Norbert Stoppacher

Identification and profiling of volatile metabolites of the biocontrol fungus Trichoderma atroviride by HS-SPME-GC-MS

In the present study we describe a method, which is based on solid phase microextraction (SPME) coupled to gas chromatography-mass spectrometry (GC-MS) and which can be used for the profiling of microbial volatile organic compounds (MVOCs) in the headspace (HS) of cultures of filamentous fungi. The method comprises the following successive steps: 1. growth of the fungus on a solid culture medium directly in headspace vials, 2. measurement of volatiles by HS-SPME-GC-MS, 3. deconvolution of mass spectra, 4. identification of volatiles by comparison of measured, deconvoluted mass spectra and linear temperature programmed retention indices (LTPRI) on two stationary GC phases with database entries and LTPRI published in the literature, and 5. profiling of the identified MVOCs. The developed method was successfully applied to cultures of the biocontrol fungus Trichoderma atroviride. An in-house library consisting of mass spectra and LTPRI values of fungal VOCs was established and used to study the profiles of MVOCs of this fungus. In total, 25 different MVOCs were identified by applying strict criteria (spectral match factor at least 90% and a maximum relative deviation of LTPRI of +/-2% from literature values). The MVOCs were assigned to the compound classes of alcohols, ketones, alkanes, furanes, pyrones (mainly the bioactive 6-pentyl-alpha-pyrone), mono- and sesquiterpenes, 13 of which have never been reported to be produced by Trichoderma spp. before. Eleven of these volatiles have been additionally confirmed using authentic standards. Finally, time course experiments and cultivation of T. atroviride in the presence of the mycotoxin fusaric acid demonstrated the potential of the method to study the dynamics of MVOC profiles as well as the effect of different environmental/biological conditions on the expression of MVOCs of filamentous fungi.

The Comprehensive Peptaibiotics Database

Peptaibiotics are nonribosomally biosynthesized peptides, which – according to definition – contain the marker amino acid α‐aminoisobutyric acid (Aib) and possess antibiotic properties. Being known since 1958, a constantly increasing number of peptaibiotics have been described and investigated with a particular emphasis on hypocrealean fungi. Starting from the existing online ‘Peptaibol Database’, first published in 1997, an exhaustive literature survey of all known peptaibiotics was carried out and resulted in a list of 1043 peptaibiotics. The gathered information was compiled and used to create the new ‘The Comprehensive Peptaibiotics Database’, which is presented here. The database was devised as a software tool based on Microsoft (MS) Access. It is freely available from the internet at http://peptaibiotics‐database.boku.ac.at and can easily be installed and operated on any computer offering a Windows XP/7 environment. It provides useful information on characteristic properties of the peptaibiotics included such as peptide category, group name of the microheterogeneous mixture to which the peptide belongs, amino acid sequence, sequence length, producing fungus, peptide subfamily, molecular formula, and monoisotopic mass. All these characteristics can be used and combined for automated search within the database, which makes The Comprehensive Peptaibiotics Database a versatile tool for the retrieval of valuable information about peptaibiotics. Sequence data have been considered as to December 14, 2012.

Heterochromatin influences the secondary metabolite profile in the plant pathogen Fusarium graminearum

Highlights ► Heterochromatin protein characterized in F. graminearum. ► Heterochromatic marks regulate secondary metabolism in this fungus. ► Aurofusarin and DON production under Hep1 regulation. ► Surprisingly, Hep1 positively regulates DON biosynthesis. ► Silencing of SM genes by heterochromatin could be conserved mechanism in ascomycetes.

The Peptaibiotics Database – A Comprehensive Online Resource

In this work, we present the ‘Peptaibiotics Database’ (PDB), a comprehensive online resource, which intends to cover all Aib‐containing non‐ribosomal fungal peptides currently described in scientific literature. This database shall extend and update the recently published ‘Comprehensive Peptaibiotics Database’ and currently consists of 1,297 peptaibiotic sequences. In a literature survey, a total of 235 peptaibiotic sequences published between January 2013 and June 2014 have been compiled, and added to the list of 1,062 peptides in the recently published ‘Comprehensive Peptaibiotics Database’.

Marker peptide selection for the determination of hazelnut by LC–MS/MS and occurrence in other nuts

The aim of this work was identifying and selecting hazelnut marker peptides and subsequently developing a complementary method of common immunoassay for the detection of hazelnut. For this purpose, at first, an in silico digestion of three major hazelnut allergens (Cor a 8, Cor a 9 and Cor a 11) was performed to get information about expected peptides. After extraction and trypsin digestion of hazelnut proteins, the samples were measured with tandem mass spectrometry (MS/MS) by direct infusion, which led to identification of 14 peptides. Eight of them with the highest MS signal were synthesized and used as standards for developing a liquid chromatography (LC)–MS/MS method in selected reaction monitoring (SRM) mode. Since almost all food allergens derived from nuts belong to the seed storage protein family and have homologue structure, a Basic Local Alignment Search Tool (BLAST) search was performed to identify the hazelnut specificity of the developed method. According to BLAST, only one peptide occurs in three other nuts, and the remaining seven selected peptides are hazelnut specific. Additionally to hazelnut, the eight other listed nuts in Directive 2003/89/EC as allergen were extracted, digested and measured with the developed method to prove the BLAST results. The analytical data confirmed that six peptides are hazelnut specific, on the contrary to anti-hazelnut antibodies, which showed cross-reactivities to all other nut extracts. Comparing these results, it could be shown that with this LC–MS/MS method in SRM mode, the specific detection of hazelnut is possible.