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Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1

Figliuzzi, M.; Jacquier, H.; Schug, A.; Tenaillon, O.; Weigt, M.

The quantitative characterization of mutational landscapes is a task of outstanding importance in evolutionary and medical biology: It is, for example, of central importance for our understanding of the phenotypic effect of mutations related to disease and antibiotic drug resistance. Here we develop a novel inference scheme for mutational landscapes, which is based on the statistical analysis of large alignments of homologs of the protein of interest. Our method is able to capture epistatic couplings between residues, and therefore to assess the dependence of mutational effects on the sequence context where they appear. Compared with recent large-scale mutagenesis data of the beta-lactamase TEM-1, a protein providing resistance against beta-lactam antibiotics, our method leads to an increase of about 40% in explicative power as compared with approaches neglecting epistasis. We find that the informative sequence context extends to residues at native distances of about 20 Å from the mutated site, reaching thus far beyond residues in direct physical contact.

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DOI: 10.5445/IR/1000052905
DOI: 10.1093/molbev/msv211
Zitationen: 73
Web of Science
Zitationen: 71
Zugehörige Institution(en) am KIT Steinbuch Centre for Computing (SCC)
Publikationstyp Zeitschriftenaufsatz
Jahr 2015
Sprache Englisch
Identifikator ISSN: 1537-1719
KITopen-ID: 1000052905
HGF-Programm 46.11.01 (POF III, LK 01)
Erschienen in Molecular Biology and Evolution
Band 33
Heft 1
Seiten 268-280
Schlagworte mutational landscape, genotype–phenotype mapping, epistasis, coevolution, statistical inference
Nachgewiesen in Scopus
Web of Science
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