KNApSAcK family databases: integrated metabolite-plant species databases for multifaceted plant research

A database (DB) describing the relationships between species and their metabolites would be useful for metabolomics research, because it targets systematic analysis of enormous numbers of organic compounds with known or unknown structures in metabolomics. We constructed an extensive species-metabolite DB for plants, the KNApSAcK Core DB, which contains 101,500 species-metabolite relationships encompassing 20,741 species and 50,048 metabolites. We also developed a search engine within the KNApSAcK Core DB for use in metabolomics research, making it possible to search for metabolites based on an accurate mass, molecular formula, metabolite name or mass spectra in several ionization modes. We also have developed databases for retrieving metabolites related to plants used for a range of purposes. In our multifaceted plant usage DB, medicinal/edible plants are related to the geographic zones (GZs) where the plants are used, their biological activities, and formulae of Japanese and Indonesian traditional medicines (Kampo and Jamu, respectively). These data are connected to the species-metabolites relationship DB within the KNApSAcK Core DB, keyed via the species names. All databases can be accessed via the website http://kanaya.naist.jp/KNApSAcK_Family/. KNApSAcK WorldMap DB comprises 41,548 GZ-plant pair entries, including 222 GZs and 15,240 medicinal/edible plants. The KAMPO DB consists of 336 formulae encompassing 278 medicinal plants; the JAMU DB consists of 5,310 formulae encompassing 550 medicinal plants. The Biological Activity DB consists of 2,418 biological activities and 33,706 pairwise relationships between medicinal plants and their biological activities. Current statistics of the binary relationships between individual databases were characterized by the degree distribution analysis, leading to a prediction of at least 1,060,000 metabolites within all plants. In the future, the study of metabolomics will need to take this huge number of metabolites into consideration.     

Selection of reliable reference genes for qRT-PCR analysis in human non-cancerous gastric tissue

Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in complex diseases like obesity and gastritis. However, variations in amount of starting material, enzymatic efficiency and presence of amplification inhibitors can lead to quantification errors. Hence, the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Human gastric tissue has been the least investigated for stability of reference gene expression. In this study, three popular algorithms, GeNorm, NormFinder and BestKeeper were used to evaluate the reference gene stability. Conclusion: HPRT1 and GAPDH are the best performing pair of reference genes for qRT-PCR profiling experiments involving non-malignant gastric tissue samples.     

Social impact and social performance of paddy rice production in Iran and Malaysia

The International Journal of Life Cycle Assessment - Sustainable agri-food production is incredibly important for society. Despite Iran and Malaysia being one of the highest production countries...     

Selection of reliable reference genes for qRT-PCR analysis in human non-cancerous gastric tissue

Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in complex diseases like obesity and gastritis. However, variations in amount of starting material, enzymatic efficiency and presence of amplification inhibitors can lead to quantification errors. Hence, the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Human gastric tissue has been the least investigated for stability of reference gene expression. In this study, three popular algorithms, GeNorm, NormFinder and BestKeeper were used to evaluate the reference gene stability. Conclusion: HPRT1 and GAPDH are the best performing pair of reference genes for qRT-PCR profiling experiments involving non-malignant gastric tissue samples.