Use of the T-RFLP technique to assess spatial and temporal changes in the bacterial community structure within an agricultural soil planted with transgenic and non-transgenic potato plants

Abstract

The aim of this study was to examine whether the terminal restriction fragment length polymorphism (T-RFLP) analysis represents an appropriate technique for monitoring highly diverse soil bacterial communities, i.e. to assess spatial and/or temporal effects on bacterial community structure. The T-RFLP method, a recently described fingerprinting technique, is based on terminal restriction fragment length polymorphisms between distinct small-subunit rRNA gene sequence types. This technique permits an automated quantification of the fluorescence signal intensities of the individual terminal restriction fragments (T-RFs) in a given community fingerprint pattern. The indigenous bacterial communities of three soil plots located within an agricultural field of 110 m(2) were compared. The first site was planted with non-transgenic potato plants, while the other two were planted with transgenic GUS and Barnase/Barstar potato plants, respectively. Once prior to planting and three times after planting, seven parallel samples were taken from each of the three soil plots. The T-RFLP analysis resulted in very complex but highly reproducible community fingerprint patterns. The percentage abundance values of defined T-RFs were calculated for the seven parallel samples of the respective soil plot. A multivariate analysis of variance was used to test T-RFLP data sets for significant differences. The statistical treatments clearly revealed spatial and temporal effects, as well as spacextime interaction effects, on the structural composition of the bacterial communities. T-RFs which showed the highest correlations to the discriminant factors were not those T-RFs which showed the largest single variations between the seven-sample means of individual plots. In summary, the T-RFLP technique, although a polymerase chain reaction-based method, proved to be a suitable technique for monitoring highly diverse soil microbial communities for changes over space and/or time.