Species Prioritization Based on Spectral Dissimilarity: A Case Study of Polyporoid Fungal Species

Abstract

Biological species collections are critical for natural product drug discovery programs. However, prioritization of target species in massive collections remains difficult. Here, we introduce an untargeted metabolomics-based prioritization workflow that uses MS/MS molecular networking to estimate scaffold-level distribution. As a demonstration, we applied the workflow to 40 polyporoid fungal species. Nine species were prioritized as candidates based on the chemical structural and compositional similarity (CSCS) metric. Most of the selected species showed relatively higher richness and uniqueness of metabolites than those of the others. Cryptoporus volvatus, one of the prioritized species, was investigated further. The chemical profiles of the extracts of C. volvatus culture and fruiting bodies were compared, and it was shown that derivative-level diversity was higher in the fruiting bodies; meanwhile, scaffold-level diversity was similar. This showed that the compounds found from a cultured fungus can also be isolated in wild mushrooms. Targeted isolation of the fruiting body extract yielded three unknown (1−3) and six known (4−9) cryptoporic acid derivatives, which are drimane-type sesquiterpenes with isocitric acid moieties that have been reported in this species. Cryptoporic acid T (1) is a trimeric cryptoporic acid reported for the first time. Compounds 2 and 5 exhibited cytotoxicity against HCT-116 cell lines with IC 50 values of 4.3 and 3.6 μM, respectively.

Identification of Antibacterial Sterols from Korean Wild Mushroom Daedaleopsis confragosa via Bioactivity- and LC-MS/MS Profile-Guided Fractionation

“…As the crude methanol extract and fractions showed different bioactivities, we performed chemical profiling of the samples to obtain insights into the bioactive components. Contrary to our hypothesis, MS ions detected in the crude extract did not overlap with those from the extract of the isolate culture of D. tricolor [ 15 ]. However, we continued the investigation on the fractions, as they showed the bioactivity.…”

“…Among these four datasets, three were available for metadata and two were obtained from our previous studies. Compound 1 was present in the fungal cell extracts of Fusarium graminearum (dataset MSV000084977) [ 28 ] and fungal culture extracts from eight species in our previous Polyporaceae dataset (MSV000085974) [ 15 ], Cerrena unicolor , Coriolopsis strumosa , Daedaleopsis tricolor , Polyporus brumalis , Microporus vernicipes , Trametes orientalis , Trametes suaveolens , and Trametopsis cervina . Interestingly, the extract of D. conragosa in the Polyporaceae dataset did not contain 1 , which suggests that the biosynthesis of 1 was not activated under the laboratory culture conditions used in this study.…”

“…D. confragosa has rarely been investigated in terms of its chemical constituents. In our recent untargeted metabolomics study on 40 species of Polyporaceae, Daedaleopsis tricolor was highlighted as one of the promising producers of unique specialized metabolites [ 15 ]. As the appearance of D. confragosa is similar to that of D. tricolor and a recent ITS sequences-based phylogenetic analysis suggested that D. confragosa and D. tricolor may be two morpho-ecological varieties of one species [ 16 ], consistent with the suggestion of a mitochondrial small subunit rDNA sequences-based study in 1999 [ 17 ], we hypothesized that D. confragosa would show unique specialized metabolites as D. tricolor .…”

Bioactive Phenolic Compounds from Peperomia obtusifolia

“…The C-1′ hydroxyl of the isocitrate unit is attached to the caffeic acid moiety at C-9 indicated by the long-range correlation from H-1′ (δ H 5.46) to C-9 (δ C 167.5) ( Figure 2 ). The methylated isocitrate moiety of 1 is similar to those found in cryptoporic acids isolated from Cryptoporus sinensis [ 16 ] and Cryptoporus volvatus [ 17 , 18 ], which are also conjugates of isocitrate. Since compound 1 was also detected in an ethanolic crude extract ( Figure S9 ), the methylation is not a processing artifact.…”

Inventa: a computational tool to discover chemical novelty in natural extracts libraries

“…It is based on the principle that dissimilar extracts would hold a particular chemistry, different from the ensemble of extracts. Recently, an application of this workflow led to the isolation of three new drimane-type sesquiterpenes (Pham et al, 2021). Finally, FERMO is a tool presently in development for the prioritization of relevant bioactive compounds (metabolites) within natural extracts based on chromatographic characteristics, bioactivity, and dereplication results.…”