Abstract
Natural enzymes have evolved over millions of years to allow for their effective operation within specific environments. However, it is significant to note that despite their wide structural and chemical diversity, relatively few natural enzymes have been successfully applied to industrial processes. To address this limitation, directed evolution (DE) (a method that mimics the process of natural selection to evolve proteins toward a user‐defined goal) coupled with droplet‐based microfluidics allows the detailed analysis of millions of enzyme variants on ultra‐short timescales, and thus the design of novel enzymes with bespoke properties. In this review, we aim at presenting the development of DE over the last years and highlighting the most important advancements in droplet‐based microfluidics, made in this context towards the high‐throughput demands of enzyme optimization. Specifically, an overview of the range of microfluidic unit operations available for the construction of DE platforms is provided, focusing on their suitability and benefits for cell‐based assays, as in the case of directed evolution experimentations.
Highlights
Living organisms often take millions of years to evolve enzymes capable of metabolizing naturally occurring substances
To address this limitation, directed evolution (DE) coupled with droplet-based microfluidics allows the detailed analysis of millions of enzyme variants on ultra-short timescales, and the design of novel enzymes with bespoke properties
Optimized by evolution over time, they can initiate, accelerate, and control a diversity of reactions within living systems, whilst ensuring high substrate specificity as well as extraordinary selectivity. Despite their wide structural and chemical diversity, relatively few natural enzymes have been successfully applied to the processing of non-living systems in industrial settings [1]
Summary
Living organisms often take millions of years to evolve enzymes capable of metabolizing naturally occurring substances. Optimized by evolution over time, they can initiate, accelerate, and control a diversity of reactions within living systems, whilst ensuring high substrate specificity as well as extraordinary selectivity Despite their wide structural and chemical diversity, relatively few natural enzymes have been successfully applied to the processing of non-living systems in industrial settings [1]. A genetically diverse “population” (or gene library) is created and translated into a corresponding library of gene products (encoded enzymes) This is followed by a selection process aimed at isolating variants with the most-desired characteristics (the “fittest”) [7]. Given that enzymes typically contain between 180 and 600 amino acids, protein engineers are motivated to devise methods that can create libraries of accessible (and manageable) size, whilst at the same time, maximizing the likelihood of identifying improved variants within a library [5, 12]. The sorting strategy involves assessing enzymatic efficiency through measurement of the time integrated fluorescence signal originating from individual droplets
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