Metabolite induction via microorganism co-culture: A potential way to enhance chemical diversity for drug discovery

Microorganisms have a long track record as important sources of novel bioactive natural products, particularly in the field of drug discovery. While microbes have been shown to biosynthesize a wide array of molecules, recent advances in genome sequencing have revealed that such organisms have the potential to yield even more structurally diverse secondary metabolites. Thus, many microbial gene clusters may be silent under standard laboratory growth conditions. In the last ten years, several methods have been developed to aid in the activation of these cryptic biosynthetic pathways. In addition to the techniques that demand prior knowledge of the genome sequences of the studied microorganisms, several genome sequence-independent tools have been developed. One of these approaches is microorganism co-culture, involving the cultivation of two or more microorganisms in the same confined environment. Microorganism co-culture is inspired by the natural microbe communities that are omnipresent in nature. Within these communities, microbes interact through signaling or defense molecules. Such compounds, produced dynamically, are of potential interest as new leads for drug discovery. Microorganism co-culture can be achieved in either solid or liquid media and has recently been used increasingly extensively to study natural interactions and discover new bioactive metabolites. Because of the complexity of microbial extracts, advanced analytical methods (e.g., mass spectrometry methods and metabolomics) are key for the successful detection and identification of co-culture-induced metabolites.     

UHPLC-Q-Orbitrap HR-MS-Based Metabolomics for Profiling the Sida rhombifolia Metabolites with Different Plant Organs and Cultivation Ages

Plant organs and cultivation ages can result in different compositions and concentration levels of plant metabolites. The metabolite profile of plants can be determined using liquid chromatography. This study determined the metabolite profiles of leaves, stems, and roots of Sida rhombifolia at different cultivation ages at 3, 4, and 5 months post-planting (MPP) using liquid chromatography-mass spectrometry/mass spectrometry (LC/MS/MS). The results identified that 41 metabolites in S. rhombifolia extract for all plant organs and cultivation ages. We successfully identified approximately 36 (leaves), 22 (stems), and 18 (roots) compounds in all extract. Using principal component analysis (PCA) with peak area as the variable, we clustered all sample extracts based on plant organs and cultivation ages. As a result of PCA, S. rhombifolia extracts were grouped according to plant organs and cultivation ages. In conclusion, a clear difference in the composition and concentration levels of metabolites was observed in the leaves, stems, and roots of S. rhombifolia harvested at 3-, 4-, and 5-MPP.     

Metabolomics driven analysis of artichoke leaf and its commercial products via UHPLC–q-TOF-MS and chemometrics

The demand to develop efficient and reliable analytical methods for the quality control of herbal medicines and nutraceuticals is on the rise, together with an increase in the legal requirements for safe and consistent levels of active principles. Here, we describe an ultra-high performance liquid chromatography method (UHPLC) coupled with quadrupole high resolution time of flight mass spectrometry (qTOF-MS) analysis for the comprehensive measurement of metabolites from three Cynara scolymus (artichoke) cultivars: American Green Globe, French Hyrious, and Egyptian Baladi. Under optimized conditions, 50 metabolites were simultaneously quantified and identified including: eight caffeic acid derivatives, six saponins, 12 flavonoids and 10 fatty acids. Principal component analysis (PCA) was used to define both similarities and differences among the three artichoke leaf cultivars. In addition, batches from seven commercially available artichoke market products were analysed and showed variable quality, particularly in caffeic acid derivatives, flavonoid and fatty acid contents. PCA analysis was able to discriminate between various preparations, including differentiation between various batches from the same supplier. To the best of our knowledge, this study provides the first approach utilizing UHPLC–MS based metabolite fingerprinting to reveal secondary metabolite compositional differences in artichoke leaf extracts.