scholarly journals Genotypic context modulates fitness landscapes: Effects on the speed and direction of evolution for antimicrobial resistance

2018 ◽  
Author(s):  
C. Brandon Ogbunugafor ◽  
Rafael F. Guerrero ◽  
Margaret J. Eppstein
Keyword(s):  
Public Health ◽  
Drug Resistance ◽  
Antimicrobial Resistance ◽  
Adaptive Evolution ◽  
Evolutionary Biology ◽  
Fitness Landscape ◽  
Genetic Differences ◽  
Fitness Landscapes ◽  
Bacterial Enzyme ◽  
Pathogen Populations

AbstractUnderstanding the forces that drive the dynamics of adaptive evolution is a goal of many subfields within evolutionary biology. The fitness landscape analogy has served as a useful abstraction for addressing these topics across many systems, and recent treatments have revealed how different environments can frame the particulars of adaptive evolution by changing the topography of fitness landscapes. In this study, we examine how the larger, ambient genotypic context in which the fitness landscape being modeled is embedded affects fitness landscape topography and subsequent evolution. Using simulations on empirical fitness landscapes, we discover that genotypic context, defined by genetic variability in regions outside of the locus under study (in this case, an essential bacterial enzyme target of antibiotics), influences the speed and direction of evolution in several surprising ways. These findings have implications for how we study the evolution of drug resistance in nature, and for presumptions about how biological evolution might be expected to occur in genetically-modified organisms. More generally, the findings speak to theory surrounding how “difference can beget difference” in adaptive evolution: that small genetic differences between organisms can greatly alter the specifics of how evolution occurs, which can rapidly drive even slightly diverged populations further apart.Author summaryTechnological advances enable scientists to engineer individual mutations at specific sites within an organism’s genome with increasing ease. These breakthroughs have provided scientists with tools to study how different engineered mutations affect the function of a given gene or protein, yielding useful insight into genotype-phenotype mapping and evolution. In this study, we use engineered strains of bacteria to show how the dynamics (speed and direction) of evolution of drug resistance in an enzyme depends on the species-type of that bacterial enzyme, and on the presence/absence of mutations in other genes in the bacterial genome. These findings have broad implications for public health, genetic engineering, and theories of speciation. In the context of public health and biomedicine, our results suggest that future efforts in managing antimicrobial resistance must consider genetic makeup of different pathogen populations before predicting how resistance will occur, rather than assuming that the same resistance pathways will appear in different pathogen populations. With regard to broader theory in evolutionary biology, our results show how even small genetic differences between organisms can alter how future evolution occurs, potentially causing closely-related populations to quickly diverge.

scholarly journals Biophysical principles predict fitness landscapes of drug resistance

2016 ◽  
Vol 113 (11) ◽  
pp. E1470-E1478 ◽  
Author(s):  
João V. Rodrigues ◽  
Shimon Bershtein ◽  
Anna Li ◽  
Elena R. Lozovsky ◽  
Daniel L. Hartl ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Protein Quality ◽  
Fitness Landscape ◽  
Catalytic Efficiency ◽  
Fitness Landscapes ◽  
Resistance Mutations ◽  
Chlamydia Muridarum ◽  
Complete Set ◽  
Essential Enzyme

Fitness landscapes of drug resistance constitute powerful tools to elucidate mutational pathways of antibiotic escape. Here, we developed a predictive biophysics-based fitness landscape of trimethoprim (TMP) resistance for Escherichia coli dihydrofolate reductase (DHFR). We investigated the activity, binding, folding stability, and intracellular abundance for a complete set of combinatorial DHFR mutants made out of three key resistance mutations and extended this analysis to DHFR originated from Chlamydia muridarum and Listeria grayi. We found that the acquisition of TMP resistance via decreased drug affinity is limited by a trade-off in catalytic efficiency. Protein stability is concurrently affected by the resistant mutants, which precludes a precise description of fitness from a single molecular trait. Application of the kinetic flux theory provided an accurate model to predict resistance phenotypes (IC50) quantitatively from a unique combination of the in vitro protein molecular properties. Further, we found that a controlled modulation of the GroEL/ES chaperonins and Lon protease levels affects the intracellular steady-state concentration of DHFR in a mutation-specific manner, whereas IC50 is changed proportionally, as indeed predicted by the model. This unveils a molecular rationale for the pleiotropic role of the protein quality control machinery on the evolution of antibiotic resistance, which, as we illustrate here, may drastically confound the evolutionary outcome. These results provide a comprehensive quantitative genotype–phenotype map for the essential enzyme that serves as an important target of antibiotic and anticancer therapies.

scholarly journals Public health evolutionary biology of antimicrobial resistance: priorities for intervention

2014 ◽  
Vol 8 (3) ◽  
pp. 223-239 ◽  
Author(s):  
Fernando Baquero ◽  
Val F. Lanza ◽  
Rafael Cantón ◽  
Teresa M. Coque
Keyword(s):  
Public Health ◽  
Antimicrobial Resistance ◽  
Evolutionary Biology

scholarly journals Lexical landscapes as largein silicodata for examining advanced properties of fitness landscapes

2019 ◽  
Author(s):  
Victor A. Meszaros ◽  
Miles D. Miller-Dickson ◽  
C. Brandon Ogbunugafor
Keyword(s):  
Evolutionary Theory ◽  
Empirical Data ◽  
In Silico ◽  
Evolutionary Biology ◽  
Fitness Landscape ◽  
Evolutionary Genetics ◽  
Higher Order ◽  
Fitness Landscapes ◽  
Adaptive Landscape ◽  
Data Sets

In silicoapproaches have served a central role in the development of evolutionary theory for generations. This especially applies to the concept of the fitness landscape, one of the most important abstractions in evolutionary genetics, and one which has benefited from the presence of large empirical data sets only in the last decade or so. In this study, we propose a method that allows us to generate enormous data sets that walk the line betweenin silicoand empirical: word usage frequencies as catalogued by the Google ngram corpora. These data can be codified or analogized in terms of a multidimensional empirical fitness landscape towards the examination of advanced concepts—adaptive landscape by environment interactions, clonal competition, higher-order epistasis and countless others. We argue that the greaterLexical Landscapesapproach can serve as a platform that offers an astronomical number of fitness landscapes for exploration (at least) or theoretical formalism (potentially) in evolutionary biology.

scholarly journals Prevalence and Predictors of Antimicrobial Resistance Among Enterococcus spp. From Dogs Presented at a Veterinary Teaching Hospital, South Africa

2021 ◽  
Vol 7 ◽  
Author(s):  
James Wabwire Oguttu ◽  
Daniel Nenene Qekwana ◽  
Agricola Odoi
Keyword(s):  
Public Health ◽  
South Africa ◽  
Drug Resistance ◽  
Antimicrobial Resistance ◽  
Teaching Hospital ◽  
Univariate Analysis ◽  
Antimicrobial Drug ◽  
Health Concern ◽  
Antimicrobial Drug Resistance ◽  
Extensive Drug Resistance

Background: While surveillance of antimicrobial drug resistance is ongoing in human medicine in South Africa, there is no such activity being performed in veterinary medicine. As a result, there is a need to investigate antimicrobial resistance among enterococci isolated from dogs in South Africa to improve understanding of the status of antimicrobial drug resistance given its public and veterinary public health importance. This study investigated antimicrobial resistance and factors associated with resistance profiles of enterococci isolated from dogs presented for veterinary care at a veterinary teaching hospital in South Africa.Methods: In total 102 Enterococcus isolated between 2007 and 2011 by a bacteriology laboratory at a teaching hospital were included in this study. Antimicrobial susceptibility of the isolates was determined against a panel of 18 antimicrobials using the Kirby Bauer disc diffusion technique. Univariate analysis was used to assess simple associations between year, season, breed group, age group, sex, and specimen as covariates and extensive drug resistance (XDR) as the outcome. Variables that were significant in the univariate analysis at a generous p-value ≤ 0.2 were included in the multivariable logistic models to investigate predictors of XDR.Results: All the Enterococcus isolates were resistant to at least one antimicrobial. High proportions of isolates were resistant against lincomycin (93%), kanamycin (87%), orbifloxacin (85%), and aminogycoside-lincosamide (77%). Ninety three percent (93%), 35.3, and 8.8% of the isolates exhibited multi-drug, extensive-drug and pan-drug resistance, respectively. Only year was significantly (p = 0.019) associated with extensive-drug resistance.Conclusion: Given the zoonotic potential of Enterococcus spp., the high antimicrobial resistance and multi-drug resistance observed in this study are a public health concern from one health perspective. The identified resistance to various antimicrobials may be useful in guiding clinicians especially in resource scarce settings where it is not always possible to perform AST when making treatment decisions.

scholarly journals Recombination and mutational robustness in neutral fitness landscapes

2019 ◽  
Author(s):  
Alexander Klug ◽  
Su-Chan Park ◽  
Joachim Krug
Keyword(s):  
Evolutionary Biology ◽  
Fitness Landscape ◽  
Genetic Recombination ◽  
Fitness Landscapes ◽  
Point Of View ◽  
Genetic Exchange ◽  
Favorable Effect ◽  
Minor Effect ◽  
Moderate Increase ◽  
Mutational Robustness

AbstractMutational robustness quantifies the effect of random mutations on fitness. When mutational robustness is high, most mutations do not change fitness or have only a minor effect on it. From the point of view of fitness landscapes, robust genotypes form neutral networks of almost equal fitness. Using deterministic population models it has been shown that selection favors genotypes inside such networks, which results in increased mutational robustness. Here we demonstrate that this effect is massively enhanced by recombination. Our results are based on a detailed analysis of mesa-shaped fitness landscapes, where we derive precise expressions for the dependence of the robustness on the landscape parameters for recombining and non-recombining populations. In addition, we carry out numerical simulations on different types of random holey landscapes as well as on an empirical fitness landscape. We show that the mutational robustness of a genotype generally correlates with its recombination weight, a new measure that quantifies the likelihood for the genotype to arise from recombination. We argue that the favorable effect of recombination on mutational robustness is a highly universal feature that may have played an important role in the emergence and maintenance of mechanisms of genetic exchange.Author summaryTwo long-standing and seemingly unrelated puzzles in evolutionary biology concern the ubiquity of sexual reproduction and the robustness of organisms against genetic perturbations. Using a theoretical approach based on the concept of a fitness landscape, in this article we argue that the two phenomena may in fact be closely related. In our setting the hereditary information of an organism is encoded in its genotype, which determines it to be either viable or non-viable, and robustness is defined as the fraction of mutations that maintain viability. Previous work has demonstrated that the purging of non-viable genotypes from the population by natural selection leads to a moderate increase in robustness. Here we show that genetic recombination acting in combination with selection massively enhances this effect, an observation that is largely independent of how genotypes are connected by mutations. This suggests that the increase of robustness may be a major driver underlying the evolution of sexual recombination and other forms of genetic exchange throughout the living world.

scholarly journals Multi-Locus Sequence Typing and Drug Resistance Analysis of Swine Origin Escherichia coli in Shandong of China and Its Potential Risk on Public Health

2021 ◽  
Vol 9 ◽  
Author(s):  
Wei Wang ◽  
Lanping Yu ◽  
Wenwen Hao ◽  
Fusen Zhang ◽  
Meijie Jiang ◽  
...  
Keyword(s):  
Public Health ◽  
Escherichia Coli ◽  
Drug Resistance ◽  
Antimicrobial Resistance ◽  
Potential Risk ◽  
Shandong Province ◽  
Multi Locus Sequence Typing ◽  
Drug Resistant ◽  
Human Origin ◽  
E Coli

The extensive use of antibiotics has caused antimicrobial resistance and multidrug resistance in Escherichia coli and gradual expands it into a worldwide problem. The resistant E. coli could be transmitted to humans through animal products, thereby creating a problem for bacterial treatment in humans and resulting in a public health issue. This study aims to investigate the molecular typing and drug resistance of swine and human origin E. coli within the same prefecture-level cities of Shandong Province and the potential risk of E. coli on public health. The drug sensitivity results indicated that tetracycline (TE) (97.17%) is a major antibiotic with high drug resistance in 106 swine origin E. coli. There was a significant difference in the drug-resistant genotypes between the two sources, of which the blaTEM positive rate was the highest in the genera of β-lactams (99% in swines and 100% in humans). Among the 146 E. coli isolates, 98 (91.51% swine origin) and 31 (77.5% human origin) isolates were simultaneously resistant to three or more classes of antibiotics, respectively. The multi-locus sequence typing (MLST) results indicate that the 106 swine origin E. coli isolates are divided into 25 STs with ST1258, ST361, and ST10 being the dominant sequence analysis typing strains. There were 19 MLST genotypes in 40 strains of human E. coli from Tai'an, Shandong Province, with ST1193, ST73, ST648, ST131, ST10, and ST1668 being the dominant strains. Moreover, the cluster analysis showed that CCl0 and CC23 were the common clonal complexes (CCs) from the two sources. Our results provide a theoretical basis for guiding the rational use of antibiotics and preventing the spread of drug-resistant bacteria, and also provide epidemiological data for the risk analysis of foodborne bacteria and antimicrobial resistance in swine farms in Shandong Province.

scholarly journals Effect of Host Species on Topography of the Fitness Landscape for a Plant RNA Virus

2016 ◽  
Vol 90 (22) ◽  
pp. 10160-10169 ◽  
Author(s):  
Héctor Cervera ◽  
Jasna Lalić ◽  
Santiago F. Elena
Keyword(s):  
Host Species ◽  
Evolutionary Biology ◽  
Evolutionary Dynamics ◽  
Fitness Landscape ◽  
Rna Virus ◽  
Fitness Landscapes ◽  
Content Type ◽  
Fine Grained ◽  
Novel Host ◽  
Fitness Tradeoffs

ABSTRACTAdaptive fitness landscapes are a fundamental concept in evolutionary biology that relate the genotypes of individuals to their fitness. In the end, the evolutionary fate of evolving populations depends on the topography of the landscape, that is, the numbers of accessible mutational pathways and possible fitness peaks (i.e., adaptive solutions). For a long time, fitness landscapes were only theoretical constructions due to a lack of precise information on the mapping between genotypes and phenotypes. In recent years, however, efforts have been devoted to characterizing the properties of empirical fitness landscapes for individual proteins or for microbes adapting to artificial environments. In a previous study, we characterized the properties of the empirical fitness landscape defined by the first five mutations fixed during adaptation of tobacco etch potyvirus (TEV) to a new experimental host,Arabidopsis thaliana. Here we evaluate the topography of this landscape in the ancestral hostNicotiana tabacum. By comparing the topographies of the landscapes for the two hosts, we found that some features remained similar, such as the existence of fitness holes and the prevalence of epistasis, including cases of sign and reciprocal sign epistasis that created rugged, uncorrelated, and highly random topographies. However, we also observed significant differences in the fine-grained details between the two landscapes due to changes in the fitness and epistatic interactions of some genotypes. Our results support the idea that not only fitness tradeoffs between hosts but also topographical incongruences among fitness landscapes in alternative hosts may contribute to virus specialization.IMPORTANCEDespite its importance for understanding virus evolutionary dynamics, very little is known about the topography of virus adaptive fitness landscapes, and even less is known about the effects that different host species and environmental conditions may have on this topography. To bridge this gap, we evaluated the topography of a small fitness landscape formed by all genotypes that result from every possible combination of the first five mutations fixed during adaptation of TEV to the novel hostA. thaliana. To assess the effect that host species may have on this topography, we evaluated the fitness of every genotype in both the ancestral and novel hosts. We found that both landscapes share some macroscopic properties, such as the existence of holes and being highly rugged and uncorrelated, yet they differ in microscopic details due to changes in the magnitude and sign of fitness and epistatic effects.

scholarly journals Fighting microbial drug resistance: a primer on the role of evolutionary biology in public health

2015 ◽  
Vol 8 (3) ◽  
pp. 211-222 ◽  
Author(s):  
Gabriel G. Perron ◽  
R. Fredrik Inglis ◽  
Pleuni S. Pennings ◽  
Sarah Cobey
Keyword(s):  
Public Health ◽  
Drug Resistance ◽  
Evolutionary Biology ◽  
Microbial Drug Resistance

scholarly journals Genetic Algorithms as a method to study adaptive walks in biological landscapes

2020 ◽  
Author(s):  
Edith Invernizzi ◽  
Graeme D Ruxton
Keyword(s):  
Genetic Algorithms ◽  
Evolutionary Biology ◽  
Fitness Landscape ◽  
Evolutionary Process ◽  
Simulation Modelling ◽  
Fitness Landscapes ◽  
Mathematical Methods ◽  
Reproductive Process ◽  
Modelling Framework ◽  
Phenotypic Fitness

AbstractThe metaphor of fitness landscapes is common in evolutionary biology, as a way to visualise the change in allele or phenotypic frequencies of a population under selection. Understanding how different factors in the evolutionary process affect the trajectory of the population across the landscape is of interest to both theoretical and empirical evolutionary biologists. However, fitness landscape studies often have to rely heavily on mathematical methods that are not easy to access by biologically trained researchers. Here, we used a method borrowed from engineering - genetic algorithms - to simulate the evolutionary process and study how different components affect the path taken through a phenotypic fitness landscape. In a simple study, we compare five selection models that reflect different degrees of dependency of fitness on trait quality: this includes strengths of selection, trait-quality dependent reproductive hierarchy and the amount of stochasticity in the reproductive process. We include an analysis of other evolutionary variables such as population size and mutation rate. We analyse a game theory problem, as a test landscape, that lends itself to analysis through a deterministic mathematical simulation, which we use for comparison. Our results show that there are differences in the speed with which different models of selection lead to the fitness optimum.Author summaryEvolution and adaptation in biology occurs in fitness landscapes, multidimensional spaces representing all possible genotypic or phenotypic combinations, where population adapt by following the cline of the fitness dimension. The study of adaptation on complex fitness landscapes has so far been limited by the need for mathematically heavy methods. Here, we present a simulation modelling framework, genetic algorithms, that can be used for evolutionary simulations of a population on a fitness landscape of chosen features and with custom evolutionary parameters.

European Surveillance of Antimicrobial Consumption: the ESAC programme

2004 ◽  
Vol 8 (32) ◽  
Author(s):  
Keyword(s):  
Public Health ◽  
Antimicrobial Resistance ◽  
Health Concern ◽  
Antimicrobial Consumption ◽  
Public Health Concern ◽  
Major Public Health Concern

Resistance to antimicrobials has become a major public health concern, and it has been shown that there is a relationship, albeit complex, between antimicrobial resistance and consumption

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