Abstract. Automated RISA (Ribosomal Intergenic Spacer Analysis) was used
to characterise bacterial (B-ARISA) and fungal (F-ARISA) communities in
soils from various geographical origins with differing vegetation cover
and with different physico-chemical characteristics. The 16S-23S intergenic
spacer region from the bacterial rRNA operon was amplified from total soil
community DNA for B-ARISA. Similarly, the two internal transcribed spacers
and the 5.8S rRNA gene (ITS1-5.8S-ITS2) from the fungal rRNA operon were
amplified from total soil community DNA for F-ARISA. Universal fluorescence-
labelled primers were used for the PCR reactions and fragments of between
200 and 1200 bp were resolved on denaturing polyacrylamide gel by use of
an automated sequencer with laser detection. Methodological (DNA
extraction and PCR amplification) and biological (inter- and intra-site)
variations were evaluated by comparing the number and intensity of peaks
(i.e. bands) between electrophoregrams (i.e. profiles) and by multivariate
analysis. Our results showed that ARISA is a high resolution, highly
reproducible technique and is a robust method for discriminating between
microbial communities. To evaluate the potential biases in community
description provided by ARISA we also examined databases on length
distribution of ribosomal IGS among bacteria (Ranjard et al., Appl.
Environ. Microbiol. 66:5334-5339, 2000) and fungi.