1.
Novel trends for producing plant triterpenoids in yeast.
Sun, W, Qin, L, Xue, H, Yu, Y, Ma, Y, Wang, Y, Li, C
Critical reviews in biotechnology. 2019;(5):618-632
Abstract
Triterpenoids possess versatile biological activities including antiviral, anticancer, and hepatoprotective activities. They are widely used in medicine and other health-related fields. However, current production of such compounds relies on plant culture and extraction, which brings about concerns for environmental, ecological, and infield problems. With increasing awareness of environmental sustainability, various microbes have been engineered to produce natural products, in which yeast turned out to be feasible for the heterologous biosynthesis of triterpenoids on account of its inherent advantages such as the robustness, safety, and sufficient precursor supplementation. This review has focused on recent progress regarding the biosynthesis of triterpenoids in yeast. The key enzymes to reconstruct the triterpenoid pathways in yeast, include: oxidosqualene cyclases, cytochrome P450s and UDP-glycosyltransferases are systematically presented. We then discuss recent metabolic engineering strategies and future prospects of protein engineering, pathway compartmentalization, product transportation, and other aspects for triterpenoid production in yeast.
2.
Chemical Differentiation of Pseudostellariae Radix from Different Cultivated Fields and Germplasms by UPLC-Triple TOF-MS/MS Coupled with Multivariate Statistical Analysis.
Hua, YJ, Hou, Y, Wang, SN, Ma, Y, Zou, LS, Liu, XH, Luo, YY, Liu, JX
Natural product communications. 2016;(12):1827-1831
Abstract
To explore rapidly the potential chemical markers for differentiating Pseudostellariae Radix from different cultivated fields :and germplasms, a method is proposed based on ultra-performance liquid chromatographytriple time-of-flight mass/mass spectrometry (UPLC-Triple TOF-MS/MS) coupled with multivariate statistical analysis. Peak matching, peak alignment, and noise filtering were used in analyzing mass spectrometric data. Accurate m/z value analysis of MS data based on software of database search and MS/MS fragment analysis were applied to identify constituents. The obtained. data were statistically analyzed with hierarchical cluster analysis (HCA), principal component analysis (PCA), and partial least squared-discriminant analysis (PLS-DA) to compare the differences among these samples. The PLS-DA loading plot obtained from all mass data showed that 21 compounds were identified as the potential chemical markers to characterize the samples. The results provide experimental data to reveal the influence of ecological environments and germplasms on metabolite biosynthesis in Pseudostellariae Radix.