South America holds the greatest diversity of native daisies (Asteraceae) in the world: an updated catalogue supporting continental-scale conservation.

Asteraceae is the world's richest plant family and is found on all continents, in environments ranging from the coast to the highest mountains. The family shows all growth forms and, as in other angiosperm families, species richness is concentrated in tropical regions. South America has the highest diversity of Asteraceae in the world, yet taxonomic and distributional knowledge gaps remain. This study compiles an updated catalog of Asteraceae native to South America, based on national and regional checklists and ongoing large-scale flora projects. The resulting checklist includes a total of 6,940 species and 564 genera native to South America to date, which represent about a quarter of the family's global diversity. Countries already considered to be megadiverse show the greatest diversity, such as Brazil with 2,095 species, followed by Peru (1,588), Argentina (1,377), and Colombia (1,244), with this diversity mainly focused on the Brazilian Highlands and the Andes. Species endemism also peaks in Brazil, but Sørensen distances reveal the Chilean flora to be eminently different from the rest of the continent. Tribes better represented in the continent are Eupatorieae, Senecioneae and Astereae, also with a remarkably presence of entirely South American subfamilies representing earliest diverging lineages of the Asteraceae, such as Barnadesioideae, Wunderlichioideae, Famatinanthoideae, and Stifftioideae. It is estimated that the discovery and description curves have not yet stabilized, and the number of species is likely to increase by 5 to 10% in the coming years, posing major challenges to continental-scale conservation.

Lychnophora pinaster in endangered campos rupestres: phenolic compounds and population ecogeography.

Lychnophora pinaster, known as arnica-mineira, is endemic to campos rupestres, at risk of extinction. The present study aimed to characterize the ecogeography and phenolic constituents of 11 L. pinaster populations collected in the mesoregions North, Jequitinhonha, Metropolitan of Belo Horizonte and Campos das Vertentes in the state of Minas Gerais, Brazil. Phenolic constituents were identified and quantified by Ultra-high performance liquid chromatography- mass spectrometry. Lychnophora pinaster occurs in sites at high altitude (700 and 1498 m), annual rainfall of up to 1455 m, soils with low fertility and predominantly loamy texture. Therefore, it can be considered tolerant to acidic soils, with low availability of nutrient. The most abundant substances in all populations were vitexin (18 - 1345 ng/g) and chlorogenic acid (60 - 767 ng/g). The 11 populations formed four groups in relation to the phenolic constituents, with group 1 consisting of the populations of the North Mesoregion (GM, OD) and Jetiquinhonha (DIMa), group 2, the Metropolitan of Belo Horizonte (SRM, NLSC, SM, RPS, CTRA), group 3, the North Mesoregion (ODMa and DI), and group 4, the Campos das Vertentes (CC). Among the populations, only those from the Metropolitan of Belo Horizonte showed correlation of soil properties with phenolic constituents.

High-Resolution Liquid Chromatography-Mass Spectrometry-Based Metabolomics for the Classification of Chuquiraga (Barnadesioideae, Asteraceae): New Phenylpropanoid Derivatives as Chemical Markers for Chuquiraga spinosa.

Despite their relatively poorly investigated phytochemistry, species of the genus Chuquiraga are widely commercialized. The present study reports the use of a high-resolution liquid chromatography-mass spectrometry-based metabolomics approach coupled with exploratory and supervised multivariate statistical analyses for species classification and chemical marker identification of four species of Chuquiraga (C. jussieui, C. weberbaueri, C. spinosa, and Chuquiraga sp.) from Ecuador and Peru. Based on these analyses, a high percentage of correct classifications (87% to 100%) allowed the prediction of the taxonomic identity of Chuquiraga species. Through the metabolite selection process, several key constituents with the potential to be chemical markers were identified. Samples of C. jussieui displayed alkyl glycosides and triterpenoid glycosides as discriminating metabolites, while Chuquiraga sp. displayed high concentrations of p-hydroxyacetophenone, p-hydroxyacetophenone 4-O-glucoside, p-hydroxyacetophenone 4-O-(6-O-apiosyl)-glucoside, and quinic acid ester derivatives as the main metabolites. Caffeic acid was characteristic for C. weberbaueri samples, whereas C. spinosa displayed higher concentrations of the following new phenylpropanoid ester derivatives: 2-O-caffeoyl-4-hydroxypentanedioic acid (24), 2-O-p-coumaroyl-4-hydroxypentanedioic acid (34), 2-O-feruloyl-4-hydroxypentanedioic acid (46), 2,4-O-dicaffeoylpentanedioic acid (71), and 2-O-caffeoyl-4-O-feruloylpentanedioic acid (77).

Metabolomic analysis applied to chemosystematics and evolution of megadiverse Brazilian Vernonieae (Asteraceae).

Vernonia sensu lato is the largest and most complex genus of the tribe Vernonieae (Asteraceae). The tribe is chemically characterized by the presence of sesquiterpene lactones and flavonoids. Over the years, several taxonomic classifications have been proposed for Vernonia s.l. and for the tribe; however, there has been no consensus among the researches. According to traditional classification, Vernonia s.l. comprises more than 1000 species divided into sections, subsections and series (sensu Bentham). In a more recent classification, these species have been segregated into other genera and some subtribes were proposed, while the genus Vernonia sensu stricto was restricted to 22 species distributed mainly in North America (sensu Robinson). In this study, species from the subtribes Vernoniinae, Lepidaploinae and Rolandrinae were analyzed by UHPLC-UV-HRMS followed by multivariate statistical analysis. Data mining was performed using unsupervised (HCA and PCA) and supervised methods (OPLS-DA). The HCA showed the segregation of the species into four main groups. Comparing the HCA with taxonomical classifications of Vernonieae, we observed that the groups of the dendogram, based on metabolic profiling, were in accordance with the generic classification proposed by Robinson and with previous phylogenetic studies. The species of the genera Stenocephalum, Stilpnopappus, Strophopappus and Rolandra (Group 1) were revealed to be more related to the species of the genus Vernonanthura (Group 2), while the genera Cyrtocymura, Chrysolaena and Echinocoryne (Group 3) were chemically more similar to the genera Lessingianthus and Lepidaploa (Group 4). These findings indicated that the subtribes Vernoniinae and Lepidaploinae are non-chemically homogeneous groups and highlighted the application of untargeted metabolomic tools for taxonomy and as indicators of species evolution. Discriminant compounds for the groups obtained by OPLS-DA were determined. Groups 1 and 2 were characterized by the presence of 3',4'-dimethoxyluteolin, glaucolide A and 8-tigloyloxyglaucolide A. The species of Groups 3 and 4 were characterized by the presence of putative acacetin 7-O-rutinoside and glaucolide B. Therefore, untargeted metabolomic approach combined with multivariate statistical analysis, as proposed herein, allowed the identification of potential chemotaxonomic markers, helping in the taxonomic classifications.

A metabolomic protocol for plant systematics by matrix-assisted laser-desorption/ionization time-of flight mass spectrometry.

Matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF MS) has been widely used for the identification and classification of microorganisms based on their proteomic fingerprints. However, the use of MALDI-TOF MS in plant research has been very limited. In the present study, a first protocol is proposed for metabolic fingerprinting by MALDI-TOF MS using three different MALDI matrices with subsequent multivariate data analysis by in-house algorithms implemented in the R environment for the taxonomic classification of plants from different genera, families and orders. By merging the data acquired with different matrices, different ionization modes and using careful algorithms and parameter selection, we demonstrate that a close taxonomic classification can be achieved based on plant metabolic fingerprints, with 92% similarity to the taxonomic classifications found in literature. The present work therefore highlights the great potential of applying MALDI-TOF MS for the taxonomic classification of plants and, furthermore, provides a preliminary foundation for future research.