Metabolomic Profiling, In Vitro Antimalarial Investigation and In Silico Modeling of the Marine Actinobacterium Strain Rhodococcus sp. UR111 Associated with the Soft Coral Nephthea sp

Antiplasmodial potential of phytochemicals from Citrus aurantifolia peels: a comprehensive in vitro and in silico study

Phytochemical investigation of Key lime (Citrus aurantifolia L., F. Rutaceae) peels afforded six metabolites, known as methyl isolimonate acetate (1), limonin (2), luteolin (3), 3`-hydroxygenkwanin (4), myricetin (5), and europetin (6). The structures of the isolated compounds were assigned by 1D NMR. In the case of limonin (2), further 1- and 2D NMR experiments were done to further confirm the structure of this most active metabolite. The antiplasmodial properties of the obtained compounds against the pathogenic NF54 strain of Plasmodium falciparum were assessed in vitro. According to antiplasmodial screening, only limonin (2), luteolin (3), and myricetin (5) were effective (IC50 values of 0.2, 3.4, and 5.9 µM, respectively). We explored the antiplasmodial potential of phytochemicals from C. aurantifolia peels using a stepwise in silico-based analysis. We first identified the unique proteins of P. falciparum that have no homolog in the human proteome, and then performed inverse docking, ΔGBinding calculation, and molecular dynamics simulation to predict the binding affinity and stability of the isolated compounds with these proteins. We found that limonin (2), luteolin (3), and myricetin (5) could interact with 20S a proteasome, choline kinase, and phosphocholine cytidylyltransferase, respectively, which are important enzymes for the survival and growth of the parasite. According to our findings, phytochemicals from C. aurantifolia peels can be considered as potential leads for the development of new safe and effective antiplasmodial agents.

Targeting antimalarial metabolites from the actinomycetes associated with the Red Sea sponge Callyspongia siphonella using a metabolomic method

Malaria is a persistent illness that is still a public health issue. On the other hand, marine organisms are considered a rich source of anti‑infective drugs and other medically significant compounds. Herein, we reported the isolation of the actinomycete associated with the Red Sea sponge Callyspongia siphonella. Using "one strain many compounds" (OSMAC) approach, a suitable strain was identified and then sub-cultured in three different media (M1, ISP2 and OLIGO). The extracts were evaluated for their in-vitro antimalarial activity against Plasmodium falciparum strain and subsequently analyzed by Liquid chromatography coupled with high-resolution mass spectrometry (LC-HR-MS). In addition, MetaboAnalyst 5.0 was used to statistically analyze the LC-MS data. Finally, Molecular docking was carried out for the dereplicated metabolites against lysyl-tRNA synthetase (PfKRS1). The phylogenetic study of the 16S rRNA sequence of the actinomycete isolate revealed its affiliation to Streptomyces genus. Antimalarial screening revealed that ISP2 media is the most active against Plasmodium falciparum strain. Based on LC-HR-MS based metabolomics and multivariate analyses, the static cultures of the media, ISP2 (ISP2-S) and M1 (M1-S), are the optimal media for metabolites production. OPLS-DA suggested that quinone derivatives are abundant in the extracts with the highest antimalarial activity. Fifteen compounds were identified where eight of these metabolites were correlated to the observed antimalarial activity of the active extracts. According to molecular docking experiments, saframycin Y3 and juglomycin E showed the greatest binding energy scores (-6.2 and -5.13) to lysyl-tRNA synthetase (PfKRS1), respectively. Using metabolomics and molecular docking investigation, the quinones, saframycin Y3 (5) and juglomycin E (1) were identified as promising antimalarial therapeutic candidates. Our approach can be used as a first evaluation stage in natural product drug development, facilitating the separation of chosen metabolites, particularly biologically active ones.

Emerging trends and applications of metabolomics in food science and nutrition

The study of all chemical processes involving metabolites is known as metabolomics. It has been developed into an essential tool in several disciplines, such as the study of plant physiology, drug development, human diseases, and nutrition. The field of food science, diagnostic biomarker research, etiological analysis in the field of medical therapy, and raw material quality, processing, and safety have all benefited from the use of metabolomics recently. Food metabolomics includes the use of metabolomics in food production, processing, and human diets. As a result of changing consumer habits and the rising of food industries all over the world, there is a remarkable increase in interest in food quality and safety. It requires the employment of various technologies for the food supply chain, processing of food, and even plant breeding. This can be achieved by understanding the metabolome of food, including its biochemistry and composition. Additionally, Food metabolomics can be used to determine the similarities and differences across crop kinds, as an indicator for tracking the process of ripening to increase crops' shelf life and attractiveness, and identifying metabolites linked to pathways responsible for postharvest disorders. Moreover, nutritional metabolomics is used to investigate the connection between diet and human health through detection of certain biomarkers. This review assessed and compiled literature on food metabolomics research with an emphasis on metabolite extraction, detection, and data processing as well as its applications to the study of food nutrition, food-based illness, and phytochemical analysis. Several studies have been published on the applications of metabolomics in food but further research concerning the use of standard reproducible procedures must be done. The results published showed promising uses in the food industry in many areas such as food production, processing, and human diets. Finally, metabolome-wide association studies (MWASs) could also be a useful predictor to detect the connection between certain diseases and low molecular weight biomarkers.