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A quantitative test of population genetics using spatiogenetic patterns in bacterial colonies.

ABSTRACT: It is widely accepted that population-genetics theory is the cornerstone of evolutionary analyses. Empirical tests of the theory, however, are challenging because of the complex relationships between space, dispersal, and evolution. Critically, we lack quantitative validation of the spatial models of population genetics. Here we combine analytics, on- and off-lattice simulations, and experiments with bacteria to perform quantitative tests of the theory. We study two bacterial species, the gut microbe Escherichia coli and the opportunistic pathogen Pseudomonas aeruginosa, and show that spatiogenetic patterns in colony biofilms of both species are accurately described by an extension of the one-dimensional stepping-stone model. We use one empirical measure, genetic diversity at the colony periphery, to parameterize our models and show that we can then accurately predict another key variable: the degree of short-range cell migration along an edge. Moreover, the model allows us to estimate other key parameters, including effective population size (density) at the expansion frontier. While our experimental system is a simplification of natural microbial community, we argue that it constitutes proof of principle that the spatial models of population genetics can quantitatively capture organismal evolution.

SUBMITTER: Korolev KS

PROVIDER: S-EPMC3385003 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature

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A quantitative test of population genetics using spatiogenetic patterns in bacterial colonies.

Korolev Kirill S KS Xavier João B JB Nelson David R DR Foster Kevin R KR

The American naturalist 20110819 4

It is widely accepted that population-genetics theory is the cornerstone of evolutionary analyses. Empirical tests of the theory, however, are challenging because of the complex relationships between space, dispersal, and evolution. Critically, we lack quantitative validation of the spatial models of population genetics. Here we combine analytics, on- and off-lattice simulations, and experiments with bacteria to perform quantitative tests of the theory. We study two bacterial species, the gut mi ...[more]

PMID: 21956031

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Project description:1. There is a growing number of empirical reports of environmental change simultaneously influencing population dynamics, life history and quantitative characters. We do not have a well-developed understanding of links between the dynamics of these quantities. 2. Insight into the joint dynamics of populations, quantitative characters and life history can be gained by deriving a model that allows the calculation of fundamental quantities that underpin population ecology, evolutionary biology and life history. The parameterization and analysis of such a model for a specific system can be used to predict how a population will respond to environmental change. 3. Age-stage-structured models can be constructed from character-demography associations that describe age-specific relationships between the character and: (i) survival; (ii) fertility; (iii) ontogenetic development of the character among survivors; and (iv) the distribution of reproductive allocation. 4. These models can be used to calculate a wide range of useful biological quantities including population growth and structure; terms in the Price equation including selection differentials; estimates of biometric heritabilities; and life history descriptors including generation time. We showcase the method through parameterization of a model using data from a well-studied population of Soay sheep Ovis aries. 5. Perturbation analysis is used to investigate how the quantities listed in summary point 4 change as each parameter in each character-demography function is altered. 6. A wide range of joint dynamics of life history, quantitative characters and population growth can be generated in response to changes in different character-demography associations; we argue this explains the diversity of observations on the consequences of environmental change from studies of free-living populations. 7. The approach we describe has the potential to explain within and between species patterns in quantitative characters, life history and population dynamics.

Project description:BACKGROUND:Currently the combination of molecular tools, imaging techniques and analysis software offer the possibility of studying gene activity through the use of fluorescent reporters and infer its distribution within complex biological three-dimensional structures. For example, the use of Confocal Scanning Laser Microscopy (CSLM) is a regularly-used approach to visually inspect the spatial distribution of a fluorescent signal. Although a plethora of generalist imaging software is available to analyze experimental pictures, the development of tailor-made software for every specific problem is still the most straightforward approach to perform the best possible image analysis. In this manuscript, we focused on developing a simple methodology to satisfy one particular need: automated processing and analysis of CSLM image stacks to generate 3D fluorescence profiles showing the average distribution detected in bacterial colonies grown in different experimental conditions for comparison purposes. RESULTS:The presented method processes batches of CSLM stacks containing three-dimensional images of an arbitrary number of colonies. Quasi-circular colonies are identified, filtered and projected onto a normalized orthogonal coordinate system, where a numerical interpolation is performed to obtain fluorescence values within a spatially fixed grid. A statistically representative three-dimensional fluorescent pattern is then generated from this data, allowing for standardized fluorescence analysis regardless of variability in colony size. The proposed methodology was evaluated by analyzing fluorescence from GFP expression subject to regulation by a stress-inducible promoter. CONCLUSIONS:This method provides a statistically reliable spatial distribution profile of fluorescence detected in analyzed samples, helping the researcher to establish general correlations between gene expression and spatial allocation under differential experimental regimes. The described methodology was coded into a MATLAB script and shared under an open source license to make it accessible to the whole community.

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A quantitative test of population genetics using spatiogenetic patterns in bacterial colonies.

Publications

A quantitative test of population genetics using spatiogenetic patterns in bacterial colonies.

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