Role of pleiotropy during adaptation of <scp>TEM</scp>‐1 <i>β</i>‐lactamase to two novel antibiotics

Schenk, Martijn; Witte, Sariette; Salverda, Merijn L.M.; Koopmanschap, Bertha; Krug, Joachim; Visser, Jaap

doi:10.1111/eva.12200

Cited by 32 publications

(34 citation statements)

References 51 publications

(127 reference statements)

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“…The order of appearance and fixation is typically conserved for three of these changes (G238S→E104K→M182T)141734. G238S and E104K jointly improve cefotaxime binding and hydrolysis, but have destabilizing effects that are compensated by M182T35.…”

Section: Resultsmentioning

confidence: 99%

Mistranslation can enhance fitness through purging of deleterious mutations

2017

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Phenotypic mutations are amino acid changes caused by mistranslation. How phenotypic mutations affect the adaptive evolution of new protein functions is unknown. Here we evolve the antibiotic resistance protein TEM-1 towards resistance on the antibiotic cefotaxime in an Escherichia coli strain with a high mistranslation rate. TEM-1 populations evolved in such strains endow host cells with a general growth advantage, not only on cefotaxime but also on several other antibiotics that ancestral TEM-1 had been unable to deactivate. High-throughput sequencing of TEM-1 populations shows that this advantage is associated with a lower incidence of weakly deleterious genotypic mutations. Our observations show that mistranslation is not just a source of noise that delays adaptive evolution. It could even facilitate adaptive evolution by exacerbating the effects of deleterious mutations and leading to their more efficient purging. The ubiquity of mistranslation and its effects render mistranslation an important factor in adaptive protein evolution.

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Section: Resultsmentioning

confidence: 99%

Mistranslation can enhance fitness through purging of deleterious mutations

2017

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“…Overcoming genetic constraints by tradeoffs in a fluctuating environment could be relevant to these transitions given its few requirements and their ubiquitous presence. Additionally, this evolutionary mode may have implications for clinically or biotechnologically relevant problems, such as the treatment of infections with multidrug protocols (64)(65)(66) and the evolutionary engineering of antibodies (67). It will be of interest to test whether this adaptive mode affects the dynamics of experimental evolution in variable environments.…”

Section: Discussionmentioning

confidence: 99%

Breaking evolutionary constraint with a tradeoff ratchet

Vos

Dawid

Šunderlíková

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Epistatic interactions can frustrate and shape evolutionary change. Indeed, phenotypes may fail to evolve when essential mutations are only accessible through positive selection if they are fixed simultaneously. How environmental variability affects such constraints is poorly understood. Here, we studied genetic constraints in fixed and fluctuating environments using the Escherichia coli lac operon as a model system for genotypeenvironment interactions. We found that, in different fixed environments, all trajectories that were reconstructed by applying point mutations within the transcription factor-operator interface became trapped at suboptima, where no additional improvements were possible. Paradoxically, repeated switching between these same environments allows unconstrained adaptation by continuous improvements. This evolutionary mode is explained by pervasive cross-environmental tradeoffs that reposition the peaks in such a way that trapped genotypes can repeatedly climb ascending slopes and hence, escape adaptive stasis. Using a Markov approach, we developed a mathematical framework to quantify the landscape-crossing rates and show that this ratchet-like adaptive mechanism is robust in a wide spectrum of fluctuating environments. Overall, this study shows that genetic constraints can be overcome by environmental change and that crossenvironmental tradeoffs do not necessarily impede but also, can facilitate adaptive evolution. Because tradeoffs and environmental variability are ubiquitous in nature, we speculate this evolutionary mode to be of general relevance.evolution | environment | epistasis | fitness landscape | constraint I t is widely believed that epistatic interactions can direct evolutionary change (1-7). Epistasis has been implicated in shaping RNA (8) and protein (4, 6, 7, 9) sequences, sensing (5) and translation (10) functions, and developmental programs (11) and speciation (12)(13)(14). Phenotypes may be difficult to evolve not because they are impossible biochemically or physically, but because essential mutations are mutually dependent and must be fixed together to be selected positively (5,(15)(16)(17). How such genetic constraints can be overcome has been considered previously: population expansion or subdivision can limit negative selection and maintain less fit phenotypes (18,19), and large populations and long waiting times can enable the joint fixation of multiple mutations (20), whereas recombination can join mutant alleles (21-23). Other mechanisms include drift (24-26), partial penetrance (27), and nonheritable lifetime plasticity (28, 29). However, how the constraining effects of such genetic interactions are affected by environmental variability remains poorly understood. It has been shown that mutational effects (30-33) and epistasis itself (34, 35) can depend on the environment, that bacterial resistance evolution can be contingent on the rate of antibiotic increase (36), and that adaptation in silico can be accelerated by environmental change (37-40). These observations sugg...

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“…These effects could be rationalized from tradeoffs between the mutations conferring resistance to the individual drugs. In a related approach using targeted mutagenesis in multiple selection cycles, the adaptation of the resistance enzyme TEM-1 beta-lactamase to the beta-lactam antibiotics cefotaxime and ceftazidime was studied when the drugs were applied individually, in combination, or alternating over time; indications for evolutionary constraints were identified but, overall, the simultaneous or alternating application of the drugs had limited effects on resistance evolution [78].…”

Section: Drug Combinations That Minimize Resistance Evolutionmentioning

confidence: 99%

Antimicrobial interactions: mechanisms and implications for drug discovery and resistance evolution

Bollenbach

2015

Current Opinion in Microbiology

217

153

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Combining antibiotics is a promising strategy for increasing treatment efficacy and for controlling resistance evolution. When drugs are combined, their effects on cells may be amplified or weakened, that is the drugs may show synergistic or antagonistic interactions. Recent work revealed the underlying mechanisms of such drug interactions by elucidating the drugs' joint effects on cell physiology. Moreover, new treatment strategies that use drug combinations to exploit evolutionary tradeoffs were shown to affect the rate of resistance evolution in predictable ways. High throughput studies have further identified drug candidates based on their interactions with established antibiotics and general principles that enable the prediction of drug interactions were suggested. Overall, the conceptual and technical foundation for the rational design of potent drug combinations is rapidly developing.

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Role of pleiotropy during adaptation of TEM‐1 β‐lactamase to two novel antibiotics

Cited by 32 publications

References 51 publications

Mistranslation can enhance fitness through purging of deleterious mutations

Mistranslation can enhance fitness through purging of deleterious mutations

Breaking evolutionary constraint with a tradeoff ratchet

Antimicrobial interactions: mechanisms and implications for drug discovery and resistance evolution

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