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. 2019 Apr;13(4):1072-1083.
doi: 10.1038/s41396-018-0340-5. Epub 2019 Jan 14.

Mixotrophic protists display contrasted biogeographies in the global ocean

Emile Faure  1   2 , Fabrice Not  3 , Anne-Sophie Benoiston  4 , Karine Labadie  5 , Lucie Bittner #  4 , Sakina-Dorothée Ayata #  6   4
Affiliations

Mixotrophic protists display contrasted biogeographies in the global ocean

Emile Faure et al. ISME J. 2019 Apr.

Abstract

Mixotrophy, or the ability to acquire carbon from both auto- and heterotrophy, is a widespread ecological trait in marine protists. Using a metabarcoding dataset of marine plankton from the global ocean, 318,054 mixotrophic metabarcodes represented by 89,951,866 sequences and belonging to 133 taxonomic lineages were identified and classified into four mixotrophic functional types: constitutive mixotrophs (CM), generalist non-constitutive mixotrophs (GNCM), endo-symbiotic specialist non-constitutive mixotrophs (eSNCM), and plastidic specialist non-constitutive mixotrophs (pSNCM). Mixotrophy appeared ubiquitous, and the distributions of the four mixotypes were analyzed to identify the abiotic factors shaping their biogeographies. Kleptoplastidic mixotrophs (GNCM and pSNCM) were detected in new zones compared to previous morphological studies. Constitutive and non-constitutive mixotrophs had similar ranges of distributions. Most lineages were evenly found in the samples, yet some of them displayed strongly contrasted distributions, both across and within mixotypes. Particularly divergent biogeographies were found within endo-symbiotic mixotrophs, depending on the ability to form colonies or the mode of symbiosis. We showed how metabarcoding can be used in a complementary way with previous morphological observations to study the biogeography of mixotrophic protists and to identify key drivers of their biogeography.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
Global distribution of mixotypes from metabarcoding data. Maps showing for each station the proportion of sequences (in %) belonging to each mixotype over the total number of mixotrophic sequences. Stations in which no sequence was found were marked as absent, ones with less than 100 sequences marked as questionable. Each Longhurst biogeographical provinces [53] is colored in the background if more than 100 sequences are detected in at least one of its stations. A coloured version of this figure can be downloaded at 10.6084/m9.figshare.6715754
Fig. 2
Fig. 2
Sequence abundance, occupancy, and spatial evenness of each mixotrophic metabarcode across sampled stations. Each metabarcode is plotted as a bubble, with its station occupancy, i.e., the number of stations in which it was found, and its station evenness, i.e., the homogeneity of its distribution among the stations in which it was detected, as coordinates. Violin plots were drawn for each mixotype on both the x and y axes. The size of each bubble is scaled to the sequence abundance found globally for the corresponding metabarcode
Fig. 3
Fig. 3
Impact of environmental variables on the distribution of marine mixotrophs. Triplot of the redundancy analysis (RDA) computed on the 62 Escoufier-selected lineages, after model selection. The adjusted R-squared of the analysis is of 34.89% (41.43% unadjusted). Each gray dot corresponds to a sample, i.e., one filter at one depth at one station. The blue dashed arrows correspond to the quantitative environmental variables. Abbreviations: MLD mixed layer depth, O2MaxD O2 maximum depth, EuphzoneD  euphotic zone depth, PAR photosynthetically active radiations, Calcite Sat. St. Calcite Saturation State, c_660 optical beam attenuation coefficient at 660 nm, c_part beam attenuation coefficient of particles, acCDOM absorption coefficient of colored dissolved organic matter. Plain arrows correspond to mixotrophic lineages, colors indicating mixotypes. For more readability, we do not represent all qualitative variables included in the model. That is why only the filter centroids are appearing, even though the sampling depth, season, season moment, i.e., early, middle or late, and biogeographical province were used in the RDA calculation
Fig. 4
Fig. 4
Contrasted global distributions of metabarcodes corresponding to two eSNCM lineages. Maps of Hellinger-transformed sequence count abundances for metabarcodes assigned to the Collodaria Siphonosphaera cyathina a and the Acantharia Acanthrometridae F3 spp. b These two lineages are opposed on the first RDA axis (Fig. 3 and S1). Size and color both illustrate abundance for better readability. Ellipses were drawn to highlight high abundance zones, and reveal the differences in lineages distribution. A coloured version of this figure can be downloaded at 10.6084/m9.figshare.6715754
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