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Collagenases are essential enzymes capable of digesting triple-helical collagen under physiological conditions. These enzymes play a key role in diverse physiological and pathophysiological processes. Collagenases are used for diverse biotechnological applications, and it is thus of major interest to identify new enzyme variants with improved characteristics such as expression yield, stability, or activity. The engineering of new enzyme variants often relies on either rational protein design or directed enzyme evolution. The latter includes screening of a large randomized or semirational genetic library, both of which require an assay that enables the identification of improved variants. Moreover, the assay should be tailored for microplates to allow the screening of hundreds or thousands of clones. Herein, we repurposed the previously reported fluorogenic assay using 3,4-dihydroxyphenylacetic acid for the quantitation of collagen, and applied it in the detection of bacterial collagenase activity in bacterial lysates. This enabled the screening of hundreds of E. coli colonies expressing an error-prone library of collagenase G from C. histolyticum, in 96-well deep-well plates, by measuring activity directly in lysates with collagen. As a proof-of-concept, a single variant exhibiting higher activity than the starting-point enzyme was expressed, purified, and characterized biochemically and computationally. This showed the feasibility of this method to support medium-high throughput screening based on direct evaluation of collagenase activity.

Successful directed evolution examples span a broad range of improved enzyme properties. Nevertheless, the most challenging step for each single directed evolution approach is an efficient identification of improved variants from a large genetic library. Thus, the development and choice of a proper high-throughput screening is a central key for the optimization of enzymes. The detection of low enzymatic activities is especially complicated when they lead to products that are present in the metabolism of the utilized genetic host. Coupled enzymatic assays based on colorimetric products have enabled the optimization of many of such enzymes, but are susceptible to problems when applied on cell extract samples. The purpose of this study was the development of a high-throughput screening for D-glycerate dehydratase activity in cell lysates. With the aid of an automated liquid handling system, we developed a high-throughput assay that relied on a pre-treatment step of cell extract prior to performing the enzymatic and assay reactions. We could successfully apply our method, which should also be transferable to other cell extract-based peroxidase assays, to identify an improved enzyme for the dehydration of D-glycerate.