EXPLORING THE DIVERSITY OF N I V I C O L O U S M Y X O M Y C E T E S: An analysis of the genetic diversity, species distribution and community composition

I N A U G U R A L D I S S E R T A T I O N

Zur

Erlangung des akademischen Grades eines

Doctor rerum naturalium (Dr. rer. nat.)

an der Mathematisch-Naturwissenschaftlichen Fakultät

der

Universität Greifswald

vorgelegt von:

Mathilde Borg Dahl

Greifswald, 30. Januar 2018

Dekan: Prof. Dr. Werner Weitschies 1. Gutachter: Prof. Dr. Martin Schnittler 2. Gutachter: Ass. Prof. Regin Rønn 3. Gutachter: Prof. Carsten Suhr Jacobsen

Tag der Promotion: 1. Oktober 2018 PREFACE

This cumulative dissertation is a product of my just under three years enrolment in the graduate school RESPONSE (GRK 2010) under the supervision of Prof. Dr. Martin Schnittler. In these years I have conducted fieldwork (including seven trips to the German Alps and a journey to the Rocky Mountains) to collect nivicolous myxomycetes and soil. I have done numerous (~700) DNA extractions and obtained sequences of the collected specimens (Greifswald, DE) as well as an Illumina library (3x 48 samples) of myxamoebae, fungi and bacteria (Copenhagen, DK). In addition I have participated in international conferences in the Czech Republic (Ecology of Soil Microorganisms, 2015), Germany (3rd Thünen Symposium on Soil Metagenomics, 2016) and Canada (The ISME conference, 2016). All of the information presented henceforth was obtained from my original independent work with collaborations with experts from around the world. I was fortunate to work with Prof. Søren J. Sørensen (University of Copenhagen, Denmark) and his lab who specialize in molecular techniques and Illumina sequencing. I also had the pleasure of visiting the laboratory of Prof. Steven K. Schmidt (University of Boulder, Colorado, USA), whose working group specializes in under-snow microbial communities. Finally my study benefitted from the collaboration with Prof. Yuri K. Novozhilov (Komarov Botanical Institute, St. Petersburg, Russia) an expert among myxomycetes taxonomist. After the abstract in Chapter 1 and a general introduction in Chapter 2, four manuscripts (on three of which I am first author) are presented in Chapter 3. Chapter 3.1 aims at establishing species delimitation of dark-spored myxomycetes by the use of a genetic marker (SSU; small subunit ribosomal RNA) and the complications in doing so are discussed. Chapter 3.2 reviews the state-of-the-art barcoding methods for myxomycetes and their potential as well as challenges and limitations are discussed. Chapter 3.3 presents an ecological study of the distribution of dark-spored myxamoebae along a natural altitudinal gradient; demonstrating fine scale niche differentiation as well as taxa specific interactions with bacteria. Finally, Chapter 3.4 presents a comparative study between the distribution of soil myxamoebae and a quantitative fructification collection from a natural altitudinal gradient in the German Alps, as well as a year to year comparison in fructification success in relation to climatic conditions. Chapter 4 summarizes the important findings of this dissertation and highlights its significant contributions to the current knowledge on 1) barcoding and 2) niche differentiation among myxamoebae in natural habitats of dark-spored myxomycetes.

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LIST OF PUBLICATIONS INCLUDED IN THIS DISSERTATION

ACCEPTED IN PEER REVIEWED JOURNALS  Borg Dahl M, Brejnrod A, Unterseher M, Hoppe T, Feng Y, Novozhilov YK, Sørensen SJ and Schnittler M (2017) Genetic barcoding of dark-spored myxomycetes (Amoebozoa) – identification, evaluation and application of an identification threshold for species differentiation in NGS studies. Molecular Ecology Resources 1–13. doi: 10.1111/1755- 0998.12725.

 Schnittler M, Shchepin O, Dagamac N, Borg Dahl M and Novozhilov YK (2017). Barcoding myxomycetes with molecular markers: challenges and opportunities. Nova Hedwigia 104:23– 341. doi: 10.1127/nova_hedwigia/2017/0397.

MANUSCRIPTS SUBMITTED FOR PEER REVIEW  Borg Dahl M, Brejnrod A, Russel J, Sørensen SJ and Schnittler M (2017) Fine scale niche differentiation among amoebal communities of dark-spored myxomycetes determined by landscape structures as well as biotic factors. Environmental Microbiology (Submitted 30.12.2017).

 Borg Dahl M, Shchepin O, Schunk C, Menzel A, Novozhilov YK and Schnittler M (2017) Distribution patterns between fruit bodies and soil amoebae of nivicolous myxomycetes. Ecology (Submitted 26.01.2018).

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CONTENT

Preface ...... i

Manuscripts submitted for peer review ...... ii

Contents ...... iii

1 Abstract ...... 1

1.1 Deutsch ...... 1

1.2 English ...... 2

2 General introduction ...... 5

2.1 Background ...... 6

2.2 Field work ...... 9

2.3 Conceptual framework of RESPONSE ...... 12

2.4 Objectives of the thesis ...... 13

2.5 Literature ...... 14

3 Publications ...... 19

3.1 Genetic barcoding of dark-spored myxomycetes (Amoebozoa) – identification, evaluation and application of an identification threshold for species differentiation in NGS studies ...... 20

3.2 Barcoding myxomycetes with molecular markers: challenges and opportunities ...... 43

3.3 Fine scale niche differentiation among amoebal communities of dark-spored myxomycetes determined by landscape structures as well as biotic factors ...... 67

3.4 Distribution patterns between fruit bodies and soil amoebae of nivicolous myxomycetes ...... 91

4 Conclusions and perspectives ...... 108

4.1 Main findings ...... 108

4.2 Challenges and limitations ...... 109

4.3 Citations ...... 109

5 Affidavits...... 110

5.1 Selbstständigkeitserklärung / Declaration ...... 110

5.2 Erklärung bei Gemeinschaftsarbeiten (Eigenanteil)/ Declaration for thesis works with joint publication (own contribution) ...... 111

5.3 Erklärung zur Abgabe einer elektronischen Kopie der Dissertation Declaration on the submission of an electronic copy of the PhD thesis ...... 113

6 Acknowledgement ...... 114

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1 ABSTRACT

1.1 DEUTSCH Myxomyceten sind Protisten, die der Großgruppe der Amöben (Amoebozoa) zugerechnet werden. Nach dem traditionellen, inzwischen durch molekulare Phylogenien überholten, System werden sie in fünf Ordnungen gegliedert: Liceales, Trichiales, Physarales, Stemonitales und Echinosteliales. Molekulare Phylogenien zeigen jedoch zwei basale Gruppen: Physarales und Stemonitales (die sogenannten dunkelsportigen Myxomyceten) als eine und die anderen genannten Ordnungen (die hellsporigen Myxomyceten) als zweite. Außer den Echinosteliales ist jedoch keine der Ordnungen monophyletisch; sie müssen neu gefasst werden. Die dunkelsporigen Myxomyceten umfassen die Mehrzahl der beschriebenen Morphospezies. Aufgrund der hohen genetischen Divergenz in DNA- Sequenzen zwischen den hell- und dunkelsportigen Myxomyceten werden in dieser Dissertation nur die letzteren berücksichtigt. Aufgrund ihrer kleinen, aber makroskopisch sichtbaren Fruktifikationen wurden die ersten Vertreter jedoch als Pilze beschrieben. Diese Fruchtkörper weisen genug Merkmale auf, um ein morphologisches Artkonzept anzuwenden, nach dem derzeit etwa 1000 Arten beschrieben sind. Basierend auf den im Gelände sichtbaren Fruktifikationen, die herbarisiert werden können, werden bereits seit 200 Jahren Studien zur Diversität von Myxomyceten duchgeführt; daher existieren umfangreiche Daten zur Ökologie und Verbreitung ihrer Fruchtkörper. Aus diesen Arbeiten ist bekannt, dass Myxomyceten charakteristische Gemeinschaften in verschiedensten terrestrischen Ökosystemen bilden und oft hoch spezifische Habitatansprüche stellen. So fruktifizieren manche Arten am Rande des schmelzenden Schnees im Gebirge (nivicole Myxomyceten), andere bevorzugen Dung von Pflanzenfressern (koprophil); eine weitere große Artengemeinschaft bevorzugt sich zersetzendes Holz (xylophil). Im Gegensatz zur Ökologie der Fruktifikationen ist relativ wenig über die Myxamöben bekannt, die den trophischen Lebensabschnitt von Myxomyceten darstellen. Neue molekulare Methoden, wie die direkte Identifikation von Arten mittels DNS-Sequenzen aus Umweltproben (ePCR), ermöglichen heute die Untersuchung von Myxamöben (und anderer Mikroorganismen). Aus ersten molekularbiologischen Studien geht hervor, dass Myxomyceten in vielen verschiedenen Bodenarten vorhanden sind und zwischen 5-50% der im Boden vorkommenden Amöben ausmachen. Um diese neuen Methoden adäquat nutzen zu können ist es nötig, molekulare DNS Marker zu etablieren und Referenzdatenbanken mit den entsprechenden Sequenzen aus akkurat bestimmten Fruktifikationen anzulegen. Damit ein Markergen zur Identifikation von Arten genutzt werden kann, muss dieses möglichst große Unterschiede zwischen Arten aufweisen und gleichzeitig möglichst uniform innerhalb einer Art sein („barcoding gap“). Im ersten Teil der hier vorliegenden Arbeit (Artikel I und II) wird die Etablierung eines solchen DNS- Markers mit der dazugehörenden Datenbank beschrieben. Dabei wird auch auf die Anwendbarkeit verschiedener Artkonzepte auf Myxomyceten eingegangen. Hierfür wurden insgesamt 1200 Aufsammlungen von Fruchtkörpern sequenziert und zu einer Datenbank zusammengestellt (zum jetzigen Zeitpunkt die größte Datenbank für eine der beiden großen Gruppen innerhalb dieser Organismen, die dunkelsporigen Myxomyceten). Genetische Distanzen zwischen zwei Sequenzen wurden genutzt, um die genetische Struktur innerhalb einer Morphospezies zu ermitteln und damit eventuell vorhandene kryptische Arten zu identifizieren. Die so geschätzte verborgene Diversität überstieg die Diversität der Morphospezies um 99%. Der optimale Grenzwert der Ähnlichkeit zweier Sequenzen zur Unterscheidung von Arten mit Hilfe von SSU- Markern betrug 99,1%. Im zweiten Teil der vorliegenden Arbeit (Artikel III und IV) wird der etablierte Grenzwert sowie die erstellte Datenbank genutzt, um Daten zu Gemeinschaften von Myxamöben in Böden zu generieren.

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Es wird untersucht, ob man vom Vorkommen der Fruchtkörpern auf die Verbreitung von Myxamöben schließen kann. In diesem Zusammenhang wird diskutiert, ob Myxomyceten als Amöben eine größere realisierte Nische aufweisen als in Form ihrer Fruchtkörper und ob die Verbreitung von Myxamöben in Verbindung zum Vorkommen potentieller Beuteorganismen (Pilze und Bakterien) steht.

Paralleles Metabarcoding von Bakterien, Pilzen und dunkelsporigen Myxomyceten in alpinen Böden wird in Artikel III vorgestellt; hier wurden die mikrobiellen Gemeinschaften entlang eines Höhentransekts in den nördlichen Kalkalpen analysiert (48 Proben). Mittels Illumina-Sequenzierung wurden aus den Bodenproben 1.68 Millionen Sequenzen aus einem Abschnitt des rRNA Genes gelesen, die für die Myxomyceten 578 Ribotypen (operational taxonomic units – OTU) zugeordnet wurden. Diese weisen eine hohe Ähnlichkeit (>98%) zu Ribotypen aus 42 morphologisch bestimmten Arten auf (die entsprechenden Zahlen für Bakterien und Pilze betrugen 2.16/5710/215 bzw. 3.67/6133/260). Mit multivariate Analysen wird das Vorkommen verschiedener Mikroben in Beziehung zu Umweltparametern gesetzt, um diskriminierende Faktoren für das Vorkommen von Myxamöben und die Grenzen ihrer ökologischen Nischen zu bestimmen.

Potentielle Interaktionen zwischen den drei Organismengemeinschaften wurden identifiziert und analysiert, indem die Zusammensetzung der Gemeinschaften mit phylogenetischen Eigenschaften sowie mit Umweltparametern in Verbindung gebracht wurden. Für alle drei Gemeinschaften wurde die Zusammensetzung hauptsächlich durch die Vegetation bestimmt. Bakterien- und Pilzegemeinschaften zeigten diesbezüglich ähnliche Reaktionen, bedingt durch das Vorkommen von potentiell symbiontischenr Pflanzen (Mykorrhizapartner) bzw. Substrate (sich zersetzendes Pflanzenmaterial). Im Unterschied zu Bakterien und Pilzen zeigen Myxamöben eine lückenhaftere, deutlich lokalere Verbreitung und deutliche Unterschiede innerhalb einzelner Gattungen. Dies scheint in Zusammenhang zur Habitatstruktur und den vorkommenden Bakterienarten zu stehen. Die Artenzusammensetzung aller drei Gruppen änderte sich entlang der Höhentransekte, vermutlich in Anpassungen an die mit der Höhe zunehmend härteren Umweltbedingungen. Zusätzlich wurde eine Vielzahl von Sequenzen (Operational Taxonomic Units – OTUs) für Myxomyceten gefunden, die denen der Gattung Lamproderma ähnelten, aber keiner von Fruktifikationen beschriebenen Art zugeordnet werden konnten. Dies ist die erste Studie, in der die ökologischen Nischen nivicoler Myxomyceten und damit die kleinräumige Nischendifferenzierung eines räuberischen Bodenprotisten beschrieben wurde. Zusätzlich wurde verucht, potentielle Beuteorganismen, aber auch potentiell antagonistische Interaktionen, zu identifizieren.

Artikel IV vergleicht abschließend die Verbreitung von Myxamöben im Boden (entsprechend der mit ePCR ermittelten Sequenzen) mit den gesammelten Fruchtkörpern im selben Gebiet (714 bestimmte Aufsammlungen von 30 Morphospezies, die zu 70 Ribotypen gehören, welche wiederum 45 Ribotypgruppen bilden, wenn ein Schwellenwert von 99.1% zugrunde gelegt wird). Die Studie zeigt einen deutlichen Zusammenhang der beiden Inventurmethoden. Die relativen Häufigkeiten der einzelnen Arten (als Fruchtkörper bzw. als Zahl der in Bodenproben ermittelten Sequenzen) unterscheiden sich jedoch stark, was zumindest teilweise auf die verschieden gute Sichtbarkeit der Fruchtkörper verschiedener Arten zurückzuführen ist. Zusätzlich konnte durch den Vergleich mehrerer Jahre die Hypothese bestätigt werden, dass die Anzahl der Fruchtkörper stark vom Einsetzen des Schneefalls im Herbst des Vorjahres und der Bodentemperatur während des Winters abhängt.

1.2 ENGLISH Myxomycetes are protists belonging to the super-group Amoebozoa. The traditional taxonomic system, which is now largely outdated by molecular studies, recognizes five orders: Liceales, Trichiales,

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Physarales, Stemonitales and Echinosteliales. Molecular phylogenies revealed two basal clades: Physarales and Stemonitales (the so-called dark-spored myxomycetes) are the first; the other above- mentioned orders form the second (the bright-spored myxomycetes). However, except for Echinosteliales none of the traditional orders appears to be monophyletic in the traditionally used delimitation. The dark-spored myxomycetes encompass the majority of the described morphospecies. Due to the high genetic divergence in DNA sequences between the bright- and dark-spored myxomycetes, only the latter are considered in this dissertation. Historically myxomycetes have been described as fungi, due to their macroscopically visible fructifications which, though considerably smaller, resemble those of fungi. These fruit bodies provide enough morphological traits to support a morphological species concept with currently ca. 1000 species described. Therefore diversity studies of myxomycetes have been conducted for over 200 years and a substantial body of data on ecology and distribution of these fructifications exist. From these studies myxomycetes are known to form often distinct communities across terrestrial ecosystems with highly specific habitat requirements, such as snowbanks (nivicolous), herbivore dung (coprophilous) or decaying wood (xylophilous). However knowledge on the myxamoebae – the trophic life stage of the myxomycetes – is very scarce. Only recent advances in molecular techniques such as direct species identification based on DNA sequences from environmental samples (ePCR), have made studies of myxamoebae (and other microbes) possible. From these first molecular based studies myxomycetes are currently estimated to account for between 5 to almost 50% of all soil amoebae, and have been shown to be present in a wide variety of soils. To fully take advantage of these new methods, a molecular DNA marker needs to be established as well as a reference sequence database. The usability of a DNA marker gene depends on its ability to separate species by a distinction between intra- and interspecific divergence between sequences of the same and related species, the so-called ‘barcoding gap’.

The first part of this thesis (article I and II) deals with the subject of establishing such a DNA marker and database, and in doing so touches upon the subject of ‘what is a myxomycetes species?’

A total of 1 200 specimens were compiled into a reference database (the largest database to date of dark-spored myxomycetes). The genetic distance from sequence-to-sequence was used to assess genetic clade structures within morphospecies and putative biospecies (sexually isolated linages) were identified. The result was an estimate of hidden diversity, exceeding that of described morphospecies by 99%. The optimum sequence similarity threshold for OTU-picking (genetic species differentiation, denoted Operational Taxonomic Unit) with the used SSU marker was identified as 99.1% similarity.

The second part of this thesis (article III and IV) presents ecological studies conducted with NGS (ePCR) in which the established threshold and database are applied and are demonstrated to provide reliable and novel insights into the soil myxamoebae community. It is investigated whether the occurrence of fruit bodies reflects the distribution of soil myxamoebae, and the research questions ‘do myxomycetes show broader realized niches as soil amoebae than as fructifications?’ and ‘are myxamoebae distributions correlated to potential prey organisms (fungi and bacteria)?’ are investigated.

In the ecological study presented in article III parallel metabarcoding of bacteria, fungi and dark-spored myxomycete was used for the first time in a joint approach to analyze the communities from an elevational transect in the northern limestone German Alps (48 soil samples). Illumina sequencing of the soil samples revealed 1.68 Mio sequences of a section of the rRNA gene, which were assigned to 578 operational taxonomic units (OTU) from myxomycetes. These show a high similarity (>98%) to 42 different morphospecies (the respective figures for bacteria and fungi were 2.16/5710/215 and 3.68/6133/260, respectively). Multivariate analyses were carried out to disentangle microbial interplay

3 and to identify the main environmental parameters determining the distribution of myxamoebae and thus setting the boundaries for their ecological niches. Potential interactions between the three target organisms were analysed by integrating community composition and phylogenetic diversity with environmental parameters. We identified niche differentiation for all three communities (bacteria, fungi and myxamoebae) which was strongly driven by the vegetation. Bacteria and fungi displayed similar community responses, driven by symbiont species and plant substrate quality. Myxamoebae showed a more patchy distribution, though still clearly stratified among genera, which seemed to be a response to both structural properties of the habitat and specific bacterial taxa. In addition we find an altitudinal species turn-over for all three communities, most likely explained by adaptation to harsh environmental conditions. Finally a high number of myxomycetes OTUs (associated with the genus Lamproderma) not currently represented in our reference database were found, representing potentially novel species. This study is the first to report niche differentiation between the guild of nivicolous (“snowbank”) myxomycetes and thus fine-scale niche differentiation among a predatory soil protist; identifying both potential food preferences and antagonistic interactions with specific bacterial taxa.

Finally, the second ecological study (article IV) focuses on comparing the distribution of myxamoebae revealed by ePCR of soil samples with fructifications collected from the same area (714 specimens determined to 30 morphospecies, which form 70 unique ribotypes that can be assigned to 45 ribotype clusters using a 99.1% similarity threshold). The study found a strong coherency between the two inventories, though with species specific relative differences in abundance, which can in part be attributed to the visibility of the fructifications. In addition, a year to year comparison of fructification records gives support to the hypothesis that the abundance of fructifications depends strongly on the onset of snowfall in the previous autumn and the soil temperature regime throughout the winter.

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2 GENERAL INTRODUCTION

CHAPTERS PAGE 2.1 BACKGROUND 6 2.1.1 Myxomycetes – life style and taxonomic position 6 2.1.2 Multiple species concepts in myxomycetes 7 2.1.3 Myxomycetes in the soil food web – Microbial ecosystems 8 2.2 FIELD WORK 9 2.3 THE CONCEPTUAL FRAMEWORK OF RESPONSE 12 2.4 OBJECTIVES OF THE THESIS 13 2.5 LITERATURE 14

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2.1 BACKGROUND

2.1.1 Myxomycetes – life style and taxonomic position Myxomycetes, also known as slime molds, are protists belonging to the super-group Amoebozoa. Historically they have been described as fungi, due to their macroscopically visible fructifications which though considerably smaller, resemble those of fungi1,2. These fructifications are a result of a completed life cycle starting as free living unicellular soil amoebae (myxamoebae), which undergo cell fusion, to produce a multi-nucleus plasmodium. The plasmodia then moves to elevated points (typically twigs or culms of grass), where sporocarps (fruit bodies) emerge, containing thousands of encapsulated spores ready to disperse and hatch into new soil myxamoebae (Figure 1a). In the soil the myxamoebae undergo mitosis and cytoplasmic division creating large numbers of clonal populations. In unfavourable conditions both the myxamoebae and the plasmodia can enter into dormant stages known as microcysts and sclerotium respectively. Their reproduction mode is currently under discussion3 (see section 2.1.3) and meiosis may (resulting in haploid spores) or may not (apomixis) occur during spore formation. The traditional taxonomic system, which is now largely outdated by molecular studies, recognizes five orders: Liceales, Trichiales, Physarales, Stemonitales and Echinosteliales. Molecular phylogenies revealed two basal clades: Physarales and Stemonitales (the so-called dark-spored myxomycetes) are the first; the other above-mentioned orders form the second (the bright-spored myxomycetes)2. However, except for Echinosteliales none of the traditional orders appears to be monophyletic in the traditionally used delimitation. The dark-spored myxomycetes encompass the majority of described morphospecies2,4–6 (Figure 1b). This deep split between the dark- and bright-spored myxomycetes, has resulted in high levels of sequence divergence between the two groups. Thus no genetic markers have yet been discovered which can on one hand resolve species5–10 but at the other hand are conservative enough to allow meaningful joint alignments of both groups. Consequently, this dissertation only considers the dark-spored myxomycetes. The fruit bodies alone provide sufficient morphological traits to support a morphological species concept with currently ca. 1000 species described11.

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Figure 1 A) The typical life cycle of a myxomycete (adapted from Rollins & Stephenson 201112). B) Phylogeny of Myxomycetes based on concatenated sequences of the elongation factor 1-alpha (EF1A) and small subunit (SSU) rRNA genes (adapted from Fiore-Donno et al 20054).

2.1.2 Multiple species concepts in myxomycetes Only a minority of myxomycetes can be induced to complete its cycle and thus form fruit bodies under laboratory conditions. Thus, empirical evidence of whether all morphospecies reflect true biospecies is lacking13. Biospecies are defined as compatible strains of haploid amoeboflagellate (myxamoebae) which can fuse and produce the diploid plasmodium – in other words, a classical sexual reproduction system14,15. In addition, early culture experiments proved the existence of presumably asexual strains (homothallic; self-fertilization or apogamic; without meiosis)15. With modern molecular techniques, the sequencing of genetic markers has provided a chance to verify the biospecies concept for natural populations of uncultivable species and to check for possible reproductive modes3,16. First studies indicated the possibility of asexual reproduction by the existence of fruit bodies from presumably clonal linages in natural habitats17, but recent studies3,10 concluded that sexual reproduction seems to dominate in natural populations, in line with studies showing sexual reproduction as a hallmark of eukaryotic life18. The usability of a DNA barcode depends on its ability to separate species by a distinction between intra- and interspecific divergence for sequences of the same and related species, the so-called ‘barcoding gap’19. Once established, ‘barcoding’ holds an enormous potential for obtaining accurate and highly detailed data on hitherto inaccessible organisms, as most microbes are. Partial sequences of the 18S rRNA gene (SSU) have been suggested as a universal eukaryotic DNA barcode20–23 due to the advantages of occurring as a multi copy gene and the homologous nature of the gene. Accordingly, SSU markers have now been successfully used for assignment of sequences to known species for a number of protists24–31. In cases of sexual reproduction a combination of independent genetic markers can be used to characterize sexually isolated lineages which represent

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putative biospecies by demonstrating exclusive recombination patterns, as demonstrated in Figure 2. Therefore, markers such as the protein elongation factor 1 alpha (EF1A, chromosomal) and the cytochrome oxydase (COI, mitochrondrial) gene, have been used as markers complementary to SSU, although these single copy genes may less readily amplify. In the few studies available which have used such loci, the patterns obtained were largely congruent with those obtained for the SSU marker3,6,10, and so it seemed reasonable to establish the SSU sequence as a barcode marker for myxomycetes as well. In Chapter 3.2 an extended discussion on the barcoding challenge in myxomycetes is presented in the form of a review.

Figure 2 An example of exclusive recombination patterns for the genetic markers SSU and COI indicating three sexually isolated linages (denoted group 1, 2a and 2b) in the bright-spored myxomycete morphospecies Trichia varia (adapted from Feng & Schnittler 201510). In chapter 3.1 a study dedicated to establishing a sequence similarity threshold for species delimitation of myxomycetes, so-called OTU-picking is presented. The study takes advantage of a large collection of specimens and expert knowledge on morphological characteristics and combines this with a partial SSU marker. The existence of a barcode gap in the vast majority of dark-spored myxomycetes is demonstrated and a threshold for OTU-picking is identified. The threshold is applied to an analysis of the myxomycete community in soil from the Northern Caucasus region. The study resulted in a large increase in estimated myxomycete taxa, thus as for many microbial groups, the true diversity of myxomycetes seems to be much greater than shown by morphological characters32, and many described morphospecies seem to consist of groups of several cryptic species3,10,33,34.

2.1.3 Myxomycetes in the soil food web – Microbial ecosystems Much of what is currently known about myxomycete assemblages and diversity has been derived from intensive local surveys based on the morphology of the fruit bodies35–37. Such diversity studies have been conducted for over 200 years and a substantial body of data on ecology and distribution of these fructifications exist38. From these studies myxomycetes are often known to form distinct communities across terrestrial ecosystems with highly specific habitat requirements, such as snowbanks (nivicolous), herbivore dung (coprophilous) or decaying wood (xylophilous)38–40. However, knowledge on abundance of myxamoebae and structure of their communities in natural environments is nearly completely lacking. The myxamoebae however, are the trophic life stages of the myxomycetes and it

8 is in this stage that they will interact and affect other members of the soil food web. Together with other unicellular eukaryotes myxamoebae are major predators of bacteria41–43 and fungi44 and thus influence major ecosystem processes such as nutrient turn-over, the activity of other microbes and consequently, of higher trophic levels and plant growth43,45–48. Only recent advances in molecular techniques have made it possible to study myxamoebae (and other microbes) in samples deriving from natural environments49–54. Due to the non-monophyletic nature of protists20,55–57, no universal primers can be developed for this group58–60 and the ‘general’ eukaryotic primers61–63 often used in studies targeting microbial eukaryotes do not amplify in myxomycetes49,63. Therefore myxomycetes have until recently been overlooked in ePCR amplicon studies. However with improved sequencing techniques and the rise of unspecific amplification52,64 myxomycetes have in recent studies been estimated to account for between 5 to almost 50% of all soil amoebae, and have also been shown to be present in a wide variety of soils52,64,65. One of the most distinct ecological guilds in myxomycetes and the main focus of this PhD thesis constitutes the nivicolous or “snowbank” species, with their specific habitat requirements first described in 1908 by Meylan66. The ca. 100 described species nearly all belong to the dark-spored myxomycetes5,6. Fruiting occurs in spring along the edge of melting snowbanks in mountains, with most accounts coming from the northern hemisphere67,68. They are hypothesized to prey on microbial communities beneath the snow, and their fruiting may be triggered by the change in abiotic conditions during snow melt69,70, which have been shown to cause a nearly complete turnover of microbial communities71. Distribution patterns of fruit body occurrences, have indicated that nivicolous species seem to exhibit a wide variety of species-specific preferences for elevation and vegetation types35,67,68. However, fruiting may occur only with optimal conditions, as suggested by a metabarcoding study from the German lowland regions49 where sequences assignable to nivicolous myxomycetes occurred at places where fruit bodies of these species were never recorded. As such, nivicolous myxomycetes may show broader realized niches as soil amoebae than can be observed from fructifications. In Chapter 3.3 an analysis of the myxamoebae distribution is presented in a combined approach to analyse the soil microbial communities by parallel metabarcoding of bacterial, fungal and nivicolous myxomycete along an elevational transect in the northern limestone Alps (Garmisch-Partenkirchen, Germany). Furthermore, recent studies have shown that the myxamoebae are quite susceptible to low temperatures72 and the abundance of fructifications seems to strongly depend upon the onset of snowfall in the previous autumn and the duration of contiguous snow cover throughout the winter69. In Chapter 3.4 the relationship between fructification success and winter climate conditions is investigated. A comparative study between the soil myxamoebae and the fructification records are reported as well as year-to-year variation in climatic conditions and subsequent fructification success from four consecutive survey years along the transect in the German Alps.

2.2 FIELD WORK

The main field work undertaken in this thesis was conducted at an elevational transect in the Kreuzjoch region below the Alpspitz summit near Garmisch-Partenkirchen in the German limestone Alps (Figure 3). The transect reaches from the Bayernhaus (47°27’55” N, 11°12'40” E, ca. 1 200 m a.s.l.) to the Osterfelder Kopf (47°26’20” N, 11°03'00” E, ca. 2 050 m a.s.l.), crossing several vegetation belts, including lowland deciduous forest, open conifer mountainous forest and above tree line scrubland. The transect was surveyed in spring of 2015, 2016 and 2017 (in addition the area was initially surveyed by the working group AG Schnittler in 2013, prior to the start of my project). Myxomycete colonies were found directly on the soil or on plant litter and/or twigs (occasionally on plant branches several

9 meters above the ground, most likely when branches hold down by snow packs returned to their original position.

Figure 3 Satellite image of the transect area and representative images of the soil sampling sites. Sites are marked with yellow pins. Numbers refers to elevation level 1 to 8; 1 200 to 1 900 m a.s.l, in 100 m steps. respectively. op: open canopy site, cl: closed canopy site, when in close proximity of each other only one mark (yellow) is given. Source map: Google Earth June 2017. Site photos by myself. Myxomycete colonies can vary in size from a few fruit bodies to several hundred. Colonies can be preserved for long term storage by gluing whatever substrate they are on into cardboard boxes (corresponding to match boxes) where their morphological appearance can persist for decades (Figure 4). However DNA extraction should be undertaken as soon after collection as possible, as the DNA quality and yield tend to decrease with time since collection, and it can be difficult to obtain good quality DNA from specimens more than five years old (personal observation during the course of this study).

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Figure 4 A representative collection of images of myxomycete colonies, demonstrating the broad morphological variety found within the dark-spored nivicolous myxomycetes and a collection box to illustrate how specimens are collected and stored. Photos are taken through the lens of a dissecting microscope (x10 magnification) by myself.

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2.3 CONCEPTUAL FRAMEWORK OF RESPONSE

This study was conducted as part of the first generation of research projects in the graduate school “Biological RESPONSEs to Novel and Changing Environments“(in short RESPONSE). Here it was part of the research cluster B (Dispersal), with the aim to understand the factors associated with species’ successful colonisation of new habitats (see research goals, RESPONSE1). Applying this research aim to the study of myxomycetes meant answering some – for non-microbiologist – basic ecological questions for these organisms, such as “What is the unit we can call a species?” and “What environmental parameters are determining the ecological niche of a myxomycete species?” The specific research objectives for this thesis are summarized in the following section.

1 From the RESPONSE web site: https://biologie.uni-greifswald.de/forschung/dfg-graduiertenkollegs/research- training-group-2010/research-projects/ accesses 03.01.2018.

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2.4 OBJECTIVES OF THE THESIS

The main focus of this thesis was to explore and establish the possible use of a molecular marker for species delimitation in myxomycetes in order to conduct diversity studies of natural communities of myxamoebae. The first part of the thesis therefore provides the basic framework for genetic species delimitation, asking: Question 1: What genetic similarity threshold should be used to identify OTUs (operational taxonomic units) which would best resemble true species of myxomycetes, when using a partial SSU gene marker? To answer this, the first research project included:

 Collection and sequencing of a large number of dark-spored nivicolous specimens from a broad geographical range.  Compiling specimen data into an integrated database including publicly available sequences.  Calculating and characterizing the genetic structure present within the database and in turn determining inter- and intraspecific sequence similarities of the identified taxa in order to identify a similarity threshold for the optimal OTU-picking threshold.  Application of the similarity threshold to a pilot NGS soil dataset to demonstrate its applicability.

The results are reported in chapter 3.1 and 3.2. In addition to Q1, micro-scale morphological characters of spore ornamentation between distinct genetic clades within two morphospecies: Lamproderma ovoideum (45 specimens) and Physarum albecens (55 specimens) were investigated, by producing and processing a total of 1 280 SEM (Scanning Electron Microscopy) images (the results are not included in this dissertation, but will form part of a larger analysis of the two taxa conducted by an associate PhD student, Oleg Shchepin). Question 2: With the modern molecular techniques at hand we are able to investigate the trophic life stage of the myxomycetes and we ask if myxamoebae 1) occupy different niches along an altitudinal gradient, 2) whether their distribution is correlated to the presence of putative food resources, i.e. bacteria and/or fungi and 3) whether their distribution correlates with the distribution of recorded fruit bodies. To answer this, the second research project included:

 Repeating surveys of nivicolous myxomycetes in spring 2015-2017 along an elevational gradient in the German Alps.  Registering environmental parameters and monitoring soil temperature via dataloggers.  Collecting soil and subsequently preparing, sequencing and processing Illumina libraries targeting myxamoebae, fungi and bacteria (3x 48 samples).  Performing complex multivariate analysis to determine the relative importance of environmental parameters for the microbial distribution as well as identifying potential interactions among the microbes. The results are reported in chapter 3.3 and 3.4.

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2.5 LITERATURE 1. Stephenson SL, Schnittler M, Novozhilov YK. (2018) Myxomycete diversity and distribution from the fossil record to the present. Biodivers Conserv 17(2):285-301. 2. Schnittler M, Novozhilov YK, Romeralo M, Brown M, Spiegel FW. (2012) Myxomycetes and Myxomycete-like Organisms. In W. Frey (Ed.), Englers Syllabus of Plant Families. Vol 4. Schweizerbart, pp. 40–88. 3. Feng Y, Klahr A, Janik P, et al. (2016) What an intron may tell: Several sexual biospecies coexist in Meriderma spp. (Myxomycetes). Protist 167(3):234-253. 4. Fiore-Donno AM, Berney C, Pawlowski J, Baldauf SL. (2005) Higher-order phylogeny of plasmodial slime molds (Myxogastria) based on elongation factor 1A and small subunit rRNA gene sequences. J Eukaryot Microbiol 52(3):201-210. 5. Fiore-Donno AM, Kamono A, Meyer M, Schnittler M, Fukui M, Cavalier-Smith T. (2012) 18S rDNA phylogeny of Lamproderma and allied genera (Stemonitales, Myxomycetes, Amoebozoa). PLoS One 7(4):e35359. 6. Fiore-Donno AM, Clissmann F, Meyer M, Schnittler M, Cavalier-Smith T. (2013) Two-gene phylogeny of bright-spored myxomycetes (Slime Moulds, superorder Lucisporidia). PLoS One 8(5):e62586. 7. Stephenson SL. (2011) From morphological to molecular: Studies of myxomycetes since the publication of the Martin and Alexopoulos (1969) monograph. Fungal Divers 50:21-34. 8. Schnittler M, Shchepin ON, Dagamac NHA, Dahl MB, Novozhilov YK. (2017) Barcoding myxomycetes with molecular markers: challenges and opportunities. Nova Hedwigia 104:323–341. 9. Fiore-Donno AM, Meyer M, Baldauf SL, Pawlowski J. (2008) Evolution of dark-spored Myxomycetes (slime-molds): Molecules versus morphology. Mol Phylogenet Evol 46(3):878-889. 10. Feng Y, Schnittler M. (2015) Sex or no sex? Group I introns and independent marker genes reveal the existence of three sexual but reproductively isolated biospecies in Trichia varia (Myxomycetes). Org Divers Evol 15(4):631-650. 11. Lado C. (2005–2018). An on line nomenclatural information system of Eumycetozoa. Retrieved from http://www.eumycetozoa.com 12. Rollins AW, Stephenson SL. (2011) Global distribution and ecology of myxomycetes. Curr Top Plan Biol 12. 13. Collins OR. (1979) Myxomycete biosystematics: some recent developments and future research opportunities. Bot Rev 45:145–201. 14. Clark J, Haskins EF. (2010) Reproductive systems in the myxomycetes : a review. Mycosphere 1(4):337-353. 15. Clark J, Haskins E. (2013) The nuclear reproductive cycle in the myxomycetes: a review. Mycosphere 4(2):233-28. 16. Walker LM, Stephenson SL. (2016) The species problem in myxomycetes revisited. Protist 167(4):319-338. 17. Fiore-Donno AM, Novozhilov YK, Meyer M, Schnittler M. (2011) Genetic structure of two protist species (Myxogastria, Amoebozoa) suggests asexual reproduction in sexual amoebae. PLoS One 6(8):e22872.

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18. Speijer D, Lukeš J, Eliáš M. (2015) Sex is a ubiquitous, ancient, and inherent attribute of eukaryotic life. Proc Natl Acad Sci USA 112(29):8827-8834. 19. Meyer CP, Paulay G. (2005) DNA barcoding: Error rates based on comprehensive sampling. PLoS Biol 3(12):e422. 20. Pawlowski J, Audic S, Adl S, et al. (2012) CBOL Protist Working Group: Barcoding eukaryotic richness beyond the animal, plant, and fungal kingdoms. PLoS Biol 10(11):e1001419. 21. Hadziavdic K, Lekang K, Lanzen A, Jonassen I, Thompson EM, Troedsson C. (2014) Characterization of the 18s rRNA gene for designing universal eukaryote specific primers. PLoS One 9(2):e87624. 22. Torres-Machorro AL, Hernández R, Cevallos AM, López-Villaseñor I. (2010) Ribosomal RNA genes in eukaryotic microorganisms: Witnesses of phylogeny? FEMS Microbiol Rev 34(1):59-86. 23. Ferris PJ, Vogt VM, Truitt CL. (1983) Inheritance of extrachromosomal rDNA in Physarum polycephalum. Mol Cell Biol 3(4):635-642. 24. Bachy C, Dolan JR, López-García P, Deschamps P, Moreira D. (2013) Accuracy of protist diversity assessments: morphology compared with cloning and direct pyrosequencing of 18S rRNA genes and ITS regions using the conspicuous tintinnid ciliates as a case study. ISME J 7:244-255. 25. Medinger R, Nolte V, Pandey RV, et al. (2010) Diversity in a hidden world: potential and limitation of next-generation sequencing for surveys of molecular diversity of eukaryotic microorganisms. Mol Ecol 19:32-40. 26. Chantangsi C, Leander BS. (2010) An SSU rDNA barcoding approach to the diversity of marine interstitial cercozoans, including descriptions of four novel genera and nine novel species. Int J Syst Evol Microbiol 60(8):1962-1977. 27. Heger TJ, Mitchell EAD, Todorov M, et al. (2010) Molecular phylogeny of euglyphid testate amoebae (Cercozoa: Euglyphida) suggests transitions between marine supralittoral and freshwater/terrestrial environments are infrequent. Mol Phylogenet Evol 55(1):113-122. 28. Jargeat P, Martos F, Carriconde F, Gryta H, Moreau PA, Gardes M. (2010) Phylogenetic species delimitation in ectomycorrhizal fungi and implications for barcoding: The case of the Tricholoma scalpturatum complex (Basidiomycota). Mol Ecol. 19(23):5216-5230. 29. Schoch CL, Seifert KA, Huhndorf S, et al. (2012) Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi. Proc Natl Acad Sci USA 109(16):6241-6246. 30. Leliaert F, Verbruggen H, Vanormelingen P, et al. (2014) DNA-based species delimitation in algae. Eur J Phycol 49(2):179-196. 31. Puillandre N, Lambert A, Brouillet S, Achaz G. (2012) ABGD, Automatic Barcode Gap Discovery for primary species delimitation. Mol Ecol 21(8):1864-1877. 32. Boenigk J, Ereshefsky M, Hoef-Emden K, Mallet J, Bass D. (2012) Concepts in protistology: Species definitions and boundaries. Eur J Protistol 48(2):96-102. 33. Dagamac NHA, Rojas C, Novozhilov YK, Moreno H, Schlueter R, Schnittler M. (2017) Speciation in progress ? A phylogeographic study among populations of Hemitrichia serpula (Myxomycetes). PLoS One 12(4):1-22.

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34. Shchepin ON, Novozhilov YK, Schnittler M. Disentangling the taxonomic structure of the Lepidoderma chailletii-carestianum species complex (Myxogastria, Amoebozoa): Genetic and Morphological Aspects. Protistology 10(4):120-129. 35. Novozhilov YK, Schnittler M, Erastova DA, Okun MV, Schepin ON, Heinrich E. (2013) Diversity of nivicolous myxomycetes of the Teberda State Biosphere Reserve (Northwestern Caucasus, Russia). Fungal Divers 59(1):109-130. 36. Ronikier A, Ronikier M, Drozdowicz A. (2008) Diversity of nivicolous myxomycetes in the Gorce mountains a low-elevation massif of the Western Carpathians. Mycotaxon 103:337-352. 37. Feng Y, Schnittler M. (2017) Molecular or morphological species? Myxomycete diversity in a deciduous forest in northeastern Germany. Nova Hedwigia 104:359–380. 38. Rojas C, Stephenson SL. (2017) Myxomycetes : Biology, Systematics, Biogeography and Ecology. Elsevier Science Publishing Co Inc. Imprint: Academic Press; 2017. 39. Liu QS, Yan SZ, Chen SL. (2015) Species diversity of myxomycetes associated with different terrestrial ecosystems, substrata (microhabitats) and environmental factors. Mycol Prog 14:27. 40. Ing B. (1994) Tansley Review No. 62. The Phytosociology of Myxomycetes. New Phytol 126(2):175-201. 41. Rønn R, Mccaig AE, Griffiths BS, Prosser JI. (2002) Impact of Protozoan Grazing on Bacterial Community Structure in Soil Microcosms. Appl Environ Microbiol 68(12):6094-6105. 42. Bonkowski M. (2004) Protozoa and plant growth: The microbial loop in soil revisited. New Phytol 162(3):617-631. 43. Tiunov AV, Semenina EE, Aleksandrova AV, Tsurikov SM, Anichkin AE, Novozhilov YK. (2015) Stable isotope composition (δ 13 C and δ 15 N values) of slime molds: placing bacterivorous soil protozoans in the food web context. Rapid Commun Mass Spectrom 29(16):1465-1472. 44. Geisen S, Koller R, Hünninghaus M, Dumack K, Urich T, Bonkowski M. (2016) The soil food web revisited: Diverse and widespread mycophagous soil protists. Soil Biol Biochem 94:10-18. 45. Bonkowski M. (2002) Protozoa and plant growth: trophic links and mutualism. Eur J Protistol 37:363-365. 46. Briones MJI. (2014) Soil fauna and soil functions: a jigsaw puzzle. Front Environ Sci 2:1-22. 47. Hünninghaus M, Koller R, Kramer S, Marhan S, Kandeler E, Bonkowski M. (2017) Changes in bacterial community composition and soil respiration indicate rapid successions of protist grazers during mineralization of maize crop residues. Pedobiologia 62:1-8. 48. Gessner MO, Swan CM, Dang CK, et al. (2010) Diversity meets decomposition. Trends Ecol Evol 25(6):372-380. 49. Fiore-Donno AM, Weinert J, Wubet T, Bonkowski M. (2016) Metacommunity analysis of amoeboid protists in grassland soils. Sci Rep 6:19068. 50. Clissmann F, Fiore-Donno AM, Hoppe B, et al. (2015) First insight into dead wood protistan diversity: a molecular sampling of bright-spored Myxomycetes (Amoebozoa, slime-moulds) in decaying beech logs. FEMS Microbiol Ecol 91(6): fiv050.

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51. Kamono A, Meyer M, Cavalier-Smith T, Fukui M, Fiore-Donno AM. (2012) Exploring slime mould diversity in high-altitude forests and grasslands by environmental RNA analysis. FEMS Microbiol Ecol 84(1):98-109. 52. Urich T, Lanzén A, Qi J, Huson DH, Schleper C, Schuster SC. (2008) Simultaneous assessment of soil microbial community structure and function through analysis of the meta- transcriptome. PLoS One 3(6):e2527. 53. Tedersoo L, Bahram M, Polme S, et al. (2014) Global diversity and geography of soil fungi. Science 346(6213):1256688-1256689. 54. Valentini A, Pompanon F, Taberlet P. (2009) DNA barcoding for ecologists. Trends Ecol Evol 24(2):110-117. 55. Adl SM, Simpson AGB, Farmer MA, et al. (2005) The New Higher Level Classification of Eukaryotes with Emphasis on the Taxonomy of Protists. J Eukaryot Microbiol 52(5):399-451. 56. Pawlowski J. (2013) The new micro-kingdoms of eukaryotes. BMC Biol. 11:40-41. 57. Baldauf SL, Roger AJ, Wenk-Siefert I, Doolittle WF. (2000) A Kingdom-level phylogeny of eukaryotes based on combined protein data. Science 290(972):972-977 58. Adl SM, Habura A, Eglit Y. (2014) Amplification primers of SSU rDNA for soil protists. Soil Biol Biochem 69:328-342. 59. Geisen S, Laros I, Vizcaíno A, Bonkowski M, de Groot GA. (2015) Not all are free-living: high-throughput DNA metabarcoding reveals a diverse community of protists parasitizing soil metazoa. Mol Ecol 24(17):4556-4569. 60. Floyd RM, Rogers AD, Lambshead PJD, Smith CR. (2005) Nematode-specific PCR primers for the 18S small subunit rRNA gene. Mol Ecol Notes 5(3):611-612. 61. Baldwin DS, Colloff MJ, Rees GN, et al. (2013) Impacts of inundation and drought on eukaryote biodiversity in semi-arid floodplain soils. Mol Ecol 22:1746-1758. 62. Lentendu G, Wubet T, Chatzinotas A, Wilhelm C, Buscot F, Schlegel M. (2014) Effects of long-term differential fertilization on eukaryotic microbial communities in an arable soil: A multiple barcoding approach. Mol Ecol 23:3341-3355. 63. Bates ST, Clemente JC, Flores GE, et al. (2013) Global biogeography of highly diverse protistan communities in soil. ISME J 7(3):652-659. 64. Geisen S, Tveit AT, Clark IM, et al. (2015) Metatranscriptomic census of active protists in soils. ISME J 9(10):2178-2190. 65. Jacquiod S, Stenbæk J, Santos SS, Winding A, Sørensen SJ, Priemé A. (2016) Metagenomes provide valuable comparative information on soil microeukaryotes. Res Microbiol 167:436-450. 66. Kowalski D. (1975) The myxomycete taxa described by Charles Meylan. Mycologia. 67:448– 494. 67. Ronikier A, Ronikier M. (2009) How “alpine” are nivicolous myxomycetes? A worldwide assessment of altitudinal distribution. Mycologia 101:1-16. 68. Lado C. (2004) Nivicolous Myxomycetes of the Iberian Peninsula: Considerations on Species Richness and Ecological Requirements. Syst Geogr Plants 74(1):143-157.

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69. Schnittler M, Erastova DA, Shchepin ON, Heinrich E, Novozhilov YK. (2015) Four years in the Caucasus – observations on the ecology of nivicolous myxomycetes. Fungal Ecol 14:105-115.

70. Schmidt SK, Lipson DA. (2004) Microbial growth under the snow: Implications for nutrient and allelochemical availability in temperate soils. Plant Soil 259:1-7. 71. Schadt CW, Martin AP, Lipson DA, Schmidt SK. (2003) Seasonal dynamics of previously unknown fungal lineages in tundra soils. Science 301:1359-1361. 72. Shchepin O, Novozhilov Y, Schnittler M. (2014) Nivicolous myxomycetes in agar culture : some results and open problems. Protistology 8(2):53-61.

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3 PUBLICATIONS

CHAPTERS PAGES 3.1 Genetic barcoding of dark-spored myxomycetes (Amoebozoa) – identification, 20-42 evaluation and application of an identification threshold for species differentiation in NGS studies.

3.2 Barcoding myxomycetes with molecular markers: challenges and opportunities. 43-66

67-90 3.3 Fine scale niche differentiation among amoebal communities of dark-spored myxomycetes determined by landscape structures as well as biotic factors.

91-107 3.4 Distribution patterns between fruit bodies and soil amoebae of nivicolous myxomycetes.

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3.1 GENETIC BARCODING OF DARK-SPORED MYXOMYCETES (AMOEBOZOA) – IDENTIFICATION, EVALUATION AND APPLICATION OF AN IDENTIFICATION THRESHOLD FOR SPECIES DIFFERENTIATION IN NGS STUDIES.

Mathilde Borg Dahl*1, Asker Daniel Brejnrod2, Martin Unterseher3, Thomas Hoppe1, Yun Feng1, Yuri Novozhilov4, Søren Johannes Sørensen2 & Martin Schnittler 1

1. Institute of Botany and Landscape Ecology, Ernst Moritz Arndt University of Greifswald, Greifswald, Germany

2. Section of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark

3. Evangelisches Schulzentrum Martinschule Greifswald, Germany.

4. V.L. Komarov Botanical Institute of the Russian Academy of Sciences, St. Petersburg, Russia

*Corresponding author: [email protected], +49 3834 86 4123, Ernst Moritz Arndt University Greifswald, Institute of Botany and Landscape Ecology, Soldmannstrasse 15, 17487 Greifswald, Mecklenburg-Vorpommern, Germany.

Manuscript published 1. October 2017 in Molecular Ecology Resources.

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Genetic barcoding of dark-spored myxomycetes (Amoebozoa) – identification, evaluation and application of a sequence similarity threshold for species differentiation in NGS studies.

MSc Mathilde Borg Dahl (MD)*1, Dr. Asker Daniel Brejnrod (AB)2, Dr. Martin Unterseher (MU)3, Dr. Thomas Hoppe (TH)1, Dr. Yun Feng (YF)1, Prof. Yuri Novozhilov (YN)4, Prof. Søren Johannes Sørensen (SJS)2 & Prof. Martin Schnittler (MS)1

1. Institute of Botany and Landscape Ecology, Ernst Moritz Arndt University of Greifswald, Greifswald, Germany

2. Section of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark

3. Evangelisches Schulzentrum Martinschule Greifswald, Germany.

4. V.L. Komarov Botanical Institute of the Russian Academy of Sciences, St. Petersburg, Russia

*Corresponding author: [email protected], +49 3834 86 4123, Ernst Moritz Arndt University Greifswald, Institute of Botany and Landscape Ecology, Soldmannstrasse 15, 17487 Greifswald, Mecklenburg-Vorpommern, Germany.

Acknowledgement

Daria Erastova, Anna Maria Fiore-Donno, Anja Klahr, Marianne Meyer, Mikhail Okun and Bernard Woerly contributed specimens for sequencing. The study was funded by a PhD position for the first author in the framework of the Research Training Programme RESPONSE (GRK 2010, German Science Foundation DFG). YN acknowledges support from the Russian Founds for Basic Research (RFBR 15-29-02622) for funding. MU wishes to thank the DFG for financial support (UN262/9-1) and Prof. Andreas Brachmann for use of facilities and supervision at LMU (Munich).

Conflict of interest

The authors declare no conflict of interests.

Subject Categories: ”Permanent Genetic Resources“

Keywords:

Barcoding gap, dark-spored myxomycetes, DNA barcoding, hidden diversity, Myxogastria, OTU threshold, 18S SSU rRNA gene, species diversity, species concept.

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Abstract

Unicellular, eukaryotic organisms (protists) play a key role in soil food webs as major predators of microorganisms. However, due to the polyphyletic nature of protists no single universal barcode can be established for this group, and the structure of many protistean communities remains unresolved. Plasmodial slime molds (Myxogastria or Myxomycetes) stand out among protists by their formation of fruit bodies, which allow for a morphological species concept. By Sanger sequencing of a large collection of morphospecies, this study presents the largest database to date of dark-spored myxomycetes and evaluate a partial 18S SSU gene marker for species annotation. We identify and discuss the use of an intraspecific sequence similarity threshold of 99.1% for species differentiation (OTU picking) in environmental PCR studies (ePCR) and estimate a hidden diversity of putative species, exceeding those of described morphospecies by 99%. When applying the identified threshold to an ePCR dataset (including sequences from both NGS and cloning) we find 64 OTUs of which 21.9% had a direct match (> 99.1% similarity) to the database and the remaining had on average 90.2 ± 0.8% similarity to their best match, thus thought to represent undiscovered diversity of dark-spored myxomycetes.

Introduction

Together with fungi, unicellular protists constitute the most abundant soil eukaryotes (Ekelund & Rønn 1994; Geisen et al. 2015b). They play a key role in soil food webs as major predators of bacteria (Rønn et al. 2002; Bonkowski, 2004) and fungi (Geisen et al. 2016); influencing main ecosystem processes such as nutrient turn-over and energy flow (Bonkowski 2004; Briones 2014; Tiunov et al. 2015). The advances in high-throughput sequencing of marker genes (e.g. reviewed in Bálint et al. 2016) and the improvement of sequence data bases for accurate taxon annotation (Nilsson et al. 2014) have enabled the exploration of the hidden world of microscopic organisms to an unprecedented level (Urich et al. 2008; Valentini, Pompanon & Taberlet 2009; Tedersoo et al. 2014). However, due to the polyophyletic nature of protists (Baldauf et al. 2000; Adl et al. 2005; Pawlowski et al. 2012; Pawlowski 2013), no universal primers can be developed for the group as a whole (Floyd et al. 2005; Adl, Habura & Eglit 2014; Geisen et al. 2015a). The usability of a DNA marker gene depends on its ability to separate species by a distinction between intra- and interspecific divergence between sequences of the same and related species, the so-called ‘barcoding gap’ (Meyer & Paulay 2005). Partial sequences of the 18S rRNA gene (SSU) have been suggested as universal eukaryotic DNA marker due to its multi-copy and homologous nature (Pawlowski et al. 2012; Hadziavdic et al. 2014), which is also the case in myxomycetes (Ferris, Vogt & Truitt, 1983; Torres-Machorro et al. 2010). In accordance, SSU markers have been successfully used to assign sequences to known species of protists as recently demonstrated for ciliates (Bachy et al. 2013), alveolates (Medinger et al. 2010), marine cercozoans (Chantangsi & Leander 2010) and euglyphid testate amoebae (Heger et al. 2010). However, in a recent study of soil cercozoans the authors found no gap between intra- and interspecific sequence variation when using the V4 region of the SSU marker for 193 morphospecies

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(Harder et al. 2016). Likewise, high similarity of SSU sequences between morphologically distinct species of Cochliopodium (Discosea) were reported by Geisen et al. (2014). Thus, in organisms with little knowledge of correct species definition, the annotation of high-throughput sequencing data may fall short and species delimitation becomes somewhat arbitrary (DeSalle, Egan & Siddall 2005; Carstens et al. 2013; Ryberg 2015). Efforts have been made to identify a region suitable for barcoding in the SSU gene for myxomycetes (reviewed in: Stephenson 2011; Schnittler et al. 2017). However, due to the high variation in some sections and the frequent occurrence of group I introns this has proven to be difficult (Lundblad et al. 2004; Fiore-Donno et al. 2013; Feng & Schnittler, 2015). As a consequence of these genetic structures myxomycetes have been largely overlooked in ePCR amplicon studies, as the so-called ‘general eukaryotic’ primers, such as All18SF/All18SR, Euk20f/516r and F515/R1119 (Baldwin et al. 2013; Bates et al. 2013; Lentendu et al. 2014) do not amplify myxomycetes (Adl, Habura, & Eglit, 2014; Fiore-Donno et al. 2016). However, in recent metatranscriptomic studies (which avoid primer-based amplification) myxomycetes were estimated to account for between 5 to almost 50% of all soil amoebae, and shown to be present in a wide variety of soils (Urich et al. 2008; Geisen et al. 2015b).

The macroscopically visible fructifications of myxomycetes (Stephenson et al. 2008; Schnittler et al. 2012) provide enough morphological traits to support a morphological species concept with currently ca. 1000 species described (Lado 2005-2016). Based on this concept the ecology, distribution and diversity of myxomycetes have been studied for over 200 years (Stephenson, Schnittler & Novozhilov 2008). Only a minority of myxomycetes can be induced to fruit in culture. However, experiments with cultivable species, mostly Physarales, revealed groups of compatible strains (Collins 1979) or so- called biospecies. Empirical evidence of whether all morphospecies reflect true biospecies is lacking (reviewed in Clark & Haskins 2010). Apart from division of amoebae, which should allow for clonal amoebal populations, asexual reproduction modes have been suggested (Fiore-Donno et al. 2011; Clark & Haskins 2013; Walker and Stephenson 2016). However, recent studies (Feng & Schnittler 2015; Feng et al. 2016) concluded that sexual reproduction seems to dominate in natural populations. This is in line with studies showing sexual reproduction as a hallmark of Amoebozoa (Lahr et al. 2011, Spiegel 2011) and of eukaryotic life in general (Speijer, Lukeš & Eliáš 2015). In case of sexual reproduction a combination of independent genetic markers can be used to characterize sexually isolated lineages which represent putative biospecies. Therefore, sequences of the protein elongation factor 1 alpha (EF1A, chromosomal) and the COI gene have been used as markers complementary to SSU. In the few available studies, the patterns obtained were largely congruent with those obtained for the SSU marker (Fiore-Donno et al. 2013; Feng & Schnittler 2015; Feng et al. 2016; Dagamac et al. 2017), and so it seems reasonable to establish the SSU sequence as a DNA marker for ePCR studies. Attempts to develop a marker universal for myxomycetes have failed due to the large divergence between two basal subgroups, called the dark- and the bright-spored myxomycetes (Fiore-Donno et al. 2012; Fiore-Donno et al. 2013). Consequently, this study focuses on only the dark-spored

23 myxomycetes, which encompasses two thirds of the morphologically described species (Lado 2005- 2016).

In this study we take advantage of a large collection of specimens, combining expert knowledge on morphological characteristics with partial SSU sequences, to establish a sequence similarity threshold for species delimitation of myxomycetes from environmental samples, the so-called OTU picking. We demonstrate the existence of a barcode gap between most morphospecies of myxomycetes, identify and discuss the use of a common threshold for OTU picking and apply this to an analysis of myxomycete communities in soil from the Northern Caucasus region.

Materials and methods

To establish a reference database of SSU sequences from dark-spored myxomycetes, we sequenced 634 specimens from 43 morphospecies and included 611 of the ca. 800 publicly available sequences in the NCBI database were included (see suppl. S1 for contributors of sequences).

DNA extraction, amplification and sequencing Fruit bodies From all specimens 3-6 fully mature sporocarps were transferred into 2 ml tubes, containing sterilized sea sand and glass beats, and homogenized with a MP Biomedical Fastprep 24TM (Santa Ana, California, USA) in 2x 45 sec at 5 m/s speed. To minimize cross-contamination, the precautions described in Novozhilov et al. (2013) were applied during sampling and isolation of the sporocarps. DNA was extracted according to manufacturer’s protocol by either the Stratec Invisorb Spin Plant Mini Kit, (Berlin, Germany), the Qiagen Plant kit (Hilden, Germany) or OMEGA Plant Kit (Norcross, Georgia, USA). The DNA was kept at -18°C. A partial SSU sequence (~350bp) was amplified using the dark-spored specific myxomycetes primers S31R (ATCTCTCAGGCCCACTCTCCAGG; Schnittler et al. 2017) and S3b (TCTCTCTGAATCTGCGWAC; Hoppe & Schnittler 2015) targeting the V2 region of the SSU. PCR conditions for 25 µL reaction mixture were 95°C for 5 min; 35 cycles of 94°C for 45 s, 57°C for 50 s, 72°C for 50 s, followed by 72°C for 6 min. Amplicons were Sanger sequenced on an ABI 3010 platform. Sequences are available from the European Nucleotide Archive (ENA), accessions: LT669954-LT670581.

Soil samples During four field surveys for fruit bodies of nivicolous myxomycete (an ecological group of species, which emerges from the soil and form fruit bodies along the edge of melting snowbanks in spring primarily in mountain regions, hence the name ‘nivicolous’) conducted in spring seasons 2010–2013, an elevational transect was studied between 1 700 and 3 000 m a.s.l. in the Teberda State Biosphere Reserve, northern Caucasus (Novozhilov et al. 2013, Schnittler et al. 2015). Seven soil samples were collected in 2011 and 2012, by pooling ca. 10 g of soil from of the uppermost soil horizon (A0) gathered over an area of ca. 2 x 2 m (for location see corresponding sites for data loggers listed in

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Schnittler et al. 2015 and suppl. S5). Samples were air-dried for transportation, and soil was filled into 2 ml tubes and homogenized as described above. DNA was extracted with the FastDNATM Spin Kit for Soil, according to manufacturer’s protocol and kept at -18°C. The preparation of the ePCR amplicon libraries are described in detail in Siddique and Unterseher (2016). In brief, two PCR steps were used to add two forward and two reverse sample identifier tags to the target DNA marker, using the primer pair S31R/S3b. Paired-end sequencing of the equimolarily pooled samples at 2 x 300 nt with two additional 8 nt index reads and 3µl of the library was performed on an Illumina MiSeqTM platform (Illumina Inc.) at the Genetics facility of the LMU (Munich). The NGS sequences were pre- processed with biopieces (www.biopieces.org) to remove technical artefacts and tags and primers were trimmed off. This script demultiplexes the sequences with 0 mismatches allowed in the barcodes. Processed sequences were run through a pipeline using UPARSE 8.1.1861 (Edgar 2010). Paired ends were merged and full length amplicons filtered with 0.5 max expected errors and otherwise default options. Sequences were pooled, dereplicated and singletons discarded as recommended, resulting in a total of 24 470 sequences. Illumina raw-files are available from NCBI (BioProject ID: PRJNA407272), scripts of processing pipelines and a database file are available from Dryad (doi:10.5061/dryad.jv77v).

Cloning In addition, PCR products from three soil samples were cloned with the NEB PCR Cloning Kit (New England Biolab). Best results in terms of an even distribution and a sufficient number of colonies were obtained by plating 100 µl transformed E. coli strain DH5α outgrowth on one LB-agar plate. A colony PCR was carried out with the vector-specific primers provided by the supplier. Amplicons were purified by SureClean Plus (BioLine, London, UK) and used for cycle sequencing (BigDye Terminator v3.1 Cycle Sequencing Kit, Applied Biosystems, Thermo Fisher Scientific, Massachusetts, USA). This resulted in 150 sequences, of which 108 were unique. Sequences are available from the European Nucleotide Archive (ENA), accessions: LT670667-LT670816.

Statistical analysis The barcoding gap The compiled sequences resulted in a reference database of 1 245 sequences representing 139 morphospecies. All sequences were aligned by MAFFT with the option FFT-NS-2 (Katoh & Standley, 2013). Sequences were trimmed to the fragment length of the marker amplicon (~350 bp); 19 sequences were removed as too short. In 111 cases, sequences were removed as they were identical or near identical (≥ 97%) to the sequences of a closely related and highly morphologically similar morphospecies, in these cases we assumed a misidentification of the morphospecies have occurred (Suppl. S2). Additionally in 13 cases the genetic dissimilarity to sequences of own morphospecies as well as any other sequence in the database were very high (>5% dissimilarity). Several of these had been given an uncertain classification in the original morphological determination (indicated by the suffix “cf”), why we considered it reasonable to doubt the determination and these sequences were

25 omitted from the database (phylogenetic trees are provided to support our classification of the specimen, see suppl. S7). Four morphospecies (Meriderma verrucosporum / M. cribrarioides and Lamproderma cribrarioides / L. spinulisporum) with a combined total of 42 sequences were removed as they formed mixed clusters of two morphospecies (Suppl. S7). These morphospecies differ mainly by spore ornamentation which may not be a reliable trait, the mixed clades are therefore likely to indicate shortcomings of the morphospecies concept. Finally, all morphospecies represented by a single sequence (69) were removed from the alignment when calculating intra- and interspecific variation, but were included for the downstream use of the reference database. After these removals the dataset consisted of 991 sequences from 68 morphospecies (Suppl. S1, database file is available from Dryad: http://dx.doi.org/10.5061/dryad.jv77v).

To determine the barcoding gap, distance scores were calculated based on the MAFFT multiple sequence alignment (MSA) with the morphospecies classification as ID (Robideau et al. 2011; Schoch et al. 2012). Distance scores were calculated with the Kimura 2-parameter model (Kimura 1980) implemented as default in the ‘Spider’ R package (Brown et al. 2012; model evaluated by R. Collins et al. 2012). From maximum likelihood phylogenetic trees (500 permutations), it was seen that 16 of the 68 morphospecies showed two or more distinct sub-clades and in comparison a significantly higher intraspecific sequence variation (p < 0.001, one-way ANOVA incl. Welch correction for non- homogenous variation). Corresponding calculations were made treating these clades as hidden diversity and thus putative species (Suppl. S3). Clades were counted as individual taxa (putative species) when they comprised of at least two sequences, displayed bootstrap values above 70 within 500 permutations and when their inter- and intraspecific variation was in the same order as among other closely related morphospecies (see Results and discussion).

OTU threshold To identify the optimum sequence similarity threshold for species differentiation, the number of sequences that were either split into two or more clades belonging to the same taxon or merged into one clade including different taxa at a given threshold was recorded for a range of threshold values (0.0% to 5.0% by 0.1% increments). The point where the cumulative error rate of these false classifications reached a minimum was defined as the threshold optimum. The calculations were carried out with the statistical software ‘R’ (R Core Team, 2016) using mainly the package ‘Spider’ (Brown et al. 2012). Due to the uneven representation of taxa the threshold calculation was bootstrapped, i.e. sampled with replacement for 2000 permutations with respect to taxon classification. The effect of the geographical distance between origin of sequences within taxa and/or the number of representative sequences were tested by Pearson’s correlation analysis.

Application for soil community analysis After establishment of the reference database and the OTU picking threshold, both were applied in the analysis of the soil samples from Caucasus (ePCR and subsequent Illumina NGS sequencing or cloning). The results were compared to the morphospecies inventory from the surveys of the same site

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(1 177 specimens belonging to 46 morphospecies, see suppl. S5 and Novozhilov et al. 2013; Schnittler et al. 2015). The OTUs were BLASTed against the newly created reference database and the top hit selected, with default settings (BLAST Command Line Applications User Manual 2016), when these were not met the OTU was assigned ‘no match’. Some sequences in the ePCR dataset were found to be of fungal origin (see Results and discussion), therefore we calculated the binding specificity of the primer pair S3b/S31R to these sequences following default settings in the PrimerProspector pipeline (Walters et al. 2011). Scores for mismatches in the alignments were calculated as following: weighted score = non-3' mismatches * 0.4 + 3' mismatches * 1.0 + non 3' gaps * 1.0 + 3' gaps * 3.0. An additional 3.0 penalty was added if the final 3' base mismatches. The 3'-end length was defined as 5 nucleotides (as default).

Results and discussion

Identifying the barcoding gap Based on the morphospecies classification 60.1% of the total number of sequences (991) show a lower genetic distance to their kin than to the nearest neighbour species, and thus the presence of a barcoding gap (Figure 1a). The maximum distance between kin sequences (intraspecific variation) varies from 0 to 0.5 with a mean of 0.09 ± 0.003 and a median of 0.04, when calculated as average per morphospecies the mean becomes 0.07 ± 0 and the median 0.02. One morphospecies is on average represented by 14 ± 2.3 sequences (median = 4). Sequences which are more similar to their nearest neighbour species than to their kin (395), thus showing no ‘gap’, have a significantly higher (p<0.001) dissimilarity to their kin (ranging from 0.06 to 0.5, median 0.14) than those displaying a ‘gap’ (intraspecific distance ranging from 0.00 to 0.24, median 0.02). Nevertheless the distance to nearest neighbour species remains the same between the two groups (average 0.10 ± 0.002, p = 0.36). These ‘no gap’ sequences belong to 17 morphospecies. Eleven of these morphospecies are comprised of two or more distinct genetic clades, which were classified as sub-clades of the given morphospecies (indicated by a, b, c, etc.). Of the remaining six morphospecies (Fuligo intermedia, Lamproderma pulchellum, L. arcyrioides, Meriderma echinulatum, Mucilago crustacea and Stemonaria irregularis) single outlying sequences, which were not classified as distinct sub-clade, are causing maximum intraspecific similarity to be higher than the distance to their nearest neighbour species (Suppl. S7). In addition, eight morphospecies (Didymium dubium, Didymium iridis, Lamproderma album, Lamproderma ovoideum, Lamproderma scintillans, Lepidoderma chailletii, Meriderma spinulosporum and Physarum albescens), which do show a ‘gap’ in similarity to their nearest neighbour species, also show the pattern of distinct sub-clades causing a high intraspecific distance. These morphospecies are assumed to be species complexes, as shown for L. chailletii (Shchepin et al. 2017) and M. spinulosporum (Feng et al. 2016), therefore the respective sub-clades were categorized as distinct taxa. Finally, a high maximum intraspecific variance is seen in three additional morphospecies (Fuligo leviderma, Lamproderma cacographicum, and Physarum sp.C) which are only represented with two or three sequences and were thus left as a single classification each, though we

27 assume that with an increase in collected specimens, a pattern of genetic sub-clades will emerge for these morphospecies as well. When sub-clades were treated as indicators of hidden diversity (putative species), the total number of taxa increased from 68 to 100 and the average representation (sequences per taxon) decreased to 10 ± 1.3 (median = 4).

When sub-clades were treated as putative species the average intraspecific variation was considerably lower and more uniformly distributed (average 0.03 ± 0.001, median = 0.02). Now 84% of all recognized taxa show the presence of a barcoding gap (Figure 1b and suppl. S3). However, besides the seven morphospecies which were not divided into sub-clades (due to the reasons given above), 11 taxa – Badhamia melanospora (sub-clade a and b), Lamproderma ovoideum (sub-clade b), L. scintillans (sub-clade d), Meriderma aggregatum (sub-clade d), Physarum albescens (sub-clade a), P. pseudonotabile (sub-clade c and g) and P. notabile (sub-clade sstr) – still contain sequences with a higher distance to their kin than to the nearest neighbour taxa. In all but P. albescens and P. pseudonotabile (which show high variation), this is due to a single outlying sequence causing maximum intraspecific distance to be greater than nearest neighbour sequence (Suppl. S7). Thus 157 sequences remain as red ‘gaps’ in Figure 1b.

Figure 1. Visualization of the barcode gap for all sequences from myxomycete fruit bodies (n = 991). Sequences are represented by vertical lines indicating the difference between maximum intraspecific distance and nearest interspecific distance and are sorted according to absolute length. For cases with no barcode gap, this figure is negative and shown as red bars. a Classification according to morphospecies, 68 taxa. b Classification including sub-clades as putative species, 100 taxa. Examples of outliers causing a high intraspecific variance (seen as ‘floating bars’) within a taxon’s clade are indicated (abbreviation for the taxa names see Suppl. S1).

The distance to nearest neighbour, varies considerably from very small between sister-clades of taxa like Lamproderma maculatum and L. pseudomaculatum (0.019 ± 0) or Meriderma echinulatum and M. carestiae (0.032 ± 0.004), to very large like for Echinostelium minutum, which closest neighbour in the database is Stemonitopsis typhina with a 0.55 ± 0 similarity. This is partly explained by the

28 incompleteness of the database and partly by the fact that some genera, like Lamproderma (Fiore- Donno et al. 2012) and Meriderma (Poulain et al. 2011; Janik and Ronikier 2016) are taxonomically better resolved, with numerous new morphospecies described in recent years (hence decreasing the distant to neighbour species). In others, like Physarum and Badhamia, even the generic delimitations are not yet clear (Nandipati et al. 2012). In the current study this is seen in the high level of ‘splitting’ seen in especially species of Physarum, where e.g. P. pseudonotabile is split into eight sub-clades and is still showing high intraspecific variation in some clades. In addition several sequences obtained from specimens with an uncertain (suffix “cf”) determination to P. notabile resemble no other sequences in the database (Suppl. S3 and S7). A larger sampling effort and a targeted study is needed to fully disentangle morphospecies in these genera.

The discovery of a significant proportion of hidden diversity has become the rule rather than the exception in environmental studies targeting protists. Examples are provided by Fiore-Donno et al. (2016) (Myxomycetes), Harder et al. (2016) (Cercozoa), Kosakyan et al. (2012) (Nebelid Testate Amoebae) and Nolte et al. (2010) (Diatoms, Chrysophyta), who all report cryptic speciation within known morphospecies. In the present study we found that 23.5% (16 of 68) morphospecies split into one or more sub-clades, resulting in 33 sub-clades equalling an increase in species diversity by 49% (33 of 68). This result is in line with a number of recent reports about cryptic species in myxomycetes. Poulain et al. (2011) propose several morphospecies within Meriderma spp. which were formerly known as one species, Lamproderma atrosporum. These were confirmed by Feng et al. (2016), who used a combination of SSU and EF1A gene markers to show five sub-clades largely corresponding to these independently described new morphospecies. The same is the case for Comatricha nigricapillitia where the specimens of the two genetic sub-clades have been shown to differ in phenotype, by having different colours (Fiore-Donno et al. 2008). Likewise, Fiore-Donno et al. (2011) found intraspecific differentiation within Lamproderma puncticulatum and L. columbinum using a larger fraction (659 bp) of the SSU gene combined with ITS sequences and EF1A markers. Similarly, intraspecific sub-clades were found for L. ovoideum (Dahl et al. unpubl. results), for the bright-spored species Tubifera ferruginosa (Leontyev et al. 2014) and Hemitrichia serpula (Dagamac et al. 2017). In all these cases, scanning electron microscopy (SEM) images of spores revealed that genetic sub-clades showed consistent differences in spore ornamentation. However, no clearly attributable morphological differences were found in three putative species within Trichia varia defined by three independent genetic markers (SSU, EF1A and COI) and group I intron distribution within the first marker (Feng & Schnittler 2015). Lastly, Aguilar et al. (2014) found a minimum of two highly distinct genetic sub- clades (and suggested up to six clades) in a case study of Badhamia melanospora. In this case, as well as for H. serpula, habitat preferences of different sub-clades were indicated by the implementation of an environmental niche model in the analyses, which also suggested limited dispersal for the respective taxa at a transcontinental scale. The number of sub-clades found within a morphospecies in the present study shows a weak correlation with both the number of sequences representing the

29 morphospecies (R2= 0.28, p<0.01) and the number of geographic origins per morphospecies (R2= 0.27, p<0.01, suppl. S4). However, in both cases the correlations are strongly influenced by the morphospecies P. pseudonotabile which is represented by 84 sequences, split into eight sub-clades and originates from six geographical sites (as mentioned above a targeted study should be conducted to fully describe this species complex). Without this morphospecies, R2 decreases to 0.12 and 0.15, respectively (Suppl. S4). This indicates that sub-clades are not an artefact of unequal sampling effort, and mounts evidence that these sub-clades represent truly distinct taxa. This is in line with the transcontinental study of Didymium difforme by Winsett & Stephenson (2011) who found no relation between genetic sub-clades (mitochondrial SSU sequences) and geographical origin, underlining the potential for long distance dispersal, as also indicated from modelling of propagule size in relation to dispersal capabilities in microbes (Wilkinson et al. 2012).

Evaluation of an OTU threshold against morphological classification Looking at a frequency distribution of the calculated pairwise similarities, the first local minima (dip) in the distribution is found at 0.18 (Figure 3a). When categorised into within and between taxa similarity, we see that this point is largely congruent with the shift between these two (intra- and interspecific) similarities, as illustrated in Figure 3b, where only the within genera similarity is plotted as interspecific similarity (as the distance to closest related species is the most relevant for determination of the threshold). Some overlap between the two (intra- and interspecific variation) exist, and thus no clear cut gap is seen. Consequently, the cumulative error rate at a given threshold value (the number of sequences assigned to multiple clades of the same morphospecies or to one clade of several morphospecies) is not diminished to zero at any point. The error rate reaches a minimum between 0.9% and 1.9% dissimilarity, between which 67 ± 1 sequences of the total 991 sequences will be misclassified (Figure 3c). To avoid a potential effect of the unequal sample size (number of representing sequences) between morphospecies, we bootstrapped the calculation of the threshold, defining the threshold as the value where the cumulative error rate reaches a minimum. Figure 3d shows the distribution of these optimum threshold values, which is seen to be a bimodal distribution with the largest peak (most frequent) at 0.9% and a second peak at 1.7% dissimilarity. A dissimilarity threshold at 0.9% corresponds to the point before the first merging of morphospecies occurs (Figure 3c). Looking at the specific cases, the first at 1.0% dissimilarity, is a single L. arcyrioides sequence merging with the sequences of L. pulveratum, two very similar morphospecies (the particular specimen of L. arcyrioides could not be determined with certainty). The next case, at 1.2% dissimilarity, merges Comatricha filamentosa with Comatricha pseudoalpina, two independently described rare morphospecies which need to be compared in a targeted study. Hereafter follows, at 1.8% dissimilarity, a re-merging of two identified sub-clades for B. melanospora (sub-clade a and b) and at 1.9% dissimilarity, the merging of L. maculatum and L. pseudomaculatum will occur (Figure 3c).

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Figure 2. Relation between sequences representing a morphospecies (left) and their average intraspecific genetic distance (right). Figures at the fare right indicate the number of distinct geographical sites where sequences originated. The average number of sequences per morphospecies is 14 ± 2. The average intraspecific distance is 0.072 ± 0 with the median at 0.019, met by Diderma globosum var. europaeum.

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Conversely, looking at the number morphospecies which will be split between clades of the same morphospecies, the number does not differ a lot across the interval, but even for the revised classification, it is considered rather high, ranging from 46 to 38 taxa within the interval 0.9% to 1.9% dissimilarity. A large part of these are the 19 taxa which holds single outlying sequences (discussed above), which causes their intraspecific variation to vary between 3% and 50%. The remaining 27 to 19 taxa with a higher intraspecific variation than 0.9% and 1.9% respectively, show maximum intraspecific distances ranging from 0.95% to 13.6% (Suppl. S3). For some, like P. notabile (sub-clade b) and C. nigricapillitia (sub-clade b), with a maximum intraspecific distances of 13.6% and 13.2% respectively, only two sequences are available for each taxon, which does not give sufficient resolution. At the opposite end of the spectra, at 0.95% dissimilarity, Lepidoderma alpestroides is found, a morphospecies represented by four sequences. Among the affected taxa are also M. carestiae (at 1.6% dissimilarity), a morphospecies which Feng et al. (2016) recently separated into two presumably sexually isolated taxa using SSU and EF1A markers, but could not be split in a satisfying way based on the specimens in the database. Based on these data (Figure 3a-c) it becomes clear that no absolute optimum can be found for the threshold value. However, to ensure an adequate capture of diversity when carrying out environmental studies by high-throughput community sequencing, we recommend to use the first peak of the bootstrapped threshold value at 0.9% dissimilarity. First, this acknowledges that recent molecular studies, although still limited, repeatedly found evidence that morphospecies are more likely to represent species complexes than single species. Second, to ensure compatibility with classical morphological studies keeping known morphospecies separated by the threshold (preventing ‘merging’), is of high importance. Thus, the case of T. varia with cryptic species (Feng & Schnittler 2015) may denote one extreme, a study of the Amoebozoa genus Cochliopodium (Geisen et al. 2014) showing high genetic similarity in morphologically distinct taxa, the other extreme. Only with a high similarity threshold the majority of the diversity, regardless if morphologically comprehensible or not, can be captured. A low threshold for intraspecific variance, as the 0.9% threshold identified here, makes the sensitivity to sequencing errors high, why stringent quality filtering should be applied when using this marker in NGS study or when Sanger sequencing specimens. In myxomycetes, more studies are needed to establish whether the sub-clades found by us represent indeed sexually isolated and/or ecologically differentiated species. This would shed light on whether a higher threshold (identifying species complexes only), will be more ecological meaningful. A threshold of 0.9% dissimilarity corresponds to an increase in diversity by 99% (68 morphospecies versus 146 putative species; the latter including 100 taxa identified in this study of which 46 will be additionally split by application of a 0.9% threshold). This order of magnitude is in line with a first diversity study of myxomycetes combining a morphological and molecular approach in species differentiation (Feng & Schnittler 2017).

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Figure 3. a Histogram of all pairwise similarities, n = 488 566. The red line indicates a local first minima at 1.8% in the distribution. b The same illustrated for intra- and interspecific similarity, the latter only including within genera similarity, n = 97 830. c Numbers of sequences that are either split into two or more clades of a given taxon (white) or merged into a clade with other taxa (black) at a given threshold for intraspecific sequence dissimilarity, n = 991. Classifications which will be merged within the minimum error rate interval (red line) are given (for abbreviations see Suppl. S1). d Histogram of the 2000 threshold values identified from bootstrap calculations with replacement (class width for similarity = 0.001). All graphs represent the classification accepting sub-clades as distinct taxa.

A case study providing novel insights into the soil myxo-amoebal community structure The reference data base presented above was applied to a data set from seven soil samples from an intensely studied area in the Caucasus mountains, where (1) fructifications were collected over four subsequent years, and amoebal communities from soil samples were investigated by (2) cloning and (3) Illumina metabarcoding (NGS) of ePCR amplicons. Applying the dissimilarity threshold of 0.9% to the Illumina dataset (24 470 sequences) resulted in 63 OTUs, of which 46 could be assigned to 26 taxa from the reference database. Of these, nine (19.6%) had a direct match (≥ 99.1% similarity) and the remaining had on average 90.2 ± 0.8% similarity to their best match (see suppl. S5). The 17 OTUs with no match to the reference database amounted to 17.9% (4 380 reads) of the total reads in the dataset. When blasted against the NCBI public database, these ‘no match’ sequences were found to be mainly of fungal origin, with the two most common sequences, OTU7 (9%) and OTU14 (8%), matching best Legeriosimilis sp. (Zygomycetes) and Sordariomycetidae sp. (Ascomycetes),

33 respectively. Surprisingly, these sequences have a relatively poor match to our primers (penalty scores of 5.8/2.6 and 5.4/5.6 for S3b/S31R primers, respectively, suppl. S5) indicating that some non-specific primer binding occurred during amplification.

The cloning approach provided only 150 sequences that clustered into 18 OTUs, matching 13 taxa in the database. For 5 OTUs a direct match was found (> 99.1% similarity), the remaining 13 OTUs matched with an average of 93.2 ± 09% similarity. All but one of the 13 taxa were also detected by NGS, leaving one species (Meriderma echinulatum) observed from both cloning and the field surveys, but not from NGS (Figure 4).

Figure 4. Relative abundance of morphospecies from the northern Caucasus transect, detected by field surveys, next generation sequencing (NGS) and cloning. For the latter two methods, OTUs were assigned to morphospecies based on ‘best match’ identification (see text). The area of the circles indicates relative abundance, calculated as proportion of the total number of field records (1 177), NGS reads (17 321) and cloned sequences (150). Blue circles are nivicolous species, red circles are non-nivicolous species (not surveyed in the field). Species potentially detectable by all tree methods are marked by dotted horizontal lines. Three bright-spored species observed from field surveys (written in grey) cannot be detected by the primers used for ePCR. Square brackets indicate species complex which are morphologically difficult to tell apart.

From 1 177 fructifications observed within the transect 44 morphospecies were determined (Suppl. S5 and Schnittler et al. 2015). Three of these were bright-spored myxomycetes and therefore not detectable with the primers used in this study. Of the 27 OTUs detected from the soil samples (26 with

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NGS, 13 with cloning), only 13 represent nivicolous myxomycetes (the targeted group of the field surveys). Figure 4 presents the comparison of the three species inventories (field surveys, NGS reads, cloning): 46 morphospecies could potentially have been detected with all three methods (being dark- spored and nivicolous). Of these, 43 were found in field surveys; 2 were detected only by the ePCR- based methods. These two species were Lamproderma piriforme (a taxon morphologically very similar to L. ovoideum; a species commonly found in the field) and the rare L. retirugisporum, both had a direct match to a reference sequence. Eleven taxa (23.9% of the 46 morphospecies) were detected as both fructifications and amoebae. Taking into account, that the field surveys covered a transect of ca. 3 700 x 50 m (ca. 185 000 m2), whereas the soil samples only represents 7 plots of ca. 2 x 2 m (ca. 28 m2), this is considered a rather high overlap.

In addition, the reference database is still not complete: sequences of four morphospecies (Meriderma verrucosporum, M. cribrarioides, Lamproderma cribrarioides and L. spinulisporum) formed mixed clusters and were removed (see Methods), three of these are represented in the fruit body collection. In addition, we lack reference sequences for Lepidoderma aggregatum and Didymium dubium var. spiralis. Finally, Meriderma carestiae var. retisporum does not form a discrete taxon in the sequence database, as the 13 sequences originating from this morphologically determined variety are identical to sequences representing M. carestiae, indicating that the description of this morphological variety may not be justified.

That the highest alpha diversity was obtained from the fruit body survey is surprising, but it is likely due to the fact that the survey was conducted at a larger spatial (a transect of 3.7 km length) and temporal (over four years) scale, including more ecological niches, than represented by the seven soil samples. Especially members of the genera Meriderma and Physarum were not detected in the soil samples. A systematic sampling approach should be applied to shed light on the relation between species composition in fruit body-based surveys and assemblages of amoebae in soil. On the other hand, the average match score for 13 OTUs to their reference sequence is far below the identified species delimitation threshold, and thus may represent novel diversity, in line with recent ePCR studies (Bass et al. 2016). The difference in beta diversity between the methods is less surprising, since the field surveys conducted in spring covered only nivicolous (“snow bank“) myxomycetes. At this time non-nivicolous species such as Lamproderma scintillans, Didymium comatum or Stemonitis flavogenita (all abundantly present in both datasets from soil) can only occur as amoebae and hence not be found, but these species are known to fruit in the area in autumn (Novozhilov et al. unpubl. data). In addition, we hypothesize that the soil samples may hold amoebae of lowland taxa which will hardly fruit at higher elevations due to sub-optimal conditions. The results thus demonstrate that the reference database has the potential to be a useful tool in obtaining novel insight into the structures of the myxomycete community in their amoebal form – the stage of their life cycle where they play an active role in microbial food webs.

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Conclusion

Our dataset represents the hitherto largest number of sequenced myxomycetes specimens from a broad geographical range. With the establishment of this reference database we opened the possibility of correct annotation of dark-spored myxomycetes for non-expert scientists performing microbial metacommunity analyses. As such, this quality checked reference database is crucial for any ePCR studies and will open a new window of opportunity for ecological studies, allowing to identify non- fruiting (amoebal) populations of myxomycetes, as demonstrated here.

As no absolute optimum for a genetic similarity threshold was discovered, the threshold remains a pragmatic tool, reflecting an approximate species number, which we believe comes close to the true number of myxomycete species. We urge further taxonomic studies to be directed towards refining the morphospecies concept and reconcile it as much as possible with the biospecies concept (with reproductive isolation proven by culture studies or combinations of molecular markers). Only approaches combining morphological analyses with multiple molecular markers can disentangle genetically diverse morphospecies and identify cases of cryptic speciation, thus contributing to expand and improve this reference database, which hopefully will provide a backbone for further metacommunity studies.

Data Accessibility

A supplementary data file (pdf) containing supplements S1-S7 is available from the Molecular Ecology Resources website: S1 Datasheet of all specimens used in this study (including label ID, specimen accession number, species determination, NCBI reference, geographic origin, sub-clade indications and exclusions). S2 Datasheet containing information on excluded sequences. S3 intra- and interspecific sequence dissimilarity S4 Correlation of sub-clades to number of sequences and geographical origin of specimen S5 Datasheet for the Caucasus survey and soil samples S6 Bioinformatic and statistical documentation S7 Maximum likelihood phylogenetic trees for all suspicious cases of morphological determination and/or sub-clades Illumina fastq-files are available from The National Center for Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov/bioproject/407272). In addition Illumina fastq-files, bioinformatic pipeline and sequence database file are available from Dryad (doi:10.5061/dryad.jv77v) Sanger sequences are available from the European Nucleotide Archive (ENA), accessions: LT669954- LT670816.

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Author Contributions

MD and MS designed the study. MD sequenced 315 additional specimens for the reference data base. MS and YN collected the soil samples, MU and TH did the library preparation (including primer design) and sequencing. YN provided unpublished sequences, YF and MS contributed with a quality- checked sub-set of sequences from the NCBI. YN and MS provided the morphological expertise and determined the specimens for all non-published sequences in this study. AB did the bioinformatic processing of the ePCR dataset; AB and MD performed all subsequent analyses. MS and SJS provided laboratory facilities and scientific supervision. MD wrote the manuscript, aided by all authors.

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3.2 BARCODING MYXOMYCETES WITH MOLECULAR MARKERS: CHALLENGES AND OPPORTUNITIES.

Martin Schnittler*1, Oleg N. Shchepin12, Nikki H. A. Dagamac1, Mathilde B. Dahl1 & Yuri K. Novozhilov2

1. Institute of Botany and Landscape Ecology, Ernst Moritz Arndt University of Greifswald, Greifswald, Germany

2. Komarov Botanical Institute of the Russian Academy of Sciences, Laboratory of Systematics and Geography of Fungi, Prof. Popov Street 2, 197376 St. Petersburg, Russia

*Corresponding author: [email protected], Ernst Moritz Arndt University Greifswald, Institute of Botany and Landscape Ecology, Soldmannstrasse 15, 17487 Greifswald, Mecklenburg-Vorpommern, Germany.

Manuscript published February 2017 in Nova Hedwigia.

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BARCODING MYXOMYCETES WITH MOLECULAR MARKERS: CHALLENGES AND OPPORTUNITIES

MARTIN SCHNITTLER1, OLEG N. SHCHEPIN2, NIKKI HEHERSON A. DAGAMAC1, MATHILDE BORG DAHL1, YURI K. NOVOZHILOV2

1 Institute of Botany and Landscape Ecology, Ernst Moritz Arndt University Greifswald Soldmannstr. 15, D-17487 Greifswald, Germany

2 Komarov Botanical Institute of the Russian Academy of Sciences, Laboratory of Systematics and Geography of Fungi, Prof. Popov Street 2, 197376 St. Petersburg, Russia

*Corresponding author: Martin Schnittler, Institute of Botany and Landscape Ecology, Ernst Moritz Arndt University Greifswald, Soldmannstr. 15, D-17487 Greifswald, Germany. Email: martin.schnittler@uni- greifswald.de

ABSTRACT

Despite the long history of studies based on fruit body occurrence and morphology, the molecular era for myxomycetes started much later than for most other groups of eukaryotes. With the first reliable phylogenies of myxomycetes now available, a barcoding approach is within reach. However, a serious challenge is the high diversity in marker genes known to be more conservative than in animals or plants. As in other groups of protists, this makes it difficult to find truly universal primers. This review reports recent advances in the development of molecular markers and assesses their suitability for barcoding the ca. 1000 described morphospecies of myxomycetes. The most advanced approach is barcoding with partial sequences of the 18S rRNA gene, but the mitochondrial cytochrome c oxidase subunit I gene also seems to represent a promising marker. Based on the limited number of studies that have employed molecular methods to investigate natural populations of myxomycetes, the consequences of such a barcoding approach for species concepts are discussed. Challenges for the analysis of environmental samples, which have a great potential to improve our understanding of the ecology and diversity of the group, are addressed,

Keywords: barcoding, COI, EF1A, ePCR, gene markers, hidden diversity, protists, SSU

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INTRODUCTION

“Barcoding” organisms (i.e., looking for molecular markers which can tell species apart) is a popular direction in contemporary taxonomy, especially in microorganisms where the majority of taxa are uncultivable and thus inaccessible for systematic studies (Epstein 2013). Furthermore, with the advent of high-throughput sequencing methods, a new era of microbial ecology has begun, as it is now possible to test ecological hypotheses which require large sample sizes and/or broad taxon coverage (Bahram et al. 2016, Bálint et al. 2016, Tedersoo et al. 2014) However, a common misconception is that a molecular marker will define a species, which is not the case. Instead, it is merely another, yet very objective, trait which can be used to tell species apart. As such, molecular markers can be effective tools that will help us to verify a species concept, but they do not free us from the work required to understand the biology of a group of organisms and develop appropriate species concepts which apply to the group in question (Briones et al. 2014)

The analysis of sequences from various markers has radically changed our view of the protistean world; there is now a better understanding of the evolution and deep relationships of eukaryotic groups, particularly for protists (Pawlowski 2013). Within the protists, myxomycetes assume a special position. Primarily, they are the most species-rich of several groups of protists that, often within independent ancestries, acquired the capability to form macroscopic fruit bodies which produce and then release airborne spores (Schnittler et al. 2006, 2012). Myxomycetes constitute a phylogenetically ancient group of eukaryotic protists, perhaps starting diversification even before the appearance of the first land plants (Fiz-Palacios et al. 2013). Except for the exosporous genus Ceratiomyxa, whose phylogenetic position is still under debate, at least the endosporous myxomycetes (Myxogastria) undoubtedly constitute a monophyletic taxon within the supergroup Amoebozoa (Pawlowski & Burki 2009, Fiore-Donno et al. 2010). With a dispersal (but not feeding) ecology similar to that of many fungi, myxomycetes can be termed “fungus-like protists”. Unlike fungi, myxomycetes act in nature as predators of other microorganisms and not as decomposers or pathogens (Keller & Braun 1999). Their amoebal stages can reach high densities in soil (Feest & Madelin 1985, Urich et al. 2008, Geisen et al. 2015), making them one of the major microbial predator groups in soil (Stephenson et al. 2011, Stephenson & Feest 2012). The classical division of the myxomycetes into five orders (Echinosteliales, Liceales, Trichales, Stemonitales and Physarales) found in most systematic treatments is now replaced by a division into two major groups, the dark-spored (Collumellidia) and the bright-spored myxomycetes (Lucidosporidia, compare Leontyev et al. 2017). This division was first recognized by Rostafiński (1875), who distinguished the Amaurosporеае (=dark-spored) and the Lamprosporеае (=bright- spored) on the basis of the color of the spore mass.

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For myxomycetes, taxonomic research historically took another direction than for most other groups of protists, since myxomycetes develop visible fruiting bodies, whose morphological characters can be studied. First, myxomycetes were already described by Linné (1792) as belonging to the fungal kingdom. From these early observations a morphological species concept emerged, and several major monographs (Rostafiński 1875, Lister 1894, 1911, 1925, Martin & Alexopoulos 1969) significantly increased the number of described species (see figure 1 in Schnittler & Mitchell 2000). The concept is based solely on morphological characters of the fruit body (Walker & Stephenson 2016), which show a complex structure often with a stalk elevating spores above the substrate and a capillitium inside a more or less durable, sometimes evanescent peridium (Schnittler et al. 2012). In contrast, the amoebae and plasmodia cannot be differentiated at the species level. This fruit body-based morphological species concept prevailed unquestioned for nearly 200 years and forms the base of virtually all of the diversity research on myxomycetes (Stephenson et al. 2008, Stephenson 2011). Currently, close to 1000 morphospecies have been described (Lado 2005–2016), but even this number appears very low in the light of present estimates for the richness of protistean species, which range from 1.4x105 to 1.6x106 (Adl et al. 2007). As such, reliable barcoding markers that are as well applicable in ePCR would open a new window of opportunity, allowing us to detect and determine trophic stages of myxomycetes (the myxamoebae) in nature (Urich et al. 2008).

A second direction of research, using a few cultivable species of mostly the Physarales as models to answer fundamental biological questions, created a competing species concept. As groups of compatible strains can be observed within a morphological species, a ‘biological species’ (biospecies) concept was developed (Clark 1995, Collins 1979). The problem lies in the applicability of this concept, since to prove species identity, single-spore cultures have to be produced and checked for subsequent sporulation – a laborious task that greatly limits the practical use of this concept. In addition, it is questionable if sexual events will always occur in the myxomycete life cycle, since homothallic, presumably apomictic, strains have been found in culture (see discussion on reproductive options in Feng et al. (2016) and Walker & Stephenson (2016). We therefore face the unsatisfying situation that two alternative species concepts exist – the practically applicable morphological concept, which may be of limited resolution, and the theoretically well founded but difficult to apply biospecies concept. Once again, molecular markers may help to link both species concepts to one another.

The purpose of this review is to discuss and generalize the first results on the use and suitability of different molecular markers for barcoding. A marker that is suitable for barcoding has to fulfil the following requirements: (i) display high inter- but low intraspecific variation for the group being studied (the barcoding gap, Meyer & Paulay 2005), (ii) possess conserved flanking sites allowing the development of universal PCR primers for broad application within a larger taxonomic group, and (iii)

46 have a short sequence to facilitate current capabilities of DNA extraction and amplification (Kress & Erickson 2008) and to allow comparison with the short sequences produced by metabarcoding approaches (=e.g. Coissac et al. 2016). Markers that match these requirements are not necessarily useful for phylogenetic research, since they are often too variable to reveal relationships between basic lineages. The following paragraphs will present markers applied in molecular studies of myxomycetes from natural populations and compare and contrast their advantages and disadvantages for a barcoding approach in the group.

RESULTS AND DISCUSSION

Barcoding in protists differs from approaches used in higher eukaryotes Many protistean groups represent deep lineages in the eukaryotic tree of life and have accumulated a considerable extent of within-group diversity (Pawlowski et al. 2012). Consequently, compared to plants, higher fungi, or animals, myxomycetes display a much higher within-group genetic variance, which is not uncommon for protists (see Adl et al. 2014 for a review on commonly used primers for the 18S rDNA gene across protistean groups). It has been found that almost no published primers are specific for higher-level taxa (e.g., phylum, class, or order) and thus do not meet the requirements for application in environmental surveys. Another problem is that many primers used in published studies to amplify sequences from particular taxa are not actually that specific and will also amplify non- related taxa, such as the plant substrate upon a myxomycete colony develops. As such, the biggest challenge is to find markers which amplify all known species of myxomycetes with comparable efficiency.

Molecular research on myxomycete diversity and phylogeny Similar to the situation in dictyostelids, where in spite of a very popular model organism (Dictyostelium discoideum) the diversity of the whole group was explored comparatively late (Schaap et al. 2006, Romeralo et al. 2007, 2011), the model species for myxomycetes (Physarum polycephalum) was already popular already during the 1980’s (Goodman 1980). However, this did not immediately trigger research directed to explore the molecular diversity of the group. Apart from their lacking economic importance (myxomycetes are neither pathogenic nor used in large scale biotechnology procedures), one reason is the high genetic diversity even in genes regarded as conservative, which makes it difficult to find primers that are universal for the whole group. Initial efforts to sequence the DNA of myxomycetes beyond model species have been made during the last decade. Current phylogenies constantly reveal that the traditional order Echinosteliales serves as a basal clade for the group, and all other remaining taxa can be split into two basal clades, the rather genetically heterogeneous group of Lucisporidia or bright-spored myxomycetes (Fiore-Donno et al.

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2013) and the more homogeneous Columellidia or dark-spored myxomycetes (Fiore-Donno et al. 2012).

SSU: 18S rRNA gene (small ribosomal subunit) This nuclear marker is represented in myxomycetes, like in many eukaryotic taxa, by several to many hundreds of extrachromosomal copies, the so-called mini-chromosomes (Torres-Machorro et al. 2010) or rDNA (Johansen et al. 1992). This greatly facilitates the amplification of DNA and helps to obtain sequences from limited material. Molecular barcoding using SSU rRNA gene sequences consequently has become extremely popular among protistologists (Guillou et al. 2013). In spite of their multiple copies, SSU sequences are usually homogeneous, since one of the parental genotypes is eliminated in crosses during plasmodial development (Ferris et al. 1983). Rare exceptions appear to prove this rule, since Feng & Schnittler (2015) reported only a single heterogeneous sequence among 198 investigated accessions of Trichia varia. In a similar study of Hemitrichia serpula, three of 135 investigated specimens revealed heterogeneous SSU sequences (Dagamac 2016). All of these instances most likely involve events of cryptic speciation (see below). Ribosomal RNA has a tertiary structure with highly conserved loops on more variable stems (Cannone et al. 2002). This uneven distribution of variability makes it possible to design primers targeting conservative regions flanking the variable helices.

Fig. 1. Schematic view of the first part of the SSU as often used for barcoding in myxomycetes, showing the approximate number of bases (nomenclature of the variable helices from Wuyts et al. 2002). Conservative parts of the gene are coded in yellow and blue (a little microsatellite found in dark-spored species); variable helices are coded in pink. Abbreviations indicate the approximate location of primers mentioned in Table 1 (black font for dark-spored, red font for bright-spored myxomycetes). For location within the whole SSU, compare Fig. 4 in Fiore-Donno et al. 2012).

Currently ten insertion sites throughout the SSU are known for the presence so-called group I introns (Fiore-Donno et al. 2013, Feng & Schnittler 2015), which may extend complete gene sequences from ca. 2 000 to more than 7 000 nucleotides. These introns are transmissible by horizontal gene transfer between species. Occurrence and length of introns varies highly between myxomycete species (Johansen et al. 1992, Lundblad et al. 2004), and cultivable members of the Physarales were 48 established as a model system for the study of group I introns (Nandipati et al. 2012, Wikmark et al. 2007a, b). The intron homing (insertion into coding sequences) most likely takes place via an intron- coded homing endonuclease (Flick et al. 1998), but reverse splicing through a RNA intermediate may also occur (Haugen et al. 2005a, Lambowitz & Belfort 1993). Due to this splicing, introns are selectively neutral (Edgell et al. 2011; Haugen et al. 2005b) and thus can degenerate rapidly. Finally, the insertion place is freed, and transmission of the introns can occur again via syngamy and subsequent karyogamy of amoebae within the sexual cycle. Described for other organisms (Goddard & Burt 1999, Goddard et al. 2006), this Goddard-Burt cycle of intron loss and insertion seems to occur in myxomycetes as well, as shown for a study on Trichia varia (Feng & Schnittler 2015). This explains the frequent occurrence of such introns in myxomycetes, which does not reflect phylogenetic relationships. Regarding the use of SSU sequences for barcoding, introns undoubtedly enhance the resolution in cases of closely related taxa, as shown for the genus Meriderma (Feng et al. 2016), but in general they are not suitable for barcoding, since the intron sequences can hardly be aligned across species, although they can be shared between evolutionarily distant taxa. From these reasons, the first part of the SSU comprising ca. 600 bp appears to be the most suitable as a barcoding marker (Fig. 1). This sequence is free of introns and includes four very variable helices (compare Fig. 4 in Fiore-Donno et al. [2012]). For dark-spored myxomycetes, nearly universal primers are available (S1 / S19R, Fiore-Donno et al. [2008]); only some species of Comatricha and Stemonitopsis apparently cannot be amplified. However, this primer pair does not exclusively amplify myxomycetes. For bright-spored myxomycetes, universal primers have not been identified, but most of the Trichales can be covered with 3–5 primers. The very deviating genus Cribraria and most species of the paraphyletic genus Licea remain difficult to work with (Fiore-Donno et al. 2013).

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Table 1: Proposed primer sequences for barcoding myxomycetes with partial SSU sequences.

Primer sequence 5' -> 3' taxonomic range FORWARD S1 aacctggttgatcctgcc dark-spored myxomycetes, all genera except some (standard) Stemonitales but amplifies as well some other protists (Fiore-Donno et al. 2008) S3b tctctctgaatctgcgwac dark-spored myxomycetes, some bright-spored, specific for myxomycetes (Hoppe & Schnittler 2015) NUSSUF3 cctgccagaatcatatgcttgtcc bright-spored myxomycetes (Feng & Schnittler 2015) NUSSUF20 tcgacaacctggttgatcctg dark-spored myxomycetes (Feng et al. 2016) S1A ctggttgatcctgccagaat bright-spored myxomycetes, especially Trichiales (Dagamac 2016) SF2Dark gttgatcctgccagtagtgt dark-spored myxomycetes (Fiore-Donno et al. 2016) S2 tggttgatcctgccagtagtgt dark-spored myxomycetes (Fiore-Donno et al. 2008) SF12 tcytaaagaytaagggatgcatgyc Lycogala epidendrum and probably other bright-spored myxomycetes (Liu et al. 2014) REVERSE S19R tgctggcaccagacttgt dark-spored myxomycetes and some bright-spored (standard) genera but covered in part by the intron insertion site S516, which may give problems in genera with this intron (Fiore-Donno et al. 2008) S30shortR cccttatcctctgtacccgt dark-spored myxomycetes, some bright-spored, rather specific for myxomycetes (unpubl.) NUSSUR4 accagacttgtcctccaattgttac bright-spored myxomycetes (Feng & Schnittler 2015)

SR4Bright tgctggcaccagacttgt bright-spored myxomycetes (Fiore-Donno et al. 2012) NUSSUR13 accagacttgtcctctaattgttac dark-spored myxomycetes (Feng et al. 2016) SRHem1 ggggtttaaaggtccccc bright-spored myxomycetes, especially Trichales (Dagamac 2016) S31R atctctcaggcccactctccagg dark-spored, specific for myxomycetes (unpubl.) SU19R gacttgtcctctaattgttactcg dark-spored myxomycetes (Fiore-Donno et al. 2012) SR19Dark gtcctctaattgttactcgad dark-spored myxomycetes (Fiore-Donno et al. 2016) SP03r tcctctaattgttactcgag dark-spored myxomycetes (Kamono et al. 2013)

Most easily amplified are the dark-spored myxomycetes, where a unique signature TCTCTCT can be used as anchor point for the beginning of a marker (Fiore-Donno et al. 2012). This section of the SSU gene seems to separate morphospecies reliably; in a study which included 530 accessions of 27 morphospecies, all morphospecies were separated (Feng & Schnittler [2016]). The same was found for nivicolous dark-spored species (144 accessions of 36 taxa, Novozhilov et al. [2013]). However, most of the investigated morphospecies seem to possess multiple ribotypes, as judged by the figures derived from several available studies: bright-spored lignicolos myxomycetes 50 ribotypes / 17 taxa, ratio 2.9, dark-spored lignicolous myxomycetes 15 / 10, 1.5 (Feng et al. 2016) and dark-spored nivicolous myxomycetes 61/36, 1.7 (Novozhilov et al. 2013). Even higher ratios are found for the number of ribotypes within the few morphospecies with multiple specimens sequenced: Lamproderma

50 puncticulatum 3, L. columbinum 7 (Fiore-Donno et al. 2011); Tubifera ferruginosa 24 (Leontyev et al. 2014, 2015), Trichia varia 18 (Feng & Schnittler 2015, Feng et al. 2016); and Badhamia melanospora 37 (Aguilar et al. 2014). Numbers of ribotypes per species vary widely, the contrasting example to those mentioned above was Hemitrichia calyculata, where 52 accessions shared a single ribotype, but these were all collected in a 3 x 3 km patch of forest (Feng & Schnittler 2016). This shows that it should be safe to expect that within most morphospecies several ribotypes will be found using this marker.

ITS: Internal Transcribed Spacer This marker became a barcoding standard for several other groups of organisms, mainly fungi (Schoch et al. 2012, Schmidt et al. 2013, Xu 2016). As obvious from its arrangement within the clusters of ribosomal genes, the marker is linked to SSU. The first primers for this region were already designed and tested by Martin et al. (2003); these authors reported large differences in the length of the ITS1- 5.8S-ITS2 region between Lamproderma sp. and Fuligo sp. (both dark-spored myxomycetes) due to simple sequence repeats. Two studies show that this marker seems to be extremely variable in myxomycetes. Winsett & Stephenson (2008) found both ITS1 and ITS2 in Didymium squamulosum to vary to such an extent that sound biogeographical conclusions were difficult to draw. Similarly, for Lamproderma spp. the ITS region was found to vary to such an extent in both sequence and length that an alignment across species was impossible (Fiore-Donno et al. 2011). Baba et al. (2015) investigated 52 morphospecies with a series of different primers and concluded that the ITS1-5.8S-ITS2 region does not mirror deep evolutionary relationships in myxomycetes but may be suitable as a barcoding tool. In contrast to the SSU region, it seems to be much more difficult or even impossible to design primers applicable for all myxomycetes or even larger taxonomic groups.

EF1A: Elongation factor 1 alpha gene This marker is a nuclear protein coding gene which seems to be present in a single copy in myxomycetes (Baldauf & Doolittle, 1997). However, from Dictyostelium discoideum two copies of EF1A are known, both located on chromosome 1 (efaAI, gene ID: 8616922; and efaAII, gene ID: 8616783). Since it is a protein-coding gene, the variation in this gene is mostly uniformly distributed and is naturally found primarily in the third base of a triplet across the whole gene, which makes it difficult to find truly universal primers. Indeed, different primer pairs are currently used for amplification of EF1A of dark-spored and bright-spored taxa (Fiore-Donno et al. 2005, Feng & Schnittler 2015). A splicesomal intron is located in the first part of the gene, which can have very different lengths, ranging from 40 bases in Trichia alpina to 719 bases in Lycogala epidendrum (Fiore-Donno et al. 2013). In some taxa this intron poses a serious problem for Sanger sequencing due to single nucleotide repeats or simple sequence repeats (e.g, in Meriderma aggregatum, Feng et al.

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[2016]). The intron might be valuable for investigating intraspecific diversity; in the bright-spored myxomycete Trichia varia it is about 60 bases long and showed differences between, but not within three intraspecific groups (Feng & Schnittler 2015). In addition, in Physarum albescens a second intron was found (Shchepin, pers. comm.). As a nuclear and chromosomal gene, this marker is independent from the extrachromosomal SSU and ITS markers. In contrast to these, it seems to show Mendelian inheritance. Therefore, heterozygous sequences occur frequently, complicating sequence edition (Feng et al. 2016). The variation in the first part of this marker differs between taxa. Relations of variation for partial SSU / partial EF1A are for Trichia varia (198 specimens): 12 ribotypes / 3 EF1A genotypes (differing only by a short intron, Feng & Schnittler [2015]); Hemitrichia serpula (30 specimens): 12 ribotypes / 16 EF1A genotypes (only exon parts, Dagamac [2016]), Meriderma atrosporum agg. (81 specimens): 21 ribotypes / 25 or 54 EF1A genotypes (with and without a splicesomal intron, Feng et al. [2016]). The second part of EF1A also showed considerable variation in Physarum albescens (63 specimens): 15 ribotypes / 20 EF1A genotypes (only exon parts, Shchepin, pers. comm.) and Lepidoderma chailletii (19 specimens): 8 ribotypes / 7 EF1A genotypes (Shchepin et al. [2016]).

COI: Mitochondrial cytochrome c oxidase subunit I gene This gene marker is widely used in protists (Adl et al. 2014). Its protein-coding sequence is sufficiently conservative to be able to design markers working for a wide taxonomic spectrum of both dark- and bright-spored myxomycetes. Mitochondrial genes in myxomycetes are inherited mostly uniparentally with complex inheritance patterns. In P. polycephalum, a hierarchy of mating-types with predictable mitochondria donors for mating crosses was found, whereas D. iridis does not show this hierarchy. However, in both species biparental inheritance of mitochondria can sometimes occur, at least in culture (Silliker & Collins 1988, Silliker et al. 2002, Moriyama & Kawano 2003). Moreover, in Ph. polycephalum mitochondrial fusion and recombination of mitochondrial genomes was revealed, complicating inheritance patterns even more (Kawano et al. 1991, 1993). In contrast to the markers listed above, currently no introns were reported for COI in myxomycetes. Recently developed primers have demonstrated the ability to amplify the second part of COI (about 540–600 bp) in several species from both major clades of myxomycetes (Feng & Schnittler 2015, Shchepin et al. 2016), thus making it a promising additional marker for the group. Sequences seem to have levels of variation comparable with that of EF1A or even higher and are well alignable across species. The resolution is often sufficient to reveal putative biospecies within a morphospecies (Feng & Schnittler 2015, Shchepin et al. 2016). Another pair of primers was developed by Liu et al. (2014) and it was possible to amplify partial COI for several dark-spored and one bright-spored species (Lycogala epidendrum), although the last was very divergent from all COI sequences of myxomycetes accessible in Genbank and may have resulted from contamination.

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Myxomycetes show several unusual types of RNA editing of mitochondrial gene transcripts, including insertions of single nucleotides (mostly C, but also U) or dinucleotides and deletion of nucleotides (Mahendran et al. 1994, Gott et al. 2005, Traphagen et al. 2010, Chen et al. 2012). This leads to a very unusual phenomenon, since protein-coding DNA sequences possess gaps in a few triplets, where the missing nucleotides are inserted during transcription. In Physarum polycephalum and Didymium iridis this editing occurs in nearly all mitochondrial genes with extremely high accuracy, but the mechanism guiding it still remains unknown (Visomirski-Robic & Gott 1995, Chen et al. 2012). Since both position and number of insertional editing sites vary considerably between myxomycete taxa (Krishnan et al. 2007), they can serve as an additional source of information in phylogenetic analyses. From this reason, alignments of COI sequences across species may show gaps which denote sites of insertional editing that differ between species. The full repertoire of insertion sites for a given COI sequence can be retrieved by aligning it with a mature mRNA of the same or other species, because the mature COI transcript is highly conservative in length. In some morphospecies, even those consisting of several putative biospecies, insertional editing sites in COI are uniform, as found for Trichia varia (Feng & Schnittler 2015) and Physarum albescens (Shchepin, pers. comm.). In other cases, such as in Lepidodema chailletii, insertion sites help to distinguish L. chailletii sensu stricto from several cryptic twin species, but as well other Lepidoderma species (Shchepin et al. 2016). More studies are needed to verify if this marker can be consistently used for all species of myxomycetes. It is independently inherited form all markers mentioned above, which makes it interesting for the investigation of speciation processes (see below). mtSSU: 16S rRNA mitochondrial SSU gene A study with a short section (ca. 250 bp) of this gene in Didymium difforme (Winsett & Stephenson 2011) and Fuligo septica (Hoppe 2013) found essentially the same patterns as seen with SSU sequences in other genera of Physarales. This marker is not yet sufficiently studied to conclude anything about its suitability for barcoding.

First results: hidden diversity and species concepts The first studies targeting within-species genetic variation of selected morphospecies of myxomycetes clearly demonstrated that the morphological approach seems to largely underestimate diversity in myxomycetes. If multiple markers are compared to each other, a pattern begins to emerge – clades with unique combinations of SSU and EF1A genotypes are found within morphologically circumscribed species. Given the independency of these two markers, free recombination within a species should be possible, but this was not observed for the investigated morphospecies. An earlier study found three and four clades for Lamproderma puncticulatum and L. columbinum, each with one ribotype and one EF1A genotype (Fiore-Donno et al. 2011). For Trichia varia, three clades were

53 found (each with several ribotypes and one EF1A genotype), and the reproductive isolation of these was confirmed by COI and patterns in intron variation in the complete SSU sequences (Feng & Schnittler 2015). These clades can be seen as reproductively isolated, putative biospecies. Similarly, for Meriderma atrosporum agg. putative biospecies where found, and evidence for reproductive isolation was provided by an analysis of alleles in the EF1A gene, which always combine within one clade (Feng et al. 2016). A third study, based on SSU and EF1A sequences, found putative biospecies within Hemitrichia serpula, with additional evidence provided by slight morphological differences (Dagamac, unpubl.). In another study, three putative biospecies were found in Lepidoderma chailletii using partial SSU, COI and EF1A sequences (Shchepin et al. 2016, in press). Therefore, the combination of independent markers seems to provide a powerful tool to study speciation within myxomycetes. What can be safely stated with the current state of knowledge? First, partial SSU sequences, which are now the most promising barcode marker, can be used to tell morphospecies apart. Second, the resolution of this marker is even higher, for most morphospecies multiple ribotypes must be expected. Third, groups of multiple, slightly deviating ribotypes seem to form putative biospecies, and this can often be verified with an independent marker. Fourth, the number of ribotypes per species seems to be clearly higher than the number of putative biospecies. As such, we must expect a significant amount of hidden diversity in myxomycetes consisting of reproductively isolated (bio)species which can not yet be differentiated on the basis of morphological characters, although further research may yield suitable characters in at least some of these cases. Moreover, cultivation studies found homothallic (single spore cultures yield fruit bodies), presumably asexual strains (see discussion in Clark & Haskins [2010, 2013]). The existence of these asexual strains could not be convincingly demonstrated for natural populations (see discussions in Fiore- Donno et al. [2011] and Feng et al. [2016]) but if they do exist, such strains will increase cryptic diversity. Since myxomycetes may disperse not only by meiospores (from fruit bodies) but also by microcysts (formed asexually by amoebae) and long-distance dispersal can occur (Kamono et al. 2009), together with the assumed low level of competition among species (Schnittler 2001) this raises an intriguing question for further research. Do such cryptic taxa have narrower ranges and ecological niches than the respective morphospecies?

Towards a database of partial SSU sequences In addition to the choice of the right marker sequence, a major obstacle for the application of the barcoding method is the compilation of a quality-checked comparison database. For a first survey with a full barcoding component (Feng & Schnittler 2016) all partial SSU sequences available in NCBI were screened (June 8, 2015), and only 73/270 unique sequences of bright-/dark-spored myxomycetes were found that (i) fit into the alignment (a substantial part of sequences seem to result from cross- contamination during sample preparation for sequencing) and (ii) were accompanied by

54 comprehensible determinations (with reference to a voucher specimen). Compared with the 1000 described morphospecies, which may be represented by 2000–10000 ribotypes as estimated from the case studies mentioned above, it becomes clear that currently only a small proportion of the molecular diversity that exists for myxomycetes has been explored, even for the most widely used marker, partial SSU sequence. The existence of error prone sequences in public databases combined with the continued ongoing description and/or renaming of new taxa and their varieties calls for a systematic pipeline ensuring quality insurance of the taxonomic assignments, connected with the ability to rename entities with sufficient backtracking throughout the databases. How to systematically and continuously improve public databases is a problem faced in all organisms, and the implications and possible solutions are beyond the scope of this review. However, these problems have been identified and addressed for several groups of organisms; good examples are the UNITE database (Kõljalg et al. 2005) and the FUNGuild analysis tool (Nguyen et al. 2016) for the reliable taxonomic and partly functional assignments of fungi, as well as the recently launched UniEuk project (www.unieuk.org) which will focus on protistean diversity, and which originates out of the EukRef Database project also recently launched (2015) with the intent of establishing a curated 18S SSU reference database for all eukaryotic lineages across the tree of life (www.eukref.org). Common for both databases are that they are based on a community effort driven by experts across the scientific community and various institutions. In addition, both databases allow for a broad range of metadata to be submitted along with sequences, thus potentially aiding the ecological understanding of the lifestyle and habitat of particular species

Use of barcoding markers for analyzing environmental samples In contrast to all other detection techniques that have contributed to the body of data on myxomycete ecology and distribution for more than 200 years (Stephenson et al. 2008), amplifying sequences from environmental samples is currently the only approach which is able to detect the trophic stages of myxomycetes at or near the species level. Culture-based studies can quantify amoebal density in the soil microhabitat (Feest 1985, 1987, Kerr 1994, Stephenson & Landolt 1996), counting plasmodium- forming units to tell myxomycete amoebae apart from their free-living relatives, but they do not allow us to differentiate between species. First approaches that employed molecular techniques to distinguish among different amoebal communities included fingerprinting methods such as denaturing gradient gel electrophoresis (DGGE, Ko Ko et al. 2009) and Terminal Restriction Fragment Length Polymorphism (TRFLP, Hoppe & Schnittler 2015). These methods provide an easy approach to compare myxamoebal communities, but they hardly provide enough resolution to allow a correct identification of species. This becomes possible with the amplification of particular markers from bulk DNA from environmental samples (DNA metabarcoding), but two obstacles remain. First, appropriate primers must be developed. Second, the resulting sequences must be assigned to species, which links this

55 approach tightly to progress in barcoding. Undoubtedly, with anonymous Operational Taxonomic Units (OTUs) numerous novel insights can be obtained and questions related to diversity, distribution and richness can be answered, but without assignment to real species these results cannot be related to the large body of fruit body-based data (Stephenson et al. 2008) on myxomycete distribution and ecology. Primer specificity is crucial: in a metagenomic study using universal primers targeting the whole SSU (Lesaulnier et al. 2008), myxomycetes were absent from the investigated soils. Most primers designed to amplify a broad spectrum of SSU sequences from eukaryotes will miss the highly divergent SSU sequences of myxomycetes (Fiore-Donno et al. 2010). However, a first study exclusively focusing on actively living protists in soil employing a transcriptomic approach (RNA) revealed members of the Amoebozoa as one of the major terrestrial protist groups. Myxomycetes accounted for 25% of all ribotypes in the soil sample and represented the single largest component of total protozoan soil biodiversity (Urich et al. 2008). A second study targeting SSU rRNA of nivicolous dark-spored myxomycetes found a high number of unknown sequences belonging to myxomycetes (Kamono et al. 2013). Comparatively easier to carry out are studies targeting DNA sequences, because they do not imply a reverse transcription step, but these cannot differentiate between active and dormant stages (such as inactive spores). The first environmental DNA studies of wood-inhabiting bright-spored myxomycetes (Clissmann et al. 2015) and of dark-spored myxomycetes from lowland soils of grasslands in Germany (Fiore-Donno et al. 2016) again demonstrated the presence of many myxomycete sequences of unknown lineages along with well-known species. As was the case in the previous study, investigations employing ePCR in lowland boreal forests (Shchepin et al., pers. comm.) obtained evidence that myxomycetes may have larger ranges as amoebal populations compared to data from fruit bodies. In both studies sequences assignable to nivicolous species were found, which usually do not fruit in lowlands. All of these studies covered the four most variable helices of the first part of the 18S rDNA gene in myxomycetes as described above.

In all these studies, a significant proportion of unknown ribotypes (up to 60–70 %) were found. These could easily be aligned to myxomycete sequences of known species identity, but they did not cluster tightly to any reference sequence and thus were assumed to belong to undescribed taxa or species not yet represented in reference databases. This proportion of "hidden diversity" continues to pose a serious methodological problem, and further research is needed to show to what extent the presence of these sequences can be explained by (i) technical errors (for instance, chimera formation), (ii) the lack of comparison sequences from fruit bodies or (iii) the fact that they truly belong to yet undiscovered taxa. The results from early metagenomic studies were often over-interpreted, leading to high estimates for hidden diversity, especially in marine algae and protists (e.g., Edgecomb et al. 2011). It is now well understood that the reliability of metagenomic results depends on three factors: (i)

56 effective management of sequencing errors, (ii) the existence of comparison databases from “real” organisms to connect OTUs to described species and (iii) the statistical methodology to cope with the still larger and increasingly complex datasets (Bálint et al. 2016). Given the fact that only a minor fraction of the ca. 1000 known morphospecies of myxomycetes (Lado 2005–2016) are currently represented by barcode sequences, and for even fewer (if any) morphospecies is the ribotype diversity known, the lack of comparison sequences certainly causes an overestimation of hidden diversity. In addition, some sequences may include amoebal strains that have lost the ability to fruit. Such non- fruiting strains of myxomycetes may exist in nature, since a loss of functionality in a single gene in the complex ontogenesis of fruit body formation may halt spore and/or the development of the entire fruit body. This will severely impede dispersal abilities, but it does not affect the survival and asexual reproduction of amoebal populations, which may persist over long periods of time. Even with databases becoming more complete, future studies are likely to include a significant number of OTUs not assignable to known species. These OTUs will often be identified only from a genetic similarity threshold (de novo picking), and the assignment of ‘unknown OTUs’ thus largely depends on the knowledge of the intraspecific variation in known species. However, setting this threshold is not a trivial task, as a full account of the intraspecific variance (number of ribotypes) is seldom known, and the continuous evolution and speciation might lead to an uneven substitution rate between species (Nebel et al. 2011, Ryberg 2015). Thresholds are often set within the range of 97% to 99% similarity (see Bálint et al. [2016] and references therein). To avoid the influence of sequencing errors, a 97% similarity threshold is often being used as a “rule of thumb”. However, this might result in a dataset not in accordance with the species taxonomy and potentially miss ecological information (Eren et al. 2013).

Outlook In spite of difficulties with primer specificity and universality, barcoding myxomycetes from their fruit bodies is now possible. Consequently, this tool should be used when a new morphospecies is described. The few available studies show a significant extent of hidden diversity in the group and indicate that the application of barcoding techniques will uncover a new level of diversity, leading to more precise data on the ecology and distribution of particular species. Barcoding myxomycete fruit bodies will also allow us to link the existing body of data with new data from studies based on environmental PCR.

ACKNOWLEDGEMENTS N.H.A.D is indebted to the DAAD (Deutscher Akademischer Austauschdienst) for a PhD scholarship. Many consumables to obtain barcode sequences were financed by projects from the Deutsche Forschungsgemeinschaft (SCHN 1080/2, RTG 2010). Y.K.N. and O.N.S. acknowledge the Russian Foundation of Basic Research (15-29-02622) for support.

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Borg Dahl et al. Fine scale niche differentiation among myxamoebae (submitted 30.12.2017).

3.3 FINE SCALE NICHE DIFFERENTIATION AMONG AMOEBAL COMMUNITIES OF DARK-SPORED MYXOMYCETES DETERMINED BY LANDSCAPE STRUCTURES AS WELL AS BIOTIC FACTORS.

Mathilde Borg Dahl*1, Asker Daniel Brejnrod2, Jakob Russel2, Søren Johannes Sørensen2 and Martin Schnittler1

1. Institute of Botany and Landscape Ecology, Ernst Moritz Arndt University Greifswald, Greifswald, Germany

2. Section of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark

*Corresponding author: [email protected], +49 3834 420 4123, Ernst Moritz Arndt University Greifswald, Institute of Botany and Landscape Ecology, Soldmannstrasse 15, 17487 Greifswald, Mecklenburg-Vorpommern, Germany. ORCID: 0000-0003-3180-2543.

Manuscript submitted the 30th December 2017 for publication in Environmental Microbiology.

Supplementary files are available online via Dropbox (Online link)1

SUMMARY Among soil-inhabiting protists, myxomycetes stand out with their macroscopic fructifications which have allowed studies on their ecology and distribution for nearly two hundred years. Although they constitute one of the major groups of soil protists, knowledge on abundance and structure of amoebal communities is largely lacking. We take advantage of modern molecular techniques, such as direct DNA amplification from environmental extracts (ePCR) in a joint approach to analyse microbial soil communities by parallel metabarcoding of bacterial, fungal and dark-spored myxomycete communities from an elevational transect in the northern limestone German Alps. We find vegetation to be the main explanatory parameter for community composition of all three communities. Bacteria and fungi display similar community responses, driven by symbiont species and plant substrate quality. Myxamoebae show a more patchy distribution, though still clearly stratified among genera, which seems to be a response to both structural properties of the habitat and specific bacterial taxa. A substantial species turnover with elevation was found for communities of all three groups of organisms, which is interpreted as an adaptation to harsh environments. Finally we report a high number of myxomycete OTUs not represented in our reference database of sequenced fruit bodies, which might represent novel species.

INTRODUCTION Soil protists are a diverse assemblage of differsent basal Eukaryotic lineages (Adl et al., 2012; Ruggiero et al., 2015) which play a crucial role in decomposition, where they stimulate activity of other microbes, alter root architecture and consequently influence higher trophic levels and plant growth (Bonkowski, 2002, 2004; Geisen et al., 2015b; Geisen and Bonkowski, 2017, Hünninghaus et al., 2017). Nearly always belonging to the invisible world, these organisms are understudied due to a lack of cultivation methods and/or morphological descriptors, which complicates diversity studies

1 https://www.dropbox.com/sh/lkdadijydb8l18p/AABjvjzHt3dGQM0ADCKNTsJha?dl=0 67

Borg Dahl et al. Fine scale niche differentiation among myxamoebae (submitted 30.12.2017).

based on morphological species differentiation. Among soil-inhabiting protists, myxomycetes are an exception due to their macroscopic fructifications (Schnittler et al., 2012) which have been studied for nearly two hundred years (Stephenson et al., 2008). Solely based on morphological characters of the fructifications, ca. 1000 species are described (Lado 2005-2017) and a substantial body of data on ecology and distribution of these fructifications exist (Stephenson et al., 2008, Alvarado, 2017). Although they constitute a major group of soil protists (Urich et al., 2008) knowledge of abundance and structure of amoebal communities is largely lacking. Advances in molecular techniques, such as direct DNA amplification from environmental extracts (ePCR), have made field studies of myxamoebae (and other microbes) possible, and myxamoebae are currently estimated to account for between 5 to almost 50% of all soil amoebae and present in a wide variety of soils (Urich et al., 2008; Geisen et al., 2015b; Jacquiod et al., 2016). As for many microbial groups, the true diversity of myxomycetes seems to be much greater than shown by morphological characters (Boenigk et al., 2012), and many described morphospecies seem to consist of groups of several cryptic species (Feng and Schnittler, 2015; Feng et al., 2016; Shchepin et al., 2016; Borg Dahl et al., 2017a; Dagamac et al., 2017).

As recently highlighted by Geisen et al. (2017) it is crucial to understand the factors determining protist community assembly and structure, in order to move forward in understanding key aspects of soil ecosystem functions, such as the implications of protist diversity and richness on carbon and nutrient cycling (Gessner et al., 2010; Hünninghaus et al., 2017). Environmental gradients are known to structure microbial communities at both global and local scale (Dumbrell et al., 2010; Lanzén et al., 2016). Climatic (e.g. solar irradiation, mean annual precipitation etc.) and chemical parameters (i.e. pH, concentation of nutrient ions etc.) have been reported as major abiotic niche differentiation axes for microbes (Lauber et al., 2009; Tedersoo et al., 2014, Thompson et al., 2017) together with soil moisture, which have been found to have a strong structuring effect on the community composition of soil protists (Geisen et al., 2014). In homogeneous habitats without an environmental gradient, stochastic processes such as drift and homogenizing dispersal may dominate, as reported for soil eukaryotes across 64 m2 of boreal forest (Bahram et al., 2015). Beside this, biotic interactions may play a role in structuring microbial community composition at a small spatial scale (Bakker et al., 2014; Lima-Mendez et al., 2015; Xiong et al., 2017). Available food resources might be one of the ways how biotic interactions determine the abundance of protists, and specific food preference have been reported for a number of protistean species. Rosenberg et al. (2009) found the amoebae Acanthamoeba castellanii to have distinct grazing preferences for specific bacterial taxa. Likewise, Glücksman et al. (2010) showed differentiated grazing preference on bacteria for cercomonad and glissomonad Cercozoa, and Krashevska et al. (2008) found abundance of soil testate amoebae to be positively correlated with their presumed food resources (bacteria, fungi or algae). In addition, amoebae have been reported to select their microbial prey according to size, not ingesting large and missing small bacterial cells (Rønn et al., 2002; Glücksman et al., 2010). Since bacterial cell size has been shown to be phylogenetically preserved (Portillo et al., 2013), this translates to different grazing pressure for different bacterial taxa.

Based on field collections of myxomycete fruiting bodies, morphospecies are known to have specific environmental habitat requirements such as herbivore dung or decaying wood (Ing, 1994; Liu, Yan, and Chen, 2015; Novozhilov et al., 2017). One of the most distinct ecological guilds in myxomycetes are the nivicolous or “snowbank” species, with their specific habitats first described in 1908 by Meylan (Kowalski, 1975). The ca. 100 described species nearly all belong to the dark-spored myxomycetes, one of two basal clades in the group (Fiore-Donno et al., 2012, 2013). Fruiting occurs in spring where fruit bodies emerges from the soil along the edge of melting snowbanks in mountains, with most accounts coming from the northern hemisphere (Lado, 2004; Ronikier and 68

Borg Dahl et al. Fine scale niche differentiation among myxamoebae (submitted 30.12.2017).

Ronikier, 2009). Myxoamoebea are hypothesized to prey on under-sow microbial communities, and fruiting might be triggered by the change in abiotic conditions during snow melt (Schmidt and Lipson, 2004; Schnittler et al., 2015), which causes a nearly complete turnover of microbial communities (Schadt et al., 2013). According to surveys based on fruit body occurrence, nivicolous species seem to exhibit different preferences for elevation and vegetation types (Lado, 2004; Ronikier and Ronikier, 2009; Novozhilov et al., 2013). However, nothing is known of the trophic life stages of the nivicolous myxomycetes. Fruiting may occur only with optimum conditions, as suggested by a metabarcoding study from German lowland regions (Fiore-Donno et al., 2016) where sequences assignable to nivicolous myxomycetes occurred at places where fruit bodies of these species were never recorded. As such, nivicolous myxomycetes may show broader realized niches as soil amoebae than as plasmodia and subsequent fructifications (see Stephenson and Schnittler, 2017 for an overview of the myxomycete life cycle).

This paper presents a joint approach to analyse microbial soil communities by parallel metabarcoding of bacterial, fungal and dark-spored myxomycete communities from a transect of the northern limestone Alps (Garmisch-Partenkirchen, Germany). We ask if 1) myxamoebae occupy different niches along an altitudinal gradient providing various habitats for nivicolous myxomycetes and 2) if this pattern may be linked to the distribution of putative food resources, i.e. bacteria and/or fungi.

For all three assemblages of soil microbes we can expect the yearly cycles of snowmelt to act as a homogenizing dispersal vector, washing soil particles and thus microbes down the mountain (Crump et al., 2012). In addition myxomycetes (Schnittler and Tesmer, 2008; Kamono et al., 2009) and at least some fungal taxa produce spores suited for long distance dispersal, thus environmental selection is considered the main cause of any stratified distribution patterns observed among the species.

RESULTS

Data quality, annotation and sample site properties Table 1 summarizes OTU yield during all steps of bioinformatics processing. For both myxomycetes and fungi three quarters (>75%) of all reads could be kept after quality filtering, for bacteria the figure was considerably lower (47%). The most likely reason is the larger fragment size of bacterial 16S amplicons, resulting in a poorer quality which hampered assembly. Approximately half of the myxomycetes OTUs, accounting for 56.2% of all reads, could be taxonomically annotated to species, genus or a previously reported ePCR sequence. The remaining OTUs formed distinct clusters which were aligned in-between clusters of annotated OTUs, as seen from the ML tree in Suppl. S1. A small proportion (0.6%, 76 OTUs) were excluded due to poor alignment, of these 36 had a match in the public available NCBI database (using default blast settings). The latter matched with scores of 85.3 ± 1.0% to mainly sequences from the bright-spored myxomycete genus Trichia, a genus including several common wood-inhabiting and at least two nivicolous species. For fungi and bacteria only 19.2% and 15.0% of all OTUs, respectively, could be annotated to family level or deeper, thus hampering a functional classification of these OTUs, since this is mostly possible for deep taxonomic resolution (von Mering et al., 2007; Nguyen et al., 2016). The obtained DNA reads and OTUs were generally not affected by environmental parameters, but for myxomycetes and bacteria significantly fewer OTUs were obtained from the top of the transect (suppl. S2).

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Table 1 Overview on bioinformatics processing steps and classification for the three analysed communities.

Myxomycetes Fungi Bacteria Assembled reads [Mio] 1.68 3.67 2.16 Remaining reads after quality trimming [Mio] 1.32 (78.2%) 3.24 (88.3%) 1.00 (46.8%) Unique reads 261.238 642.682 492.016 OTUs 578 6133 5710 Unique taxon annotations 42 260 215 Sequences mapped to OTUs by similarity 1.40 (83.7%) 3.21 (87.0%) 0.98 (45.5%) a threshold [Mio] OTUs annotated to (accumulated percentage) Species 159 (27.5%) 56 (0.9%) - Genus 86 (42.4%) 316 (6.1%) 311 (5.4%) Family - 808 (19.2%) 546 (15.0%) Order - 789 (32.1%) 483 (23.5%) Class - 382 (38.3%) 523 (32.6%) Phylum - 2890 (85.5%) 2634 (78.8%) Domain - 892 (100.0%) 1035 (96.9%) b - Env. Sequence 80 (56.2%) - unclassified - 253 (100.0%) 178 (100.0%) a Sequence similarity threshold is 99.1% for myxomycetes and 97% for bacteria and fungi. b Unclassified OTUs with >95% match to previously published ePCR sequences form either Caucasus (Borg Dahl et al., 2017a) or Germany (Fiore-Donno et al., 2016). The average proportion of OTUs shared within sample sites was 47%, 60% and 52% for myxomycetes, fungi and bacteria, respectively (Table 2). Almost no OTUs (<0.5% for all three communities) were present in all samples. For bacteria 29% of the OTUs were present in half of the samples, whereas the corresponding figures for myxomycetes and fungi were below 5%. Consequently, the 16 sample sites explained approximately 40 to 50% of the variance between samples for all three communities (Table 2).

Table 2 Overview of the numbers of OTUs shared between different fractions of the samples for myxomycetes, fungi and bacteria. “Explained variance” corresponds to the %R2 value from Permanova on Bray-Curtis dissimilarity matrix with 10 000 permutations, p < 0.001.

Myxomycetes Fungi Bacteria Total OTUs 578 6133 5710 Average number of OTUs per sample (± SD) 41 ± 17 947 ± 168 2 035 ± 581 Range 13–94 603–1340 848–3149 a Average number of OTUs shared within sample site (± 19 ± 12 568 ± 122 1 064 ± 326 SD) Per cent 47 ± 28 60 ± 13 52 ± 16 b OTUs present in all samples 0.00% 0.03% 0.44% OTUs present in 50% of all samples 1.04% 3.82% 29.36% OTUs present in 25% of all samples 6.92% 17.85% 58.46% c Community variance explained by sample sites 41.5% 47.4% 53.4% 70

Borg Dahl et al. Fine scale niche differentiation among myxamoebae (submitted 30.12.2017).

a OTU present in two out of the three samples per site. b Exhaustively processed samples were 41, 45 and 45 samples for myxomycetes, bacteria and fungi respectively. c A total of 16 sites (8 elevations x 2 canopy types) with three samples per site.

Explanatory power of environmental factors for microbial communities The total variance explained by the assessed environmental parameters (summarized in Table 3), as revealed from permutational multivariate analysis of variance (PERMANOVA) was between 30 to 40% for each of the three targeted community (Fig. 1a-c and Table 4). Among the environmental variables, ‘vegetation’ was found to explain the largest proportion (ca. 10%) of community variance between samples for all three groups of organisms.

Table 3 Summary of environmental data for each sample site. Vegetation types: MF: mixed forest, M: natural wet meadows, C: clearing, CF: conifer forest, S: mosaic of shrub thickets and alpine meadows. Canopy types: op: open, cl: closed. Dominant plant types: Wo: woody plants, He: herbs.

Site Elevation Exposition Inclination p H Vegetation Canopy Dominant a b ± s.d. (degrees) (degrees) ± s.d. type type plant type (m.a.s.l) 1cl 1195 ± 11 66.3 ± 50.6 0.7 ± 1.2 - MF cl Wo 1op 1202 ± 2 71.3 ± 19.9 4.7 ± 1.5 7.3 ± 0.2 M op He 2cl 1303 ± 14 51.3 ± 3.2 10 ± 6.6 - MF cl Wo

d 2op 1292 ± 3 306 ± 45 24.3 ± 0.6 6.8 ± 0.3 C op He 3cl 1296 ± 18 21.7 ± 20.6 25.7 ± 1.5 5.6 ± 0.0 MF cl Wo 3op 1296 ± 7 51.7 ± 36.1 29.3 ± 17.8 7.0 ± 0.0 M op He 4cl 1400 ± 19 350.3 ± 8.7 16.3 ± 6.7 4.8 ± 0.1 CF cl Wo 4op 1368 ± 13 348.7 ± 15.5 6.7 ± 9.9 6.7 ± 0.1 C op He 5cl 1498 ± 9 349.3 ± 9.7 28.7 ± 6.7 4.8 ± 0.2 CF cl Wo 5op 1469 ± 22 343.3 ± 14.7 25.7 ± 8.3 5.1 ± 0.4 M op He 6cl 1649 ± 25 335.3 ± 3.1 24 ± 3.6 4.6 ± 0.2 CF cl Wo 6op 1608 ± 24 20.7 ± 28.1 0 ± 0 6.4 ± 0.2 C op He

c 7cl 1707 ± 5 320.3 ± 54.6 37.3 ± 3.1 6.6 ± 0.1 S op Wo 7op 1599 ± 3 17 ± 16 4 ± 4.6 6.5 ± 0.1 S op Wo 8cl 1903 ± 13 74.3 ± 11 18.7 ± 4 6.2 ± 0.1 S op Wo 8op 1883 ± 8 75 ± 8.5 18 ± 3 6.7 ± 0.0 S op Wo a for PERMANOVA the exposition was categorized as: E: East (45-135°), W: West (225-315°) and N: North (315-360° and 0-45°). b Average from three technical replicates. Measures from site 1cl and 2cl were lost, for PERMANOVA the average pH 6.4 was used. c Shrubs occur only at the uppermost elevation belt (1800-1900 m a.s.l.) as thickets of Pinus mugo and Alnus viridis, therefore the vegetation is generally classified as an ‘open canopy’ type. d The dominant plant types in the clearings (C) is herbal, but the sites contain dead tree trunks.

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Table 4 Explained variance by the environmental parameters in the community composition of myxomycetes, fungi and bacteria. Values correspond to % R2 value from Permanova on Bray-Curtis dissimilarity matrix with 1 000 permutations. Ŧ p<0.1, A p < 0.05, B p < 0.01, C p < 0.001.

Borg Dahl et al. Fine scale niche differentiation among myxamoebae (submitted 30.12.2017).

Total constrained variance: 29.6% a) 6_op_C b) 4_cl_B Total constrained variance: 43.0% Myxomycetes 4_op_C Stress: 0.25 Bacteria 4_cl_A Stress: 0.08 Inclination 4_cl_C 4_cl_A 6_cl_A 7_cl_C 6_cl_A Conifer forest 6_op_BConifer forest 4_cl_C

0.5 6_op_A 2_cl_A 7_op_B7_cl_C 0.5

) 1_cl_C 6_cl_C 6_cl_C ) Closed canopy2_cl_C 6_cl_B 1_cl_B 7_cl_A 6_cl_B 3_cl_C Clearing3_op_A 4_op_A 1_cl_A 2_op_A 4_op_C 2_cl_B 5_cl_A 3_cl_A 1_op_B North 5_cl_B 5_cl_B5_cl_C 8_cl_C 3_op_A2_op_B 5_cl_A Wood 2_cl_B Closed canopy 2_op_CWest 8_cl_B Herbal 5_cl_C Meadow North5_op_C 8_op_C

0.0 1_op_C3_op_CMixed forest 3_op_B Elevation 0.0 5_op_B

total variancetotal East 2_op_C2_op_B Wood Elevation 5_op_B5_op_A Shrub Open canopy Herbal

of 8_cl_A

of total varianceof total 8_op_A 1_cl_CWest 1_op_A Open canopy 2_cl_A1_cl_B Inclination Clearing 5_op_C2_cl_C Shrub 3_op_B 1_cl_A East 7_cl_A 4_op_B 8_cl_A Meadow (6.9% 8_op_B 6_op_A 7_op_A 3_cl_C 0.5 7_cl_B - 6_op_C 8_cl_B 2_op_A 7_op_B

0.5 3_op_C

- 8_op_C 8_cl_C RDA2 (5.9%RDA2 1_op_C 8_op_B RDA2 pH 7_op_C pH Mixed forest 1_op_A 3_cl_B 4_op_B 3_cl_A

-1.5 -1.0 -0.5 0.0 0.5 1.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 RDA1 (6.5% of total variance) RDA1 (21.3% of total variance)

c) Total constrained variance: 33.5% Table 4 Explained variance by the environmental parameters in the community composition Fungi 4_cl_A Inclination 3_cl_C Stress: 0.14 4_cl_B 2 3_cl_A4_op_C of myxomycetes, fungi and bacteria. Values correspond to % R value from Permanova on 0.5 Mixed forest Conifer forest Bray-Curtis dissimilarity matrix with 1 000 permutations. Ŧ p<0.1, * p < 0.05, ** p < 0.01, 3_cl_B4_cl_CClosed canopy 2_op_B2_cl_C 2_op_C West 2_cl_A *** p < 0.001. 6_op_A1_cl_B1_cl_C 3_op_A2_cl_B Elevation Clearing1_cl_A6_cl_BWood 7_cl_C 5_cl_C5_cl_BNorth 7_cl_A7_cl_B 5_cl_A 8_cl_C 5_op_A 6_cl_A 8_op_B Myxomycetes Fungi Bacteria 0.0 5_op_B4_op_B 8_cl_A8_cl_B8_op_C 6_op_B4_op_A Shrub 8_op_A 6_op_C 3_op_B Open canopy 7_op_B Elevation 2.9% 2.6% 2.3% Herbal 7_op_A East 7_op_C Ŧ

3_op_C pH 2.7% 2.7% 3.0% total variance)total

Canopy 3.0%Ŧ 2.7%Ŧ 3.8%Ŧ 0.5 - Vegetation type 10.3%*** 9.5%*** 11.8%** Meadow

(5.8% of (5.8% pH Plant type 0 0 0

Aspect 4.9% 4.8% 5.3% RDA2 RDA2

1.0 Inclination 2.3% 3.0%* 2.9% - 1_op_C 1_op_A 1_op_B Residual 73.9% 75.0% 70.8%

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 RDA1 (10.5% of total variance)

Figure 1 Redundancy analysis (RDA) ordination plots for the community of a) myxomycetes, b) bacteria and b) fungi. Categorical parameters represented by their centroid position. Continuous variables (elevation, inclination, pH) are indicated by arrows.

A modified Raup-Crick (RC) index independent of variation in alpha-diversity between samples, as provided by Chase et al. (2011), was used as an indication if any causal mechanism may have governed assembly for all or some of the three communities. The index calculates whether the observed dissimilarities across samples are higher or lower than those estimated from a random distribution (generated from 1 000 permutations); it ranges from –1 to 1. When assuming no dispersal limitation within the study area, values near –1 should point to a mass effect (homogenizing dispersal: less dissimilar than by random assembly), values near 0 should indicate drift (random assembly) and values near 1 should reveal environmental selection (more dissimilar than by random assembly). Figure 2a shows the RC index for the three communities compared within sample sites, within a vegetation type and between vegetation types. For bacteria and fungi, both the comparison within sample sites and within a vegetation type display a high level of homogenization of the communities between samples (index values largely at –1). Conversely, figures for comparisons between vegetation types, are found at either end of the index spectrum (–1 and +1), suggesting strong environmental selection between some sample pairs (+1) and homogenization (–1) between others (Fig. 2a). The myxomycetes show a less clear signal in all three categories, with a mostly homogenized distribution within sites (index values near –1), but a higher degree of random distribution within and between vegetation types.

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Fungi a) Sample site, n = 42 c)

Same vegetation, n = 144

Other vegetation, n = 804 **

Bacteria Sample site, n = 42

Same vegetation, n = 142

Other vegetation, n = 806

Myomycetes Sample site, n = 35

Same vegetation, n = 114 Bacteria_Herbal type Bacteria_Woody type Bacteria_Between type Other vegetation, n = 671 Myxomycetes_Herbal type Myxomycetes_Woody type Myxomycetes_Between type

-1.0 -0.5 0.0 0.5 1.0 Raup-Crick index of dissimilarity b) d) ***

Bacteria_Low pH (4.5 - 6.5)

Bacteria_Sample site Bacteria_Neutral pH (6.5 - 7.5) Bacteria_Same Vegetation Bacteria_Between pH type Bacteria_Other Vegetation Myxomycetes_Low pH (4.5 - 6.5) Myxomycetes_Sample site Myxomycetes_Same Vegetation Myxomycetes_Neutral pH (6.5 - 7.5) Myxomycetes_Other Vegetation Myxomycetes_Between pH type

-5.0 -2.5 0.0 2.5 -5.0 -2.5 0.0 2.5 SEMPD index of genetic distance SEMPD index of genetic distance Figure 2 Violin plots of a) Raup-Crick (RC) indices for myxomycete (red), fungal (yellow) and bacterial (blue) communities calculated for comparisons within a sample site (lightest colour), within a vegetation type (medium colour) and between vegetation types (dark colour). Index values at –1 indicate homogenizing dispersal, values near 0 drift (random) and values near 1 environmental selection as main underlying mechanisms for community assembly. b) Standardized effect size of the mean pairwise distances (SEMPD) within myxomycetes and bacteria shown for the same comparisons as in (a). c) SEMPD between samples when grouped by dominant plant type (‘woody’ or ‘herbal’). d) SEMPD between samples when grouped by low (4.5- 6.5) or neutral (6.5-7.5) pH. All distributions are shown as area plots, where the broadest part indicates the highest abundance. Significance is indicated as: ** p< 0.01, *** p< 0.001.

Supplementary to the OTU based community analysis, we identified whether the variance in beta diversity was phylogenetically preserved – and thus potentially governed by a common functional selection pressure – by calculating the standardized effect size of the mean pairwise genetic distance (SEMPD) between samples. Neither bacteria nor myxomycetes were found to show significantly lower phylogenetic distances between samples of the same site or vegetation type than expected by chance (null model, Fig. 2b). However, genetic distances between samples grouped by plant type and

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pH were found to be lower for bacteria in samples with low pH and where woody plants dominated (Fig. 2c-d). For myxomycetes a tendency for lower genetic distance in the samples originating from ‘open canopy’ systems was seen (p = 0.11, see suppl. S3).

Community composition Figure 3 presents a heatmap of the most dominant OTUs from each vegetation type. For bacteria these belong to the phyla Acidobacteria, Actinobacteria, Bacterioides, Firmicutes, Proteobacteria and Verrucomicrobia. Fungal OTUs were mostly assigned to taxa from Ascomycota (Archaeorhizomycetes, Dothideomycetes, Leotiomycetes, Sordariomycetes and Leotiomycetes), Basidiomycota (Agaricomycetes and Tremellomycetes) and Zygomycota (Mortierellomycotina).

Meadow (M) Clearing (C) Conifer forest (CF) Mixed forest (MF) Shrub (S) Uncl. Acidobacteria Gp2 OTU93 Uncl. Actinomycetales OTU9 Uncl. Bacillales OTU13 Uncl. Rhizobiales OTU2 Uncl. Alphaproteobacteria OTU1633 Uncl. Alphaproteobacteria OTU150 Uncl. Acidobacteria Gp3 OTU34 Uncl. Chitinophagaceae OTU5 Uncl. Rhizobiales OTU1 Uncl. Betaproteobacteria OTU152 Uncl. Betaproteobacteria OTU188 Uncl. Spartobacteria OTU20 Uncl. Spartobacteria OTU58 Uncl. Bacteroidetes OTU2187 Uncl. Bacteroidetes OTU695 Bacteria Uncl. Bacteroidetes OTU1649 Uncl. Bacteria OTU648 Uncl. Nitrospira OTU50 Uncl. Spartobacteria OTU6 Uncl. Alphaproteobacteria OTU8 Uncl. Proteobacteria OTU270 Uncl. Alphaproteobacteria OTU37 Uncl. Acidobacteria Gp6 OTU519 Uncl. Bacteria OTU14 Uncl. Archaeorhizomyces OTU2107468 Uncl. Archaeorhizomyces OTU997718 Uncl. Archaeorhizomycetes OTU2486022 Uncl. Agaricomycetes OTU541706 Uncl. Cantharellales OTU2530056 Uncl. Helotiales OTU747475 Uncl. Ascomycota OTU1147840 Cryptococcus terricola OTU1222223 Amphinema byssoides OTU12 Uncl. Hysteriales OTU660380 Uncl. Ascomycota OTU401 Uncl. Archaeorhizomyces OTU1275829 Uncl. Mortierella OTU57813 Uncl. Cenococcum OTU497994 Uncl. Russulaceae OTU321924 Uncl. Russulaceae OTU117463 Uncl. Sebacinaceae OTU101 Uncl. Basidiomycota OTU56520 Uncl. Sebacinaceae OTU1349823

Fungi Uncl. Agaricales OTU644755 Uncl. Russula OTU985510 Uncl. Pyronemataceae OTU827759 Uncl. Sordariomycetes OTU153045 Uncl. Pleosporales OTU136349 Uncl. Ascomycota OTU209061 Uncl. Ascomycota OTU517289 Uncl. Pezizales OTU640706 Uncl. Ascomycota OTU793565 Uncl. Agaricales OTU2005931 Uncl. Basidiomycota OTU1282942 Uncl. Russulales OTU1541985 Uncl. Archaeorhizomycetales OTU2385447 Uncl. Fungi OTU2087590 Uncl. Xylariales OTU2087466 Uncl. Helotiales OTU949082 CAU RU OTU52 (Lamproderma) Diderma microcarpum OTU12 Meriderma echinulatum OTU46 Meriderma OTU4 Meriderma OTU29 Lamproderma echinosporum OTU65 Lamproderma pulveratum OTU18 Meriderma OTU45 CAU RU OTU20 (Unknown) Lamproderma piriforme OTU62 Meriderma OTU118 Didymium OTU9 NoID OTU168 (Meriderma) Physarum albescens a OTU8 NoID OTU14 (Lamproderma) Lamproderma arcyrioides OTU60 Didymium OTU48 CAU RU OTU225 (Unknown) CAU RU OTU496 (Unknown)

Myxomycetes NoID OTU1 (Lamproderma) NoID OTU26 (Lamproderma) NoID OTU76 (Lamproderma) NoID OTU11 (Lamproderma) CAU RU OTU180 (Lamproderma) Lamproderma retirugisporum OTU107 NoID OTU164 (Diderma) CAU RU OTU230 (Lamproderma) Diderma meyerae OTU75 Lamproderma retirugisporum OTU376

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Figure 3 Stacked heatmap of the log-transformed Bray-Curtis distance of the most abundant OTUs from each vegetation type of each community, representing 18% (bacteria), 18% (fungi) and 48% (myxomycetes) of the total community. Red colours indicate relatively high abundance, blue colours indicate relatively low abundance for a given OTU across samples. OTUs with similar distribution pattern across samples are clustered and the matrix is constrained by sample order (sample ID given at the bottom). Vegetation types are sorted according to similarity and separated by spacers. Taxonomic classification and OTU ID are given at the right side. Myxomycete OTUs with no match to our database have been assigned (in parentheses) to the closest genus based on the phylogenetic tree in Suppl. S1. From the heatmap it is evident that samples of the vegetation types ‘clearing’ (C) and ‘conifer forest’ (CF) have a less clear signature than the other vegetation types, and that they share a similar community composition. Furthermore, these samples share their community with both those from vegetation types dominated by herbs (M) and by woody plants (MF, S). In forests and shrub thickets root associated bacteria such as Rhizobiales and the cellulose degrading Chitinophagaceae (Bailey et al., 2013) are dominant. In meadows and clearings (C, M) the nitrite-oxidizing bacterial genus Nitrospira dominates as well as several members of the free living fungal saprotrophs of the class Sordariomycetes. Finally, members of the EM fungal family Russulaceae are dominant in all but the shrubby (S) sites, where root associated fungi of the Archaeorhizomycetes, are dominant.

For myxomycetes many of the dominant OTUs could not be annotated to a taxon in the reference database, but approximately half of these OTUs matched previously published environmental sequences. Within the taxonomically annotated OTUs species of the genera Diderma, Lamproderma and Meriderma are dominant, as well as a few species of Didymium and a single species of Physarum (P. albescens), the latter being exclusively found at high elevations in plots with shrubby (S) vegetation. The majority of the myxomycete OTUs show a ‘hot spot’ distribution with high abundance in a few samples (e.g. Diderma microcarpum, Lamproderma arcyrioides and P. albescens). Exceptions are OTU18 (Lamproderma pulveratum) and OTU52 (an unknown ‘Caucasus’ sequence), which are found in high abundance in a large number of samples representing all vegetation types. OTUs assigned to Meriderma are dominant in mixed forests (MF) and are found to be significantly more abundant in sites with woody plants (p= 0.03). OTUs assigned to members of Lamproderma did not show clear patterns, although unassigned OTUs which cluster close to this genus Lamproderma are dominant at wet natural meadows (M, Fig. 3). Furthermore, several genera (Diachea, Diachaopsis and Physarum) occur almost exclusively at the upper part of the transect corresponding to shrubby (S) vegetation.

Functional changes Ectomycorrhizal (EM) fungi were significantly more abundant in forests and scrublands (CF, MF, S: 74.6% of all classified EM reads, p< 0.05), with the highest abundance (38.6% of all classified EM reads) at the mixed forests (MF). Saprotroph and arbuscular (AM) fungi were not found to be affected by the vegetation types (p = 0.19). For bacteria there was a significant increase in gram positive bacteria towards the top of the transect (S sites), where relative abundance increased from 10 ± 1% at 1 200 to 1 700 m elevation to 27 ± 3% at 1 800 to 1 900 m elevation (p = 0.006). Of the annotated myxomycete OTUs 82% belonged to nivicolous species, while 15% belonged to non- nivicolous species (known to fruit in summer and/or autumn). Neither the total number of nivicolous nor non-nivicolous species per site were correlated to one of the environmental parameters.

Co-occurrence patterns and microbial interactions Species assembly of the myxomycete community was weakly correlated with that of both the bacterial and fungal community, showing Mantels correlation coefficients of 0.17 and 0.20, respectively (p < 0.001). The bacterial and fungal communities were stronger correlated with each other (Mantel test = 0.38, p < 0.001). However, the alpha-diversity of myxomycetes was strongly

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correlated with the alpha-diversity of both bacteria and fungi (Pearson’s R2 = 0.51, p= 0.002 and R2 = 0.58, p <0.001 respectively). This relationship was still present after omitting the top elevation samples, which had significantly fewer OTUs of both myxomycetes and bacteria (R2 = 0.44, p= 0.02 and R2 = 0.47, p = 0.01 respectively); results are summarized in Table 5.

Table 5 Correlation coefficients between communities (Mantel) and alpha-diversity (Pearson's) of myxomycetes, fungi and bacteria for community composition / total alpha-diversity / alpha-diversity (minus samples at top elevation). Significance levels: A p < 0.05, B p < 0.01, C p < 0.001.

Bacteria Fungi C B A C C A Myxomycetes 0.17 / 0.51 / 0.44 0.20 / 0.58 / 0.47 C C A Fungi 0.38 / 0.54 / 0.37 -

Two taxa of two different myxomycete genera (Lamproderma arcyroides and Meriderma carestiae) were chosen (based on their high frequency and total abundance) for interaction calculations between them and bacteria applying the algorithm for calculating a global interaction coefficient by Shang et al. (2017). Figure 4 shows an interaction network calculated for three taxonomic levels in bacteria (phylum, order and family). At phylum level (bold font) only a positive interaction between L. arcyrioides and the Firmicutes is seen together with a weak negative interaction with Betaproteobacteria (the phylum Proteobacteria is represented by the two classes Alpha- and Betaproteobacteria). At order level (regular font), it becomes evident that the positive interaction with Firmicutes is driven by an interaction with members of the Basiliales, further positive interactions with Sphingobacteriales is seen. At family level (small font), a strong positive interaction is found between L. arcyrioides and the family Nakamurellaceae (Actinobacteria) as well as Mycobacteriaceae (Actinobacteria) but also negative interactions to members of the Actinobacteria are seen with Micromonosporaceae and Microbacteriaceae. Only a weak negative interaction between M. carestiae and Nakamurellaceae is identified. In addition, no interactions were found between L. arcyrioides and M. carestiae and any fungal taxa.

Figure 4 Network representing the interaction Nitrospirae between the two myxomycete species Lamproderma arcyrioides and Meriderma carestiae and bacteria. Only the most abundant (see text) taxa are included, thus 67.0%, 21.7% and 7.3% of the Lamproderma arcyrioides

bacterial community are 5 represented at phylum (bold Meriderma carestiae font), order (regular font) and family (small font) level respectively. Gram+ (light grey) and Gram– (dark grey) is indicated. Positive (red) and negative (blue) interactions are indicated as well as the direction (arrowhead) and strength (relative thickness of line) of the interaction. 76

Borg Dahl et al. Fine scale niche differentiation among myxamoebae (submitted 30.12.2017).

DISCUSSION

As predators of other microorganisms myxomycete amoebae are among the key players in soil ecosystems and are certainly abundant (Urich et al., 2008), but so far very few studies have focused on these organisms. Three studies targeting soil-inhabiting amoebae of dark-spored myxomycetes have been reported: An RNA-based study employing cloning investigated myxamoeba from alpine soils from three (France, Scotland and Japan) mountain sites (Kamono et al., 2012) and two DNA- based study employing Illumina metabarcoding investigated 1) lowland soils from three German regions (Fiore-Donno et al., 2016) and 2) soils from the Caucasus mountains (Borg Dahl et al., 2017a). All studies report highly site specific community compositions at regional/global scale. As a novelty, this study investigates the distribution of myxomycetes at a small geographical scale, while simultaneously assessing the diversity of fungi and bacteria, and asks for interdependencies between the three communities.

Drivers of community composition The specific sample site accounted for the largest proportion of community variance for all three communities, which may be explained by autocorrelation in community compositions, as it was reported for soil amoeba at distances up to six meters in a temperate forest (Bahram et al., 2015), and up to more than a 100 meters for soil bacteria (King et al., 2010) and rotifers (Robeson et al., 2011). Furthermore, the growth form of the fungal mycelia (Finlay and Read, 1986), might potentially cause a resampling of the same individual (overlapping mycelium), resulting in the very strong homogenization within sites as seen for fungi (RC index approaching –1, Fig. 3a).

Among the tested environmental parameters, vegetation type was found to be the strongest explanatory parameter of the community variation for all three communities. As the five vegetation types are to some extent spatially spread along the transect (see Table 3 and suppl. S4), all three microbial groups seem not to be severely dispersal limited within the study area, which is in accordance with our assumptions.

However, not all vegetation types seem to reflect the true niche boundaries of the microbes. This is evident from the heatmap, where especially the clearing (C) and conifer forest (CF) cannot be easily distinguished from each other. In addition the RC index for between vegetation comparisons, finds an equally large fraction to cluster at either ends of the spectrum (–1 or +1) for fungi and bacteria (no pattern emerges for myxomycetes). This indicates overlap in the community composition between sites of different vegetation types. Sample sites classified as clearings (C) represent a semi- natural environment, occurring as a result of deforestation. Both root debris and left tree trunks might affect the microbial community at these sites to resemble that of conifer forests (CF), potentially driven by a similar selection based on the comparable plant substrates available for decomposition (Figs. 2c and 3). In addition, conifer forests (CF) share communities with natural meadows (M), possibly explained by the grassy understorey found in the subalpine light coniferous forests (suppl. S4 and Fig. 3). Finally, a strong link in alpha-diversity between all three communities across sample site was observed, suggesting that environmental parameters (e.g. soil moisture, nutrient availability etc.) not captured in this study facilitate high or low diversity across communities.

Similar niche differentiation for primary decomposers and symbiont species Not surprisingly, differences in bacterial and fungal communities between vegetation types are mainly driven by the relative abundance of symbiontic species, such as ectomycorrhizal (Russulaceae) and root-associated fungi (Helotiales, Tedersoo et al., 2009) or root-associated bacteria (Rhizobiales and 77

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Nitrospira). This is in line with the ecology of these species (Finlay 2008; van der Heijden et al., 2008) and the well-known strong link between these and vascular plants (Wardle et al., 2004; van der Putten et al., 2013). Beside the direct link via symbiontic species, both bacteria and fungi are indirectly affected by the vegetation, as they are both primary decomposers of plant material. Debris from woody plants can be expected to be more recalcitrant to decay than debris from herbs (Wardle et al., 2004). Specialized degradation of recalcitrant compounds is known to be phylogenetically preserved (Boer et al., 2005; Kohler et al., 2015), likely due to the complexity of such traits (Martiny et al., 2015). In accordance a lower genetic distance between members of bacterial communities of forests and shrubby sites was observed (similarly for sites with low pH, as typically for conifer forests), suggesting environmental selection for phylogenetically conserved traits (Fig. 2c-d). In accordance, members of Bacteroidetes were among the dominant bacteria at sites dominated by herbs, whereas members of Acidobacteria dominate the forests and shrubs (Fig. 3). These taxa have been shown to inversely correlate with soil carbon mineralization rates across ecosystems (Fierer et al., 2007; Philippot et al., 2009; de Vries et al., 2012). An exception are members of the Acidobacteria Gp6 which in accordance with our results Naether et al., (2012) found to be dominant in grasslands. Thus, the dominant bacterial groups seem to reflect differences in quality of organic remnants derived from the prevailing plant types at the sampling sites. Among the fungi Basidiomycetes account for the lion’s share of lignin degradation in soil (the ‘white root’ fungi, Boer et al., 2005) and include most ectomycorrhizal fungal linages, which are colonizing woody plants (Taylor and Alexander, 2005; Finlay, 2008). In accordance, Basidiomycetes are found significantly more abundant in the ‘woody’ sites. As free living saprotrophs and member of the Ascomycetes, the Xylariales with their ability to degrade lignin are an exception (Osono and Takeda, 2002). Their dominance in meadows and clearing sites therefore suggests a functional redundancy in the fungal communities of herb-dominated (M, C) sites and those dominated by woody plants (MF, CF, S). This suggests that selection for fungal species, is more likely driven by specific plant associations – i.e. selection for symbiont species – than by debris quality. This is in line with other studies showing plant community as a strong structuring parameter for fungal community composition (Peay et al., 2013; Mueller et al., 2014), due to direct plant-fungal interaction and the ability of plants to control fungal metabolic activity through root exudates (Högberg et al., 2001; Högberg and Read, 2006; Chagnon et al., 2013). In contrast, myxomycetes are not known to be either symbiotic nor parasitic in respect to plants (Schnittler et al., 2012), although myxamoebae were recovered from cultures of wood from living trees (Taylor et al., 2015). However, algae have been suggested as an overlooked food source for several phagotrophic protists (Seppey et al., 2017) and the relative longevity of some green algae (Lazo, 1961) and members of Enterobacteriales bacteria (Venkataramani and Daniel, 1987) engulfed by myxomycete plasmodia may point to at least temporary symbioses between myxomycetes and certain food organisms.

Myxomycete niche differentiation and interactions Although 10.3% of the community variance in myxomycetes was explained by vegetation type, the communities within vegetation types are much less clearly homogenized for myxomycetes than for bacteria and fungi (Fig. 3a). Fungal and bacterial community seems to be affected by similar environmental parameters and thus experience similar selection pressures, as indicated by the correlation between the sample similarities in the two communities (correlation coefficient 0.4). On the contrary neither the bacterial nor fungal community are highly correlated to the myxomycetes community (correlation coefficient 0.2). This is in contrast to Lanzén et al., (2016) who found that the community of ‘protists’ (generated from general eukaryotic primers, which do not amplify myxomycetes) correlated strongly with the fungal community along an elevational gradient in the Pyrenees similar to the gradient in our study. The protist community in this study was dominated by

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Cercozoa, Ciliophoa and a number of parasitic linages, which differ in lifestyle from the myxomycetes. However, several Cercozoa have been found to exhibit specific food preferences and be linked to the distribution of their prey (Adl and Gupta, 2006; Hess et al., 2012; Geisen et al., 2015a). We observe a clear differentiation in the occurrence of some myxomycete genera, especially the dominant genus Meriderma, which exhibited a clear preference for forested sites. However, no interactions between the case species M. carestiae and bacteria or fungi was identified, supporting the argument that co-occurrence cannot be taken to imply interaction (Faust and Raes, 2012; Shang et al., 2017).

In contrast, the myxomycete Lamproderma arcyrioides (a genus not closely related to Meriderma, Fiore-Donno et al., 2012) seems to have clear associations with bacterial taxa that are consistent across different taxonomic resolution. The strongest positive interactions were found for Bacilliales (Firmicutes) as well as the Nakamurellaceae (Actinobacteria), both gram positive bacterial taxa. Furthermore, we found a positive interaction to Sphingobacteriales, an order of Bacteroidetes. This is in strong accordance with a study of Rosenberg et al. (2009), who reported Firmicutes and Bacteroidetes to be preferred by the soil amoeba Acanthamoeba castellanii. Also Hünninghaus et al. (2017) found A. castellanii to have a clear grazing preference for gram positive bacteria and finally Shang et al. (2017) reported a positive interaction between Myxomycetes and Actinobacteria across 150 grassland samples. In our case both positive and negative interactions between members of the Actinomycetales and L. arcyrioides are seen, which likely mask a general interaction coefficient at higher taxonomic levels (phyla or orders). These results generally contradict studies reporting gram positive bacteria as less digestible for amoebae than gram negative ones due to their cell wall structure (Taylor and Berger, 1976; Iriberri et al., 1994; Rønn et al., 2002). Murase et al. (2006) found the gram positive taxa Bacillus and Clostridia sp. to be favoured by grazing protists (mainly Cercozoa). Both myxomycetes and acanthamoebae belong to the super-group Amoebozoa whereas Cercozoa are members of the super-group Rhizaria (Pawlowski and Burki, 2009). Both groups include numerous species that are common in soil, which could suggest niche differentiation between these protistean groups in relation to grazing preferences. However, predatory soil protists as well as Firmicutes and Actinobacteria (both among the most species-rich phyla of bacteria) all include a large variety of lifestyles and occupy different ecological niches (Churchman, 2015). Finally, some Bacillus species have been shown to be directly harmful for and to strongly reduce the abundance of members of both Amoebozoa and Rhizaria (Xiong et al., 2017). Thus general patterns at such coarse classification levels may not exist, as also indicated by the both positive and negative interactions found in this study between the myxomycete L. arcyrioides and members of the Actinomycetales. No interactions were found between the myxomycete taxa and any fungal taxa (data not shown) which is in line with the assumption that bacteria serves as the main food source for myxomycetes(Stephenson and Feest, 2012; Tiunov et al., 2015).

Adaption to harsh environments All three investigated communities showed a clear turnover towards the upper part of the transect (sites 7 and 8, open alpine meadows with shrub tickets, vegetation type S), and alpha diversity decreased for both bacteria and myxomycetes. The relative abundance of gram positive bacteria increased, driven by an increase in the abundance of unclassified members of Actinomycetales and Firmicutes (orders Bacillales and Clostridiales). The latter are capable of entering dormant spore stages and can thus prevail in frozen environments and proliferate during the summer season (Lazzaro et al., 2015). Many members of both Firmicutes and Actinomycetales are slow-growing recalcitrant carbon recyclers (Goodfellow and Williams, 1983; Deslippe et al., 2012), which is reported to be an evolutionary trade-off for the need of labile nitrogen to support the cost of extracellular enzymes (Treseder et al., 2011). As nitrogen limitation typically increases with altitude, 79

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the abundance of gram positive bacteria decreases (Margesin and Miteva, 2011; Whitaker et al., 2014). Our results thus contradict previous studies. No chemical analysis of soils were made for this study, however if available nitrogen is the issue, one could speculate that a potential source is both artificial snow and salts used for commercial skiing, which have been reported to have both direct and indirect consequences for soil chemistry, including nitrogen availability (Rixen et al., 2003; Roux- Fouillet et al., 2011). In spite of the general trend of decreasing alpha-diversity with increasing elevation, some myxomycete OTUs are restricted to the upper part of the transect. These are members of the genera Diachea (D. subsessilis) and Diacheopsis (D. metallica) along with species of Diderma (D. alpinum, D. fallax and D. microcarpum) and Physarum (P. albescens). Nivicolous myxomycetes as a group should be well adapted to the environmental stressors found in alpine regions. For example, white calcareous outer or iridescent membranous peridia should reflect or scatter UV radiation, likewise nivicolous species possess often very dark (strongly melanised) and large spores (Lado, 2004). Of the observed OTUs which were assignable to species, all but D. subsessilis are known as ‘strictly’ nivicolous species (Ronikier and Ronikier 2009). However, Kamono et al. (2013) found as well OTUs assignable to D. subsessilis present in alpine soil. They suggested that amoebae of this litter-inhabiting species might live in alpine soils but not undergo fruiting (and will thus never be recorded), referring to studies of amoebal growth in for example liquid environments where fruiting is not possible (Dyková et al., 2007). Although the existence of a hitherto unknown and closely related taxon cannot be ruled out, our finding of D. subsessilis at the upper most part of the transect where it has never been reported to fruit (Schnittler unpubl.), supports the possible presence of lowland species as non-fruiting amoebal populations in alpine environments.

For fungal species, diversity does not clearly decrease towards the top of the transect, but a turnover is visible: species of Russulaceae, which is the largest ectomycorrhizal fungal family with adaptation to a broad range of plants (Brundrett, 2002) are common all over the transect except at the top. Here, members of the root associated fungal linage Archaeorhizomycetes (Rosling et al., 2011) become dominant. In accordance with this study, a mutually excluding relationship between these two fungal linages was recently reported in a meta-study targeting the distribution of Archaeorhizomycetes in a broad range of soil types (Choma et al., 2016). In addition, these authors found Archaeorhizomycetes to have the highest relative abundance in ‘scrubland’ and to be presumably unaffected by heavy metal stressors. Other studies have found Archaeorhizomycetes to be dominant in tundra soils (Schadt et al., 2003; Lanzén et al., 2016, Borg Dahl et al., 2017b); together with our results this indicates that these fungi are indeed adapted to environmental stress (cold temperatures and increased concentrations of heavy metals).

Highly abundant unknown myxomycetes? Interestingly, 31.1% (80 of 257) of all unknown myxomycete OTUs (no match to our reference database, dissimilarity > 5%, Borg Dahl et al., 2017a) were assigned with an average match of 97.4 ± 1.3% to other unknown sequences from one or both of the two previously published ePCR datasets targeting myxomycetes with comparable SSU markers (Fiore-Donno et al., 2016; Borg Dahl et al., 2017a). This indicates that these sequences indeed belong to myxomycetes (Fiore-Donno et al., 2016 used a different primer pair, making the risk of them being an artefact negligible). Second, it lends evidence to the existence of several genetically highly distinct (bootstrap support >95%) and abundant linages, which are currently not represented by sequences from fruit bodies (Suppl. S1). The majority of the unknown OTUs cluster in close proximity to sequences from Lamproderma spp., a genus well represented in the reference database. This pattern is highly consistent with the phylogenetic tree reported by Fiore-Donno et al. (2016); these authors found numerous unknown OTUs similar to L. scintillans and L. echinosporum. Their OTUs are not identical but very close to the 80

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ones found by us, and occurred as well mostly in grassland. A good example in our study is OTU1, which is highly abundant and occurs primarily in samples from clearing and meadow sites (Fig. 3), assuming a phylogenetic position being closest to L. aeneum. Although difficult for nivicolous species (Shchepin et al., 2014), cultivation should be attempted to disentangle these genetic clusters further.

In summary, our parallel study on three major groups of soil microbes suggest that the fungal community is mainly determined by vegetation features, which also structure the bacterial community indirectly via quality of organic plant debris and soil pH. Though myxomycetes showed a much less structured and more patchy distribution, vegetation was found to be a main explanatory variable for their community composition as well, indicating a clear niche differentiation, which could be a response to both structural properties of the habitat and specific bacterial taxa. All communities show some kind of elevational turnover, which was interpreted as an adaptation to harsh environments. Finally, we report a high number of unknown myxomycete OTUs forming taxonomic clades especially within the genus of Lamproderma, which might represent novel species which may rarely or never fruit.

METHODS

Study area and sample collections The study area is an east exposed transect in the Kreuzjoch region below the Alpspitz summit near Garmisch-Partenkirchen in the German limestone Alps, reaching from the Bayernhaus (47°27’55” N, 11°12'40” E, ca. 1 200 m a.s.l.) to the Osterfelder Kopf (47°26’20” N, 11°03'00” E, ca. 2 050 m a.s.l.). This transect was surveyed for nivicolous myxomycetes in spring 2013, 2015, 2016 and 2017. The area is affected by skiing activities during winter and cattle grazing in summer, resulting in a semi- natural vegetation cover, due to fragmentation and clearings. The lowermost parts of the transect supported mixed forests (MF) with beech (Fagus sylvatica L.), fir (Abies alba Mill.) and spruce (Picea abies (L.) H. Karst.); with increasing elevation the two former species gradually drop out, and from 1 400 m onwards spruce dominates (conifer forest, CF). The timberline is reached at ca. 1 700 m, and forests give place to shrub (S) thickets composed of Pinus mugo Turra, Alnus alnobetula (Ehrh) K. Koch (= A. viridis (Chaix) DC.) and Sorbus aucuparia L. Open grasslands occur at all elevations, either as small natural wet meadows (M) or semi-natural pastures in the forest belt, where trees have been cut (clearings, C). In places with wet soil and/or strongly affected by cattle grazing, broadleaved forbs (Rumex alpinus L., Senecio alpinus (L.) Scop.) dominate. Sites at every 100 m elevation were carefully chosen not to be directly influenced by the maintenance of the ski tracks. To cover the full range of potential habitats along the transect pairs of open (op) and closed (cl) canopy sites were selected at each elevation level, resulting in 16 sites. Characteristics of the sample sites are summarized in Table 3 (for map and images of the sites see suppl. S4).

Soil samples were collected at June 1, 2016 from each site in three biological replicates approximately 10 meters apart from each other. For each of the 48 samples, four teaspoons of soils (~ 20 g) from the upper most soil layer (excluding litter) were collected within 1m2 and pooled in order to mitigate any fine scale spatial distribution at the site (Franklin and Mills 2003; Adl and Gupta 2006). The samples were kept cool at fridge temperature (approx. 5°C) for four days (during fieldwork and transportation), to mimic natural conditions and avoid further disturbance of the microbial community (like freezing, thawing or heating) before processing. In addition pH was measured and the aspect and inclination of the slope per site were registered using GPS status & toolbox (MobiWIA) application for smartphone.

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DNA extraction, amplification and sequencing Soil samples were homogenized by hand and 0.25g were transferred to a 96 well-plate and lysed using the PowerMag® Soil DNA Isolation Kit optimized for epMotion® (MO-BIO Laboratories, Inc., Carlsberg, CA, USA) using the epMotion robotic platform model (Eppendorf) according to the manufactures protocol.

PCR amplifications were done in two steps for each target community: myxomycetes, fungi and bacteria (see suppl. S5 for list of primers and target gene markers). All reactions were run in 25 µL reaction volume, using HiFi polymerase (PCR Biosystems, London, UK). The PCR conditions were 94°C for 2 min; in 33 or 16 cycles of 94°C for 30 s, 57°C for 30 s, 72°C for 30 s, followed by 72°C for 5min, for PCR-I and PCR-II respectively. Two µl of PCR-I product was used as template for PCR- II. Amplicons were purified using AMPure ® XP Beads and the DNA concentration was normalized using SequalPrepTM normalization plates (Thermo Fisher Scientific, Harris et al., 2010). Paired-end sequencing was performed on an Illumina MiSeqTM platform (Illumina Inc.) at the Section for Microbial Molecular Ecology, University of Copenhagen (Denmark). Illumina raw-files are available from NCBI (BioProject ID: PRJNA418896).

A mock community consisting of equimolar amounts of amplicons from fruit bodies of 15 species of nivicolous myxomycetes was included in the sequencing run in three technical replicates, using three different tag indexes. PCR products were generated as described above. After PCR-I the amplicon products were purified (AMPure XP Beads, Beckman Coulter, Indiana, USA), quantified (Qubit fluorometer, Invitrogen, Californien, USA) and pooled in aliquot amounts (6.5ng/µL) before adding the individual tag-primers in PCR-II. The DNA read abundance between replicates was consistent, thus comparisons between samples should provide reliable information (See suppl. S6).

Bioinformatic processing Samples which had failed to amplify or only amplified one OTU were excluded, this applied to three samples for each fungi and bacteria, and seven samples for myxomycetes (see suppl. S2). For each targeted community (myxomycetes, bacteria and fungi), sequences were trimmed of primer sequences and barcodes and assembled using Usearch v.9.0.2132 (Edgar, 2010). Sequences which could not be assembled, singletons, chimeras and sequences with a quality score less than 25 were discarded. Sequences were denoised to generate OTUs, hereafter all raw reads were mapped back to generate abundance tables, as recommended by Edgar and Flyvbjerg (2014). The 16S and ITS sequences were mapped back with a 97% similarity threshold and were classified using the SILVA (Pruesse et al., 2007) and UNITE (Abarenkov et al., 2010) database, respectively. Only taxonomic annotations with a 90% confidence estimate as provided by the ‘utax’-command were accepted (Edgar, 2016).

For the myxomycetes a new pipeline was created. First, the recently identified 99.1% similarity threshold (Borg Dahl et al., 2017a) was used to generate the OTU abundance table. Myxomycete OTUs were taxonomically assigned using a custom reference database (Borg Dahl et al., 2017a). OTUs with a match score ≥ 98.0% were annotated to morphospecies (the acceptance threshold for taxonomic annotation was set slightly lower than the threshold for OTU picking, due to the undoubtedly incomplete cover of genotypes within morphospecies in our database, see Borg Dahl et al., 2017a). Furthermore, OTUs with match scores between 95% and 98% were assinged to the most similar myxomycete genus. Finally, sequences with no match by these criteria were assigned ‘No ID’. All ‘No ID’ OTUs (340) were aligned against previously published ePCR datasets targeting myxomycetes in soil with the same or an alignable SSU marker as in our study, from 1) a mountain ridge in the northern Caucasus (Borg Dahl et al., 2017a, same marker) and 2) a grassland study in Germany (Fiore-Donno et al., 2016, alignable marker), and annotated (‘ePCR CAU’ or ‘ePCR DE’ 82

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respectively) when matches were ≥ 95% similar. Sequences were aligned using the online tool MAFFT (Katoh et al., 2002) with the FFT-NS-I algorithm (iterative refinement method). A small proportion of OTUs (0.6%, 76 sequences) showed poor alignment and was excluded, assumed to be of non-myxomycetes origin (see discussion, all OTU tables are available from suppl. S7). The most abundant OTUs (> 200 reads) were used to build a Maximum-Likelihood (ML) phylogenetic tree in MEGA6 (Tamura et al., 2013) with 1 000 bootstraps (suppl. S1).

Data analysis

Effects of environmental parameters The explanatory power of the environmental parameters on community composition was tested with PERMANOVAs (permutational multivariate analysis of variance) performed on Bray-Curtis (BC) dissimilarity matrixes with 1 000 permutations using the ‘adonis2’ function with the setting ‘by = margin’ from the R package ‘vegan’ (Oksanen et al., 2017). Included parameters (see Table 3) comprised: elevation, inclination, exposition, pH, canopy type (open or closed), plant type (herbal or woody) and vegetation type (meadow, clearing, mixed forest, conifer forest, shrub). The total explained variance by the environmental parameters for each organism was obtained with the setting ‘by = null’ in the ‘adonis2’ function. In addition, RDA ordinations (redundancy analyses) were carried out for graphical presentation. The BC dissimilarities of the three communities were tested for correlation with a Mantel test (Kendall's rank correlation tau) as well as for their alpha-diversities (Pearson’s R). Correlation between the distribution of functional groups in fungi (free living saprotroph, arbuscular- and ectomycorrhizal lifestyle, classification adapted from Tedersoo et al. (2014), see suppl. S8) and bacteria (gram+ or gram- classification, see suppl. S8) were tested among the environmental parameters using a Kruskal-Wallis test.

To identify if any causal mechanism governs assembly for each of the three communities a modified Raup-Crick (RC) index independent of variation in alpha-diversity between samples (Chase et al., 2011) was calculated. For this, the datasets were rarefied to the lowest number of reads recorded for each community: 5 527, 31 165 and 8 666 reads for bacteria (16S), fungi (ITS) and myxomycetes (18S) respectively (see suppl. S9 for calculation script).

To see if variance in beta diversity was phylogenetically preserved, mean pairwise genetic distances (MPD) between samples were calculated using the ‘ses.comdist’ function from the R package ‘MicEco’ (Russel, 2016). Phylogenetic distances were obtained from MAFFT alignments (see above). This was only possible for myxomycetes and bacteria; for fungi the high variance in the ITS marker hampered the construction of a phylogenetic tree. Similar to the RC index, the method calculates the MPD between pairwise samples by generating a random null model (from 1 000 permutations) and calculate the standardized effect size (SEMPD) as: Observed MPD between communities - Mean MPD between null communities / Standard deviation of MPD between null communities. MPD was weighted in accordance to OTU abundance. Whether the genetic distance in groups of samples were significantly different from the overall mean was tested using ‘ses.permtest’ (MicEco) with 1 000 permutations and p-values ‘fdr’ corrected (false discovery rate, Benjamini and Hochberg, 1995).

For graphic presentation of the community and the environmental parameters RDA ordinations and heatmaps were generated. For the heatmap the eight most abundant OTUs, with presence in minimum half of the samples from a given vegetation type was picked, and duplicates removed (one OTU could be the most abundant in several vegetation types). Data were log transformed before z- scores were calculated. OTUs with similar distribution patterns across samples were identified by hierarchical clustering of a Bray-Curtis distance matrix constrained by sample order, using the ‘coniss’ clustering method from the R package ‘vegan’ (Oksanen et al., 2017). 83

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All statistical calculations were performed in R v. 3.3.3 (R Core Team 2013) using mainly the packages ‘vegan’ (Oksanen et al., 2017), ‘phyloseq’ (McMurdie and Holmes, 2013), ‘ecodist’ (Goslee et al., 2007) and ‘MicEco’ (Russel, 2016). Graphics were made using ‘heatmap.plus’ (Allen Day, 2012) and ‘ggplot2’ (Wickham, 2009). Analysis scripts are provided in suppl. S9 and raw results in S3.

Microbial interaction Global interaction coefficients between bacterial taxa and two myxomycete taxa (Lamproderma arcyroides and Meriderma carestiae) were calculated by applying the algorithm by Shang et al. (2017). The myxomycete taxa were chosen based on their high frequency and total abundance. The coefficient was calculated for the bacterial community summarized ascendingly from phyla to family level, including only taxa present in more than half of the samples and being among the 50 (phyla) or 25 (order and family) percentile with the highest total abundance at a given taxonomic level. The same analysis was carried out for fungi. Interaction coefficients were standardized by scaling to the largest interaction found.

ACKNOWLEDGEMENT MD thanks Dr. Martin Steen Mortensen for assistance with the robot soil extraction and Luma George Odish for laboratorial assistance in preparation of the Illumina library. Dr. Samuel Jacquiod helped with advice and assistance for the statistical calculations. We also thank Stefan Kellerer and Klaus Kellner, the wardens of the Tröglhütte of the DAV (Deutscher Alpenverein), for making our stay at the field site pleasant. We wish to express a general gratitude to researchers for sharing their data and programming codes as well as engaging in online discussion forums (particularly Stack Overflow), which has greatly benefited the analysis in this study. Funding for this study was provided in the frame of a PhD position for MD within the Research Training Group RESPONSE (RTG 2010), supported by the Deutsche Forschungsgemeinschaft (DFG).

SUPPLEMENTARY DATA AVAILABLE ONLINE (Online link) S1 Maximum-Likelihood phylogenetic tree of the most abundant myxomycetes OTUs.

S2 Sample quality.

S3 Result script.

S4 Satellite image of the transect area and representative images of the soil sampling sites.

S5 List of primers used to amplify the three target communities.

S6 DNA reads of mock samples.

S7 OTU tables.

S8 Functional classification. S9 Analysis script.

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3.4 DISTRIBUTION PATTERNS BETWEEN FRUIT BODIES AND SOIL AMOEBAE OF NIVICOLOUS MYXOMYCETES

Mathilde Borg Dahl1*, Oleg Shchepin1,2, Christian Schunk3, Annette Menzel3,4, Yuri K. Novozhilov2 & Martin Schnittler1

1. Institute of Botany and Landscape Ecology, Ernst Moritz Arndt University of Greifswald, Greifswald, Germany

2. Komarov Botanical Institute of the Russian Academy of Sciences, Laboratory of Systematics and Geography of Fungi, Prof. Popov Street 2, 197376 St. Petersburg, Russia

3. Ecoclimatology, Technical University of Munich, Freising, Germany

4. Institute of Advanced Study, Technical University of Munich, Garching, Germany

*Corresponding author: [email protected], Ernst Moritz Arndt University Greifswald, Institute of Botany and Landscape Ecology, Soldmannstrasse 15, 17487 Greifswald, Mecklenburg-Vorpommern, Germany. Manuscript submitted the 26th January 2018 for publication in Ecology.

Supplementary files are available online via Dropbox (Online link)1

ABSTRACT Among soil-inhabiting protists, myxomycetes stand out by their macroscopic fructifications which have allowed studies on their ecology and distribution for nearly two hundred years. One of the most distinct ecological guilds in myxomycetes are the nivicolous or “snowbank” species, which produce fruit bodies at the edge of melting snowbanks in spring in mountain regions. However, relations between the occurrence of fructifications and myxamoebae remain unknown. In this study we take advantage of modern molecular techniques, by direct DNA amplification from soil extracts (DNA metabarcoding) to compare the distribution of soil-inhabiting myxamoebae with fructifications collected within four consecutive years along an elevational transect in the northern limestone German Alps. We report a coherent community composition between fructification and soil amoebae, though with species-specific relative differences in abundance, which can in part be attributed to the visibility of the fructifications which differs between species. Although patterns vary among species, myxamoebae are found at both low and high elevations, whereas fruit bodies are mainly found at higher elevations only, likely explained by the presence of a stable and long-lasting snow pack at higher elevations. In addition, a year to year comparison of fructification records lends support to the hypothesis that the abundance of fructifications depends strongly on the onset of snowfall in the previous autumn and the soil temperature regime throughout the winter.

INTRODUCTION Soil protists are a diverse assemblage of different basal Eukaryotic lineages (Adl et al. 2012, Ruggiero et al. 2015), which play a crucial role in decomposition where they through their predation regulate and stimulate activity of other microbes and consequently influence higher trophic levels and plant growth (Bonkowski 2002, 2004, Gessner et al. 2010, Geisen et al. 2015, Geisen and Bonkowski

1 https://www.dropbox.com/sh/lkdadijydb8l18p/AABjvjzHt3dGQM0ADCKNTsJha?dl=0 91

Borg Dahl et al. Fruit bodies vs. soil amoebae distribution (submitted 26.01.2018).

2017, Hünninghaus et al. 2017). Nearly always belonging to the invisible world, these organisms are understudied, due to a lack of cultivation methods and/or morphological descriptors, which complicates diversity studies based on morphological species differentiation. Among soil-inhabiting protists, myxomycetes are an exception due to their macroscopic fructifications (Schnittler et al. 2012) which have been studied for nearly two hundred years (Stephenson et al. 2008). Based solely on morphological characters of the fructifications, ca. 1000 species are described (Lado 2005–2017) and a substantial body of data on ecology and distribution of these fructifications exists (Rojas and Stephenson 2017). However, knowledge on abundance of myxamoebae and structure of their communities in natural environments is nearly completely lacking. Advances in molecular techniques, such as direct DNA amplification from environmental extracts (ePCR), have made studies of myxamoebae (and other microbes) possible, and they are currently estimated to account for between 5 to almost 50% of all soil amoebae and present in a wide variety of soils (Urich et al. 2008, Geisen et al. 2015, Jacquiod et al. 2016). As for many microbial groups (Boenigk et al. 2012), the true diversity of myxomycetes seems to be much greater than shown by morphological characters, and many described morphospecies seem to consist of groups of several cryptic species (Feng and Schnittler 2015, Shchepin et al. 2016, Feng et al. 2016, Borg Dahl et al. 2017a, Dagamac et al. 2017). Based on field collections of myxomycete fruiting bodies, morphospecies are known to require specific habitats such as herbivore dung or decaying wood (Ing 1994, Liu et al. 2015, Novozhilov et al. 2017). One of the most distinct ecological guilds in myxomycetes constitutes the nivicolous or “snowbank” species, with their specific habitats first described in 1908 by Meylan (Kowalski 1975). The ca. 100 described species nearly all belong to the dark-spored myxomycetes, one of two basal clades in the group (Fiore-Donno et al. 2012, 2013). Fruiting occurs in spring, where fruit bodies emerges from the soil along the edge of melting snowbanks in mountains, with most accounts coming from the northern hemisphere (Lado 2004, Ronikier and Ronikier 2009). A recent analysis of nivicolous species from the same transect as presented in this study showed that the distribution of myxamoebae is explained best by a combination of vegetation traits and elevation (Borg Dahl et al. 2017b). This is in accordance with data on the distribution of fruit bodies of nivicolous species, which have been reported to exhibit a wide variety of species-specific preferences for elevation and vegetation type (Lado 2004, Ronikier and Ronikier 2009, Novozhilov et al. 2013, Schnittler et al. 2015). However, a quantitative comparison between the occurrence of myxomycete fruit bodies and amoebae along a natural elevation gradient across various vegetation types has never been conducted. Recent studies have shown that the amoebae are quite susceptible to low temperatures (Shchepin et al. 2014). Results of a study from the northern Caucasus using data loggers (Schnittler et al. 2015) suggest that the abundance of fructifications depends strongly on the onset of snowfall in the previous autumn and the duration of contiguous snow cover throughout the winter. This paper compares a quantitative survey of fruit bodies from a transect of the northern limestone German Alps with a dataset of soil myxamoebal populations obtained by environmental PCR from the same transect (which we recently published, Borg Dahl et al. 2017b). We ask if 1) the occurrence of fructifications reflects that of myxamoebae and 2) if year to year variations in fructification records can be explained by the stability and duration of the winter temperature and snow regime.

MATERIALS AND METHODS

Study area and specimen collection The study area was previously described in Borg Dahl et al. (2017b). In brief: The area is an east exposed transect below the Alpspitz summit near Garmisch-Partenkirchen in the German limestone 92

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Alps reaching from the Bayernhaus (47°27’55” N, 11°12'40” E, ca. 1,200m a.s.l.) to the Osterfelder Kopf (47°26’20” N, 11°03'00” E, ca. 2,050m a.s.l.). The lowermost parts of the transect support mixed forests with beech (Fagus sylvatica L.), fir (Abies alba Mill.) and spruce (Picea abies (L.) H. Karst.); with increasing elevation the two former species gradually drop out, and from 1,400m onwards spruce dominates. The timberline is reached at ca. 1,700m, and forests give place to shrub thickets composed of Pinus mugo Turra and Alnus alnobetula (Ehrh) K. Koch (= A. viridis (Chaix) DC.). Open grasslands occur at all elevations, either as small natural wet meadows or as semi-natural pastures in the forest belt, where trees have been cut. In places with wet soil and/or strongly affected by cattle grazing, broadleaved forbs (Rumex alpinus L., Senecio alpinus (L.) Scop.) dominate. One open (op) canopy site and one closed (cl) were chosen at every 100m elevation (to cover the full range of potential habitats), resulting in 16 sites. Soil samples were collected the 1st of June 2016 from the 16 sites in three biological replicates approximately 10 meters apart from each other. Ca. 20g of soil from the upper most soil layer (excluding litter) was collected within 1m2 per replicate and pooled (see Borg Dahl et al. 2017b for further details). Environmental parameters like soil pH, slope exposition and inclination were recorded for each site. The entire transect was surveyed for nivicolous myxomycetes for ca. one week in spring 2013, 2015, 2016 and 2017 by two investigators. From all observed fructifications of myxomycete a part of a colony was collected, and boxed immediately in the field to avoid cross-contamination by spores (see discussion in Novozhilov et al. 2013). Collections included as well colonies found outside of the plots designated for studying soil amoebae. Myxomycete colonies found further than 20cm apart from each other were collected separately. For each collected colony the aspect and inclination of the slope as well as GPS coordinates were recorded using GPS status & Toolbox (MobiWIA) application for smartphone (see suppl. S1 for a collection list). According to Schnittler et al. (2015) the number of days suitable for amoebal growth can be estimated as days with a daily average soil temperature between –0.5 and 2°C as well as with fluctuations not exceeding three degrees, indicating the presence of an insulating layer of snow, which should provide optimum conditions for amoebal growth of nivicolous myxomycetes and undersnow microbial communities (Schmidt and Lipson 2004). Likewise days with soil frost, considered unsuitable for growth and potentially lethal for the soil amoebae, were defined as days where temperature did not rise above –0.5°C (Shchepin et al. 2014). In May 2015 Hobo Pro v2 U23 data loggers were installed at the collection sites in a bottom-up perforated plastic cup and placed in level with the soil surface, logging temperature every 30 minutes from October to June each year. In addition, soil temperatures and snow cover data from 2013 to 2017 were obtained from the climate station ‘Kreuzalm’ (47°27’05” N, 11°04'20” E) belonging to the section of Ecoclimatology, Technical University Munich (TUM) situated in close proximity of the 5th survey plot at the middle of the transect (1,578m.a.s.l.). The station logs soil temperature at 5cm depth every 10min, from 2014 onwards a sensor monitoring snow height was installed

Morphological determinations Specimens were determined according to Neubert et al. (1995, 2000) and Poulain et al. (2011), applying the morphological species concept of the latter authors for the genera Diderma and Meriderma. Microscopic characters were assessed by mounting material in Hoyers Medium and using a Leica DM2500 microscope. All material was deposited in the personal collection of M. Schnittler (Greifswald, Germany) to be stored at the Botanical State Collection, Munich (M); duplicates of many specimens were additionally deposited in mycological herbarium of the V.L. Komarov Botanical Institute, St. Petersburg, Russia (LE). Nomenclature follows Lado (2005–2017), with exception of some tentatively described species (e.g. Meriderma aggregatum ad. int., Poulain et al. 2011). DNA extraction from fruit bodies

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DNA from myxomycete fruit bodies was extracted following previously published protocols (Borg Dahl et al. 2017a). In brief, 3–6 fully mature sporocarps (fruit bodies) were mechanically homogenized with a MP Biomedical Fastprep 24 (Santa Ana, California, USA). DNA was extracted with the OMEGA Plant Kit (Norcross, Georgia, USA) according to manufacturer’s protocol. A partial SSU sequence (~350bp) was amplified using the primers S31R (Schnittler et al. 2017) and S3bF (Hoppe and Schnittler 2015) specific for dark-spored myxomycetes. Amplicons were Sanger sequenced at an ABI 3010 platform. Sequences are available from the European Nucleotide Archive (ENA), accessions: LT669954–LT670816 and MG819747 - MG820028 (see suppl. S1).

DNA extraction from soil samples For this study we used the community composition (table of Operational Taxonomic Units, OTU) of myxamoebae recently obtained from soil samples (reported in Borg Dahl et al. 2017b and available from suppl. S2) and compared with quantitative fruitification records from the same area. The OTU table contained raw DNA read counts (ranging from 8,666 to 56,651 reads per sample) which in numbers were independent from measured environmental parameters (incl. elevation). Likewise the OTU richness was not correlated with the number of DNA reads, but decreased with elevation (Borg Dahl et al. 2017b). For DNA extraction from soil 0.25g fresh soil was lysed and DNA extracted using the epMotion robotic platform model (Eppendorf) and manufactures protocol. PCR amplifications were done in two steps with the primer pairs: S1/SU19R (Fiore-Donno et al. 2008) and S31R/S3b (Hoppe and Schnittler 2015; Schnittler et al. 2017). Paired-end sequencing was performed on an Illumina MiSeq platform (Illumina Inc.). The newly established 99.1% similarity threshold for OTU-picking was used to make abundance tables and the OTUs were annotated using a custom reference database (Borg Dahl et al. 2017a). The 99.1% threshold takes into account the existence of sub-clades within described morphospecies which may constitute putative biospecies (see discussion in Feng and Schnittler 2015, 2017). Since we must assume that most of these cryptic species are not yet formally described and many may lack attributable morphological characters, OTUs were assigned to morphospecies using a slightly lower similarity threshold (≥98.0%) if accompanied by a confidence score >90% as provided by the ‘utax’-command (Edgar 2016). Further OTUs with match score between 95% and 98% were assigned to the myxomycete genus represented by the ‘best match’ sequence.

Data analysis All sequences from fruit bodies were aligned with the online tool MAFFT (Katoh et al. 2002) applying the FFT-NS-I algorithm (iterative refinement method), excluding from further analyses four specimens where morphological determination and ribotype obviously deviated (most likely caused by cross-contamination). Sequences from the remaining 533 specimens were numbered for unique ribotypes, and pairwise genetic distances according to the ‘greedy clustering’ (Edgar 2013) model were calculated (suppl. S1). Applying the 99.1% threshold found by Borg Dahl et al. (2017b), ribotypes were clustered, and the clusters were labelled with the name of the respective morphospecies plus a suffix -a to -e for morphospecies including more than one cluster. Finally, for all unique ribotypes a phylogenetic tree was built with the Maximum-Likelihood (ML) algorithm implemented in MEGA6 (Tamura et al. 2013) with 500 bootstraps (suppl. S3). For comparison with the distribution of myxamoebae (OTUs), fruit body records were assigned to eight elevational belts of 100m width, spanning the range between 1,100 and 1,900m (35 specimens collected at lower or higher elevations were assigned to the first and last belt, respectively Basic statistical analyses were performed in R v. 3.3.3 (R Core Team 2017) using mainly the packages ‘vegan’ (Oksanen et al. 2017) and ‘iNEXT’ (Chao and Colwell 2014). This included species/ribotype accumulation curves and calculations for sampling coverage (number of items to be expected)

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Borg Dahl et al. Fruit bodies vs. soil amoebae distribution (submitted 26.01.2018). according to Chao and Jost (2012). Graphics were compiled using ‘ggplot2’ (Wickham 2009) and ‘ggmap’ (Kahle and Wickham 2013). Analysis scripts are provided in suppl. S4.

RESULTS

Alpha diversity and year to year comparison In total 732 colonies of fruit bodies were collected within four years of survey, of these 714 specimens could be successfully determined and assigned to 30 morphospecies, all known to be nivicolous species (suppl. S1). A total of 537 specimens (75.3% of all determinable records) were sequenced, and all but four clustered within the clade forming the respective morphospecies – at this level virtually no contradictions were found between the morphospecies determination and barcoding results (suppl. S3). However, one morphospecies sometimes included several ribotypes. For the 533 clearly assignable sequences 70 unique ribotypes were found, 22 of these as singletons. Clustering of these sequences with the same similarity threshold as that has been used to generate the soil OTUs (99.1% similarity) resulted in 45 ribotype clusters. Taking into account rare mutations and sequencing errors, these 45 clusters were considered to represent truly unique ribotypes (suppl. S1, S3). This resulted in an estimated sampling coverage of 99.6% for morphospecies and 98.5% for ribotypes (Fig. 1A).

Three specimens belonged to the bright-spored genus Trichia (T. alpina and T. sordida) and were thus excluded from the comparison with soil OTUs, as the primers used to target myxamoebae do not amplify these. From the soil samples 503 OTUs of dark-spored myxomycetes were identified (for sample rarefaction curves see suppl. Fig. S5), of these 245 (representing 60.1% of all reads) could be assigned to a reference sequence from fruit bodies (see suppl. S2 of Borg Dahl et al. 2017b). Of these annotated OTUs, 93.5% belonged to nivicolous species, representing a total of 24 morphospecies (suppl. S2). The following figures only consider nivicolous taxa, not OTUs assigned to other myxomycetes (i.e. with a summer/autumn peak in fructification, which were not recorded during the survey). Of the 70 unique ribotypes obtained from fruit body-derived sequences 34 were identical to a sequence from soil (100% similarity) and additionally 19 had a match to a soil sequence within the threshold for OTU picking (99.1% similarity; assumed to represent the same taxon). Finally, 17 sequences (5 ribotype clusters) representing 79 specimens were recorded only from fruit bodies and had no 99.1% match among the 503 OTUs from soil (Suppl. S6). One was a single collection of the rare Lamproderma pulchellum. But also from the complex morphospecies L. ovoideum (common in both the ePCR-based and the fruit body-based inventory) 42 of 83 sequences had no match among OTUs from soil with the chosen threshold. On average, these ribotypes had a match to a soil OTU with 94.1% ± 4.8% similarity (ranging from 87.3% to 98.8% similarity). Ribotypes showing a lesser than 99.1% match were found in all of the survey years with abundant fruiting (2013: 21 ribotypes, 2015: 24, 2016: 34). There was a strong correlation between the number of fruit bodies sequenced from a site and the number of sequences shared with the soil OTUs from the same site (Pearson's R = 0.94, p<0.001) as well as the number of unique ribotypes discovered per morphospecies (Pearson's R = 0.98, p<0.001, Fig. 1C).

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A) B) C) 60 70

60 s N: 44 8 N: 78 7 40 50 6

5 40 N: 66 N: 219

observed fruit body ribotypes body fruit observed 30 4 20 Elevation 20 N: 56 3N: 39

umber of umber 1: < 1200m Number of Morphotypes / Rribotype / Morphotypes of Number 2: ≥ 1200m < 1300m 3: ≥ 1300m < 1400m Morphospecies n Total 10 4: ≥ 1400m < 1500m Ribotypes 2 5: ≥ 1500m < 1600m 0 N: 6 N: 20 6: ≥ 1600m < 1700m 0 7: ≥ 1700m < 1800m 0 500 1000 1 8: ≥ 1800m Number of specimens Unique soil OTU Unique fruit ribotype Shared sequence Figure 1 A) Species accumulation curves for morphospecies collected as fruit bodies (circle) and their ribotype clusters (triangle); symbols mark the final point for the accumulation curves. Both curves are extrapolated to double collection size and the 95% confidence intervals are given (grey bands). B) Numbers of unique ribotypes derived from fruit bodies (total 70) showing a direct match (black), > 99.1% similarity (dark grey) or less (light grey) to a soil OTU. C) The relative proportion in observed sequences (ribotypes and OTUs) which are either unique for the soil (black), unique for the fruit body records (grey) or shared between the two datasets (99.1% similarity match; white) along the plots from the elevational transect (white numbers 1 to 8, showing the position of the respective plots). N represents the number of successfully sequenced specimens from each elevation level. A between-year comparison of the collected specimens revealed comparable figures for abundance of genera and morphospecies and thus a considerable overlap in registered morphospecies (Fig. 2A- B), except for 2017. The collection from this year was very poor with only 12 specimens collected, in contrast the largest collection was obtained in 2016 with 327 specimens recorded (Fig. 2B). All morphospecies recorded more than 20 times were found in each of the years 2013, 2015 and 2016 with good fruiting. In both inventories (soil ePCR and collected fruit bodies) the genera Lamproderma and Diderma were the most diverse, and their fructifications were the most frequent (Fig. 1C). The relative abundance between genera were mostly consistent, though members of the genus Meriderma (with dull black fruit bodies) were found twice as abundant as reads in the NGS record than in the fruit body record (10.6% vs. 5.0% respectively). The most species-rich genus in both inventories was Lamproderma with 8 and 11 morphospecies observed from NGS and fruit body records, respectively (Fig. 3). However, from Fig. 3 it is evident that the relative abundances of morphospecies differ between the two types of inventories.

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A) B) C) Diderma Unique for 2016: Unique for 2015: Didymium Lamproderma pulchellum Lamproderma piriforme 300 300 000 Meriderma carestiae var. retisporum Lamproderma 600 2016, N: 24 2015, N: 24 Lepidoderma Meriderma Physarum

200 1 22 2 200 000 400 17 18 17

100 100 000 Unique for 2013: 200 Lamproderma cristatum 2 Meriderma spinulosporum 2013, N: 20

0 0 0 N: 179 N: 194 N: 325 N: 12 N: 710 N: 330,970 2013 2015 2016 2017 Specimens NGS reads

Figure 2 A) Venn diagram showing the number of morphospecies shared between survey years (circle scaled to total number of morphospecies recorded), 2017 is not taken into account due to the low number of records. B) Total number of fructification records (only nivicolous species) within each genus per year. C) Total number of records/reads for the main genera (nivicolous species only) in the complete inventories from collected fruit bodies and ePCR from soil. The genera Diacheopsis and Trichia are excluded due to their low representation, together accounting for 0.4% (collections, Diacheopsis not found) and 2.5% (OTU reads, Trichia as bright-spored species not detected) of the total records. Slightly more morphospecies were registered in the fruit body inventory in comparison to ePCR. Three morphospecies recorded as collections were not represented in the reference database and could thus not be assigned to OTUs. First, sequences of Lamproderma cristatum formed mixed clades with those of L. spinulosporum, therefore both are currently excluded from the reference database. Second, Meriderma carestiae var. retisporum does not form a discrete taxon/clade in the sequence database, as the sequences originating from this morphologically determined variety are identical to sequences representing M. carestiae, indicating that the description of this morphological variety may not be justified. The third case considers the complex morphospecies Lamproderma ovoideum. This morphospecies has a number of closely related taxa, which most likely constitute biospecies in the sense of Feng et al. (2016). Some of these have already been described formally (e.g. L. ovoideoechinulatum, Poulain et al. 2011). In the reference database 97 specimens (83 originating from the field survey described herein) belonging to L. ovoideum agg. have been sequenced and among these sequences several distinct genetic subclades exist. We expect at least some of these subclades to be equivalent to the described taxa within L. ovoideum agg. However, a taxonomic revision still needs to be carried out. This leaves Lamproderma pulchellum (1 record, 0.2% of the 533 sequenced records), L. zonatum (3 records, 0.6%) and Meriderma aggregatum (15 records, 2.8%) as morphospecies only recorded as fruit bodies. Conversely Diacheopsis metallica (1.0% of a total of 425,603 reads assigned to nivicolous taxa) and Lamproderma pulveratum (16.4%), both known as nivicolous species, were only recorded from the soil OTUs (Fig. 3).

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Fruit records NGS reads Fruit records NGS reads

Diderma alpinum Diderma fallax Didymium difforme Diderma globosum var. europaeum Didymium dubium Diderma meyerae Diderma microcarpum Diderma niveum

N: 256/6 (36.1%) N: 100,748/6 (30.1%) N: 32/2 (4.5%) N: 21,899/2 (6.5%)

Fruit records NGS reads Fruit records NGS reads Lamproderma aeneum Lamproderma album Lamproderma arcyrioides Lamproderma cristatum Meriderma aggregatum Lamproderma echinosporum Meriderma carestiae Lamproderma ovoideum Meriderma echinulatum Lamproderma piriforme Meriderma spinulisporum Lamproderma pulchellum Lamproderma pulveratum Lamproderma retirugisporum N: 312/11 (43.9%) N: 140,038/8 (41.8%) N: 41/4 (5.8%) N: 35,458/3 (10.6%) Lamproderma sauteri Lamproderma zonatum Fruit records NGS reads

Physarum albescens Physarum alpestre Physarum vernum

N: 34/3 (4.8%) N: 20,622/3 (6.2%)

Figure 3 Proportions of specimens and OTU reads for the most common genera of nivicolous myxomycetes. Below each pie chart the total number of records (specimens or DNA reads) / total number of morphospecies is given; the per cent figure in parentheses indicates the relative abundance of the respective genus. The genera Diacheopsis (D. metallica), Lepidoderma (L. chailletii) are excluded due to their low representation; together accounting for 0.5% (collections) and 2.5% (OTU reads) of the total records.

Elevational species turnover When plotting the records from fruit bodies by their GPS coordinates it is evident that all major genera of nivicolous myxomycetes are represented across the full length of the transect (Fig. 4). However, a peak in records from fruit bodies was observed at the upper-middle part of the transect (level 6; 1,500–1,700m.a.s.l.), whereas no clear peak in abundance across genera was seen for the OTU reads (Fig. 4). For the latter the genus Diderma as well as members of both Lamproderma and Physarum were found primarily at the lower half of the transect, whereas Lepidoderma (though only represented by the morphospecies L. chailletii with two distinct ribotypes) was mainly found at the upper half of the transect.

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longitude 11.125 11.100 11.075 11.050 11.125 11.100 11.075 11.050 11.125 11.100 11.075 11.050

47.44

lat itude 47.46

Diderma Didymium Lamproderma 47.48 Fruit Fruit Fruit 1.00 0.75 0.50 0.25 0.00 NGS NGS NGS 1.00 0.75 0.50 0.25 0.00 47.44

47.46 lat itude

47.48 Lepidoderma Meriderma Physarum Fruit Fruit Fruit 1.00 * * 0.75 0.50 0.25 0.00 NGS NGS NGS 1.00 0.75 0.50 0.25 0.00 2 4 6 8 2 4 6 8 2 4 6 8 Diderma alpinum D. niveum L. ovoideum M. echinulatum D. fallax Didymium difforme L. retirugisporum M. spinulisporum D. globosum var. europaeum Lamproderma aeneum L. sauteri Physarum albescens D. meyerae L. album Lepidoderma chailletii P. vernum D. microcarpum L. arcyrioides Meriderma carestiae

* Vertical line represents two records of P. albescens or M. echinulatum only found at elevation level 6 (1,700m a.s.l.) Figure 4 Elevational distribution of records from fructifications / OTUs from ePCR plotted for each genus. The map shows collections of fruit bodies. The two plots below each map show elevational distribution for fruit body records and OTUs plotted along the elevational gradient (Numbers 1 to 8; 1,200 to 1,900m.a.s.l. in steps of 100m). Only nivicolous taxa occurring in both surveys were included. Abundance was scaled to the highest number of records per taxon. OTU records were square root transformed for improved graphic presentation. Map source: Google Earth.

Year-to-year snow and temperature regimes Figure 5 shows the average daily soil temperature at 5 cm depth from 2013 to 2017 and the estimated snow height at the Kreuzalm climate station. From the plots it is evident that there is a clear correlation between the presence of a snow cover and the degree of freezing observed in the soil. This was most clearly visible for the winter 2016/17, where an unstable snow cover did not prevent severe soil freezing (blue circle in Fig. 5).

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A) soil temperature at 5 cm depth [°C]

20

15

10

5 0

60 B) Snow height [cm] Severe soil frost and unstable snow cover

50 Summer vegetation

Approx. sampling time

40

30

20

10 0

Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan 2013 2014 2015 2016 2017 2018

Figure 5 Measurements from January 2013 to October 2017 of A) soil temperature at 5 cm depth and B) snow height. The ‘height’ registered by the sensor during summer is the reflection of the surrounding vegetation (herbs, indicated with a green dotted line). Short solid lines indicate the time of the four myxomycete surveys. A severe soil freezing during winter 2016/17 caused by an instable snow cover is indicated (blue circle and arrows). Data were obtained from the TUM climate station ‘Kreuzalm’ (47°27’05” N, 11°04'20” E). The snow height sensor was installed in 2014. The estimated number of days where temperatures were considered suitable for amoebal growth and the number of days considered unsuitable for growth are summarised for each site as well as for the ‘Kreuzalm’ climate station in Table 1 (see suppl. S7 for site-specific temperature plots from 2015/16 and 2016/17). In the winter 2015/16 the number of days suitable for amoebal growth was correlated with elevation (Pearson’s R = 0.71, p< 0.005), while no correlation was seen for unsuitable days (Pearson’s R = 0.49, p= 0.07). On the contrary, in winter 2016/17 the number of days with soil frost (unsuitable for growth) was correlated with elevation (Pearson’s R = 0.68, p< 0.005), while no correlation was seen for the number of suitable growth days (Pearson’s R = 0.32, p= 0.22).

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Table 1 Calculations for the number of days suitable / non-suitable for amoebal growth for each study site along the elevation gradient in winter 2015/16 and winter 2016/17 based on temperature data from loggers placed in the upper layer of the soil. The same calculations carried out with data from the ‘Kreuzalm’ climate station site for the years 2013 to 2017, corresponding to the plot in Fig. 2A.

Site Elevation Winter Days not Days suitableb ± s.d. suitablea

1cl 1195 ± 11 2015/2016 ; 2016/2017 107 ; 119 0 ; 2

1op 1202 ± 2 2015/2016 ; 2016/2017 115 ; 102 5 ; 33

2cl 1303 ± 14 2015/2016 ; 2016/2017 98 ; 100 2 ; 10

2op 1292 ± 3 2015/2016 ; 2016/2017 140 ; 112 2 ; 41

3cl 1296 ± 18 2015/2016 ; 2016/2017 129 ; 131 0 ; 4

3op 1296 ± 7 2015/2016 ; 2016/2017 123 ; 86 12 ; 53

4cl 1400 ± 19 2015/2016 ; 2016/2017 122 ; 137 0 ; 22

4op 1368 ± 13 2015/2016 ; 2016/2017 138 ; 123 4 ; 32

5cl 1498 ± 9 2015/2016 ; 2016/2017 -c ; 100 - ; 50

5op 1469 ± 22 2015/2016 ; 2016/2017 - ; 109 - ; 40

6cl 1649 ± 25 2015/2016 ; 2016/2017 150 ; 113 0 ; 47

6op 1608 ± 24 2015/2016 ; 2016/2017 170 ; 127 20 ; 59

7cl 1707 ± 5 2015/2016 ; 2016/2017 150 ; 115 36 ; 70

7op 1599 ± 3 2015/2016 ; 2016/2017 209 ; 168 1 ; 29

8cl 1903 ± 13 2015/2016 ; 2016/2017 171 ; 126 6 ; 56

8op 1883 ± 8 2015/2016 ; 2016/2017 128 ; 104 21 ; 62

Kreuzalm 1578 2012/2013 113 55 Kreuzalm 1578 2013/2014 118 18 Kreuzalm 1578 2014/2015 90 59 Kreuzalm 1578 2015/2016 146 0 Kreuzalm 1578 2016/2017 95 23 a Defined as days with daily average temp. between –0.5 and 2°C and daily fluctuations < 3°C. b Defined as days with maximum temp. < –0.5°C. c Data loggers for site 5 were lost for winter 2015/16.

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Borg Dahl et al. Fruit bodies vs. soil amoebae distribution (submitted 26.01.2018).

DISCUSSION As predators of other microorganisms myxomycete amoebae are among the key players in soil ecosystems and certainly abundant (Urich et al. 2008). Whereas a significant body of literature with thousands of papers exists on the distribution and ecology of the fructifications (Novozhilov et al. 2017), only four studies focused on identifying myxamoebae by ePCR (see Borg Dahl et al. 2017b), and no study exists that relates results from DNA metabarcoding of amoebal populations to what is known from DNA barcoding of the myxomycete fructifications. As such, our view on myxomycete ecology resembles that of a gardener who is trying to figure out the structure of an orchard but sees only the apples, not the trees where they belong to.

The fruits reflect the trees – Fruit body records vs. NGS records The relative abundances of genera when comparing the specimen-based inventory to the taxonomic composition of the annotated OTU reads were found to be quite consistent, except for a large fraction of the OTUs that remained unclassified and could often be assigned only to a genus, not to a species. At morphospecies level, relative abundances differed considerably, especially for the rare genera Didymium and Physarum. Only a few specimens were found for these genera, and their OTU reads were equally scarce and patchy (Fig. 2C and Borg Dahl et al. 2017b), indicating that for both inventories the sampling effort was not sufficient to allow a reliable comparison within these genera. For the dominant genera Diderma and Lamproderma, both represented by several hundred specimens, relative abundances coincided far better. Apart from random effects for rare species, the remaining differences may be partly explained by the relative visibility of the fruit bodies. Taxa with large fruit bodies and preferring open areas were often overrepresented as specimens compared to OTU reads. Among species with white (calcareous) fructifications, prominent examples were Diderma meyeri, D. globosum var. europaeum or Physarum vernum. However, Didymium difforme and Physarum albescens were clearly underrepresented as specimens (15 and 2 records) in comparison to OTU reads. This is plausible for the inconspicuous D. difforme, preferring deeper sections of litter, but not for P. albescens which forms large and conspicuous colonies from quite motile plasmodia which may climb up on living twigs (M. Schnittler, personal experience). A variation in the 18S SSU gene copy number between taxa can also be responsible for a bias in the relative abundance observed for the taxa, however such variation is not expected to be severe between closely related taxa of the same size and biomass (Godhe et al. 2008, Medinger et al. 2010). Surprisingly, 5 of the 45 ribotype clusters (representing 79 of the 533 sequences) observed from fruit body records were not found among the OTU reads. The majority (57.0%) of these ribotypes originated from other survey years than 2016 when the soil samples were collected. This suggests that the community composition fluctuates between years and may be influenced by the ability of myxomycetes to undergo long distance dispersal (Kamono et al. 2009, Wilkinson et al. 2012). We expect ribotypes represented by fruit bodies to have reached a high amoebal cell density in the soil prior to fruit body formation (Clark and Haskins 2013) and it is thus surprising that not all ribotypes obtained from specimens collected in 2016 were discovered among the OTU reads. A ready explanation is the different area covered by the fruit-body-based surveys (>30ha) in comparison to the plots for collecting soil samples (ca. 48m2), especially when considering the patchy distribution of myxamoebae (Borg Dahl et al. 2017b). This analysis of the OTU distribution along the transect suggested highly species-specific habitat requirements among myxamoebae, driven by indirect effects of the vegetation and potentially the presence of specific bacterial taxa (Kamono et al. 2012, Fiore- Donno et al. 2016, Borg Dahl et al. 2017b). Thus fruit bodies of rare species may have unintendedly been collected in habitats not represented by the soil samples.

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Borg Dahl et al. Fruit bodies vs. soil amoebae distribution (submitted 26.01.2018).

Elevational species turn over For some taxa the elevational distribution patterns observed from specimens and OTU reads are in accordance with each other, examples are L. chailletii, M. carestiae and M. spinulisporum (though a peak at lower elevation was observed for the latter in the OTU reads which was not reflected by the specimens). However, for the majority of species their elevational distribution was shifted towards higher elevations in the fruit body inventory compared to the OTU inventory. This holds true for all members of the genus Diderma as well as for some species of Lamproderma (L. album and L. arcyrioides) and Meriderma spinulisporum. Spring snowmelt will often happen gradually from the mountain valley towards top and in addition cold spells will regularly move in and re-cover the mountains in snow. Fruit bodies which have emerged with the first snowmelt at lower elevations may thus be coved and subsequently destroyed following such events. Therefore it cannot be ruled out that the shifted distribution observed between the occurrences of taxa in the NGS and the fruit body records reflects a bias introduced by the survey timing, although the lower parts of the transect were always carefully examined for remains of fruit bodies, which are quite durable especially in the genera Lamproderma (with a flexible columella) and Diderma (with a whitish hypothallus, Poulain et al. 2011). Furthermore in our recent analysis of the distribution range of the soil myxamoebae (Borg Dahl et al. 2017b) vegetation type was found to be a strong explanatory parameter for the myxamoebae distribution rather than the elevation per se.

Snow regime dictates fructification success The data presented in this study mounts evidence for the hypothesis that soil freezing has severe consequences for the development of myxomycete fructifications in the following spring which is in accordance with observations for northern Caucasus (Schnittler et al. 2015). This is especially evident from the winter 2016/17 where hard soil frost was observed along with a more unstable snow cover compared to previous years and the following spring’s survey resulted in only 12 collected specimens. Contrary in the previous winter (2015/16) no soil frost was observed, instead a long lasting snow cover was registered at ‘Kreuzalm’ climate station (146 days; the longest within our survey period) which was followed by the largest collection made within the investigation period (325 specimens). Going further back to the winter 2014/15, the growing conditions seemed to be similarly ‘bad’ as for the winter 2016/17 with 59 days of permanent soil frost and only 90 days of estimated snow cover. The subsequent survey resulted in 194 collected specimens, which was much less than in spring 2016 but substantially more than in 2017. This indicates that the severity of the soil freezing is of equal importance for the fructification success. The lowest soil temperature registered at the Kreuzalm climate station in winter 2016/17 was –2.8°C on the 2nd January 2017 in a week where minimum daily soil temperatures were on average –1.8 ± 0.5°C accompanied by average minimum air temperatures –11.6 ± 7.6°C. In comparison, the coldest registered temperature in the winter 2014/15 was –0.7°C which was registered in long continuous periods, and the daily minimum temperatures ranged between –0.3°C and –0.7°C throughout the entire winter. With Shchepin et al. (2014) we assume that frost events severely reduce numbers of myxamoebae, caused by either direct cell die off from a rapid drop in temperature (presumably the case in winter 2016/17) or by lowered growth rate as a result of consistently low temperatures (presumably the case in winter 2014/15). Both cases would result in a lower amoebal density in the soil, which would subsequently lower the success rate for the individual amoebae to encounter a compatible mating type and form a plasmodium (Clark and Haskins 2013). However, to our knowledge quantitative measures of the myxamoebal population dynamics in natural environment have not been attempted in this or any other studies. A targeted analysis including direct cell counts from extracts and/or quantitative molecular techniques such as qPCR may be a next step to elucidate the mechanisms how temperature affects the fruiting success in different myxomycete species.

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Borg Dahl et al. Fruit bodies vs. soil amoebae distribution (submitted 26.01.2018).

CONCLUSION Our analysis of four years of fructification records revealed an overall consistent pattern in observed taxa between years. In addition, fructifications were largely found to reflect the soil amoebal community, though exceptions existed and five taxa were found to be represented only by one of the two inventories – of these, three were fructifications not represented in the reference database. For some but not all species a bias towards species forming large fructifications in open areas was seen in their relative frequency in the fruit body-based inventory. Finally, large discrepancies were found between the relative abundance of species in rare genera (being represented by only a few specimens and/or OTU reads), indicating that despite four years of quantitative surveying, these taxa were not sufficiently sampled to constitute the basis for a reliable taxa composition. Together with the already long known evidence for species-specific habitat requirements, the finding that fruit body-based surveys reflect relatively well the soil myxamoebal community represents a unique possibility to include myxomycetes as a microbial representative in classical monitoring programmes and/or citizen science initiatives. Thus, myxomycetes may indicate specific habitat features in the same way as plants, insects, amphibians etc. do in habitat quality assessments. To fully take an advantage of myxomycetes as an indicator group more studies need to be conducted which target the interplay and associations between myxomycetes and other members of the microbial community. However, the relatively high proportion of OTU reads that clearly belong to myxomycetes but have never been found in any fruit body-based survey (Borg Dahl et al. 2017b) indicates that there is more diversity in the soil than we see at fruit body level. From our sequential climate monitoring and fruit body surveys we found strong evidence that soil temperature regime during winter is crucial for the fruiting success of myxomycetes. Similar effects can undoubtedly be expected to occur for other microbial groups and thus altered snow and temperature regimes (as expected from the current climate changes) might have far reaching consequences for the soil microbial community, with both direct (in the same way as the myxomycetes were effected) and indirect effects (as a consequence of the altered microbial community structure), which are not yet elucidated.

ACKNOWLEDGEMENT The authors thank Nikki Dagamac, Thomas Hoppe and Paulina Janik for assisting in field work and Stefan Kellerer and Klaus Kellner, the wardens of the Tröglhütte of the DAV (Deutscher Alpenverein), for making our stay at the field site pleasant. In addition we wish to express a general gratitude to researchers for sharing their data and programming codes as well as engaging in online discussion forums (particularly Stack Overflow). Funding for this study was provided in the frame of a PhD position for MD within the Research Training Group RESPONSE (RTG 2010), supported by the Deutsche Forschungsgemeinschaft (DFG). AM and CS were funded by the Bavarian State Ministry of the Environment and Consumer Protection (KLIMAGRAD II project). YN and OS were funded by RFBR (Russian Foundation of Basic Research, project 15-29-02622 ofi_m).

SUPPLEMENTARY DATA AVAILABLE ONLINE (Online link) S1 – List of specimens collected and their morphological determination, including elevation and coordinates of the location (format dd.ddddd°). For sequences the collection number of specimen, the unique ribotype (number), ribotype cluster (number), the taxonomical assignment of the sequences (abbreviation of genus and species plus a suffix for the respective ribotype cluster) and the GenBank entry number is given. S2 – Table of OTUs recovered from 41 soil samples.

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Borg Dahl et al. Fruit bodies vs. soil amoebae distribution (submitted 26.01.2018).

S3 – Maximum Likelihood phylogenetic tree of the 70 unique ribotypes fond within 533 sequenced specimens. Labels include a collection number of a reference specimen, the code of the ribotype cluster (a, b, c etc.) and the number of specimens per unique ribotype. S4 – Analysis script (R and cmd command prompt) including ribotype calculations and soil match scores as well as diversity estimates. S5 – Rarefraction curves for soil samples. S6 – Table showing matches between ribotypes from the sequenced specimens and OTUs from ePCR of 41 soil samples. S7 – Site-specific temperature plots from winter 2015/16 and 2016/17.

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4 CONCLUSIONS AND PERSPECTIVES

4.1 MAIN FINDINGS

This study focused on establishing metabarcoding for dark-spored myxomycetes as a baseline for diversity and ecological studies of the myxamoebae. Though the error rate of the established marker and threshold could not be diminished completely, a threshold for OTU-picking was established which identifies taxa of dark-spored myxomycetes believed to come close to the true number of existing myxomycete species. The estimated number of taxa, as common for microbial species, approximately doubles the figure of the number of currently described species by morphological characters. The study thus increased substantially the current knowledge of the diversity of dark- spored myxomycetes.

When applied, the chosen marker (a part of the rRNA gene) resulted in ecological meaningful communities and shed light on unknown distribution patters of the myxamoebae population as well as the identification of potentially novel taxa of myxomycetes, as demonstrated in the ePCR studies (articles I and III).

In addition, this study presents one of the few quantitative surveys for fructifications carried out on a spatial (natural gradient) and temporal (through four years) scale. This allowed for the first time a direct comparison between the relative distributions of myxomycete fructifications and that of the amoebal stages in soil, as well as a year-to-year comparison of the fruiting success in relation to climatic parameters.

Finally the work conducted in this study largely increased the number of sequenced reference specimens, thus benefitting future studies of dark-spored myxomycetes.

The main conclusions of the four articles presented in this thesis can be summarized to:

 When using the custom-made primers S31R/S3bF designed for dark-spored myxomycetes targeting a partial sequences of the SSU gene a genetic similarity threshold of 99.1% should be used for OTU-picking and it is recommend to use confidence estimators when annotating OTUs (articles I and II).  The true diversity of myxomycete species is most likely two fold greater than the number of morphospecies currently described (article I).  Among the considered environmental parameters, vegetation was found to be a main explanatory parameter for the myxamoebae community composition. In addition, an altitudinal species turn-over was found, most likely explained by adaptation to harsh environmental conditions (article III).  Positive interactions between the myxamoeba of the morphospecies Lamproderma arcyrioides and (especially) gram positive bacteria was found and interpreted as an indication of a food preference (article III).  A coherent pattern was observed between the fructification records and the soil amoebae community composition (article IV).

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 The quantitative fructification records from four consecutive years showed consistency in year-to-year community composition, but frost events during winter were found to have severe consequences for the fructification success the following spring (article IV).

4.2 CHALLENGES AND LIMITATIONS

A major challenge in this study have been to establish the identification of true biospecies of myxomycetes, i.e. sexually isolated linages, by a single genetic marker (barcode). At the same time the barcode constitute the basis for applying NGS methodology and thus conduct diversity studies of myxomycetes in their amoebal (trophic) life stage. Establishing the genetic species delimitation was therefore a necessary milestone in order to engage in the main scientific questions of this thesis, namely “What define the ecological niche of nivicolous myxomycetes?” and thus contribute to the overall goals of RESPONSE.

The challenges arise from the existence of several species concepts, as described in the introduction. As so, the biospecies concepts (arrived form old cultivation studies of mating types) demands tedious work to verify and is for most described morphospecies not possible, due to lack of cultivation methods (as is the case for the nivicolous species). Second the morphospecies have been revealed, in accumulating recent data, to not reflect one biospecies but rather reflect complexes of several cryptic species, which in turn have sparse if any morphological characters to differentiate between them. Therefore a true verification of the marker and threshold can at the moment not be done and thus the identified OTU-picking threshold remained a pragmatic tool, however it presents an indispensable baseline for the conduction of any NGS study of dark-spored myxomycetes and thus enables studies of the myxamoebae ecology as well as diversity.

The development of new technics and continues improvement of analytic methods means that the field of environmental microbiology is undergoing rapid evolution. As so, the newest trends moves away from both targeted (primer-based) sequencing and OTU clustering altogether, and rely instead on unspecific amplification and improved sequencing-, assembly- and quality algorithms (Thompson et al., 2017).

For studies targeting collected specimens of myxomycetes, the current state of the art for species validation is obtained by using a combination of two or more independent gene markers. However if the species are to be fully validated by genetic means, true genotypes should be established with the use of either SNP (single-nucleotide polymorphism) or full genome sequencing. With still dropping sequencing prices as well as increasing analytic/computational capacity this should be within reasonable limits in terms of labour and economy in the near future. In addition genetic markers with a higher resolution (such as SNPs) would allow for studies of the population dynamics, which the ‘species’ marker like those discussed in this dissertation (SSU, COI, EF1A) does not fully allow, due to lack of intraspecific variance (the threshold at 99.1% leaves 0.9% intraspecific variance in the SSU marker).

4.3 CITATIONS Thompson LR, Sanders JG, McDonald D, Amir A, Ladau J, Locey KJ et al. (2017) A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551: 457–463.

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5 AFFIDAVITS

5.1 SELBSTSTÄNDIGKEITSERKLÄRUNG / DECLARATION

Hiermit erkläre ich, dass diese Arbeit bisher von mir weder an der Mathematisch- Naturwissenschaftlichen Fakultät der Ernst-Moritz-Arndt-Universität Greifswald noch einer anderen wissenschaftlichen Einrichtung zum Zwecke der Promotion eingereicht wurde.

Ferner erkläre ich, dass ich diese Arbeit selbstständig verfasst und keine anderen als die darin angegebenen Hilfsmittel und Hilfen benutzt und keine Textabschnitte eines Dritten ohne Kennzeichnung übernommen habe.

I hereby declare that I have submitted this work so far neither at the Faculty of Science and Mathematics at the Ernst-Moritz-Arndt-Universität Greifswald nor at any other university with the purpose to earn a PhD degree.

Furthermore I declare that I have written this work as an independent effort and did not use any other sources and guides than those cited in the work. I did not copy any paragraphs of a third author without marking them as a citation.

Greifswald 30th January 2018 Mathilde Borg Dahl

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5.2 ERKLÄRUNG BEI GEMEINSHAFTSARBEITEN SELBSTSTÄNDIG

Hiermit erkläre ich, dass die in der folgenden Inhaltsübersicht mit meinem Namen gekennzeichneten Kapitel von mir selbständig verfasst worden sind:

1. Abstract Borg Dahl M/ Schnittler M (Deutsch)

2. Introduction Borg Dahl M

3. Publications -

3.1. Genetic barcoding of dark-spored Borg Dahl M, Brejnrod A, Unterseher M, myxomycetes (Amoebozoa)—Identification, Hoppe T, Feng Y, Novozhilov Y, Sørensen SJ evaluation and application of a sequence and Schnittler M similarity threshold for species differentiation in NGS studies

3.2. Barcoding myxomycetes with molecular Schnittler M, Shchepin ON, Dagamac NHA, markers: challenges and opportunities Borg Dahl M and Novozhilov Y

3.3. Fine scale niche differentiation among Borg Dahl M, Brejnrod A, Russel J, Sørensen SJ amoebal communities of dark-spored and Schnittler M myxomycetes determined by landscape structures as well as biotic factors

3.4 Distribution patterns between fruit bodies Borg Dahl M, Shchepin ON, Schunk C, Menzel and soil amoebae of nivicolous myxomycetes A, Novozhilov YK and Schnittler M

4 Conclusion & Perspectives Borg Dahl M

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Ich erkläre weiterhin, das ich die im folgenden beschriebenen Teile derjenigen Kapitel, bei denen ich nicht Alleinautor bin, selbstständig verfasst habe:

I hereby declare that I have independently written the following parts of chapters where I was not the sole author.

Chapter 3.1 Genetic barcoding of dark-spored myxomycetes (Amoebozoa)—Identification, evaluation and application of a sequence similarity threshold for species differentiation in NGS studies. I conceptualized the analysis and methodologies that were employed in this manuscript. In addition I sequenced 315 specimens, compiled and organized the reference database. Soil samples were collected by Prof. Schnittler and Prof. Novozhilov. Illumina library were carried out by Dr. Unterseher and Dr. Hoppe. Dr. Feng contributed with a quality controlled selection of publicly available sequences. Data analysis, and interpretation were done by me with the assistance from Dr. Brejnrod. I wrote the manuscript as the first and corresponding author aided by all co-authors.

Chapter 3.2 Barcoding myxomycetes with molecular markers: challenges and opportunities. I contributed to this manuscript with general knowledge of barcoding analyses and database management. I contributed to the quality reading of the manuscript prior to submission.

Chapter 3.3 Fine scale niche differentiation among amoebal communities of dark-spored myxomycetes determined by landscape structures as well as biotic factors. Together with Prof. M. Schnittler I conceptualized the study design and methodologies that were employed in this article. I participated in all fieldwork and did all the laboratory work. Data analysis, and interpretation were done by me with the assistance of Prof. Schnittler, Dr. Brejnrod and MSc. Russel. Prof. Sørensen provided laboratory facilities and scientific supervision. I wrote the manuscript as the first and corresponding author aided by all co-authors.

Chapter 3.4 Distribution patterns between fruit bodies and soil amoebae of nivicolous myxomycetes. Together with Prof. Schnittler I conceptualized the study design and methodologies that were employed in this article. I participated in all fieldwork. MSc. Shchepin, Prof. Novozhilov and Prof. Schnittler partially participated in field work, did morphological determinations and contributed with sequenced specimens. Prof. Menzel and Dr. Schunk provided data from the TUM climate station. Data management, analysis, and interpretation were done by me with the assistance of Prof. Schnittler. I wrote the manuscript as the first and corresponding author aided by all co-authors.

Greifswald 30th January 2018 Mathilde Borg Dahl

Die Unterschrift weiterer Autoren kann aus technischen Gründen nicht eingeholt werden. Da die betreffenden Kapitel jedoch in Zeitschriften veröffentlicht sind, haben alle Mitautoren in die Publikation eingewilligt

Prof. Dr. Martin Schnittler (Wissenschaftlicher Betreuer)

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5.3 ERKLÄRUNG ZUR ABGABE EINER ELEKTRONISCHEN KOPIE DER DISSERTATION DECLARATION ON THE SUBMISSION OF AN ELECTRONIC COPY OF THE PHD THESIS

Mathematisch-Naturwissenschaftliche Fakultät Einverständniserklärung nach § 4 Abs. 1 Nr. c Promotionsordnung Faculty of Science and Mathematics Declaration of consent according to § 4 sect. 1 Nr. c Doctoral Degree Regulations

Hiermit erkläre ich, dass von der Arbeit eine elektronische Kopie gefertigt und gespeichert werden darf, um unter Beachtung der datenschutzrechtlichen Vorschriften eine elektronische Überprüfung der Einhaltung der wissenschaftlichen Standards zu ermöglichen.

I hereby declare my consent to produce and store an electronic copy of this thesis for the purpose to enable an electronic examination of the thesis with the goal to exclude plagiarism and to obey good scientific practices.

Datum:

Unterschrift: Mathilde Borg Dahl

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6 ACKNOWLEDGEMENT

Several people have made invaluable contributions to this PhD study for which I am very grateful. First I wish to thank my supervisor Prof. Martin Schnittler for his enthusiastic interest in the science of myxomycetes and his eye for details. Secondly I wish to thank my office roommate David Würth who set out on this PhD-journey simultaneously with me – Thanks for the great company, the coffee, the candy and the laughs. I also wish to thank the people in the working group General Botany and Plant Systematics and the entire group of RESPONSE-people for numerously good times, during seminars, summer schools, talks, lunchbreaks and RESPONSible parties. A great thanks to Prof. Søren J. Sørensen for the collaboration with the section Molecular Microbial Ecology (MME) at University of Copenhagen and to Luma George Odish for laboratorial assistance. A special thank you to my friend and collaborator Dr. Asker Brejnrod for his engagement in my work and for contributing with high scientific quality. Also a special thanks to Dr. Samuel Jacquiod for showing great patience and willingness to explain and advise me on statistical methodology. I thank the staff members of other institutes at the EMA University Greifswald namely Dr. Rabea Schlüter and Stefan Bock at the Imaging Center at Institute of Microbiology for their assistance with numerous images of spore ornamentation. Imme Burkart-Juergens from the Welcome Center at the International Office for being very kind and for extensive help with the German bureaucracy. I also wish to thank Stefan Kellerer and Klaus Kellner, the wardens of the Tröglhütte of the DAV (Deutscher Alpenverein), for making my many stays at the field site pleasant. Prof. Steven K. Schmidt for hosting me during my three weeks visit to his laboratory in Boulder, Colorado and Adam Solon for good company and participation in my field work in the Rocky Mountains. Finally I wish to thank the funding for this study, which was secured by the German Science Foundation (DFG) with my PhD position in the framework of the Research Training Programme RESPONSE (GRK 2010).

Lastly I will spend a few lines expressing my gratitude for all the truly wonderful people who have been, are and I am sure will continue to come into my life. I am blessed with very good fortune.

Mathilde Borg Dahl

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