Open and reusable annotated mass spectrometry dataset of a chemodiverse collection of 1,600 plant extracts

Abstract

As privileged structures, natural products often display potent biological activities. However, the discovery of novel bioactive scaffolds is often hampered by the chemical complexity of the biological matrices they are found in. Large natural extract collections are thus extremely valuable for their chemical novelty potential but also complicated to exploit in the frame of drug-discovery projects. In the end, it is the pure chemical substances that are desired for structural determination purposes and bioactivity evaluation. Researchers interested in the exploration of large and chemodiverse extract collections should thus establish strategies aiming to efficiently tackle such chemical complexity and access these structures. Establishing carefully crafted digital layers documenting the spectral and chemical complexity as well as bioactivity results of natural extracts collections can help prioritize time-consuming but mandatory isolation efforts. In this note, we report the results of our initial exploration of a collection of 1,600 plant extracts in the frame of a drug-discovery effort. After describing the taxonomic coverage of this collection, we present the results of its liquid chromatography high-resolution mass spectrometric profiling and the exploitation of these profiles using computational solutions. The resulting annotated mass spectral dataset and associated chemical and taxonomic metadata are made available to the community, and data reuse cases are proposed. We are currently continuing our exploration of this plant extract collection for drug-discovery purposes (notably looking for novel antitrypanosomatids, anti-infective and prometabolic compounds) and ecometabolomics insights. We believe that such a dataset can be exploited and reused by researchers interested in computational natural products exploration.

A Sample-Centric and Knowledge-Driven Computational Framework for Natural Products Drug Discovery

“…receiving the accession number 03-FR-2020. 75,76 The grounded dry roots plant material of Prisitimera indica (Willd.) A.C.Sm.…”

Leaf metabolic traits reveal hidden dimensions of plant form and function

“…Competing interests: The authors declare that they have no competing interests. Data and materials availability: Raw tropical metabolomics data are available under the DOI 10.25345/ C59J97 (36). Raw temperate species metabolomics data are available on GNPS using the link https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=32bb23eb0e0b475da0336f6f84254d05 (37).…”

Leaf metabolic traits reveal hidden dimensions of plant form and function

“…We expressed the leaf metabolomes of tropical ( 36 ) and temperate ( 37 ) plant species as the presence or absence of annotated metabolic features (i.e., metabolites) detected through liquid chromatography mass spectrometry (tropical N = 3356; temperate N = 2227). We then characterized the chemistry of the leaf metabolome by examining variation in the chemical properties of all unique metabolites from both datasets (N = 4292) ( 31 ).…”

“…Data and materials availability. Raw tropical metabolomics data are available under the DOI 10.25345/C59J97 36 . Raw temperate species metabolomics data are available under the DOI 10.6084/m9.figshare.13032740 37 .…”

“…Finally, we combined metabolic traits with eight widely used functional traits (plant height, seed mass, stem specific density, leaf area, specific leaf area and leaf carbon, nitrogen and phosphorus concentrations; hereafter "classical traits") (7) to determine whether axes of metabolic specialization are colinear with, or orthogonal to, plant life-history strategies described by classical functional traits. Five chemical properties capture chemical variation in the leaf metabolome We expressed the leaf metabolomes of tropical (36) and temperate (37) plant species as the presence or absence of annotated metabolic features (i.e., metabolites) detected through liquid chromatography mass spectrometry (tropical N = 3356; temperate N = 2227). We then characterized the chemistry of the leaf metabolome by examining variation in the chemical properties of all unique metabolites from both datasets (N = 4292) (31).…”