Planktonic microbial eukaryotes in polar surface waters:recent advances in high-throughput sequencing

Microbial protistan eukaryotes constitute a fundamental component of microbial food webs and contribute a crucial role in many global biogeochemical cycles (Dìez et al. 2001). Polar protistan taxonomy has been studied by conventional microscopy since the 1840s (Ehrenberg 1840) and there is a rich and detailed description of the most abundant taxa (see Horner 1985; Scott and Thomas 2005 for reviews of Arctic and Antarctic literature, respectively). These studies naturally concentrated on those species that could be identified initially by optical microscopy and later by electron microscopy. Consequently, the diatoms and dinoflagellates are mostly well characterized but it was always understood that there were many small flagellated taxa that could not be identified by conventional methods. The advent of molecular methods has started the process of obtaining a complete characterization of polar microbial eukaryote diversity. In recent years, high-throughput sequencing, which is typically characterized by being highly scalable, allowing the entire genome to be sequenced at once, has been increasingly used to enumerate and compare marine microbial diversity in polar environments, including a variety of oceanic water masses (Liu et al. 2019; Swalethorp et al. 2019), glacial-influenced coastal ecosystems (Luo et al. 2009; Moreno-Pino et al. 2016; Piquet et al. 2010), sea ice and melt-ponds (Kilias et al. 2014). However, there still remains an urgent need for a more comprehensive understanding of microbial eukaryote communities in polar ecosystems.

'Polar Ocean' is a collective term for the Arctic Ocean (about 4–5% of Earth's oceans) and the southern part of the Southern Ocean (south of the Antarctic Convergence, about 10% of Earth's oceans). The Arctic Ocean has an inclement environment that undergoes large seasonal variations in temperature, sea-ice concentration and solar radiation. Its hydrological condition is complex and has been considered a 'twin estuary', connecting the Pacific Ocean through the Bering Strait and the Atlantic Ocean through Fram Strait and Davis Strait (Fig. 1a) (Aagaard et al. 1985; Lovejoy 2014). Because of this connection between the Arctic Ocean and neighboring seas, the diversity of Arctic microbial eukaryotes can act as an indicator of water mass and connectivity (Aagaard et al. 1985; Lovejoy 2014).

Figure 1.  Map of bipolar Ocean with main currents in Arctic Ocean (a) and Southern Ocean (b)

Antarctica plays an essential role in driving, magnifying and moderating the global climate system. Due to the annual freeze/thaw cycle, the growth and melting of Antarctic sea ice represents one of the most significant seasonal events on Earth (AASSP 2011). Coastal areas of Antarctica and the surrounding Southern Ocean have unique physicochemical properties (Fig. 1b). Furthermore, due to the strong pulse of primary production in them in summer, these areas play a central role in global biogeochemical cycles (Sarmiento et al. 2004).

The effects of global warming have been particularly evident in polar ecosystems, especially in polar oceans, and this has resulted in a reduction in their capacity to absorb CO₂ (Le Quéré et al. 2007). The direct impacts of ocean acidification on marine microorganisms has been well studied (Hancock et al. 2018; McNeil and Matear 2008) but the associated effects on nutrient supply, including iron, and stratification at higher latitudes (Sarmiento and Le Quéré 1996), is less well known. So, three key questions arise: which microbial eukaryotes are present in polar oceans? How are they distributed and how have they evolved and adapted to the increasing warming in the polar oceans? This review focuses on data obtained using molecular methods but does not attempt to address molecular mechanisms of cold adaptation and evolution.

The following sections review our understanding of polar microbial eukaryote communities in surface marine environments, highlighting information that has been obtained using PCR amplification and high-throughput sequencing of 18S rRNA gene fragments.

Due to the extensive ice cover and strong salinity stratification, the Arctic Ocean is considered to be less turbulent than other oceans (Rainville et al. 2011). The persistent stratification means that for most of the Arctic Ocean and surrounding waters the nutrient levels in the euphotic zone are limiting and much of the productivity actually occurs in a subsurface chlorophyll maximum (SCM) layer (Lovejoy 2007; Martin et al. 2010). Given the significant recent changes in hydrological conditions in the Arctic Ocean, identifying characteristic groups of organisms from different water bodies and depths is critical to predicting the impact of these changes on carbon and energy cycling (Tsubouchi et al. 2012). Sequence-based 18S rRNA gene surveys can identify and compare variations in microbial eukaryote communities in marine environments, providing a tool for understanding the diversity and distribution of various taxonomic units in the ocean (Massana et al. 2006). To date, research on the 18S rRNA gene in the Arctic Ocean has focused on surface or SCM layers (Fig. 2a) (Comeau et al. 2011).

Figure 2.  Investigations conducted by using high-throughput sequencing on 18S rRNA gene of planktonic microbial eukaryote community in Arctic Ocean (a) and Southern Ocean (b) (Bachy et al. 2011; Balzano et al. 2012; Comeau et al. 2011; Fuentes et al. 2019; Hyoung et al. 2012; Liu et al. 2019; Luo et al. 2016; Marquardt et al. 2016; Metfies et al. 2016; Monier et al. 2013; Moreno-Pino et al. 2016; Piwosz et al. 2013; Swalethorp et al. 2019; Torstensson et al. 2015; Wolf et al. 2013, 2014; Zoccarato et al. 2016)

While the Arctic Ocean has similar a microbial biomass and community composition to communities from other oceans, there are some specific species and groups that are not present in the Arctic Ocean, such as cyanobacteria, and their ecological functions may be substituted by eukaryotic algae (Pedrós-Alió et al. 2015). For the Arctic Ocean, the V4 region of the 18S rRNA gene is most frequently used for taxonomic identification to the levels of species or genera (Monier et al. 2013). All major phytoplankton groups have been reported in Arctic waters, including chlorophytes, dinoflagellates, prymnesiophytes, diatoms, prasinophytes, cryptophytes etc. (Liu et al. 2019; Lovejoy et al. 2011). Mixotrophic groups that supplement their energy or nutrient requirements by phagotrophy, including phylogenetically diverse flagellates, dinoflagellates and a few ciliates, are also common in Arctic waters (Lovejoy 2014). Chrysophytes are one of group of potential mixotrophic flagellates that have been reported from sea ice and Arctic marine waters (Lovejoy et al. 2002a; Rozanska et al. 2008). Most frequent among the small marine heterotrophic flagellates are the phylogenetically diverse marine stramenopiles (MASTs), Picozoa, Telonemia, Cerozoans, Choanoflagellates and Katablepharidia (Massana et al. 2006). MASTs belonging to clades MAST-1, MAST-2, MAST-3, MAST-7 and MAST-8 (Massana and Pedrós-Alió 2008), are common in upper Arctic waters (Comeau et al. 2011; Lovejoy et al. 2006) and sea ice (Comeau et al. 2013). It seems that the different MAST clades appear to be associated with different environments. Cryothecomonads are the most common heterotrophic cercozoan group found in Arctic waters and they are present in both in the water column and in sea ice (Comeau et al. 2013; Thaler and Lovejoy 2012).

The microbial eukaryotic communities in Arctic upper mixed layer depths differ regionally (Lovejoy 2014). In Baffin Bay, which has a complex hydrology with water masses and ice conditions varying substantially over short distances, microbial eukaryotic organisms did not cluster together (Lovejoy et al. 2002b). In Barrow Strait, chlorophytes and cryptophytes were the dominant plastidic, and MAST-2 the most numerous aplastidic groups investigated (Piwosz et al. 2013), while in a high-Arctic fjord (Isfjorden), dinoflagellates were dominant all year (Marquardt et al. 2016). A determination of dominance by dinoflagellates using molecular methods, however, always needs to be treated with caution because of the influence of their disproportionately large genome size. Phaeocystaceae, Micromonas sp., Dinophyceae and Syndiniales comprised a high proportion of sequence reads from Fram Strait and large parts of the central Arctic Ocean.

In the Nordic Seas, Archaeplastida, mainly Prasinophyceae, was present in all samples and was the largest component in cold waters, while Rhizaria and Alveoata were most abundant in the samples influenced by warmer waters. The structure of the picoeukaryotic communities showed a clear spatial pattern, similar to that shown by the distribution of ocean currents (Liu et al. 2019). Due to the Atlantic inflow, environmental conditions in Nansen Basin may be more similar to those of Fram Strait, and in the future, the biodiversity and biomass of picoeukaryotes in Nansen Basin could resemble those currently observed in Fram Strait (Metfies et al. 2016). Alveolates were the most abundant and diverse group in water and sea ice near the North Pole found in gene libraries (Bachy et al. 2011). Throughout the Beaufort Sea, the picoplankton was dominated by Mamiellophyceae (Balzano et al. 2012). In most areas, picoplankton are the medium of biogeochemical cycling (Doolittle et al. 2008). Microbial eukaryotic community composition and biogeography in the Arctic Ocean may be the result of advection of ocean currents.

Microbial eukaryote communities sampled from lower polar latitudes were significantly correlated with temperature and nutrients whereas those from higher latitudes were correlated with sea ice cover, latitude of the sample site and chlorophyll concentration (Luo et al. 2018). Microbial communities are expected to be affected by ongoing environmental changes. Rising global temperatures are having a profound effect on the Arctic, including a sharp decrease in multiyear sea ice. Comeau et al. (2011) have found that changes in microbial community structure relate to changes in ice cover. Ice melting increases light transmission and could cause increased water column stratification, both of which could drive change in microbial community structure. As the extent and thickness of Arctic sea ice is decreasing, and more and more of the sea surface is exposed to solar radiation, primary production has increased (Pabi et al. 2008). In addition, the abundance of predatory species such as Laboea, Monodinium, Strombidium and several unclassified ciliates has been found to increase, while that of usually summer-dominant dinoflagellate taxa has decreased (Onda et al. 2017). Thus, these small ciliates may be advantaged by climate change and may be expected to dominate in the future Arctic (Onda et al. 2017). Alternatively, increasing sea ice melting is facilitating the invasion of Atlantic and Pacific phytoplankton species northward to the Arctic (Hegseth and Sundfjord 2008).

While photosynthetic microbial eukaryotes are responsible for most marine primary production (Matrai et al. 2013), there are significant regional differences in the microbial eukaryotic communities due to factors such as latitude, temperature and sea ice cover (Luo et al. 2018). In the Atlantic sector, Archaeplastida, Alveolata and Stramenopiles are the dominant groups, while in the Pacific sector, there is a higher abundance of Archaeplastida, especially in Nansen Basin and the Nordic Seas (Fig. 3). Their dominance in these regions is most likely due to the relatively low temperature caused by the unique hydrological condition (Liu et al. 2019). Despite both being in the Pacific sector, the composition of the microbial eukaryotic communities in the Bering Strait and the Canadian Basin also quite different. The dominant group in Bering Strait is Stramenopiles, while in Canadian Basin it is Alveolata (Fig. 3). In addition, diatoms and nano-sized plankton provided most of the taxonomic diversity in Bering Strait. These results can be explained by the observation that relatively larger phytoplankton dominate in warmer oceans over smaller phytoplankton (Hyoung et al. 2012).

Figure 3.  Community composition of microbial eukaryotes in different areas of the Arctic Ocean

Marine Antarctic microbial communities are mainly composed of two key microbiological functional groups: photosynthetic eukaryotes and bacteria, although cyanobacteria is almost completely absent. However, most research on microbial biodiversity, using high-throughput sequencing technology in the coastal waters of the Antarctic and the Southern Ocean, has focused on bacteria, with only a few reports on the unicellular eukaryotic community (Fig. 2b).

The microbial eukaryotic diversity of Fildes Bay, King George Island, (using molecular methods) included several different phylotypes, belonging to the Dinophyceae, Bacillariophyta, Prasinophytae, Ciliophora, Cercozoa and Fungi groups, with Bacillariophyta being dominant (Moreno-Pino et al. 2016). Moreno-Pino et al. (2016) also found that in surface waters around the South Shetland Islands, the environmental filtering effect had a significant impact on the composition of the phytoplankton communities. Based on data collected at different sites in Chile Bay (Greenwich Island, South Shetlands) during the spring bloom, it was postulated that autotrophic organisms were affected by preceding blooms during spring (Alcamán-Arias et al. 2018; Fuentes et al. 2019). Diatoms, especially Thalassiosirales, were the most abundant phytoplankton group in this period. However, this is not always the case, since during a bloom in Ardley Cove and Great Wall Cove, dinoflagellates, Cryptomonadales and Prymnesiophyceae were the dominant groups (Luo et al. 2016).

Microeukaryotic biodiversity data from the open Antarctic seas (Amundsen Sea and Ross Sea), collected from a small polynya directly under the ice, had moderate diversity indices, with dinoflagellates, being dominant (Torstensson et al. 2015). Swalethorp et al. (2019) undertook a 15-day induced bloom microcosm experiment to assess the succession of microzooplankton. They found that dinoflagellate biomass and microzooplankton size distribution evenness were correlated with more environmental variables than ciliates during an extensive summer bloom of Phaeocystis antarctica in the Amundsen Sea. Wolf et al. (2013) used automated ribosomal intergenic spacer analysis (ARISA) and 454-pyrosequencing, combined with pigment measurements via high performance liquid chromatography (HPLC) to study the protistan community along a west–east transect in the Amundsen Sea. They identified some characteristic offshore and inshore communities. Overall, both the microbial eukaryote biomass and total chlorophyll a were higher in inshore samples. Diatoms were the most abundant group in the entire area. Among them, the dominant inshore species were Eucampia sp. and Pseudo-nitzschia sp., while the dominant offshore species was Chaetoceros sp. In the easternmost sampling station, Phaeocystis sp. was the dominant species. Ciliates were most abundant under the ice, while haptophytes least abundant. Wolf et al. (2014) also reported on the composition and geographical distribution of protistan communities on a cross section from the coast of New Zealand to the eastern Ross Sea in the austral late summer. They found unique biogeographic distribution patterns determined by specific geographic environmental conditions. In contrast to the Arctic Ocean, picoeukaryotes were not the dominant group throughout the investigated transect and showed only a very low contribution south of the Polar Front. Some small stramenopiles, Syndiniales, and dinoflagellates dominated in the Subantarctic Zone, while the relative abundance of diatoms increased southwards into the Antarctic Zone and Polar Frontal Zone. South of the Polar Front, most sequences belonged to haptophytes, most likely Phaeocystis. As in previous studies, the dominant group found by Zoccarato et al. (2016) was dinoflagellates, representing 69% of the total sequences, however, once again, the disproportionately large genome size of dinoflagellates is likely to have skewed the abundance data. Unlike other studies however, they observed that the abundance of the dinoflagellate phylotype SL163A10 was significantly high, accounting for 63% of the total sequence. The dinoflagellate phylotype SL163A10 is kleptoplastic and may be an important primary producer in sea ice. It thus seems that mixotrophic flagellates play a more important role in the sea ice microbial ecosystem, not only during the polar night but also during summer when potential food sources are abundant, than previously considered.

Previous Southern Ocean studies have suggested that the microbial eukaryote community surrounding the South Shetland Islands is dominated by Stramenopiles. In the open seas, like the Amundsen Sea and the Ross Sea, they are dominated by Alveolata (Fig. 4). This may be due to the fact that the sampling time was biased towards spring and summer and the melting sea ice led to a diatom bloom in the waters around the Fildes Peninsula (Liu and Jiang 2020). Compared with coastal waters, nutrients levels in the open sea are often lower, which is more suitable for mixotrophs groups of Alveolata (Lovejoy 2014).

Figure 4.  Community composition of microbial eukaryotes in different areas of the Southern Ocean

Most studies have demonstrated that climate change is happening faster than expected, especially in polar regions (Holland and Bitz 2003). However, global change, including climate change, could lead to a significant loss of global microbial biodiversity and numerous studies have shown that much of the diversity of certain microbial groups has not yet been discovered; this is a cause for considerable concern (e.g., Lovejoy et al. 2011; Lovejoy 2014).

The molecular methods used in the study of Arctic microbial eukaryotes in areas such as Canadian Basin, Beaufort Sea, Amundsen Basin and Nansen Basin, has resulted in the realization that the diversity of uncultivated marine microbial eukaryotes was much greater than previously thought (Seenivasan et al. 2013). This discovery highlights the urgency for a greater effort to investigate Arctic microbial eukaryotes, especially in areas along the Arctic continental shelf. The few available studies of Arctic estuaries, coasts and shelves, were conducted primarily in the Canadian sector (e.g., Canadian Basin and Baffin Bay) and the Russian sector (e.g., Chukchi Sea, East Siberian Sea and Laptev Sea along the Russian mainland).

The Antarctic Peninsula has been reported to be one of the most rapidly warming regions on Earth (Doran et al. 2002; Turner et al. 2005). Although there have been many previous investigations of the coastal waters of the Antarctic Peninsula, microbial eukaryote diversity data (molecular) of Antarctic open waters remains scarce (e.g., Liu and Jiang 2020; Luo et al. 2016). A few studies have used the high-throughput sequencing techniques and have discussed the diversity of microbial eukaryote diversity in the Pacific sector but there is no comparable microbial eukaryote diversity dataset from the Atlantic and Indian Ocean sectors.

Although numerous surveys have been conducted on the microbial eukaryote diversity in the Arctic or Antarctic Oceans respectively, there is still insufficient molecular data to establish a bipolar biological information database to compare the biogeography and the speciation differences (Chown et al. 2015; Poulin et al. 2011; Wilkins et al. 2013). In addition, the lack of morphological data on uncultured species hinders assessment of claims of highly novel diversity in marine eukaryotes (Moon-van-de Staay et al. 2001). Furthermore, sequencing technology combined with multiplexing, which gathers many samples for high-throughput sequencing during a single run, coupled with improved bioinformatics methods (Caporaso et al. 2010; Huse et al. 2008) provides more information on the microeukaryotic biodiversity and distribution. Massive environmental nucleic acid sequencing methods, such as metagenomics or metatranscriptomics, have rarely been used in polar studies. They are expected to perform functional analysis of the whole microbial community, without prior knowledge of which organisms are present or exactly how they are interacting in the environment (Keeling et al. 2014). Furthermore, previous studies have shown that high rDNA copy numbers are present in different protistan groups, such as diatoms, dinoflagellates (Godhe et al. 2008), and ciliates (Gong et al. 2013). These may cause inaccuracy in species identification and molecular ecology and especially lead to the overestimation of the relative abundance of protists with a large size genome.

More and more investigations are focusing on the description of co-occurrence patterns and linkages within microbes through network analysis (Cavicchioli 2015). Networks of prokaryotes are intimately linked to ecosystem functioning and play a crucial role in maintaining biodiversity in polar areas (de Sousa et al. 2019; Grzymski et al. 2012). In addition, co-occurrence patterns of prokaryotes, based on next-generation sequencing data, have been shown to be able to predict positive and negative interactions between planktonic bacteria and environmental variables (Mo et al. 2018). However, similar research on microbial eukaryotes is far less advanced in the Arctic (Onda et al. 2017) and Antarctic oceans (Mikhailov et al. 2019). Furthermore, software, such as Gephi, Cytoscape and R provide strong support for the complex co-occurrence network analysis between biotic and abiotic systems (Fig. 5). Thus, integrated co-occurrence networks, that link microbial eukaryotes and environmental parameters, would be a robust tool to understand the diversity variations and functional response to climate changes in future research on bipolar marine environments (Liu and Jiang 2020).

Figure 5.  The co-occurrence network can reflect the interspecies interaction in the ecosystem as well as the relationship between species and environmental factors

This work is supported by the Natural Science Foundation of China (no. 41676178), the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology (Qingdao), China (nos. 2018SDKJ0104-4, 2018SDKJ0406-6), the National Key Research and Development Program of China (no. 2017YFA0603200), and the Grant from Education Department of Shandong Province (S190007170001).

QL and QZ collected and analyzed data;AM revised and polished the language;EY reviewed the content;YJ designed and wrote this review.All authors contributed to the information gathering,ideas and concepts,construction of fgures,and/or writing of the manuscript.

The authors declare that they have no confict of interest.

We declare that all applicable international,national,and/or institutional guidelines for sampling, care,and experimental use of organisms for the study have been followed and all necessary approvals have been obtained.