PNNL

Abstract

Monitoring diversity changes and contamination in mixed cultures and simplemicrocosms is challenged by fast community structure dynamics, and the need for means allowing fast, cost-efficient and accurate identification of microorganisms at high phylogenetic resolution. The method we explored is a variant of Automated rRNA Intergenic Spacer Analysis based on Intra-Genomic Diversity Fingerprinting (ARISAIGDF), and identifies phylotypes with multiple 16S–23S rRNA gene Intergenic Transcribed Spacers. We verified the effect of PCR conditions (annealing temperature, duration of final extension, number of cycles, group-specific primers and formamide) on ARISA-IGD fingerprints of 44 strains of Shewanella.We present a digitization algorithmand data analysis procedures needed to determine confidence in strain identification. Though using stringent PCR conditions and group-specific primers allow reasonably accurate identification of strains with three ARISA-IGD amplicons within the 82–1000 bp size range, ARISA-IGDF is best for phylotypes with =4 unambiguously different amplicons. This method allows monitoring the occurrence of culturable microbes and can be implemented in applications requiring high phylogenetic resolution, reproducibility, low cost and high throughput such as identifying contamination and monitoring the evolution of diversity in mixed cultures and low diversity microcosms and periodic screening of small microbial culture libraries.