24 research outputs found

    Enzyme evolution and engineering using insertions and deletions

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    In Nature, proteins evolve and acquire new functions by accumulating mutations. Substitutions and InDels (Insertions and Deletions), as well as circular permutations and rearrangement of protein domains, account for the majority of evolutionary changes. While the effects of substitutions have been extensively studied and documented, understanding the structural and functional effects of InDels still remains a challenge. InDels are assumed to be highly deleterious mutations because they are more likely to disrupt the structural integrity of proteins than are substitutions. On the other hand, they may induce significant structural changes that substitutions alone cannot cause and thus are believed to be key players in many natural evolutionary processes, such as the modification of active site loops to generate new enzyme functions1 or the emergence of new protein structures2. We aimed at performing directed evolution by randomly incorporating InDels to investigate how they would be tolerated and whether they could be selected for functional improvements. Starting from a previously reported methodology3, we developed a library construction approach to randomly incorporate InDels within a DNA sequence of interest and applied it to generate InDel variant libraries of a promiscuous enzyme (phosphotriesterase4). We screened the resulting libraries (i) to compare the impact of InDels to that of substitutions on the enzyme, (ii) to identify adaptive InDels improving a new (or promiscuous) activity and (iii) to investigate the interaction between InDels and substitutions in an adaptive process. Our results show that, while being generally more deleterious than substitutions, InDels can also lead to functional improvements and may allow access to alternative evolutionary trajectories. References 1 Park et al. (2006). Science 311, 535–538. 2 Grishin (2001). J Struct Biol 134:167–185. 3 Jones et al. (2014). Methods in Mol Biol 1179:159-72. 4 Tokuriki et al. (2012). Nature Comm 3:1257

    Absorbance-activated-droplet sorting for directed enzyme evolution

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    The successful creation of custom-made enzymes by directed evolution relies in no small part on screening as many variants as possible. Massive scale-down of assay volumes by compartmentalization of library members in water-in-oil emulsion droplets has recently led to the development of ultrahigh-throughput screening platforms that use small volumes (typically picoliters) and allow sorting of more than 106 variants per hour 1,2. The key technical module to make this possible is a microfluidic droplet sorter that has so far relied exclusively on fluorescent readouts. To extend the range of assays amenable to this approach, we developed a highly efficient microfluidic absorbance-activated droplet sorter (AADS)3. Using this module, microdroplets can be sorted based on absorbance readout at rates of up to more than a million droplets in 3 hours. To validate this device, we implemented a miniaturized coupled assay for an NAD+- dependent amino acid dehydrogenase. The detection limit (10 μM in a coupled assay producing a formazan dye) enables accurate kinetic readouts and sorting experiments showed that the AADS successfully enriched active variants up to 2,800-fold from an overwhelming majority of inactive ones at ≈ 100 Hz. Furthermore, improved variants showing increased solubility (up to 60%) and thermostability (up to 12 °C) were identified after two rounds of directed evolution, thereby demonstrating the usefulness of this sorting module for enzyme engineering. This AADS makes the most widely used optical detection format amenable to screens of unprecedented size, paving the way for the implementation of chromogenic assays in droplet microfluidics workflows. We are currently expanding its range of applications towards the monitoring of cell growth for the development of survival assays and the detection of weak enzymatic reactions. 1. Colin P-Y, Kintses B, Gielen F, et al. Ultrahigh-throughput discovery of promiscuous enzymes by picodroplet functional metagenomics. Nat Commun. 2015; vol: 6, p:1-12. doi:10.1038/ncomms10008. 2. Colin PY, Zinchenko A, Hollfelder F. Enzyme engineering in biomimetic compartments. Curr Opin Struct Biol. 2015; vol: 33, p: 42-51. doi:10.1016/j.sbi.2015.06.001. 3. Gielen F, Hours R, Emond S, Fischlechner M, Schell U, Hollfelder F. Ultrahigh-throughput-directed enzyme evolution by absorbance-activated droplet sorting (AADS). Proc Natl Acad Sci U S A. 2016; vol: 113, p: E7383-E7389. doi:10.1073/pnas.160692711

    TreasureDrop – enzyme engineering for applied biocatalysis using microfluidics

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    Enzymes have established as a new class of catalysts in the field of modern synthetic chemistry. Engineering is arguable the most promising approach to generate desired catalytic activities and its success directly correlates with the library size that can be screened. One of the most powerful technologies enabling the quick and cost-effective testing of millions of enzyme variants is the recently introduced microfluidic droplet-based screening. Interestingly, even though numerous publications highlight its potential, an unambiguous evidence of its ability to provide synthetically relevant biocatalysts still needs to be furnished. We present the engineering of an alcohol dehydrogenase for the challenging enantioselective reduction of a prochiral ketone targeting an important key building block for biologically active compounds. The final aim is not only to obtain an improved variant which allows to perform the selected biotransformation efficiently, but also a comparison of varying evolution paths. Please click Additional Files below to see the full abstract

    Accessing unexplored regions of sequence space in directed enzyme evolution via insertion/deletion mutagenesis

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    Abstract: Insertions and deletions (InDels) are frequently observed in natural protein evolution, yet their potential remains untapped in laboratory evolution. Here we introduce a transposon-based mutagenesis approach (TRIAD) to generate libraries of random variants with short in-frame InDels, and screen TRIAD libraries to evolve a promiscuous arylesterase activity in a phosphotriesterase. The evolution exhibits features that differ from previous point mutagenesis campaigns: while the average activity of TRIAD variants is more compromised, a larger proportion has successfully adapted for the activity. Different functional profiles emerge: (i) both strong and weak trade-off between activities are observed; (ii) trade-off is more severe (20- to 35-fold increased kcat/KM in arylesterase with 60-400-fold decreases in phosphotriesterase activity) and (iii) improvements are present in kcat rather than just in KM, suggesting adaptive solutions. These distinct features make TRIAD an alternative to widely used point mutagenesis, accessing functional innovations and traversing unexplored fitness landscape regions

    Engineering the protein dynamics of an ancestral luciferase.

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    Protein dynamics are often invoked in explanations of enzyme catalysis, but their design has proven elusive. Here we track the role of dynamics in evolution, starting from the evolvable and thermostable ancestral protein AncHLD-RLuc which catalyses both dehalogenase and luciferase reactions. Insertion-deletion (InDel) backbone mutagenesis of AncHLD-RLuc challenged the scaffold dynamics. Screening for both activities reveals InDel mutations localized in three distinct regions that lead to altered protein dynamics (based on crystallographic B-factors, hydrogen exchange, and molecular dynamics simulations). An anisotropic network model highlights the importance of the conformational flexibility of a loop-helix fragment of Renilla luciferases for ligand binding. Transplantation of this dynamic fragment leads to lower product inhibition and highly stable glow-type bioluminescence. The success of our approach suggests that a strategy comprising (i) constructing a stable and evolvable template, (ii) mapping functional regions by backbone mutagenesis, and (iii) transplantation of dynamic features, can lead to functionally innovative proteins
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