Resolution of natural microbial community dynamics by community fingerprinting, flow cytometry, and trend interpretation analysis.

Natural microbial communities generally have an unknown structure and composition because of their still not yet cultivable members. Therefore, understanding the relationships among the bacterial members, prediction of their behaviour, and controlling their functions are difficult and often only partly successful endeavours to date. This study aims to test a new idea that allows to follow community dynamics on the basis of a simple concept. Terminal restriction fragment length polymorphism (T-RFLP) analysis of bacterial 16S ribosomal RNA genes was used to describe a community profile that we define as composition of a community. Flow cytometry and analysis of DNA contents and forward scatter characteristics of the single cells were used to describe a community profile, which we define as structure of a community. Both approaches were brought together by a non-metric multidimensional scaling (n-MDS) for trend interpretation of changes in the complex community data sets. This was done on the basis of a graphical evaluation of the cytometric data, leading to the newly developed Dalmatian plot tool, which gave an unexpected insight into the dynamics of the unknown bacterial members of the investigated natural microbial community. The approach presented here was compared with other techniques described in the literature. The microbial community investigated in this study was obtained from a BTEX contaminated anoxic aquifer. The indigenous bacteria were allowed to colonise in situ microcosms consisting of activated carbon. These microcosms were amended with benzene and one of the electron acceptors nitrate, sulphate or ferric iron to stimulate microbial growth. The data obtained in this study indicated that the composition (via T-RFLP) and structure (via flow cytometry) of the natural bacterial community were influenced by the hydro-geochemical conditions in the test site, but also by the supplied electron acceptors, which led to distinct shifts in relative abundances of specific community members. It was concluded that engineered environments can be successfully monitored by single cell analytics in combination with established molecular tools and sophisticated statistical analyses, a combination that holds great promise for studying and monitoring natural microbial community behaviour.