Synthetic biology identifies the minimal gene set required for paclitaxel biosynthesis in a plant chassis

The diterpenoid paclitaxel (Taxol) is a chemotherapy medication widely used as a first-line treatment against several types of solid cancers. The supply of paclitaxel from natural sources is limited. However, missing knowledge about the genes involved in several specific metabolic steps of paclitaxel biosynthesis has rendered it difficult to engineer the full pathway. In this study, we used a combination of transcriptomics, cell biology, metabolomics, and pathway reconstitution to identify the complete gene set required for the heterologous production of paclitaxel. We identified the missing steps from the current model of paclitaxel biosynthesis and confirmed the activity of most of the missing enzymes via heterologous expression in Nicotiana benthamiana. Notably, we identified a new C4β-C20 epoxidase that could overcome the first bottleneck of metabolic engineering. We used both previously characterized and newly identified oxomutases/epoxidases, taxane 1β-hydroxylase, taxane 9α-hydroxylase, taxane 9α-dioxygenase, and phenylalanine-CoA ligase, to successfully biosynthesize the key intermediate baccatin III and to convert baccatin III into paclitaxel in N. benthamiana. In combination, these approaches establish a metabolic route to taxoid biosynthesis and provide insights into the unique chemistry that plants use to generate complex bioactive metabolites

Open Power System Data - Frictionless data for electricity system modelling

The quality of electricity system modelling heavily depends on the input data used. Although a lot of data is publicly available, it is often dispersed, tedious to process and partly contains errors. We argue that a central provision of input data for modelling has the character of a public good: it reduces overall societal costs for quantitative energy research as redundant work is avoided, and it improves transparency and reproducibility in electricity system modelling. This paper describes the Open Power System Data platform that aims at realising the efficiency and quality gains of centralised data provision by collecting, checking, processing, aggregating, documenting and publishing data required by most modellers. We conclude that the platform can provide substantial benefits to energy system analysis by raising efficiency of data pre-processing, providing a method for making data pre-processing for energy system modelling traceable, flexible and reproducible and improving the quality of original data published by data providers.Comment: This is the postprint version of the articl

MOVING: A User-Centric Platform for Online Literacy Training and Learning

Part of the Progress in IS book series (PROIS)In this paper, we present an overview of the MOVING platform, a user-driven approach that enables young researchers, decision makers, and public administrators to use machine learning and data mining tools to search, organize, and manage large-scale information sources on the web such as scientific publications, videos of research talks, and social media. In order to provide a concise overview of the platform, we focus on its front end, which is the MOVING web application. By presenting the main components of the web application, we illustrate what functionalities and capabilities the platform offer its end-users, rather than delving into the data analysis and machine learning technologies that make these functionalities possible