scholarly journals NEW MODEL SYSTEMS FOR EXPERIMENTAL EVOLUTION

Evolution ◽  
2013 ◽  
Vol 67 (7) ◽  
pp. 1847-1848 ◽  
Author(s):  
Sinéad Collins
Keyword(s):  
Experimental Evolution ◽  
Model Systems ◽  
New Model

Are we there yet? Tracking the development of new model systems

2008 ◽  
Vol 24 (7) ◽  
pp. 353-360 ◽  
Author(s):  
Arhat Abzhanov ◽  
Cassandra G. Extavour ◽  
Andrew Groover ◽  
Scott A. Hodges ◽  
Hopi E. Hoekstra ◽  
...  
Keyword(s):  
Model Systems ◽  
New Model

scholarly journals New model systems provide insights into Myc-induced transformation

Oncogene ◽  
2011 ◽  
Vol 30 (34) ◽  
pp. 3727-3734 ◽  
Author(s):  
A R Wasylishen ◽  
A Stojanova ◽  
S Oliveri ◽  
A C Rust ◽  
A D Schimmer ◽  
...  
Keyword(s):  
Model Systems ◽  
New Model

scholarly journals Escherichia coli has a Unique Transcriptional Program in Long-Term Stationary Phase

2020 ◽  
Author(s):  
Karin E. Kram ◽  
Autumn Henderson ◽  
Steven E. Finkel
Keyword(s):  
Escherichia Coli ◽  
Stationary Phase ◽  
Experimental Evolution ◽  
Model Systems ◽  
Natural Environments ◽  
Complex Environments ◽  
Transcriptional Program ◽  
Complex Environment ◽  
Stressful Environment

AbstractMicrobes live in complex and consistently changing environments, but it is difficult to replicate this in the laboratory. Escherichia coli has been used as a model organism in experimental evolution studies for years; specifically, we and others have used it to study evolution in complex environments by incubating the cells into long-term stationary phase (LTSP) in rich media. In LTSP, cells experience a variety of stresses and changing conditions. While we have hypothesized that this experimental system is more similar to natural environments than some other lab conditions, we do not yet know how cells respond to this environment biochemically or physiologically. In this study, we begin to unravel the cells’ responses to this environment by characterizing the transcriptome of cells during LTSP. We found that cells in LTSP have a unique transcriptional program, and that several genes are uniquely upregulated or downregulated in this phase. Further, we identified two genes, cspB and cspI, which are most highly expressed in LTSP, even though these genes are primarily known to respond to cold-shock. When competed with wild-type cells, these genes are also important for survival during LTSP. These data allow us to compare biochemical responses to multiple environments and identify useful model systems, identify gene products that may play a role in survival in this complex environment, and identify novel functions of proteins.ImportanceExperimental evolution studies have elucidated evolutionary processes, but usually in chemically well-defined and/or constant environments. Using complex environments is important to begin to understand how evolution may occur in natural environments, such as soils or within a host. However, characterizing the stresses cells experience in these complex environments can be challenging. One way to approach this is by determining how cells biochemically acclimate to heterogenous environments. In this study we begin to characterize physiological changes by analyzing the transcriptome of cells in a dynamic complex environment. By characterizing the transcriptional profile of cells in long-term stationary phase, a heterogenous and stressful environment, we can begin to understand how cells physiologically and biochemically react to the laboratory environment, and how this compares to more natural conditions.

Evolution, Microbes, and Changing Ocean Conditions

2020 ◽  
Vol 12 (1) ◽  
pp. 181-208 ◽  
Author(s):  
Sinéad Collins ◽  
Philip W. Boyd ◽  
Martina A. Doblin
Keyword(s):  
Experimental Evolution ◽  
Environmental Variability ◽  
Cumulative Effect ◽  
Model Systems ◽  
Environmental Drivers ◽  
Marine Microbes ◽  
Evolutionary Potential ◽  
Tolerance Limits ◽  
Different Types

Experimental evolution and the associated theory are underutilized in marine microbial studies; the two fields have developed largely in isolation. Here, we review evolutionary tools for addressing four key areas of ocean global change biology: linking plastic and evolutionary trait changes, the contribution of environmental variability to determining trait values, the role of multiple environmental drivers in trait change, and the fate of populations near their tolerance limits. Wherever possible, we highlight which data from marine studies could use evolutionary approaches and where marine model systems can advance our understanding of evolution. Finally, we discuss the emerging field of marine microbial experimental evolution. We propose a framework linking changes in environmental quality (defined as the cumulative effect on population growth rate) with population traits affecting evolutionary potential, in order to understand which evolutionary processes are likely to be most important across a range of locations for different types of marine microbes.

scholarly journals Comment on ''Effects of long-term high CO<sub>2</sub> exposure on two species of coccolithophore'' by Müller et al. (2010)

2010 ◽  
Vol 7 (7) ◽  
pp. 2199-2202 ◽  
Author(s):  
S. Collins
Keyword(s):  
Global Change ◽  
Experimental Evolution ◽  
Marine Phytoplankton ◽  
Model Systems ◽  
Price Equation ◽  
High Pco2 ◽  
Phenotypic Change ◽  
Marine Microbes ◽  
Marine Microbe

Abstract. Populations can respond to environmental change over tens or hundreds of generations by shifts in phenotype that can be the result of a sustained physiological response, evolutionary (genetic) change, shifts in community composition, or some combination of these factors. Microbes evolve on human timescales, and evolution may contribute to marine phytoplankton responses to global change over the coming decades. However, it is still unknown whether evolutionary responses are likely to contribute significantly to phenotypic change in marine microbial communities under high pCO2 regimes or other aspects of global change. Recent work by Müller et al. (2010) highlights that long-term responses of marine microbes to global change must be empirically measured and the underlying cause of changes in phenotype explained. Here, I briefly discuss how tools from experimental microbial evolution may be used to detect and measure evolutionary responses in marine phytoplankton grown in high CO2 environments and other environments of interest. I outline why the particular biology of marine microbes makes conventional experimental evolution challenging right now and make a case that marine microbes are good candidates for the development of new model systems in experimental evolution. I suggest that "black box" frameworks that focus on partitioning phenotypic change, such as the Price equation, may be useful in cases where direct measurements of evolutionary responses alone are difficult, and that such approaches could be used to test hypotheses about the underlying causes of phenotypic shifts in marine microbe communities responding to global change.

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