The Molecular Genetics of Plasmid Partition: Special Vector Systems for the Analysis of Plasmid Partition

  • Ann L. Abeles
  • Stuart J. Austin
Part of the Genetic Engineering book series (GEPM, volume 11)

Abstract

Plasmids are autonomously replicating elements that are dispensable for cell viability and are therefore vulnerable to loss from the growing cells. However, naturally occurring plasmids are very stably maintained in populations of the host bacteria. Thus, the individual copies must be distributed within the dividing cell in such a way as to ensure that each daughter cell receives at least one copy. This can be termed plasmid partition. A simple way of achieving this would result if the plasmids were maintained at a very high copy number in a form where the individual copies were free to diffuse in the cytoplasm. Distribution of copies to daughter cells would then be random, but the probability of losing the plasmid entirely would be low. It is possible that some bacterial plasmids do rely on this simple method for their inheritance. However, the naturally occurring plasmids that have been studied so far show evidence of specific strategies to aid their distribution. Efficient site-specific recombination systems have been described that resolve the multimeric plasmids that can accumulate in the population, thus maximizing the pool of plasmids available for distribution (1, 2). Other mechanisms can kill a large proportion of those cells that lose the plasmid (3–8). These systems appear to work by a “poison and antidote” principle; the plasmid produces both a toxic agent and a product that inactivates it. Should the plasmid be lost due to an error in replication or partition, the inactivating material decays or is diluted and the toxic material persists and kills the cell (3, 7, 9).

Keywords

Partition System Partition Region Partition Locus polA Strain Partition Sequence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Plenum Press, New York 1989

Authors and Affiliations

  • Ann L. Abeles
    • 1
  • Stuart J. Austin
    • 1
  1. 1.Frederick Cancer Research FacilityFrederickUSA

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