New Phytologist Supporting Information

Article title: Species-specific Root Microbiota Dynamics in Response to Plant-Available Phosphorus

Authors: Natacha Bodenhausen, Vincent Somerville, Alessandro Desirò, Jean-Claude Walser, Lorenzo Borghi, Marcel G.A. van der Heijden and Klaus Schlaeppi

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The following Supporting Information is available for this article:

Figure S1 | Analysis steps Figure S2 | Comparison of ITS PCR approaches for plant root samples Figure S3 | Rarefaction curves for bacterial and fungal OTU richness Figure S4 | Effects of plant species and P-levels on microbial richness, diversity and evenness Figure S5 | Beta-diversity analysis including the soil samples Figure S6 | Identification of endobacteria by phylogenetic placement

Table S1 | Effects of plant species and P treatment on alpha diversity (ANOVA) Table S2 | Effects of plant species and P treatment on community composition (PERMANOVA) Table S3 | Effects P treatment on species-specific community compositions (PERMANOVA) Table S4 | Statistics from identifying phosphate sensitive microbes Table S5 | Network characteristics

Methods S1 | Microbiota profiling and analysis

Notes S1 | Comparison of PCR approaches Notes S2 | Bioinformatic scripts Notes S3 | Data analysis in R Notes S4 | Mapping endobacteria Notes S5 | Comparison of ITS profiling approaches Alpha diversity all samples Rarefaction analysis Figure S3 (vegan) Raw counts plant samples Rarefication (500x) to Figure S4 ANOVA 15’000 seq/sample Table S1 Filter: OTUs with min. 4 counts in min. 4 samples

Normalization by all samples PCoA, Filtered counts total sum scaling (TSS) PERMANOVA plant Figure S5, Table S2 plant samples samples Differential abundance testing PCoA, PERMANOVA Normalization by Table S4 (edgeR) trimmed mean of M Taxonomic Figure 4, Table S3 Identification of P values (TMM) composition sensitive OTUs Figure 2 Beta diversity (phyloseq, vegan)

Spearman rank Display network graph Data display with ternary correlation and Figure 6, Table S5 (igraph) plots and boxplots module detection Co-occurrence analysis Figure 5

Figure S1 | Analysis steps The schematic flow diagram illustrates the steps of the analysis in R. Individual types of normalization steps, analyses or statistical tests are indicated with the blue boxes. Larger grey boxes segment the analysis and indicate the major R-packages that were used in alpha- and beta diversity analyses, differential abundance testing and network analysis. Analysis outputs (Figures and Tables) are indicated in red at their respective analysis steps.

Figure S2 | Comparison of ITS PCR approaches for plant root samples To profile the root-associated fungal communities of Petunia, we first evaluated three ITS PCR approaches to test whether they avoid co-amplification of plant ITS sequences and whether they permit a reliable quantification of Glomeromycotina fungi. Four root DNA extracts from Petunia growing under low P conditions (=heavily colonized by AMF) were amplified with ITS1F and ITS2 by McGuire et al. (2013), fITS7 and ITS4 by Ihrmark et al. (2012) and the ITS1F with the reverse complement of fITS7. (a) The illustration depicts the positions of the PCR primers amplifying the internal transcribed spacer (ITS) regions between the small- and large ribosomal sub-units (SSU/LSU) of the ribosomal operon. Separate community profiles were produced and inspected for the proportions of plant and AMF sequences as well as for fungal diversity. Taxonomic composition of the 4 replicate extracts is reported at the level of (b) and within the fungi at the level of detected Phyla (c). (d) The diversity captured by the PCR approaches was determined by rarefying the fungi data and recording OTU richness. Bars represent means (n = 100; ± s.e.m.) and letters indicate groups differing significantly at P < 0.05 (Tukey’s HSD).

Bacteria

2000 Soil Petunia Arabidopsis 1500

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number of fOTUs number 500

0 0 10000 20000 30000 40000 50000 60000 70000 Sample Size

Fungi

700 Soil Petunia 600 Arabidopsis 500

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Figure S3 | Rarefaction curves for bacterial and fungal OTU richness We conducted a sampling intensity analysis for (a) and fungi (b) with all samples (Arabidopsis and Petunia with reddish and blueish colors, respectively, and the increasing P-levels (low, medium to high) are marked with increasing hue. Random sub-samplings were conducted for sequencing depths in steps of 100 sequences with 1000 iterations per sequencing depth. The average number of detected OTUs is reported for each sampling depth. The black vertical line indicates the selected rarefaction depth (15,000 sequences) used statistical analysis of alpha diversity (Fig. S4).

Figure 4 Alpha diversity S: *** T: *** SxT: S: *** T: * SxT: *** Arabidopsis Petunia Arabidopsis Petunia 1000 A AB B A AB B 300 B A A A A A ● ●

● ●● ● ● ● ●● ●● ● ●●● ● ●● ● ● ●● ● ● ●●● 800 200 ●●● ● ● ● ● ● ●● ●

● ●● ● ● ● ● ● ●● ● ● ● ●

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fOTU richness fOTU ●● bOTU richness bOTU ● ●● 100 600 ● ● ●● ●●●● ●●●● ● ● ●● ●● ●●●

●● ●● ● ●●

low medium high low medium high low medium high low medium high S: *** T: ** SxT: S: *** T: SxT: Arabidopsis Petunia Arabidopsis Petunia A A A A B B A A A A A A ● ●● ●

120 ●● ● ●

20 ● ●

● ● ● ●● ● ●● ●● ●● ● ● ● ● ● ●●● ●● ●● 80 ●● ● ●● ● ● ● 10 ●● ●● fOTU diversity fOTU bOTU diversity bOTU ●● ● ● 40 ●● ●●● ●● ● ●●● ● ● ●● ●●●●●●●●● ● ● ●●●●●●● ●●●●●●● 0 0 low medium high low medium high low medium high low medium high S: *** T: ** SxT: S: *** T: . SxT: * Arabidopsis Petunia Arabidopsis Petunia A A A A AB B 0.125 A B B A A A ● ● 0.15 ● ●● ● 0.100 ●

● ● ●● ●● ● ● ●● ● ●● ● ● ●● ●●● ●● ● 0.075 ●●

0.10 ●● ●●● ●● ●

● ● ●● ●● 0.050 ● ●

●●● ● ● evenness fOTU ● bOTU evenness bOTU ● ● ●● 0.05 ● ● ● ●● ● ● 0.025 ●● ● ●●●●●● ●●●● ● ● ●● ●●●●●●●●

low medium high low medium high low medium high low medium high

Figure S4 | Effects of plant species and P-levels on microbial richness, diversity and evenness Alpha diversity was assessed based on OTU richness, Shannon diversity and Sheldon evenness on data with a common sequencing depth of 15’000 sequences per sample. ANOVA was used to test for species- (S), treatment- (T) or their interaction (SxT) effects and their level of significance is indicated above plots (P < 0.001 ***; P < 0.01 **; P < 0.05 *; Table S1 contains the details of this ANOVA). Different letters indicate significant pairwise differences between different levels of P availability (P < 0.05, Tukey HSD).

Figure S4 Beta diversity (with soil) Bacteria Fungi

●● ●● ● ●● ● ●● ●●● ● ● ●●● ●●● ● ● 0.1 ● ● ●●●● ●● 0.25 ● ● ● ● 0.0 ●● ● ●●● ●●●● ● ● ● ● ● ● ● ● ●● ●●● ● ● ● ●●● ● ●●● ●● 0.00 ●● ● ● ●●●●● ● ● ● PCo 2 (9.2%) ● ● ● ●● ● PCo 2 (23.9%) −0.1 ●●●

●● ● ●● ● ● ● ●● ●●●●●● ● ● ●●●● ● ● ● ● ●●● −0.25 ●●● −0.2 ● ● −0.2 0.0 0.2 0.4 −0.4 −0.2 0.0 0.2 PCo 1 (45.8%) PCo 1 (52.1%)

Figure S5 | Beta-diversity analysis including the soil samples Principal coordinate analysis using Bray-Curtis dissimilarities were performed to investigate effects of plant species and P-levels on community composition. (a) Bacterial and (b) fungal communities associated with Arabidopsis roots (reddish colors), with Petunia roots (blueish colors) and found in unplanted soil (brownish colors), all sampled from varying levels of P availability (low, medium to high, marked with increasing hue).

bOTU 1020 bOTU 1046 BRE from Mortierella elongata FMR13-2, AB558494 BRE from Mortierellomycotina Burkholderia bOTU 1682 Uncultured bacterium, KC663974

bOTU 33 endobacteria Uncultured bacterium, EF019895 Environmental BRE bOTU 390 Mycoavidus cysteinexigens B1-EB, LC005489 * M. cysteinexigens from Mortierella elongata AG77, KP772716 bOTU 1995 Mycoavidus cysteinexigens from Mortierellomycotina M. cysteinexigens from Mortierella humilis PMI1414, KP772723 M. cysteinexigens from Mortierella elongata AG67, KP772725 CaGg from Scutellospora pellucida BR208A, JF816842

CaGg from Scutellospora pellucida BR208A, JF816849 -

bOTU 134 related BRE CaGg from Gigaspora margarita BEG34, X89727 CaGg from Scutellospora castanea BEG1, AJ251636 CaGg from Gigaspora margarita CM23, KF378649 Candidatus Glomeribacter gigasporarum CaGg from Gigaspora margarita CM47, KF378652 from Glomeromycotina CaGg from Gigaspora margarita MAFF520054, KF378648 * CaGg from Gigaspora margarita BR444, JF816839

CaGg from Scutellospora pellucida CL750A, JF816850 CaGg from Scutellospora pellucida FL704, JF816857 bOTU 2298 Burkholderia endofungorum, AM420302 Burkholderia endofungorum, HQ005412 Burkholderia rhizoxinica, AJ938142 Burkholderia rhizoxinica, HQ005411 Burkholderia pseudomallei, AY305818 Burkholderia mallei, NR041725 Burkholderia oklahomensis, NR118070 * Burkholderia cepacia, AY741362 Burkholderia graminis, NR029213 74 Burkholderia phytofirmans, NR042931 bOTU 84 Burkholderia mimosarum, HE864347 Pandoraea apista, NR028749 Pandoraea terrae, NR152002 Pseudoduganella sp., KU647209 bOTU 11 Duganella sp., KU647207 Pseudoduganella danionis, NR152711 Herbaspirillum huttiense, EU046556 Herbaspirillum aquaticum, FJ267649 Uncultured bacterium, AB487893 bOTU 2334 Uncultured bacterium, JX394270 Herbaspirillum sp., AB769222 Herbaspirillum sp., AB542410 * bOTU 1822 99 Ralstonia pickettii, NR043152 bOTU 529 Ralstonia solanacearum, CP012939 basilensis, CP010536 Cupriavidus metallidurans, CP000352 Thiobacillus thioparus, GU967681 bOTU 915 Thiobacillus sajanensis, DQ390445 Spirillum winogradskyi, AY845251 Spirillum kriegii, AY845252 bOTU 800 Nitrosovibrio tenuis, M96397 Nitrosospira multiformis, NR074736 * Gallionella capsiferriformans, NR074658 Sulfuricella denitrificans, AB506456 Azospira restricta, DQ974114 Rhodocyclus tenuis, D16208 Thiobacter subterraneus, AB180657 Chromobacterium aquaticum, EU109734 Aquitalea pelogenes, NR 148648 Neisseria gonorrhoeae, X07714 87 Uncultured Betaproteobacterium, AY922020 bOTU 1623 Uncultured Derxia sp., FJ946585 100 Achromobacter xylosoxidans, KP967463 Alcaligenes sp., GU731240 bOTU 914 Bordetella sp. S318, HM102497 Alcaligenes endophyticus, NR156855 Alcaligenes pakistanensis, AB920828 Uncultured Inhella sp., LN875043 Inhella sp., MF801372 bOTU 29 CaMg from Claroideoglomus etunicatum CA301, KP763319 CaMg from Claroideoglomus etunicatum CL372, KP763328

CaMg from Claroideoglomus etunicatum MX916B, KP763360 Mycoplasma CaMg from Claroideoglomus claroideum Att79-12, FJ984660 86 bOTU 330 CaMg from Gigaspora margarita CM21, KF378701 CaMg from Gigaspora margarita CM47, KF378698 * bOTU 1797 CaMg from Claroideoglomus claroideum Att79-12 , FJ984658 CaMg from Funneliformis mosseae Att109-20, FJ984709 CaMg from Claroideoglomus etunicatum AZ201C, KP763286 bOTU 778 CaMg from Claroideoglomus claroideum MUCL 46102, FJ984671 CaMg from Claroideoglomus etunicatum CA-OT126-3-2, FJ984689 72 bOTU 3291 CaMg from Scutellospora gilmorei Att590-16, FJ984735 CaMg from Gigaspora margarita CM23, KF378694 CaMg from Claroideoglomus etunicatum KS887, KP763351 CaMg from Funneliformis caledonius Att263-23, FJ984653 CaMg from Funneliformis mosseae Att109-20, FJ984707 CaMg from Glomeromycotina CaMg from Funneliformis mosseae Bol17, FJ984704

CaMg from Rhizoglomus clarum AU402B, KU992724 -

CaMg from Rhizoglomus clarum CL156, KU992754 related CaMg from Funneliformis caledonius Att263-23, FJ984648 CaMg from Funneliformis caledonius Att263-23, FJ984654 CaMg from Claroideoglomus claroideum Att79-12, FJ984662

CaMg from Funneliformis caledonius Att263-23, FJ984652 * CaMg from Glomus versiforme Att475-45, FJ984724 CaMg from Glomus versiforme Att475-45, FJ984725 CaMg from Cetraspora pellucida CL750A KP763394 * CaMg from Gigaspora albida BR601A, KP763383 CaMg from Gigaspora margarita MAFF520054, KF378704 CaMg from Racocetra verrucosa VA103A, KM065895 CaMg from Ambispora fennica Att200-26, FJ984643 CaMg from Claroideoglomus etunicatum AZ201C, KP763291 endobacteria CaMg from Ambispora appendicula Att1235-2 FJ984635 CaMg from Geosiphon pyriformis AS402, FJ984679 CaMg from Claroideoglomus etunicatum CA301, KP763316 CaMg from Claroideoglomus etunicatum IA205, KP763336 MRE from Jimgerdemannia flammicorona OSC 62257, KM594001 MRE from Jimgerdemannia flammicorona OSC 111442, KM594003 MRE from Jimgerdemannia lactiflua AD001, KM593997 MRE from Jimgerdemannia lactiflua T32530, KM594012 MRE from Endogone incrassata T32492, KM594011 MRE from Endogonaceae MRE from Jimgerdemannia lactiflua OSC 111744, KM594005 * MRE from Endogone sp. T26631, KM594002 * MRE from Endogone incrassata T32417, KM594010 MRE from Mortierella rostafinskii NRRL A-17819, MG052970 MRE from Mortierellomycotina sp. GBAus27b, MG052969 MRE from Mortierellomycotina sp. AD185, MG052968 MRE from Lobosporangium transversale NRRL 5525, MG052967 MRE MRE from Mortierella selenospora CBS 811.68, MG052966 92 MRE from Mortierella elongata AD073, MG052974 MRE from Mortierellomycotina MRE from Mortierella humilis AD092, MG052975 MRE from Mortierella elongata NVP80, MG052971 MRE from Mortierella gamsii AM1032, MG052972 MRE from Mortierella capitata AD192, MG052973 Mycoplasma canis, NR028813 Mycoplasma synoviae, X52083 Mycoplasma gallinarum, L24105 * Entomoplasma lucivorax, AF547212 Entomoplasma freundtii, NR028691 Mesoplasma florum, AF300327 Mesoplasma coleopterae, DQ514605 Spiroplasma diabroticae, GU908490 * Spiroplasma apis, GU993267 Mycoplasma genitalium, NR074611 Mycoplasma pneumoniae, AB680604 Ureaplasma gallorale, U62937 Ureaplasma urealyticum, M23935 Acholeplasma parvum, NR042961 Acholeplasma granularum, AY538166 Candidatus phytoplasma, Y16392 Anaeroplasma varium, NR044663 Nostoc commune, AB098071 Anabaena sphaerica, KX580773 0.2

Figure S6 | Phylogenetic placement of the 22 candidate endobacteria OTUs as identified by the clustering approach Twelve OTUs out of 22 turn out to be phylogenetically close to Burkholderia-related endobacteria (BRE) or Mycoplasma-related endobacteria (MRE). In detail, eight and four candidate endobacteria OTUs cluster within the BRE (in red) and MRE (in blue) clade, respectively. The remaining ten candidate endobacteria OTUs cluster with non-endobacteria Betaproteobacteria taxa. Further details are in Figure 7. The tree shows the topology obtained with the Bayesian method. Branches with Bayesian posterior probabilities (BPP) ≥0.95 and ML bootstrap support values ≥70 are thickened; asterisks (*) indicate branches with BPP ≥0.95 but ML bootstrap support values <70; ML bootstrap support values ≥70 are shown for branches having BPP <0.95. Sequences generated in this study are in bold. Mycoavidus cysteinexigens B1-EB, LC005489 Burkholderia-related M. cysteinexigens from Mortierella elongata AG77, KP772716 Mycoavidus cysteinexigens and BRE M. cysteinexigens from Mortierella humilis PMI1414, KP772723

71 endobacteria M. cysteinexigens from Mortierella elongata AG67, KP772725 from Mortierellomycotina 71 BRE from Mortierella elongata FMR13-2, AB558494 CaGg from Scutellospora pellucida BR208A, JF816842 CaGg from Scutellospora pellucida BR208A, JF816849 bOTU 134 80 CaGg from Gigaspora margarita BEG34 X89727 BRE * CaGg from Scutellospora castanea BEG1 AJ251636 Candidatus Glomeribacter gigasporarum CaGg from Gigaspora margarita CM23 KF378649 CaGg from Gigaspora margarita CM47 KF378652 from Glomeromycotina CaGg from Gigaspora margarita MAFF520054 KF378648 CaGg from Gigaspora margarita BR444 JF816839 CaGg from Scutellospora pellucida CL750A, JF816850 CaGg from Scutellospora pellucida FL704, JF816857 Burkholderia endofungorum, AM420302 Burkholderia endofungorum, HQ005412 Burkholderia rhizoxinica, AJ938142 Betaproteobacteria Burkholderia rhizoxinica, HQ005411 Burkholderia pseudomallei, AY305818 Burkholderia mallei, NR041725 Burkholderia oklahomensis, NR118070 Burkholderia cepacia, AY741362 Burkholderia phytofirmans, NR042931 Burkholderia graminis, NR029213 Burkholderia mimosarum, HE864347 Pandoraea apista, NR028749 Pandoraea terrae, NR152002 Pseudoduganella sp., KU647209 Duganella sp., KU647207 Pseudoduganella danionis, NR152711 87 Herbaspirillum huttiense, EU046556 Herbaspirillum1 aquaticum, FJ267649 bOTU 2808 Uncultured bacterium, JX394270 Uncultured bacterium, AB487893 Herbaspirillum sp., AB769222 Herbaspirillum sp., AB542410 Cupriavidus metallidurans, CP000352 Cupriavidus basilensis, CP010536 Ralstonia pickettii, NR043152 Ralstonia solanacearum, CP012939 100 Achromobacter xylosoxidans, KP967463 Alcaligenes sp., GU731240 Bordetella sp., HM102497 Alcaligenes endophyticus, NR156855 Alcaligenes pakistanensis, AB920828 Uncultured Inhella sp., LN875043 Inhella sp., MF801372 Uncultured Derxia sp., FJ946585 Uncultured Betaproteobacterium, AY922020 bOTU 676 Chromobacterium aquaticum, EU109734 Aquitalea pelogenes, NR148648 Neisseria gonorrhoeae, X07714 Uncultured bacterium, KC663974 Uncultured bacterium, EF019895 bOTU 587 bOTU 928 Thiobacillus sajanensis, DQ390445 Thiobacillus1 thioparus, GU967681 Spirillum winogradskyi, AY845251 Spirillum kriegii, AY845252 Nitrosovibrio tenuis,M96397 Nitrosospira multiformis, NR074736 * Gallionella capsiferriformans, NR074658 Sulfuricella denitrificans, AB506456 bOTU 419 Rhodocyclus tenuis, D16208 bOTU 13 Azospira restricta,DQ974114 Thiobacter subterraneus, AB180657 bOTU 491

4 bOTUs

13 bOTUs

61 bOTUs

24 bOTUs

CaMg from Claroideoglomus etunicatum CA301, KP763319

CaMg from Claroideoglomus etunicatum CL372, KP763328 Mycoplasma-related endobacteria CaMg from Claroideoglomus etunicatum MX916B, KP763360 CaMg from Claroideoglomus claroideum Att79-12, FJ984660 CaMg from Gigaspora margarita CM21, KF378701 * CaMg from Gigaspora margarita CM47, KF378698 CaMg from Claroideoglomus claroideum Att79-12, FJ984658 CaMg from Funneliformis mosseae Att109-20, FJ984709 bOTU 778 CaMg from CaMg from Claroideoglomus etunicatum AZ201C, KP763286 CaMg from Claroideoglomus claroideum MUCL 46102, FJ984671 Glomeromycotina CaMg from Claroideoglomus etunicatum CA-OT126-3-2, FJ984689 CaMg from Gigaspora margarita CM23, KF378694 89 CaMg from Scutellospora gilmorei Att590-16, FJ984735 CaMg from Claroideoglomus etunicatum KS887, KP763351 CaMg from Funneliformis caledonius Att263-23, FJ984653 CaMg from Funneliformis mosseae Att109-20, FJ984707 * CaMg from Funneliformis mosseae Bol17, FJ984704 CaMg from Rhizoglomus clarum AU402B, KU992724 CaMg from Rhizoglomus clarum CL156, KU992754 MRE from Jimgerdemannia flammicorona OSC 62257, KM594001 MRE from Jimgerdemannia flammicorona OSC 111442, KM594003 MRE from Jimgerdemannia lactiflua AD001, KM593997 MRE from Jimgerdemannia lactiflua T32530, KM594012 MRE from Endogone incrassata T32492, KM594011 MRE from Endogonaceae MRE from Jimgerdemannia lactiflua OSC 111744, KM594005 Mollicutes MRE from Endogone sp. T26631, KM594002 MRE from Endogone incrassata T32417, KM594010 CaMg from Ambispora appendicula Att1235-2, FJ984635 CaMg from Geosiphon pyriformis AS402, FJ984679 CaMg from Claroideoglomus etunicatum CA301, KP763316 CaMg from Claroideoglomus etunicatum IA205, KP763336 CaMg from Cetraspora pellucida CL750A, KP763394 88 CaMg from Gigaspora albida BR601A, KP763383 CaMg from Gigaspora margarita MAFF520054, KF378704 CaMg from Glomeromycotina CaMg from Racocetra verrucosa VA103A, KM065895 CaMg from Claroideoglomus claroideum Att79-12, FJ984662 * CaMg from Funneliformis caledonius Att263-23, FJ984652 CaMg from Glomus versiforme Att475-45, FJ984724 CaMg from Glomus versiforme Att475-45, FJ984725 MRE from Mortierella rostafinskii NRRL A-17819, MG052970 MRE from Mortierellomycotina sp. GBAus27b, MG052969 MRE from Mortierellomycotina MRE from Mortierellomycotina sp. AD185, MG052968 CaMg from Ambispora fennica Att200-26, FJ984643 CaMg from Claroideoglomus etunicatum AZ201C, KP763291 CaMg from Funneliformis caledonius Att263-23, FJ984648 CaMg from Glomeromycotina MRE CaMg from Funneliformis caledonius Att263-23, FJ984654 MRE from Lobosporangium transversale NRRL 5525, MG052967 MRE from Mortierella selenospora CBS 811.68, MG052966 90 MRE from Mortierella elongata AD073, MG052974 MRE from Mortierella humilis AD092, MG052975 MRE from Mortierellomycotina MRE from Mortierella elongata NVP80, MG052971 MRE from Mortierella gamsii AM1032, MG052972 MRE from Mortierella capitata AD192, MG052973 Mycoplasma canis, NR028813 Mycoplasma synoviae,X52083 Mycoplasma gallinarum, L24105 Entomoplasma lucivorax, AF547212 Entomoplasma freundtii, NR028691 Mesoplasma florum, AF300327 Mesoplasma coleopterae, DQ514605 Spiroplasma diabroticae, GU908490 * Spiroplasma apis, GU993267 Mycoplasma genitalium, NR074611 Mycoplasma pneumoniae, AB680604 Ureaplasma gallorale, U62937 Ureaplasma urealyticum, M23935 Acholeplasma parvum, NR042961 Acholeplasma granularum, AY538166 Candidatus phytoplasma, Y16392 Anaeroplasma varium, NR044663

* 12 bOTUs

6bOTUs

Nostoc commune, AB098071 Anabaena sphaerica, KX580773

0.2

Figure S7 | Phylogenetic placement of the 129 candidate endobacteria OTUs as identified by the network analysis approach Fig. S7 ff: Two OTUs out of 129 turn out to be phylogenetically close to Burkholderia-related endobacteria (BRE) or Mycoplasma-related endobacteria (MRE). In detail, bOTU 134 clusters within the BRE clade (in red), as sister to a clade encompassing Candidatus Glomeribacter gigasporarum (CaGg) sequences retrieved from Scutellospora pellucida (Glomeromycotina), whereas bOTU 778 clusters within the MRE clade (in blue), together with Candidatus Moeniiplasma glomeromycotorum (CaMg) sequences retrieved from different strains of Claroideoglomus spp. (Glomeromycotina). Seven candidate endobacteria OTUs out of 129 cluster with non-BRE Betaproteobacteria taxa. The remaining bOTUs (120) are not related to Betaproteobacteria or Mollicutes: clades encompassing those bOTUs are drawn as collapsed (triangles) and the number of bOTUs clustering within these clades is given. The tree shows the topology obtained with the Bayesian method. Branches with Bayesian posterior probabilities (BPP) ≥0.95 and ML bootstrap support values ≥70 are thickened; asterisks (*) indicate branches with BPP ≥0.95 but ML bootstrap support values <70; ML bootstrap support values ≥70 are shown for branches having BPP <0.95. Sequences generated in this study are in bold.

Table S1 | Effects of plant species and P treatment on alpha diversity (ANOVA) Statistic testing for differences in α-diversity between Arabidopsis and Petunia root bacterial and fungal root microbiota in varying levels of P availability was performed using analysis of variance (ANOVA). ANOVA was used to test for species- (S), treatment- (T) or their interaction (SxT) effects on OTU richness, Shannon diversity and Sheldon evenness. Alpha diversity metrics were determined on data with a common sequencing depth of 15’000 sequences per sample. Significant F-tests are indicated in bold.

species treatment interaction Metric F P F P F P richness 14.826 0.000396 9.565 0.000378 0.822 0.446615 diversity 18.255 0.000108 7.432 0.001724 0.749 0.479160

Bacteria evenness 18.233 0.000109 5.203 0.009581 0.540 0.586555

richness 245.820 <2e16 3.704 0.03446 8.496 0.00095 diversity 1078.151 <2e16 0.004 0.996 1.000 0.378 Fungi evenness 407.092 <2e16 3.107 0.0569 4.540 0.0175

Table S2 | Effects of plant species and P treatment on community composition (PERMANOVA) Statistic testing for differences in beta-diversity between Arabidopsis and Petunia root bacterial and fungal root microbiota in varying levels of P availability was performed using permutational analysis of variance (PERMANOVA). PERMANOVA was used to test for species- (S), treatment- (T) or their interaction (SxT) effects on community composition based on Bray-Curtis dissimilarities. Significance is indicated in bold.

species treatment interaction R2 P R2 P R2 P Bacteria 0.1412 0.001 0.07188 0.004 0.05336 0.023 Fungi 0.5306 0.001 0.03846 0.066 0.03748 0.069

Table S3 | Effects P treatment on species-specific community compositions (PERMANOVA) Statistic testing for differences in beta-diversity as a function of varying levels of P availability was performed separately for Arabidopsis and Petunia root microbiota using permutational analysis of variance (PERMANOVA). PERMANOVA was used to test for treatment effects on community composition based on Bray-Curtis dissimilarities. Significance is indicated in bold.

Arabidopsis Petunia R2 P R2 P Bacteria 0.15022 0.001 0.14124 0.003 Fungi 0.21702 0.002 0.132266 0.057

Table S4 | Statistics from identifying phosphate sensitive microbes This additional file (separate XLSX table) reports statistic results from the edgeR analyses of P sensitive bOTUs and fOTUs in Arabidopsis and Petunia. All OTUs with FDR < 0.05 are listed with their taxonomy assignments, log fold-change (FC), log counts per million (CPM), the likelihood ratio (LR) test and probability (P) values and false-discovery rate (FDR) corrected P values. In addition, the logCPM abundances of each OTU in Arabidopsis, Petunia and soil in low, medium and high P conditions are given.

Table S5 | Network characteristics This additional file (separate XLSX table) reports characteristics from the co-occurrence network analyses presented in Figure 7. All OTUs of the networks are listed with their assignments, module assignments and whether the present keystone OTUs in Arabidopsis and Petunia.

Methods S1 | Microbiota profiling and analysis

DNA extraction and PCR DNA was extracted from the root and soil samples using the NucleoSpin Soil kit (Macherey-Nagel, Düren, Germany). Roots were lyophilized, placed in 2 ml centrifuge tubes, to which one metal bead was added. Samples were ground to a fine powder for 2 min at 25 Hz using a Retsch TissueLyser (Retsch, Haan, Germany). Buffer SL1 and enhancer solution SX was used. DNA was quantified with Picogreen and diluted to 1 ng/µl for soil samples and 10 ng/µl for root samples. We first evaluated several PCR approaches to compare the levels of co-amplified plant sequences, abundance of AMF and general fungal diversity in Petunia roots: 1) ITS1F (Gardes & Bruns, 1993) and ITS2 (White et al., 1990), 2) fITS7 (Ihrmark et al., 2012) and ITS4 (White et al., 1990) and 3) ITS1F with the reverse complement of fITS7. The Notes S1 contain the bioinformatic script, barcode-to-sample assignments, input data, analysis script and markdown report for the comparison of the PCR approaches. Based on this analysis, the PCR primers ITS1F and ITS2 were chosen to study the fungal community. PCR primers 799F (Chelius & Triplett, 2001) and 1193R (Bodenhausen et al., 2013) were used to amplify hypervariable regions V5, V6 and V7 of the 16S rRNA gene for the bacterial community. To confirm the fungal community results from Illumina sequencing, we prepared an additional library for SMRT sequencing where the entire ITS region was amplified with the PCR primers ITS1F and ITS4. The barcode-to-sample assignment can be taken from the sample table included in Notes S3. PCR reactions for each library were prepared in similar way. The reaction volume was 20 µl, and contained 1x 5Prime Hot Master mix 200 nM of each primer and 0.3% BSA. Cycling programs consisted of an initial denaturation at 94°C for 2 minutes (16S) or 3 minutes (ITS, SMRT), followed by 30 cycles of denaturation at 94°C for 30 seconds (16S), 45 seconds (ITS, SMRT), annealing at 55°C (16S, SMRT) or 50°C (ITS) for 30 seconds (16S) or 1 minute (ITS, SMRT), and elongation at 65°C (16S) or 72°C (ITS, SMRT) for 30 seconds (16S) or 1 minute (SMRT) or 90 second (ITS). PCR were run in triplicate with a negative control for each primer mix and verified on a 1% agarose gel. Triplicate PCR products were pooled, cleaned with PCR clean-up kit (Macherey-Nagel, Düren, Germany), quantified using a Quant-iT Picogreen dsDNA Assay Kit (Invitrogen, Eugene, OR USA) on a Varian Cary Eclipse fluorescence spectrometer (Agilent Technologies, Santa Clara, CA USA). Equimolar amount of each PCR product were combined. For 16S library preparation, the smaller band which corresponds to 16S rRNA gene was selected with the gel extraction kit (Macherey-Nagel, Düren, Germany). Pooled PCR products were concentrated with Agencourt AMPure XP kit (Beckman Coulter, Brea, CA, USA) and quantified with Qubit dsDNA HS assay on a Qubit 2.0 fluorometer (Invitrogen, Eugene, OR USA) and combined with other libraries before sequencing.

Sequencing and Bioinformatics The MiSeq libraries were prepared at the Functional Genomics Center Zurich (www.fgcz.ch) with the NEBNext DNA library Ultra kit (New England Biolabs, Ipswich, MA, USA). After end-repairing and polyadenylating the amplicons, NEBNext Adaptor were ligated. The ligated samples were run on a 2% agarose gel and the desired fragment length were excised (50bp +/- the target fragment length). DNA from the gel was purified with MinElute Gel Extraction Kit (Qiagen, Hilden, Germany). Fragments containing Nebnext adapters on both ends were selectively enriched with PCR using 4 cycles. Quality and quantity of the enriched libraries were validated using Qubit® (1.0) Fluorometer and Tapestation (Agilent Technologies, Santa Clara, CA USA). The libraries were normalized to 4nM in Tris-Cl 10 mM, pH 8.5 with 0.1% Tween 20. The libraries were sequenced at FGCZ on the Illumina MiSeq Personal Sequencer (Illumina, San Diego, CA, USA) using a 600 cycle v3 Sequencing kit (Cat n° MS-102-3003), in paired-end 2x 300 bp mode. The PacBio SMRT bell library was prepared at the FGCZ using the DNA Template Prep Kit 1.0 (Pacific Biosciences p/n 100-259-100), following the manufacturer’s instructions. After DNA quantification with a Qubit Fluorometer dsDNA Broad Range assay (Life Technologies p/n 32850), the fragment size distribution was assessed with a Bioanalyzer 2100 12K DNA Chip assay (Agilent p/n 5067-1508). 500-750ng of amplicon DNA was DNA-damage repaired and end-repaired using polishing enzymes. A blunt end ligation reaction followed by exonuclease treatment was performed to create the SMRT bell template. The library was quality inspected and quantified on the Bioanalyzer 12Kb DNA Chip and on a Qubit Fluorometer (Life technologies) respectively. A ready to sequence SMRT bell-Polymerase Complex was created using the Sequel binding kit 2.0 (Pacific Biosciences p/n 100-862-200) according to the manufacturer instructions. The Pacific Biosciences Sequel instrument was programmed to sequence the sample on 1 Sequel™ SMRT® Cell 1M v2 (Pacific Biosciences p/n 101-008-000), taking 1 movie of 10 hours using the Sequel Sequencing Kit 2.0 (Pacific Biosciences p/n 101-310-400). After the run, the quality of the sequencing data was checked using the “run QC module” of the PacBio SMRT Link software. DNA sequence analysis were performed at the Scientific Compute Cluster Euler, at ETH, Zurich. The MiSeq data was processed similar to the workflow described in Hartman et al. (Hartman et al., 2017). Briefly, to improve merging, read ends were trimmed by run if needed (seqtk v.1.2-r94, https://github.com/lh3/seqtk.git) and subsequently merged (FLASH v.1.2.11; (Magoč & Salzberg, 2011) into amplicons. In a next step, CUTADAPT v1.4.2 (Martin, 2011) was used to trim off barcode and primer sequence and demultiplex amplicons based on barcode information. Demultiplexed reads were subsequently quality filtered using prinseq-lite v0.20.4 (Schmieder & Edwards, 2011). The quality filtered sequences were clustered into operational taxonomic units (OTUs, ≥97% sequence similarity) using usearch v10.0.240 (Edgar, 2013). SINTAX (http://dx.doi.org/10.1101/074161) was used for taxonomic assignments using either SILVA 16S v128 (Quast et al., 2013) for the bacterial community or UNITE v7.2 (Abarenkov et al., 2010) database for the fungal community. The SMRT sequencing data was processed following Schlaeppi et al. (2016). In brief, ≥5- pass ‘reads of insert’ (ROI; also, circular consensus sequences CCS) were extracted from the raw data 8) using default parameters. The software mothur v.1.34.4 (Schloss et al., 2009) and flexbar (Dodt et al., 2012) were employed for quality filtering and demultiplexing, respectively. Some raw reads were affected by multi-primer artefacts (Tedersoo et al., 2018)and we employed Usearch (v10.0.240, (Edgar, 2013) to detect and discarded these reads containing primer sequences within the read. OTU clustering and taxonomic annotation were conducted using the same tools as for the MiSeq data. Bioinformatics scripts and report files are available as Notes S2. The raw sequencing data of the two MiSeq runs and the SMRT sequencing are available from the European Nucleotide Archive under the study accession PRJEB27162.

Identification of endobacteria OTUs by phylogenetic placement To identify endobacteria OTUs, we pre-selected candidates in the microbiome dataset using two approaches and then validated their representative sequences by fine mapping to a reference tree of known endobacteria sequences. For the latter we created a custom database with curated endobacteria 16S rDNA references containing published sequences of Burkholderia-related endobacteria (BRE), such as Candidatus Glomeribacter gigasporarum and Mycoavidus cysteinexigens, and Mycoplasma-related endobacteria (MRE) retrieved from Glomeromycotina, such as Candidatus Moeniiplasma glomeromycotorum, Endogonaceae (Mucoromycotina) and Mortierellomycotina. We pursued two alternative strategies to identify candidate endobacteria OTUs. The first approach was based on sequence clustering and secondly, we employed co-occurrence characteristics from network analysis (e.g., high degree of co-occurrence between fungal and bacterial OTUs) and we explored if this of information would be useful to identify candidate endobacteria OTUs. For the first strategy, we employed usearch (v8) to map the curated endobacteria sequences to the representative bacteria OTUs (bOTU) sequences of the microbiome dataset. We allowed up to 10% sequence divergence to account for the high variability among 16S rDNA endobacteria sequences, in particular from MRE, known to display high level of sequence diversity (Desirò et al., 2018). This approach yielded 22 candidate endobacteria OTUs, which we then placed into the reference tree. For the second strategy, we searched the co-occurrence characteristics from network analysis as follows: we first identified all fungal OTUs (fOTUs) assigned to Glomeromycotina and Mortierellomycotina (we did not identify fOTUs assigned to Endogonaceae; may be linked to the use of universal ITS primers, which tend not to capture this family, (Tedersoo et al., 2016), the fungal lineages known to harbor BRE and/or MRE, and then selected all bOTUs that significantly co-occur with them (Spearman’s rho > 0.7 and P < 0.001). This approach yielded 129 candidate endobacteria OTUs, which we then placed into the reference tree. Placement to a common phylogenetic tree was achieved by aligning candidate endobacteria OTUs (from clustering or network approaches) to an endobacteria reference dataset. Sequences were aligned with MAFFT (Katoh & Standley, 2013) Phylogenetic analyses were carried out with MrBayes v.3.2.6 (Ronquist et al., 2012) and RAxML v.8.2.4 (Stamatakis, 2014). Prior to Bayesian phylogenetic reconstructions, best-fit nucleotide substitution models were estimated with jModelTest v.2.1.9 (Darriba et al., 2012). Bayesian analyses were performed running the Markov chain Monte Carlo for 10 million generations under the TrN+I+G nucleotide substitution model. Maximum likelihood analyses were conducted with the automatic ‘bootstrapping’ option under the GTRCAT nucleotide substitution model. For tree inference, Betaproteobacteria and Mollicutes reference sequences were included together with outgroup sequences belonging to . Candidate endobacteria OTUs were considered as BRE or MRE OTUs if they clustered within an endobacteria clade in the reference phylogenetic tree. Command line and analysis code in R (including markdown report) as well as the database with curated endobacteria 16S rDNA reference sequences are available as Notes S4.

Notes S1 | Comparison of PCR approaches This additional zip archive comprises the bioinformatic command line code, input data and R script for the comparison of the PCR approaches. It also contains the R markdown output as a detailed PDF-report of ITS PCR approaches.

Notes S2 | Bioinformatic scripts This additional zip archive comprises all bioinformatic command line scripts including all individual parameters and support files that were utilized to process the raw sequencing data from the MiSeq- and SMRT-sequencing data.

Notes S3 | Data analysis in R This additional zip archive comprises the R scripts, functions and support files that document and permit to reproduce the main data analysis in R. The main data analysis covers the steps illustrated in Fig. S1.

Notes S4 | Mapping endobacteria This additional zip archive comprises the command line and analysis code in R as well as the database with curated endobacteria 16S rDNA reference sequences. In addition, it contains the R markdown output as a detailed PDF-report of mapping the OTUs to the endobacteria database.

Notes S5 | Comparison of ITS profiling approaches This additional zip archive comprises the R code (and its markdown report), which was used to compare the MiSeq- versus the SMRT-sequencing based profiling of fungal communities. It contains the R markdown output as a detailed PDF-report for the comparison of ITS profiling approaches.

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