Applying Parallel Factor Analysis models to HPLC diode array detector datasets reveals strain dependent regulation of polyketide biosynthesis in Fusarium graminearum, Fusarium culmorum and Fusarium pseudograminearum

Fungal secondary metabolites confer an indiscriminate resource of bioactive compounds with both pharmaceutical and industrial relevance. Synthesis of these compounds is tightly controlled through regulatory networks. These networks act in response to the environmental conditions in which the fungus grows. One class of fungal secondary metabolites that have drawn increased attention, is the polyketides produced by a high number of fungi and bacteria. The increasing number of publicly available genomic sequences of filamentous fungi, combined with new and highly efficient DNA-cloning techniques, has allowed the use of new efficient approaches to study the regulation and synthesis of these compounds. With the availability of new molecular genetic tools, a new bottleneck has occurred in fungal molecular biology; the analytical chemical analysis of the generated transgenic mutants. In this study, a method based on PARAFAC data analysis of HPLC data is presented and shown useful for gaining overview of complex and diverse datasets. Further, the strain specific and nutrient dependent regulation of polyketide synthesis is discussed.