Comparative study of water environment variation in the industrial aquaculture system of sea cucumber Apostichopus japonicus

This study investigated the microbial community, water quality, bacterial densities and growth performance in the industrial aquaculture system of sea cucumber Apostichopus japonicus without water exchange. Six treatments were set including, C (control treatment without sea cucumber culturing), S (small individual treatment), B (big individual treatment), Sd (small individual treatment with high density), Ss (small individual treatment adding carbohydrate source) and Sb (small individual treatment adding effective microorganisms). A total of 27916–32236 optimized reads and 564–742 operational taxonomic units (OTUs) were obtained from each samples. The phylum Proteobacteria, Actinobacteria, Bacteroidetes and Cyanobacteria predominated, representing 69.01–97.21% of the bacterial communities in the water samples. Cluster analysis and principal component analysis (PCA) showed that higher similarity was observed among S, Sd, Ss and Sb. The densities of TB and Vibrio in Ss were significantly higher than those in the other culture treatments after the 7th day. The concentrations of NH4-N, NO2-N, NO3-N and PO4-P in Ss and Sb were relatively lower than the other treatments. Conclusively, no deterioration was found in the water environment parameters during the 21-day culture period without water exchange, indicating that low-level water exchange protocol may be applied to the industrial aquaculture system. Based on the effects of different operations on culture system, industrial aquaculture is proved to be a viable way to rear sea cucumber.

[1]  Pedro A. Galleguillos,et al.  Distribution of prokaryotic genetic diversity in athalassohaline lakes of the Atacama Desert, Northern Chile. , 2004, FEMS microbiology ecology.

[2]  Y. Avnimelech Carbon/nitrogen ratio as a control element in aquaculture systems , 1999 .

[3]  J. Schrama,et al.  The effect of carbohydrate addition on water quality and the nitrogen budget in extensive shrimp culture systems , 2006 .

[4]  William A. Walters,et al.  QIIME allows analysis of high-throughput community sequencing data , 2010, Nature Methods.

[5]  Robert C. Edgar,et al.  UPARSE: highly accurate OTU sequences from microbial amplicon reads , 2013, Nature Methods.

[6]  J. Tiedje,et al.  Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy , 2007, Applied and Environmental Microbiology.

[7]  K. R. Clarke,et al.  Non‐parametric multivariate analyses of changes in community structure , 1993 .

[8]  William A. Walters,et al.  Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample , 2010, Proceedings of the National Academy of Sciences.

[9]  M. Verdegem,et al.  C/N ratio control and substrate addition for periphyton development jointly enhance freshwater prawn Macrobrachium rosenbergii production in ponds , 2008 .

[10]  H. Gabr,et al.  Effects of salinity on energy budget in pond-cultured sea cucumber Apostichopus japonicus (Selenka) (Echinodermata: Holothuroidea) , 2010 .

[11]  J. C. Goldman,et al.  Regulation of gross growth efficiency and ammonium regeneration in bacteria by substrate C: N ratio1 , 1987 .

[12]  William A. Walters,et al.  Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms , 2012, The ISME Journal.

[13]  P. J. Thompson,et al.  The contribution of flocculated material to shrimp (Litopenaeus vannamei) nutrition in a high-intensity, zero-exchange system , 2004 .

[14]  Rudolf Amann,et al.  Flow Sorting of Marine Bacterioplankton after Fluorescence In Situ Hybridization , 2004, Applied and Environmental Microbiology.

[15]  M. Simon,et al.  Phylogeny of Proteobacteria and Bacteroidetes from oxic habitats of a tidal flat ecosystem. , 2005, FEMS microbiology ecology.

[16]  Eoin L. Brodie,et al.  Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB , 2006, Applied and Environmental Microbiology.