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1 Supplementary material for Groundwater chemistry determines the prokaryotic community structure of waterworks sand filters 5 6 Christian N. Albers*, Lea EllegaardJensen, Christoffer B. Harder, Søren Rosendahl, 7 Berith E. Knudsen, Flemming Ekelund, Jens Aamand Page S2. Figure S1, Location of the sampled waterworks in Denmark. Page S3. Figure S2, images of filter materials. Page S5. Figure S3, rarefaction curves. Page S6. Figure S4, distribution of bacterial phyla in the analysis with 558 sequences from each of 22 waterworks samples. Page S7. Figure S5, Prokaryotic groups in the total dataset. Page S8. Table S1, construction of waterworks and filters. Page S9. Table S2, physical and chemical characteristics of filter material and water. Page S10. Table S3, primer set coverage of eukaryotic phyla. Page S11. Table S4, relative abundance of the bacterial phyla divided into classes, orders and families. S1
2 Figure S1. The location of the sampled waterworks in Denmark. Only the initial three letters of each waterworks name are shown. UTMcoordinates of waterworks (UTMzone 32): Astrup ( , ); Aike ( , ); Vejle S ( , ); Svenstrup ( , ); Odense ( , ); Lindved ( , ); Lunde ( , ); Landet ( , ); Islevbro ( , ); Søndersø ( , ); Hvidovre ( , ) S2
3 29 S3
4 Figure S2. Images of all sampled filter materials. Each image is ~8 mm from left to right. Each row of images is one waterworks. Names from Table 1 are shown in the lower left corner. S4
5 Figure S3. Rarefaction curves for the analysis with 2147 sequences from each of 18 waterworks sand filter samples. Only the initial three letters of each waterworks name are shown S5
6 Figure S4. Distribution of bacterial phyla (Proteobacteria separated into classes) by percent of total number of sequences from each filter sample in the analysis with 558 sequences from each of 22 waterworks samples. For clarity, taxonomic groups not represented by at least 1 % in at least one sample are not included. Upper: Top samples (010 cm of first filter and intermediate sample for the Astrup filter). Lower: Samples taken at approximately 50% total filter depth (Table 1). Only the initial three letters of each waterworks name are shown. 45 S6
7 Figure S5. Prokaryotic groups in sand filters from 11 Danish waterworks (22 filter samples). Bacterial phyla (Proteobacteria separated into classes) are shown as a percentage of the total numbers of OTUs (left) or the total number of sequences (right) S7
8 Table S1. Construction of each waterworks and its filters. Micrographs of filter samples are available in Supplementary Figure S2. All filters were backwashed regularly with 25 days intervals in most waterworks, except in Islevbro and Søndersø waterworks which had longer intervals (1017 days). The retention times of the filters are calculated based on a porosity of the filter material of At Lunde waterworks we could only obtain a top sample and at Astrup waterworks which had two filters in series, an additional 50 cm sample of the 1st filter was taken as an intermediate sample. Waterworks Filter sample name Parent filter material** Aquifer type*** Name Filters* Ret. Time (min) 1 st 010cm 1 st 50cm 2 nd 010cm 1 st filter 010 cm 1 st filter 50 cm 2 nd filter 010 cm Astrup BF, TF 7 T I D Qrz (8) Qrz Qrz (16) Sand (51143) Aike PF, TF 7 T D Chalk (21) Chalk (21) Sand (57166) Vejle S BF, SF 8 T D Anth (7) Anth/qrz Sand (2236) Svenstrup BF, TF 8 T D Qrz (4) Qrz (4) Sand (2946) Odense H BF, SF 26 T D Anth (26) Qrz Sand+chalk (4490) Lindved BF, SF 52 T D Anth (34) Qrz Chalk+sand (25120) Lunde PF, SF N.A. T Chalk (3) Sand (3956) Landet BF, SF 23 T D GAC (6) GAC/qrz Sand (1425) Islevbro BF, SF 11 T D Anth (25) Anth Chalk (1193) Søndersø BF, SF 6 T D Anth (16) Qrz Chalk (24120) Hvidovre BF, SF 9 T D Qrz (40) Qrz Chalk (770) N.A. Data not available, but filter is designed for retention times between 5 and 10 minutes. *BF, basin filter; PF, pressurized filter; SF, single filter; TF, two filters; T, topsample; I, intermediatesample; D, depthsample. The filter height was ~1 m in the basin filters and up to 2 m in the pressurized filters. ** Original filter material in most cases was coated with Fe and/or Mn oxides. Qrz, quartz sand; Anth, anthracite; GAC, granulated activated carbon; / denotes a mixture. Chalk is crushed bryozo and coral chalk (Nevtraco, 98% CaCO 3 ). Age in years of filter material is in parentheses. The age for the two 1 st filter samples of each waterworks is identical. *** Sand: Both sand and gravel. Depth of the filters used to abstract water from the aquifer in meters below surface is in parantheses. Depth ranges are for all wells in use, varying from 3 to ~50 wells. S8
9 Table S2. Main physical and chemical characteristics of filter material and water at each waterworks (full version of Table 1). In all cases, treated water contained less than 0.1 mg/l Fe and less than 0.02 mg/l of both Mn and ammonium. Data on filter materials and raw water are from this study. Data on treated water and methane in raw water from the year of sampling (2011) were derived from the national Jupiter database (see Materials and Methods). BET is the specific surface area (see Materials and Methods). Filter material Raw water Treated water Fe Mn BET Fe Mn CH 4 NH 4 + ph dh NVOC O 2 NO 3 Ptot Ca 2+ Mg 2+ mg/g mg/g m 2 /g mg/l mg/l mg/l AstrupT Astrup I < Astrup D AikeT AikeD VejleT VejleD SvenstrupT SvenstrupD OdenseT OdenseD LindvedT LindvedD < < LundeT LandetT LandetD IslevbroT IslevbroD SøndersøT Søndersø D HvidovreT HvidovreD N.A., not analyzed N.A <0.1 < <0.1 < < S9
10 Table S3. Primer set (MPRK341F and MPRK806R) coverage tested in the SILVA database ( silva.de/search/testprime/). The coverage is the fraction covered by both primers. Phyla shown in Figure 1 are included in the table as well as the overall coverage for Bacteria and Archaea (including the Crenarchaeota). Prokaryotic group Coverage (%) BACTERIA (total) 84.9 Planctomycetes 2.6 Nitrospirae 90.5 Gemmatimonadetes 88.2 Proteobacteria 91.6 Alpha 91.7 Beta 92.0 Gamma 91.6 Delta 89.7 Chloroflexi 38.0 Actinobacteria 83.3 Acidobacteria 91.5 ARCHAEA (total) 80.3 Crenarchaeota S10
11 Table S4. Relative abundance of the bacterial phyla in the sand filter samples given as percent of the number of sequences in the standardized data set with 18 filter samples. The phyla are further divided into classes, orders and families in cases where these could be assigned. Only orders and families with greater abundance than 1% in at least one sample has been given a column of its own. Phylum Proteobacteria Class Alphaproteobacteria Order Rhizobiales Sphingomonadales Rhodospirillales Parvularculales Family Hyphomicrobiaceae Nordella Xanthobacteraceae Methylobacteriaceae Methylocystaceae Phyllobacteriaceae Parvularculaceae LanT LanD LunT OdeT LinT AikD AstI AstD IslT IslD SønT SønD VejT VejD SveT SveD HviT HviD S11
12 Phylum Proteobacteria Class Order Nitrosomonadales Betaproteobacteria Nitrosomonadales Burkholderiales Burkholderiales Hydrogenophilales Bdellovibrionales Deltaproteobacteria Desulfuromonadales Myxococcales GRWP3330 Gammaproteobacteria Legionellales Methylococcales Family Gallionellaceae Nitrosomonadaceae Comamonadaceae Methylococcaceae 83 LanT LanD LunT OdeT LinT AikD AstI AstD IslT IslD SønT SønD VejT VejD SveT SveD HviT HviD S12
13 Phylum Proteobac. Acidobacteria Actinobacteria Class Order Gammaproteobac. Acidobacteria Actinobacteria Xanthomonadales Acidobacteriales Holophagae Family Acidobacteriaceae Acidimicrobineae Corynebacterineae Frankineae Kineosporiineae Micrococcineae Micromonosporineae Pseudonocardineae Propionibacterineae 87 LanT LanD LunT OdeT LinT AikD AstI AstD IslT IslD SønT SønD VejT VejD SveT SveD HviT HviD S13
14 Phylum Chloroflexi Gemmatimonadetes Nitrospirae Planctomycetes Cyanobacteria Bacteroidetes Chlamydiae Firmicutes Spirochaetae Verrucomicrobia Chlorobi Archaea Unassigned Class Nitrospira Chlamydiae Spirochaetes Opitutae Chlorobia Order Nitrospirales Chlamydiales Spirochaetales Chlorobiales Family Nitrospiraceae 89 LanT LanD LunT OdeT LinT AikD AstI AstD IslT IslD SønT SønD VejT VejD SveT SveD HviT HviD Domain most sequences belonged to the Crenarchaeota S14
experimental factor Poly- mer Type
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