Studying the evolutionary potential of ancestral aryl sulfatases in the alkaline phosphatase family with droplet microfluidicsOpen Access

Eenink, Berhard D. G.; Holstein, Josephin M.; Heberlein, Magdalena; Dilkaute, Carina; Jose, Joachim; Hollfelder, Florian; van Loo, Bert; Bornberg-Bauer, Erich; Kaminski, Tomasz S.; Lange, Andreas

Research article in digital collection | Preprint

Abstract

Characterizing the dynamics and functional shifts during protein evolution is essential, both for understanding protein evolution and for rationalizing efficient strategies for e.g. enzymes with desired and effective functions. Most proteins organize in families, sets of divergent sequences which share a common ancestor and have a similar structural fold. We study aryl sulfatases (ASs), a subfamily of the large and evolutionary old alkaline phosphatase superfamily. In this manuscript we present how ultrahigh-throughput droplet micro-fluidics can be used for studying aryl sulfatases and their computationally reconstructed putative common ancestors. We compare the evolvability and robustness of three ancestors and four extant ASs which all exhibit catalytic promiscuity towards a range of substrate classes. Fourteen libraries with varying mutation rates were expressed in single-cell microdroplets. In general, higher mutation rates resulted in wider distribution of active variants but fewer improved variants overall. However, the impact of mutation rate differed between enzymes, with some benefiting from higher and others from lower mutation rate, underscoring the need to test diverse mutagenesis regimes.

Details about the publication

Name of the repositorybioRxiv
StatusPublished
Release year2025 (12/08/2025)
Language in which the publication is writtenEnglish
DOI10.1101/2024.12.10.627700
Keywordsancestral aryl sulfatases

Authors from the University of Münster

Bornberg-Bauer, Erich
Research Group Evolutionary Bioinformatics
Dilkaute, Carina
Professur für Pharmazeutische Chemie (Prof. Jose)
Eenink, Bernard Derk Gertjan
Research Group Evolutionary Bioinformatics
Heberlein, Magdalena
Research Group Evolutionary Bioinformatics
Jose, Joachim
Professur für Pharmazeutische Chemie (Prof. Jose)
Lange, Andreas
Research Group Evolutionary Bioinformatics

Projects the publication originates from

Duration: 01/03/2017 - 30/11/2021
Funded by: EC H2020 - Marie Skłodowska-Curie Actions - Innovative Training Network
Type of project: EU-project hosted outside University of Münster