Abstract

Anaerobic fungi (phylum Neocallimastigomycota) are common inhabitants of the digestive tract of mammalian herbivores, and in the rumen, can account for up to 20% of the microbial biomass. Anaerobic fungi play a primary role in the degradation of lignocellulosic plant material. They also have a syntrophic interaction with methanogenic archaea, which increases their fiber degradation activity. To date, nine anaerobic fungal genera have been described, with further novel taxonomic groupings known to exist based on culture-independent molecular surveys. However, the true extent of their diversity may be even more extensively underestimated as anaerobic fungi continue being discovered in yet unexplored gut and non-gut environments. Additionally many studies are now known to have used primers that provide incomplete coverage of the Neocallimastigomycota. For ecological studies the internal transcribed spacer 1 region (ITS1) has been the taxonomic marker of choice, but due to various limitations the large subunit rRNA (LSU) is now being increasingly used. How the continued expansion of our knowledge regarding anaerobic fungal diversity will impact on our understanding of their biology and ecological role remains unclear; particularly as it is becoming apparent that anaerobic fungi display niche differentiation. As a consequence, there is a need to move beyond the broad generalization of anaerobic fungi as fiber-degraders, and explore the fundamental differences that underpin their ability to exist in distinct ecological niches. Application of genomics, transcriptomics, proteomics and metabolomics to their study in pure/mixed cultures and environmental samples will be invaluable in this process. To date the genomes and transcriptomes of several characterized anaerobic fungal isolates have been successfully generated. In contrast, the application of proteomics and metabolomics to anaerobic fungal analysis is still in its infancy. A central problem for all analyses, however, is the limited functional annotation of anaerobic fungal sequence data. There is therefore an urgent need to expand information held within publicly available reference databases. Once this challenge is overcome, along with improved sample collection and extraction, the application of these techniques will be key in furthering our understanding of the ecological role and impact of anaerobic fungi in the wide range of environments they inhabit.

Highlights

  • INTRODUCTIONAnaerobic fungi (phylum Neocallimastigomycota) are the most effective fiber degrading microorganisms in the gut of mammalian herbivores

  • Anaerobic fungi are the most effective fiber degrading microorganisms in the gut of mammalian herbivores

  • We focus on the different types of molecular methods, including ‘omics approaches, that have been used to date in the study of anaerobic fungi, and we highlight the challenges that currently exist—many of which are fundamentally different from those encountered with the more routinely studied rumen bacteria and archaea

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Summary

INTRODUCTION

Anaerobic fungi (phylum Neocallimastigomycota) are the most effective fiber degrading microorganisms in the gut of mammalian herbivores This is due to their combined mechanical and enzymatic activity, and the associated ability to penetrate plant structural barriers (Orpin, 1975; Ho et al, 1988; Lee et al, 1999). Those useful for generation sequencing (NGS) based diversity studies, are those found on the multicopy rrn (rRNA) operon (Figure 1) These loci have a high copy number 200) per genome meaning only small amounts of tissue or environmental sample are needed for efficient PCR amplification These loci are not protein coding, having a relatively high mutation rate enabling good phylogenetic resolution (Hibbett et al, 2007). It has been found that anaerobic fungi have two paralogous copies of EF-1α (Eckart et al, 2010), which is perhaps not that surprising considering the large amount of repetition that has been reported to occur in anaerobic fungal genomes

Molecular Methods for Anaerobic Fungi
Findings
CONCLUSIONS
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