(346f) Library-Based Identification of Genetic Loci Imparting Tolerance and Flow-Cytometry Based Assays for Developing Complex Tolerant Phenotypes

Renewable energy sources are becoming increasingly more attractive amid rising oil costs and environmental concerns. Biofuels are receiving substantial attention from the scientific community, as they can be derived from renewable biomass, are considered carbon neutral and can reduce polluting emissions. To achieve the goal of economically producing chemicals and biofuels, improvements are required in cellulose degradation, increased product yields, and higher strain tolerance to chemicals (biofuels).

Our lab is interested in developing tools that would allow us to engineer tolerant phenotypes. As part of the process of developing library-based tools and assays for identifying multigene-based programs that impart tolerance to chemicals, we use tolerance to ethanol as a model case. In this study, in order to increase ethanol tolerance of bacteria, a plasmid-based genomic library of 3-6 kb inserts was constructed and cloned into Escherichia coli. The library-bearing cell population was stressed with ethanol, and the plasmids conferring a selective advantage to the bacteria were enriched via transfers to media with higher ethanol content. Sequencing of plasmid inserts repeatedly identified two genes, murA and yrbA, coding for an enzyme involved in cell-wall biosynthesis and a transcriptional regulator, respectively. These genes were subsequently individually cloned and overexpressed in E. coli. The cells were characterized in minimum inhibitory concentration (MIC) assays, where they grew to higher densities compared to the control strain up to an ethanol concentration of 6% (v/v). Furthermore, flow cytometry was used to sort the stressed cells after the MIC assays into viable or non-viable cells. E. coli were stained with Syto9 and the DNA dye Propidium Iodide (PI) to investigate cell integrity and quantitate cell survival. The staining pattern of cells stressed with ethanol changes substantially as the alcohol concentration increases, with cells dying and becoming more permeable to PI at the higher ethanol concentrations tested. Together, the MIC assay and flow cytometry can be used to screen for more tolerant cells, which can then be sorted and sub-cultured. We also show that murA has an important role in ethanol tolerance and we explore the mechanism underlying the impact of the gene on ethanol tolerance.

Key words: genomic library, flow cytometry, gene over-expression, minimum inhibitory concentration, ethanol tolerance