Microbial Ecology

, Volume 49, Issue 1, pp 63–72 | Cite as

Frequency and Diversity of Nitrate Reductase Genes among Nitrate-Dissimilating Pseudomonas in the Rhizosphere of Perennial Grasses Grown in Field Conditions

  • L. Roussel-Delif
  • S. Tarnawski
  • J. Hamelin
  • L. Philippot
  • M. Aragno
  • N. FrominEmail author


A total of 1246 Pseudomonas strains were isolated from the rhizosphere of two perennial grasses (Lolium perenne and Molinia coerulea) with different nitrogen requirements. The plants were grown in their native soil under ambient and elevated atmospheric CO2 content (pCO2) at the Swiss FACE (Free Air CO2 Enrichment) facility. Root-, rhizosphere-, and non-rhizospheric soil–associated strains were characterized in terms of their ability to reduce nitrate during an in vitro assay and with respect to the genes encoding the membrane-bound (named NAR) and periplasmic (NAP) nitrate reductases so far described in the genus Pseudomonas. The diversity of corresponding genes was assessed by PCR-RFLP on narG and napA genes, which encode the catalytic subunit of nitrate reductases. The frequency of nitrate-dissimilating strains decreased with root proximity for both plants and was enhanced under elevated pCO2 in the rhizosphere of L. perenne. NAR (54% of strains) as well as NAP (49%) forms were present in nitrate-reducing strains, 15.5% of the 439 strains tested harbouring both genes. The relative proportions of narG and napA detected in Pseudomonas strains were different according to root proximity and for both pCO2 treatments: the NAR form was more abundant close to the root surface and for plants grown under elevated pCO2. Putative denitrifiers harbored mainly the membrane-bound (NAR) form of nitrate reductase. Finally, both narG and napA sequences displayed a high level of diversity. Anyway, this diversity was correlated neither with the root proximity nor with the pCO2 treatment.


Denitrification Nitrate Reductase Perennial Grass Nitrate Reducer napA 
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.



This work was supported by the Swiss National Science Foundation (grant numbers 3100-055899.98 and 31-68208.02). We are also grateful to the Swiss National Centre of Competence in Research (NCCR) “Plant Survival.” We thank Marie-Laure Heusler for technical assistance, Jakob Zopfi and Raymond Flynn for English corrections, and Jacqueline Moret for statistical analysis.


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Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • L. Roussel-Delif
    • 1
  • S. Tarnawski
    • 1
  • J. Hamelin
    • 1
  • L. Philippot
    • 2
  • M. Aragno
    • 1
  • N. Fromin
    • 1
    Email author
  1. 1.Laboratoire de MicrobiologieUniversité de NeuchâtelNeuchâtelSwitzerland
  2. 2.UMRA111, Microbiologie des Sols-Géosols, Laboratoire de Microbiologie des SolsInstitut National de la Recherche AgronomiqueDijon CedexFrance

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