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ISME J. 2011 May;5(5):780-91. doi: 10.1038/ismej.2010.175. Epub 2010 Dec 9.

Partitioning core and satellite taxa from within cystic fibrosis lung bacterial communities.

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1
NERC Centre for Ecology and Hydrology, Wallingford, UK. cjvdg@ceh.ac.uk

Abstract

Cystic fibrosis (CF) patients suffer from chronic bacterial lung infections that lead to death in the majority of cases. The need to maintain lung function in these patients means that characterising these infections is vital. Increasingly, culture-independent analyses are expanding the number of bacterial species associated with CF respiratory samples; however, the potential significance of these species is not known. Here, we applied ecological statistical tools to such culture-independent data, in a novel manner, to partition taxa within the metacommunity into core and satellite species. Sputa and clinical data were obtained from 14 clinically stable adult CF patients. Fourteen rRNA gene libraries were constructed with 35 genera and 82 taxa, identified in 2139 bacterial clones. Shannon-Wiener and taxa-richness analyses confirmed no undersampling of bacterial diversity. By decomposing the distribution using the ratio of variance to the mean taxon abundance, we partitioned objectively the species abundance distribution into core and satellite species. The satellite group comprised 67 bacterial taxa from 33 genera and the core group, 15 taxa from 7 genera (including Pseudomonas (1 taxon), Streptococcus (2), Neisseria (2), Catonella (1), Porphyromonas (1), Prevotella (5) and Veillonella (3)], the last four being anaerobes). The core group was dominated by Pseudomonas aeruginosa. Other recognised CF pathogens were rare. Mantel and partial Mantel tests assessed which clinical factors influenced the composition observed. CF transmembrane conductance regulator genotype and antibiotic treatment correlated with all core taxa. Lung function correlated with richness. The clinical significance of these core and satellite species findings in the CF lung is discussed. GenBank accession numbers: FM995625–FM997761.

PMID:
21151003
PMCID:
PMC3105771
DOI:
10.1038/ismej.2010.175
[Indexed for MEDLINE]
Free PMC Article

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