Programming stress-induced altruistic death in engineered bacteria.

dc.contributor.author

Tanouchi, Yu

dc.contributor.author

Pai, Anand

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Buchler, Nicolas E

dc.contributor.author

You, Lingchong

dc.coverage.spatial

England

dc.date.accessioned

2015-01-08T18:09:36Z

dc.date.issued

2012

dc.description.abstract

Programmed death is often associated with a bacterial stress response. This behavior appears paradoxical, as it offers no benefit to the individual. This paradox can be explained if the death is 'altruistic': the killing of some cells can benefit the survivors through release of 'public goods'. However, the conditions where bacterial programmed death becomes advantageous have not been unambiguously demonstrated experimentally. Here, we determined such conditions by engineering tunable, stress-induced altruistic death in the bacterium Escherichia coli. Using a mathematical model, we predicted the existence of an optimal programmed death rate that maximizes population growth under stress. We further predicted that altruistic death could generate the 'Eagle effect', a counter-intuitive phenomenon where bacteria appear to grow better when treated with higher antibiotic concentrations. In support of these modeling insights, we experimentally demonstrated both the optimality in programmed death rate and the Eagle effect using our engineered system. Our findings fill a critical conceptual gap in the analysis of the evolution of bacterial programmed death, and have implications for a design of antibiotic treatment.

dc.identifier

http://www.ncbi.nlm.nih.gov/pubmed/23169002

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msb201257

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1744-4292

dc.identifier.uri

https://hdl.handle.net/10161/9352

dc.language

eng

dc.publisher

EMBO

dc.relation.ispartof

Mol Syst Biol

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10.1038/msb.2012.57

dc.subject

Apoptosis

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Escherichia coli

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Genetic Engineering

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Microbial Viability

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Models, Biological

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Reproducibility of Results

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Stress, Physiological

dc.title

Programming stress-induced altruistic death in engineered bacteria.

dc.type

Journal article

duke.contributor.orcid

Buchler, Nicolas E|0000-0003-3940-3432

pubs.author-url

http://www.ncbi.nlm.nih.gov/pubmed/23169002

pubs.begin-page

626

pubs.organisational-group

Basic Science Departments

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Biology

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Biomedical Engineering

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Duke

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Molecular Genetics and Microbiology

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Physics

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Pratt School of Engineering

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School of Medicine

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Trinity College of Arts & Sciences

pubs.publication-status

Published

pubs.volume

8

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