High-resolution detection of bacterial profile of ocean water, before and after being used by shrimp farms

Marco A. Porchas-Cornejo, Marcel Martínez-Porchas*, Francisco Vargas-Albores, Teresa Gollas-Galvan, Luis Rafael Martínez-Córdova, Roberto Vazquez-Euan, Emilio Peña-Messina

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Bacterial diversity was evaluated in ocean water by next-generation sequencing (16S rRNA gene, V3/V4 regions) before and after being used by several shrimp farms with an operative capacity of >500 Ha and biomass producing of 3.5 t/Ha. A total of 22 bacteria species were identified in water before being incorporated into farm facilities; of these, Proteobacteria, Cyanobacteria, Bacteroidetes, and Actinobacteria resulted to be the most abundant phyla. After being used by shrimp farms, water decreased in quality (high concentrations of organic matter and nitrogenous metabolites) and the bacterial profile was modified in the outlet channel (effluent). Herein, beta diversity revealed changes in the bacterial profile of inlet and outlet water; for instance, different bacteria were detected de novo (some non-indigenous) and other were no longer detected; a total of 16 species (5 de novo) were registered in the effluent and Cyanobacteria, Actinobacteria, Proteobacteria, and Planctomycetes were the most abundant phyla. Many of the species thriving in the effluent resulted to be associated to the decomposition and recycling of organic matter and nitrogenous compounds. The farms acted as bioreactors favoring bacteria other than those detected in the inlet channel.

Original languageEnglish
Pages (from-to)1833-1843
Number of pages11
JournalAquaculture International
Volume25
Issue number5
DOIs
StatePublished - 1 Oct 2017

Bibliographical note

Publisher Copyright:
© 2017, Springer International Publishing Switzerland.

Keywords

  • 16S rRNA gene
  • Aquaculture effluent
  • Bacterial diversity
  • Effluent receiving ecosystems
  • Next-generation sequencing
  • Non-indigenous bacteria
  • Targeted metagenomics

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