Abstract

Protein fitness landscapes (as introduced by Maynard Smith) are a powerful concept for describing sequence-function relationships by illustrating the vast combinatorial sequence space as functional hills and valleys, with an address defined by amino acid sequence combinations. This metaphorical representation is often invoked to explain directed evolution experiments in protein engineering. Yet fitness landscapes are rarely ‘measured’ experimentally: the immense vastness of possible sequence/function spaces makes comprehensive high-quality datasets difficult to obtain. The combination of ultrahigh-throughput screening (with >10e7 assays in a day in microfluidic droplets ), with next generation sequencing (based on UMI -encoding) and the interpretation of such large datasets that characterise genotype-phenotype maps, is providing an opportunity for more systematic exploration of large parameter spaces in protein engineering.

These ideas will guide the search for new enzymes, amongst them enzymes for recycling and bioremediation of plastic waste in the environment. Modern life generates enormous amounts of plastic waste: 359 million tons of plastics are produced annually worldwide, of which 90% is produced from fossil fuels and 79% accumulates in landfill or in the natural environment. Collectively all these plastics create an environmental hazard. As Nature did not encounter plastics for most of its evolutionary history, plastic-degrading enzymes with a metabolic role did not exist. Will we be able to find novel enzymes in the vastness of sequence space for entirely new, non-natural functions?