Analysing metabolomes from various natural sources is a task that requires methods providing high chromatographic resolution for detailed metabolite profiling or high throughput for rapid fingerprinting for metabolomics [1,2]. Furthermore these methods should give on-line spectroscopic information for the identification of each individual metabolite for dereplication purposes. In this respect the introduction of UHPLC has allowed a remarkable decrease in analysis time and increase in peak capacity, sensitivity and reproducibility compared to conventional HPLC. In complement to this powerful chromatographic method, the introduction of benchtop high resolution MS instruments that provide sensitive detection and accurate MS and MS/MS information for dereplication has been key for metabolomics. Recently the development of neural network mining methods for metabolite identification have revolutionized conventional MS/MS database search for establishing link between metabolites having similar fragmentation pattern that greatly help metabolite annotation. For unambiguous de-novo identification, LC-MS targeted isolation together with at-line microNMR approaches provide low microgram level of metabolites sufficient for acquiring a full set of 1D and 2D NMR spectra. Such information complements well the search in MS and chemotaxonomic data bases for dereplication. In addition to these methods, HPLC activity-based profiling provides information on the bioactivity of metabolites of interest, directly at the analytical scale, speeding up the drug discovery process in natural product research. The impact of these technologies in NP research studies and future trends will be discussed. This will be illustrated by examples or our latest metabolomics and bioactivity-guided isolation studies on plants and microorganisms.
Wolfender JL, Rudaz S, Choi YH, Kim HK. Plant metabolomics: from holistic data to relevant biomarkers. Curr. Med. Chem. 2013 20: 1056-90.
Wolfender J-L, Marti G, Thomas A, Bertrand S. Current approaches and challenges for the metabolite profiling of complex natural extracts. J Chromatogr A 2015 1382: 136-164.
Danilo Corradini,1 Isabella Nicoletti,1 Imre Molnár2
1 National Research Council, Institute of Chemical Methodologies, Area della Ricerca di Roma 1, 00015 Monterotondo, Rome, Italy
Plant secondary metabolites are organic compounds produced by plants, which are not involved in the growth, photosynthesis, reproduction and other primary functions of the plants but are believed to have a role in defence mechanisms, such as protection against herbivores, pests and pathogens. Phenolic compounds are one of the main classes of secondary metabolites and because are widely distributed in the plant kingdom form an integral part of human diet. In addition to confer specific sensorial characteristics to plant-derived foods and/or beneficial effects on human health, phenolic compounds are also biomolecules with pharmacological activity employed in phytotherapeutic medicine. The identification and quantification of these target compounds in plants tissues and agro-food matrices is a challenging task, continuously requesting the development of more robust, efficient and sensitive instrumental analytical techniques. This communication discusses fundamental and practical aspects of both reversed phase high performance liquid chromatography (RP-HPLC) and capillary zone electrophoresis (CZE) tailored for the analysis of plant secondary metabolites. The communication reports the results of our recent studies carried out to evaluate the influence of various operational parameters and experimental conditions employed in CZE and in RP-HPLC on the separation performance of phenolic compounds and other secondary metabolites in plant tissues and agro-food matrices. Because both RP-HPLC and CZE require the use of a liquid phase, whose composition plays a fundamental role on the separation mechanisms and performance, most of our investigations has been focused on the selection of the proper composition of the liquid phase, which, in the case of RP-HPLC, has been optimized by a quality by design approach.
Metabolomics and Lipidomics, involve targeted and untargeted analysis of various endogenous biomolecules, in complex samples estimated 5000-20,000 metabolites in a single plant. Thus multiple modes of analysis are needed to enable identification as well as quantitation to get a better understanding of these thousands Metabolites.
NMR, GC/MS, UHPLC/MS, USFC/MS are currently used for metabolome analysis, lately advancements in Ion Mobility separation, (a gas-phase separation tool) namely Traveling-Wave Ion Mobility (TWIM) combined with high-sensitivity mass spectrometry QTOF-MS, have been used to set the stage for a myriad of metabolomics studies, in plants and other organisms.
Here we describe the use of UHPLC - TWIM- QTOF-MS, to generated, Retention Times, Drift times, and accurate Mass. For the polar and semi polar metabolites. In addition, we used Super Critical Fluid Chromatography USFC-TWIM-QTOF-MS for the non-polar and semi polar metabolites analysis.
Plant and Algae samples data, were analyzed by a dedicated software tool, using multiple parameters such as, Retention Time, exact mass, MS/MS fragments, isotope distribution, and drift times, in order to achieve a three dimension resolution and more reliable data. That enables searching external databases, such as: LipidBlast, ChemSpider, METLIN, Elemental Composition, and our own database.
With the added parameters and the software tool, we found many more lipids in our samples, than with our previous method. We hope to verify some of these in the near future.
1 University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Department of Chemistry and Biochemistry, Mănăstur 3-5 Cluj-Napoca, 400372, Romania
Fruits and berries contains large amount of xanthophylls which are often esterified with various fatty acids . The saponification procedure, usually performed prior chromatographic separation, also removes the acyl moieties of xanthophyll esters and unable the proper characterization of native carotenoid extracts from plant materials.
The fruits of Hippophae rhamnoides (sea buckthorn), Physalis alkekengi (Chinese lanterns) and Prunus armeniaca (apricot) fruits were used for the analysis of esterified xanthophylls. Characterization of unsaponified extracts was performed by HPLC-DAD-APCI-MS on C18 and C30 RP columns. Pure esters of zeaxanthin (Z) and β-cryptoxanthin (BCR) with myristic (M), palmitic (P), oleic (O) and linoleic (L) acids were obtained by semi-synthesis and used for identification and stability studies. The major xanthophylls in all three fruits are Z and BCR, small amounts of lutein being identified only in sea buckthorn berries. In the sepals of Physalis alkekengi Z and β-cryptoxanthin was almost completely esterified with M and P acids. Sea buckthorn berries of various cultivars were analyzed and found to contain a significantly higher number (14) of both mono- and diesters. Z was mainly esterified with P acid but esters with O and palmitoleic acids were also found. Interestingly, lutein was the only xanthophyll esterified with polyunsaturated fatty acids (L, hexadecadienoic). Apricot fruits are rich sources of β-carotene and the only important xanthophyll is BCR. Investigations on several cultivars showed a high variability in carotenoid and esters content and profile. The major fatty acids esterifying BCR are P, stearic and lauric acids but small amounts of esters with O, L and linolenic acids were also detected. Stability tests performed on pure esters and on sea buckthorn fruits showed a better stability of esterified xanthophylls compared to the free form during thermal treatment and storage.
This work was supported by a grant of the Romanian National Authority for Scientific Research CNCS-UEFISCDI, project PN-II-ID-PCE-2011-3-0721
Jelena Trifković,1 Petar Ristivojević,2 Filip Andrić,1 Dušanka Milojković-Opsenica1
1 University of Belgrade, Faculty of Chemistry, P.O. Box 51, 11158 Belgrade, Serbia
High-performance thin-layer chromatography (HPTLC), as a method of chemical fingerprinting, is suitable for rapid assessment of the authenticity of the natural products. It is often used as alternative to HPLC for monitoring the production of extracts and final products. Considering the introduction of biological fingerprinting analysis, as a method of screening the natural samples for the presence of most active compounds, use of chemometric classification methods, application of powerful scanning and image capturing and processing devices and algorithms, advancement in development of novel microstructured and nano monolithic stationary phases as well as various separation modalities, HPTLC fingerprinting is becoming attractive and fruitful field of separation science. Development of efficient and reliable fingerprint TLC method requires chemometric approach at several levels starting with application of experimental design and optimization techniques for the separation step, followed by data acquisition, and signal manipulation, and finally solving classification and modeling problem. However, serious lack in application of aforementioned techniques still remains a major shortcoming of majority fingerprint studies.1 The opportunities of contemporary planar chromatography in pattern recognition and fingerprint analysis will be presented on the example of HPTLC analysis of propolis, pollen and plant resin samples.2 An application of multivariate image analysis and pattern recognition methods will be discussed in detail.
This work has been supported by the Ministry of Education, Science and Technological Development of Serbia, grant no. 172017, Slovenian Research Agency, project P1-0005, Center of Excellence for Molecular Food Sciences, Faculty of Chemistry University of Belgrade, and ENFIST Centre of Excellence.
Dušanka Milojković-Opsenica, Petar Ristivojević, Filip Andrić, Jelena Trifković, Chromatographia, 76 (19-20) (2013) 1239-1247.
P. Ristivojević, F. Lj. Andrić, J. Đ. Trifković, I. Vovk, Lj. Ž. Stanisavljević, Ž. Lj. Tešić, D. M. Milojković-Opsenica, Journal of Chemometrics, 28 (2014) 301-310.