Dataset Information

Selecting Better Biocatalysts by Complementing Recoded Bacteria.

ABSTRACT: In vivo selections are powerful tools for the directed evolution of enzymes. However, the need to link enzymatic activity to cellular survival makes selections for enzymes that do not fulfill a metabolic function challenging. Here, we present an in vivo selection strategy that leverages recoded organisms addicted to non-canonical amino acids (ncAAs) to evolve biocatalysts that can provide these building blocks from synthetic precursors. We exemplify our platform by engineering carbamoylases that display catalytic efficiencies more than five orders of magnitude higher than those observed for the wild-type enzyme for ncAA-precursors. As growth rates of bacteria under selective conditions correlate with enzymatic activities, we were able to elicit improved variants from populations by performing serial passaging. By requiring minimal human intervention and no specialized equipment, we surmise that our strategy will become a versatile tool for the in vivo directed evolution of diverse biocatalysts.

SUBMITTER: Rubini R

PROVIDER: S-EPMC10107544 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Selecting Better Biocatalysts by Complementing Recoded Bacteria.

Rubini Rudy R Jansen Suzanne C SC Beekhuis Houdijn H Rozeboom Henriëtte J HJ Mayer Clemens C

Angewandte Chemie (International ed. in English) 20221207 2

In vivo selections are powerful tools for the directed evolution of enzymes. However, the need to link enzymatic activity to cellular survival makes selections for enzymes that do not fulfill a metabolic function challenging. Here, we present an in vivo selection strategy that leverages recoded organisms addicted to non-canonical amino acids (ncAAs) to evolve biocatalysts that can provide these building blocks from synthetic precursors. We exemplify our platform by engineering carbamoylases that ...[more]

PMID: 36342942

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Project description:BACKGROUND: Avian brood parasites and their hosts are involved in complex offence-defense coevolutionary arms races. The most common pair of reciprocal adaptations in these systems is egg discrimination by hosts and egg mimicry by parasites. As mimicry improves, more advanced host adaptations evolve such as decreased intra- and increased interclutch variation in egg appearance to facilitate detection of parasitic eggs. As interclutch variation increases, parasites able to choose hosts matching best their own egg phenotype should be selected, but this requires that parasites know their own egg phenotype and select host nests correspondingly. METHODOLOGY/PRINCIPAL FINDINGS: We compared egg mimicry of common cuckoo Cuculus canorus eggs in naturally parasitized marsh warbler Acrocephalus palustris nests and their nearest unparasitized conspecific neighbors having similar laying dates and nest-site characteristics. Modeling of avian vision and image analyses revealed no evidence that cuckoos parasitize nests where their eggs better match the host eggs. Cuckoo eggs were as good mimics, in terms of background and spot color, background luminance, spotting pattern and egg size, of host eggs in the nests actually exploited as those in the neighboring unparasitized nests. CONCLUSIONS/SIGNIFICANCE: We reviewed the evidence for brood parasites selecting better-matching host egg phenotypes from several relevant studies and argue that such selection probably cannot exist in host-parasite systems where host interclutch variation is continuous and overall low or moderate. To date there is also no evidence that parasites prefer certain egg phenotypes in systems where it should be most advantageous, i.e., when both hosts and parasites lay polymorphic eggs. Hence, the existence of an ability to select host nests to maximize mimicry by brood parasites appears unlikely, but this possibility should be further explored in cuckoo-host systems where the host has evolved discrete egg phenotypes.

Dataset Information

Selecting Better Biocatalysts by Complementing Recoded Bacteria.

Publications

Selecting Better Biocatalysts by Complementing Recoded Bacteria.

Similar Datasets

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