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The application of bacterial indicator phylotypes to predict shrimp health status

Applied Microbiology and Biotechnology volume 98, pages 8291–8299 (2014)Cite this article

Abstract

The incidence of shrimp disease is closely associated with the microbial composition in surrounding water, but it remains uncertain whether microbial indicator phylotypes are predictive for shrimp health status (healthy or diseased). To test this idea, we combined the data from our previous works, to investigate the feasibility of indicator phylotypes as independent variables to predict the health status during a shrimp culture procedure. The results showed linearly increased dissimilarities (P < 0.001) of the bacterioplankton community over time, while the communities dramatically deviated from this defined trend when disease occurred. This sudden shift in the bacterial community appears to cause severe mass mortality of the shrimps. In particular, we created a model to identify indicators that discriminated ponds with diseased shrimp populations from these with healthy shrimp populations. As a result, 13 indicative families were screened, in which seven are healthy indicator and six are diseased indictor. An improved logistic regression model additionally revealed that the occurrences of these indicator families could be predictive of the shrimp health status with a high degree of accuracy (>79 %). Overall, this study provides solid evidences that indicator phylotypes could be served as independent variables for predicting the incidences of shrimp disease.

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Acknowledgments

This work was financially supported by the National High Technology Research and Development Program of China (863 Program, 2012AA092000), the Experimental Technology Research and Development Project of Ningbo University (SYJS-201405), Natural Science Foundation of Ningbo City (2013A610169) and of Ningbo University (XYL14004), Research Fund from 2011 Center of Modern Marine Aquaculture of East China Sea, and the KC Wong Magna Fund of Ningbo University.

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Affiliations

  1. School of Marine Sciences, Ningbo University, Ningbo, 315211, China

    Jinbo Xiong & Demin Zhang

  2. Faculty of Architectural, Civil Engineering and Environment, Ningbo University, Ningbo, 315211, China

    Jianlin Zhu

  3. 2011 Center of Modern Marine Aquaculture of East China Sea, Ningbo, China

    Jinbo Xiong & Demin Zhang

Authors
  1. Jinbo Xiong
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  2. Jianlin Zhu
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  3. Demin Zhang
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Corresponding author

Correspondence to Demin Zhang.

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Jinbo Xiong and Jianlin Zhu contributed equally.

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Xiong, J., Zhu, J. & Zhang, D. The application of bacterial indicator phylotypes to predict shrimp health status. Appl Microbiol Biotechnol 98, 8291–8299 (2014). https://doi.org/10.1007/s00253-014-5941-y

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  • DOI: https://doi.org/10.1007/s00253-014-5941-y

Keywords

  • Bacterioplankton community
  • Indicator phylotypes
  • Incidence of disease
  • Logistic regression model