Department of Energy, Environmental and Chemical Engineering, Washington University, Saint Louis, MO, 63130, USA.
Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, NY, 12180, USA.
Microb Cell Fact. 2019 Feb 8;18(1):35. doi: 10.1186/s12934-019-1083-3.
During microbial applications, metabolic burdens can lead to a significant drop in cell performance. Novel synthetic biology tools or multi-step bioprocessing (e.g., fermentation followed by chemical conversions) are therefore needed to avoid compromised biochemical productivity from over-burdened cells. A possible solution to address metabolic burden is Division of Labor (DoL) via natural and synthetic microbial consortia. In particular, consolidated bioprocesses and metabolic cooperation for detoxification or cross feeding (e.g., vitamin C fermentation) have shown numerous successes in industrial level applications. However, distributing a metabolic pathway among proper hosts remains an engineering conundrum due to several challenges: complex subpopulation dynamics/interactions with a short time-window for stable production, suboptimal cultivation of microbial communities, proliferation of cheaters or low-producers, intermediate metabolite dilution, transport barriers between species, and breaks in metabolite channeling through biosynthesis pathways. To develop stable consortia, optimization of strain inoculations, nutritional divergence and crossing feeding, evolution of mutualistic growth, cell immobilization, and biosensors may potentially be used to control cell populations. Another opportunity is direct integration of non-bioprocesses (e.g., microbial electrosynthesis) to power cell metabolism and improve carbon efficiency. Additionally, metabolic modeling and C-metabolic flux analysis of mixed culture metabolism and cross-feeding offers a computational approach to complement experimental research for improved consortia performance.
在微生物应用中，代谢负担可能导致细胞性能显著下降。因此，需要新型合成生物学工具或多步生物加工（例如，发酵后进行化学转化）来避免因细胞负担过重而降低生化生产力。解决代谢负担的一种可能方法是通过自然和合成微生物群落实现分工（Division of Labor，DoL）。特别是，在工业应用中，整合生物加工和代谢合作用于解毒或交叉喂养（例如，维生素 C 发酵）已经取得了许多成功。然而，由于存在几个挑战，将代谢途径分配给合适的宿主仍然是一个工程难题：复杂的亚群动态/与稳定生产的短时间窗口之间的相互作用、微生物群落的培养效果不佳、作弊者或低产者的增殖、中间代谢物稀释、物种之间的运输障碍以及生物合成途径中代谢物通道的中断。为了开发稳定的群落，可以优化菌株接种、营养分歧和交叉喂养、互利生长的进化、细胞固定化和生物传感器的使用，以控制细胞群体。另一个机会是直接整合非生物过程（例如，微生物电合成）为细胞代谢提供动力并提高碳效率。此外，对混合培养代谢和交叉喂养的代谢建模和 C 代谢通量分析为改进群落性能提供了一种计算方法，补充了实验研究。
