Supplementary Information
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1 Supplementary Information 2 3 Homogeneous selection promotes microdiversity in the glacier-fed stream 4 microbiome 5 6 Stilianos Fodelianakis1, Alex D. Washburne2,3, Massimo Bourquin1, Paraskevi Pramateftaki1, 7 Tyler J. Kohler1, Michail Styllas1, Matteo Tolosano1, Vincent De Staercke1, Martina Schön1, 8 Susheel Bhanu Busi4, Jade Brandani1, Paul Wilmes4, Hannes Peter1 & Tom J. Battin1 9 10 1Stream Biofilm & Ecosystem Research Lab, ENAC Division, Ecole Polytechnique Federale de 11 Lausanne 12 2Department of Microbiology and Immunology, Montana State University, USA 13 3Selva Analytics, LLC, Bozeman, Montana, USA 14 4Systems Ecology Research Group, Luxembourg Centre for Systems Biomedicine, University of 15 Luxembourg, Esch-sur-Alzette, Luxembourg 16 17 Supplementary Results 18 19 Detailed taxonomic diversity 20 The communities in the different glacier-fed streams were both rich in terms of the 21 number of detected SVs and in terms of the number of taxonomic groups. We detected 8186 SVs 22 in total and 640 ± 60 SVs per glacier-fed stream on average. In terms of taxonomy, there were 36 23 assigned bacterial Phyla, 112 Classes, 162 Orders, 156 Families and 159 Genera present in the 24 sampled communities. The most diverse and abundant Phyla were Proteobacteria (3267 SVs, 25 34.4-90.2% of total cells per sample), Bacteroidetes (1324 SVs, 1.8-31.9% of total cells per 26 sample) and Planctomycetes (728 SVs, 0.5-9.9% of total cells per sample) and the most diverse 27 and abundant Classes within these three phyla were Betaproteobacteria (1429 SVs, 15.2-78.8% 28 of total cells per sample), Saprospirae (481 SVs, 0.09-13.4% of total cells per sample) and 29 Planctomycetia (539 SVs, 0.4-8.5% of total cells per sample), respectively (Fig. S6). 30 31 Core microbiome 32 The core microbiome, which we defined as the taxonomic units present in at least one 33 sample at every reach, included 11 Phyla, 20 Classes, 29 Orders, 18 Families and 11 Genera 34 (Fig. 1, Table S2). The 11 Genera within the core microbiome included a total of 1133 SVs 35 (13.9% of the total SVs) that comprised on average 34.8% (13.6 – 62%) of the total cells per 36 gram of dry sediment per community. Six core Genera were taxonomically affiliated to 37 Betaproteobacteria; Methylotenera, Polaromonas, Rhodoferax, Leptothrix, Methylibium and 38 Rubrivivax, containing 541 SVs and comprising on average 25.1% of the total cells per gram of 39 dry sediment per community. Two core Genera were affiliated to Planctomycetes; Gemmata and 40 Planctomyces, containing 258 SVs and comprising on average 1.3% of the total cells per gram of 41 dry sediment per community. Two core Genera were affiliated to Alphaproteobacteria; 42 Hyphomicrobium and Novosphingobium, containing 113 SVs and comprising on average 3.5% 43 of the total cells per gram of dry sediment per community. One core Genus was affiliated to 44 Bacteroidetes; Flavobacterium, containing 205 SVs and comprising on average 3% of the total 45 cells per gram of dry sediment per community, and one Genus was affiliated to Nitrospirae; 46 Nitrospira, containing 20 SVs and comprising on average 1.9% of the total cells per gram of dry 47 sediment per community. 48 49 Environmental drivers of bacterial β-diversity 50 Using distance-based redundancy analysis and a forward stepwise model building, we 51 found that seven of the recorded environmental parameters, namely conductivity, dissolved 52 oxygen, latitude, chl-α content, pH, water temperature and turbidity, could collectively explain 53 43.5% of the variance in the Bray-Curtis (BC) dissimilarity among the samples (Fig. S4, Table 54 S6). Conductivity had the highest proportion of variance explained (14.1%), followed by 55 dissolved oxygen (8.1%), latitude (5.7%), chl-α content (5.6%) and pH (4.3%) while the rest of 56 the variables explained low proportions of variance (1.4-2.3%). 57 The samples had a distinct clustering pattern along the first constrained axis that 58 explained 18.8% of the total BC variance (Fig. S4). The left axis side was characterized by a 59 low-dispersion cluster of samples from turbulent streams with high conductivity, pH and 60 dissolved oxygen, and the right axis side was characterized by a high-dispersion cluster of 61 samples from warmer streams with higher chl-α content. The second constrained axis explained 62 8.7% of total BC variance and was mostly associated with latitude, suggesting that a part of 63 community variability can be explained by geographic legacies. Samples from the same stream 64 but at different reaches (UP and DN) clustered mostly together and the variance explained by the 65 factor “reach” was non-significant. 66 Supplementary Figures 67 68 Figure S1. The location of the sampled glacier-fed streams (GFS) at the Southern Alps of 69 New Zealand. GFS are assigned numbers from 1 to 21 (excluding 4) for operational purposes. 70 Map colors correspond to the altitude as per the legend on the right. Mantel correlation Mantel -0.002 0.000 0.002 0.004 0.000 0.002 0.004 0.006 0.008 0.010 71 Distance class index 72 Figure S2. Mantel correlogram between phylogenetic distances and niche distances among 73 all the Sequence Variants. Filled squares correspond to significant correlations and empty 74 squares correspond to non-significant correlations. The phylogenetic distances were Hellinger- 75 transformed before the correlations. The niche distances were calculated as the Euclidean 76 distances of standardized niche optima regarding the environmental parameters that explained a 77 significant proportion of β-diversity as per the db-RDA analysis, namely conductivity, dissolved 78 oxygen, latitude, chl-α, pH, water temperature and turbidity. 0.7 0.8 0.5 0.6 0.3 0.4 0.4 0.5 0.6 Relative abundance of clades under selection under clades of abundance Relative Relative species richness of clades under selection clades of richness species Relative 1e+05 5e+05 5e+06 5e+07 1e+05 5e+05 5e+06 5e+07 A −1 B −1 Cells gram of dry sediment Cells gram of dry sediment 79 80 Figure S3. The inverse relationship between the relative species richness (A) and the 81 relative abundance (B) of phylogenetic clades under environmental selection and total 82 bacterial cell density A. The relative species richness of the clades under environmental 83 selection (y-axis) as a function of total bacterial cell density (x-axis, in log-scale). B. The 84 relative abundance of the clades under environmental selection (y-axis) as a function of 85 total bacterial cell density (x-axis, in log-scale). Adjusted R2= 0.252, and 0.282, for panels A 86 and B, respectively. For both panels p<<0.001 and n=119. 88 88 77 99 8 21 9 77 21 9 9 77 1 9 21 21 21 Reach 2020 lat 222 2 DN 2 202020 20 6 UP 3 10 DO 17 66 3 101818 17 11311101918 1810 turb 1717 13 13 1 1010191818 17 13 6 0 1 1919 pH 17 6 1111 19 Conductivity (μS cm-1) 3 3 Cond 131313 12 1111 125 3 1212 1212 water_temp 11 15 100 15 15 Chla 15 75 15 50 1616 -1 1616 16 25 55 55 CAP2 (19.2% of fitted, 8.7% of total variance) oftotal 8.7% fitted, (19.2% of CAP2 1414 -1.0 -0.5 0.0 0.5 1.0 CAP1 (41% of fitted, 18.8% of total variance) 87 88 Figure S4. The constrained ordination plot of the distance-based redundancy analysis on 89 the BC dissimilarity of bacterial communities from all the sampled streams. Factors 90 included in the model are plotted as vectors. Samples are colored based on conductivity that was 91 the factor explaining most of the BC variance, as per the legend on the middle right. Sample 92 symbols are given according to the reach as per the legend on the upper right. Numbers above 93 samples indicate the location of the stream as per Figure S1. Axes are scaled based on the 94 variance they explain. Cond: conductivity, DO: dissolved oxygen, lat: latitude, Chla: chl-α 95 content, water_temp: water temperature, turb: turbidity. 96 97 Figure S5. Flow cytometry scatterplot of green (FITC-H – x-axis) versus red (PerCP-H – y- 98 axis) fluorescence of a typical sediment fixed extract. The polygon delineates the gate used for 99 counting cells, which is based on events with disproportionately more green fluorescence 100 compared to red fluorescence because of SybrGreen staining. On the contrary, debris is shown 101 on the middle left as a dense cluster of events with higher red:green fluorescence ratio. 1,300 1,200 1,100 1,000 900 800 700 600 NumberSequence Variants of 500 400 300 200 100 0 -1000 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 102 Sequencing Depth 103 Figure S6. The rarefaction curves of the generated 16S rRNA gene amplicons from all the 104 samples. The number of sequences is shown on the x-axis and the number of observed sequence 105 variants (SVs) are shown on the y-axis. Rarefaction was performed at intervals of 100 sequences 106 with 10 permutations per sequence interval at a sequencing depth of up to 10,000 reads. The 107 range of the obtained values is represented with boxplots. Different colors represent different 108 samples. GL1 GL2 GL3 GL5 GL6 GL7 GL8 GL9 GL10 GL11 GL12 GL13 GL14 GL15 GL16 GL17 GL18 GL19 GL20 GL21 0.00 −0.25 Class [Chloracidobacteria] [Pedosphaerae] [Saprospirae] Alphaproteobacteria −0.50 Betaproteobacteria Epsilonproteobacteria Flavobacteriia Relative abundance Relative Gammaproteobacteria Others −0.75 Planctomycetia −1.00 DN UP DN UP DN UP DN UP DN UP DN UP DN UP DN UP DN UP DN UP DN UP DN UP DN UP DN UP DN UP DN UP DN UP DN UP DN UP DN UP 109 110 Figure S7.