Unveiling the impact of glycerol phosphate (DOP) in the dinoflagellate Peridinium bipes by physiological and transcriptomic analysis

Background The ability to use dissolved organic phosphorus (DOP) is important for survival and competition when phytoplankton are faced with scarcity of dissolved inorganic phosphorus (DIP). However, phosphorus availability to the freshwater dinoflagellate Peridinium bipes has received relatively little attention, the efficiency of glycerol phosphate use by phytoplankton has rarely been investigated, and the regulatory molecular mechanisms remain unclear. Result In the present study, cultures of the freshwater dinoflagellate Peridinium bipes were set up in 119 medium (+DIP), DIP-depleted 119 medium (P-free), and beta-glycerol phosphate-replacing-DIP medium (+DOP). Gene expression was analyzed using transcriptomic sequencing. The growth rate of cells in DOP treatment group was similar to that in DIP group, but chlorophyll a fluorescence parameters RC/CS0, ABS/CS0, TR0/CS0, ET0/CS0 and RE0/CS0 markedly decreased in the DOP group. Transcriptomic analysis revealed that genes involved in photosynthesis, including psbA, psbB, psbC, psbD, psaA and psaB, were downregulated in the DOP group relative to the DIP group. Glycerol-3-phosphate dehydrogenase and glyceraldehyde-3-phosphate dehydrogenase, rather than alkaline phosphatase, were responsible for beta-glycerol phosphate use. Intercellular gluconeogenesis metabolism was markedly changed in the DOP group. In addition, genes involved in ATP synthases, the TCA cycle, oxidative phosphorylation, fatty acid metabolism and amino acid metabolism in P. bipes were significantly upregulated in the DOP group compared with the DIP treatment. Conclusions These findings suggested that beta-glycerol phosphate could influence the photosynthesis and metabolism of P. bipes, which provided a comprehensive understanding of the phosphorus physiology of P. bipes. The mechanisms underlying the use of beta-glycerol phosphate and other DOPs are different in different species of dinoflagellates and other phytoplankton. DIP reduction may be more effective in controlling the bloom of P. bipes than DOP reduction

Comparison of Data Mining Techniques in the Cloud for Software Engineering

Mining software engineering data has recently become an important research topic to meet the goal of improving the software engineering processes, software productivity, and quality. On the other hand, mining software engineering data poses several challenges such as high computational cost, hardware limitations, and data management issues (i.e., the availability, reliability, and security of data). To address these problems, this chapter proposes the application of data mining techniques in cloud, the environment on software engineering data, due to cloud computing benefits such as increased computing speed, scalability, flexibility, availability, and cost efficiency. It compares the performances of five classification algorithms (decision forest, neural network, support vector machine, logistic regression, and Bayes point machine) in the cloud in terms of both accuracy and runtime efficiency. It presents experimental studies conducted on five different real-world software engineering data related to the various software engineering tasks, including software defect prediction, software quality evaluation, vulnerability analysis, issue lifetime estimation, and code readability prediction. Experimental results show that the cloud is a powerful platform to build data mining applications for software engineering