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Combining Medicinal Plant In Vitro Culture with Machine Learning Technologies for Maximizing the Production of Phenolic Compounds.

ABSTRACT: We combined machine learning and plant in vitro culture methodologies as a novel approach for unraveling the phytochemical potential of unexploited medicinal plants. In order to induce phenolic compound biosynthesis, the in vitro culture of three different species of Bryophyllum under nutritional stress was established. To optimize phenolic extraction, four solvents with different MeOH proportions were used, and total phenolic content (TPC), flavonoid content (FC) and radical-scavenging activity (RSA) were determined. All results were subjected to data modeling with the application of artificial neural networks to provide insight into the significant factors that influence such multifactorial processes. Our findings suggest that aerial parts accumulate a higher proportion of phenolic compounds and flavonoids in comparison to roots. TPC was increased under ammonium concentrations below 15 mM, and their extraction was maximum when using solvents with intermediate methanol proportions (55-85%). The same behavior was reported for RSA, and, conversely, FC was independent of culture media composition, and their extraction was enhanced using solvents with high methanol proportions (>85%). These findings confer a wide perspective about the relationship between abiotic stress and secondary metabolism and could serve as the starting point for the optimization of bioactive compound production at a biotechnological scale.

SUBMITTER: Garcia-Perez P

PROVIDER: S-EPMC7139750 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Combining Medicinal Plant In Vitro Culture with Machine Learning Technologies for Maximizing the Production of Phenolic Compounds.

García-Pérez Pascual P Lozano-Milo Eva E Landín Mariana M Gallego Pedro Pablo PP

Antioxidants (Basel, Switzerland) 20200304 3

We combined machine learning and plant in vitro culture methodologies as a novel approach for unraveling the phytochemical potential of unexploited medicinal plants<i>.</i> In order to induce phenolic compound biosynthesis, the in vitro culture of three different species of <i>Bryophyllum</i> under nutritional stress was established. To optimize phenolic extraction, four solvents with different MeOH proportions were used, and total phenolic content (TPC), flavonoid content (FC) and radical-scave ...[more]

PMID: 32143282

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Project description:Juniperus procera is a natural source of bioactive compounds with the potential of antitumor, antimicrobial, insecticidal, antifungal, and antioxidant activities. An optimization method was developed for total phenolic content (TPC), total flavonoid content (TFC), and total tannin content (TTC) in leaf and seed extract of Juniperus procera. Organic solvents (methanol (99.8%), ethanol (99%), and acetone (99.5%)), and deionized water (DI) were used for extraction. The estimation of TPC, TFC, and TTC in plant materials was carried out using UV-spectrophotometer and HPLC with the standards gallic acid, quercetin, and tannic acid. Recovery of TPC in leaf extract ranged from 2.9 to 9.7 mg GAE/g DW, TFC from 0.9 to 5.9 mg QE/g DW, and TTC ranged from 1.5 to 4.3 mg TA/g DW while the TPC value in the seed extract ranged from 0.53 to 2.6 mg GAE/g DW, TFC from 0.5 to 1.6 mg QE/g DW, and TTC ranged from 0.5 to 1.4 mg TA/g DW. This result revealed that methanol is the best solvent for recovery of the TPC value (9.7 mg) from leaf extract in comparison to other solvents. Ethanol recorded the highest result of TFC (5.9 mg) in leaf extract among the solvents whereas acetone was the best for TTC yield recovery from leaf extract (4.3 mg). In the case of the seed extract, ethanol was the best solvent for both TPC (2.6 mg), and TFC (1.6 mg) recovery in comparison to other solvents. Total tannin content in methanol resulted in significant recovery from seed extract (1.4 mg). Separation and quantification of gallic acid, quercetin, and tannic acid in plant materials were undertaken using HPLC. Gallic acid in leaf and seed of J. procera ranged from 6.6 to 9.2, 6.5 to 7.2 µg/g DW, quercetin from 6.3 to 18.2, 0.9 to 4.2 µg/g DW, and tannic acid from 16.2 to 29.3, 6.6 to 9.3 µg/g DW, respectively. Solvents have shown a significant effect in the extraction of phenolic compounds. Moreover, phytochemicals in plant materials were identified using GC-MS and resulted in very important bioactive compounds, which include anti-inflammatory, antibacterial, and antitumor agents such as ferruginol, phenanthrene, and n-hexadecanoic acid. In conclusion, the optimal solvent for extraction depends on the part of the plant material and the compounds that are to be isolated.

Dataset Information

Combining Medicinal Plant In Vitro Culture with Machine Learning Technologies for Maximizing the Production of Phenolic Compounds.

Publications

Combining Medicinal Plant In Vitro Culture with Machine Learning Technologies for Maximizing the Production of Phenolic Compounds.

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