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Elicitation of High (p)ppGpp Levels in Streptococcus equisimilis without Imposing Nutritional Deprivation

  • Kerstin Steiner
  • Undine Mechold
  • Horst Malke
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 418)

Abstract

In Escherichia coli, the intracellular levels of guanosine polyphosphates [(p)ppGpp] rise following numerous environmental stresses and have wide-reaching effects on gene expression and, consequently, cellular physiology and metabolism1. To contribute to understanding how the pathogenic streptococci respond to environmental cues during the infectious process, we have analyzed the function of the rel Seq gene found in the streptokinase gene region of S. equisimilis H46A4. This strain accumulates (p)ppGpp during amino acid starvation and carbon source exhaustion, a response that is accompanied by the coupled cessation of net protein and RNA synthesis3. As judged by the relaxed response of insertion mutants, rel Seq determines (p)ppGpp accumulation during amino acid deprivation and can thus be operationally defined as encoding the stringent factor of S. equisimilis 3. However, unlike the relA gene of E. coli, rel Seq is bifunctional, encoding, like E. coli spoT, also a strong (p)ppGpp hydrolytic activity2. Literally nothing is known about the pleiotropic effects of the stringent response in the streptococci, which is particularly true of possible regulatory functions of (p)ppGpp in the expression control of virulence genes. To approach this problem, we describe here a plasmid that specifies elevated (p)ppGpp levels in S. equisimilis. Such a construct should circumvent the need of provoking the stringent response by transient nutrient starvation protocols, which may complicate interpretations of effects due solely to (p)ppGpp.

Keywords

Stringent Response Amino Acid Starvation Thin Layer Chromatogram Amino Acid Deprivation Formic Acid Extract 
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

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Kerstin Steiner
    • 1
  • Undine Mechold
    • 1
  • Horst Malke
    • 1
  1. 1.Institute for Molecular BiologyJena UniversityJenaGermany

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