Linking gene expression to performance in a fungal vapor-phase bioreactor treating ethylbenzene

Large quantities of volatile organic compounds (VOCs) are emitted from industrial sources into the atmosphere every year. Fungal biofiltration has been demonstrated to be an attractive treatment option for VOCs. In this technology, contaminated air is passed through a biologically active packed bed where the microorganisms degrade the pollutants to benign products. Most biofilter research conducted to date has relied solely on macroscale monitoring such as degradation profiles and nitrogen availability. While these macroscale parameters are important for system performance, they neglect molecular level biodegradation mechanisms in the biofilm. In this research, quantitative real-time reverse transcription polymerase chain reaction (qRT PCR) was used to quantify gene expression variations in the biofilm. The objective of this research was to assess the utility of the qRT-PCR tool for linking microscale gene expression to macroscale bioreactor performance and optimization. The model system used was a biofilter inoculated with the fungus Exophiala lecanii-corni treating ethylbenzene. A comparative threshold method was employed to quantify the relative gene expression of the target gene to a housekeeping gene (18S rRNA). A portion of a key gene involved in ethylbenzene metabolism (ElHDO – homogentisate dioxygenase) was isolated and its gene expression monitored as a function of substrate feed, nutrient concentration and transient loading conditions. In batch experiments, qRT-PCR effectively described changes in relative gene target expression numbers (TN) as a function of substrate mixtures and nutrient concentrations. In the biofilter, TN was found to be a leading indicator of bioreactor failure when a repressor compound was introduced into the column feed. During the transient feed experiment, ElHDO expression slowly shutdown over a 24-hour time period when the ethylbenzene feed was discontinued, but rapidly recovered upon its re-introduction to the system. Overall, qRT-PCR provides valuable insights into the microscale phenomena occurring in the biofilm. However, this method may not be well suited to describe the effect of operational modifications which cause only small gene expression changes due to its low sensitivity under such conditions.