Protistan diversity in a permanently stratified meromictic lake (Lake Alatsee, SW

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Germany).1

Accepted Article

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Andreas Oikonomou, Sabine Filker, Hans-Werner Breiner, Thorsten Stoeck*

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Department of Ecology, University of Kaiserslautern, Erwin Schroedinger Str. 14, D-67663,

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Kaiserslautern, Germany

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*

Corresponding author: Thorsten Stoeck

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address: Erwin Schrödinger Str. 14, 67663 Kaiserslautern, Germany

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e-mail: [email protected]

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telephone number: +49 631-2052502

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fax number: +49 631-2052502

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Running title: Eukaryotic communities in a meromictic lake

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This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/1462-2920.12666

1 This article is protected by copyright. All rights reserved.

Accepted Article

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Summary

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Protists play a crucial role for ecosystem function(ing) and oxygen is one of the strongest

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barriers against their local dispersal. However, protistan diversity in freshwater habitats with

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oxygen gradients received very little attention. We applied high-throughput sequencing of the

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V9 region (18S rRNA gene) to provide a hitherto unique spatiotemporal analysis of protistan

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diversity along the oxygen gradient of a freshwater meromictic lake (Lake Alatsee, SW

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Germany). In the mixolimnion, the communities experienced most seasonal structural

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changes, with Stramenopiles dominating in autumn and Dinoflagellata in summer. The

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suboxic interface supported the highest diversity, but only 23 OTUs95% (mainly Euglenozoa,

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after quality check and removal of OTUs with less than three sequences) were exclusively

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associated with this habitat. Eukaryotic communities in the anoxic monimolimnion showed

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the most stable seasonal pattern, with Chrysophyta and Bicosoecida being the dominant taxa.

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Our data pinpoint to the ecological role of the interface as a short-term “meeting point” for

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protists, contributing to the coupling of the mixolimnion and the monimolimnion. Our

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analyses of divergent genetic diversity suggest a high degree of previously undescribed

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OTUs. Future research will have to reveal if this result actually points to a high number of

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undescribed species in such freshwater habitats.

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2 This article is protected by copyright. All rights reserved.

Accepted Article

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Introduction

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Ecological processes in freshwater systems depend on species diversity and

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contemporary functional traits of the corresponding organisms (Cardinale et al., 2011).

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Therefore, a cornerstone for a better understanding of invidual ecosystems and their

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function(ing) is an in-depth knowledge of the taxonomic inventory of these ecosystems. A

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key element in freshwater ecosystems are unicellular eukaryotes (protists), which are of

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crucial importance when it comes to energy- and carbon flow (Finlay and Esteban, 1998;

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Sherr and Sherr, 2002). For example, small pigmented protists exert a resource-control

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through the dependence of bacteria on photosynthetically produced carbon while mixotrophic

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and heterotrophic protists have a predatory control and are major loss factors for bacteria

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(Jürgens and Massana, 2008; Sanders, 2011). As prey, protists channel carbon and energy to

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higher trophic levels. For example, they significantly contribute to the diet of a variety of

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multicellular organisms such as Daphnia (Callieri et al., 1999). Because of the multitude of

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distinct functional traits of individual protistan taxon groups, their differential feeding

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preferences and responses and their distinct food-quality (Callieri et al., 1999; Glücksman et

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al., 2010; Roberts et al., 2011; Šimek et al., 2013) the taxon composition of protistan

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communities in individual habitats plays a crucial role for ecosystem function(ing). Even

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though the diversity of protists in freshwater systems is presumably much higher compared to

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ocean surface waters (Logares et al., 2009), freshwater bodies, specifically mountain lakes,

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have received only very little attention compared to marine waters when it comes to protistan

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plankton diversity (Triadó-Margarit and Casamayor, 2012).

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Among freshwater lakes, stratified meromictic lakes with a pronounced oxygen

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gradient belong to the most complex systems (oxic mixolimnion, suboxic chemocline, anoxic 3 This article is protected by copyright. All rights reserved.

sulfidic monimolimnion). Prior molecular diversity surveys have revealed the fine-scale

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architecture of protistan plankton communities in stratified marine or brackish water bodies

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(Stoeck et al., 2003; Stoeck et al., 2006; Stock et al., 2009; Behnke et al., 2010; Wylezich and

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Jürgens, 2011). Because oxygen is one of the strongest barriers against local protistan

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dispersal and gene flow (Forster et al., 2012), it is not surprising that all of these studies

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uncovered substantial changes in protistan community structures along stratification gradients

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with a very high diversity of previously described and undescribed protists. Only very few

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protistan diversity studies have targeted freshwater habitats with oxygen gradients (Šlapeta et

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al., 2005; Lepère et al., 2006; Lefèvre et al., 2007). The recurrent microscopic observations of

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the same morphotypes in freshwater ecosystems around the world have fuelled the idea of a

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global dispersal of protists and a relatively low global protist species richness (Finlay and

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Esteban, 1998). The same authors even claim “there is every reason to believe that all species

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of freshwater protozoa could eventually be discovered in one small pond”, provided this pond

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includes the different habitats that select for distinct protists, such as oxygen gradients. If this

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were true, detailed ecological studies in few model lakes would help to understand the

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ecosystem function(ing) of lakes worldwide. The sequence data coming from the few

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molecular diversity studies that targeted either oxygenated (Richards et al., 2005; Šlapeta et

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al., 2005; Luo et al., 2011) or oxygen-depleted (Luo et al., 2005; Lefèvre et al., 2007)

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freshwater habitats contradict these microscopy observations. However, a rejection of this

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global dispersal / low diversity of protists hypothesis in freshwater lakes requires a recording

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of the full deck of the protistan inventory, which also considers seasonal community

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dynamics. Both microscopy and 18S rDNA clone-library analyses are severely limited in this

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respect. Microscopy allows only the differentiation of taxa with morphologically distinct

Accepted Article

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characters recognizable by the taxonomist; cost-intensive clone-library analyses usually detect

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only the most abundant genes present in an environmental sample due to the relatively low

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number of clones that can be analysed by an individual project. 4 This article is protected by copyright. All rights reserved.

Next generation sequencing (NGS) technologies, such as Illumina sequencing,

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circumvent these shortcomings of microscopy and clone-library analyses and allow for a deep

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sequencing of a high number of samples at relatively low costs (Shendure and Ji, 2008). Here,

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we take advantage of this approach to provide the first molecular in-depth analyses of

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protistan community diversity along a stratification gradient in a meromictic mountain lake in

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three different seasons.

Accepted Article

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Results

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Study site

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Lake Alatsee (47° 33´ 39´´ N, 10° 38´ 14´´ E) is a meromictic mountain lake with a

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maximum depth of 35 m and an 18 ha surface area located in Allgäu, Germany. The water

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column of the lake is characterized by an upper oxygenated mixolimnion and a permanently

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anoxic, sulfide-rich monimolimnion below 20 meters (Fig. 1). The monimolimnion dates back

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to ca 8 000 - 10 000 years (Fröbisch et al., 1977; Weis, 1983) and a stable chemocline at a

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depth of 16 - 19 meters with dense populations of purple sulfur bacteria (Fritz et al., 2012)

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separates the mixolimnion from the monimolimnion. Temperature, oxygen and hydrogen

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sulfide concentration were measured in situ by means of an MS08 AMT probe system

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(Analysenmeßtechnik GmbH, Germany). Profiles for lake characterization are provided in

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Fig. 1.

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V9 amplicon analyses

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We obtained 18 644 652 raw sequences in total, 13 761 912 of which met our

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stringency criteria as “high quality” sequences (chimeras removed). These sequences

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clustered into 24 283 OTUs95% that could be taxonomically assigned to protists and fungi.

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Removal of OTUs with less than three sequences resulted in 8 698 OTUs95%. Results for all 5 This article is protected by copyright. All rights reserved.

community analyses derive from data set excluding OTUs with less than three sequences. The

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number of OTUs collapsed with decreasing sequence similarity threshold at which OTUs

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were called (Fig. 2). The initial collapse from OTU100% to OTU95% was exponential,

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indicating a high, possibly intraspecific, microdiversity, which is very difficult to interpret

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taxonomically and ecologically (Stoeck et al., 2010; Dunthorn et al., 2012). From OTU95%

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downwards, the collapse of OTU-numbers is linear with a low decrease, providing our

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reasoning to choose OTUs called at 95% sequence similarity for statistical analyses and

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taxonomic assignments.

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Diversity partitioning Simpson’s alpha diversity revealed no general pattern for specific seasons or specific

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depths (Fig. 3). The IF harbored the lowest diversity in autumn (IF-Au). In Spring (Sp) and

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summer (Su), the mixolimnion (MIXO-Sp and MIXO-Su) showed similar diversity values to

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the monimolimnion (MONO-Sp and MONO-Su, respectively).

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The stratification gradient in the lake’s water column rather than seasonal patterns is

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mirrored in the Jaccard (Jabundance)-UPGMA distance, which revealed three discrete clusters

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(Fig. 4). Identical clusters were also recovered with the incidence based Jaccard index (J binary)

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(Fig. S1). All communities from the oxic mixolimnion (MIXO-Au, MIXO-Sp and MIXO-Su)

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were united in one cluster and were clearly separated from the cluster of the anoxic samples

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(MONO-Au, MONO-Sp and MONO-Su). The MIXO-Sp and MIXO-Su protistan

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communities are more similar to each other than to the MIXO-Au community, confirming the

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Simpson’s alpha-diversity pattern of these three communities (see above, Fig. 3). The only

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exception disrupting the stratification gradient pattern is the IF protistan community collected

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in spring (IF-Sp), which appeared relatively similar to the MONO-Sp community, and

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clusters within the anoxic MONO-clade. The reasoning for this clustering can be found in the

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following numbers: 71% of all OTUs detected in IF-Sp were also found in the MONO-Sp 6 This article is protected by copyright. All rights reserved.

protistan community. In comparison, IF-Sp and IF-Su share 51%, whereas IF-Sp and IF-Au

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share only 42%.

Accepted Article

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Taxonomic protistan community composition In terms of major taxonomic groups, there is only moderate variation among depths

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and among seasons (Fig. 5). An interesting observation on higher taxon level is the

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dominance of Ciliophora, Dinoflagellata, Stramenopiles and Cryptophyta in the mixolimnion

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(MIXO) and interface (IF) at all seasons with other taxon groups (e.g. Amoebozoa,

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Euglenozoa, Fungi, Chlorophyta, Metamonada) being less diverse. Alveolata OTUs

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(Ciliophora and Dinoflagellata) peak in the summer samples in the MIXO (68% of all OTUs

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in this sample) and in the IF (51%) with specifically Dinoflagellata showing a notable

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increase in the summer samples. In the anoxic sulfidic monimolimnion (MONO), the relative

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proportion of Stramenopiles OTUs is still in the same order of magnitude as in the other two

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sample depths, but the relative proportion of OTUs in other taxon groups is more evenly

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distributed. For example, Alveolata account for only 30% maximum (summer sample).

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Because spatial structuring along the stratification gradient is a stronger force shaping

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community patterns rather than seasonal changes (see above, Fig. 4) we analyzed the protistan

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communities on higher taxonomic resolution by depths pooled over the three seasons (Fig. 6).

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Differences in community structures in the MIXO, IF and MONO became evident, when

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identifying and visualizing the taxonomic OTU distribution that is unique to each of these

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depths. We identified 412 OTUs exclusively present in the MIXO (=15% of all OTUs

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observed only in the MIXO), only 23 OTUs unique in the IF (=6% of all OTUs observed only

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in the IF) and 111 OTUs in the anoxic sulfidic MONO (=22% of all OTUs observed only in

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the MONO). Ciliophora accounted for 52% of the exclusive OTUs in the MIXO, followed by

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Stramenopiles (22%) and Dinoflagellata (18%) (Fig. 6A). A similar picture emerged for the

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IF regarding Ciliophora (52%) and Stramenopiles (26%) (Fig. 6B). However, in the MIXO, 7 This article is protected by copyright. All rights reserved.

the vast majority of exclusive ciliates are Spirotrichea (Fig. 6A). This is different in the IF, in

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which the proportion of exclusive colpodean and protostomatean OTUs is as large as the

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proportion of spirotrichs (Fig. 6B). Furthermore, in contrast to the MIXO, no unique

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Chlorophyta and Centrohelida were found. Therefore unique Euglenozoa (2 Kinetoplastea

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OTUs and 1 Euglinida OTU) occurred in the IF together with 1 unique OTU assigned to

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Peridiniophycidae (Dinoflagellata) and 1 Cryptophyta OTU. The relative taxonomic

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distribution of the exclusive OTUs in the anoxic sulfidic MONO decisively differed from both

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above water compartments (Fig. 6C). Exclusive Amoebozoa accounted for 27%, followed by

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Metamonada (21%). Exclusive Chlorophyta accounted for 11% in the MONO. Exclusive

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OTUs assigned to Cercozoa (6%), Fungi (4%), and Apusomonadida (2%) occurred only in

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MONO. The proportion of exclusive Ciliophora, Dinoflagellata and Stramenopiles OTUs

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decreased dramatically in the MONO compared to the MIXO and IF.

Accepted Article

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Divergent genetic diversity

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The 200 most abundant OTUs95% pooled over depths and seasons (Fig. 7) were

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dominated by Ciliophora OTUs (n=56) and Stramenopiles (n=55), followed by Dinoflagellata

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(n=23), Chlorophyta and Fungi (each n=12), Cryptophyta (n=11) and Cercozoa (n=7).

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Numerous other taxon groups were included with less than five OTUs. Basically, the diversity

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detected in these 200 most abundant OTUs95% can be categorized as follows:

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a) OTUs that are 95%-100% similar to deposited sequences of described taxa (blue-

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dark green). In total, 80 OTUs (40%) in our analysis fell into this category. Nearly half of the

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ciliate OTUs (n=28), nearly half of all Dinophyceae OTUs (n=11) and more than half of all

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Chlorophyta OTUs (n=7) in this analysis. Of the 55 Stramenopiles, 17 are 95-100% similar to

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deposited sequences of described taxa, almost all of which are Chrysophytes. But only 4

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Cryptophyta, 3 Fungi and 1 Cercozoa OTU fell into this category.

8 This article is protected by copyright. All rights reserved.

b) OTUs that are 85%-94.9% similar to deposited sequences of described taxa

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(yellow-green). In total 104 of the 200 most abundant OTUs fell into this biggest category.

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c) OTUs that are 80%-84.9% similar to deposited sequences of described taxa (red-

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orange). In this category of highly divergent sequences we found 16 out of 200 OTUs

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consisting of five Stramenopiles, 2 Dinoflagellata, 2 Cryptophyta, 2 Cercozoa and one of each

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Apicomplexa, Kinetoplastida, Fungi, Heterolobosea and Jakobida. Interestingly, none of the

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numerous abundant Ciliophora and none of the abundant Chlorophyta OTUs fell into this

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category.

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Discussion

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Seasonal patterns of protistan plankton and their spatial distribution along stratification

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gradients are well documented from molecular as well as from microscopy studies (Fenchel et

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al., 1990; Behnke et al., 2006; Saccà et al., 2008; Stock et al., 2009; Behnke et al., 2010;

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Wylezich and Jürgens, 2011; Esteban et al., 2012; Stoeck et al., 2014). However, the depth of

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(sequence) sampling conducted in a permanently stratified freshwater meromictic lake in a

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temporal and spatial resolution is hitherto unique. Therefore, the data obtained in this study

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provided new insights into an only little-studied ecosystem.

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The protistan community in the oxic mixolimnion experienced most structural changes

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during seasons. This is not unexpected because this water layer is mostly affected by

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atmospheric changes such as temperature and light availability, but also by seasonal

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succession of zooplankton affecting protistan community structures (Miracle et al., 1992;

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Klaveness and Løvhøiden, 2007; Stewart et al., 2009). The dominant role of stramenopiles

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has been identified in oligotrophic mixed freshwater bodies (Richards et al., 2005), including

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the mixolimnion of meromictic lakes (Tarbe et al., 2011). The ecophysiological versatility of

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Dinoflagellata makes them a very successful and abundant component in freshwater 9 This article is protected by copyright. All rights reserved.

ecosystems (Smayda, 2002; Taylor et al., 2008), which also applies to meromictic lakes. The

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strong seasonal fluctuations of Dinoflagellata with summer-peaks may seem surprising at first

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sight, because Dinoflagellata can adapt to low-light conditions (autumn and winter) and

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maintain maximum cell division rates (Chan, 1978; Jakobsen et al., 2000). However, under

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nutrient-limitation as in the oligotrophic mixolimnion of lake Alatsee, low-light adaptation in

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Dinoflagellata may fail (Prézelin and Matlick, 1983). Furthermore, increasing temperatures

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are likely to support dinoflagellate diversity peaks in summer. Even though freshwater

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dinoflagellates adapted to cold-water are well known (e.g. Borghiella dodgei with optimal

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growth rate at 5°C, (Flaim et al., 2012)), a large proportion of Dinoflagellata in lake Alatsee

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seems to appear only in higher abundances at elevated temperatures. One example is

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Peridinium, which was also detected in the mixolimnion of lake Alatsee, showing an optimal

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growth at 23°C (Lindström, 1984). Representatives of the class Spirotrichea dominated the

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exclusive Ciliophora found in the lake’s mixolimnion. Ciliophora is one of the most diverse

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eukaryotic taxon groups occurring in a variety of aquatic habitats (Foissner et al., 2008).

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Within this phylum, the class Spirotrichea (mainly oligotrichids) constitute a quantitatively

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important fraction of the ciliate population in the epilimnion of freshwater lakes persisting

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throughout all seasons (James et al., 1995; Zingel and Ott, 2000; Pfister et al., 2002).

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Spirotrichea are gradually replaced from the hypolimnion of freshwater lakes when oxygen

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levels drop (James et al., 1995; Zingel, 2005), such as in the suboxic interface.

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Seasonal variation is less pronounced in the suboxic interface, where Ciliophora

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dominated the planktonic protists in autumn and summer. Through a variety of lifestyles,

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ciliates belong to the most successful protistan taxon groups that can cope with low-oxygen

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conditions or anoxia (Fenchel and Finlay, 1995 and references within). A motile response of

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many ciliates to oxygen sensing results in an aggregation of these organisms at oxic-anoxic

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boundary layers in aquatic habitats where they find their preferred oxygen tension (Fenchel

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and Finlay, 2008). This finding is congruent with the dominance of ciliates at natural oxic10 This article is protected by copyright. All rights reserved.

anoxic boundary layers in molecular studies (Šlapeta et al., 2005; Behnke et al., 2006; Stock

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et al., 2009). It was an interesting observation that the interface supports the highest overall

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protistan diversity, but at the same time only very few OTUs were exclusive to this habitat.

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Furthermore, in terms of taxon composition, the interface displays the highest seasonal

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dynamic (Fig. 4). These data point to the special ecological importance of boundary layers in

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meromictic lakes. The interface is inhabited by dense populations of purple sulfur bacteria

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(PBS) including Chromatium, Lamprocystis, Thiocystis and Thiodyction (Fritz et al., 2012),

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all of which are typical for such chemoclines in the photic zone of stratified lakes (Storelli et

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al., 2013). Investigations in a comparable chemocline at Lake Cadagno in Switzerland

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showed that these bacteria are the ecosystem’s key players in inorganic carbon

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photoassimilation (Camacho et al., 2001). Likewise, other products of anaerobic bacterial

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metabolism originating from the sediment and the monimolimnion such as sulfide, methane

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and ammonia, also support a rich and abundant bacterial community in the chemocline of

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meromictic lakes (Cloern et al., 1983; Lüthy et al., 2000; Pimenov et al., 2003). The variety

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of chemoautotrophs in the chemocline then resupplies several oxidants such as Fe3+, NO2- and

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NO3- and S0 to the anoxic monimolimnion (for a model of the processes see Esteban et al.,

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2012). Even though no comparable studies exist for Lake Alatsee, it is reasonable to assume

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that the same applies to the bacteria and microbial processes in this lake’s chemocline. Thus,

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despite the small relative volume of the chemocline in meromictic lakes, this layer is the

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motor for fluxes, the lynchpin for metabolic products and connects the different water layers

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with each other. The role of protists in these processes, however, is unknown. Our data,

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showing that the interface in lake Alatsee is a short-term “meeting point” for protists residing

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in the mixolimnion and protists inhabiting the anoxic monimolimnion, suggest that protists

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may play a pivotal role in these processes and also in the coupling of the different water

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layers. Experiments with e.g. stable isotopes could confirm the role of protists in these

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ecosystem processes.

Accepted Article

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11 This article is protected by copyright. All rights reserved.

Only one major eukaryote evolutionary lineage occurred exclusively in lake Alatsee’s

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chemocline, namely Euglenozoa (Fig. 6). This corroborates with previous findings: Tuomi et

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al. (1997) identified dense Euglena populations immediately on top of a chemocline in a

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meromictic Norwegian lake as responsible for a green water color. Such phototrophic

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euglenids are frequent inhabitants of chemoclines under reduced light levels and can tolerate

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sulfide concentrations (Klaveness and Løvhøiden, 2007). Orsi and colleagues (2011) provided

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evidence on the apparent habitat specialization of Euglenozoa in suboxic habitats. Likewise,

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Cryptophyta often form considerable populations at the oxic-anoxic transition zone of

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stratified water masses (Gasol et al., 1993). In contrast to euglenids, cryptophytes migrate

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further into the anoxic and sulfidic monimolimnion in order to reduce predation losses

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(Pedrós-Alió et al., 1995). Their occurrence in the upper mixolimnion is less frequent and is

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primarily controlled by predation (Gervais, 1998), explaining the exclusive observation of

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Cryptophyta in the chemocline and the monimolimnion (Fig. 6).

Accepted Article

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The eukaryotic communities in the anoxic monimolimnion showed the most stable

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seasonal pattern (Fig. 5), corroborating well with the stable hydro-physicochemical conditions

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in this deeper water layer throughout the different seasons. In addition, the lack of seasonally

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fluctuating multicellular grazers in such permanently anoxic and sulfidic water bodies most

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likely contributes to maintaining a seasonally relatively stable community with little

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dynamics, successions and fluctuations. Stramenopile diversity, mainly Chrysophyta and

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Bicosoecida, dominated the protistan communities in the anoxic monimolimnion of lake

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Alatsee. This was unexpected because previous microscopy and molecular diversity analyses

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found ciliates as main components in anoxic compartments of stratified water columns

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(Finlay et al., 1996; Guhl et al., 1996; Behnke et al., 2010; Charvet et al., 2012), even though

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Chrysophyta and Bicosoecida are frequent and abundant members in oxygen-depleted

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habitats (Luo et al., 2005; Behnke et al., 2006; Stock et al., 2009; Wylezich and Jürgens,

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2011). The ecological importance of phagotrophic stramenopiles as a trophic link and their 12 This article is protected by copyright. All rights reserved.

potential involvement in regulating bacterial populations in anoxic marine systems has been

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discussed earlier (Stoeck et al., 2007; Orsi et al., 2011; Massana et al., 2013). Even though

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morphologically and phylogenetically marine stramenopiles are clearly distinct from

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freshwater stramenopiles (Park and Simpson, 2010), their ecological importance in anoxic

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freshwater habitats is very likely the same.

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The lower diversity of Ciliophora in lake Alatsee’s anoxic monimolimnion is most

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likely associated with their low grazing potential and efficiency (Oikonomou et al., 2014). It

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seems that the prevailing bacterial community structure in lake Alatsee’s monimolimnion

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does not allow the growth of diverse and large ciliate populations (despite the numerous

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adaptation mechanisms of ciliates to anoxia, Fenchel and Finlay, 1995), compared to the

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much smaller bicosoecid and chrysophyte flagellates. Thus, biotic interactions also seem to

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play an important role shaping protistan plankton community structures in the anoxic water

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bodies of meromictic lakes. The classes Armophorea and Karyorelictea of Ciliophora were

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exclusively found interannually in the anoxic samples. These groups typically have a lifestyle

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adapted to anoxic conditions (Fenchel and Finlay, 1995; Lynn and Small, 2002), explaining

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their exclusive residency in anoxic habitats of stratified water columns (Stock et al., 2009).

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Additionally, the exclusive occurrence of Amoebozoa (mainly archamoebae) and

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Metamonada (mainly the free-living diplomonads) in the anoxic monimolimnion is rooted in

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these organism lifestyles and anaerobic metabolism (Bringaud et al., 2010). These occur very

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rarely in oxygenated freshwater ecosystems and are frequent inhabitants in oxygen-depleted

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freshwater (Bernard et al., 2000). The exclusive OTUs of Fungi in the anoxic compartment

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was less surprising. They are well documented from anoxic habitats (Luo et al., 2005; Orsi et

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al., 2011), and recent experiments show evidence for fungal anaerobic metabolism (such as

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denitrification, Stief et al., 2014).

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The appearance of Chlorophyta in the lake’s dark zone is not unusual. Some members

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of the Chlorophyta (e.g. Chlamydomonas sp.) are capable of producing oxygen in the light, 13 This article is protected by copyright. All rights reserved.

but turn rapidly to anaerobic metabolism after exposure to anoxia and darkness (Meuser et al.,

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2009; Atteia et al., 2013). Moreover, several green algae are able to tolerate anoxic conditions

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in the monimolimnia of meromictic lakes for an extended period of time (Klaveness and

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Løvhøiden, 2007), while others can switch to a phagotrophic lifestyle (Bell and Laybourn-

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Parry, 2003; Maruyama and Kim, 2013). In the anoxic monimolimnion Chlorophyta may find

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a refuge from the predation they experience in the photic zones of lakes (Arvola et al., 1992).

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Our results indicate that freshwater anaerobic communities are different from the

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anaerobic communities in brackish environments (Stock et al., 2009; Behnke et al., 2010), in

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saline meromictic lakes (Charvet et al., 2012) and in stratified marine water columns (Stoeck

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et al., 2003; Stoeck et al., 2006). Our network analyses (Fig. 7) revealed a high degree of

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genetic divergence when comparing our obtained V9 18S rDNA amplicons to deposited gene

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data. Such observations are not unusual, when it comes to low-abundant taxa (“rare OTUs”),

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because this category of organisms usually refers to the microbes that present themselves only

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very rarely under the microscope (Lynch et al., 2012). However, we find such a high genetic

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divergence even in the most abundant OTUs. Most of this genetic divergence lies in the

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cercozoans and the stramenopiles. But also in the ciliates, a taxon group that belongs to the

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morphologically best-characterized protists because of intense microscopy research for almost

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two centuries (Ehrenberg, 1838), we still find substantial genetic divergence.

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It remains unclear whether we are dealing with hitherto novel eukaryotic lineages or

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described but unsequenced eukaryotic groups. Taxonomic boundaries differ among various

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eukaryotic groups and a unified classification for 18S genera does not exist (Caron et al.,

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2009). Phylogenetic analyses of full length sequences are needed to accurately describe such

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hidden diversity and would help to uncover the unsequenced or novel status of such

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phylotypes. One approach would be the design of specific reverse primers targeting selected

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SWARMs, which in combination with more universal (but still group-specific) forward

361

primers would produce the near complete 18S rDNA fragment for a solid phylogenetic 14 This article is protected by copyright. All rights reserved.

analysis. Based on this fragment, specific FISH-probes could be designed for the hunt of the

363

corresponding morphotype in fixed sample material (Kolodziej and Stoeck, 2007; Massana

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and Pedrós-Alió, 2008). Previous hunts for organisms behind novel genes nicely demonstrate

365

that in bacteria (Lynch et al., 2012) as well as in protists novel genes often correspond to

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novel organisms (Kolodziej and Stoeck, 2007; Massana and Pedrós-Alió, 2008).

Accepted Article

362

367

Several approaches have been suggested in the literature of how to access the

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organisms behind novel genes and to reveal their taxonomic identity. Such approaches include

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the design of specific oligonucleotide probes targeting the new gene-bearing organisms

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microscopically (Kolodziej and Stoeck, 2007); or the single-cell sequencing of lugol-fixed

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and photo-documented cells from environmental samples (Auinger et al., 2008; Stoeck et al.,

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2014). Comparing genes with morphology is under the current circumstances more than

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difficult (for a detailed discussion we refer to Stoeck et al., 2014). A promising approach

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towards this goal is the comparison of taxonomic marker genes like the hypervariable V4

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region of the SSU rDNA (Pawlowski and Holzmann, 2014) in combination with deep-

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sequencing of as many freshwater habitats as possible. The tools are at hand and affordable.

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Even though taxonomic assignments of most of the obtained OTUs at a species-level are still

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not possible, novel and powerful computational tools are available for a multiple-sample

379

comparison (Bittner et al., 2010; Caporaso et al., 2010; Barberán et al., 2012; Lynch et al.,

380

2012) allowing the inference of geographical patterns of OTUs.

381 382

Experimental procedures

383 384 385

Sample collection Water samples were collected with a 5 l Niskin bottle (Hydro-Bios GmbH, Germany)

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from the mixolimnion (6-7 meters), the interface (18-19 meters) and the anoxic

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monimolimnion (22-23 meters) of lake Alatsee in autumn 2011 (October 27), spring 2012 15 This article is protected by copyright. All rights reserved.

(May 29) and summer 2012 (August 28). To avoid contact with the atmosphere, samples from

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the suboxic interface and the anoxic monimolimnion were directly transferred to evacuated

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and sterile 3 l Ethyl Vinyl Acetate bags (EVA bags, Baxter UK). Cells from each sample were

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collected on 0.65 µm Durapore membranes (Millipore Co.) under gentle pressure (< 50 ml

392

min-1) using a peristaltic pump (Ecoline ISM 1079, Ismatec, Germany). The filtration step

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was carried out in the field immediately after sampling. Depending on the cell concentration

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in each sample, 1.2 - 2.5 l of water was filtered per sample. To avoid oxygen contamination,

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the interface and monimolimnion samples were filtered by connecting the filtration system

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directly to the EVA bags. Three replicate membrane filters were obtained for each layer and

397

each season. The membranes were stored in RNAlater (Qiagen GmbH, Germany) for 24 h at

398

room temperature and then were frozen at - 80°C until further processing in the lab.

Accepted Article

388

399 400

DNA extraction, PCR amplification and Illumina sequencing

401

Each filter was cut with a sterile scalpel into smaller pieces and transferred to a Lysis

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Matrix E tube (MP Biomedicals, Germany), followed by the addition of 600 µl RLT-Buffer

403

and 6 µl β-mercaptoethanol. Filters were then shaken at 30 Hz for 45 s using a mixer mill

404

(MM200, Retsch, Germany). The tubes were centrifuged (14 000 rpm, 3 min), the supernatant

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was retained and DNA extraction followed the protocol of Qiagen GmbH (Hilden, Germany)

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All Prep DNA/RNA Mini kit (after step 4).

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The concentration of bulk DNA was measured spectrophotometrically (NanoDrop

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2000, Thermo Scientific, Wilmington, DE, USA). The hyper-variable V9 region of the 18S

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rRNA gene was amplified using the primers 1391F (5´-GTACACACCGCCCGTC-3´ (Lane,

410

1991), S. cerevisiae position 1629-1644) and EukB (5´-GATCCTTCTGCAGGTTCACCTAC

411

-3´ (Medlin et al., 1988), S. cerevisiae position 1773-1797). The highly conserved nature of

412

the 1391F primer appears to recover more taxa compared to eukaryotic-specific primers

413

targeting the same gene region (Amaral-Zettler et al., 2009). Primers were synthesized by 16 This article is protected by copyright. All rights reserved.

Biomers (Ulm, Germany) with a hexamer sample-specific identifier tagged to the primer

415

sequence (Table S1).

Accepted Article

414

416

The PCR mixture, containing 1 U of Phusion High Fidelity DNA Polymerase (New

417

England Biolabs), was heated to 98°C for 30 s and the V9 region was amplified by 27 cycles

418

consisting of 98°C for 10 s, 60°C for 30 s and 72°C for 30 s, followed by a final 10-min

419

elongation step at 72°C. To minimize potential PCR amplification bias, we performed 3

420

independent 50 µL PCR reactions for each layer and each season. The PCR products from all

421

amplifications were visualized by agarose gel electrophoresis (2%) under UV light. The three

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PCR reactions from the same layer of the same season were pooled together and purified

423

using the MiniElute® Reaction Cleanup kit (Qiagen GmbH, Germany).

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All V9 tags were sequenced with the Illumina MiSeq platform from the forward (5´-

425

end) and the reverse (3´- end) primer and the paired-end reads generated from the same

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amplicon were merged together with FLASH-1.2.4 (Magoč and Salzberg, 2011) by LGC

427

Genomics GmbH (Germany). The sequence tags have been deposited to NCBI’s Sequence

428

Read Archive (SRA) and can be found under the accession number SRP044320.

429 430 431

Sequence data processing Sequences with inaccurate hexamer identifiers, with one or with both primers incorrect

432

or incomplete and those containing one or more ambiguous nucleotides (Ns) were discarded

433

as “low quality” sequences, using QIIME v.1.7.0 (Caporaso et al., 2010). All sequences

434

starting with reverse primers were reverse complemented using a custom script. Sequences

435

with a length of 80 - 200 nucleotides, after trimming the primers were grouped into

436

Operational Taxonomic Units (OTUs) called at 100% to 89% sequence similarity in 1%-steps

437

using a modified pipeline script of usearch quality filter (usearch_qf, Edgar et al., 2011). In

438

detail, the modified script (available upon request from the authors) dereplicated the

439

sequences, sorted them by decreasing abundance and performed a de novo chimera check 17 This article is protected by copyright. All rights reserved.

using the UCHIME algorithm (Edgar et al., 2011). The detected chimeric sequences were

441

discarded and the remaining non-chimeric sequences were clustered using Uclust (Edgar et

442

al., 2010). The longest sequence of each cluster was picked as representative sequence of each

443

OTU for the following taxonomic analysis.

Accepted Article

440

444

Taxonomic affiliation for OTUs called at 95% sequence similarity (OTU95%, reasoning

445

see above) was performed with the software tool JAguc (Nebel et al., 2011) as described in

446

(Stoeck et al., 2010) using the non-redundant nucleotide NCBI database release 197.0. Non-

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target OTUs assigned to Archaea, Bacteria, Metazoa or Embryophyta were discarded from

448

downstream analyses. The classification of major protistan taxon groups followed Adl et al.,

449

(2012).

450 451 452

Community analyses Indices of alpha diversity and similarities among the samples (beta diversity) were

453

calculated with QIIME v.1.7.0. We used the Simpson’s index of diversity (1-D), as it provides

454

robust quantification and meaningful comparison of the microbial diversity in molecular data

455

sets (Haegeman et al., 2013). The Jaccard index was used as a measure of similarity between

456

the samples based on both abundance (Jabundance) and incidence (Jbinary). Prior to beta diversity

457

estimation, the number of sequences per sample was rarefied to the smallest sample by using

458

the single_rarefaction.py-script in QIIME. Jaccard similarity values were transformed to

459

distance matrixes for an Unweighted Pair Group Method with Arithmetic Mean (UPGMA)

460

cluster analyses. Bootstrap values were calculated to measure the robustness of the UPGMA

461

dendrogramms using the jackknifed_beta_diversity.py-script and considering a total of 1 000

462

support trees. Because community statistics predominantly relies on abundant taxa or OTUs

463

(see review Dunthorn et al., 2014), we here conducted community analyses with data sets

464

excluding OTUs that include less than three sequences to accelerate computation time for

465

millions of sequence reads. Previous molecular diversity studies with amplicon data sets and 18 This article is protected by copyright. All rights reserved.

statistical analyses have already convincingly and in detail shown that diversity patterns at the

467

community scale are not affected by the removal of rare OTUs (Gobet et al., 2010; Pommier

468

et al., 2010; Zinger et al., 2012).

Accepted Article

466

469 470 471

Analyses for the detection of divergent genetic diversity To identify divergent genetic protistan diversity in lake Alatsee, the cleaned Illumina-

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V9-reads of all depths and layers were combined, dereplicated and grouped using the

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SWARM clustering method (Mahé et al., 2014, https://github.com/torognes/swarm).

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SWARM group reads were based on a selected maximum number of nucleotide differences

475

(in this study d=1). Seed sequences (i.e. most abundant sequence of each swarm) were culled

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from the biggest 200 target swarms and subjected to BLAST analyses against Genbank´s nr

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nucleotide database (v. 201.0) to infer their taxonomic identity. The seed sequences of each

478

swarm were then aligned with Seaview (Galtier et al., 1996), prior to calculating sequence

479

similarities between each of the seed sequences using the custom script PairAligner (provided

480

by Dr. Markus Nebel, University of Kaiserslautern). The igraph R package (Csárdi and

481

Nepusz, 2006, R Development Core Team 2008) was used to build the network based on the

482

sequence similarity values. In this network two nodes were connected by an edge if they

483

shared a sequence similarity of at least 90%. The resulting network was visualized and

484

modified with Gephi v.0.8.2-beta (Bastian et al., 2009) according to the swarms’ taxonomic

485

affiliation and BLAST hit value.

486 487

Acknowledgments

488 489

This research was supported by grant STO414/10-1 of the Deutsche

490

Forschungsgemeinschaft (DFG) to TS. We are grateful to Maria Pachiadaki and Maria

491

Siegesmund for their valuable help in field sampling, to Lucie Bittner and Josef Schüle for 19 This article is protected by copyright. All rights reserved.

modifying the script usearch_qf in order to process large Illumina datasets. Katharina Zweig

493

is acknowledged for helping with estimations of the overlapping percentages of OTUs among

494

samples. We would also like to thank the authorities of the city of Füssen, Germany, for

495

permission to sample lake Alatsee.

Accepted Article

492

496 497

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Accepted Article

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of aquatic microbial diversity. Mol Ecol 21: 1878-1896.

Accepted Article

745

762 763

Table and Figure legends

764 765

Fig. 1. Depth profiles of oxygen, temperature, and sulfide in (A) autumn 2011, (B) spring

766

2012 and (C) summer 2012 in meromictic lake Alatsee. The grey area indicates the transition

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zone.

768 769

Fig. 2. Number of OTUs as a function of clustering threshold.

770 30 This article is protected by copyright. All rights reserved.

Fig. 3. Alpha diversity within each particular sample defined by the Simpson index (1-D).

772

Samples correspond to MIXO: mixolimnion (oxic), IF: interface, MONO: monimolimnion

773

(anoxic) and Au: autumn, Sp: spring, Su: summer.

Accepted Article

771

774 775

Fig. 4. Hierarchical clustering (Jabundance) of samples based on protistan and fungal OTUs95%,

776

after excluding OTUs that include less than three sequences. Bootstrap values indicate the

777

strength of the relationships in the UPGMA dendrogramm. Samples correspond to MIXO:

778

mixolimnion (oxic), IF: interface, MONO: monimolimnion (anoxic) and Au: autumn, Sp:

779

spring, Su: summer. The length of the reference bar represents a linkage distance of 0.02.

780 781

Fig. 5. Relative taxonomic distribution of classified protistan and fungal OTUs95%.

782

Taxonomic groups that were represented by a proportion of ≤ 1% of total number of OTUs in

783

at least one of the samples are grouped in the category Others. Samples correspond to MIXO:

784

mixolimnion (oxic), IF: interface, MONO: monimolimnion (anoxic) and Au: autumn, Sp:

785

spring, Su: summer.

786 787

Fig. 6. Taxonomic distribution of OTUs found exclusively in (A) oxic mixolimnion, (B)

788

interface and (C) anoxic monimolimnion in all examined seasons. Underlined color code

789

corresponds to inner circles. Outer rings represent the subcategories of the inner circles with

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> 5% of total number of OTUs and correspond to the numbered colors. Number (#) of OTUs

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denotes the total number of OTUs found exclusively in all seasons in each water mass. The

792

category “Others” denotes groups that were represented by a proportion of ≤ 1% of total

793

number of OTUs in each water mass.

794 795

Fig. 7. Divergent genetic diversity network of 200 most abundant swarms (OTUs95%) in lake

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Alatsee, pooled over depth and seasons. The node size is indicative of the number of 31 This article is protected by copyright. All rights reserved.

sequences in each swarm. Two nodes are connected if they share a sequence similarity of at

798

least 90%. The novelty level is denoted by BLAST identity against Genbank sequences, red-

799

orange: highly divergent swarms.

Accepted Article

797

800 801

Fig. S1. Hierarchical clustering (Jbinary) of samples based on protistan and fungal OTUs95%,

802

after excluding OTUs that include less than three sequences. Bootstrap values indicate the

803

strength of the relationships in the UPGMA dendrogramm. Samples correspond to MIXO:

804

mixolimnion (oxic), IF: interface, MONO: monimolimnion (anoxic) and Au: autumn, Sp:

805

spring, Su: summer. Protistan and fungal OTUs were clustered at a 95% similarity level. Bar

806

scales represent the proportion of linkage distance.

807 808

Table S1. Hexamer identifiers (in bold) used for distinguishing between the samples. Pr:

809

denotes the position of either the forward 1391F or the reverse EukB primer. We considered

810

carefully the combination of a highly conserved forward primer and a eukaryotic-specific

811

reverse primer to avoid biases towards few eukaryotic taxa. The initial bases (underlined)

812

were added before the hexamers to avoid a too strong light signal generated by the first bases

813

at the beginning of the sequencing procedure. Samples 5´-Initial bases-Hexamer-Pr-3´ MIXO-Au TGC-AGCGTC-Pr IF-Au TAGT-ATACTC-Pr MONO-Au C-ATCGAC-Pr MIXO-Sp T-ACACAC-Pr IF-Sp AT-ACGAGC-Pr MONO-Sp ATC-AGACGC-Pr MIXO-Su ACAG-ACTATC-Pr IF-Su T-AGCTAC-Pr MONO-Su TC-ATACTC-Pr

814

32 This article is protected by copyright. All rights reserved.

Oxygen concentration [mg l-1] & Temperature [°C]

A

0

5

10

15

20

25

80

100

Oxygen 5

Temperature Sulfide

10

Depth

Accepted Article

0

15 20 25 30 0

20

40

60

Sulfide concentration [mg l-1]

B

Oxygen concentration [mg l-1] & Temperature [°C] 0

5

10

15

20

25

0

20

40

60

80

100

0

5

Depth

10

15

20

25

30

Sulfide concentration [mg

l-1]

Oxygen concentration [mg l-1] & Temperature [°C]

C

0

5

0

20

10

15

20

25

40

60

80

100

0

5

Depth

10

15

20

25

30

EMI_12666_F1.eps

Sulfide concentration [mg l-1]

Accepted Article 600000

Number of OTUs

500000

400000

300000

200000

100000

0

100

EMI_12666_F2.eps

99

98

97

96

95

94

Clustering threshold (%)

93

92

91

90

89

Accepted Article 0.99 0.97

Simpson index

0.95 0.93 0.91 0.89 0.87 0.85

EMI_12666_F3.eps

Samples

Accepted Article

EMI_12666_F4.eps

MIXO-Au

1

MIXO-Sp

0.88

MIXO-Su IF-Au

0.98

IF-Su 1

1 0.98 0.98

IF-Sp MONO-Sp MONO-Au MONO-Su

Accepted Article 100% 90%

Percentage of classified OTUs

80%

Others

70%

Stramenopiles Metamonada

60%

Amoebozoa Euglenozoa

50%

Fungi

40%

Chlorophyta Cryptophyta

30%

Dinoflagellata

Ciliophora

20% 10%

0%

EMI_12666_F5.eps

Samples

Accepted Article A)

B)

MIXOLIMNION # of OTUs: 412

1

3

C)

INTERFACE

# of OTUs: 23

1

1

2 4

7 8 3 6

2

5 2

3

1

6 3

3

3

2

1

1

2

1

1

# of OTUs: 111

1

2

2

MONIMOLIMNION

1

2 3 1

2 9 6 43

5

1 6

4

2 5

1

3

Ciliophora

Stramenopiles

Euglenozoa

Metamonada

Centrohelida

1 2 3 4 5 6 7 8 9

1 2 3 4 5 6

1 Kinetoplastea 2 Euglinida

1 Diplomonadida 2 Preaxostyla 3 Parabasalia Chlorophyta

Protalveolata

1 Ulvophyceae 2 Chlorophyceae 3 Mamiellophyceae Cercozoa

Others

Spirotrichea Colpodea Protostomatea Nassophorea Heterotricheaa Oligohymenophorea Armophorea Karyorelictea Other Ciliophora

EMI_12666_F6.eps

Chrysophyceae Synurales Raphidiophyceae Bolidomonas Bicosoecida Other Stramenopiles

Cryptophyta 1 Cryptomonadales 2 Pyrenomonadales

Dinoflagellata

Amoebozoa

1 Peridiniphycidae 2 Gymnodiniphycidae 3 Other Dinoflagellata

1 Archamoebae 2 Discocea 3 Other Amoebozoa

1 Cercomonadidae 2 Other Cercozoa

Fungi Apusomonadida

Accepted Article

EMI_12666_F7.eps