Phytochemical valorization of bryophyllum spp. Medicinal plants combining biotechnological and machine learning tools

Abstract

In this thesis project, the in vitro culture of three medicinal species belonging to Bryophyllum subgenus (genus Kalanchoe, Crassulaceae) will be established. Bryophyllum species present a highly valuable phytochemical interest (Bryophyllum daigremontianum, Bryophyllum tubiflorum and Bryophyllum x houghtonii), as a consequence of their use in traditional medicine, across Africa, South America and Asia. The bioactive properties linked to Bryophyllum, i.e.: antioxidant, cytotoxic and antineoplastic activities, have been attributed to several compounds, as a result of secondary metabolite biosythesis, as it is the case of phenolic compounds and bufadienolides. In order to study such properties, the establishment of in vitro culture is a crucial step for the application of biotechnological strategies on Bryophyllum. Nutritional stress will be applied to in vitro-cultured individuals, thus increasing their secondary metabolism rate and, consequently, getting a high amount of plant with an increased phenolic production. Furthermore, the Bryophyllum cell culture will be carried out, by the establishment of callus and cell suspension cultures, with the aim of enabling the use of Bryophyllum cultures as a biotechnological tool for the mass production of phenolic compounds, thanks to the process of elicitation, which constitutes an efficient strategy for the induction of secondary metabolism, by the use of elicitors, such as jasmonates. The phenolic compounds found in Bryophyllum extracts will be later identified by liquid chromatography coupled to mass spectrometry and their efficiency and distribution as antioxidant agents, will be analyzed through oil-water biphasic systems. These findings will reveal an approximation of their real distribution within biological systems, as they are highly compartmentalized. Finally, all studied processes will be modelled, based on the application of artifical intelligence techniques, associated to neurofuzzy logic through artificial neural networks, with the purpose of achieving the optimum parameters and conditions that take place across all the process of studying the biotechnological potential associated to Bryophyllum.