A Case Study of Eukaryogenesis: The Evolution of Photoreception by Photolyase/Cryptochrome Proteins

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Abstract

Eukaryogenesis, the origin of the eukaryotes, is still poorly understood. Herein, we show how a detailed all-kingdom phylogenetic analysis overlaid with a map of key biochemical features can provide valuable clues. The photolyase/cryptochrome family of proteins are well known to repair DNA in response to potentially harmful effects of sunlight and to entrain circadian rhythms. Phylogenetic analysis of photolyase/cryptochrome protein sequences from a wide range of prokaryotes and eukaryotes points to a number of horizontal gene transfer events between ancestral bacteria and ancestral eukaryotes. Previous experimental research has characterised patterns of tryptophan residues in these proteins that are important for photoreception, specifically a tryptophan dyad, a canonical tryptophan triad, an alternative tryptophan triad, a tryptophan tetrad and an alternative tetrad. Our results suggest that the spread of the different triad and tetrad motifs across the kingdoms of life accompanied the putative horizontal gene transfers and is consistent with multiple bacterial contributions to eukaryogenesis.

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Most cited references 56

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MUSCLE: multiple sequence alignment with high accuracy and high throughput.

R. C. Edgar (2004)

We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.

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New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

Stéphane Guindon, Jean-François Dufayard, Vincent Lefort … (2010)

PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.

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The Phyre2 web portal for protein modeling, prediction and analysis.

Lawrence Kelley, Stefans Mezulis, Christopher Yates … (2015)

Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission.

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Author and article information

Contributors

Paul C. Taylor:

ORCID: http://orcid.org/0000-0002-6607-944X

p.c.taylor@leeds.ac.uk

Journal

Journal ID (nlm-ta): J Mol Evol

Journal ID (iso-abbrev): J Mol Evol

Title: Journal of Molecular Evolution

Publisher: Springer US (New York )

ISSN (Print): 0022-2844

ISSN (Electronic): 1432-1432

Publication date (Electronic): 26 September 2020

Publication date PMC-release: 26 September 2020

Publication date (Print): 2020

Volume: 88

Issue: 8

Pages: 662-673

Affiliations

[1 ]GRID grid.9909.9, ISNI 0000 0004 1936 8403, School of Chemistry, , University of Leeds, ; Woodhouse Lane, Leeds, LS2 9JT UK

[2 ]GRID grid.9909.9, ISNI 0000 0004 1936 8403, Astbury Centre for Structural Molecular Biology, , University of Leeds, ; Woodhouse Lane, Leeds, LS2 9JT UK

Author notes

Handling Editor: Alan Christensen.

Author information

Jennifer A. Miles http://orcid.org/0000-0001-8839-9201

Paul C. Taylor http://orcid.org/0000-0002-6607-944X

Article

Publisher ID: 9965

DOI: 10.1007/s00239-020-09965-x

PMC ID: 7560933

PubMed ID: 32979052

SO-VID: 0c72eab9-5d3a-40b9-a390-9149d1393eb5

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 16 January 2020

Date accepted : 5 September 2020

Funding

Funded by: University of Leeds

Open Access :

Open Access funding provided by University of Leeds

Custom metadata

ScienceOpen disciplines: Evolutionary Biology

Keywords: cryptochrome,photolyase,cyanobacteria,horizontal gene transfer,eukaryogenesis

Data availability:

ScienceOpen disciplines: Evolutionary Biology

Keywords: cryptochrome, photolyase, cyanobacteria, horizontal gene transfer, eukaryogenesis

A Case Study of Eukaryogenesis: The Evolution of Photoreception by Photolyase/Cryptochrome Proteins

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Teaching and learning evolution

Most cited references 56

MUSCLE: multiple sequence alignment with high accuracy and high throughput.

New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

The Phyre2 web portal for protein modeling, prediction and analysis.

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