Introduction

The identification of filamentous fungi has always been considered difficult and many misunderstandings and misidentifications can bee found in the literature (Frisvad 1989; Mantle 1987). Phenotypic characters, e.g., morphology and growth on selected media have traditionally formed the basis for fungal taxonomy (Domsch et al. 1980; Mantle 1987; Pitt 1979; Raper and Fennell 1977; Raper and Thom 1949). Advancements in the developments of analytical methodology have allowed the use of "secondary" metabolite profiling for fungal identification and been used to revise the taxonomy within genera of Penicillium, Aspergillus, Fusarium, Alternaria, and their perfect states. The success of metabolite profiling in the classification of filamentous fungi relies on the fact that a major part of the fungal growth is expressed by the production of numerous diverse metabolites, most of which are excreted into the media. The extracellular metabolites have been termed the exome, a subgroup of the metabolome (all metabolites), and these are related to the genome as illustrated in Figure 1. The reasons why most filamentous fungi produce such a diverse profile of secondary metabolites are still unclear, but they are probably produced as a result of stimuli and are directed against, or support actions on, receptor systems (Christophersen 1996) or as outward directed (extrovert) differentiation products. Possible others functions, include chemical signaling between organisms (Christophersen 1996; Frisvad 1994a). Williams et al. (1989) described their functions as "... serve the producing organisms by improving their survival fitness ... ."

Commonly used macro- and micromorphological characters (rough conidia, fluffy mycelia, color, etc.) can be difficult to determine unequivocally and are difficult to link to gene sequences. The production of secondary metabolites can typically be linked to a particular gene sequence or gene cluster and is most likely to be regulated as a response to growth factors. However, there are far more metabolites than genes as demonstrated by modern metabolomics. Schwab (2002) estimates that there might be as many as 10-100 metabolites for each gene in higher organisms. Therefore, a metabolite profile can provide an indirect method of detecting a large set of metabolite coding genes which are expressed at the same time. Metabolite profiling also allows detection of a specific gene cluster through the identification of different compounds from that pathway. Turner (1971) and Turner and Aldridge (1983) suggested subdividing secondary metabolites according to their biosynthetic origin. In this way a selected metabolite originating from a pathway, e.g., polyketide, terpene, diketopiperazine, and cyclopeptide is treated as representative of that particular pathway. This is important, as only a limited number of members of a biosynthetic pathway are expressed under a given set of conditions, e.g., external stimuli and growth conditions (Section 2.2). Mantle (1987) has reviewed secondary metabolite production by Penicillium species based on biosynthetic pathways. He suggested a renaming of original isolates according to new taxonomic systems and emphasized that frequent misidentifications have lead to errors, especially for isolates no longer available for the scientific community. Frisvad and Filtenborg (1983) first demonstrated the advantage of secondary metabolite profiling in fungal taxonomy with the genus Penicillium,

Figure 1 The profile of extra-cellular metabolites or the exome is linked to genomics through a mostly one-way connection from the genome. Far more metabolites than genes are found in most cells, and metabolite profiles are phenotypic characters as are most other characters used in classical mycology.

Figure 1 The profile of extra-cellular metabolites or the exome is linked to genomics through a mostly one-way connection from the genome. Far more metabolites than genes are found in most cells, and metabolite profiles are phenotypic characters as are most other characters used in classical mycology.

using a simple agar-plug-TLC technique. They later also included HPLC methods in their studies. Efficient identification based on metabolite profiling relies on combining this information with more classical tools and a priori knowledge. For general use it is important to know at least the genus of the fungus being studied and which growth media to use. The analytical methodology depends on the group/genus being studied, but can vary from the simple TLC approach to hyphenated LC-MS-MS. This combined approach is illustrated in Figure 2. It is important to note that efficient identification of fungi will, in most cases, require the use of profiles of metabolites from crude extracts, rather than single or selected metabolites. However, a limited number of species-specific metabolites can be used efficiently as markers for particular species in particular cases. This chapter focuses on the practical considerations in the use of metabolite profiles in identification. The text follows the general approach illustrated in Figure 2, and four different cases of various techniques are given.

Figure 2 Efficient identification of filamentous fungi requires a synthesis of mycology, analytical chemistry and informatics although the metabolite profile can sometime give the full
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