ABSTRACT
In the course of investigations on peptaibol chemodiversity from marine-derived Trichoderma spp., five new 15-residue peptaibols named pentadecaibins I-V (1-5) were isolated from the solid culture of the strain Trichoderma sp. MMS1255 belonging to the T. harzianum species complex. Phylogenetic analyses allowed precise positioning of the strain close to T. lentiforme lineage inside the Harzianum clade. Peptaibol sequences were elucidated on the basis of their MS/MS fragmentation and extensive 2D NMR experiments. Amino acid configurations were determined by Marfey's analyses. The pentadecaibins are based on the sequences Ac-Aib1-Gly2-Ala3-Leu4-Aib/Iva5-Gln6-Aib/Iva7-Val/Leu8-Aib9-Ala10-Aib11-Aib12-Aib13-Gln14-Pheol15. Characteristic of the pentadecaibin sequences is the lack of the Aib-Pro motif commonly present in peptaibols produced by Trichoderma spp. Genome sequencing of Trichoderma sp. MMS1255 allowed the detection of a 15-module NRPS-encoding gene closely associated with pentadecaibin biosynthesis. Pentadecaibins were assessed for their potential antiproliferative and antimicrobial activities.
Subject(s)
Peptaibols/chemistry , Trichoderma/chemistry , Amino Acid Sequence , Aquatic Organisms/chemistry , Cell Line, Tumor , Humans , Microbial Sensitivity Tests , Phylogeny , Trichoderma/classificationABSTRACT
This study investigates the potential and complementarity of high-throughput multipulse and multidimensional NMR methods for metabolomics. Through a chemical ecology case study, three methods are investigated, offering a continuum of methods with complementary features in terms of resolution, sensitivity and experiment time. Ultrafast 2D COSY, adiabatic INEPT and SYMAPS HSQC are shown to provide a very good classification ability, comparable to the reference 1D 1H NMR method. Moreover, a detailed analysis of discriminant buckets upon supervised statistical analysis shows that all methods are highly complementary, since they are able to highlight discriminant signals that could not be detected by 1D 1H NMR. In particular, fast 2D methods appear very efficient to discriminate signals located in highly crowded regions of the 1H spectrum. Overall, the combination of these recent methods within a single NMR metabolomics workflow allows to maximize the accessible metabolic information, and also raises exciting challenges in terms of NMR data analysis for chemical ecology.