energy balance model for uptake and excretion of nutrients during anaerobic incubation. An enriched culture of Tetrasphaera polyphosphate accumulating organisms (PAOs) grown in a laboratory sequencing batch reactor was assayed between pH 4.7 and 8.7 using glycine or aspartate as the sole carbon source. Multiple linear regression analyses evaluated the significance of changes (p < 0.05) in extracellular electrogenic ions likely contributing to transmembrane energy currents in PAOs. The glycine model (R² = 0.90) was significant with explanatory variables K⁺, Na⁺, NH₄⁺, and H⁺ change suggesting cation driven secondary transport. The aspartate model (R² = 0.86) was not significant (p = 0.12) but demonstrated similar cation dependence and an average pH dependence suggesting cation driven secondary transport with changing energy requirements due to pH. These findings support the hypothesis that organic carbon uptake in Tetrasphaera PAOs may be limited by transmembrane ion current energy and not kinetics as suggested for other PAOs. Transport inhibitors, more complete ion profiles, and a comparison to kinetic models could be used to further develop and refine the model.