scholarly journals Predicting mutational routes to new adaptive phenotypes

2018 ◽  
Author(s):  
Peter A. Lind ◽  
Eric Libby ◽  
Jenny Herzog ◽  
Paul B. Rainey

AbstractPredicting evolutionary change poses numerous challenges. Here we take advantage of the model bacterium Pseudomonas fluorescens in which the genotype-to-phenotype map determining evolution of the adaptive “wrinkly spreader” (WS) type is known. We present mathematical descriptions of three necessary regulatory pathways and use these to predict both the rate at which each mutational route is used and the expected mutational targets. To test predictions, mutation rates and targets were determined for each pathway. Unanticipated mutational hotspots caused experimental observations to depart from predictions but additional data led to refined models. A mismatch was observed between the spectra of WS-causing mutations obtained with and without selection due to low fitness of previously undetected WS-causing mutations. Our findings contribute toward the development of mechanistic models for forecasting evolution, highlight current limitations, and draw attention to challenges in predicting locus-specific mutational biases and fitness effects.Impact statementA combination of genetics, experimental evolution and mathematical modelling defines information necessary to predict the outcome of short-term adaptive evolution.

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Peter A Lind ◽  
Eric Libby ◽  
Jenny Herzog ◽  
Paul B Rainey

Predicting evolutionary change poses numerous challenges. Here we take advantage of the model bacterium Pseudomonas fluorescens in which the genotype-to-phenotype map determining evolution of the adaptive ‘wrinkly spreader’ (WS) type is known. We present mathematical descriptions of three necessary regulatory pathways and use these to predict both the rate at which each mutational route is used and the expected mutational targets. To test predictions, mutation rates and targets were determined for each pathway. Unanticipated mutational hotspots caused experimental observations to depart from predictions but additional data led to refined models. A mismatch was observed between the spectra of WS-causing mutations obtained with and without selection due to low fitness of previously undetected WS-causing mutations. Our findings contribute toward the development of mechanistic models for forecasting evolution, highlight current limitations, and draw attention to challenges in predicting locus-specific mutational biases and fitness effects.


2018 ◽  
Author(s):  
Peter A. Lind

AbstractExperimental evolution is often highly repeatable, but the underlying causes are generally unknown, which prevents extension of evolutionary forecasts to related species. Data on adaptive phenotypes, mutation rates and targets from the Pseudomonas fluorescens SBW25 Wrinkly Spreader system combined with mathematical models of the genotype-to-phenotype map allowed evolutionary forecasts to be made for several related Pseudomonas species. Predicted outcomes of experimental evolution in terms of phenotype, types of mutations, relative rates of pathways and mutational targets were then tested in Pseudomonas protegens Pf-5. As predicted, most mutations were found in three specific regulatory pathways resulting in increased production of Pel exopolysaccharide. Mutations were, as predicted, mainly found to disrupt negative regulation with a smaller number in upstream promoter regions. Mutated regions in proteins could also be predicted, but most mutations were not identical to those previously found. This study demonstrates the potential of short-term evolutionary forecasting in experimental populations.Impact statementConservation of genotype-to-phenotype maps allows successful prediction of short-term evolution in P. protegens Pf-5 and lays the foundation for evolutionary forecasting in other Pseudomonas.


2017 ◽  
Author(s):  
Jamie R. Blundell ◽  
Katja Schwartz ◽  
Danielle Francois ◽  
Daniel S. Fisher ◽  
Gavin Sherlock ◽  
...  

The dynamics of genetic diversity in large clonally-evolving cell populations are poorly understood, despite having implications for the treatment of cancer and microbial infections. Here, we combine barcode lineage tracking, sequencing of adaptive clones, and mathematical modelling of mutational dynamics to understand diversity changes during experimental evolution. We find that, despite differences in beneficial mutational mechanisms and fitness effects between two environments, early adaptive genetic diversity increases predictably, driven by the expansion of many single-mutant lineages. However, a crash in diversity follows, caused by highly-fit double-mutants fed from exponentially growing single-mutants, a process closely related to the classic Luria-Delbruck experiment. The diversity crash is likely to be a general feature of clonal evolution, however its timing and magnitude is stochastic and depends on the population size, the distribution of beneficial fitness effects, and patterns of epistasis.


Physiology ◽  
1995 ◽  
Vol 10 (6) ◽  
pp. 253-259 ◽  
Author(s):  
AM Bertorello ◽  
AI Katz

Short-term regulation of membrane Na+ -K+-ATPase activity is achieved by complex networks of receptor-mediated intracellular signals. Such regulatory pathways include activation of cyclic AMP-dependent protein kinase or protein kinase C and involve reversible phosphorylation of the catalytic (a) subunit of the enzyme directly, of additional mediators like eicosanoids and the actin cytoskeleton, or both.


2011 ◽  
Vol 279 (1727) ◽  
pp. 247-256 ◽  
Author(s):  
Bjørn Østman ◽  
Arend Hintze ◽  
Christoph Adami

Evolutionary adaptation is often likened to climbing a hill or peak. While this process is simple for fitness landscapes where mutations are independent, the interaction between mutations (epistasis) as well as mutations at loci that affect more than one trait (pleiotropy) are crucial in complex and realistic fitness landscapes. We investigate the impact of epistasis and pleiotropy on adaptive evolution by studying the evolution of a population of asexual haploid organisms (haplotypes) in a model of N interacting loci, where each locus interacts with K other loci. We use a quantitative measure of the magnitude of epistatic interactions between substitutions, and find that it is an increasing function of K . When haplotypes adapt at high mutation rates, more epistatic pairs of substitutions are observed on the line of descent than expected. The highest fitness is attained in landscapes with an intermediate amount of ruggedness that balance the higher fitness potential of interacting genes with their concomitant decreased evolvability. Our findings imply that the synergism between loci that interact epistatically is crucial for evolving genetic modules with high fitness, while too much ruggedness stalls the adaptive process.


mBio ◽  
2017 ◽  
Vol 8 (5) ◽  
Author(s):  
Berra Erkosar ◽  
Sylvain Kolly ◽  
Jan R. van der Meer ◽  
Tadeusz J. Kawecki

ABSTRACTNumerous studies have shown that animal nutrition is tightly linked to gut microbiota, especially under nutritional stress. InDrosophila melanogaster, microbiota are known to promote juvenile growth, development, and survival on poor diets, mainly through enhanced digestion leading to changes in hormonal signaling. Here, we show that this reliance on microbiota is greatly reduced in replicatedDrosophilapopulations that became genetically adapted to a poor larval diet in the course of over 170 generations of experimental evolution. Protein and polysaccharide digestion in these poor-diet-adapted populations became much less dependent on colonization with microbiota. This was accompanied by changes in expression levels of dFOXO transcription factor, a key regulator of cell growth and survival, and many of its targets. These evolutionary changes in the expression of dFOXO targets to a large degree mimic the response of the same genes to microbiota, suggesting that the evolutionary adaptation to poor diet acted on mechanisms that normally mediate the response to microbiota. Our study suggests that some metazoans have retained the evolutionary potential to adapt their physiology such that association with microbiota may become optional rather than essential.IMPORTANCEAnimals depend on gut microbiota for various metabolic tasks, particularly under conditions of nutritional stress, a relationship usually regarded as an inherent aspect of animal physiology. Here, we use experimental evolution in fly populations to show that the degree of host dependence on microbiota can substantially and rapidly change as the host population evolves in response to poor diet. Our results suggest that, although microbiota may initially greatly facilitate coping with suboptimal diets, chronic nutritional stress experienced over multiple generations leads to evolutionary adaptation in physiology and gut digestive properties that reduces dependence on the microbiota for growth and survival. Thus, despite its ancient evolutionary history, the reliance of animal hosts on their microbial partners can be surprisingly flexible and may be relaxed by short-term evolution.IMPORTANCEAnimals depend on gut microbiota for various metabolic tasks, particularly under conditions of nutritional stress, a relationship usually regarded as an inherent aspect of animal physiology. Here, we use experimental evolution in fly populations to show that the degree of host dependence on microbiota can substantially and rapidly change as the host population evolves in response to poor diet. Our results suggest that, although microbiota may initially greatly facilitate coping with suboptimal diets, chronic nutritional stress experienced over multiple generations leads to evolutionary adaptation in physiology and gut digestive properties that reduces dependence on the microbiota for growth and survival. Thus, despite its ancient evolutionary history, the reliance of animal hosts on their microbial partners can be surprisingly flexible and may be relaxed by short-term evolution.


2012 ◽  
Vol 12 (1) ◽  
pp. 252 ◽  
Author(s):  
Adérito L Monjane ◽  
Daniel Pande ◽  
Francisco Lakay ◽  
Dionne N Shepherd ◽  
Eric van der Walt ◽  
...  

Ekonomika ◽  
1997 ◽  
Vol 42 ◽  
Author(s):  
Žilvinas Kalinauskas ◽  
Bronislava Kaminskienė ◽  
Rimantas Rudzkis

Monthly data on price indices of consumer goods and services as well as groups of some goods and the principal monetary indices in Lithuania are considered in this paper using methods of mathematical statistics. The main goal of this work is to construct mathematical models of the consumer price (ePI) index, fit for short-term prediction. Statistical dependency between prices and monetary indicators is investigated in the paper. Trends and seasonal components are estimated. Random fluctuations are described using autoregression models. Regressive models of prices and monetary indicators as regressors are constructed. Errors of indicator prediction using the proposed models are estimated. An expert analysis of the state of the national economy is made, taking into account changes in price, production, and unemployment indicators. Due to data inaccuracy and frequent recalculation of indicators, only a qualitative analysis was made without applying mathematical means.


2016 ◽  
Author(s):  
Tim Coulson ◽  
Bruce E Kendall ◽  
Julia Barthold ◽  
Floriane Plard ◽  
Susanne Schindler ◽  
...  

AbstractUnderstanding how the natural world will be impacted by environmental change over the coming decades is one of the most pressing challenges facing humanity. Addressing this challenge is difficult because environmental change can generate both population level plastic and evolutionary responses, with plastic responses being either adaptive or non-adaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses, and that the rate of adaptive evolution to a new environment depends upon whether plastic responses are adaptive or non-adaptive. Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full machinery of the evolutionarily explicit models we develop will be needed to predict responses to environmental change, or whether simpler non-evolutionary models that are now widely constructed may be sufficient.


2021 ◽  
Author(s):  
Yoav Ram ◽  
Yitzhak Tzachi Pilpel ◽  
Gabriela Aleksandra Lobinska

The mutation rate is an important determinant of evolutionary dynamics. Because the mutation rate determines the rate of appearance of beneficial and deleterious mutations, it is subject to second-order selection. The mutation rate varies between and within species and populations, increases under stress, and is genetically controlled by mutator alleles. The mutation rate may also vary among genetically identical individuals: empirical evidence from bacteria suggests that the mutation rate may be affected by translation errors and expression noise in various proteins (1). Importantly, this non-genetic variation may be heritable via transgenerational epigenetic inheritance. Here we investigate how the inheritance mode of the mutation rate affects the rate of adaptive evolution on rugged fitness landscapes. We model an asexual population with two mutation rate phenotypes, non-mutator and mutator. An offspring may switch from its parental phenotype to the other phenotype. The rate of switching between the mutation rate phenotypes is allowed to span a range of values. Thus, the mutation rate can be interpreted as a genetically inherited trait when the switching rate is low, as an epigenetically inherited trait when the switching rate is intermediate, or as a randomly determined trait when the switching rate is high. We find that epigenetically inherited mutation rates result in the highest rates of adaptation on rugged fitness landscapes for most realistic parameter sets. This is because an intermediate switching rate can maintain the association between a mutator phenotype and pre-existing mutations, which facilitates the crossing of fitness valleys. Our results provide a rationale for the evolution of epigenetic inheritance of the mutation rate, suggesting that it could have been selected because it facilitates adaptive evolution.


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