RISA

RISA is the acronym for "rRNA intergenic spacer analysis". RISA is a method for analyzing microbial samples that provides estimates of microbial diversity and community composition without the biases associated with culture-based approaches or the labor associated with the preparation of small-subunit rRNA gene clone libraries (Fisher MM et al. 1999).

RISA was originally used to compare diversity in soils and to study microbial diversity in the rhizosphere and marine environment (Fisher MM et al. 1999). The method involves PCR amplification of the intergenic region between the small (16S) and large (23S) subunit of rRNA genes in the rRNA operon from total bacterial community DNA using oligonucleotide primers targeting conserved regions in the 16S and 23S genes.

The 16S-23S intergenic region, which can encode tRNAs depending on the bacterial species, exhibits considerable heterogeneity in both length and nucleotide sequence. Both types of variation have been used extensively to differentiate bacterial strains, including mycological samples . In RISA, the length heterogeneity of the intergenic spacer is exploited. The PCR product (a mixture of fragments derived from members of the community) is electrophoresed in a polyacrylamide gel and the DNA is visualized by silver staining. The result is a complex banding pattern that provides a community-specific profile, with each DNA band corresponding to at least one organism in the original assemblage.

In the automated approach, the initial steps of DNA extraction and PCR amplification are the same as in RISA, except that the PCR is performed with a fluorescently labeled oligonucleotide primer (Porcellato D et al. 2014). The electrophoretic step is then performed using an automated system that enables laser detection of the fluorescent DNA fragments. ARISA-PCR can generate DNA fragments with a length of up to 1,400 bp.

1. Fisher MM et al. (1999) Automated approach for ribosomal intergenic spacer analysis of microbial diversity and its application to freshwater bacterial communities. Appl Environ Microbiol 65:4630-4636.
2. Johnston-Monje D et al. (2020) Botanical microbiomes on the cheap: Inexpensive molecular fingerprinting methods to study plant-associated communities of bacteria and fungi. Appl Plant Sci. 8:e11334.
3. Porcellato D et al. (2014) Application of ARISA to assess the influence of salt content and cation type on microbiological diversity of Cheddar cheese. Lett Appl Microbiol 59:207-216.
4. Saro C et al. (2018) Comparison of automated ribosomal intergenic spacer analysis (ARISA) and denaturing gradient gel electrophoresis (DGGE) techniques for analyzing the influence of diet on ruminal bacterial diversity. Arch Anim Nutr 72: 85-99.