Mixed-culture biotechnologies producing storage compounds as biofuels and biomaterials: engineering waste treatment communities

提高废水处理系统的可持续性部分是通过回收增值产品和能源，如生物塑料(例如，聚羟基烷酸酯，PHA)和生物柴油(从油脂中提取)。活性污泥处理系统中的微生物群落由于其环境条件的快速变化而自然产生存储化合物。由于碳储存化合物包括PHA、甘油三酯和糖原，废水处理系统是生产工业相关生物材料的潜在动力。就PHA而言，目前的纯培养生产成本是化学合成塑料成本的4-9倍。显然，从不需要底物和灭菌的废液中生产有可能极大地降低这一成本。 缺乏对导致特定储存化合物积累的微生物选择的基本理解，无法维持对这些过程的合理开发方法。当葡萄糖或醋酸盐作为单一碳源投加到混合活性污泥培养物中时，为什么会积累糖原或PHA？我们如何选择有能力积累不同种类PHA的生物体(短链与长链)。提出了一种解决这些问题的(Meta)基因组学方法，首先使用我们构建的约氏红球菌RHA1基因组规模的代谢模型，并确定与活性污泥情况下的生长最相关的目标函数。其次，这些发现将通过向一些基因组规模的异养生物模型提出类似的问题来扩展，以预测活性污泥中微生物竞争的结果。最后，将在全规模活性污泥系统中确定不同存储容量的种群中的基因和蛋白质表达谱，以将特定生物的生态功能与其存储化合物的积累联系起来。这些数据将为优化生产特定储存化合物的活性污泥处理的合理设计提供指导。

Improving the sustainability of wastewater treatment systems passes in part by the recovery of value added products and energy such as bioplastics (e.g., polyhydroxyalkanoates, PHA) and biodiesel (from lipids). Microbial communities in activated sludge treatment systems naturally produce storage compounds because of the rapidly changing conditions of their environment. Since carbon storage compounds include PHA, triacyglycerol lipids, and glycogen, wastewater treatment systems are potential powerhouses for the production of industrially relevant biomaterials. In the case of PHA, the current pure culture production costs are 4-9 times higher than the cost of chemically synthesized plastics. It is clear that production from a waste stream where substrate and sterilization would not be necessary has the potential to reduce tremendously this cost. A fundamental understanding of microbial selection leading to the accumulation of given storage compounds is missing to sustain a rational development approach to these processes. Why glycogen or PHA are accumulated when glucose or acetate are fed to the mixed activated sludge culture as single carbon sources? How can we select for organisms with capacities to accumulate different kinds of PHA (short-chains vs long-chains). A (meta)genomics approach to these problems is proposed by first using the genome-scale metabolic model of Rhodococcus jostii RHA1 that we constructed and determining the objective functions that are most relevant for growth in activated sludge situations. Second, these finding will be expanded by asking similar questions to a selection of genome-scale models of heterotrophs to predict the outcome of microbial competitions in activated sludge. Finally, gene and protein expression profiles will be determined in populations with different storage capacities in full-scale activated sludge systems to link the ecological function of specific organism to their accumulation of storage compounds. These data will provide directions for the rational design of activated sludge treatments optimized for the production of specific storage compounds.