When the most potent combination of antibiotics selects for the greatest bacterial load: the smile-frown transition.

Conventional wisdom holds that the best way to treat infection with antibiotics is to 'hit early and hit hard'. A favoured strategy is to deploy two antibiotics that produce a stronger effect in combination than if either drug were used alone. But are such synergistic combinations necessar...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Rafael Pena-Miller, David Laehnemann, Gunther Jansen, Ayari Fuentes-Hernandez, Philip Rosenstiel, Hinrich Schulenburg, Robert Beardmore
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/070ccd08a7cd4ce0ba3a11bf439ee3f1
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:070ccd08a7cd4ce0ba3a11bf439ee3f1
record_format	dspace
spelling	oai:doaj.org-article:070ccd08a7cd4ce0ba3a11bf439ee3f12021-11-18T05:37:09ZWhen the most potent combination of antibiotics selects for the greatest bacterial load: the smile-frown transition.1544-91731545-788510.1371/journal.pbio.1001540https://doaj.org/article/070ccd08a7cd4ce0ba3a11bf439ee3f12013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23630452/?tool=EBIhttps://doaj.org/toc/1544-9173https://doaj.org/toc/1545-7885Conventional wisdom holds that the best way to treat infection with antibiotics is to 'hit early and hit hard'. A favoured strategy is to deploy two antibiotics that produce a stronger effect in combination than if either drug were used alone. But are such synergistic combinations necessarily optimal? We combine mathematical modelling, evolution experiments, whole genome sequencing and genetic manipulation of a resistance mechanism to demonstrate that deploying synergistic antibiotics can, in practice, be the worst strategy if bacterial clearance is not achieved after the first treatment phase. As treatment proceeds, it is only to be expected that the strength of antibiotic synergy will diminish as the frequency of drug-resistant bacteria increases. Indeed, antibiotic efficacy decays exponentially in our five-day evolution experiments. However, as the theory of competitive release predicts, drug-resistant bacteria replicate fastest when their drug-susceptible competitors are eliminated by overly-aggressive treatment. Here, synergy exerts such strong selection for resistance that an antagonism consistently emerges by day 1 and the initially most aggressive treatment produces the greatest bacterial load, a fortiori greater than if just one drug were given. Whole genome sequencing reveals that such rapid evolution is the result of the amplification of a genomic region containing four drug-resistance mechanisms, including the acrAB efflux operon. When this operon is deleted in genetically manipulated mutants and the evolution experiment repeated, antagonism fails to emerge in five days and antibiotic synergy is maintained for longer. We therefore conclude that unless super-inhibitory doses are achieved and maintained until the pathogen is successfully cleared, synergistic antibiotics can have the opposite effect to that intended by helping to increase pathogen load where, and when, the drugs are found at sub-inhibitory concentrations.Rafael Pena-MillerDavid LaehnemannGunther JansenAyari Fuentes-HernandezPhilip RosenstielHinrich SchulenburgRobert BeardmorePublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Biology, Vol 11, Iss 4, p e1001540 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Rafael Pena-Miller David Laehnemann Gunther Jansen Ayari Fuentes-Hernandez Philip Rosenstiel Hinrich Schulenburg Robert Beardmore When the most potent combination of antibiotics selects for the greatest bacterial load: the smile-frown transition.
description	Conventional wisdom holds that the best way to treat infection with antibiotics is to 'hit early and hit hard'. A favoured strategy is to deploy two antibiotics that produce a stronger effect in combination than if either drug were used alone. But are such synergistic combinations necessarily optimal? We combine mathematical modelling, evolution experiments, whole genome sequencing and genetic manipulation of a resistance mechanism to demonstrate that deploying synergistic antibiotics can, in practice, be the worst strategy if bacterial clearance is not achieved after the first treatment phase. As treatment proceeds, it is only to be expected that the strength of antibiotic synergy will diminish as the frequency of drug-resistant bacteria increases. Indeed, antibiotic efficacy decays exponentially in our five-day evolution experiments. However, as the theory of competitive release predicts, drug-resistant bacteria replicate fastest when their drug-susceptible competitors are eliminated by overly-aggressive treatment. Here, synergy exerts such strong selection for resistance that an antagonism consistently emerges by day 1 and the initially most aggressive treatment produces the greatest bacterial load, a fortiori greater than if just one drug were given. Whole genome sequencing reveals that such rapid evolution is the result of the amplification of a genomic region containing four drug-resistance mechanisms, including the acrAB efflux operon. When this operon is deleted in genetically manipulated mutants and the evolution experiment repeated, antagonism fails to emerge in five days and antibiotic synergy is maintained for longer. We therefore conclude that unless super-inhibitory doses are achieved and maintained until the pathogen is successfully cleared, synergistic antibiotics can have the opposite effect to that intended by helping to increase pathogen load where, and when, the drugs are found at sub-inhibitory concentrations.
format	article
author	Rafael Pena-Miller David Laehnemann Gunther Jansen Ayari Fuentes-Hernandez Philip Rosenstiel Hinrich Schulenburg Robert Beardmore
author_facet	Rafael Pena-Miller David Laehnemann Gunther Jansen Ayari Fuentes-Hernandez Philip Rosenstiel Hinrich Schulenburg Robert Beardmore
author_sort	Rafael Pena-Miller
title	When the most potent combination of antibiotics selects for the greatest bacterial load: the smile-frown transition.
title_short	When the most potent combination of antibiotics selects for the greatest bacterial load: the smile-frown transition.
title_full	When the most potent combination of antibiotics selects for the greatest bacterial load: the smile-frown transition.
title_fullStr	When the most potent combination of antibiotics selects for the greatest bacterial load: the smile-frown transition.
title_full_unstemmed	When the most potent combination of antibiotics selects for the greatest bacterial load: the smile-frown transition.
title_sort	when the most potent combination of antibiotics selects for the greatest bacterial load: the smile-frown transition.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/070ccd08a7cd4ce0ba3a11bf439ee3f1
work_keys_str_mv	AT rafaelpenamiller whenthemostpotentcombinationofantibioticsselectsforthegreatestbacterialloadthesmilefrowntransition AT davidlaehnemann whenthemostpotentcombinationofantibioticsselectsforthegreatestbacterialloadthesmilefrowntransition AT guntherjansen whenthemostpotentcombinationofantibioticsselectsforthegreatestbacterialloadthesmilefrowntransition AT ayarifuenteshernandez whenthemostpotentcombinationofantibioticsselectsforthegreatestbacterialloadthesmilefrowntransition AT philiprosenstiel whenthemostpotentcombinationofantibioticsselectsforthegreatestbacterialloadthesmilefrowntransition AT hinrichschulenburg whenthemostpotentcombinationofantibioticsselectsforthegreatestbacterialloadthesmilefrowntransition AT robertbeardmore whenthemostpotentcombinationofantibioticsselectsforthegreatestbacterialloadthesmilefrowntransition
_version_	1718424830723751936

When the most potent combination of antibiotics selects for the greatest bacterial load: the smile-frown transition.

Ejemplares similares