title: Automated and unbiased classification of chemical profiles from fungi using high performance liquid chromatography.
abstract: In this paper we present a method for unbiased/unsupervised classification and identification of closely related fungi, using chemical analysis of secondary metabolite profiles created by HPLC with UV diode array detection. For two chromatographic data matrices a vector of locally aligned full spectral similarities is calculated along the retention time axis. The vector depicts the evaluating of the alikeness between two fungal extracts based upon eluted compounds and corresponding UV-absorbance spectra. For assessment of the chemotaxonomic grouping the vector is condensed to one similarity describing the overall degree of similarity between the profiles. Two sets of data were used in this study: One set was used in the method development and a second dataset used for method validation. First we developed a method for evaluating the secondary metabolite production from closely related Penicillium species. Then the algorithm was validated on fungal isolates belonging to the genus Alternaria. The results showed that the species may be segregated into taxa in full accordance with published taxonomy.
authors.affiliation: Informatics and Mathematical Modelling (IMM), Richard Petersens Plads, building 321, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark. meh@biocentrum.dtu.dk
authors.forename: Michael Edberg
authors.initials: ME
authors.lastname: Hansen
authors.forename: Birgitte
authors.initials: B
authors.lastname: Andersen
authors.forename: Jørn
authors.initials: J
authors.lastname: Smedsgaard
mesh_terms: D000465:Algorithms; D000528:Alternaria / Q000737:chemistry / Q000145:classification; D001331:Automation; D002851:Chromatography, High Pressure Liquid / Q000379:methods*; D016208:Databases, Factual; D005658:Fungi / Q000737:chemistry* / Q000145:classification*; D016533:Mycological Typing Techniques / Q000379:methods* / Q000706:statistics & numerical data; D010407:Penicillium / Q000737:chemistry / Q000145:classification