Applied Microbiology and Biotechnology

Influence of water management on the active root-associated microbiota involved in arsenic, iron and sulfur cycles in rice paddies --Manuscript Draft--

Manuscript Number: AMAB-D-17-00287R2 Full Title: Influence of water management on the active root-associated microbiota involved in arsenic, iron and sulfur cycles in rice paddies Article Type: Original Article Section/Category: Environmental biotechnology Corresponding Author: Lucia Cavalca Universita degli Studi di Milano ITALY Corresponding Author Secondary Information: Corresponding Author's Institution: Universita degli Studi di Milano

Corresponding Author's Secondary Institution: First Author: Sarah Zecchin, PhD First Author Secondary Information: Order of Authors: Sarah Zecchin, PhD Anna Corsini, PhD Maria Martin, PhD Lucia Cavalca Order of Authors Secondary Information:

Funding Information: Ministero dell’Istruzione, dell’Università e Dr. Sarah Zecchin della Ricerca (IT) Ministero dell’Istruzione, dell’Università e Not applicable della Ricerca (PRIN 2010JBNLJ7-004)

Abstract: In recent years the role of microorganisms inhabiting rice rhizosphere in promoting arsenic contamination has emerged. However, little is known concerning the species and metabolic properties involved in this phenomenon. In this study, the influence of water management on the rhizosphere microbiota in relation to arsenic dissolution in soil solution was tested. Rice plants were cultivated in macrocosms under different water regimes: continuous flooding, continuous flooding with a 2 weeks-period drainage before flowering and dry soil watered every 10 days. The active bacterial communities in rhizosphere soil and in rhizoplane were characterized by 16S rRNA pyrosequencing. An in-depth analysis of microbial taxa with direct or indirect effects on arsenic speciation was performed and related contribution was evaluated. Continuous flooding promoted high diversity in the rhizosphere, with the plant strongly determining species richness and evenness. On the contrary, under watering the communities were uniform, with little differences between rhizosphere soil and rhizoplane. Arsenic-releasing and arsenite-methylating bacteria were selected by continuous flooding, where they represented 8 % of the total. On the contrary, bacteria decreasing arsenic solubility were more abundant under watering, with relative abundance of 10 %. These values reflected arsenic concentrations in soil solution, respectively 135 µg L-1 and negligible in continuous flooding and under watering. When short-term drainage was applied before flowering, intermediate conditions were achieved. This evidence strongly indicates an active role of the rhizosphere microbiota in driving arsenic biogeochemistry in rice paddies, influenced by water management, explaining

Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation Manuscript Click here to download Manuscript Zecchin_et_al_AMB_Unmarked_Revision2.doc Click here to view linked References

1 Influence of water management on the active root-associated microbiota

1 2 involved in arsenic, iron and sulfur cycles in rice paddies 2 a a b a* 3 3 Sarah Zecchin , Anna Corsini , Maria Martin and Lucia Cavalca 4 5 4 6 5 7 8 6 aDipartimento di Scienze per gli Alimenti, la Nutrizione e l'Ambiente (DeFENS), Università degli 9 10 7 Studi di Milano, Milano, Italy 11 12 8 13 b 14 9 Department of Agriculture, Forest and Food Science, University of Turin, Turin, Italy 15 16 10 17 11 18 19 12 * Corresponding author 20 21 13 E-mail address: [email protected] 22 23 14 Telephone: +39 02 503 19116 24 25 15 Fax: +39 02 503 19238 26 27 16 28 17 29 30 18 Authors E-mail addresses 31 32 19 [email protected], [email protected], [email protected] 33 34 20 35 36 21 37 22 38 39 23 40 41 24 42 43 25 44 45 26 46 47 27 48 28 49 50 29 51 52 30 53 54 31 55 56 32 57 58 33 59 34 60 61 35 62 63 1 64 65 36 Abstract

1 37 2 38 In recent years, the role of microorganisms inhabiting rice rhizosphere in promoting arsenic 3 4 39 contamination has emerged. However, little is known concerning the species and metabolic 5 6 40 properties involved in this phenomenon. In this study, the influence of water management on the 7 8 41 rhizosphere microbiota in relation to arsenic dissolution in soil solution was tested. 9 10 42 Rice plants were cultivated in macrocosms under different water regimes: continuous flooding, 11 12 43 continuous flooding with a 2 weeks-period drainage before flowering and dry soil watered every 10 13 44 days. The active bacterial communities in rhizosphere soil and in rhizoplane were characterized by 14 15 45 16S rRNA pyrosequencing. An in-depth analysis of microbial taxa with direct or indirect effects on 16 17 46 arsenic speciation was performed and related contribution was evaluated. 18 19 47 Continuous flooding promoted high diversity in the rhizosphere, with the plant strongly determining 20 21 48 species richness and evenness. On the contrary, under watering the communities were uniform, with 22 23 49 little differences between rhizosphere soil and rhizoplane. Arsenic-releasing and arsenite- 24 50 methylating bacteria were selected by continuous flooding, where they represented 8 % of the total. 25 26 51 On the contrary, bacteria decreasing arsenic solubility were more abundant under watering, with 27 28 52 relative abundance of 10 %. These values reflected arsenic concentrations in soil solution, 29 30 53 respectively 135 µg L-1 and negligible in continuous flooding and under watering. When short-term 31 32 54 drainage was applied before flowering, intermediate conditions were achieved. 33 34 55 This evidence strongly indicates an active role of the rhizosphere microbiota in driving arsenic 35 56 biogeochemistry in rice paddies, influenced by water management, explaining amounts and 36 37 57 speciation of arsenic often found in rice grains. 38 39 58 40 41 59 42 43 60 44 61 45 46 47 62 Keywords 48 63 Rice rhizosphere microbiota; arsenic bacteria; sulfate-reducing bacteria; iron-reducing bacteria; 49 50 64 sulfur-oxidizing bacteria; iron-oxidizing bacteria. 51 52 65 53 54 66 55 56 67 57 58 68 59 69 60 61 70 62 63 2 64 65 71 Introduction

1 72 2 73 Arsenic contamination of groundwater resources and soils represents an issue in many areas of the 3 4 74 world (Singh et al. 2015; Heikens 2006). However, arsenic (As) speciation and the physicochemical 5 6 75 characteristics of the environment determine its bioavailability more than its concentrations. In rice 7 8 76 fields the prolonged flooding usually adopted for cultivation leads to As release from soil minerals 9 10 77 with the consequent accumulation of the metalloid in the grains (Zhu et al. 2014; Sun et al. 2014; 11 12 78 Ma et al. 2014). Recent studies revealed that, on average, As content in rice from different countries 13 79 exceeds the law limits established by the Commission regulation (EU) 2015/1006 (Ma et al. 2014; 14 15 80 EFSA 2009, 2014). 16 17 81 The two inorganic As species mainly present in rice field soil, arsenate [As(V)] and arsenite 18 19 82 [As(III)], have different biogeochemical properties. Nevertheless, both As species show high 20 21 83 affinity for iron oxides/hydroxides (Meharg 2012; Martin et al. 2014). 22 23 84 Continuous flooding in paddy soils leads to strongly reduced conditions, with the consequent rapid 24 85 dissolution of these minerals and the release of As into the pore water (Zhu et al. 2014; Meharg 25 26 86 2012). Furthermore, As(V) is reduced to As(III) abiotically by sulfide, ferrous iron [Fe(II)], H2 or 27 28 87 reduced organic acids, or by As(V)-reducing bacteria (Cavalca et al. 2013; Meharg et al. 2012). 29 30 88 Several studies reported that As(III) in flooded rice fields is the predominant As species (Zhu et al. 31 32 89 2014; Takahashi et al. 2004). At very low redox potentials, where microbial sulfate reduction is 33 34 90 favored, sulfide produced by this activity can co-precipitate with As(III) forming a variety of 35 91 minerals, such as orpiment (As2S3) (Zhu et al. 2014; Kocar and Fendorf 2009). If soil is aerated, for 36 37 92 example after a drainage period, As(III) can be oxidized to As(V) by oxygen, manganese oxides 38 39 93 and H2O2 as well as by microbial As(III) oxidation (Meharg 2012). 40 41 94 The genetic properties and the encoded enzymatic systems that allow several groups of 42 43 95 microorganisms to resist to high As concentrations or to use As for metabolic purposes have been 44 96 45 recently reviewed by various authors (Andres et al. 2016; Zhu et al. 2014; Yamamura et al. 2014; 46 97 Cavalca et al. 2013; Zheng et al. 2012; Slyemi and Bonnefoy 2012). Interestingly, in rice paddy 47 48 98 soils with low As concentration a high diversity of microbial genes for As processing has been 49 50 99 detected (Xiao et al. 2016), indicating the potential role of native communities on As 51 52100 transformations beyond abiotic factors. Among these processes, the microbial methylation of 53 54101 As(III) in rice rhizosphere is receiving great attention in the last few years. Recent studies indicated 55 102 that rice roots microbiome is entirely responsible for the production of methylated As present in rice 56 57103 grains, which accounts for 50 % of total As content (Lomax et al. 2012; Arao et al. 2011; Zhao et al. 58 59104 2013). Furthermore, continuous flooding of rice fields has been demonstrated to increase the 60 61105 concentration of methylated As in rice grains (Ma et al. 2014; Li et al. 2009). 62 63 3 64 65 106 In addition to direct As transformations, several metabolic activities of microorganisms could 107 indirectly influence As speciation and bioavailability in the environment. Given the above 1 2108 mentioned affinity of As for iron and sulfide minerals, microorganisms involved in iron and sulfur 3 4109 cycles could promote either the release or the sequestration of As from the pore water of rice 5 6110 paddies. Dissimilatory iron-reducing bacteria (DFeRB) use ferric iron [Fe(III)] as electron acceptor 7 8111 for anaerobic respiration, contributing to the release of As from iron minerals (Lee 2013). 9 112 Conversely, iron-oxidizing bacteria (FeOB) are chemolithoautotrophic bacteria that couple the 10 11113 oxidation of Fe(II) to the reduction of a variety of electron acceptors (Emerson 2012; Hedrich et al. 12 13114 2011; Emerson et al. 2010). With their activity these bacteria promote the co-precipitation of As 14 15115 with iron minerals. As already stated, dissimilatory sulfate-reducing bacteria (DSRB) are strict 16 2- - 17116 anaerobes that reduce sulfate (SO4 ) to sulfide (HS ) for their energy metabolism (Rabus et al. 18 19117 2015; Ramel et al. 2015; Pester et al. 2012; Pereira et al. 2011), potentially contributing to the 20 118 formation of As S in anoxic compartments of rice fields soils. On the other hand, a variety of 21 2 3 22 - 2- 2- 119 sulfur-oxidizing bacteria (SOB) can oxidize HS to SO3 , and/or the latter to SO4 , leading to the 23 24120 release of As into the pore water in rice paddies (Stubner 1998; Friedrich et al. 2005; Hamilton et al. 25 26121 2015; Dahl et al. 2008). 27 28122 The recent instructions established by the Commission regulation (EU) 2015/1006 concerning rice 29 30123 consumption in relation to As exposure have arisen great concern in the most important European 31 124 rice producing countries like Italy. Although the scientific community has often focused the 32 33125 attention on As contamination of rice, especially in Asia, very little is known about the role of 34 35126 different rhizospheric microbial populations and the microbial metabolic processes that drive As 36 37127 biogeochemistry. In this study, the bacterial community inhabiting the rhizosphere of rice plants 38 39128 cultivated with different water regimes in an unpolluted soil has been investigated in order to 40 41129 identify specific populations responsible for As contamination of rice grains. 42130 43 44131 Materials and methods 45 46132 47 48133 Experimental setup 49 50134 Nine rice paddy macrocosms containing 10-15 rice plants (Oryza sativa subsp. japonica, variety 51 -1 52135 Loto) each were set up in tanks filled with rice field soil (sandy-loam texture; pH 6.0; 11.4 mg kg 53 -1 54136 of total As content and 33.1 g kg of aqua regia extractable Fe). Three replicates for each 55 137 macrocosm were managed either under continuous flooding (CF), under continuous flooding with a 56 57138 2-weeks period of drainage before flowering (CF-D) or in dry soil with watering nearly every 7-10 58 59139 days, or when the soil was excessively dry, always taking care to maintain aerobic conditions in soil 60 61140 all over the cropping season (D) (Fig. 1). After 12 days from germination CF and CF-D 62 63 4 64 65 141 macrocosms were flooded and D were watered. CF-D treatments were drained 47 days after 142 germination for 14 days, followed by re-flooding. Then, they were re-flooded until sampling. All 1 2143 samplings were performed at the flowering stage. At this time point, the CF macrocosms were still 3 4144 flooded, whereas the CF-D and the D macrocosms were re-flooded the previous day. Before re- 5 6145 flooding, CF-D macrocosms underwent the 14-day period of drainage. 7 8146 9 147 10 Chemical analyses of pore water 11148 Three replicates of pore water samples were obtained from each macrocosm using Rhizon soil 12 13149 moisture samplers (Rhizosphere®, Rhizosphere Research Products, Wageningen, NL). In D 14 15150 macrocosms, pore water was sampled the day after watering, in order to allow the restoration of 16 17151 soil-solution equilibria and, at the same time, to have the possibility to obtain a solution sample. 18 19152 The Eh was measured in the soil right before sampling (portable pH/mV Measuring Instrument 20 153 pH197i, WTW, Weinheim, Germany; equipped with a WTW SenTix® ORP electrode). The 21 22154 concentration of total As in the pore water samples was quantified with HG-AAS (Perkin-Elmer 23 24155 4100 equipped with a FIAS 400 hydride generator; Perkin-Elmer Inc., Waltham, Massachusetts). 25 26156 For As speciation in pore water and in rice grain, refer to the treatments labelled as CF, 2IED and 27 28157 AR in Zecchin et al. (2017), corresponding to CF, CF-D and D respectively. Fe(II) was determined 29 30158 with the orthophenantroline method (Loeppert and Inskeep 1996); N-nitrate, P-phosphate and S- 31 159 sulfate were determined with ion chromatography [Dionex DX-500 system, AS9 analytical column, 32 33160 with AG9 pre-column (Dionex, Sunnyvale, CA, USA)]. 34 35161 36 37162 38 163 Rhizosphere soil and rhizoplane separation 39 40164 Three plants from each macrocosm replicate, for a total of nine plants for each water management, 41 42165 were sampled after 60 days from germination, at flowering stage. This stage was chosen because 43 44166 previous studies indicated that, in rice, As is mainly translocated during flowering (Zheng et al. 45 46167 2011). 47 48168 Immediately after sampling, samples were pooled in one composite sample for each treatment, 49169 according to Somenahally et al. (2011) and rhizosphere soil and rhizoplane were collected 50 51170 according to Cavalca et al. (2010). Rhizosphere soil was defined as the soil removed from roots 52 53171 after shaking (180 rpm) in tetrasodium pyrophosphate buffer (0.2%, pH 8.0) for 1 h at 30 °C. The 54 55172 rhizoplane fraction was the biomass suspension resulting after 3 cycles of sonication (30 s each) of 56 57173 roots, previously washed thoroughly with sterile distilled water and submerged in 1:2 ratio (w/v) in 58 59174 1x phosphate buffer saline (PBS) solution. Immediately after separation, samples were stored at -80 60175 °C. An aliquot of the original soil used for the experiment was also sampled as the time zero control 61 62 63 5 64 65 176 (T0). 177 1 2178 RNA isolation 3 4179 Total RNA was isolated using the RNA PowerSoil® Total RNA Isolation Kit (MO BIO, Carlsbad, 5 6180 USA), according to manufacturer’s instructions. To remove residual genomic DNA from isolated 7 8181 RNA, 1 U of DNaseI (Thermo Fisher Scientific, Waltham, Massachusetts, USA) was added to 1 µg 9 182 of RNA and each reaction was incubated according to manufacturer’s instructions. The purity of 10 11183 RNA was tested both via agarose gel electrophoresis and with PCR amplification of bacterial 16S 12 13184 rRNA genes (see details in the following sub section). The purified RNA was reverse transcribed 14 15185 with iScriptTM cDNA Synthesis Kit (BIO-RAD, Hercules, California, USA) according to 16 17186 manufacturer’s instructions. 18 19187 20 188 21 Barcoded pyrosequencing of 16S rRNA 22189 Pyrosequencing of 16S rRNA was performed from reverse-transcribed RNA isolated from the T0 23 24190 soil and from rhizosphere soil and rhizoplane sampled during the reproductive phase. Bacterial 16S 25 26191 rRNA was amplified with the universal bacterial primers 27F (5’ - GAG AGT TTG ATC CTG 27 28192 GCT CAG - 3’) and 1495R (5’ - CTA CGG CTA CCT TGT TAC GA - 3’) from each sample in 29 30193 triplicate in a 25 µL reaction volume containing 10 ng of cDNA, 0.3 µM primers and 1x Taq PCR 31 194 Mastermix kit (QIAGEN, Hilden, Germany). The thermal incubation included a first denaturation at 32 33195 95 °C for 5 min followed by 35 cycles of denaturation at 95 °C for 1 min, annealing at 55 °C for 40 34 35196 sec and elongation at 72 °C for 1 min and 40 sec; the final elongation was performed at 72 °C for 10 36 37197 min. Replicated amplicons were pooled and purified with MinElute PCR Purification kit 38 -1 39198 (QIAGEN) to a final concentration of 20 ng µL . Pyrosequencing was performed at Molecular 40 41199 Research LP (MRDNA, Shallowater, Texas, USA) by bacterial Tag-Encoded FLX Amplicon 42200 Pyrosequencing (bTEFAP), using the primer 27F. The sequences were processed and analyzed with 43 44201 the QIIME tools (Caporaso et al. 2010a). Sequences with less than 200 bases of with barcodes or 45 46202 primer biases, homopolymers and chimeras were removed from the analysis. According to the 47 48203 quality scores, all sequences were trimmed at 400 bp. Operational Taxonomic Units (OTUs) were 49 50204 defined with a 97 % similarity cut-off with the uclust method (Edgar 2010) using the last SILVA 51 52205 SSU Ref dataset (Quast et al. 2013) as reference database. Representative sequences for each OTU 53206 were aligned using the PyNAST method (Caporaso et al. 2010b). After taxonomic assignment, 54 55207 sequences belonging to chloroplasts were removed and OTU tables were generated for each sample. 56 57208 Phylogenetic analysis was performed using the FastTree method (Price et al. 2009). To measure the 58 59209 bacterial diversity within the samples, the OTU tables were rarefied and different indices of alpha 60 61210 diversity were calculated assuming a sample size of 2000. The OTU richness and the diversity 62 63 6 64 65 211 within each sample was evaluated with different alpha diversity indices (observed species, Fisher’s 212 alpha, ACE, Simpson evenness). To compare the bacterial diversity between the samples, principal 1 2213 coordinates analysis (PCoA) of the rarefied OTU tables was performed calculating unweighted and 3 4214 weighted UniFrac distances (Hamady and Knight 2009). The significance of the differences 5 6215 emerged with the beta diversity was tested with the multi-response permutation procedure (MRPP; 7 8216 Mielke et al. 1976). To distinguish between core and rare taxa, the rank abundance was plotted. 9 217 Statistically significant differences of single OTUs among different water managements were 10 11218 evaluated with one-way analysis of variance (ANOVA) at p < 0.05 with Bonferroni's correction. 12 13219 14 15220 Predictive microbial arsenic, iron and sulfur processing profiling 16 17221 In order to point out the bacterial populations involved in arsenic, iron and sulfur cycles, a reference 18 19222 database was specifically constructed on the bases of information available in the literature on 20 223 bacterial strains with experimentally-demonstrated metabolisms related to these elements. For taxa 21 22224 included in the database, the presence of genes related to arsenic, iron and sulfur metabolisms was 23 24225 checked in the NCBI database. Genera were selected for their documented capacity to reduce As(V) 25 26226 as an electron acceptor [dissimilatory As(V)-reducing bacteria, DAsRB], to resist to arsenic with 27 28227 different mechanisms (arsenic resistant bacteria, AsRB), to oxidize As(III) [As(III)-oxidizing 29 30228 bacteria, AsOB] or to methylate As(III) [As(III)-methylating bacteria, AsMB]. The metabolisms 31 229 that indirectly influence arsenic dynamics considered in this analysis were dissimilatory Fe(III)- 32 2- 33230 reduction (DFeRB), Fe(II)-oxidation (FeOB), dissimilatory SO4 reduction (DSRB) and sulfur- 34 35231 oxidation (SOB). 36 37232 38 39233 Accession numbers 40 41234 All the 16S rRNA sequences retrieved in this study are deposited in the NCBI Bioproject 42235 (https://www.ncbi.nlm.nih.gov/bioproject/) PRJNA353766. 43 44236 45 46237 Results 47 48238 49 50239 Effect of agronomic management on pore water chemistry and rice grain contamination 51 52240 At the flowering stage, relatively high concentrations of As and Fe(II) were dissolved in the pore 53 54241 water in the CF macrocosms (Table 1), indicating reduced conditions induced by continuous 55 242 flooding. The prevalent As form was As(V) comprising 88% of the total As in pore water. Organic 56 57243 arsenic forms were not detected (Zecchin et al. 2017). In CF-D and D both dissolved As and Fe(II) 58 59244 were almost negligible at the considered sampling date, proving that the recent drainage of the CF- 60 61245 D macrocosms had been effective in restoring an oxidative environment in soil and that the 62 63 7 64 65 246 watering of the D macrocosms the day before sampling did not induce any appreciable reductive 247 dissolution of Fe and As. In the CF macrocosms, the average redox potential measured in the three 1 2248 replicates was below -200 mV, whereas in the CF-D and D macrocosms the values were above zero 3 4249 (data not shown). Nitrate and sulfate, which are reducible species, showed different patterns, being 5 6250 more abundant in the aerobic rice test D and in the just drained macrocosm CF-D, compared with 7 8251 the flooded ones. The concentration of dissolved phosphate, as expected, remained comparable in 9 252 the different treatments. Total arsenic content in rice grains varied significantly according to the 10 11253 water regime: 237 ± 38 g kg-1 in CF, 68 ± 4 g kg-1 in CF-D and 5 ± 3 g kg-1 in D. Methylated 12 13254 As forms represented 46% of total As in CF, and 18% in CF-D and they were negligible in D 14 15255 (Zecchin et al. 2017). 16 17256 18 19257 Ecology of active microbiota in rice rhizosphere 20 21258 Sequencing of 16S rRNA produced 230,791 reads. The average length of reads with quality score 22259 above 25 was 408 bp, therefore the sequence region beyond the nucleotide position 400 was 23 24260 removed in all reads. The total number of sequences that passed the quality control for each sample 25 26261 and the related number of OTUs are listed in Table 2. 27 28262 Different indexes for alpha diversity (ACE, Simpson evenness, observed species) were calculated 29 30263 and compared (Fig.1). The expected number of species in all rhizosphere soil samples was similar 31 32264 to the T0 soil. The rhizoplane samples of CF and CF-D plants showed the highest species richness 33265 (Fig. 2a), whereas the rhizoplane of D was the sample with the lowest species richness, evidencing 34 35266 a plant effect induced by flooding. Simpson’s evenness in all samples was below 0.5, indicating the 36 37267 predominance of specific groups among the whole community. In the rhizoplane of CF plants, 38 39268 species were more evenly distributed with respect to all the other samples. In the rhizoplane of CF- 40 41269 D plants, although species richness was similar to CF plants, evenness was lower. The bacterial 42 270 43 community of the rhizosphere soil of CF plants was the most heterogeneous. The rarefaction 44271 analysis performed on the observed species confirmed the ACE trend, with the diversity within the 45 46272 samples decreasing as follows: CF rhizoplane < CF-D rhizoplane < CF rhizosphere soil < T0 < D 47 48273 rhizosphere soil < CF-D rhizosphere soil < D rhizoplane (Fig. 2b). 49 50274 51 52275 Driving forces of microbial community differentiation 53 276 According to the PCoA analysis, the bacterial communities developed in both compartments of D 54 55277 were similar to each other, clustering in groups III and V according to unweighted and weighted 56 57278 UniFrac, respectively (Fig. 3a and 3d). On the contrary, the CF and CF-D treatments led to a 58 59279 significant differentiation between rhizosphere soil and the rhizoplane. Interestingly, the 60 61280 communities selected in CF and CF-D rhizoplanes were similar, clustering in groups I and IV 62 63 8 64 65 281 according to unweighted and weighted UniFrac, respectively (Fig. 3a and 3d). The CF rhizosphere 282 soil community was similar to the T0 soil. In CF-D rhizosphere soil the phylogenetic composition 1 2283 of the community was similar to the community in T0 (Fig. 3a and 3d). However, when considering 3 4284 the relative abundances of the taxa, these samples were more similar to CF and CF-D rhizoplanes 5 6285 (Fig. 3d). The water regime and the compartment by themselves did not influence significantly the 7 8286 bacterial communities developed in the different samples (Fig. 3b, 3c, 3e and 3f, A: 0.08, 0.03, 0.26 9 287 and 0.11, respectively). More likely, a combination of factors drove the differentiation of the 10 11288 communities, which was best reflected by groups IV, V and VI (A: 0.38, p < 0.001). 12 13289 14 15290 Phylogenetic composition of the different communities 16 17291 In total 40193 OTUs at genus level were found in all samples. Two opposite trends were observed 18 19292 concerning the number of OTUs exclusively present after each treatment in rhizosphere soil and in 20 293 the rhizoplane (Fig. 4). In rhizosphere soil, 25.8 %, 30.5 % and 30.9 % of the total number of OTUs 21 22294 were exclusively present in CF, CF-D and D, respectively (Fig. 4a). On the contrary, in rhizoplane 23 24295 they were 33.6 %, 30.6% and 22.6 %, respectively (Fig. 4b). In rhizosphere soil, CF-D shared 4.6 % 25 26296 of OTUs with D treatments, with respect to 3% with CF. In the rhizoplane, CF-D shared 7.2% of 27 28297 the OTUs with CF treatments, compared to 1.7% in common with D. 29 30298 A total of 33 phyla were detected in the samples. The number of phyla in the T0 soil was higher 31 299 with respect to all rhizosphere compartments of rice cultivated with different water regimes (Table 32 33300 2). In both compartments the number of phyla decreased from CF to CF-D to D. On the basis of the 34 35301 rank abundance plot, taxa with relative abundance below 0.01 % were considered as part of the rare 36 37302 biosphere (Online Resource, Fig. S1a). According to this definition, the fraction of rare phyla was 38 39303 higher in the T0 soil, followed by both compartments of CF plants, both compartments of CF-D 40 41304 plants and both compartments of D plants (Online Resource, Fig. S1b). 42305 The percentage of sequences that could not be assigned to any known phylum ranged between 2.3 43 44306 % and 6.9 % (Fig. 5). In the T0 soil, the phyla Acidobacteria, Actinobacteria and Proteobacteria 45 46307 were the most abundant, accounting for 9.13%, 30.69% and 36.72% of the bacterial community 47 48308 respectively (Fig. 5a). In CF rhizosphere soil, the abundance of Proteobacteria decreased to 25.10 49 50309 %, with the concomitant increase of Acidobacteria and Actinobacteria, which accounted for 12.61 51 52310 % and 37.14 % of the total, respectively. In the rhizoplane under CF, Actinobacteria represented 53311 only 2.52 %, whereas Proteobacteria and Acidobacteria accounted for 54.43 % and 20.83 % 54 55312 respectively. In CF rhizosphere soil Actinobacteria belonging to an uncultured genus of the order 56 57313 Gaiellales were significantly more abundant (p < 0.05) with respect to the other treatments, whereas 58 59314 in the rhizoplane the same microorganisms were more abundant in D (Fig. 5b, Online Resource, 60 61315 Table S3). The genera Marmoricola and Nocardioides also contributed with 3.8 % and 1.9 % 62 63 9 64 65 316 respectively. In CF rhizoplane Acidobacteria of the order DA023 and Candidatus 317 Chloracidobacterium were represented by 7.81 % and 4.21 % of the sequencing library respectively 1 2318 (Fig. 5b). Bacteria belonging to the class Deltaproteobacteria were selected by CF, accounting for 3 4319 4.5 % and 6% of the total community in CF rhizosphere soil and rhizoplane (Fig. 5a). Iron-reducing 5 6320 Deltaproteobacteria belonging to the genera Anaeromyxobacter and Geobacter were the most 7 8321 contributors for this class in CF rhizosphere soil and rhizoplane respectively (Online Resource, 9 322 Table S2). 10 11323 In the rhizosphere soil and in the rhizoplane under CF-D, the phylum Proteobacteria accounted 12 13324 respectively for 82.34 % and 68.10 % of all bacterial phyla (Fig. 5a). In CF-D rhizosphere soil, this 14 15325 phylum was the only one with abundance above 10 %, whereas in CF-D rhizoplane the phylum 16 17326 Acidobacteria contributed with 17.78 %. The classes Alphaproteobacteria and Betaproteobacteria 18 19327 were mainly responsible for the dominance of the phylum Proteobacteria in both compartments. In 20 328 CF-D rhizosphere soil, members of the class accounted for more than 45%, 21 Betaproteobacteria 22329 with the Comamonadaceae family accounting for 38% of the total bacterial community (Fig. 5b, 23 24330 Online Resource, Table S2). Within this family, Ramlibacter, Piscinibacter and other unknown 25 26331 genera represented 11 %, 3.3 % and 21 % of the whole community respectively. In CF-D 27 28332 rhizoplane, on the other hand, several members of the class Alphaproteobacteria made up almost 50 29 30333 % of the total community (Fig. 5a). Within these members, the genus Sphingomonas accounted for 31 334 17 % in both compartment. 32 33335 In both compartments of D the two most abundant phyla were Proteobacteria and Actinobacteria, 34 35336 respectively accounting for 53.68 % and 31.31% in D rhizosphere soil and 60.56 % and 25.25 % in 36 37337 D rhizoplane (Fig. 5a). Within Proteobacteria, the classes Alphaproteobacteria, 38 39338 Betaproteobacteria and Gammaproteobacteria were the most abundant. In D rhizosphere soil they 40 41339 accounted for 30.3 %, 6.8 % and 15.6 % respectively, with Sphingomonas responsible for 15.2 % of 42340 the total community. In the D rhizoplane, the three above mentioned classes accounted for 39.2 %, 43 44341 11.2 % and 9.5 %. In this compartment Sphingomonas and Variovorax represented 28 % and 6.8 % 45 46342 of the total community respectively. Within the phylum Actinobacteria, the genus Arthrobacter 47 48343 accounted for 14.3 % and 5.9 % in D rhizosphere soil and D rhizoplane respectively. Different 49 50344 OTUs belonging to this genus were significantly more abundant (p < 0.05) in D with respect to the 51 52345 other water regimes (Online Resource, Table S3). In D rhizoplane, the genera Marmoricola and 53346 Nocardioides also contributed with 2.1 % and 2.9 % respectively. 54 55347 56 57348 Bacterial populations potentially involved in arsenic, iron and sulfur cycles 58 59349 In order to predict the bacterial community functional profiles, although potential, related to As, Fe 60 61350 and S processing, a survey was conducted in the literature to search for taxa that were 62 63 10 64 65 351 experimentally demonstrated to be involved in those biogeochemical cycles or in whose genomes 352 the presence of genetic markers was displayed (Online Resource, Table S1). 1 2353 In the T0 soil, bacteria able to resist or to process As, either by reduction, oxidation or methylation, 3 4354 accounted for 6.39 % of the bacterial community (Online Resource, Fig. S2a). Within these, 58.96 5 6355 % were putative AsMB, 23.83 % were AsOB, 12.35 % were putatively ars/ACR operons-carrying 7 8356 species (AsRB) and 4.85 % DAsRB. Bacteria involved in iron and sulfur cycle represented 1.4 % of 9 357 the total: within these, 22.34% were DFeRB, 35.55 % were FeOB, 3.61 % were DSRB and 38.5 % 10 11358 were SOB (Online Resource, Fig. S2b). 12 13359 DAsRB, DFeRB and DSRB were significantly more abundant in rhizosphere soil and in the 14 15360 rhizoplane of plants cultivated under CF with respect to CF-D and D (Fig. 6). In the rhizoplane, 16 17361 DAsRB and DFeRB accounted for more than 2 % of the total community, whereas DSRB 18 19362 represented 0.1 % of the community. Among DAsRB and DFeRB, Geobacter and Bacillus genera 20 363 were significantly higher in CF and CF-D water regimes. The same trend was observed for DFeRB 21 22364 of the genus Anaeromyxobacter. Among DSRB, Desulfobacteraceae varied significantly being 23 24365 more abundant in the rhizosphere soil of CF plants (Table 3). 25 26366 AsOB were significantly more abundant in D plants of both root compartments (Fig 5). AOB 27 28367 accounted for 10% of the total community in D plants, whereas in CF and CF-D plants they were 29 30368 always overall below 3%. Rhizobium, Variovorax, Pseudomonas and Stenotrophomonas 31 369 significantly contributed to this variation. FeOB mirrored this trend in rhizospheric soil, whereas in 32 33370 the rhizoplane they were not affected by the agronomic managements and they were always below 34 35371 1%. FeOB as Thermomonas and Pseudomonas were more abundant in D, whereas Leptothrix, 36 37372 Rhodobacter and Aquabacterium were more abundant in CF (Table 3). Differently from As- and 38 39373 Fe-oxidising bacteria, sulfur-oxidizing bacteria (SOB) as Rhodovolum and Anaeromyxibacter were 40 41374 significantly more abundant in CF plants in both root compartments, doubling from 1.49 % in 42375 rhizosphere soil to 2.88% in the rhizoplane (Fig. 6), while Aurantimonas was the only SOB genus 43 44376 significantly higher in D (Table 3). 45 46377 The abundance of AsRB in rhizosphere soil was included between 2.6% and 3.4%, without 47 48378 significant variations due to the water regimes (Fig. 6). This was reflected by the opposite trends of 49 50379 relative abundance of different genera, like Pseudomonas (stimulated in D) and Anaeromyxibacter 51 52380 (higher in CF) (Table 3). In the rhizoplane, on the contrary, AsRB accounted for 3.91 % of the total 53381 in CF plants, with respect to 1.14 % and 0.72 % in CF-D and D plants. 54 55382 Similarly, AsMB were present in rhizosphere soil with abundances between 1.93 % and 4.97 %, 56 57383 with no significant variations among the three water managements. In the rhizoplane, AsMB were 58 59384 significantly more abundant in CF plants (4.64 %) than in CF-D (2.66 %) and D (1.11 %) plants 60 61385 (Fig. 6). 62 63 11 64 65 386

1387 Discussion 2 388 3 4389 Continuous flooding lead to the dissolution of As and Fe in the CF macrocosms, as expected 5 6390 according to previous studies (Yamaguchi et al. 2011; Borch et al. 2010; Takahashi et al. 2004), 7 8391 following the well assessed reductive dissolution of Fe and Mn oxides and the reduction of As(V) 9 10392 to the more soluble As(III). The temporary establishment of an oxic environment in the CF-D soils 11 12393 was followed by very low As and Fe concentrations in solution, comparable to those encountered in 13 394 the D ones, assessing a fast chemical response of the system to the water management. The 14 15395 mobilization of As in pore water in CF agronomic schemes has been recently proven to lead to As 16 17396 enrichment of rice grains, if compared to the CF-D and D ones (Zecchin et al. 2017; Spanu et al. 18 19397 2012). 20 21398 The species richness and evenness of the samples, the PCoA analysis and the core microbiome 22 23399 analysis reflected the chemical characteristics determined by the different water regimes and 24 400 indicated a strong influence of the presence of the plant in CF and CF-D agronomic conditions. The 25 26401 rhizosphere of CF and CF-D plants reflected an anoxic environment, where strictly anaerobic 27 28402 species were selected. By contrast, in the rhizoplane of these plants, the release of organic matter 29 30403 and oxygen by the roots likely promoted a higher diversity. In D rhizosphere the proximity to the 31 32404 plant did not lead to a sharp differentiation in the bacterial community, possibly linking the lower 33 34405 development of the roots and the aerenchyma in such condition to a lower turn-over of oxygen and 35406 carbon sources, and consequently the lack of a chemical gradient (Suralta and Yamauchi 2008). In 36 37407 rhizosphere soil of CF and CF-D treatments, populations with similar phylogenetic affiliation were 38 39408 selected during the vegetative phase, whereas the two-weeks drainage period led to a differentiation 40 41409 in the abundances but not in the phylogenetic structure of the community (Fig. 3). In rhizosphere 42 43410 soil of CF-D plants, the stress induced by sharp short-term changes in the redox conditions could 44 411 45 have selected for more versatile species in common with D. In the rhizosphere of D less species 46412 where stimulated, probably indicating a lower degree of electron acceptors restoration given by 47 48413 either the absence of a redox interface or by the fact that these plants do not grow under optimal 49 50414 conditions (i.e. continuous flooding). 51 52415 The three dominant phyla found in all the samples, i.e. Actinobacteria, Acidobacteria and 53 54416 Proteobacteria, resembled what commonly found in plants rhizosphere (Bulgarelli et al. 2013). 55 417 represented a significant part of the original community of the rice paddy soil used 56 Actinobacteria 57418 for this experiment, contrary to what seen in previous studies carried out on rice paddy soils from 58 59419 different locations (Edwards et al. 2015; Wörner et al. 2016). These microorganisms are common 60 61420 soil inhabitants and plant commensals (Ventura et al. 2007). Most of them, including members of 62 63 12 64 65 421 the genera Marmoricola and Nocardioides and of the order Gaiellales, are aerobic and degrade a 422 variety of complex polysaccharides deriving from the plant (Barka et al. 2016; Kügler et al. 2015; 1 2423 Urzì et al. 2000; Lee 2007; Dastager et al. 2008; Lee and Lee 2010; Lee et al. 2011; Yoon and Park 3 4424 2006; Albuquerque et al. 2011). The genus Arthrobacter, quite abundant in rhizosphere soil of D 5 6425 plants, is commonly found in soils with neutral pH. Members of this genus are versatile concerning 7 8426 carbon source and highly resistant to environmental stress like aridity (Jones and Keddie 2006). The 9 427 high abundance of members of the order together with Fe(III)- and SO 2--reducing 10 Gaiellales 4 11428 genera in the rhizosphere of CF plants indicates the presence of microhabitats with different levels 12 13429 of oxygen and electron acceptors. Members of the phylum Acidobacteria are commonly found in 14 15430 soils as well as in rhizosphere soil (Bulgarelli et al. 2013; Ward et al. 2009). As a confirmation of 16 17431 these outcomes, in previous studies these organisms were found to be more abundant in bulk and 18 19432 rhizosphere soil with respect to the rhizoplane (Edwards et al. 2015). They are usually aerobic, 20 433 capable of nitrate and nitrite reduction, heterotrophs, able to degrade complex substrates and 21 22434 tolerant to variation of soil humidity (Ward et al. 2009). 23 24435 Member of the Proteobacteria phylum were favored by the proximity to the plant, where the release 25 26436 of C compounds is higher and determines the prevalence of r-strategist bacteria (Edwards et al. 27 28437 2015). These microorganisms have often been found more abundant in the rhizoplane and in the 29 30438 endosphere (Edwards et al. 2015) with respect to the bulk of rice field soil. The high abundance 31 439 observed in CF-D for Alphaproteobacteria and Betaproteobacteria might be due to the decrease of 32 33440 members of the other taxa, less resistant to the alternation of wet/dry periods. Shrestha and 34 35441 colleagues (2009) also observed that members belonging to these two classes were more active in 36 37442 oxic paddy soil. The genus Ramlibacter sp., including aerobic heterotrophs, often isolated from 38 39443 soils, has been demonstrated to be resistant to dryness stress (Lee et al. 2014). The genus 40 41444 Sphingomonas, strictly aerobic and facultative photoorganotroph (Yabuuchi and Kosako 2005), 42445 found its ideal habitat in the rhizoplane of D. Piscinibacter are described as chemoheterotrophs and 43 44446 facultative aerobic (Song and Cho 2007; Stackebrandt et al. 2009). Deltaproteobacteria are more 45 46447 frequently detected in anoxic rice paddies (Shrestha et al. 2009; Pester et al. 2012; Lu et al. 2006). 47 48448 According to these observations, in this study members of this class were more abundant in CF 49 50449 rhizosphere compartments. 51 52450 Most of the above mentioned genera, with high relative abundance in the different treatments, are 53451 not known to have arsenic-processing capacities. This aspect probably reflects the fact that the soil 54 55452 used for this experiment did not contain high As concentration. Therefore, As was not the main 56 57453 factor shaping the bacterial communities in this environment. 58 59454 Nowadays, apart from metagenomic analysis, tools to predict functional profiling of microbial 60 61455 systems relay on 16S rRNA data associated to databases using marker gene data and reference 62 63 13 64 65 456 genomes (Langille et al. 2013). The central idea is that despite various important forms of microbial 457 genome plasticity (gene loss, duplication, or gene transfer), the genes present in microbial genomes 1 2458 are much more similar amongst related bacteria or archaea than distant relatives. In line with this 3 4459 approach, the database built in the presence study was used to assess potential functionalities related 5 6460 to arsenic/iron/sulfur biogeochemical cycles. Such data might be useful in future studies to focus 7 8461 the attention on specific microbial taxa when considering metagenomic libraries. Although this 9 462 approach can indicate only potential functions in a microbial community, the trends observed were 10 11463 consistent with the soil physical-chemical conditions in the different water managements and with 12 13464 previous data based on marker gene quantification (Zecchin et al. 2017). 14 15465 In this study, we observed that DSRB were more abundant in rhizosphere soil of CF if compared to 16 17466 rhizoplane, whereas DAsRB and DFeRB in the same treatment were closer to the roots. The 18 19467 observed pattern, with DFeRB more abundant than DAsRB, probably reflects the redox scale 20 468 predicted by Kocar and Fendorf (2009), who demonstrated that at pH < 6.5 Fe(III)-reduction is 21 22469 favored over dissimilatory As(V)-reduction. Members of the genera Geobacter and 23 24470 Anaeromyxobacter were confirmed to be common Fe(III)-reducing inhabitants of anoxic paddy 25 26471 fields, promoted by a CF water regime (Hori et al. 2010; Shrestha et al. 2009; Treude et al. 2003). 27 28472 The best habitat for FeOB was the rhizosphere of D plants. This could be due to a sharp redox 29 30473 interface in CF and CF-D, with only little areas with the optimal concentration of Fe(II) and O2, and 31 474 a wider microoxic area in D rhizosphere. Similarly, populations of AsOB were more abundant in D 32 33475 rhizosphere, confirming what observed in previous studies (Das et al. 2016). The presence of both 34 35476 FeOB and AsOB might contribute to the conversion of As(III) to As(V) and its co-precipitaion with 36 37477 Fe oxides. Conversely, in CF DFeRB predominate over FeOB. Therefore, the process of dissolution 38 39478 of Fe oxides and consequent release of As is promoted over its precipitation. 40 41479 Genera of SOB were more abundant in the rhizoplane of CF plants, in contrast with what observed 42480 by Das et al. 2016. The rhizoplane of CF plants could be an optimal habitat for SOB since reduced 43 44481 sulfur compounds are produced by DSRB but, at the same time, little amounts of oxygen needed by 45 46482 these organisms are released by the roots. It has often been reported that SOB are related to 47 48483 ecosystems characterized by sharp opposing gradients of O2 and reduced sulfur compound (Dahl et 49 50484 al. 2008). Considering that SOB potentially promote sulfide minerals dissolution, their presence in 51 52485 CF rhizosphere might contribute to As release from sulfide minerals. Microbial mineral weathering 53486 for nutrient acquisition has already been reported as a cause of As release to soil solution from 54 55487 apatite (Mailloux et al. 2009). These evidences strongly suggest that these microorganism-mediated 56 57488 processes affect As translocation to rice grains in accordance with previous studies (Zecchin et al. 58 59489 2017; Somenahally et al. 2011), thus posing a health issue. 60 61490 Although in the rhizosphere soil of all the treatments AsRB were equally represented, in the 62 63 14 64 65 491 rhizoplane these organisms were more abundant in CF plants. This was probably a consequence of 492 the fact that arsenic was strongly released in that region, where iron oxides and sulfide minerals are 1 2493 present and probably dissolved by DFeRB and SOB. In the rhizoplane, the bacterial diversity was 3 4494 generally lower than in the rhizosphere soil. In the latter, the higher diversity included 5 6495 microorganisms generally present in soil characterized by an average distribution of As resistance. 7 8496 Arsenic-methylating bacteria were present in rice rhizosphere. Particularly, in CF plants this activity 9 497 was selected and probably enhanced by the presence of As(III) and organic matter, which are the 10 11498 substrates for this reaction. This is in accordance with recent evidence that under CF more organic 12 13499 As is produced with respect to sprinkler irrigation and aerobic rice (Moreno-Jiménez et al. 2014; Li 14 15500 et al. 2009). Organic As constituted almost 50 % of total As in rice grains in CF condition in the 16 17501 same experimental set up (Zecchin et al. 2017). Furthermore, recent evidence indicates that organic 18 19502 As accumulated in rice grains derives from microbial methylation carried out in the rhizosphere 20 503 (Lomax et al. 2012). Among versatile bacteria related to arsenic reduction or methylation and to Fe 21 22504 dissimilative reduction, Geobacter, rare in the T0 soil according to rank abundance analysis (Online 23 24505 Resource, Fig. S1), significantly increased in CF and CF-D rhizosphere soils and rhizoplanes, but 25 26506 not in D water regime. Previous data of Geobacter-specific gene quantification (Zecchin et al. 27 28507 2017) are in accordance with the bar-coded sequence data obtained in the present work, thus 29 30508 evidencing a putative role of Geobacter in As release from soil mineral to pore water and in As 31 509 methylation. In accordance with the increase of DAsRB and AsMB in CF and CF-D water regimes, 32 33510 higher As(III) concentrations were detected in the corresponding soil pore water and higher 34 35511 methylated As was detected in the corresponding rice grains. 36 37512 Together, these outcomes indicate a dramatic effect of water management of rice paddies in shaping 38 39513 the rhizosphere microbiota. Continuous flooding promotes the proliferation of As-releasing 40 41514 bacterial taxa, whereas in aerobic rice microorganisms that reduce the solubility of As in the soil 42515 solution are favored. Introducing a 2 weeks-drainage period before the flowering stage within a 43 44516 continuous flooding regime leads to intermediate relative abundances of As-affecting bacteria. A 45 46517 decrease in the flooding intensity might be helpful for the selection of an As-stabilizing microbial 47 48518 community with the reduction of bioavailable As concentration in the soil solution, thus decreasing 49 50519 As contamination in rice grains. 51 52520 53521 Funding 54 55522 The research was supported by Ministry of University and Research program PRIN (2010JBNLJ7- 56 57523 004). Sarah Zecchin was awarded of a PhD fellowship from the University of Milan, Doctorate 58 59524 School of Food Systems. 60 61525 62 63 15 64 65 526 Conflict of interest 527 The authors declare that they have no conflict of interest. 1 2528 3 4529 Ethical statement 5 6530 This article does not contain any study with human participants or animals performed by any of the 7 8531 authors. 9 532 10 11533 Informed consent 12 13534 Informed consent was obtained from all individual participants included in the study. 14 15535 16 17536 References 18 19537 20 21538 Albuquerque L, França L, Rainey FA, Schumann P, Nobre MF, da Costa MS (2011) Gaiella occulta gen. nov., sp. nov, 22539 a novel representative of a deep branching phylogenetic lineage within the class Actinobacteria and proposal of 23 24540 Gaiellaceae fam. nov. and Gaiellales ord. nov.. System Appl Microbiol 34:595-599 25541 26 27542 Andres J, Bertin PN (2016) The microbial genomics of arsenic. FEMS Microbiol Reviews 39:1-24 28543 29 30544 Arao T, Kawasaki A, Baba K, Matsumoto S (2011) Effects of arsenic compound amendment on arsenic speciation in 31545 rice grain. Environ Sci Technol 45:1291-1297 32 33546 34547 Barka EA, Vatsa P, Sanchez L, Gaveau-Vallant N, Jacquard C, Klenk HP, Clément C, Ouhdouch Y, van Wezel GP 35 36548 (2016) Taxonomy, physiology, and natural products of Actinobacteria. Microbiol Mol Biol Reviews 80:1-43 37549 38 39550 Borch T, Kretzschmar R, Kappler A, Van Cappellen P, Ginder-Vogel M, Voegelin A, Campbell K (2010) 40551 Biogeochemical redox processes and their impact on contaminant dynamics. Environ Sci Technol 44:15-23 41 42552 43 553 Bulgarelli D, Schlaeppi K, Spaepen S, van Themaat EVL, Schulze-Lefert P (2013) Structure and functions of the 44 45554 bacterial microbiota of plants. Annu Rev Plant Biol 64:807-838 46 555 47 48556 Caporaso JG, Bittinger K, Bushman FD, DeSantis TZ, Andersen GL, Knight R (2010) PyNAST: a flexible tool for 49 50557 aligning sequences to a template alignment. Bioinformatics 26(2):266-267 (b) 51558 52 53559 Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Gonzalez Peña A, Goodrich 54560 JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, 55 56561 Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R 57562 (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7(5):335-336 (a) 58 59563 60564 Cavalca L, Corsini A, Zaccheo P, Andreoni V, Muyzer G (2013) Microbial transformations of arsenic: perspectives for 61 62 63 16 64 65 565 biological removal of arsenic from water. Future Microbiol 86:753-768 566 1567 Commission E (2015) Commission regulation (EC) No 2015/1006 of 25 June 2015 amending Regulation (EC) No 2 3568 1881/2006 as regard maximum levels of inorganic arsenic in foodstuffs. OJ L 161:14-16 4 569 5 6570 Dahl C, Friedrich C, Kletzin A (2008) Sulfur oxidation in prokaryotes. In: Encyclopedia of Life Sciences (ELS). John 7 571 Wiley & Sons, Chichester, UK 8 9572 10 11573 Das S, Chou ML, Jean JS, Liu CC, Yang HJ (2016) Water management impacts on arsenic behavior and rhizosphere 12574 bacterial communities and activities in a rice agro-ecosystem. Sci Total Environ 542:642–652 13 14575 15576 Dastager SG, Lee J, Ju Y, Park D, Kim C (2008) Marmoricola bigeumensis sp. nov., a member of the family 16 17577 Nocardioidaceae. Int J Syst Evol Micr 58:1060-1063 18578 19 20579 Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2480-2461 21580 22 23581 Edwards J, Johnson C, Santos-Medellín C, Lurie E, Podishetty NK, Bhatnagar S, Eisen JA, Sundaresan V (2015) 24582 Structure, variation, and assembly of the root-associated microbiomes of rice. PNAS 112:911-920 25 26583 27584 Emerson D (2012) Biogeochemistry and microbiology of microaerobic Fe(II) oxidation. Biochem Soc Trans 40:1211- 28 29585 1216 30586 31 32587 Emerson D, Fleming EJ, McBeth JM (2010) Iron-oxidizing bacteria: an environmental and genomic perspective. Ann 33588 Rev Microbiol 64:561-83 34 35589 36 590 European Food Safety Authority (2009) Scientific opinion on arsenic in food. EFSA J 7:1-1351 37 38591 39 592 European Food Safety Authority (2014) Dietary exposure to inorganic arsenic in the European population. EFSA J 40 41593 12:3597 42 594 43 44595 Friedrich CG, Bardischewsky F, Rother D, Quentmeier A, Fischer J (2005) Prokaryotic sulfur oxidation. Curr Opin 45 46596 Microbiol 8:253-259 47597 48 49598 Hamady M, Knight R (2009) Microbial community profiling for human microbiome projects: tools, techniques and 50599 challenges. Genome Res 19:1141-1152 51 52600 53601 Hamilton TL, Jones DS, Schaperdoth I, Macalady JL (2015) Metagenomic insight into S(0) precipitation in a terrestrial 54 55602 subsurface lithoautotrophic ecosystem. Front Microbiol 5:1-16 56603 57 58604 Hedrich S, Schlömann M, Johnson DB (2011) The iron-oxidizing proteobacteria. Microbiology 157:1551-1564 59605 60 61606 Heikens A (2006) Arsenic contamination of irrigation water, soil and crops in Bangladesh: risk implications for 62 63 17 64 65 607 sustainable agriculture and food safety in Asia. RAP Publication (FAO), Bangkok, Thailand 608 1609 Hori T, Müller A, Igarashi Y, Conrad R, Friedrich MW (2010) Identification of iron-reducing microorganisms in anoxic 2 3610 rice paddy soil by 13C-acetate probing. ISME J 4:267-278 4 611 5 6612 Huang H, Jia Y, Sun GX, Zhu YG (2012) Arsenic speciation and volatilization from flooded paddy soils amended with 7 613 different organic matters. Environ Sci Technol 46:2163-2168 8 9614 10 11615 Jia Y, Huang H, Zhong M, Wang F, Zhang L, Zhu YG (2013) Microbial arsenic methylation in soil and rice 12616 rhizosphere. Environ Sci Technol 47:3141-3148 13 14617 15618 Jones D, Keddie RM (2006) The genus Arthrobacter. Prokaryotes 3:945-960 16 17619 18620 Kocar BD, Fendorf S (2009) Thermodynamic constraints on reductive reactions influencing the biogeochemistry of 19 20621 arsenic in soils and sediments. Environ Sci Technol 43:4871-4877 21622 22 23623 Kügler JH, Le Roes-Hill M, Syldatk C, Hausmann R (2015) Surfactants tailored by the class Actinobacteria. Frontier 24624 Microbiol 6:1-23 25 26625 27626 Langille MGI, Zaneveld J, Caporaso JG, McDonald D, Knights D, Reyes JA, Clemente JC, Burkepile DE, Vega 28 29627 Thurber RL, Knight R, Beiko RG, Huttenhower C (2013) Predictive functional profiling of microbial communities 30628 using 16S rRNA marker gene sequences. Nat Biotechnol 31(9):814-821 31 32629 33630 Lee S (2013) Enhancement of arsenic mobility by Fe(III)-reducing bacteria from iron oxide minerals. J Mater Cycles 34 35631 Waste 15:362-369 36 632 37 38633 Lee SD (2007) Marmoricola aequoreus sp. nov., a novel actinobacterium isolated from a marine sediment. Int J Syst 39 634 Evol Microbiol 57:1391-1395 40 41635 42 636 Lee SD, Lee DW, Ko Y (2011) sp. nov.. Int J Syst Evol Microbiol 61:1628-1631 43 Marmoricola korecus 44637 45 46638 Lee DW, Lee SD (2010) Marmoricola scoriae sp. nov., isolated from volcanic ash. Int J Syst Evol Microbiol 60:2135- 47639 2139 48 49640 50641 Lee HJ, Lee SH, Lee S, Lee JS, Kim Y, Kim S, Joen CO (2014) Ramlibacter solisilvae sp. nov., isolated from forest 51 52642 soil, and emended description of the genus Ramlibacter. Int J Syst Evol Microbiol 64:1317-1322 53643 54 55644 Li R, Ago Y,Liu W, Mitani N, Feldmann J, McGrath SP, Ma JF,Zhao F (2009) The rice aquaporin Lsi1 mediates uptake 56645 of methylated arsenic species. Plant Physiol 150:2071-2080 57 58646 59647 Li RY, Stroud JL, Ma JF, McGrath SP, Zhao FJ (2009) Mitigation of arsenic accumulation in rice with water 60 61648 management and silicon fertilization mitigation of arsenic accumulation in rice with water management and silicon 62 63 18 64 65 649 fertilization. Environ Sci Technol 43:3778-3783 650 1651 Loeppert RH, Inskeep WP (1996) Iron. In: Sparks DL, Page AL, Helmke PA, Loeppert RH, Soltanpour PN, Tabatabai 2 3652 MA, Summer ME (ed) Methods of soil analysis. Part 3. Chemical methods. Soil Science Society of America, Madison, 4 653 WI, USA, pp 639-663 5 6654 7 655 Lomax C, Liu WJ, Wu L, Xue K, Xiong J, Zhou J, McGrath SP, Meharg AA, Miller AJ, Zhao FJ (2012) Methylated 8 9656 arsenic species in plants originate from soil microorganisms. New Phytol 193:665-72 10 11657 12658 Lu YH, Rosencrantz D, Liesack W, Conrad R (2006) Structure and activity of bacterial community inhabiting rice roots 13 14659 and the rhizosphere. Environ Microbiol 8:1351-1360 15660 16 17661 Ma R, Shen J, Wu J, Tang Z, Shen Q, Zhao FJ (2014) Impact of agronomic practices on arsenic accumulation and 18662 speciation in rice grain. Environ Pollut 194:217-223 19 20663 21664 Mailloux BJ, Alexandrova E, Keimowitz AR, Wovkulich K, Freyer GA, Herron M, Stolz JF, Kenna TC, Pichler T, 22 23665 Polizzotto ML, Dong H, Bishop M, Knappett PSK (2009) Microbial mineral weathering for nutrient acquisition releases 24666 arsenic. Appl Environ Microbiol 75:2558-2565 25 26667 27668 Martin M, Violante A, Ajmone-Marsan F, Barberis E (2014). Surface interactions of arsenite andarsenate on soil 28 29669 colloids. Soil Sci Soc Am J 78:157-170 30670 31 32671 Meharg AA, Zhao F (2012) Biogeochemistry of arsenic in paddy environments. In: Arsenic & Rice. Springer 33672 Netherlands, Berlin, Germany pp 71-101 34 35673 36 674 Meng X, Qin J, Wang L, Duan G, Sun G, Wu H, Chu C, Ling H, Rosen BP, Zhu Y (2011) Arsenic biotransformation 37 38675 and volatilization in transgenic rice. New Phytol 191:49-56 39 676 40 41677 Mielke PW, Berry KJ, Johnson ES (1976). Multi-response permutation procedures for a priori classifications. Commun 42 678 Stat Theor Methods 5:1409-1424 43 44679 45 46680 Moreno-Jiménez E, Meharg AA, Smolders E, Manzano R, Becerra D, Sánchez-Llerena J, Albarrán Á, López-Piñero A 47681 (2014) Sprinkler irrigation of rice fields reduces grain arsenic but enhances cadmium. Sci Total Environ 485-486:468- 48 49682 473 50683 51 52684 Pereira IAC, Ramos AR, Grein F, Marques MC, da Silva SM, Venceslau SS (2011) A comparative genomic analysis of 53685 energy metabolism in sulfate reducing bacteria and archaea. Front Microbiol 2:1-22 54 55686 56687 Pester M, Knorr K, Friedrich MW, Wagner M, Loy A (2012). Sulfate-reducing microorganisms in wetlands - fameless 57 58688 actors in carbon cycling and climate change. Front Microbiol 3:1-19 59689 60 61690 Price MN, Dehal PS, Arkin AP (2009) FastTree: computing large minimum evolution trees with profiles instead of a 62 63 19 64 65 691 distance matrix. Mol Biol Evol 26:1641-1650 692 1693 Quast C, Pruesse E, Ylmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2013) The SILVA ribosomal 2 3694 RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41:590-596 4 695 5 6696 Rabus R, Venceslau SS, Wöhlbrand L, Voordouw G, Wall JD, Pereira IAC (2015) A post-genomic view of the 7 697 ecophysiology, catabolism and biotechnological relevance of sulphate-reducing prokaryotes. Adv Microb Physiol 8 9698 66:55-321 10 11699 12700 Ramel F, Brasseur G, Pieulle L, Valette O, Hirschler-Réa A, Fardeau ML, Dolla A (2015) Growth of the obligate 13 14701 anaerobe Desulfovibrio vulgaris Hildenborough under continuous low oxygen concentration sparging: impact of the 15702 membrane-bound oxygen reductases. PLoS One 10:1-17 16 17703 18704 Shrestha PM, Kube M, Reinhardt R, Liesack W (2009) Transcriptional activity of paddy soil bacterial communities. 19 20705 Environ Microbiol 11:960-970 21706 22 23707 Singh R, Singh S, Parihar P, Singh VP, Prasad SM (2015) Arsenic contamination, consequences and remediation 24708 techniques: A review. Ecotoxicol Environ Saf 112:247-270 25 26709 27710 Slyemi D, Bonnefoy V (2012) How prokaryotes deal with arsenic. Environ Microbiol Rep 4:571-586 28 29711 30712 Somenahally AC, Hollister EB, Loeppert RH, Yan W, Gentry TJ (2011) Microbial communities in rice rhizosphere 31 32713 altered by intermittent and continuous flooding in fields with long-term arsenic application. Soil Biol Biochem 43:1220- 33714 1228 (a) 34 35715 36 716 Song J, Cho J (2007) Methylibium aquaticum sp. nov., a betaproteobacterium isolated from a eutrophic freshwater 37 38717 pond. Int J Syst Evol Microbiol 57:2125-2128 39 718 40 41719 Spanu A, Daga L, Orlandoni AM, Sanna G (2012) The role of irrigation techniques in arsenic bioaccumulation in rice 42 720 ( L.). Environ Sci Technol 42:8333-8340 43 Oryza sativa 44721 45 46722 Stackebrandt E, Verbarg S, Frühling A, Busse H, Tindall BJ (2009) Dissection of the genus Methylibium: 47723 reclassification of Methylibium aquaticum as Piscinibacter aquaticus gen. nov., comb. nov. and Methylibium 48 49724 subsaxonicum as Rivibacter subsaxonicus gen. nov., comb. nov. and emended descriptions of the genera Rhizobacter 50725 and Methylibium. Int J Syst Evol Microbiol 59:2552-2560 51 52726 53727 Stubner S, Wind T, Conrad R (1998) Sulfur oxidation in rice field soil: activity, enumeration, isolation and 54 55728 characterization of thiosulfate-oxidizing bacteria. System Appl Microbiol 21:569-578 56729 57 58730 Sun L, Zheng M, Liu H, Peng S, Huang J, Cui K, Nie L (2014) Water management practices affect arsenic and 59731 cadmium accumulation in rice grains. Scientific World J 2014: Article ID 596438 60 61732 62 63 20 64 65 733 Suralta RR, Yamauchi A (2008) Root growth, aerenchyma development, and oxygen transport in rice genotype 734 subjected to drought and waterlogging. Environ Exp Bot 64(1):75-82 1735 2 3736 Takahashi Y, Minamikawa R, Hattori KH, Kurishima K, Kihou N, Yuita K (2004) Arsenic behavior in paddy fields 4 737 during the cycle of flooded and non-flooded periods. Environ Sci Technol 38:1038-1044 5 6738 7 739 Treude N, Rosencrantz D, Liesack W, Schnell S (2003) Strain FAc12, a dissimilatory iron-reducing member of the 8 9740 Anaeromyxobacter subgroup of Myxococcales. FEMS Microbiol Ecol 44:261-269 10 11741 12742 Urzì C, Salamone P, Schumann P, Stackebrandt E (2000) Marmoricola aurantiacus gen. nov., sp. nov., a coccoid 13 14743 member of the family Nocardioidaceae isolated from a marble statue. Int J Syst Evol Microbiol 50:529-536 15744 16 17745 Ventura M, Canchaya C, Tauch A, Chandra G, Fitzgerald GF, Chater KF, van Sinderen D (2007) Genomics of 18746 Actinobacteria: tracing the evolutionary history of an ancient phylum. Microbiol Mol Biol R 71:495-548 19 20747 21748 Wang P, Sun G, Jia Y, Meharg AA, Zhu Y (2014) A review on completing arsenic biogeochemical cycle: microbial 22 23749 volatilization of arsines in environment. J Environ Sci 26:371-381 24750 25 26751 Ward NL, Challacombe JF, Janssen PH, Henrissat B, Coutinho PM, Wu M, Xie G, Haft DH, Sait M, Badger J, 27752 Barabote RD, Bradley B, Brettin TS, Brinkac LM, Bruce D, Creasy T, Daugherty SC, Davidsen TM, DeBoy RT, Detter 28 29753 JC, Dodson RJ, Durkin AS, Ganapathy A, Gwinn-Giglio M, Han CS, Khouri H, Paulsen I, Penn K, Ren Q, Rosovitz 30754 MJ, Selengut JD, Shrivastava S, Sullivan SA, Tapia R, Thompson LS, Watkins KL, Yang Q, Yu C, Zafar N, Zhou L, 31 32755 Kuske CR (2009) Three genomes from the phylum Acidobacteria provide insight into the lifestyles of these 33756 microorganisms in soils. Appl Environ Microbiol 75:2046-2056 34 35757 36 758 Wörner S, Zecchin S, Dan J, Hristova Todorova N, Loy A, Conrad R, Pester M (2016) Gypsum amendment to rice 37 38759 paddy soil stimulated bacteria involved in sulfur cycling but largely preserved the phylogenetic composition of the total 39 760 bacterial community. Environ Microbiol Rep 8:413-423 40 41761 42 762 Xiao K, Li L, Ma L, Zhang S, Bao P, Zhang T, Zhu Y (2016) Metagenomic analysis revealed highly diverse microbial 43 44763 arsenic metabolism genes in paddy soils with low-arsenic contents. Environ Poll 211:1-8 45 46764 47765 Yabuuchi E, Kosako Y (2005) Sphingomonas. Bergey’s Manual of Systematics of Archaea and Bacteria, John Wiley & 48 49766 Sons, Chichester, UK 50767 51768 Yamaguchi N, Nakamura T, Dong D, Takahashi Y, Amachi S, Makino T (2011). Arsenic release from flooded paddy 52 53769 soils is influenced by speciation, Eh, pH, and iron dissolution. Chemosphere 83:25-932 54 55770 56771 Yamamura S, Amachi S (2014) Microbiology of inorganic arsenic: from metabolism to bioremediation. J Biosci Bioeng 57 58772 1:1-9 59773 60 61774 Ye J, Rensing C, Rosen BP, Zhu Y (2012) Arsenic biomethylation by photosynthetic organisms. Trends Plant Sci 62 63 21 64 65 775 17:155-162 776 1 777 Yoon J, Park Y (2006) The genus Nocardioides. Prokaryotes 3: 099-1113 2 3778 4 779 Zecchin S, Corsini A, Martin M, Romani M, Beone GM, Zanchi R, Zanzo E, Tenni D, Fontanella MC, Cavalca L 5 6780 (2017) Rhizospheric iron and arsenic bacteria affected by water regime: Implications for metalloid uptake by rice. Soil 7 781 Biol Biochem 106:129-137 8 9782 10 11783 Zhao FJ, Harris E, Yan J, Ma J, Wu L, Liu W, McGrath SP, Zhou J, Zhu YG (2013) Arsenic methylation in soils and its 12784 relationship with microbial arsM abundance and diversity, and As speciation in rice. Environ Sci Technol 47:7147-7154 13 14785 15786 Zheng MZ, Cai C, Hu Y, Sun GX, Williams PN, Cui HJ, Li G, Zhao FJ, Zhu YG (2011) Spatial distribution of arsenic 16 17787 and temporal variation of its concentration in rice. New Phytol 189:200-209 18788 19 20789 Zheng R, Sun G, Zhu Y (2012) Effects of microbial process on the fate of arsenic in paddy soil. Chinese Sci Bull 21790 58:186-193 22 23791 24792 Zhu YG, Yoshinaga M, Zhao FJ, Rosen, BP (2014) Earth abides arsenic biotransformation. Annu Rev Earth Planet Sci 25 26793 42:443-467 27794 28 29795 30 31796 32 33797 Figure captions 34 35798 36 37799 Fig. 1 Scheme of the water regimes used in the experimental setup. Red arrows indicate sampling 38 800 points 39 40801 41 42802 Fig. 2 Alpha diversity evaluated with ACE index and Simpson’s evenness measure, assuming a 43 44803 sample size of 2000 reads (a) and by observed species on rarefied samples (b). Values are shown for 45 46804 the original soil (T0), rhizosphere soil and rhizoplane treated under continuous flooding (CF RS and 47 48805 CF RP), under CF with 14 days of drainage before flowering (CF-D RS and CF-D RP) and under 49806 watering every 10 days (D RS and D RP) 50 51807 52 53808 Fig. 3 Beta diversity analysis of all treatments, included original soil (T0), rhizosphere soil and 54 55809 rhizoplane treated with continuous flooding (CF RS and CF RP), with 14 days of drainage before 56810 flowering (CF-D RS and CF-D RP) and with watering every 10 days (D RS and D RP). The 57 58811 principal coordinate analysis was performed calculating unweighted (a, b, c) and weighted UniFrac 59 60812 distances (d, e, f) according to Hamady and Knight (2009). The significance of the groups 61 62 63 22 64 65 813 determined by the sample identity (a, d), the water regime (b, e) and the root-soil compartment (c, f) 814 was tested with multi-response permutation procedure (MRPP) 1 2815 3 4816 Fig. 4 Shared and exclusive OTUs at 97% similarity retrieved under continuous flooding (CF), 5 6817 under continuous flooding with drainage before flowering (CF-D) and with watering (D) in 7818 rhizosphere soil (a) and in the rhizoplane (b) 8 9819 10 11820 Fig. 5 Relative abundance (%) of phyla and proteobacterial classes (a) and genera above 1 % of 12 13821 relative abundance (b) retrieved in the treatments: initial soil (T0), continuously flooded rhizosphere 14822 soil and rhizoplane (CF RS and CF RP), with 14 days of drainage before flowering (CF-D RS and 15 16823 CF-D RP) and with watering every 10 days (D RS and D RP) 17 18824 19 20825 Fig. 6 Relative abundance (% ± SD) of species potentially able to process arsenic directly (a) or 21826 indirectly as a consequence of their metabolism (b) in rhizosphere soil and rhizoplane of plants 22 23827 cultivated under continuous flooding (CF RS and CF RP), under continuous flooding with 14 days 24 25828 drainage before flowering (CF-D RS and CF-D RP) or with watering every 10 days (D RS and D 26 27829 RP). The metabolic groups considered in this analysis were dissimilatory As(V)-reducing bacteria 28 29830 (DAsRB), As-resistant bacteria (AsRB), As(III)-oxidizing bacteria and As(III)-methylating bacteria 30 831 31 (AsMB), dissimilatory Fe(III)-reducing bacteria (DFeRB), Fe(II)-oxidizing bacteria (FeOB), 32 2- 832 dissimilatory SO4 -reducing bacteria (DSRB) and sulfur-oxidizing bacteria (SOB) 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 23 64 65 Table

Table 1 Chemical analyses of the soil solution in the macrocosms.

Chemical Parameter CF1 CF-D2 D3

Tot As (μg L-1) 125.3±5.2 1.82±0.41 Bdl4

Fe(II) (mg L-1) 51.1±1.75 0.05±0.01 0.21±0.05

2- -1 S-SO4 (mg L ) 0.06±0.01 4.09±0.27 1.69±0.52

2- -1 N-NO3 (mg L ) 0.04±0.01 0.27±0.05 2.31±0.91

2- -1 P-PO4 (mg L ) 0.33±0.18 0.19±0.001 0.23±0.03

pH 6.2±0.25 5.9±0.25 6.0±0.34

1Continuous flooding. 2Continuous flooding with 14 days drainage before flowering. 3Watering every 7-10 days. 4Below detection limit.

Table 2 Number of reads produced with 16S rRNA amplicon pyrosequencing that passed the quality check, with related diversity information. Seq. length Standardized2 Compartment Sample ID N. of reads N. of OTUs1 N. of phyla (bp) N. of OTUs Soil T03 18428 365 26 5598 898 55 32 Rhizosphere CF4 16497 365 27 5934 984 28 28 soil CF-D5 28005 364 28 7108 777 31 24 D6 26309 365 26 7097 836 33 18 Rhizoplane CF 20370 364 28 8088 1158 51 25 CF-D 19346 364 27 7579 1062 67 19 D 21424 364 27 5122 699 61 15 1Operational taxonomic units defined at 97% sequence identity. 2Standardized sampling effort of 2000 reads. 3Initial soil used for the experiment. 4Continuous flooding. 5Continuous flooding with 14 days drainage before flowering. 6Watering every 7-10 days.

Table 3 Relative abundance of taxa (%) involved in arsenic, iron and sulfur cycles (for references see Table S1) that significantly varied in the root compartments of rice plants from different treatments. Rhizosphere soil Rhizoplane Taxon T01 CF2 CF-D3 D4 CF CF-D D Anaeromyxobacter 0.13±0.11 1.11±0.35 0.13±0.02 0 0.64±0.32 0.12±0.09 0 Aquabacterium 0 0.07±0.05 0.05±0.01 0.01±0.01 0.03±0.03 0 0 Aurantimonas 0 0 0 0.31±0.11 0 0 0.12±0.08 Bacillus 0.28±0.23 0.23±0.05 0.02±0.04 0.14±0.08 0.18±0.07 0.15±0.1 0.04±0.02 Desulfobacteraceae 0.03±0.03 0.59±0.3 0.01±0.01 0 0.05±0.04 0.07±0.07 0 Geobacter 0.03±0.02 0.65±0.13 0.45±0.16 0.02±0.04 2.04±0.54 0.55±0.25 0 Leptothrix 0 0.1±0.05 0.07±0.02 0 0.02±0.02 0.01±0.02 0 Pseudomonas 0.04±0.03 0.28±0.01 1.82±0.35 2.69±0.59 0.34±0.19 0.01±0.02 0.18±0.07 Rhizobium 0.27±0.35 0.04±0.001 0.07±0.04 2.06±0.63 0.44±0.16 1.21±0.25 1.90±0.47 Rhodobacter 0 0.2±0.21 0.13±0.04 0.06±0.02 0.1±0.03 0.01±0.02 0 Rhodovulum 0 0.13±0.05 0.05±0.03 0 0.05±0.06 0 0 Stenotrophomonas 0.01±0.01 0 0.07±0.08 0.83±0.22 0.01±0.02 0 0.98±0.38 Thermomonas 0.12±0.12 0.05±0.06 0.26±0.16 1.48±0.53 0.10±0.07 0.09±0.04 0.77±0.1 Variovorax 1.1±0.51 0.23±0.06 0.69±0.04 0.22±0.06 0.16±0.11 0.08±0.02 6.76±1.44 1Initial soil used for the experiment. 2Continuous flooding. 3Continuous flooding with 14 days drainage before flowering. 4Watering every 7-10 days.

Figure Click here to download Figure FIG1.tiff Figure Click here to download Figure FIG2.tiff Figure Click here to download Figure FIG3.tiff Figure Click here to download Figure FIG4.tiff Figure Click here to download Figure FIG6.tiff Figure Click here to download Figure FIG5a.tiff Figure Click here to download Figure Fig5b.tiff Supplementary Tables and Figures

Applied Microbiology and Biotechnology

Influence of water management on the active root-associated microbiota involved in arsenic, iron and sulfur cycles in rice paddies

Sarah Zecchina, Anna Corsinia, Maria Martinb and Lucia Cavalcaa*

aDipartimento di Scienze per gli Alimenti, la Nutrizione e l'Ambiente (DeFENS), Università degli

Studi di Milano, Milano, Italy

bDepartment of Agriculture, Forest and Food Science, University of Turin, Turin, Italy

*corresponding author:

Phone: +39 02 503 19116 Fax: +39 02 503 19238 E-mail: [email protected]

1 Supplementary Figures

Contents

Table S1 Bacterial taxa retrieved in this study for which arsenic-processing and/or iron- and sulfur- processing have been experimentally demonstrated or inferred by the presence of marker genes. Numbers are referred to the literature reported in pages 10-12.

Table S2 Relative abundance (% ± SD) of taxa involved in either direct or indirect arsenic processing (see Table S1). Values are shown for the different compartments, managed either with continuous flooding (CF), with continuous flooding with 2 weeks of drainage before flowering (CF-D) or with watering every 10 days (D).

Table S3 Mean counts (number of reads) calculated for the OTUs that vary significantly (according to ANOVA, p < 0.05, after Bonferroni’s correction) in the macrocosms treated either with continuous flooding (CF), with continuous flooding with 2 weeks of drainage before flowering (CF-D) or with watering every 10 days (D).

Figure S1 Rank abundance (a) and number of phyla categorized according to their relative abundance (b). Values are shown for the original soil, rhizosphere soil and rhizoplane (T0, RS and RP) managed either with continuous flooding (CF), with continuous flooding with 14 days drainage before flowering (CF-D) or with watering every 10 days (D)

Figure S2 Relative abundance (%) of species potentially able to process arsenic directly (a) or indirectly as a consequence of their metabolism (b) in the T0 soil. The metabolic groups considered in this analysis were dissimilatory As(V)-reducing bacteria (DAsRB), As-resistant bacteria (AsRB), As(III)-oxidizing bacteria and As(III)-methylating bacteria (AsMB), dissimilatory Fe(III)-reducing 2- bacteria (DFeRB), Fe(II)-oxidizing bacteria (FeOB), dissimilatory SO4 -reducing bacteria (DSRB)

2 Table S1 Bacterial taxa retrieved in this study for which arsenic-processing and/or iron- and sulfur- processing have been experimentally demonstrated or inferred by the presence of marker genes. Numbers are referred to the literature reported in pages 10-12.

As DISS. Diss. Fe(II) Sulfur Diss. As(V) resistance As(III) As(III) Taxon Fe(III) sulfate oxidation oxidation reduction (ars or oxidation methylation reduction reduction ACR) Candidatus ------1 Solibacter Geothrix 2, 3, 4 ------Mycobacterium - - - - - 5 - - Amycolatopsis ------1 Streptomyces - - - - - 5 - - Conexibacter ------1 Aurantimonas - - 6 - - - - - Bradyrhizobium - - 6 - - - - - Rhodopseudomonas - 2, 7, 8, 9 6 - - 10 - 11, 1, 12 Rhodomicrobium - 7, 8 - - - - - 1 Methylobacterium - - 13 - - - - - Mesorhyzobium - 7 - - - 5 14 - Rhizobium ------14 - Magnetospirillum - - - - - 10 - - Rhodobacter - 2, 7, 8, 9 6 - - - - - Rhodovulum - - 7, 8 - - - - - Sphingopyxis - - - - - 5 - - Achromobacter - - - - - 10 15, 14 12 Burkholderia - - - - - 10 15 12 Limnobacter ------15 - Polynucleobacter - - 6 - - - - - Ralstonia - - 6 - - - 15 - Acidovorax - 2, 7, 8, 9 - - - - 15 - Aquabacterium - 7, 8 ------Comamonas - - 6 - - - - - Leptothrix - 2, 8, 9 ------Polaromonas - - 6 - - 10 15 - Variovorax ------14 - Herminiimonas - - 6 - - - 15, 14 - Thiobacillus 4 2, 7, 8, 9 6 - - - - 1 Sideroxydans - 2, 7, 8, 9 - - - 10 - - Dechloromonas - 7 6 - - 10 15 - Acidiferrobacter - 8 ------Acinetobacter - - - - - 10 15 - Pseudomonas - 7 - - - 5 15 - Stenotrophomonas ------15 - Thermomonas - 7, 8 ------Desulfobacteraceae - - - 16 - - - - Pelobacter 4 - - - - 10 - - Geobacter 2, 3, 4 7 - - 15, 10 10 - 21 Geothermobacter 17 ------

3 Anaeromyxobacter 18 - 6 - - 10 - - Desulfomonile - - - 16 - - - - Syntrophus - - - - - 10 - - Desulfovirga - - - 16 - - - - Syntrophobacter - - - 16 - - - - Cytophaga ------1 Flavobacterium ------12 Chitinophaga ------1 Niastella ------1 Nostoc ------19 Bacillus 4 - - - 15, 10 5 - - Clostridium ------20 Desulfitobacterium - - - - 15, 10 - - 1 Desulfosporosinus - - - 16 15, 10 - - - Pelotomaculum ------1 Gemmatimonas ------1 Nitrospira ------1 Spirochaeta - - 6 - - - - - Opitutus - - - - - 10 - 1

4

Table S2 Relative abundance of taxa involved in either direct or indirect arsenic processing (see Table S1).

Rhizosphere soil Rhizoplane Taxon T01 CF2 CF-D3 D4 CF CF-D D Candidatus Solibacter 0.67±0.255 0.71±0.3 0.56±0.17 0.34±0.06 0.97±0.21 0.92±0.21 0.35±0.17 Geothrix 0 0.01±0.02 0.02±0.02 0 0.02±0.02 0 0 Mycobacterium 0.01±0.01 0.01±0.02 0.01±0.01 0.01±0.01 0 0 0.01±0.02 Amycolatopsis 0.01±0.01 0 0 0 0 0 0 Streptomyces 0.14±0.19 0.03±0.02 0.01±0.02 0.12±0.01 0.01±0.02 0 0.21±0.1 Conexibacter 0.09±0.09 0.1±0.06 0 0 0.02±0.04 0 0 Aurantimonas 0 0 0 0.31±0.11 0 0 0.12±0.08 Bradyrhizobium 0.34±0.27 0.01±0.02 0.11±0.1 0.09±0.04 1.76±0.6 2.11±0.05 0.03±0.03 Rhodopseudomonas 0 0 0.01±0.01 0.01±0.01 0.09±0.06 0 0 Rhodomicrobium 0.05±0.04 0.05±0.06 0 0 0.02±0.02 0 0.01±0.02 Methylobacterium 0.02±0.03 0.01±0.02 0.01±0.01 0.01±0.03 0.03±0.03 0 0.14±0.02 Mesorhizobium 0.01±0.01 0 0 0.04±0.001 0.02±0.02 0.02±0.02 0.01±0.01 Rhizobium 0.27±0.35 0.04±0.001 0.07±0.04 2.06±0.63 0.44±0.16 1.21±0.25 1.90±0.47 Magnetospirillum 0.01±0.02 0.1±0.06 0.19±0.07 0 0.19±0.12 0.15±0.12 0 Rhodobacter 0 0.2±0.21 0.13±0.04 0.06±0.02 0.1±0.03 0.01±0.02 0 Rhodovulum 0 0.13±0.05 0.05±0.03 0 0.05±0.06 0 0 Sphingopyxis 0 0 0 0.05±0.03 0 0.06±0.02 0.16±0.09 Achromobacter 0.01±0.01 0.01±0.02 0.01±0.01 0.04±0.03 0.01±0.02 0.02±0.02 0.04±0.06 Burkholderia 0.03±0.02 0.05±0.02 0.01±0.01 0.15±0.03 0 0 0.04±0.03 Limnobacter 0 0 0.03±0.02 0 0 0 0 Polynucleobacter 0 0 0 0 0.01±0.02 0.01±0.02 0 Ralstonia 0 0 0.01±0.01 0.07±0.03 0.01±0.02 0 0.05±0.05 Acidovorax 0.02±0.03 0.03±0.02 0.07±0.07 0.06±0.02 0.14±0.16 0.08±0.1 0.01±0.01 Aquabacterium 0 0.07±0.05 0.05±0.01 0.01±0.01 0.03±0.03 0 0 Comamonas 0.01±0.02 0.01±0.02 0.34±0.09 0.04±0.01 0.01±0.02 0.04±0.02 0 Leptothrix 0 0.1±0.05 0.07±0.02 0 0.02±0.02 0.01±0.02 0 Polaromonas 0.02±0.02 0 0 0 0 0 0.01±0.01 Variovorax 1.1±0.51 0.23±0.06 0.69±0.04 0.22±0.06 0.16±0.11 0.08±0.02 6.76±1.44 Herminiimonas 0.01±0.02 0 0.01±0.01 0 0 0 0 Thiobacillus 0±0.01 0 0 0 0.05±0.04 0.03±0.03 0 Sideroxydans 0.02±0.03 0 0.04±0.02 0 0.03±0.03 0.02±0.02 0 Dechloromonas 0 0 0.03±0.03 0 0.06±0.03 0.02±0.02 0 Acidiferrobacter 0 0.01±0.02 0 0 0 0.02±0.04 0 Acinetobacter 0 0 0 0.12±0.05 0.02±0.04 0 0.01±0.01 Pseudomonas 0.04±0.03 0.28±0.01 1.82±0.35 2.69±0.59 0.34±0.19 0.01±0.02 0.18±0.07 Stenotrophomonas 0.01±0.01 0 0.07±0.08 0.83±0.22 0.01±0.02 0 0.98±0.38 Thermomonas 0.12±0.12 0.05±0.06 0.26±0.16 1.48±0.53 0.10±0.07 0.09±0.04 0.77±0.1 Desulfobacteraceae 0.03±0.03 0.59±0.3 0.01±0.01 0 0.05±0.04 0.07±0.07 0 Pelobacter 0 0 0.01±0.01 0 0.01±0.02 0 0 Geobacter 0.03±0.02 0.65±0.13 0.45±0.16 0.02±0.04 2.04±0.54 0.55±0.25 0 Geothermobacter 0 0.05±0.05 0 0 0 0 0 Anaeromyxobacter 0.13±0.11 1.11±0.35 0.13±0.02 0 0.64±0.32 0.12±0.09 0 Desulfomonile 0 0 0 0 0.02±0.02 0.06±0.04 0

5 Syntrophus 0.01±0.01 0.05±0.06 0 0 0.11±0.04 0 0 Desulfovirga 0 0 0 0.01±0.01 0 0 0 Syntrophobacter 0.02±0.03 0.03±0.02 0 0 0.03±0.03 0 0 Cytophaga 0 0 0 0 0 0.01±0.02 0 Flavobacterium 0.02±0.01 0 0 0 0 0 0 Chitinophaga 0 0 0 0 0 0.01±0.02 0.03±0.02 Niastella 0.01±0.01 0 0.03±0.01 0 0.05±0.05 0 0.04±0.02 Nostoc 2.11±2.01 0.98±0.44 0.01±0.01 0.04±0.02 0.15±0.04 0.18±0.04 0.28±0.03 Bacillus 0.28±0.23 0.23±0.05 0.02±0.04 0.14±0.08 0.18±0.07 0.15±0.1 0.04±0.02 Clostridium 0.04±0.04 0.18±0.02 0.07±0.01 0.15±0.02 0.55±0.13 0.23±0.01 0 Desulfitobacterium 0 0 0 0 0 0.01±0.02 0 Desulfosporosinus 0 0 0.01±0.01 0 0 0 0 Pelotomaculum 0 0.03±0.02 0 0 0.01±0.02 0 0 Gemmatimonas 0.64±0.37 1.89±0.59 0.74±0.11 1.71±0.45 0.43±0.14 0.48±0.24 0.32±0.07 Nitrospira 0.01±0.01 0 0 0.03±0.01 0.08±0.07 0.2±0.15 0.01±0.01 Spirochaeta 0.01±0.02 0 0 0 0.05±0.05 0.01±0.02 0 Opitutus 0.05±0.02 0.01±0.02 0.04±0.04 0.01±0.01 0.15±0.13 0.01±0.02 0 1Initial soil used for the experiment. 2Continuous flooding. 3Continuous flooding with 14 days drainage before flowering. 4Watering every 7-10 days. 5Data are reported as percentage (%) ± standard deviation.

6

Table S3 Mean counts (number of reads) calculated for the OTUs that vary significantly (according to ANOVA, p < 0.05, after Bonferroni’s correction) in the macrocosms.

Compartment CF1 CF-D2 D3 Taxon OTU 0 0 83.7 Micrococcales denovo23217 1.7 0.7 39.7 Arthrobacter AB637277 0 0.3 22.3 Arthrobacter EU221355 0 0 37.7 Arthrobacter FJ382040 0.3 0.3 8.7 Agromyces denovo36205 Uncultured denovo9942 5.7 0 0 Gaiellales 0 22 0.7 Flavisolibacter denovo35275 0.3 9.3 0.3 Sphingomonas denovo27415 2 59.3 9.3 Pelomonas FJ269077 Rhizosphere soil 22.7 222.7 12 Comamonadaceae JN869130 1 18.3 0 Comamonadaceae EF018534 2.3 29 1 Comamonadaceae FQ658719 0 10.7 1 Comamonadaceae EU133771 0 5.3 0 Comamonadaceae JF267702 0 5.3 0 Comamonadaceae AY491563 4 110 21 Ramlibacter HQ640565 0.3 21.3 0.7 Pseudomonas JN038312 0 0 13.3 Xanthomonadaceae HQ341391 0 1.3 123 Lysobacter FR682714 7.3 0.7 0 Dictyoglomus denovo11774 0 0 25.3 Bacteria denovo26504 4 0.7 48.3 Arthrobacter FQ659744 0 1 12 Nocardioides denovo13694 Rhizoplane Uncultured EU132848 1.3 0 20 Gaiellales 0 0 13 Flavisolibacter JN409004 1Continuous flooding. 2Continuous flooding with 14 days drainage before flowering. 3Watering every 7-10 days.

7

Figure S1 Rank abundance (a) and number of phyla categorized according to their relative abundance (b). Values are shown for the original soil, rhizosphere soil and rhizoplane (T0, RS and RP) managed either with continuous flooding (CF), with continuous flooding with 14 days drainage before flowering (CF-D) or with watering every 10 days (D)

Figure S2 Relative abundance (%) of species potentially able to process arsenic directly (a) or indirectly as a consequence of their metabolism (b) in the T0 soil. The metabolic groups considered in this analysis were dissimilatory As(V)-reducing bacteria (DAsRB), As-resistant bacteria (AsRB),

8 As(III)-oxidizing bacteria and As(III)-methylating bacteria (AsMB), dissimilatory Fe(III)-reducing 2- bacteria (DfeRB), Fe(II)-oxidizing bacteria (FeOB), dissimilatory SO4 -reducing bacteria (DSRB)

9 References

1Jia Y, Huang H, Sun GX, Zhao FJ, Zhu YG (2012) Pathways and relative contributions to arsenic volatilization from rice plants and paddy soil. Environ Sc Technol 46:8090-8096

2Melton ED, Swanner ED, Behrens S, Schmidt C, Kappler A (2014) The interplay of microbially mediated and abiotic reactions in the biogeochemical Fe cycle. Nat Rev Microbiol 12:797-808

3Lee S (2013) Enhancement of arsenic mobility by Fe(III)-reducing bacteria from iron oxide minerals. J Mater Cycles Waste 15:362-369

4Lovley D (2006) Dissimilatory Fe(III)- and Mn(IV)-reducing prokaryotes. Prokaryotes 2:635-658

5Achour AR, Bauda P, Billard P (2007) Diversity of arsenite transporter genes from arsenic-resistant soil bacteria. Res Microbiol 158:128-137

6Meyer B, Imhoff JF, Kuever J (2007) Molecular analysis of the distribution and phylogeny of the soxB gene among sulfur-oxidizing bacteria – evolution of the Sox sulfur oxidation enzyme system. Environ Microbiol 9(12):2957-2977

7Dubinina GA, Sorokina AY (2014) Neutrophilic lithotrophic iron-oxidizing prokaryotes and their role in the biogeochemical processes of the iron cycle. Microbiology 83:1–14

8Hedrich S, Schlömann M, Johnson DB (2011) The iron-oxidizing proteobacteria. Microbiology 157:1551-1564

9Emerson D, Fleming EJ, McBeth JM (2010) Iron-oxidizing bacteria: an environmental and genomic perspective. Ann Rev Microbiol 64:561-83

10Giloteaux L, Duran R, Casiot C, Bruneel O, Elbaz-Poulichet F, Goñi-Urriza M (2013) Three-year survey of sulfate-reducing bacteria community structure in Carnoulès acid mine drainage (France), highly contaminated by arsenic. FEMS Microbiol Ecol 83:724-737

10 11Zhu YG, Yoshinaga M, Zhao FJ, Rosen, BP (2014) Earth abides arsenic biotransformation. Annu Rev Earth Planet Sci 42:443-467

12Drewniak L, Sklodowska A (2013) Arsenic-transforming microbes and their role in biomining processes. Environ Sci Pollut Res 20:7728-7739

13Friedrich CG, Bardischewsky F, Rother D, Quentmeier A, Fischer J (2005) Prokaryotic sulfur oxidation. Curr Opin Microbiol 8:253-259

14Hamamura N, Macur RE, Korf S, Ackerman G, Taylor WP, Kozubal M, Reysenbach AL, Inskeep WP (2009) Linking microbial oxidation of arsenic with detection and phylogenetic analysis of arsenite oxidase genes in diverse geothermal environments. 11(2):421-431

15Cavalca L, Corsini A, Zaccheo P, Andreoni V, Muyzer G (2013) Microbial transformations of arsenic: perspectives for biological removal of arsenic from water. Future Microbiol 86:753–768

16Muyzer G, Stams AJM (2008) The ecology and biotechnology of sulphate-reducing bacteria. Nat Rev Microbiol 6:441-454

17Kashefi K, Holmes DE, Baross JA, Lovley DR (2003) Thermophyli in the Geobacteraceae: Geothermobacter ehrlichii gen. nov., sp. nov., a novel thermophilic member of the Geobacteraceae from the “Bag City” hydrothermal vent. Appl Environ Microbiol 69(5):2985-2993

18Hori T, Müller A, Igarashi Y, Conrad R, Friedrich MW (2010) Identification of iron-reducing microorganisms in anoxic rice paddy soil by 13C-acetate probing. ISME J 4:267-278

19Ye J, Rensing C, Rosen BP, Zhu Y (2012) Arsenic biomethylation by photosynthetic organisms. Trends Plant Sci 17:155-162

20Bentley R, Chasteen TG (2002) Microbial methylation of metalloids: arsenic, antimony, and bismuth. Microbiol Mol Biol Rev 66(2): 250

11 21Aklujkar M, Krushkal J, DiBartolo G, Lapidus A, Land ML, Lovley DR (2009) The genome sequence of Geobacter metallireducens: features of metabolism, physiology and regulation common and dissimilar to Geobacter sulfurreducens. BMC Microbiology 9:109

12