การพัฒนาสมรรถนะของเซลล์เชื้อเพลิงจุลินทรีย์ด้วยแบบจำลองสหสัมพันธ์ของเมแทบอลิซึมสำหรับน้ำเสียจากโรงงานสับปะรดที่มีคุณสมบัติไม่แน่นอน

The growing world population not only increases wastes and uses up of natural resources through daily consumption, but also through the demand on higher industrial production for food and commodity. Wastewater is a common undesired remaining generated at almost all processes, which is required treatment before discharging to environment. As to minimize cost and extra energy for wastewater treatment, technology has been developed to synergize the benefit of waste utilization and energy generation such as microbial fuel cell (MFC). MFC is a device that uses microbes to turn organic materials in wastewater into electricity. MFC is helpful for industries that deal with a variety of wastes in their effluents and hence require a strong waste management system. While MFC is conceptually absolute method for wastewater treatment, it is still challenging to sustainably maintain its best performance under the variable microbial activity from dynamic condition of the industry. Previous studies by CASB and ECoWaste laboratories in this promising sustainable technology, MFC has shown a good potency on treating sulfide-rich organic wastewater and generating electricity from the real industrial wastewater, canned-pineapple industry. However, the performance of the MFC technology is dependent on the contained microorganisms, which can differ particularly in variable environmental conditions. It can also be influenced by seasonal production and operating conditions in the factories. This caused inconsistency of the MFC performance together with low-achieved electricity. Based on this reason, it could be one of the main factors limiting the application of MFC in real industrial wastewater treatment.

In this work, we will further investigate microbial community interactions in the MFC using multi-species genome-scaled metabolic model leading to explore how the microbial composition was assembled under dynamic of wastewater characteristics. We hypothesize that exchanges of metabolites between cells in the microbial community, a metabolic cross feeding, may be one of underlying mechanisms resulting in the adaptation of microbial composition as we already explored in the previous study using metagenomic approach. As microorganisms live together as a community, studies of microbial interactions including metabolic cross feeding have been reported as an importance on the community structure. Here, we will employ an in silico analysis, multi-species metabolic model to investigate the metabolic cross feeding of microbial community in MFC treating canned-pine apple wastewater under the low-organic loading wastewater (M2L) condition. An understanding of this research work will fundamentally reveal microbial relationships that determine the microbial composition in microbial electrochemical system (MES). Furthermore, analysis of model will also allow predicting strategies for the MFC performance sustainability and improvement under dynamic wastewater properties. Additionally, the model itself can serve as a platform to simulate an in silico experiment which could be useful for future studies or new wastewater properties.