Research abstract

Article abstract


Nature Biotechnology 24, 1263 - 1269 (2006)
Published online: 24 September 2006 | doi:10.1038/nbt1247

Metagenomic analysis of two enhanced biological phosphorus removal (EBPR) sludge communities

Héctor García Martín1,5, Natalia Ivanova1,5, Victor Kunin1, Falk Warnecke1, Kerrie W Barry1, Alice C McHardy4, Christine Yeates2, Shaomei He3, Asaf A Salamov1, Ernest Szeto1, Eileen Dalin1, Nik H Putnam1, Harris J Shapiro1, Jasmyn L Pangilinan1, Isidore Rigoutsos4, Nikos C Kyrpides1, Linda Louise Blackall2, Katherine D McMahon3 & Philip Hugenholtz1


Enhanced biological phosphorus removal (EBPR) is one of the best-studied microbially mediated industrial processes because of its ecological and economic relevance. Despite this, it is not well understood at the metabolic level. Here we present a metagenomic analysis of two lab-scale EBPR sludges dominated by the uncultured bacterium, “Candidatus Accumulibacter phosphatis.” The analysis sheds light on several controversies in EBPR metabolic models and provides hypotheses explaining the dominance of A. phosphatis in this habitat, its lifestyle outside EBPR and probable cultivation requirements. Comparison of the same species from different EBPR sludges highlights recent evolutionary dynamics in the A. phosphatis genome that could be linked to mechanisms for environmental adaptation. In spite of an apparent lack of phylogenetic overlap in the flanking communities of the two sludges studied, common functional themes were found, at least one of them complementary to the inferred metabolism of the dominant organism. The present study provides a much needed blueprint for a systems-level understanding of EBPR and illustrates that metagenomics enables detailed, often novel, insights into even well-studied biological systems.

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  1. DOE Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, California 94598, USA.
  2. Advanced Wastewater Management Centre, University of Queensland, St. Lucia, 4072, Queensland, Australia.
  3. Civil and Environmental Engineering Department, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, Wisconsin 53706, USA.
  4. IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598, USA.
  5. These authors contributed equally to this work.

Correspondence to: Philip Hugenholtz1 e-mail: phugenholtz@lbl.gov