scholarly journals Ancestral sequence reconstruction produces thermally stable enzymes with mesophilic enzyme-like catalytic properties

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ryutaro Furukawa ◽  
Wakako Toma ◽  
Koji Yamazaki ◽  
Satoshi Akanuma

Abstract Enzymes have high catalytic efficiency and low environmental impact, and are therefore potentially useful tools for various industrial processes. Crucially, however, natural enzymes do not always have the properties required for specific processes. It may be necessary, therefore, to design, engineer, and evolve enzymes with properties that are not found in natural enzymes. In particular, the creation of enzymes that are thermally stable and catalytically active at low temperature is desirable for processes involving both high and low temperatures. In the current study, we designed two ancestral sequences of 3-isopropylmalate dehydrogenase by an ancestral sequence reconstruction technique based on a phylogenetic analysis of extant homologous amino acid sequences. Genes encoding the designed sequences were artificially synthesized and expressed in Escherichia coli. The reconstructed enzymes were found to be slightly more thermally stable than the extant thermophilic homologue from Thermus thermophilus. Moreover, they had considerably higher low-temperature catalytic activity as compared with the T. thermophilus enzyme. Detailed analyses of their temperature-dependent specific activities and kinetic properties showed that the reconstructed enzymes have catalytic properties similar to those of mesophilic homologues. Collectively, our study demonstrates that ancestral sequence reconstruction can produce a thermally stable enzyme with catalytic properties adapted to low-temperature reactions.

2016 ◽  
Vol 474 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Yosephine Gumulya ◽  
Elizabeth M.J. Gillam

A central goal in molecular evolution is to understand the ways in which genes and proteins evolve in response to changing environments. In the absence of intact DNA from fossils, ancestral sequence reconstruction (ASR) can be used to infer the evolutionary precursors of extant proteins. To date, ancestral proteins belonging to eubacteria, archaea, yeast and vertebrates have been inferred that have been hypothesized to date from between several million to over 3 billion years ago. ASR has yielded insights into the early history of life on Earth and the evolution of proteins and macromolecular complexes. Recently, however, ASR has developed from a tool for testing hypotheses about protein evolution to a useful means for designing novel proteins. The strength of this approach lies in the ability to infer ancestral sequences encoding proteins that have desirable properties compared with contemporary forms, particularly thermostability and broad substrate range, making them good starting points for laboratory evolution. Developments in technologies for DNA sequencing and synthesis and computational phylogenetic analysis have led to an escalation in the number of ancient proteins resurrected in the last decade and greatly facilitated the use of ASR in the burgeoning field of synthetic biology. However, the primary challenge of ASR remains in accurately inferring ancestral states, despite the uncertainty arising from evolutionary models, incomplete sequences and limited phylogenetic trees. This review will focus, firstly, on the use of ASR to uncover links between sequence and phenotype and, secondly, on the practical application of ASR in protein engineering.


2017 ◽  
Vol 19 (22) ◽  
pp. 5375-5380 ◽  
Author(s):  
Matthew Wilding ◽  
Thomas S. Peat ◽  
Subha Kalyaanamoorthy ◽  
Janet Newman ◽  
Colin Scott ◽  
...  

The use of ancestral sequence reconstruction to design novel biocatalysts with improved catalytic properties for the production of polyamide precursors.


2019 ◽  
Vol 35 (21) ◽  
pp. 4290-4297 ◽  
Author(s):  
A Oliva ◽  
S Pulicani ◽  
V Lefort ◽  
L Bréhélin ◽  
O Gascuel ◽  
...  

Abstract Motivation The reconstruction of ancestral genetic sequences from the analysis of contemporaneous data is a powerful tool to improve our understanding of molecular evolution. Various statistical criteria defined in a phylogenetic framework can be used to infer nucleotide, amino-acid or codon states at internal nodes of the tree, for every position along the sequence. These criteria generally select the state that maximizes (or minimizes) a given criterion. Although it is perfectly sensible from a statistical perspective, that strategy fails to convey useful information about the level of uncertainty associated to the inference. Results The present study introduces a new criterion for ancestral sequence reconstruction, the minimum posterior expected error (MPEE), that selects a single state whenever the signal conveyed by the data is strong, and a combination of multiple states otherwise. We also assess the performance of a criterion based on the Brier scoring scheme which, like MPEE, does not rely on any tuning parameters. The precision and accuracy of several other criteria that involve arbitrarily set tuning parameters are also evaluated. Large scale simulations demonstrate the benefits of using the MPEE and Brier-based criteria with a substantial increase in the accuracy of the inference of past sequences compared to the standard approach and realistic compromises on the precision of the solutions returned. Availability and implementation The software package PhyML (https://github.com/stephaneguindon/phyml) provides an implementation of the Maximum A Posteriori (MAP) and MPEE criteria for reconstructing ancestral nucleotide and amino-acid sequences.


Author(s):  
Milos Musil ◽  
Rayyan Tariq Khan ◽  
Andy Beier ◽  
Jan Stourac ◽  
Hannes Konegger ◽  
...  

Abstract There is a great interest in increasing proteins’ stability to widen their usability in numerous biomedical and biotechnological applications. However, native proteins cannot usually withstand the harsh industrial environment, since they are evolved to function under mild conditions. Ancestral sequence reconstruction is a well-established method for deducing the evolutionary history of genes. Besides its applicability to discover the most probable evolutionary ancestors of the modern proteins, ancestral sequence reconstruction has proven to be a useful approach for the design of highly stable proteins. Recently, several computational tools were developed, which make the ancestral reconstruction algorithms accessible to the community, while leaving the most crucial steps of the preparation of the input data on users’ side. FireProtASR aims to overcome this obstacle by constructing a fully automated workflow, allowing even the unexperienced users to obtain ancestral sequences based on a sequence query as the only input. FireProtASR is complemented with an interactive, easy-to-use web interface and is freely available at https://loschmidt.chemi.muni.cz/fireprotasr/.


2018 ◽  
Vol 35 (15) ◽  
pp. 2562-2568
Author(s):  
Asher Moshe ◽  
Tal Pupko

Abstract Motivation Ancestral sequence reconstruction (ASR) is widely used to understand protein evolution, structure and function. Current ASR methodologies do not fully consider differences in evolutionary constraints among positions imposed by the three-dimensional (3D) structure of the protein. Here, we developed an ASR algorithm that allows different protein sites to evolve according to different mixtures of replacement matrices. We show that assigning replacement matrices to protein positions based on their solvent accessibility leads to ASR with higher log-likelihoods compared to naïve models that assume a single replacement matrix for all sites. Improved ASR log-likelihoods are also demonstrated when solvent accessibility is predicted from protein sequences rather than inferred from a known 3D structure. Finally, we show that using such structure-aware mixture models results in substantial differences in the inferred ancestral sequences. Availability and implementation http://fastml.tau.ac.il. Supplementary information Supplementary data are available at Bioinformatics online.


2021 ◽  
Vol 69 ◽  
pp. 131-141
Author(s):  
Matthew A. Spence ◽  
Joe A. Kaczmarski ◽  
Jake W. Saunders ◽  
Colin J. Jackson

2018 ◽  
Vol 35 (7) ◽  
pp. 1783-1797 ◽  
Author(s):  
Ricardo Assunção Vialle ◽  
Asif U Tamuri ◽  
Nick Goldman

2019 ◽  
Vol 400 (3) ◽  
pp. 367-381 ◽  
Author(s):  
Kristina Straub ◽  
Mona Linde ◽  
Cosimo Kropp ◽  
Samuel Blanquart ◽  
Patrick Babinger ◽  
...  

Abstract 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.


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