Metabolic Variability in Micro-Populations

Biological cells in a population are variable in practically every property. Much is known about how variability of single cells is reflected in the statistical properties of infinitely large populations; however, many biologically relevant situations entail finite times and intermediate-sized popul...

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Vydané v:	PloS one Ročník 7; číslo 12; s. e52105
Hlavní autori:	Elhanati, Yuval, Brenner, Naama
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Public Library of Science 27.12.2012 Public Library of Science (PLoS)
Predmet:	Adaptation, Biological Biology Biotechnology Cell Physiological Phenomena Computer Simulation Humans Initial conditions Inoculum Metabolism Metabolites Microfluidics Microorganisms Models, Theoretical Nature Phenotype Population Population (statistical) Population Density Population Dynamics Population Growth Population number Probability theory Properties (attributes) Random variables Random walk Statistical analysis Statistics Stochastic models Stochastic processes Stochasticity Studies Theory Variability Israel
ISSN:	1932-6203, 1932-6203
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Popis
Shrnutí:	Biological cells in a population are variable in practically every property. Much is known about how variability of single cells is reflected in the statistical properties of infinitely large populations; however, many biologically relevant situations entail finite times and intermediate-sized populations. The statistical properties of an ensemble of finite populations then come into focus, raising questions concerning inter-population variability and dependence on initial conditions. Recent technologies of microfluidic and microdroplet-based population growth realize these situations and make them immediately relevant for experiments and biotechnological application. We here study the statistical properties, arising from metabolic variability of single cells, in an ensemble of micro-populations grown to saturation in a finite environment such as a micro-droplet. We develop a discrete stochastic model for this growth process, describing the possible histories as a random walk in a phenotypic space with an absorbing boundary. Using a mapping to Polya's Urn, a classic problem of probability theory, we find that distributions approach a limiting inoculum-dependent form after a large number of divisions. Thus, population size and structure are random variables whose mean, variance and in general their distribution can reflect initial conditions after many generations of growth. Implications of our results to experiments and to biotechnology are discussed.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Conceived and designed the experiments: NB YE. Performed the experiments: NB YE. Wrote the paper: YE NB. Competing Interests: The authors have declared that no competing interests exist.
ISSN:	1932-6203 1932-6203
DOI:	10.1371/journal.pone.0052105