Quantitative Description of a Protein Fitness Landscape Based on Molecular Features

Autores
Meini, María Rocío; Tomatis, Pablo Emiliano; Weinreich, Daniel M.; Vila, Alejandro Jose
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Understanding the driving forces behind protein evolution requires the ability to correlate the molecular impact of mutations with organismal fitness. To address this issue, we employ here metallo--lactamases as a model system, which are Zn(II) dependent enzymes that mediate antibiotic resistance. We present a study of all the possible evolutionary pathways leading to a metallo--lactamase variant optimized by directed evolution. By studying the activity, stability and Zn(II) binding capabilities of all mutants in the preferred evolutionary pathways, we show that this local fitness landscape is strongly conditioned by epistatic interactions arising from the pleiotropic effect of mutations in the different molecular features of the enzyme. Activity and stability assays in purified enzymes do not provide explanatory power. Instead, measurement of these molecular features in an environment resembling the native one provides an accurate description of the observed antibiotic resistance profile. We report that optimization of Zn(II) binding abilities of metallo--lactamases during evolution is more critical than stabilization of the protein to enhance fitness. A global analysis of these parameters allows us to connect genotype with fitness based on quantitative biochemical and biophysical parameters.
Fil: Meini, María Rocío. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; Argentina
Fil: Tomatis, Pablo Emiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; Argentina
Fil: Weinreich, Daniel M.. University Brown; Estados Unidos
Fil: Vila, Alejandro Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; Argentina
Materia
Antibiotic Resistance
Epistasis
Metallo-ß-Lactamase
Protein Evolution
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/21363
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Quantitative Description of a Protein Fitness Landscape Based on Molecular FeaturesMeini, María RocíoTomatis, Pablo EmilianoWeinreich, Daniel M.Vila, Alejandro JoseAntibiotic ResistanceEpistasisMetallo-ß-LactamaseProtein Evolutionhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Understanding the driving forces behind protein evolution requires the ability to correlate the molecular impact of mutations with organismal fitness. To address this issue, we employ here metallo--lactamases as a model system, which are Zn(II) dependent enzymes that mediate antibiotic resistance. We present a study of all the possible evolutionary pathways leading to a metallo--lactamase variant optimized by directed evolution. By studying the activity, stability and Zn(II) binding capabilities of all mutants in the preferred evolutionary pathways, we show that this local fitness landscape is strongly conditioned by epistatic interactions arising from the pleiotropic effect of mutations in the different molecular features of the enzyme. Activity and stability assays in purified enzymes do not provide explanatory power. Instead, measurement of these molecular features in an environment resembling the native one provides an accurate description of the observed antibiotic resistance profile. We report that optimization of Zn(II) binding abilities of metallo--lactamases during evolution is more critical than stabilization of the protein to enhance fitness. A global analysis of these parameters allows us to connect genotype with fitness based on quantitative biochemical and biophysical parameters.Fil: Meini, María Rocío. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; ArgentinaFil: Tomatis, Pablo Emiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; ArgentinaFil: Weinreich, Daniel M.. University Brown; Estados UnidosFil: Vila, Alejandro Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; ArgentinaOxford University Press2015-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/21363Meini, María Rocío; Tomatis, Pablo Emiliano; Weinreich, Daniel M.; Vila, Alejandro Jose; Quantitative Description of a Protein Fitness Landscape Based on Molecular Features; Oxford University Press; Molecular Biology And Evolution; 32; 7; 3-2015; 1774-17870737-4038CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1093/molbev/msv059info:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/mbe/article-lookup/doi/10.1093/molbev/msv059info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:56:08Zoai:ri.conicet.gov.ar:11336/21363instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:56:08.371CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Quantitative Description of a Protein Fitness Landscape Based on Molecular Features
title Quantitative Description of a Protein Fitness Landscape Based on Molecular Features
spellingShingle Quantitative Description of a Protein Fitness Landscape Based on Molecular Features
Meini, María Rocío
Antibiotic Resistance
Epistasis
Metallo-ß-Lactamase
Protein Evolution
title_short Quantitative Description of a Protein Fitness Landscape Based on Molecular Features
title_full Quantitative Description of a Protein Fitness Landscape Based on Molecular Features
title_fullStr Quantitative Description of a Protein Fitness Landscape Based on Molecular Features
title_full_unstemmed Quantitative Description of a Protein Fitness Landscape Based on Molecular Features
title_sort Quantitative Description of a Protein Fitness Landscape Based on Molecular Features
dc.creator.none.fl_str_mv Meini, María Rocío
Tomatis, Pablo Emiliano
Weinreich, Daniel M.
Vila, Alejandro Jose
author Meini, María Rocío
author_facet Meini, María Rocío
Tomatis, Pablo Emiliano
Weinreich, Daniel M.
Vila, Alejandro Jose
author_role author
author2 Tomatis, Pablo Emiliano
Weinreich, Daniel M.
Vila, Alejandro Jose
author2_role author
author
author
dc.subject.none.fl_str_mv Antibiotic Resistance
Epistasis
Metallo-ß-Lactamase
Protein Evolution
topic Antibiotic Resistance
Epistasis
Metallo-ß-Lactamase
Protein Evolution
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Understanding the driving forces behind protein evolution requires the ability to correlate the molecular impact of mutations with organismal fitness. To address this issue, we employ here metallo--lactamases as a model system, which are Zn(II) dependent enzymes that mediate antibiotic resistance. We present a study of all the possible evolutionary pathways leading to a metallo--lactamase variant optimized by directed evolution. By studying the activity, stability and Zn(II) binding capabilities of all mutants in the preferred evolutionary pathways, we show that this local fitness landscape is strongly conditioned by epistatic interactions arising from the pleiotropic effect of mutations in the different molecular features of the enzyme. Activity and stability assays in purified enzymes do not provide explanatory power. Instead, measurement of these molecular features in an environment resembling the native one provides an accurate description of the observed antibiotic resistance profile. We report that optimization of Zn(II) binding abilities of metallo--lactamases during evolution is more critical than stabilization of the protein to enhance fitness. A global analysis of these parameters allows us to connect genotype with fitness based on quantitative biochemical and biophysical parameters.
Fil: Meini, María Rocío. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; Argentina
Fil: Tomatis, Pablo Emiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; Argentina
Fil: Weinreich, Daniel M.. University Brown; Estados Unidos
Fil: Vila, Alejandro Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Biología Molecular y Celular de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Biología Molecular y Celular de Rosario; Argentina
description Understanding the driving forces behind protein evolution requires the ability to correlate the molecular impact of mutations with organismal fitness. To address this issue, we employ here metallo--lactamases as a model system, which are Zn(II) dependent enzymes that mediate antibiotic resistance. We present a study of all the possible evolutionary pathways leading to a metallo--lactamase variant optimized by directed evolution. By studying the activity, stability and Zn(II) binding capabilities of all mutants in the preferred evolutionary pathways, we show that this local fitness landscape is strongly conditioned by epistatic interactions arising from the pleiotropic effect of mutations in the different molecular features of the enzyme. Activity and stability assays in purified enzymes do not provide explanatory power. Instead, measurement of these molecular features in an environment resembling the native one provides an accurate description of the observed antibiotic resistance profile. We report that optimization of Zn(II) binding abilities of metallo--lactamases during evolution is more critical than stabilization of the protein to enhance fitness. A global analysis of these parameters allows us to connect genotype with fitness based on quantitative biochemical and biophysical parameters.
publishDate 2015
dc.date.none.fl_str_mv 2015-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/21363
Meini, María Rocío; Tomatis, Pablo Emiliano; Weinreich, Daniel M.; Vila, Alejandro Jose; Quantitative Description of a Protein Fitness Landscape Based on Molecular Features; Oxford University Press; Molecular Biology And Evolution; 32; 7; 3-2015; 1774-1787
0737-4038
CONICET Digital
CONICET
url http://hdl.handle.net/11336/21363
identifier_str_mv Meini, María Rocío; Tomatis, Pablo Emiliano; Weinreich, Daniel M.; Vila, Alejandro Jose; Quantitative Description of a Protein Fitness Landscape Based on Molecular Features; Oxford University Press; Molecular Biology And Evolution; 32; 7; 3-2015; 1774-1787
0737-4038
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1093/molbev/msv059
info:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/mbe/article-lookup/doi/10.1093/molbev/msv059
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.982451

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