Approaches to analyse dynamic microbial communities such as those seen in cystic fibrosis lung

Abstract

Microbial communities play vital roles in many aspects of our lives, although our understanding of microbial biogeography and community profiles remains unclear. The number of microbes or the diversity of the microbes, even in small environmental niches, is staggering. Current microbiological methods used to analyse these communities are limited, in that many microorganisms cannot be cultured. Even for the isolates that can be cultured, the expense of identifying them definitively is much too high to be practical. Many recent molecular technologies, combined with bioinformatic tools, are raising the bar by improving the sensitivity and reliability of microbial community analysis. These tools and techniques range from those that attempt to understand a microbial community from their length heterogeneity profiles to those that help to identify the strains and species of a random sampling of the microbes in a given sample. These technologies are reviewed here, using the microbial communities present in the lungs of cystic fibrosis patients as a paradigm.

Figure 1

Schematic representation of the variable and conserved regions of the I6S rRNA genes, using Escherichia coli rrsA (ECDHI0B_4040) as a reference. The diagram illustrates the approximate positions of nine variable (V) regions that are interspersed with conserved regions. LH-PCR primer sequences for the conserved regions are included. The 8 F, 112 F/R, 338 F/R, 518 F/R and 785 F/R primers have also been referred to as 27 IF P2, 355 F/R, 536 F/R and 802 F/R, respectively. F and R refer to forward and reverse, respectively. The degenerate nucleotides M, R, S, Wand Y stand for A/C, A/G, G/C, A/T and C/T, respectively.

Figure 2

A sample amplicon length heterogeneity electropherogram using primers 8F and 338R. The x-axis represents amplicon length in base pairs, and relative abundance (proportional to intensity) is represented on the y-axis.