Summary: Naturally occurring populations of bacteria and archaea are vital to life on the earth and are of enormous practical significance in medicine, engineering and agriculture. However, the rules governing the formation of such communities are still poorly understood, and there is a need for a usable mathematical description of this process. Typically, microbial community structure is thought to be shaped mainly by deterministic factors such as competition and niche differentiation. Here we show, for a wide range of prokaryotic communities, that the relative abundance and frequency with which different taxa are observed in samples can be explained by a neutral community model (NCM). The NCM, which is a stochastic, birth–death immigration process, does not explicitly represent the deterministic factors and therefore cannot be a complete or literal description of community assembly. However, its success suggests that chance and immigration are important forces in shaping the patterns seen in prokaryotic communities.

Two recent, independent advances in ecology have generated interest and controversy: the development of neutral community models (NCMs) and the exten

Chronic rhinosinusitis (CRS) is an inflammatory condition that affects up to 12% of the human population in developed countries. Previous studies examining the potential role of the sinus bacterial microbiota within CRS infections have found inconsistent results, possibly because of inconsistencies in sampling strategies. The aim of this study was to determine whether the sinus microbiome is altered in CRS and additionally if the middle meatus is a suitable representative site for sampling the sinus microbiome. Swab samples were collected from 12 healthy controls and 21 CRS patients, including all eight sinuses for CRS patients and between one and five sinuses for control subjects. The left and right middle meatus and nostril swabs were also collected. Significant differences in the sinus microbiomes between CRS and control samples were revealed using high-throughput 16S rRNA gene sequencing. The genus Escherichia was over-represented in CRS sinuses, and associations between control patients and Corynebacterium and Dolosigranulum were also identified. Comparisons of the middle meatuses between groups did not reflect these differences, and the abundance of the genus Escherichia was significantly lower at this location. Additionally, intra-patient variation was lower between sinuses than between sinus and middle meatus, which together with the above results suggests that the middle meatus is not an effective representative sampling site.

The extent of microbial diversity is an intrinsically fascinating subject of profound practical importance. The term ‘diversity’ may allude to the number of taxa or species richness as well as their relative abundance. There is uncertainty about both, primarily because sample sizes are too small. Non-parametric diversity estimators make gross underestimates if used with small sample sizes on unevenly distributed communities. One can make richness estimates over many scales using small samples by assuming a species/taxa-abundance distribution. However, no one knows what the underlying taxa-abundance distributions are for bacterial communities. Latterly, diversity has been estimated by fitting data from gene clone libraries and extrapolating from this to taxa-abundance curves to estimate richness. However, since sample sizes are small, we cannot be sure that such samples are representative of the community from which they were drawn. It is however possible to formulate, and calibrate, models that predict the diversity of local communities and of samples drawn from that local community. The calibration of such models suggests that migration rates are small and decrease as the community gets larger. The preliminary predictions of the model are qualitatively consistent with the patterns seen in clone libraries in ‘real life’. The validation of this model is also confounded by small sample sizes. However, if such models were properly validated, they could form invaluable tools for the prediction of microbial diversity and a basis for the systematic exploration of microbial diversity on the planet.