Biology subjects

Sutirth Dey

Publications and source records attributed to Sutirth Dey.

9 recordsLinked to original sources

bioRxiv2016

Larger Numbers can Impede Adaptation in Microbial Populations despite Entailing Greater Genetic Variation

Periodic bottlenecks play a major role in shaping the adaptive dynamics of natural and laboratory populations of asexual microbes. Here we study how they affect the Extent of Adaptation (EoA), in such populations. EoA, the average fitness gain relative to the ancestor, is the quantity of interest in a large number of microbial experimental-evolution studies which assume that for any given bottleneck size (N0) and number of generations between bottlenecks (g), the harmonic mean size (HM=N0g) will predict the ensuing evolutionary dynamics. However, there are no theoretical or empirical validations for HM being a good predictor of EoA. Using experimental-evolution with Escherichia coli and individual-based simulations, we show that HM fails to predict EoA (i.e., higher N0g does not lead to higher EoA). This is because although higher g allows populations to arrive at superior benefits by entailing increased variation, it also reduces the efficacy of selection, which lowers EoA. We show that EoA can be maximized in evolution experiments by either maximizing N0 and/or minimizing g. We also conjecture that N0/g is a better predictor of EoA than N0g. Our results call for a re-evaluation of the role of population size in predicting fitness trajectories. They also aid in predicting adaptation in asexual populations, which has important evolutionary, epidemiological and economic implications.

Evolutionary Biology↗

bioRxiv2016

Escherichia coli populations adapt to complex, unpredictable fluctuations by minimizing trade-offs across environments

In nature, organisms are simultaneously exposed to multiple stresses (i.e. complex environments) that often fluctuate unpredictably. While both these factors have been studied in isolation, the interaction of the two remains poorly explored. To address this issue, we selected laboratory populations of Escherichia coli under complex (i.e. stressful combinations of pH, H2O2 and NaCl) unpredictably fluctuating environments for ~900 generations. We compared the growth rates and the corresponding trade-off patterns of these populations to those that were selected under constant values of the component stresses (i.e. pH, H2O2 and NaCl) for the same duration. The fluctuation-selected populations had greater mean growth rate and lower variation for growth rate over all the selection environments experienced. However, while the populations selected under constant stresses experienced trade-offs in the environments other than those in which they were selected, the fluctuation-selected populations could by-pass the across-environment trade-offs almost entirely. Interestingly, trade-offs were found between growth rates and carrying capacities. The results suggest that complexity and fluctuations can strongly affect the underlying trade-off structure in evolving populations.

Evolutionary Biology↗

bioRxiv2016

Escherichia coli populations adapt to complex, unpredictable fluctuations without any trade-offs across environments

In nature, organisms are simultaneously exposed to multiple stresses (i.e. complex environments) that often fluctuate unpredictably. While both these factors have been studied in isolation, the interaction of the two remains poorly explored. To address this issue, we selected laboratory populations of Escherichia coli under complex (i.e. stressful combinations of pH, H2O2 and NaCl) unpredictably fluctuating environments for ~900 generations. We compared the growth rates and the corresponding trade-off patterns of these populations to those that were selected under constant values of the component stresses (i.e. pH, H2O2 and NaCl) for the same duration. The fluctuation-selected populations had greater mean growth rate and lower variation for growth rate over all the selection environments experienced. However, while the populations selected under constant stresses experienced severe tradeoffs in many of the environments other than those in which they were selected, the fluctuation-selected populations could by-pass the across-environment trade-offs completely. Interestingly, trade-offs were found between growth rates and carrying capacities. The results suggest that complexity and fluctuations can strongly affect the underlying trade-off structure in evolving populations.

Evolutionary Biology↗

bioRxiv2016

Selection for dispersal leads to evolution of kernel and increased locomotor activity in Drosophila melanogaster

Global climate is changing rapidly and is accompanied by large-scale fragmentation and destruction of habitats. Since dispersal is the first line of defense for mobile organisms to cope with such adversities in their environment, it is important to understand the causes and consequences of evolution of dispersal. Although dispersal is a complex phenomenon involving multiple dispersal-traits like propensity (tendency to leave the natal patch) and ability (to travel long distances), the relationship between these traits is not always straight-forward, it is not clear whether these traits can evolve simultaneously or not, and how their interactions affect the overall dispersal profile. To investigate these issues, we subjected four large (N[~]2500) outbred populations of Drosophila melanogaster to artificial selection for increased dispersal, in a setup that mimicked increasing habitat fragmentation over 33 generations. The propensity and ability of the selected populations were significantly greater than the non-selected controls and the difference persisted even in the absence of proximate drivers for dispersal. The dispersal kernel evolved to have significantly greater standard deviation and reduced values of skew and kurtosis, which ultimately translated into the evolution of a greater frequency of long-distance dispersers (LDDs). We also found that although sex-biased dispersal exists in Drosophila melanogaster, its expression can vary depending on which dispersal component is being measured and the environmental condition under which dispersal takes place. Interestingly though, there was no difference between the two sexes in terms of dispersal evolution. We discuss possible reasons for why some of our results do not agree with previous laboratory and field studies. The rapid evolution of multiple components of dispersal and the kernel, expressed even in the absence of stress, indicates that dispersal evolution cannot be ignored while investigating eco-evolutionary phenomena like speed of range expansion, disease spread, evolution of invasive species and destabilization of metapopulation dynamics.\n\nData AccessibilityData will be deposited to dryad if accepted.

Ecology↗

bioRxiv2015

Simultaneous enhancement of multiple stability properties using two-parameter control methods in Drosophila melanogaster

AbstractAlthough a large number of methods have been proposed to control the non-linear dynamics of unstable popuations, very few have been actually adopted for application. One reason for this gap is the fact that few control methods have been empirically verified using biological populations. To address this issue, we investigated the effects of two well-studied control methods (Both Limiter Control and Target-Oriented Control) on the dynamics of unstable populations of Drosophila melanogaster. We show that both methods can significantly reduce population fluctuations, decrease extinction probability and increase effective population size simultaneously. This is in contrast with single parameter control methods that are not able to achieve multiple aspects of stability at the same time. We use the distribution of population sizes to derive biologically intuitive explanations for the mechanisms of how these two control methods attain stability. Finally, we show that non-Drosophila specific biologically realistic simulations are able to capture almost all the trends of our data. This shows that our results are likely generalizable over a wide range of taxa. The primary insight of our study is that control methods that incorporate both culling and restocking have better all-round performance in terms of stabilizing populations.

Ecology↗

bioRxiv2015

Stabilizing the dynamics of laboratory populations of Drosophila melanogaster through upper and lower limiter controls

Although a large number of methods exist to control the dynamics of populations to a desired state, few of them have been empirically validated. This limits the scope of using these methods in real-life scenarios. To address this issue, we tested the efficacy of two well-known control methods in enhancing different kinds of stability in highly fluctuating, extinction-prone populations of Drosophila melanogaster. The Upper Limiter Control (ULC) method was able to reduce the fluctuations in population sizes as well as the extinction probability of the populations. On the negative side, it had no effect on the effective population size and required a large amount of effort. On the other hand, Lower Limiter Control (LLC) enhanced effective population size and reduced extinction probability at a relatively low amount of effort. However, its effects on population fluctuations were equivocal. We examined the population size distributions with and without the control methods, to derive biologically intuitive explanations for how these control methods work. We also show that biologically-realistic simulations, using a very general population dynamics model, are able to capture most of the trends of our data. This suggests that our results are likely to be generalizable to a wide range of scenarios.

Ecology↗

bioRxiv2015

Environmental fluctuations do not select for increased variation or population-based resistance in Escherichia coli

Little is known about the mechanisms that enable organisms to cope with unpredictable environments. To address this issue, we used replicate populations of Escherichia coli selected under complex, randomly changing environments. Under four novel stresses that had no known correlation with the selection environments, individual cells of the selected populations had significantly lower lag and greater yield compared to the controls. More importantly, there were no outliers in terms of growth, thus ruling out the evolution of population-based resistance. We also assayed the standing phenotypic variation of the selected populations, in terms of their growth on 94 different substrates. Contrary to expectations, there was no increase in the standing variation of the selected populations, nor was there any significant divergence from the ancestors. This suggested that the greater fitness in novel environments is brought about by selection at the level of the individuals, which restricts the suite of traits that can potentially evolve through this mechanism. Given that day-to-day climatic variability of the world is rising, these results have potential public health implications. Our results also underline the need for a very different kind of theoretical approach to study the effects of fluctuating environments.

Evolutionary Biology↗

bioRxiv2015

Rethinking inheritance, yet again: inheritomes, contextomes and dynamic phenotypes

In recent years, there have been many calls for an extended evolutionary synthesis, based in part upon growing evidence for non-genetic mechanisms of inheritance, i.e., similarities in phenotype between parents and offspring that are not due to shared genes. While there has been an impressive marshalling of evidence for diverse forms of non-genetic inheritance (epigenetic, ecological, behavioural, symbolic), there have been relatively few studies trying to integrate the different forms of inheritance into a common conceptual structure, a development that would be important to formalizing elements of the extended evolutionary synthesis. Here, we propose a framework for an extended view of inheritance and introduce some conceptual distinctions that we believe are important to this issue. In this framework, the phenotype is conceived of as a dynamic entity, its state at any point in time resulting from intertwined effects of previous phenotypic state, and of hereditary materials (DNA and otherwise) and environment. We contrast our framework with the standard gene-based view of inheritance, and also discuss our framework in the specific context of recent attempts to accommodate non-genetic inheritance within the framework of classical quantitative genetics and the Price equation. In particular, we believe that the extended view of inheritance and effects on the phenotype developed here is particularly well-suited to individual-based simulation studies of evolutionary dynamics. The results of such simulations, in turn, could be useful for assessing how well extended models based on quantitative genetics or the Price equation perform at capturing complex evolutionary dynamics.

Evolutionary Biology↗

bioRxiv2014

E. coli populations in unpredictably fluctuating environments evolve to face novel stresses through enhanced efflux activity

There is considerable understanding about how laboratory populations respond to predictable (constant or deteriorating-environment) selection for single environmental variables like temperature or pH. However, such insights may not apply when selection environments comprise multiple variables that fluctuate unpredictably, as is common in nature. To address this issue, we grew replicate laboratory populations of E. coli in nutrient broth whose pH and concentrations of salt (NaCl) and hydrogen peroxide (H2O2) were randomly changed daily. After [~]170 generations, the fitness of the selected populations had not increased in any of the three selection environments. However, these selected populations had significantly greater fitness in four novel environments which have no known fitness-correlation with tolerance to pH, NaCl or H2O2. Interestingly, contrary to expectations, hypermutators did not evolve. Instead, the selected populations evolved an increased ability for energy dependent efflux activity that might enable them to throw out toxins, including antibiotics, from the cell at a faster rate. This provides an alternate mechanism for how evolvability can evolve in bacteria and potentially lead to broad spectrum antibiotic resistance, even in the absence of prior antibiotic exposure. Given that environmental variability is increasing in nature, this might have serious consequences for public-health.

Evolutionary Biology↗