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Applied and environmental microbiology

Community-Level and Species-Specific Associations between Phytoplankton and Particle-Associated Vibrio Species in Delaware's Inland Bays.


PMID 26070682

Abstract

Vibrio species are an abundant and diverse group of bacteria that form associations with phytoplankton. Correlations between Vibrio and phytoplankton abundance have been noted, suggesting that growth is enhanced during algal blooms or that association with phytoplankton provides a refuge from predation. Here, we investigated relationships between particle-associated Vibrio spp. and phytoplankton in Delaware's inland bays (DIB). The relative abundances of particle-associated Vibrio spp. and algal classes that form blooms in DIB (dinoflagellates, diatoms, and raphidophytes) were determined using quantitative PCR. The results demonstrated a significant correlation between particle-associated Vibrio abundance and phytoplankton, with higher correlations to diatoms and raphidophytes than to dinoflagellates. Species-specific associations were examined during a mixed bloom of Heterosigma akashiwo and Fibrocapsa japonica (Raphidophyceae) and indicated a significant positive correlation for particle-associated Vibrio abundance with H. akashiwo but a negative correlation with F. japonica. Changes in Vibrio assemblages during the bloom were evaluated using automated ribosomal intergenic spacer analysis (ARISA), which revealed significant differences between each size fraction but no significant change in Vibrio assemblages over the course of the bloom. Microzooplankton grazing experiments showed that losses of particle-associated Vibrio spp. may be offset by increased growth in the Vibrio population. Moreover, analysis of Vibrio assemblages by ARISA also indicated an increase in the relative abundance for specific members of the Vibrio community despite higher grazing pressure on the particle-associated population as a whole. The results of this investigation demonstrate links between phytoplankton and Vibrio that may lead to predictions of potential health risks and inform future management practices in this region.