Using a Sequential Regimen to Eliminate Bacteria at Sublethal Antibiotic Dosages

Fuentes-Hernández, Ayari; Plucain, Jessica; Gori, Fabio; Peña‐Miller, Rafael; Reding, Carlos; Jansen, Gunther; Schulenburg, Hinrich; Gudelj, Ivana; Beardmore, Robert

doi:10.1371/journal.pbio.1002104

Cited by 84 publications

(97 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Exposing bacteria to fluctuating environments has been shown to be a potentially good strategy for slowing down the development of resistance [12,19,68]. More broadly, mechanisms of memory and history dependence in bacterial systems are being uncovered to better understand the dynamics of bacterial survival and adaptation in changing environments [69][70][71].…”

Section: Discussionmentioning

confidence: 99%

“…For consistency, stocks were revived from Days 0 (Ancestor), 5,10,15,19,20,25,30,35 During analysis of the mutations, we deduced that there were some cross-contaminations between replicates in a few lineages. Namely, we saw sets of mutations that were identical in 2 replicates.…”

Section: Adaptive Laboratory Evolutionmentioning

confidence: 99%

“…Collateral sensitivities between drugs have been used to design drug cycling strategies and to explain the decreased rate of adaptation to certain antibiotics [12,14,[18][19][20][21][22][23]. Drug deployment strategies that exploit such collateral sensitivities between pairs of antibiotics to minimize resistance evolution have been tested in vitro.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

History of Antibiotic Adaptation Influences Microbial Evolutionary Dynamics During Subsequent Treatment

Yen

Papin

2016

Preprint

View full text Add to dashboard Cite

Antibiotic regimens often include the sequential changing of drugs to limit the development and evolution of resistance of bacterial pathogens. It remains unclear how history of adaptation to one antibiotic can influence the resistance profiles when bacteria subsequently adapt to a different antibiotic. Here, we experimentally evolved Pseudomonas aeruginosa to six 2-drug sequences. We observed drug order-specific effects, whereby adaptation to the first drug can limit the rate of subsequent adaptation to the second drug, adaptation to the second drug can restore susceptibility to the first drug, or final resistance levels depend on the order of the 2-drug sequence. These findings demonstrate how resistance not only depends on the current drug regimen but also the history of past regimens. These orderspecific effects may allow for rational forecasting of the evolutionary dynamics of bacteria given knowledge of past adaptations and provide support for the need to consider the history of past drug exposure when designing strategies to mitigate resistance and combat bacterial infections. Author summaryBacteria readily adapt to their environments and can develop ways to survive and grow in the presence of antibiotics. While many studies have investigated how bacteria evolve to become resistant to single drugs, it is unclear how adaptation to other drugs and environments in the past affect the way bacteria adapt to new drugs and environments. In this study, we allowed bacteria in a laboratory setting to adapt to three different antibiotics. We first exposed wild-type susceptible bacteria to high concentrations of the three antibiotics individually and then exposed these populations to each of the other drugs. By tracking the levels of resistance to all three drugs in all of the treatments, we identified cases in which past adaptation to one treatment influenced subsequent evolutionary dynamics with regard to both phenotypes (levels of resistance) and genotypes (genes that became mutated). Additionally, by allowing bacterial isolates originating from human patients to adapt to the three drugs, we recapitulated a subset of the adaptation history-dependent evolutionary dynamics. Overall, this study sheds light on how adaptation history in PLOS Biology | https://doi.org/10.1371/journal

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Adaptive Laboratory Evolutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

History of Antibiotic Adaptation Influences Microbial Evolutionary Dynamics During Subsequent Treatment

Yen

Papin

2016

Preprint

View full text Add to dashboard Cite

show abstract

“…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.

View full text Add to dashboard Cite

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...

show abstract

“…Environmental changes may be abrupt and severe, in which case populations are likely to drastically reduce in size and face extinction [70,71]. Adaptive evolution leading to population recovery is termed evolutionary rescue [72 -74].…”

Section: The Race Against Extinctionmentioning

confidence: 99%

Molecular and cellular bases of adaptation to a changing environment in microorganisms

Bleuven

Landry

2016

Proc. R. Soc. B.

View full text Add to dashboard Cite

Environmental heterogeneity constitutes an evolutionary challenge for organisms. While evolutionary dynamics under variable conditions has been explored for decades, we still know relatively little about the cellular and molecular mechanisms involved. It is of paramount importance to examine these molecular bases because they may play an important role in shaping the course of evolution. In this review, we examine the diversity of adaptive mechanisms in the face of environmental changes. We exploit the recent literature on microbial systems because those have benefited the most from the recent emergence of genetic engineering and experimental evolution followed by genome sequencing. We identify four emerging trends: (i) an adaptive molecular change in a pathway often results in fitness trade-off in alternative environments but the effects are dependent on a mutation's genetic background; (ii) adaptive changes often modify transcriptional and signalling pathways; (iii) several adaptive changes may occur within the same molecular pathway but be associated with pleiotropy of different signs across environments; (iv) because of their large associated costs, macromolecular changes such as gene amplification and aneuploidy may be a rapid mechanism of adaptation in the short-term only. The course of adaptation in a variable environment, therefore, depends on the complexity of the environment but also on the molecular relationships among the genes involved and between the genes and the phenotypes under selection.

show abstract

Using a Sequential Regimen to Eliminate Bacteria at Sublethal Antibiotic Dosages

Cited by 84 publications

References 50 publications

History of Antibiotic Adaptation Influences Microbial Evolutionary Dynamics During Subsequent Treatment

History of Antibiotic Adaptation Influences Microbial Evolutionary Dynamics During Subsequent Treatment

Breaking evolutionary constraint with a tradeoff ratchet

Molecular and cellular bases of adaptation to a changing environment in microorganisms

Contact Info

Product

Resources

About