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Capturing the mutational landscape of the beta-lactamase TEM-1

  1. Olivier Tenaillona,b,1
  1. aInstitut National de la Santé et de la Recherche Médicale (INSERM), Unité Mixte de Recherche en Santé (UMR-S) 722, F-75018 Paris, France;
  2. bUniv Paris Diderot, Sorbonne Paris Cité, UMR-S 722 INSERM, F-75018 Paris, France;
  3. cService de Bactériologie-Virologie, Groupe Hospitalier Lariboisière-Fernand Widal, Assistance Publique-Hôpitaux de Paris (AP-HP), F-75475 Paris, France;
  4. dINSERM, UMR-S 738, F-75018 Paris, France;
  5. eUniv Paris Diderot, Sorbonne Paris Cité, UMR-S 738 INSERM, F-75018 Paris, France;
  6. fLaboratoire de Biochimie, UMR 7654, Ecole Polytechnique, Centre National de la Recherche Scientifique, F-91128 Palaiseau Cedex, France;
  7. gEquipe d'Accueil 3964, Université Paris Diderot, F-75018 Paris, France;
  8. hGénoscope, Commissariat à L’Energie Atomique–Institut de Génomique, 91057 Evry Cedex, France;
  9. iService de Microbiologie-Hygiène, Hôpital Louis Mourier, AP-HP, F-92700 Colombes, France; and
  10. jCentre d’Ecologie Fonctionnelle et Evolutive, Centre National de la Recherche Scientifique, UMR5175, F-34293 Montpellier Cedex 5, France

  1. Edited by Bruce R. Levin, Emory University, Atlanta, GA, and approved June 25, 2013 (received for review September 21, 2012)

Abstract

Adaptation proceeds through the selection of mutations. The distribution of mutant fitness effect and the forces shaping this distribution are therefore keys to predict the evolutionary fate of organisms and their constituents such as enzymes. Here, by producing and sequencing a comprehensive collection of 10,000 mutants, we explore the mutational landscape of one enzyme involved in the spread of antibiotic resistance, the beta-lactamase TEM-1. We measured mutation impact on the enzyme activity through the estimation of amoxicillin minimum inhibitory concentration on a subset of 990 mutants carrying a unique missense mutation, representing 64% of possible amino acid changes in that protein reachable by point mutation. We established that mutation type, solvent accessibility of residues, and the predicted effect of mutations on protein stability primarily determined alone or in combination changes in minimum inhibitory concentration of mutants. Moreover, we were able to capture the drastic modification of the mutational landscape induced by a single stabilizing point mutation (M182T) by a simple model of protein stability. This work thereby provides an integrated framework to study mutation effects and a tool to understand/define better the epistatic interactions.

Footnotes

  • ↵1To whom correspondence may be addressed. E-mail: herve.jacquier{at}lrb.aphp.fr or olivier.tenaillon{at}inserm.fr.

  • Author contributions: H.J., H.L.N., Y.M., E.S., B.B., G.B., P.-A.G., and O.T. designed research; H.J., A.B., J.G., E.P., J.P., and O.T. performed research; H.J., H.L.N., Y.M., E.S., P.-A.G., and O.T. contributed new reagents/analytic tools; H.J., A.B., H.L.N., Y.M., E.S., and O.T. analyzed data; and H.J., Y.M., and O.T. wrote the paper.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1215206110/-/DCSupplemental.

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