Observing Growth and Division of Large Numbers of Individual Bacteria by Image Analysis

Elfwing, Anders; Marc, Yvan Le; Baranyi, József; Ballagi, Andras

doi:10.1128/aem.70.2.675-678.2004

Cited by 136 publications

(108 citation statements)

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“…For example, early observations of isolated cells under a light microscope demonstrated a unimodal distribution of fission times (Powell 1958). More recently, the development of microfluidic devices has allowed for detailed single-cell observations of bacterial fission on an unprecedented scale (Elfwing et al 2004;Wakamoto et al 2005;Siegal-Gaskins and Crosson 2008), demonstrating that fission times within the first few generations of a lineage remain correlated, with a CV of 30%.Finally, bacterial populations in batch culture have become perhaps the most influential model system for the study of adaptation (Kawecki et al 2012;Kussell 2012;Barrick and Lenski 2013), and growth in batch culture is characterized by its own "life-history" traits. In particular, growth begins only after a well-documented delay, the lag phase, and continues until the population density is high and resources are depleted; when resources are sufficiently low, cell replication ceases and the relatively quiescent stationary phase begins.…”

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Survival Probability of Beneficial Mutations in Bacterial Batch Culture

Wahl

Zhu²

2015

Genetics

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The survival of rare beneficial mutations can be extremely sensitive to the organism's life history and the trait affected by the mutation. Given the tremendous impact of bacteria in batch culture as a model system for the study of adaptation, it is important to understand the survival probability of beneficial mutations in these populations. Here we develop a life-history model for bacterial populations in batch culture and predict the survival of mutations that increase fitness through their effects on specific traits: lag time, fission time, viability, and the timing of stationary phase. We find that if beneficial mutations are present in the founding population at the beginning of culture growth, mutations that reduce the mortality of daughter cells are the most likely to survive drift. In contrast, of mutations that occur de novo during growth, those that delay the onset of stationary phase are the most likely to survive. Our model predicts that approximately fivefold population growth between bottlenecks will optimize the occurrence and survival of beneficial mutations of all four types. This prediction is relatively insensitive to other model parameters, such as the lag time, fission time, or mortality rate of the population. We further estimate that bottlenecks that are more severe than this optimal prediction substantially reduce the occurrence and survival of adaptive mutations.KEYWORDS fixation probability; serial passaging; adaptation; experimental evolution; life history I T is well understood that most de novo mutations, even if they confer a substantial fitness advantage to the organism, do not survive the vicissitudes of genetic drift when initially rare (Fisher 1922;Haldane 1927;Wright 1929;Kimura 1964). The influences of population size, population structure, and environmental fluctuations on the fate of beneficial mutations have all been well studied, including cyclic (Otto and Whitlock 1997;Pollak 2000) or dynamically changing population sizes (Lambert 2006; Parsons and Quince 2007a,b), population subdivision (Barton 1993;Cherry 2003;Whitlock 2003) and migration (Lundy and Possingham 1998;Shpak and Proulx 2007), fluctuating selection (Haccou and Iwasa 1996;Lande 2007), or several of these factors in combination (Uecker and Hermisson 2011;Waxman 2011).A phenomenon that is perhaps less well appreciated is the sensitivity of a beneficial mutation's fate-survival or extinction-to the details of the organism's life history and the trait affected by the mutation. Studies of the extinction process in a population of changing size have demonstrated that extinction probabilities sensitively depend on whether mutations increase birth rates or reduce death rates (Parsons and Quince 2007a,b) or if mutations affect other life-history traits (Lambert 2006). Previous work has also compared the fate of mutations that reduce generation times with those that increase offspring survival (Wahl and Dehaan 2004). From these studies a clear picture is emerging: beneficial mutations that confer the same ...

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Survival Probability of Beneficial Mutations in Bacterial Batch Culture

Wahl

Zhu²

2015

Genetics

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“…Scenarios II and III should model the experimental data more closely than Scenario I because Equations (1) and (2) [4], because this variability seems to be randomly distributed [24]. Recalculating the lag phases of samples more likely to contain more than one cell is easily accomplished by substituting N 0 or X initial in Equations (1) and (2), respectively, by the number of cells predicted by the Poisson function.…”

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confidence: 99%

“…Therefore, it is understandable that researchers [1][2][3][4][5][6][7][8][9] have paid attention to the distribution of single cells lag times and to the techniques that can measure them. Measuring the lag time of individual cells requires direct microscopic observation [4,8] or techniques to isolate single cells [10]. Cell isolation can be achieved by diluting [2], sorting by flow cytometry [11] or inactivating all organisms except one [9].…”

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The Poisson Distribution Is Applied to Improve the Estimation of Individual Cell and Micropopulation Lag Phases

Aguirre¹,

Bravo²,

Ordóñez³

et al. 2012

AiM

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Many articles dealing with individual cell lag phase determination assume that growth, when observed, comes from one cell. This assumption is not in agreement with the Poisson distribution, which uses the probability of growth in a sample to predict how many samples contain one, two, or some other number of cells. This article analyses and compares different approaches to improve the accuracy of lag phase estimation of individual cells and micropopulations. It argues that if the highest initial load, as predicted by the Poisson distribution, is assigned to the sample with the shortest lag phase, the second highest to the sample with the second shortest lag phase and so on, the resulting lag phase distributions would be more accurate. This study also proposes the use of a robust test, permutation test, to compare lag phase distributions obtained in different situations.

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“…Reported notification rates of zoonoses in confirmed human cases in the EU, 2013. EFSA European summary report (42).…”

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Improvement of methods for the detection of Gram-negative foodborne pathogens

Margot¹

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Observing Growth and Division of Large Numbers of Individual Bacteria by Image Analysis

Cited by 136 publications

References 13 publications

Survival Probability of Beneficial Mutations in Bacterial Batch Culture

Survival Probability of Beneficial Mutations in Bacterial Batch Culture

The Poisson Distribution Is Applied to Improve the Estimation of Individual Cell and Micropopulation Lag Phases

Improvement of methods for the detection of Gram-negative foodborne pathogens

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