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Network Study on SecA – A Component of Sec Secretion System in Bacteria Pseudomonas Aeruginosa

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Advances in Neural Networks – ISNN 2018 (ISNN 2018)

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Abstract

Pseudomonas aeruginosa is a Gram-negative bacterium and infects plants, animals and humans. Secretion systems in P. aeruginosa play an important role in infections. Sec secretion system has eight components, of which SecA is an ATPase. However, gene network study on how SecA functions under different experimental conditions has yet to be done. In this study, network is used to analyze P. aeruginosa genes under four types of experimental conditions, i.e. stress, habitat, nutrition and mutation. Special attention is given to (i) how many clusters form under control and experimental conditions, (ii) how many genes in SecA cluster, (iii) how many genes change their membership together with SecA, and (iv) which gene connects with SecA under control and experimental conditions, and their functions. The results demonstrate how genes reorganize under experimental conditions, and discussion is given to the reasons for such reorganizations.

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Acknowledgements

This study was partly supported by National Natural Science Foundation of China (31460296 and 31560315), and Special Funds for Building of Guangxi Talent Highland.

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Authors and Affiliations

  1. State Key Laboratory of Non-food Biomass and Enzyme Technology, National Engineering Research Center for Non-food Biorefinery, Guangxi Key Laboratory of Bio-refinery, Guangxi Academy of Sciences, 98 Daling Road, Nanning, 530007, Guangxi, China

    Shaomin Yan & Guang Wu

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  1. Shaomin Yan
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  2. Guang Wu
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Correspondence to Guang Wu .

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Editors and Affiliations

  1. Texas A&M University at Qatar, Doha, Qatar

    Tingwen Huang

  2. Sichuan University, Chengdu, China

    Jiancheng Lv

  3. Southeast University, Nanjing, China

    Changyin Sun

  4. United Institute of Informatics Problems, Minsk, Belarus

    Alexander V. Tuzikov

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Yan, S., Wu, G. (2018). Network Study on SecA – A Component of Sec Secretion System in Bacteria Pseudomonas Aeruginosa. In: Huang, T., Lv, J., Sun, C., Tuzikov, A. (eds) Advances in Neural Networks – ISNN 2018. ISNN 2018. Lecture Notes in Computer Science(), vol 10878. Springer, Cham. https://doi.org/10.1007/978-3-319-92537-0_91

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  • DOI: https://doi.org/10.1007/978-3-319-92537-0_91

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-92537-0

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