Preliminary safety assessment of a membrane-bound delta 9 desaturase candidate protein for transgenic oilseed crops

AbstractA gene encoding delta 9 desaturase (D9DS), an integral membrane protein, is being considered for incorporation into oilseed crops to reduce saturated fatty acids and thus improve human nutritional value. Typically, a safety assessment for transgenic crops involves purifying heterologously produced transgenic proteins in an active form for use in safety studies. Membrane-bound proteins have been very difficult to isolate in an active form due to their inherent physicochemical properties. Described here are methods used to derive enriched preparations of the active D9DS protein for use in early stage safety studies. Results of these studies, in combination with bioinformatic results and knowledge of the mode of action of the protein, along with a history of safe consumption of related proteins, provides a weight of evidence supporting the safety of the D9DS protein in food and feed

Identification and Characterization of the CYP52 Family of Candida tropicalis ATCC 20336, Important for the Conversion of Fatty Acids and Alkanes to α,ω-Dicarboxylic Acids

Candida tropicalis ATCC 20336 excretes α,ω-dicarboxylic acids as a by-product when cultured on n-alkanes or fatty acids as the carbon source. Previously, a β-oxidation-blocked derivative of ATCC 20336 was constructed which showed a dramatic increase in the production of dicarboxylic acids. This paper describes the next steps in strain improvement, which were directed toward the isolation and characterization of genes encoding the ω-hydroxylase enzymes catalyzing the first step in the ω-oxidation pathway. Cytochrome P450 monooxygenase (CYP) and the accompanying NADPH cytochrome P450 reductase (NCP) constitute the hydroxylase complex responsible for the first and rate-limiting step of ω-oxidation of n-alkanes and fatty acids. 10 members of the alkane-inducible P450 gene family (CYP52) of C. tropicalis ATCC20336 as well as the accompanying NCP were cloned and sequenced. The 10 CYP genes represent four unique genes with their putative alleles and two unique genes for which no allelic variant was identified. Of the 10 genes, CYP52A13 and CYP52A14 showed the highest levels of mRNA induction, as determined by quantitative competitive reverse transcription-PCR during fermentation with pure oleic fatty acid (27-fold increase), pure octadecane (32-fold increase), and a mixed fatty acid feed, Emersol 267 (54-fold increase). The allelic pair CYP52A17 and CYP52A18 was also induced under all three conditions but to a lesser extent. Moderate induction of CYP52A12 was observed. These results identify the CYP52 and NCP genes as being involved in α,ω-dicarboxylic acid production by C. tropicalis and provide the foundation for biocatalyst improvement

Machine Learning Strategy for Solar Energy optimisation in Distributed systems

Using renewable energies such as wind and solar energy, two types of renewable energy, we may adjust the structure of the energy system, addressing both energy and environmental challenges at the same time. As a result of its impact on the environment, wind and solar energy generation are inherently unreliable sources of energy. Lithium batteries, a technology that is becoming increasingly mature in terms of energy storage, are a critical component of the answer to the problem of instability. In order to avoid waste and expense increases, the capacity should not be too large or too small, respectively. Power consumption restricts the amount of energy that may be stored, but industrial power usage is unpredictable and non-periodic. This is a significant task that needs the development of a model that can dispatch while still providing a reasonable amount of storage. In this paper, we develop a KNN classification model that considers the test cyclic of photovoltaic (PV) generation that includes battery installation, data on electricity consumption and data on PV generation in India. These metrics are used to develop an energy management model. The model aims at the reduction of operation cost and optimal storage of energy that should satisfy the grid demands. The results of simulation and the comparison of the theoretical results shows that the proposed model has higher optimisation of energy in the storage devices in case of distributed systems