The mammalian gut houses a complex microbial community which is believed to play a significant role in host physiology. In recent years, several microbial community analysis methods have been implemented to study the whole gut microbial environment, in contrast to classical microbiological methods focusing on bacteria which can be cultivated. One of these is automated ribosomal intergenic spacer analysis (ARISA), an inexpensive and popular way of analyzing bacterial diversity and community fingerprinting in ecological samples. ARISA uses the natural variability in length of the DNA fragment found between the 16S and 23S genes in different bacterial lineages to infer diversity. This method is now being supplanted by affordable next-generation sequencing technologies that can also simultaneously annotate operational taxonomic units for taxonomic identification. We compared ARISA and pyrosequencing of samples from the rumen microbiome of cows, previously sampled at different stages of development and varying in microbial complexity using several ecological parameters. We revealed close agreement between ARISA and pyrosequencing outputs, especially in their ability to discriminate samples from different ecological niches. In contrast, the ARISA method seemed to underestimate sample richness. The good performance of the relatively inexpensive ARISA makes it relevant for straightforward use in bacterial fingerprinting analysis as well as for quick cross-validation of pyrosequencing data.
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