Bioluminescent reporters for catabolic gene expression and pollutant bioavailability

The application of visualized catabolic nah-gene expression using a luxCDABE gene fusion provides a valuable method to measure quantitatively and specifically naphthalene and salicylate bioavailability. It has been demonstrated that the physiological state of the test culture together with the intrinsic regulation mechanisms of the naphthalene degradation pathway as well as the physiological aspects of the lux gene fusion have to be taken into account. The method presented provides a high potential for in situ bioprocess monitoring. In addition, the results obtained with immobilized cells provide a basis for the development of biosensors for environmental applications in specific pollutant monitoring in waste streams and soil slurry systems but, as a general method, also for more conventional biotechnological process control. 8 refs., 2 figs., 1 tab

A destabilized bacterial luciferase for dynamic gene expression studies

Fusions of genetic regulatory elements with reporter genes have long been used as tools for monitoring gene expression and have become a major component in synthetic gene circuit implementation. A major limitation of many of these systems is the relatively long half-life of the reporter protein(s), which prevents monitoring both the initiation and the termination of transcription in real-time. Furthermore, when used as components in synthetic gene circuits, the long time constants associated with reporter protein decay may significantly degrade circuit performance. In this study, short half-life variants of LuxA and LuxB from Photorhabdus luminescens were constructed in Escherichia coli by inclusion of an 11-amino acid carboxy-terminal tag that is recognized by endogenous tail-specific proteases. Results indicated that the addition of the C-terminal tag affected the functional half-life of the holoenzyme when the tag was added to luxA or to both luxA and luxB, but modification of luxB alone did not have a significant effect. In addition, it was also found that alteration of the terminal three amino acid residues of the carboxy-terminal tag fused to LuxA generated variants with half-lives of intermediate length in a manner similar to that reported for GFP. This report is the first instance of the C-terminal tagging approach for the regulation of protein half-life to be applied to an enzyme or monomer of a multi-subunit enzyme complex and will extend the utility of the bacterial luciferase reporter genes for the monitoring of dynamic changes in gene expression

Forecasting the 2016 US Presidential Elections Using Sentiment Analysis

Part 4: Social Media and Web 3.0 for SmartnessInternational audienceThe aim of this paper is to make a zealous effort towards true prediction of the 2016 US Presidential Elections. We propose a novel technique to predict the outcome of US presidential elections using sentiment analysis. For this data was collected from a famous social networking website (SNW) Twitter in form of tweets within a period starting from September 1, 2016 to October 31, 2016. To accomplish this mammoth task of prediction, we build a model in WEKA 3.8 using support vector machine which is a supervised machine learning algorithm. Our results showed that Donald Trump was likely to emerge winner of 2016 US Presidential Elections

pvsR: An Open Source Interface to Big Data on the American Political Sphere

Digital data from the political sphere is abundant, omnipresent and more and more directly accessible through the Internet. Project Vote Smart (PVS) is a prominent example of this big public data and covers various aspects of U.S. politics in astonishing detail. Despite the vast potential of PVS’ data for political science, economics, and sociology, it is hardly used in empirical research. The systematic compilation of semi-structured data can be complicated and time consuming as the data format is not designed for conventional scientific research. This paper presents a new tool that makes the data easily accessible to a broad scientific community. We provide the software called pvsR as an add-on to the R programming environment for statistical computing. This open source interface (OSI) serves as a direct link between a statistical analysis and the large PVS database. The free and open code is expected to substantially reduce the cost of research with PVS’ new big public data in a vast variety of possible applications. We discuss its advantages vis-a`-vis traditional methods of data generation as well as already existing interfaces. The validity of the library is documented based on an illustration involving female representation in local politics. In addition, pvsR facilitates the replication of research with PVS data at low costs, including the pre-processing of data. Similar OSIs are recommended for other big public databases