Dataset Information

Mass Spectrometry Imaging of Specialized Metabolites for Predicting Lichen Fitness and Snail Foraging.

ABSTRACT: Lichens are slow-growing organisms supposed to synthetize specialized metabolites to protect themselves against diverse grazers. As predicted by the optimal defense theory (ODT), lichens are expected to invest specialized metabolites in higher levels in reproductive tissues compared to thallus. We investigated whether Laser Desorption Ionization coupled to Mass Spectrometry Imaging (LDI-MSI) could be a relevant tool for chemical ecology issues such as ODT. In the present study, this method was applied to cross-sections of thalli and reproductive tissues of the lichen Pseudocyphellaria crocata. Spatial mapping revealed phenolic families of metabolites. A quantification of these metabolites was carried out in addition to spatial imaging. By this method, accumulation of specialized metabolites was observed in both reproductive parts (apothecia and soralia) of P. crocata, but their nature depended on the lichen organs: apothecia concentrated norstictic acid, tenuiorin, and pulvinic acid derivatives, whereas soralia mainly contained tenuiorin and pulvinic acid. Stictic acid, tenuiorin and calycin, tested in no-choices feeding experiments, were deterrent for N. hookeri while entire thalli were consumed by the snail. To improve better knowledge in relationships between grazed and grazing organisms, LDI-MSI appears to be a complementary tool in ecological studies.

SUBMITTER: Gadea A

PROVIDER: S-EPMC7020473 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Mass Spectrometry Imaging of Specialized Metabolites for Predicting Lichen Fitness and Snail Foraging.

Gadea Alice A Fanuel Mathieu M Le Lamer Anne-Cécile AC Boustie Joël J Rogniaux Hélène H Charrier Maryvonne M Lohézic-Le Devehat Françoise F

Plants (Basel, Switzerland) 20200106 1

Lichens are slow-growing organisms supposed to synthetize specialized metabolites to protect themselves against diverse grazers. As predicted by the optimal defense theory (ODT), lichens are expected to invest specialized metabolites in higher levels in reproductive tissues compared to thallus. We investigated whether Laser Desorption Ionization coupled to Mass Spectrometry Imaging (LDI-MSI) could be a relevant tool for chemical ecology issues such as ODT. In the present study, this method was a ...[more]

PMID: 31935813

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Project description:Mass spectrometry imaging (MSI) provides insight into the molecular distribution of a broad range of compounds and, therefore, is frequently applied in the pharmaceutical industry. Pharmacokinetic and toxicological studies deploy MSI to localize potential drugs and their metabolites in biological tissues but currently require other analytical tools to quantify these pharmaceutical compounds in the same tissues. Quantitative mass spectrometry imaging (Q-MSI) is a field with challenges due to the high biological variability in samples combined with the limited sample cleanup and separation strategies available prior to MSI. In consequence, more selectivity in MSI instruments is required. This can be provided by multiple reaction monitoring (MRM) which uses specific precursor ion-product ion transitions. This targeted approach is in particular suitable for pharmaceutical compounds because their molecular identity is known prior to analysis. In this work, we compared different analytical platforms to assess the performance of MRM detection compared to other MS instruments/MS modes used in a Q-MSI workflow for two drug candidates (A and B). Limit of detection (LOD), linearity, and precision and accuracy of high and low quality control (QC) samples were compared between MS instruments/modes. MRM mode on a triple quadrupole mass spectrometer (QqQ) provided the best overall performance with the following results for compounds A and B: LOD 35.5 and 2.5 μg/g tissue, R2 0.97 and 0.98 linearity, relative standard deviation QC <13.6%, and 97-112% accuracy. Other MS modes resulted in LOD 6.7-569.4 and 2.6-119.1 μg/g tissue, R2 0.86-0.98 and 0.86-0.98 linearity, relative standard deviation QC < 19.4 and < 37.5%, and 70-356% and 64-398% accuracy for drug candidates A and B, respectively. In addition, we propose an optimized 3D printed mimetic tissue model to increase the overall analytical throughput of our approach for large animal studies. The MRM imaging platform was applied as proof-of-principle for quantitative detection of drug candidates A and B in four dog livers and compared to LC-MS. The Q-MSI concentrations differed <3.5 times with the concentrations observed by LC-MS. Our presented MRM-based Q-MSI approach provides a more selective and high-throughput analytical platform due to MRM specificity combined with an optimized 3D printed mimetic tissue model.

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Dataset Information

Mass Spectrometry Imaging of Specialized Metabolites for Predicting Lichen Fitness and Snail Foraging.

Publications

Mass Spectrometry Imaging of Specialized Metabolites for Predicting Lichen Fitness and Snail Foraging.

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