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混养原生动物在全球海洋中表现出截然不同的生物地理学特征。

Mixotrophic protists display contrasted biogeographies in the global ocean.

机构信息

Sorbonne Université, CNRS, Laboratoire d'océanographie de Villefranche, LOV, 06230, Villefranche-sur-Mer, France.

Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum national d'Histoire naturelle, CNRS, Sorbonne Université, EPHE, CP 50, 57 rue Cuvier, 75005, Paris, France.

出版信息

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

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.

摘要

混养,即同时从自养和异养中获取碳的能力,是海洋原生生物中广泛存在的生态特征。利用全球海洋浮游生物的 metabarcoding 数据集,通过 89,951,866 条序列代表的 318,054 个混养 metabarcodes,并归属于 133 个分类群,将其分为四种混养功能类型:组成性混养生物(CM)、普通非组成性混养生物(GNCM)、内共生专性非组成性混养生物(eSNCM)和质体专性非组成性混养生物(pSNCM)。混养现象无处不在,分析了这四种混养类型的分布,以确定塑造它们生物地理学的非生物因素。与以前的形态学研究相比,kleptoplastidic 混养生物(GNCM 和 pSNCM)在新区域被检测到。组成性和非组成性混养生物的分布范围相似。大多数类群在样本中均匀分布,但其中一些类群的分布存在强烈的对比,无论是在混养类型之间还是内部。内共生混养生物的生物地理学差异特别大,这取决于形成群体的能力或共生方式。我们展示了 metabarcoding 如何与以前的形态学观察相结合,用于研究混养原生生物的生物地理学,并确定其生物地理学的关键驱动因素。

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