Ancestral Sequence Reconstruction as a Tool for the Elucidation of a Stepwise Evolutionary Adaptation

Strategies for modulating transglycosylation activity, substrate specificity, and product polymerization degree of engineered transglycosylases

Glycosides are widely used in many fields due to their favorable biological activity. The traditional plant extractions and chemical methods for glycosides production are limited by environmentally unfriendly, laborious protecting group strategies and low yields. Alternatively, enzymatic glycosylation has drawn special attention due to its mild reaction conditions, high catalytic efficiency, and specific stereo-/regioselectivity. Glycosyltransferases (GTs) and retaining glycoside hydrolases (rGHs) are two major enzymes for the formation of glycosidic linkages. Therein GTs generally use nucleotide phosphate activated donors. In contrast, GHs can use broader simple and affordable glycosyl donors, showing great potential in industrial applications. However, most rGHs mainly show hydrolysis activity and only a few rGHs, namely non-Leloir transglycosylases (TGs), innately present strong transglycosylation activities. To address this problem, various strategies have recently been developed to successfully tailor rGHs to alleviate their hydrolysis activity and obtain the engineered TGs. This review summarizes the current modification strategies in TGs engineering, with a special focus on transglycosylation activity enhancement, substrate specificity modulation, and product polymerization degree distribution, which provides a reference for exploiting the transglycosylation potentials of rGHs.

Sequence selection by FitSS4ASR alleviates ancestral sequence reconstruction as exemplified for geranylgeranylglyceryl phosphate synthase

For evolutionary studies, but also for protein engineering, ancestral sequence reconstruction (ASR) has become an indispensable tool. The first step of every ASR protocol is the preparation of a representative sequence set containing at most a few hundred recent homologs whose composition determines decisively the outcome of a reconstruction. A common approach for sequence selection consists of several rounds of manual recompilation that is driven by embedded phylogenetic analyses of the varied sequence sets. For ASR of a geranylgeranylglyceryl phosphate synthase, we additionally utilized FitSS4ASR, which replaces this time-consuming protocol with an efficient and more rational approach. FitSS4ASR applies orthogonal filters to a set of homologs to eliminate outlier sequences and those bearing only a weak phylogenetic signal. To demonstrate the usefulness of FitSS4ASR, we determined experimentally the oligomerization state of eight predecessors, which is a delicate and taxon-specific property. Corresponding ancestors deduced in a manual approach and by means of FitSS4ASR had the same dimeric or hexameric conformation; this concordance testifies to the efficiency of FitSS4ASR for sequence selection. FitSS4ASR-based results of two other ASR experiments were added to the Supporting Information. Program and documentation are available at https://gitlab.bioinf.ur.de/hek61586/FitSS4ASR.