Plants Assemble Species Specific Bacterial Communities From Common Core Taxa in Three Arcto-Alpine Climate Zones

This is an electronic reprint of the original article. This reprint may differ from the original in pagination and typographic detail. Author(s): Title: Year: Version: Please cite the original version: All material supplied via JYX is protected by copyright and other intellectual property rights, and duplication or sale of all or part of any of the repository collections is not permitted, except that material may be duplicated by you for your research use or educational purposes in electronic or print form. You must obtain permission for any other use. Electronic or print copies may not be offered, whether for sale or otherwise to anyone who is not an authorised user. Plants Assemble Species Specific Bacterial Communities From Common Core Taxa in Three Arcto-Alpine Climate Zones Gopala Krishnan, Manoj Kumar; Brader, Günter; Sessitsch, Angela; Mäki, Anita; Elsas, Jan Dirk Van; Nissinen, Riitta Gopala Krishnan, M. K., Brader, G., Sessitsch, A., Mäki, A., Elsas, J. D. V., & Nissinen, R. (2017). Plants Assemble Species Specific Bacterial Communities From Common Core Taxa in Three Arcto-Alpine Climate Zones. Frontiers in Microbiology, 8, 12. https://doi.org/10.3389/fmicb.2017.00012 2017 Plants Assemble Species Specific Bacterial Communities From Common Core Taxa in Three ArctoAlpine Climate Zones Manoj Kumar1, 2*, Günter Brader3, Angela Sessitsch3, Anita Mäki2, Jan Dirk Van Elsas1, Riitta Nissinen2 1Department of Microbial Ecology, University of Groningen, Netherlands, 2Department of Biological and Environmental Science, University of Jyväskylä, Finland, 3Health & Environment Department, AIT Austrian Institute of Technology, Austria Submitted to Journal: Frontiers in Microbiology Specialty Section: Plant Biotic Interactions ISSN: 1664-302X Article type: Original Research Article Received on: 21 May 2016 Accepted on: 03 Jan 2017 Provisional PDF published on: 03 Jan 2017 Frontiers website link: www.frontiersin.org Citation: Kumar M, Brader G, Sessitsch A, Mäki A, Van_elsas J and Nissinen R(2016) Plants Assemble Species Specific Bacterial Communities From Common Core Taxa in Three Arcto-Alpine Climate Zones. Front. Microbiol. 8:12. doi:10.3389/fmicb.2017.00012 Copyright statement: © 2017 Kumar, Brader, Sessitsch, Mäki, Van_elsas and Nissinen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Provisional This Provisional PDF corresponds to the article as it appeared upon acceptance, after peer-review. Fully formatted PDF and full text (HTML) versions will be made available soon. Frontiers in Microbiology | www.frontiersin.org Provisional 1 Plants Assemble Species Specific Bacterial Communities 1 From Common Core Taxa in Three Arcto-Alpine Climate 2 Zones 3 4 Manoj Kumar 1,2*, Günter Brader3, Angela Sessitsch3, Anita Mäki2, Jan Dirk van 5 Elsas1, Riitta Nissinen2 6 7 Affiliations 8 1 Department of Microbial Ecology, University of Groningen, Groningen, the 9 Netherlands 10 2 Department of Biological and Environmental Science, University of Jyväskylä, 11 Jyväskylä, Finland 12 3 Health & Environment Department, AIT Austrian Institute of Technology, Tulln, 13 Austria 14 15 Correspondence : 16 Manoj Kumar, [email protected] 17 18 19 20 5918 words, 7 Figures 21 22 Keywords: endophytic bacteria, arcto-alpine plant, biogeographical diversity, core 23 bacteriome, Oxyria digyna, Saxifraga oppositifolia. 24 25 Running title: Bacterial communities in arcto-alpine plants. 26 Provisional 2 Abstract 27 Evidence for the pivotal role of plant-associated bacteria to plant health and 28 productivity has accumulated rapidly in the last years. However, key questions related 29 to what drives plant bacteriomes remain unanswered, among which is the impact of 30 climate zones on plant-associated microbiota. This is particularly true for wild plants 31 in arcto-alpine biomes. Here, we hypothesized that the bacterial communities 32 associated with pioneer plants in these regions have major roles in plant health 33 support, and this is reflected in the formation of climate and host plant specific 34 endophytic communities. We thus compared the bacteriomes associated with the 35 native perennial plants Oxyria digyna and Saxifraga oppositifolia in three arcto-alpine 36 regions (alpine, low Arctic and high Arctic) with those in the corresponding bulk 37 soils. As expected, the bulk soil bacterial communities in the three regions were 38 significantly different. The relative abundances of Proteobacteria decreased 39 progressively from the alpine to the high-arctic soils, whereas those of Actinobacteria 40 increased. The candidate division AD3 and Acidobacteria abounded in the low Arctic 41 soils. Furthermore, plant species and geographic region were the major determinants 42 of the structures of the endophere communities. The plants in the alpine region had 43 higher relative abundances of Proteobacteria, while plants from the lowand high-44 arctic regions were dominated by Firmicutes. A highly-conserved shared set of 45 ubiquitous bacterial taxa (core bacteriome) was found to occur in the two plant 46 species. Burkholderiales, Actinomycetales and Rhizobiales were the main taxa in this 47 core, and they were also the main contributors to the differences in the endosphere 48 bacterial community structures across compartments as well as regions. We postulate 49 that the composition of this core is driven by selection by the two plants. 50 51 Provisional 3 Introduction 52 Among the terrestrial environments on Earth, arctic and alpine ecosystems cover 53 about 8% of the global land area, which is more than the area covered by tropical 54 forests (Chapin and Körner, 1996). These arctic and alpine ecosystems have the least 55 biologically usable heat and the lowest diversity of plants (Billings and Mooney, 56 1968). The plants in these systems are well adapted to cold and short growing seasons 57 and low-nutrient soils. The typical plant species occurring in both biomes are 58 collectively referred to as arcto-alpine vegetation. These plants are important in these 59 soils, as they constitute the prime settlers that are at the basis of the local living 60 ecosystem. It has been hypothesized that the local microbiota plays an important role 61 in the ecological success of these pioneering plants (Borin et al., 2010; Mapelli et al., 62 2011). While arctic and alpine biomes share many characteristics, including short and 63 cool growing seasons, cold winters and soils with low levels of nutrients, there are 64 also distinct differences: the alpine biome is characterized by high annual and diurnal 65 temperature fluctuation and high solar intensity in the summer and, in general, well-66 drained soils. The vegetation in the Arctic, on the other hand, experiences weeks to 67 months long polar night in winter and 24-hour daylight during the growing season. 68 Moreover, arctic soils are typically water-logged due to underlying permafrost 69 (Körner, 2003). These differences have led to ‘climatic ecotypes’ within arcto-alpine 70 vegetation, where the growth morphology and phenology of the same plant species in 71 different biomes reflect adaptation to distinct climates. 72 73 Endophytic bacteria are ubiquitous across both cultivated and wild plants. They have 74 been shown to contribute to major aspects of plant life, including regulation of growth 75 and development, nutrient acquisition and protection from biotic and abiotic stressors 76 (reviewed in Hardoim et al., 2015). Studies conducted mainly in agricultural or model 77 plant systems have offered a rapidly growing insight into the assembly, structure and 78 function of the endophytic communities in plants (Compant et al., 2010; Zhang et al., 79 2006). Soil type and plant species and genotype are both known to shape the 80 rhizosphere (Berg and Smalla, 2009; Garbeva et al., 2004) and root endosphere 81 communities (Bulgarelli et al., 2013). Rhizosphere soil is considered to be the main 82 source of endophytes (Bulgarelli et al., 2013), but vertical transmission via seeds has 83 also been reported (Puente et al., 2009; Hardoim et al., 2012). However, the factors 84 governing the plant-associated microbiota of perennial wild plants in the 85 aforementioned arcto-alpine soils may differ from those of model or well-fertilized 86 crop plants. For plants in the low-arctic fell tundra, we have previously shown that 87 plant species, rather than sampling site, determines the structure of the endophytic 88 (Nissinen et al., 2012) and rhizospheric (Kumar et al., 2016) microbial communities. 89 90 Most bacterial species are considered to be cosmopolitan, as they have been found 91 across biogeographic regions in habitats like soils, sediments, lakes and the sea 92 (Hanson et al., 2012). Interestingly, the bacterial diversity in arctic soils has been 93 shown not to differ from that of other biomes (Chu et al., 2010). With respect to 94 community structure, endemism per region has been observed for bacteria, with some 95 taxa reportedly being restricted to distinct geographical regions (Cho, 2000; Oakley et 96 al., 2010). 97 98 The main goal of this study was to investigate the factors that shape the bacterial 99 communities associated with two plant species in three geographic regions, from the 100 high Arctic to the Alps. Our target plant species, Oxyria digyna and Saxifraga 101 Provisional 4 oppositifolia, are arcto-alpine plant species with wide distribution from the high 102 Arctic to the mid-latitude alpine tundra. Both are typical pioneer species that 103 efficiently colonize low-nutrient tundra soils. O. digyna is a member of the 104 Polygonaceae (order Caryophyllales), whereas S. oppositifolia belongs to the order 105 Saxifragales, which diverged from other core eudicots 114-124 MYA (Soltis et al., 106 2000; Wikström et al., 2001). We focused on the root endophytic bacteria, and also 107 examined the bacterial communities in the relevant rhizosphere and bulk soil samples. 108 109 We hypothesized that (1) geographic region, related to climate zone, determines the 110 diversity and community structure of the soil bacterial communities in the selected 111 habitats, and (2) plants strongly shape the plant-associated communities, resulting in 112 plant species specificity, regardless of the geographic region. We also hypothesized 113 that (3) part of the plant-associated bacteria are consistently present in their hosts, 114 constituting an endophytic core microbiome. 115 116 To achieve our aims, we used community DNA based amplicon sequencing targeting 117 the bacterial 16S rRNA gene region and subsequent analyses. 118 119 Materials and Methods 120 121 Sampling locations and study sites 122 Plant and soil samples were collected from eight sampling sites in three distinct 123 regions representing different climate zones; Ny-Ålesund, high Arctic (3 sampling 124 sites), Kilpisjärvi, low Arctic (3 sampling sites) and Mayrhofen, European Alps (2 125 sampling sites) (Figure 1A). Kilpisjärvi is at the northwestern Finland and located 126 along the Fenno-Scandinavian border. Its flora is dominated by mountain birch forest 127 in the valleys and by fell tundra at higher elevations. The annual mean temperature is 128 about -2.2°C with plant growth season of ca. 90-100 days. Ny-Ålesund (Svalbard, 129 Norway) is located on an isolated archipelago in the high Arctic; the land cover is 130 dominated by glaciers and permafrost layers, and the mean annual temperature is -131 4°C. The soil temperatures have been reported to be below zero for more than 250 132 days per year ranging from -6°C to -25°C (Coulson and Hodkinson, 1995). Most 133 biological activity is restricted to less than 10% of the total land mass coupled with 134 about three months of plant growing season. The sampling location in the Mayrhofen 135 is located above the tree line south of Mayrhofen over the snow-covered mountains 136 (altitude ca. 2400 m above sea level) in the alpine tundra of the European Alps. 137 Coordinates and details of sampling sites are listed in Supplemental Table S1. 138 139 Sample collection and processing 140 12 replicates of bulk soil samples (the top 5 cm soil was removed and soil samples 141 from 5-10 cm and 10-15 cm, corresponding to major root mass of target plant species, 142 were both used for analysis) and six samples of both O. digyna and S. oppositifolia 143 (as whole plants with adhering rhizosphere soils) were collected from all sites, except 144 in site “Saana” (Kilpisjärvi) where only O. digyna plants were sampled and site 145 “Cliff” (Mayrhofen) where we sampled only 6 bulk soil samples. Sampling was 146 performed during summer 2012. All harvested plants were flowering at the time of 147 the sampling. Rhizosphere and bulk soil samples were processed and stored as 148 specified by Kumar et al. (2016). After removing rhizosphere soils, plant roots were 149 thoroughly washed with water and surface sterilized by immersing the plant material 150 into 3% sodium hypochlorite for 3 minutes and then subsequently in sterile double 151 Provisional 5 distilled water (3 x 90 s). 80-100 mg of root samples were weighed, snap frozen with 152 liquid nitrogen and stored at -80˚C for further DNA analysis. 153 Soil pH and soil organic matter (SOM) content were measured as described in Kumar 154 et al. (2016), while available phosphorous (P) was measured based on Bray No 1 155 extraction method (Bray and Kurtz, 1945). All the soil chemical analyses were 156 performed in duplicates (2 technical replicates) per sample, and with 4-8 biological 157 replicates per site and sample type (Table 1). 158 159 DNA isolation 160 Microbial DNA from soil samples were extracted following manufacturer’s 161 instruction using MoBio Power soil kit (MoBio, Carlsbad, CA USA). For soil 162 samples 0.5 g of soil was used instead of 0.25 g because of low microbial counts in 163 our soils (data not shown). For isolation of endophyte samples, Invisorb Spin Plant 164 Mini Kit (STRATEC Biomedical AG, Germany) was used in order to ensure 165 prolonged stability of endophytic DNA in the plant derived samples. Frozen plant 166 tissues were homogenized by bead beating for 45 s with 0.1mm sterilized glass beads 167 with FastPrep homogenizer (mpbio.com), followed by DNA extraction according to 168 manufacturer’s protocol. 169 170 16S rRNA gene library generation and sequencing 171 After isolating DNA from all six plant replicates from both plant species, four (rhizo172 and endosphere) or eight (bulk soil) samples technically best samples (good DNA 173 yield, good PCR amplification) were included in the next generation sequencing 174 library construction.16S rRNA gene was amplified using primers 799f/1492r (Chelius 175 and Triplett, 2001) and M13-1062f/1390r in a nested approach. The nested primers 176 targeting the V6-V8 regions of 16s rRNA gene enable elimination of plant chloroplast 177 16S rRNA gene amplicons as well as separation of endophyte amplicons from plant 178 mitochondrial amplicons by size fractionation (799f-1492r, Chelius and Triplett 179 (2001)) and produce an amplicon with high phylogenetic coverage and optimal size 180 for IonTorrent sequencing (1062f-1390r). Primers 1062f (Ghyselinck et al., 2013)and 181 1390r (Zheng et al., 1996) were tagged with M13 sequences to enable sample 182 barcoding as described below and in Mäki et al. (2016). Both reactions had 1 µl of 183 sample DNA, 1x PCR buffer, 1 mg/ml of BSA, 0.2 mM dNTP’s, 0.3 µM of each 184 primer and 1250 U/ml GoTaq DNA Polymerase (Promega, WI USA) in a 30µl 185 reaction volume. 5-10 and 25-30 ng of soil and endophyte DNA, respectively, was 186 used in the first PCR, and 1µl of 1:10 diluted amplicons (for bulk and rhizosphere soil 187 samples) and 1 µl of amplicons (for endosphere samples) from the first PCR were 188 used as a template for the second run. Amplifications for both PCR reactions were 189 performed as follows: 3 mins denaturation at 95°C followed by 35 cycles of 190 denaturing, annealing, and extension at 95°C for 45 secs, 54°C for 45 secs and 72°C 191 for 1 min, respectively. Final extension was carried out at 72°C for 5 mins. Prior to 192 library production, the PCR protocol was optimized with regard to several primer pair 193 combinations, PCR protocols and test of PCR blockers to mimimize the strong 194 interference of mitochondrial rRNA in O. digyna and S. oppositifolia. The above 195 described protocol, using high coverage, minimal bias primer pairs, was shown to 196 produce enough eubacterial (endophytic) amplicons with no observable decline in 197 diversity (as detected by T-RFLP) for sequencing, while most alternatives lead to very 198 low amplification levels endophytes and strong mitochondrial signal. 199 200 Provisional 6 Sequence libraries were prepared by running a third PCR to attach the M-13 barcode 201 system developed by Mäki et al. (2016). Amplicons from second PCR were diluted 202 1:5 and re-amplified using barcode attached M13 system as forward primer and 203 1390r-P1 with adaptor A as a reverse primer. PCR mix and conditions were similar as 204 described above, with an exception of using 8 cycles for amplification. Amplified 205 libraries were purified using Agencourt AMPure XP PCR purification system 206 (Beckman Coulter, CA USA). Purified samples were quantified with Qubit 207 Fluorometer (Invitrogen, MA USA) and an equivalent DNA quantity of each sample 208 was pooled together. The pooled samples were then size fractionated (size selection 209 range of 350-550 bp) using Pippin Prep (Sage Science, MA USA) 2% Agarose gel 210 cassette (Marker B) following the manufacturer’s protocol. Size fractioned libraries 211 were sequenced using Ion 314 chip kit V2 BC on Ion Torrent PGM (Life 212 Technologies, CA USA) in Biocenter Oulu, Finland. 213 214 Bioinformatics and statistical analysis 215 The raw sequence reads were processed using QIIME (Caporaso et al., 2010) and 216 UPARSE (Edgar, 2013) based on a 16S rRNA gene data analysis pipeline developed 217 by Pylro et al. (2014) with slight modifications in quality filtering. Sequences were 218 trimmed by removing sequences with low quality reads (Q score <25) and shorter 219 base pair (<150) length. Furthermore, all the raw reads were trimmed (200 bp), 220 aligned and clustered at 97% identity using USEARCH algorithm (Edgar, 2010). 221 UCLUST algorithm along with Greengenes database (DeSantis et al., 2006) was used 222 to assign taxonomies at 97% identity to the individual OTUs. In total, 426,135 high-223 quality reads (1468 reads - 5331 reads per sample) were clustered into 985 OTUs. For 224 alpha diversity analysis all the samples were rarefied (subsampled) to 1400 reads per 225 sample. Shannon index and species richness were obtained using Univariate Diversity 226 Indices (DIVERSE, PRIMER 6 (PRIMER-E Ltd)). The differences in diversity 227 indexes between the soil samples and their correlation with soil physico-chemical 228 properties were determined using two-way ANOVA and Pearson correlation (SPSS 229 Statistics, IBM). The significance of the differences between the soil samples were 230 tested by Games-Howell post-hoc tests (two-way ANOVA). 231 232 To normalize the data for community structure and other analyses all the samples with 233 more than the median reads were rarefied to the median (2780 reads), while the 234 samples with less reads were used as such, as described in deCárcer et al. (2011). In 235 addition, all the singletons and OTUs with less than 50 reads were removed before 236 processing. The influence of sampling site, geographic region, plant compartment and 237 plant species on bacterial community structures, based on Bray-Curtis distance 238 matrixes of square root transformed abundance data, were analysed using 239 permutational multivariate analysis of variance (PERMANOVA) and visualized by 240 PCoA ordinations at the OTU level. Taxonomic groups (phyla or OTU) with strongest 241 impact on significant differences between community structures were identified with 242 SIMPER (Similarity Percentages - species contributions), all performed with 243 PRIMER 6 software package with PERMANOVA+ add-on (primer-e.com). 244 245 All the Ternary plots were made by calculating the mean relative abundances of 246 OTUs per geographic region/compartment and with the function ‘ternaryplot’ ‘vcd’ 247 (Meyer et al., 2015) from the R package. All other graphs (bar and scatter plots), also 248 based on the mean relative abundances of taxa, were constructed using the R package 249 ‘graphics’. 250 Provisional 13 depth; the plants often grow at close proximity to each other. However, they are 550 taxonomically quite distant (Soltis et al., 2000; Wikström et al., 2001) and have 551 differing mycorrhizal associations. O. digyna is non-mycorrhizal, whereas S. 552 oppositifolia is endomycorrhizal, which is likely to have strong impact on its nutrient 553 acquisition efficiency. 554 555 Despite these differences, the endosphere communities of these two plants were 556 strikingly similar. While we did find an effect of plant species on the endosphere 557 community structures (Table 3, Figure 6c), the plants shared a core microbiome, 558 dominated by Burkholderiales, Actinomycetales and Rhizobiales, across plants in the 559 three arcto-alpine climatic regions. Of these, Actinomycetales and Burkholderiales 560 have been reported as components of the core root microbiome of, e.g., A. thaliana 561 (Schlaeppi et al., 2014). Rhizobiales are known plant symbionts with nitrogen fixing 562 abilities, while Burkholderiales are well known for their biodegradative capacities and 563 antagonistic properties towards multiple soil-borne fungal pathogens (Benítez and 564 McSpadden Gardener, 2009; Chebotar et al., 2015). In our study, the core microbiome 565 OTUs representing Burkholderiales, especially Comamonadaceae and 566 Oxalobacteraceae, were relatively more abundant in O. digyna. We have repeatedly 567 isolated bacteria from O. digyna vegetative tissues with very high sequence 568 homologies to the above core OTUs (Nissinen et al., 2012; unpublished). Further, we 569 have isolated or detected (in clone libraries) bacteria in O. digyna seeds with 100% 570 (16S rRNA gene based) identity to six of the core OTUs (OTUs 2 and 16 representing 571 Rhizobiales, OTUs 8, 13 and 35 (Burkholderiales) and OTU 15 (Actinomycetales) 572 (unpublished data). Core OTUs related to similar strains from seeds were highly 573 enriched (Figure 7) in the endosphere or rhizosphere soils. Part of these core 574 organisms could thus be seed-transmitted and colonize the rhizoand endosphere of 575 developing seedlings, as previously described by Puente et al. (2009) in desert cacti. 576 This indicates the potential importance of such seed-transmitted endophytes in 577 pioneer plants. Horizontal transmission of a set of endophytes has also been observed 578 by Hardoim et al. (2012) and Johnston-Monje and Raizada (2011). 579 580 In addition, these core OTUs were among the primary drivers of region, compartment 581 or host plant species differences among the bacterial communities. The higher relative 582 abundances of Clostridia in Ny-Ålesund and Rhizobia in Mayrhofen in the 583 endosphere communities is one such example, as discussed above. 584 585 In summary, we here report that, on the basis of data obtained with two plant species, 586 host plant-specific endophytic communities can be acquired despite a distance of over 587 3000 km and differences in climate and chemistry between soils. These plant species-588 specific assemblages are formed from a shared core set of bacteria, most of which are 589 strongly enriched in the endosphere. We surmised that plant-driven selection 590 processes play a role, possibly concomitant with a highly efficient adaptation and 591 fitness of these bacteria in the plant environment. Some of the core OTUs could even 592 be seed-inherited, explaining their tight association with the host plant. Very closely-593 related endophytic taxa have previously been found to be shared by plants from other 594 cold climates (Carrell and Frank, 2015; Nissinen et al., 2012; Poosakkannu et al., 595 2015), indicating the ecological tightness of [efficient] establishment of specific 596 bacteria in arcto-alpine plants. 597 598 Conflict of interest 599 Provisional 14 The authors declare that the research was conducted in the absence of any commercial 600 or financial relationships that could be construed as a potential conflict of interest. 601 602 Author contributions 603 Study was conceptualized and designed by RN and MK. Field work was performed 604 by MK, RN and GB. Sample processing was done by MK and RN. Supporting soil 605 analysis was done by MK while library preparation for sequence analysis was done by 606 MK with assistance of AM. Bioinformatics analysis was performed by MK and the 607 data analysis was done by MK and RN. Manuscript draft was prepared by MK, RN 608 and JE and revisions was done by MK, RN, AM, GB, AS and JE. Final version for 609 the submission was prepared by MK and RN. 610 611 Nucleotide sequence data 612 Nucleotide sequence data has been submitted to the ENA database and with 613 accession number PRJEB17695. 614 615 Funding 616 This research was funded by NWO project 821.01.005 (for JE), Finnish cultural 617 foundation Lapland regional fund (for RN) and by Finnish Academy, project 259180 618 (for RN) 619 620 621 Acknowledgements 622 Authors acknowledge Maarten Loonen and other members of Netherlands Arctic 623 Station, Ny-Ålesund, Svalbard and Kilpisjärvi Biological Station of the University of 624 Helsinki for assistance in sampling. We also thank Andrés López-Sépulcre and Jenni 625 Niku for their valuable suggestions with statistical analysis and Jolanda Brons for her 626 assistance in soil physico-chemical analysis. 627 628 629 Supplementary material 630 S1 Site coordinates 631 S2 Phylum, class, order and family level analyses of the data. 632 633 References 634 Benítez, M. S., and McSpadden Gardener, B. B. (2009). Linking sequence to function 635 in soil bacteria: Sequence-directed isolation of novel bacteria contributing to 636 soilborne plant disease suppression. Applied and Environmental Microbiology 637 75, 915–924. doi:10.1128/AEM.01296-08. 638 Berg, G., and Smalla, K. (2009). Plant species and soil type cooperatively shape the 639 structure and function of microbial communities in the rhizosphere. FEMS 640 microbiology ecology 68, 1–13. doi:10.1111/j.1574-6941.2009.00654.x. 641 Billings, W., and Mooney, H. (1968). 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(2003). 869 Bacterial phylogenetic diversity and a novel candidate division of two humid 870 region, sandy surface soils. Soil Biology and Biochemistry 35, 915–924. 871 doi:10.1016/S0038-0717(03)00124-X. 872 873 874 875 876 877 Provisional 20 Figure legends 878 879 Figure 1. Sampling sites and OTU distribution. (A) Map of Europe depicting our three 880 sampling locations Mayrhofen from Austrian Alps, Kilpisjärvi from low-arctic 881 Finnish Lapland and Ny-Ålesund from high-arctic Svalbard archipelago. (B)Venn 882 diagrams of shared OTUs (number of reads of respective OTUs) across three regions 883 and (C) compartments. 884 885 Figure 2 Estimated Shannon diversity (A) in bulk soil, rhizosphere soil and 886 endophytic bacterial communities from three climatic regions Mayrhofen, Kilpisjärvi 887 and Ny-Ålesund (B) Scatter plots of bulk soil communities explaining the correlation 888 (Pearson correlation) between Shannon diversity with soil-physico chemical 889 properties from three climatic regions. 890 891 Figure 3 Distribution of OTUs and phyla across regions (A) Ternary plot of OTU 892 distribution across three climatic regions. Each circle represents one OTU, and the 893 size, color and position of the circle represent its relative abundance, bacterial phylum 894 and affiliation of the OTU with the different regions, respectively. (B-D) Average 895 relative abundances of bacterial phyla distributed across different regions in (B) Bulk 896 soil samples, (C) Rhizosphere soil samples, (D) Endosphere samples. Major phyla 897 (average relative abundance above 1%) with significantly differential distribution (as 898 detected by Kruskal-Wallis analysis) are marked with asterikses. 899 900 Figure 4 Distribution of OTUs and phyla across different compartments (A) Ternary 901 plot of all OTUs plotted based on the compartment specificity. Each circle represents 902 one OTU. The size, color and position of each OTU represents it relative abundance, 903 bacterial phyla and contribution of the OTU to the nearby compartments respectively. 904 (B) Distribution of average relative abundance of selected major bacterial phyla from 905 all three regions across the compartments. Major phyla (average relative abundance 906 above 1%) with significantly differential distribution (detected by Kruskal-Wallis 907 analysis) are marked with asteriskses. 908 909 Figure 5 Principal Coordinate Analysis (PCoA) plots of bacterial communities from 910 bulk soils, rhizosphere soils and endospheres of O. digyna and S. oppositifolia from 911 three climatic regions Mayrhofen, Kilpisjärvi and Ny-Ålesund. (A) All samples, (B) 912 Bulk soils and rhizosphere soils, (C) Endospheres from O. digyna and S. oppositifolia. 913 The symbol colors correspond to compartment (A and B) or plant species (C) and the 914 shapes of the symbols correspond to the geographic regions. Compartment, region 915 and plant species all had significant impact on community structures in global as well 916 as in pair wise analyses (PERMANOVA P=0.001). All ordinations are based on Bray-917 Curtis distance matrixes. 918 919 Figure 6 (A) Venn diagram of common shared OTUs and plant species specific OTUs 920 (number of reads of the respective OTUs) between O. digyna and S. oppositifolia 921 from all the endosphere samples. Average relative abundance of endophytic bacterial 922 communities associated with O. digyna and S. oppositifolia endosphere samples at 923 different taxonomical level. (B) bacterial class, (c) bacterial order. Only selected 924 major bacterial orders and classes were classified and shown. Manoj bacterial classes 925 or orders (with average relative abundance above 1% in endosphere) with 926 Provisional 21 significantly different distribution (detected by Kruskal-Wallis analysis) are marked 927 with asterikses. 928 929 Figure 7 Relative distribution of core OTUs’ reads across different compartments. 930 The graph is based on average read count of each OTU in different compartments. 931 932 933 Provisional 22 Table 1. Soil physico-chemical properties 934 Region Sampling Site [] SOM (%) pH Available Phosphorous mg/kg Mayrhofen Alps (A) [8] 0.01 (0.002) 7.03 (0.9) 1.84 (1.1) Cliff (C) [4] 0.02 (0.002) 4.60 (0.1) 1.48 (0.4) Average 0.01 (0.002) 5.81 (0.5) 1.66 (0.8) Kilpisjärvi Jehkas New (JN) [8] 0.02 (0.002) 5.55 (0.2) 1.31 (0.4) Jehkas Old (JO) [8] 0.02 (0.008) 6.36 (0.4) 0.76 (0.4) Saana (S) [8] 0.02 (0.01) 5.49 (0.6) 2.45 (1.5) Average 0.02 (0.01) 5.80 (0.5) 1.51 (0.8) NyÅlesund Knudsenheia (K) [8] 0.03 (0.01) 7.4 (0.9) 0.83 (0.5) Midtre Lovénbreen (M) [8] 0.03 (0.03) 6.4 (1.2) 0.63 (0.1) Red River (RR) [8] 0.04 (0.01) 7.78 (0.5) 0.34 (0.1) Average 0.04 (0.02) 7.20 (0.9) 0.60 (0.3) ( ) – Standard deviation values 935 [] – number of biological replicates/sampling site 936 Provisional Figure 02.TIF Provisional Figure 03.TIFF Provisional Figure 04.TIFF Provisional Figure 05.TIF Provisional Figure 06.TIFF Provisional Figure 07.TIF Provisional