The 16S gene metagenomic analysis performed thanks to next generation sequencing in Litopenaeus. vannamei gut allows determining the effect of different feed additives (prebiotics, probiotics, etc.) on bacterial composition and metabolic potential (1,2,3).
The bioassay consisted of two treatments in triplicate as follows: (I) Control, without additives; (II) Bacillus thuringiensis added in culture water every 4 d, BT (3 x 106 CFU/L). Physicochemical parameters (temperature, dissolved oxygen, pH and salinity) were measured daily. At day 26, samples for gut microbiota analysis were taken. DNA was extracted with CTAB method. Primers V3-338f and V3-533r were used to amplify the V3 region of bacterial 16S rDNA by PCR (4). Illumina MiniSeq was used to sequence amplicons. Reads were generated using the 2 x 150 pair-end (300 cycles). Shaman, MicrobiomeAnalyst, and Ivikodak softwares were used to analyze the microbial sequences. In the statistical analysis, a Kruskall-Wallis analysis and ANOSIM test were used.
Among 397 OTUs, 378 OTUs corresponded to BT treatment and 372 OTUs for control condition. The two groups shared 353 OTUs. The group with the most OTUs was BT (25) (Fig. 1).
Diversity and composition of the bacterial community did not change among treatment and the control group. Predominant bacteria in shrimp gut belonged to Proteobacteria, Bacteroidetes, Vibrio, and Ruegeria. Pseudoruegeria, Ruegeria, and Roseobacter increased metabolic features, whereas Vibrio decreased. The same trend was observed in quorum sensing (Table 1).
Vibrio showed a trend to decrease in abundance, metabolism and functional importance in BT treatment. B. thuringiensis IPNGSM1 in water affected bacteria with probiotic potential (Ruegeria and Roseobacter) positively and vibrio negatively at abundance and metabolism and quorum sensing levels.
Refeences
Xing, M., Hou, Z., Yuan, J., Liu, Y., Qu, Y., Liu, B., 2013. Taxonomic and functional metagenomic profiling of gastrointestinal tract microbiome of the farmed adult turbot (Scophthalmus maximus). FEMS Microbiol. Ecol. 86(3): 432-43.
Wang, W.L., Xu, S.Y., Ren, Z.G., Tao, L., Jiang, J.W., Zheng, S.S., 2015. Application of metagenomics in the human gut microbiome. World J. Gastroenterol. 21(3): 803-814.
Nagpal, S., Haque, M.M., Mande, S.S., 2016. Vikodak - A Modular Framework for Inferring Functional Potential of Microbial Communities from 16S Metagenomic Datasets. PLoS ONE 11(2): 1-19.
Huse SM, Dethlefsen L, Huber JA, Welch DM, Relman DA, Sogin ML (2008) Correction: exploring microbial diversity and taxonomy using SSU rRNA hypervariable Tag sequencing. PLOS Genet 4(10): 1371.