α-Terpineol: An Aggregation Pheromone in Optatus palmaris (Coleoptera: Curculionidae) (Pascoe, 1889) Enhanced by Its Host-Plant Volatiles.

The Annonaceae fruits weevil (Optatus palmaris) causes high losses to the soursop production in Mexico. Damage occurs when larvae and adults feed on the fruits; however, there is limited research about control strategies against this pest. However, pheromones provide a high potential management scheme for this curculio. Thus, this research characterized the behavior and volatile production of O. palmaris in response to their feeding habits. Olfactometry assays established preference by weevils to volatiles produced by feeding males and soursop. The behavior observed suggests the presence of an aggregation pheromone and a kairomone. Subsequently, insect volatiles sampled by solid-phase microextraction and dynamic headspace detected a unique compound on feeding males increased especially when feeding. Feeding-starvation experiments showed an averaged fifteen-fold increase in the concentration of a monoterpenoid on males feeding on soursop, and a decrease of the release of this compound males stop feeding. GC-MS analysis of volatiles identified this compound as α-terpineol. Further olfactometry assays using α-terpineol and soursop, demonstrated that this combination is double attractive to Annonaceae weevils than only soursop volatiles. The results showed a complementation effect between α-terpineol and soursop volatiles. Thus, α-terpineol is the aggregation pheromone of O. palmaris, and its concentration is enhanced by host-plant volatiles.

HPTLC-Based Chemical Profiling: An Approach to Monitor Plant Metabolic Expansion Caused by Fungal Endophytes.

Fungal endophytes isolated from two latex bearing species were chosen as models to show their potential to expand their host plant chemical diversity. Thirty-three strains were isolated from Alstonia scholaris (Apocynaceae) and Euphorbia myrsinites (Euphorbiaceae). High performance thin layer chromatography (HPTLC) was used to metabolically profile samples. The selected strains were well clustered in three major groups by hierarchical clustering analysis (HCA) of the HPTLC data, and the chemical profiles were strongly correlated with the strains' colony size. This correlation was confirmed by orthogonal partial least squares (OPLS) modeling using colony size as "Y" variable. Based on the multivariate data analysis of the HPTLC data, the fastest growing strains of each cluster were selected and used for subsequent experiments: co-culturing to investigate interactions between endophytes-phytopathogens, and biotransformation of plant metabolites by endophytes. The strains exhibited a high capacity to fight against fungal pathogens. Moreover, there was an increase in the antifungal activity after being fed with host-plant metabolites. These results suggest that endophytes play a role in plant defense mechanisms either directly or by biotransformation/induction of metabolites. Regarding HPTLC-based metabolomics, it has proved to be a robust approach to monitor the interactions among fungal endophytes, the host plant and potential phytopathogens.

Metabolic Profiling of Saponin-Rich Ophiopogon japonicus Roots Based on 1H NMR and HPTLC Platforms.

Ideally, metabolomics should deal with all the metabolites that are found within cells and biological systems. The most common technologies for metabolomics include mass spectrometry, and in most cases, hyphenated to chromatographic separations (liquid chromatography- or gas chromatography-mass spectrometry) and nuclear magnetic resonance spectroscopy. However, limitations such as low sensitivity and highly congested spectra in nuclear magnetic resonance spectroscopy and relatively low signal reproducibility in mass spectrometry impede the progression of these techniques from being universal metabolomics tools. These disadvantages are more notorious in studies of certain plant secondary metabolites, such as saponins, which are difficult to analyse, but have a great biological importance in organisms. In this study, high-performance thin-layer chromatography was used as a supplementary tool for metabolomics. A method consisting of coupling 1H nuclear magnetic resonance spectroscopy and high-performance thin-layer chromatography was applied to distinguish between Ophiopogon japonicus roots that were collected from two growth locations and were of different ages. The results allowed the root samples from the two growth locations to be clearly distinguished. The difficulties encountered in the identification of the marker compounds by 1H nuclear magnetic resonance spectroscopy was overcome using high-performance thin-layer chromatography to separate and isolate the compounds. The saponins, ophiojaponin C or ophiopogonin D, were found to be marker metabolites in the root samples and proved to be greatly influenced by plant growth location, but barely by age variation. The procedure used in this study is fully described with the purpose of making a valuable contribution to the quality control of saponin-rich herbal drugs using high-performance thin-layer chromatography as a supplementary analytical tool for metabolomics research.

Broad range chemical profiling of natural deep eutectic solvent extracts using a high performance thin layer chromatography-based method.

Natural deep eutectic solvents (NADES) made mainly with abundant primary metabolites are being increasingly applied in green chemistry. The advantages of NADES as green solvents have led to their use in novel green products for the food, cosmetics and pharma markets. However, one of the main difficulties encountered in the development of novel products and their quality control arises from their low vapour pressure and high viscosity. These features create the need for the development of new analytical methods suited to this type of sample. In this study, such a method was developed and applied to analyse the efficiency of a diverse set of NADES for the extraction of compounds of interest from two model plants, Ginkgo biloba and Panax ginseng. The method uses high-performance thin-layer chromatography (HPTLC) coupled with multivariate data analysis (MVDA). It was successfully applied to the comparative quali- and quantitative analysis of very chemically diverse metabolites (e.g., phenolics, terpenoids, phenolic acids and saponins) that are present in the extracts obtained from the plants using six different NADES. The composition of each NADES was a combination of two or three compounds mixed in defined molar ratios; malic acid-choline chloride (1:1), malic acid-glucose (1:1), choline chloride-glucose (5:2), malic acid-proline (1:1), glucose-fructose-sucrose (1:1:1) and glycerol-proline-sucrose (9:4:1). Of these mixtures, malic acid-choline chloride (1:1) and glycerol-proline-sucrose (1:1:1) for G. biloba leaves, and malic acid-choline chloride (1:1) and malic acid-glucose (1:1) for P. ginseng leaves and stems showed the highest yields of the target compounds. Interestingly, none of the NADES extracted ginkgolic acids as much as the conventional organic solvents. As these compounds are considered to be toxic, the fact that these NADES produce virtually ginkgolic acid-free extracts is extremely useful. The effect of adding different volumes of water to the most efficient NADES was also evaluated and the results revealed that there is a great influence exerted by the water content, with maximum yields of ginkgolides, phenolics and ginsenosides being obtained with approximately 20% water (w/w).

Investigation of species and environmental effects on rhubarb roots metabolome using 1H NMR combined with high performance thin layer chromatography.

INTRODUCTION: The pharmacological activities of medicinal plants are reported to be due to a wide range of metabolites, therein, the concentrations of which are greatly affected by many genetic and/or environmental factors. In this context, a metabolomics approach has been applied to reveal these relationships. The investigation of such complex networks that involve the correlation between multiple biotic and abiotic factors and the metabolome, requires the input of information acquired by more than one analytical platform. Thus, development of new metabolomics techniques or hyphenations is continuously needed. OBJECTIVES: Feasibility of high performance thin-layer chromatography (HPTLC) were investigated as a supplementary tool for medicinal plants metabolomics supporting 1H nuclear magnetic resonance (1H NMR) spectroscopy. METHOD: The overall metabolic difference of plant material collected from two species (Rheum palmatum and Rheum tanguticum) in different geographical locations and altitudes were analyzed by 1H NMR- and HPTLC-based metabolic profiling. Both NMR and HPTLC data were submitted to multivariate data analysis including principal component analysis and orthogonal partial least square analysis. RESULTS: The NMR and HPTLC profiles showed that while chemical variations of rhubarb are in some degree affected by all the factors tested in this study, the most influential factor was altitude of growth. The metabolites responsible for altitude differentiation were chrysophanol, emodin and sennoside A, whereas aloe emodin, catechin, and rhein were the key species-specific markers. CONCLUSION: These results demonstrated the potential of HTPLC as a supporting tool for metabolomics due to its high profiling capacity of targeted metabolic groups and preparative capability.