Microbial ecology is currently undergoing a revolution, with repercussions spreading throughout microbiology, ecology and ecosystem science. The rapid accumulation of molecular data is uncovering vast diversity, abundant uncultivated microbial groups and novel microbial functions. This accumulation of data requires the application of theory to provide organization, structure, mechanistic insight and, ultimately, predictive power that is of practical value, but the application of theory in microbial ecology is currently very limited. Here we argue that the full potential of the ongoing revolution will not be realized if research is not directed and driven by theory, and that the generality of established ecological theory must be tested using microbial systems.

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.

The power law that describes the relationship between species richness and area size is one of the few generalizations in ecology, but recent studies show that this relationship differs for microbes. We demonstrate that the natural bacterial communities inhabiting small aquatic islands (treeholes) do indeed follow the species-area law. The result requires a re-evaluation of the current understanding of how natural microbial communities operate and implies that analogous processes structure both microbial communities and communities of larger organisms.

SummaryDespite its long-term use in bioremediation, bioaugmentation of contaminated sites with microbial cells continues to be a source of controversy within environmental microbiology. This largely results from its notoriously unreliable performance record. In this article, we argue that the unpredictable nature of the approach comes from the initial strain selection step. Up until now, this has been dictated by the search for catabolically competent microorganisms, with little or no consideration given to other essential features that are required to be functionally active and persistent in target habitats. We describe how technical advances in molecular biology and analytical chemistry, now enable assessments of the functional diversity and spatial distribution of microbial communities to be made in situ. These advances now enable microbial populations, targeted for exploitation, to be differentiated to the cell level, an advance that is bound to improve microbial selection and exploitation. We argue that this information-based approach is already proving to be more effective than the traditional 'black-box' approach of strain selection. The future perspectives and opportunities for improving selection of effective microbial strains for bioaugmentation are also discussed.