Enzymes play an increasingly important role as biocatalysts in many industrial processes, such as the food, pharmaceutical, and detergent industries [1–3]. Enzymes exhibit several advantages compared to conventional chemical catalysts owing to their high substrate specificity, high catalytic efficiency, biodegradability, no toxicity, and relatively mild operational conditions with respect to pH and temperature. These enzyme traits make them is receiving more attention both from industry and academia.
Amylases are one of the most important industrial starch-hydrolyzing enzymes [4]. α-Amylase (EC 3.2.1.1) capable of hydrolyzing α-1,4-glycosidic bonds in starch and related polymers into glucose, maltose, and maltotriose units. Therefore, α-amylases have a wide range of industrial applications in food processing, beverage, pharmaceutical, biofuels, detergent, and textile industries [5–6]. Various α-amylases are widely distributed in animals, plants, and microorganisms. The microbial source of amylase is more preferred for industrial production due to the economical bulk production capacity, eco-friendly nature, easier handling, and ease of product modification [7–9]. Among the microorganisms, the bacteria B. licheniformis has been proven to be a potent cell factory for the industrial production of α-amylase and other proteins, because of its free of endotoxins, its superior capacity of extracellular protein secretion, its higher thermal stability, and the economic feasibility of large-scale fermentation [10].
To meet the growing demands in the industry, more research is needed to improve the performance of B. licheniformis strain, thus increase the yields of target proteins and decrease of production costs. Recent developments in genome sequences and recombinant DNA technology may provide new ways of improving enzyme function and production [11–15]. However, the low transformation efficiency and lack of effective genome editing tools have limited its widespread use [16]. Moreover, the use of recombinant DNA technology in the food industry is tightly regulated and consumer’s responses toward genetically modified food ingredients are largely negative [17].
Directed evolution employing iterative rounds of random mutagenesis and library screening can be used for strain improvement purposes [18–19]. Random mutagenesis is one of the most commonly employed methods for diversity generation. This method does not require detailed knowledge about the strain and enzyme. Recently, a novel mutation machine named ARTP has been extensively used for microbial mutation [20–23]. Compared with traditional mutagenesis strategies by using nitrosoguanidine and ultraviolet treatment, ARTP mutagenesis is a more environmentally friendly, operating security and higher diversity mutagenesis method [20, 24].
Besides the mutation efficiency, the success of directed evolution experiments hinges on an efficient HTS strategy to the isolation of the desired mutants from a large mutant library [19, 25–26]. Conventional screening methods, such as halo and microtiter plate assays, are costly and low-throughput. Fluorescence-activated cell sorting (FACS) is an ultrahigh throughput method for single-cell sorting and analysis. However, FACS requires fluorescent marker(s) which must remain either inside or surface of the cells to be sorted [27–28]. In vitro compartmentalization (IVC) by compartmentalized cells and their extracellular products in water-in-oil-in-water double emulsion enables screening of 10,000 events/s using FACS [29]. However, the IVC-FACS assay is limited by the complex double emulsion generation and modification [30]. In contrast, droplet-based microfluidic technology enables the generation and manipulation of highly monodisperse water-in-oil droplets at ultrahigh frequencies [31–39]. Single cell and its extracellular product were encapsulated in picoliter-sized droplets using the microfluidic droplet generation device at rate of thousands per second. Each droplet acts as an individual microreactor to link the phenotype of the cell to its genotype. Following droplet collection and off-chip incubation, the droplets were reinjected into the sorting device and sorted based on their fluorescence signals at a rate of hundreds per second. In the past decade, fluorescence-activated droplet sorting (FADS) has been applied to the screening of many microorganisms that produce various enzymes and metabolites [40]. Although the commercial microfluidic devices and reagents (oil, surfactant, etc.) are available from several companies, such as Dolomite, BioRad, and RainDance Technologies, the lack of commercial droplet-based microfluidic platforms has limited its widespread use in common laboratories [41]. In contrast to the rapid progress of the flow cytometer, only limited research has been done on the development of microfluidic instruments for water-in-oil droplet sorting [36].
In this study, we developed an integrated microfluidic droplet sorting platform based on FADS. The platform allowed droplet generation, long-term droplet incubation, and sorting of droplets with a throughput of up to 1×106 droplets per hour. A mixture of Bacillus strains with high and low fluorescence was successfully enriched to verify the feasibility of our platform. We further applied the platform to screen a mutant library of α-amylase-producing B. licheniformis generated by ARTP, and The mutants with higher α-amylase production capacity were successfully identified. This microfluidic droplet sorting platform should be extremely useful for accelerating the process of strain development.