Mesozooplankton Grazing on Picocyanobacteria in the Baltic Sea as Inferred from Molecular Diet Analysis

<div><p>Our current knowledge on the microbial component of zooplankton diet is limited, and it is generally assumed that bacteria-sized prey is not directly consumed by most mesozooplankton grazers in the marine food webs. We questioned this assumption and conducted field and laboratory studies to examine picocyanobacteria contribution to the diets of Baltic Sea zooplankton, including copepods. First, qPCR targeting ITS-1 rDNA sequence of the picocyanobacteria <i>Synechococcus</i> spp. was used to examine picocyanobacterial DNA occurrence in the guts of Baltic zooplankton (copepods, cladocerans and rotifers). All field-collected zooplankton were found to consume picocyanobacteria in substantial quantities. In terms of <i>Synechococcus</i> quantity, the individual gut content was highest in cladocerans, whereas biomass-specific gut content was highest in rotifers and copepod nauplii. Moreover, the gut content in copepods was positively related to the picocyanobacteria abundance and negatively to the total phytoplankton abundance in the water column at the time of sampling. This indicates that increased availability of picocyanobacteria resulted in the increased intake of this prey and that copepods may rely more on picoplankton when food in the preferred size range declines. Second, a feeding experiments with a laboratory reared copepod <i>Acartia tonsa</i> fed a mixture of the picocyanobacterium <i>Synechococcus bacillaris</i> and microalga <i>Rhodomonas salina</i> confirmed that copepods ingested <i>Synechococcus</i>, even when the alternative food was plentiful. Finally, palatability of the picocyanobacteria for <i>A. tonsa</i> was demonstrated using uptake of ¹³C by the copepods as a proxy for carbon uptake in feeding experiment with ¹³C-labeled <i>S. bacillaris</i>. These findings suggest that, if abundant, picoplankton may become an important component of mesozooplankton diet, which needs to be accounted for in food web models and productivity assessments.</p>