1887

Abstract

Identification of microbial community members in complex environmental samples is time consuming and repetitive. Here, ribosomal sequences and hidden Markov models are used in a novel approach to rapidly assign fungi to their presumptive genera. The ITS1 and ITS2 fragments from a range of axenic, anaerobic gut fungal cultures, including several type strains, were isolated and the RNA secondary structures predicted for these sequences were used to generate a fingerprinting program. The methodology was then tested and the algorithms improved using a collection of environmentally derived sequences, providing a rapid indicator of the fungal diversity and numbers of novel sequence groups within the environmental sample from which they were derived. While the methodology was developed to assist in investigations involving the rumen ecosystem, it has potential generic application in studying diversity and population dynamics in other microbial ecosystems.

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2005-05-01
2019-11-21
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Representative alignment of 12 ITS1 sequences plus flanking regions from anaerobic gut fungi showing Variable Regions I–IV [PDF file](15 KB)

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An alignment of the five (EO12A-D, Ozkose, 2001; NZB7, this study) and nine (EO17, EO14A-H; Ozkose, 2001) sequences for ITS1 Variable Regions I–IV, together with the ITS1 Variable Regions II–IV sequences from the eleven of the forty-eight environmental samples that group together as Novel Group 1 [PDF file](15 KB)

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