Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.
Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.
J Ind Microbiol Biotechnol. 2020 Dec;47(12):1155-1160. doi: 10.1007/s10295-020-02316-1. Epub 2020 Sep 27.
Genetically encoded biosensors are powerful tools used to screen metabolite-producing microbial strains. Traditionally, biosensor-based screening approaches also use fluorescence-activated cell sorting (FACS). However, these approaches are limited by the measurement of intracellular fluorescence signals in single cells, rather than the signals associated with populations comprising multiple cells. This characteristic reduces the accuracy of screening because of the variability in signal levels among individual cells. To overcome this limitation, we introduced an approach that combined biosensors with droplet microfluidics (i.e., fluorescence-activated droplet sorting, FADS) to detect labeled cells at a multi-copy level and in an independent droplet microenvironment. We used our previously reported genetically encoded biosensor, 3-dehydroshikimic acid (3-DHS), as a model with which to establish the biosensor-based FADS screening method. We then characterized and compared the effects of the sorting method on the biosensor-based screening system by subjecting the same mutant library to FACS and FADS. Notably, our developed biosensor-enabled, droplet microfluidics-based FADS screening system yielded an improved positive mutant enrichment rate and increased productivity by the best mutant, compared with the single-cell FACS system. In conclusion, the combination of a biosensor and droplet microfluidics yielded a more efficient screening method that could be applied to the biosensor-based high-throughput screening of other metabolites.
基因编码生物传感器是用于筛选代谢产物产生微生物菌株的强大工具。传统上,基于生物传感器的筛选方法也使用荧光激活细胞分选(FACS)。然而,这些方法受到单个细胞内荧光信号测量的限制,而不是与包含多个细胞的群体相关的信号。由于单个细胞之间信号水平的可变性,这种特性降低了筛选的准确性。为了克服这一限制,我们引入了一种将生物传感器与液滴微流控(即荧光激活液滴分选,FADS)相结合的方法,以在多拷贝水平和独立的液滴微环境中检测标记细胞。我们使用先前报道的基因编码生物传感器 3-去氢莽草酸(3-DHS)作为模型,建立基于生物传感器的 FADS 筛选方法。然后,我们通过将相同的突变文库进行 FACS 和 FADS 处理,对分选方法对基于生物传感器的筛选系统的影响进行了表征和比较。值得注意的是,与单细胞 FACS 系统相比,我们开发的基于生物传感器的液滴微流控 FADS 筛选系统提高了阳性突变体的富集率和最佳突变体的生产力。总之,生物传感器与液滴微流控的结合产生了一种更有效的筛选方法,可应用于其他代谢物的基于生物传感器的高通量筛选。