Literature DB >> 27473512

The use of chemometrics to study multifunctional indole alkaloids from Psychotria nemorosa (Palicourea comb. nov.). Part I: Extraction and fractionation optimization based on metabolic profiling.

Luiz C Klein-Júnior1, Johan Viaene2, Juliana Salton3, Mariana Koetz3, André L Gasper4, Amélia T Henriques3, Yvan Vander Heyden5.   

Abstract

Extraction methods evaluation to access plants metabolome is usually performed visually, lacking a truthful method of data handling. In the present study the major aim was developing reliable time- and solvent-saving extraction and fractionation methods to access alkaloid profiling of Psychotria nemorosa leaves. Ultrasound assisted extraction was selected as extraction method. Determined from a Fractional Factorial Design (FFD) approach, yield, sum of peak areas, and peak numbers were rather meaningless responses. However, Euclidean distance calculations between the UPLC-DAD metabolic profiles and the blank injection evidenced the extracts are highly diverse. Coupled with the calculation and plotting of effects per time point, it was possible to indicate thermolabile peaks. After screening, time and temperature were selected for optimization, while plant:solvent ratio was set at 1:50 (m/v), number of extractions at one and particle size at ≤180μm. From Central Composite Design (CCD) results modeling heights of important peaks, previously indicated by the FFD metabolic profile analysis, time was set at 65min and temperature at 45°C, thus avoiding degradation. For the fractionation step, a solid phase extraction method was optimized by a Box-Behnken Design (BBD) approach using the sum of peak areas as response. Sample concentration was consequently set at 150mg/mL, % acetonitrile in dichloromethane at 40% as eluting solvent, and eluting volume at 30mL. Summarized, the Euclidean distance and the metabolite profiles provided significant responses for accessing P. nemorosa alkaloids, allowing developing reliable extraction and fractionation methods, avoiding degradation and decreasing the required time and solvent volume.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Euclidean distance; Experimental design; Metabolic profiling; Metabolomics; Phytochemical analysis

Mesh:

Substances:

Year:  2016        PMID: 27473512     DOI: 10.1016/j.chroma.2016.07.030

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  5 in total

1.  Untargeted LC-MS metabolomic studies of Asteraceae species to discover inhibitors of Leishmania major dihydroorotate dehydrogenase.

Authors:  Lucas A Chibli; Annylory L Rosa; Maria Cristina Nonato; Fernando B Da Costa
Journal:  Metabolomics       Date:  2019-04-04       Impact factor: 4.290

2.  Oscillatoria sp. as a Potent Anti-phytopathogenic Agent and Plant Immune Stimulator Against Root-Knot Nematode of Soybean cv. Giza 111.

Authors:  Rehab Y Ghareeb; Nader R Abdelsalam; Dahlia M El Maghraby; Mahmoud H Ghozlan; Eman El-Argawy; Reda A I Abou-Shanab
Journal:  Front Plant Sci       Date:  2022-05-26       Impact factor: 6.627

3.  A protocol for high-throughput, untargeted forest community metabolomics using mass spectrometry molecular networks.

Authors:  Brian E Sedio; Cristopher A Boya P; Juan Camilo Rojas Echeverri
Journal:  Appl Plant Sci       Date:  2018-04-02       Impact factor: 1.936

4.  Phytochemistry by design: a case study of the chemical composition of Ocotea guianensis optimized extracts focused on untargeted metabolomics analysis.

Authors:  Ananda da Silva Antonio; Ana Tayná Chaves Aguiar; Gustavo Ramalho Cardoso Dos Santos; Henrique Marcelo Gualberto Pereira; Valdir Florêncio da Veiga-Junior; Larissa Silveira Moreira Wiedemann
Journal:  RSC Adv       Date:  2020-01-21       Impact factor: 4.036

5.  Ultrasound-assisted extraction optimization and validation of an HPLC-DAD method for the quantification of polyphenols in leaf extracts of Cecropia species.

Authors:  Andrés Rivera-Mondragón; Géraldine Broeckx; Sebastiaan Bijttebier; Tania Naessens; Erik Fransen; Filip Kiekens; Catherina Caballero-George; Yvan Vander Heyden; Sandra Apers; Luc Pieters; Kenn Foubert
Journal:  Sci Rep       Date:  2019-02-14       Impact factor: 4.379

  5 in total

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