Background: Truffles are symbiotic fungi that develop underground in association with plant roots, forming ectomycorrhizae. They are primarily known for the organoleptic qualities of their hypogeous fruiting bodies. Primarily, Tuber magnatum Pico is a greatly appreciated truffle species mainly distributed in Italy and Balkans. Its price and features are mostly depending on its geographical origin. However, the genetic variation within T. magnatum has been only partially investigated as well as its adaptation to several environments. Results: Here, we applied an integrated omic strategy to T. magnatum fruiting bodies collected during several seasons from three different areas located in the North, Center and South of Italy, with the aim to distinguish them according to molecular and biochemical traits and to verify the impact of several environments on these properties. With the proteomic approach based on two-dimensional electrophoresis (2-DE) followed by mass spectrometry, we were able to identify proteins specifically linked to the sample origin. We further associated the proteomic results to an RNA-seq profiling, which confirmed the possibility to differentiate samples according to their source and provided a basis for the detailed analysis of genes involved in sulfur metabolism. Finally, geographical specificities were associated with the set of volatile compounds produced by the fruiting bodies, as quantitatively and qualitatively determined through proton transfer reaction-mass spectrometry (PTR-MS) and gas-chromatography-mass spectrometry (GC-MS). In particular, a partial least squares-discriminant analysis (PLS-DA) model built from the latter data was able to return high confidence predictions of sample source. Conclusions: Results provide a characterization of white fruiting bodies by a wide range of different molecules, suggesting the role for specific compounds in the responses and adaptation to distinct environments.

Tuberomics: A molecular profiling for the adaption of edible fungi (tuber magnatum pico) to different natural environments

Trovato E.;Sciarrone D.;Zoccali M.;Mondello L.;
2020

Abstract

Background: Truffles are symbiotic fungi that develop underground in association with plant roots, forming ectomycorrhizae. They are primarily known for the organoleptic qualities of their hypogeous fruiting bodies. Primarily, Tuber magnatum Pico is a greatly appreciated truffle species mainly distributed in Italy and Balkans. Its price and features are mostly depending on its geographical origin. However, the genetic variation within T. magnatum has been only partially investigated as well as its adaptation to several environments. Results: Here, we applied an integrated omic strategy to T. magnatum fruiting bodies collected during several seasons from three different areas located in the North, Center and South of Italy, with the aim to distinguish them according to molecular and biochemical traits and to verify the impact of several environments on these properties. With the proteomic approach based on two-dimensional electrophoresis (2-DE) followed by mass spectrometry, we were able to identify proteins specifically linked to the sample origin. We further associated the proteomic results to an RNA-seq profiling, which confirmed the possibility to differentiate samples according to their source and provided a basis for the detailed analysis of genes involved in sulfur metabolism. Finally, geographical specificities were associated with the set of volatile compounds produced by the fruiting bodies, as quantitatively and qualitatively determined through proton transfer reaction-mass spectrometry (PTR-MS) and gas-chromatography-mass spectrometry (GC-MS). In particular, a partial least squares-discriminant analysis (PLS-DA) model built from the latter data was able to return high confidence predictions of sample source. Conclusions: Results provide a characterization of white fruiting bodies by a wide range of different molecules, suggesting the role for specific compounds in the responses and adaptation to distinct environments.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11570/3160035
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