Metal distribution and biological diversity of crusts in paddy fields polluted with different levels of cadmium

Ecotoxicology and Environmental Safety 184 (2019) 109620

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Metal distribution and biological diversity of crusts in paddy fields polluted with different levels of cadmium

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Huijuan Songa, Liang Penga,∗, Zhiyi Lia, Xiaozhou Denga, Jihai Shaoa, Ji-dong Gua,b a b

Department of Environmental Science and Engineering, Hunan Agricultural University, Changsha, 410128, PR China Laboratory of Environmental Microbiology and Toxicology, School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, PR China

A R T I C LE I N FO

A B S T R A C T

Keywords: Crust Heavy metal Paddy field Irrigation water

The paddy-crusts (PCs) play an important pole in the transformation and transfer of heavy metal in paddy. Different PCs were collected from paddy fields whose soils contained cadmium (Cd) at four concentration levels (0.61, 0.71, 1.53, and 7.08 mg/kg) in Hunan Province, China P.R. at Sep 2017. This metal's distribution among and biological community structures of PCs were both measured. Our results indicated that PCs were able to accumulate Cd from irrigation water and soil. With greater Cd levels in paddy fields, the weak EPS-binding Cd fraction decreased whereas the non-EDTA-exchangeable Cd fraction increased. The sorbed Cd fraction was initially enhanced at low-to mid-level Cd concentrations, but then gradually declined. Biomineralization was shown to function as the dominant Cd accumulation mechanism in non-EDTA-exchangeable fractions. The biological diversity of soil microbes decreased with more Cd in soil, and the Proteobacteria, Bacteroidetes, and Cyanobacteria were the dominant phyla in all the sampled PCs. Canonical correspondence analysis (CCA) between the composition of microbial communities and soil chemical variables in the PCs clustered all samples based on the Cd-contaminated level, and demonstrated that Cd, Mn, and Fe all significantly influenced the microbial communities. In particular, the Alphaproteobacteria and Chloroplast classes of bacteria may play a significant role in Cd accumulation via the bio-mineralization process. Taken together, our results provide basic empirical information to better understand the heavy metal speciation transformation mechanisms of PCs upon Cd-contaminated paddy fields.

1. Introduction Soil crusts are widely distributed on the soil surface of many ecosystems and are composed of inorganic matter (iron [Fe] and manganese [Mn] oxides) and various biological components, such as cyanobacteria, algae, microfungi, lichens, and bryophytes. Via nitrogen fixation and erosion control these inconspicuous crusts contribute importantly to soil fertility and stability (Belnap et al., 2004) in semi-arid region. Field studies of soil crusts have mainly focused on their ecological functions (Belnap and Gillette, 1998), and more recently on the structure and succession of bacterial communities in arid lands or deserts (Chilton et al., 2014; Hilty et al., 2004). In rice paddy fields, the soil surface is widely covered with soil crusts yet despite being so common, rarely are these paddy crusts (PCs) investigated for how their ecological and environmental functioning is affected in paddy fields contaminated by heavy metals. Irrigation water is the dominant source of heavy metal contamination in most paddy fields (Li et al., 2017). Since PCs arise from the joint

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outcome of soil and water/atmosphere interactions, they provide the primary pathway by which heavy metals infiltrate paddy fields. Thus, PCs likely have a key role to play in the fate of heavy metals that arrive from outside sources. Compared to simple communities, such as algae (Chen et al., 2015) and bacteria (Luo et al., 2011a), the multi-species community nature of PCs can presumably better adapt to a range of environmental stresses, including the respective toxicity arising from heavy metals, through to the optimization of microbiota composition and structure (Wu et al., 2014). In PCs, the microorganism is usually enclosed in a matrix of extracellular polymeric substances (EPS), which contains both proteins and polysaccharides (Sheng et al., 2010). This EPS can efficiently capture heavy metals through chelating effects, and then accumulate heavy metals from irrigation water. In paddy fields, PCs can effectively entrap Cu and Cd (Cu- and Cd-hydrate species) from irrigation water (Yang et al., 2016). Nevertheless, very little is known in detail about heavy metal how to bond with the PCs and their distribution site in PCs. Metal distribution within PCs is controlled by four main processes

Corresponding author. College of Resource and Environment, Hunan Agricultural University, Changsha, 410128, PR China. E-mail addresses: [email protected] (H. Song), [email protected] (L. Peng).

https://doi.org/10.1016/j.ecoenv.2019.109620 Received 1 May 2019; Received in revised form 25 August 2019; Accepted 28 August 2019 Available online 04 September 2019 0147-6513/ © 2019 Elsevier Inc. All rights reserved.

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the soil surface using a plastic spade and immediately transferred to glass beakers containing locally used irrigation water, and then all samples were kept cold in an ice box. Fresh PC material was lyophilized in a freeze dryer (FD-1-50, Taikang Biotechnology Co., Ltd., Taikang, China) and their chemical characterization determined by an X-ray photoelectron spectrometer (XPS, K-Alpha 1063, Thermo Fisher Scientific, Waltham, USA). The crystal forms of the materials were measured with a diffractometer (TTRIII, Rigaku, Tokyo, Japan) and PC samples’ surface structure and morphology characterized by Scanning Electron Microscope-Energy Dispersive Spectrometer (SEM-EDS, JEM-1230 HC, JPN). The soil sample in each site was the mixture of 5 random samples collected below the PCs and at the depth of 0–5 cm. The total soil in every site is about 2 Kg. The irrigation water was collected 3 times in one month, i.e. 20, 10 and 0 days prior to the PC harvesting. The irrigation water in each site was collected near every PC and then mixture. The total volume of the collected irrigation water in every site is 1.0 L and then 2.0 mL HNO3 was added into the polyethylene bottle to stabilization heavy metal. The total metal concentration of water and soil was measured by ICP-OES after digestion. Each water sample was transferred into a glass tube, to which 3 mL of HCl and 1 mL of HNO3 were added, and the final solutions placed in a water bath at 100 °C. Soil samples from the four sites were dried and digested 0.50 g of soil with 4.50 mL of HCl and 1.50 mL of HNO3 in glass tubes, using a digester (XJS36-42W, XJS, CHN), for 1.5 h at a temperature of 150 °C. Then, 5 mL of HClO4 was added to each glass tube, and the samples sequentially digested for 2.5 h at the temperature of 220 °C.

(Stewart et al., 2015): weak-EPS binding, cellular surfaces absorption, intracellular uptake or biomineralization. Some studies have focused exclusively on the metal binding properties of EPS (e.g., Guibaud et al., 2006; Shou et al., 2017), with other measuring total metal accumulation and subsequent toxic effects on PCs (e.g., Morin et al., 2008). But clearly our understanding of how metals are distributed in PCs and their effects on the organisms in PCs remains far from complete. Recently, Stewart et al. (2015) investigated how exposure to Pb influenced this metal's distribution and its effect on periphyton in a simulated stream setting. Although no significant effects of Pb on Fe and Mn distributions were detected, greater Cu accumulation did occur when the levels of free Cu2+ in the exposure medium were higher. However, in that study the presence of inorganic Fe and Mn was associated with the non-EDTAexchangeable fraction, which likely sequestered Pb and explains the negligible biological effects found. Obviously, Cd and Pb differ in their effects on PCs because the former is more active than the latter metal. But less is known about Cd's accumulation and its species distributions in the PCs in paddy fields varying in levels of Cd contamination. Disturbance can profoundly affect the coverage, species composition, and physiological functioning of PCs (Belnap and Eldridge, 2001). The impacts of co-contamination by Cu and Cd on the structure and activity of the microbial community in a periphyton were recently investigated by Yang et al. (2015), who found that dominant microorganism species shifted from photoautotrophs to heterotrophs under combined exposure to Cu and Cd. More recently, Li et al. (2016) investigated the differentiation of microbial activity and functional diversity between various biocrust elements in a heterogeneous crustal community. Much research has investigated the effects of Cd contamination on soil microbial community composition (Duan and Min, 2004; Epelde et al., 2016; Zheng and Zheng, 2012), but the vulnerable microorganismal species and the resistant species to Cd in PCs is largely unknown. And the microorganismal species responsible to the Cd accumulation in the PCs should be investigated. Filling this gap is crucial to better understand the fate of heavy metals in paddy fields. This study's objective was to elucidate the metal distribution and biological community structures within PCs collected from four locations differing in Cd contamination. Metal distributions were determined in three operationally defined fractions: EPS, sorbed, and nonEDTA-exchangeable. The EPS fraction consisted of metals bound to water-soluble macromolecules or colloids, including weak EPS-binding fraction. The sorbed fraction consisted of EDTA-exchangeable metals that were complexed with EPS, i.e., metals directly sorbed onto cell surfaces. The functional groups such as –OH, –COOH, –C]O and –NH2 in the organism can trap metal ion with complex effect (Shou et al., 2017). The non-EDTA-exchangeable fraction consisted of metals not removed by EDTA that were either intracellular accumulated or sorbed into inorganic solid phases. Additionally, the concentrations of Mn, Fe and Zn substances in these operationally-defined fractions were measured to assess whether or not Cd accumulation was driven by a mineralization process in PCs. Furthermore, both bacterial diversity and biological community structures were analyzed for the four sampled PCs, to identify those microorganisms attributable to Cd accumulation.

2.2. Metal distributions among the PC fractions After the lyophilization step, the total metal concentration per PC was directly measured by ICP-OES after digestion. The digestion process of PC was the same as that of soil. To measure metal concentrations of different species, sub-samples (0.50 g) were taken from each PC and mixed with 50 mL of ultrapure water and then re-suspended for a further 30 s in a water sonication bath (KQ2200DE, Kunshan Ultrasonic Instruments Co., Ltd., CHN). Each suspension contained an individual PC sample (in three parallel samples), for which metal concentrations were quantified following Stewart et al. (2015). Briefly, the suspensions were centrifuged at 8000 rpm for 10 min, and all of the supernatant containing loosely bound, water-soluble EPS was directly digested. The remaining biomass was re-suspended in EDTA (4 mM) for 20 min to remove any metals directly bound to cell walls or those bound tightly to the EPS associated with cells (Meylan et al., 2003). After centrifugation, its supernatant including the EDTA-exchangeable metals was digested; leftover biomass was re-suspended and centrifuged in a 10 mM 3-(N-morpholino) propanesulfonic acid (MOPS) solution to remove any residual metalEDTA complexes. Next, its metal concentration was measured and included in our calculation of metals relevant to the sorbed fraction. Thus, the metal concentration of the remaining biomass operationally defined the non-EDTA-exchangeable fraction. All fractions were digested, appropriately thinned, with the metal concentrations of the digests determined by inductively coupled plasma optical emission spectrometry (ICP-OES, Optima 8300 Spectrometer, PerkinElmer, Waltham, MA, USA). Metal concentrations were first normalized on a dry-weight basis. All these samples were also analyzed by ICP-OES to determine their metal concentrations after the digestion, and likewise normalized. The total carbon (TC) concentration was quantified by a total organic carbon (TOC) analyzer (Vario TOC cube, Elementar, Langenselbold, Germany) and total nitrogen (TN) determined following the Kjeldahl method (Kirk, 1950) for the PCs.

2. Materials and methods 2.1. Collection of paddy crusts (PCs), irrigation water and soil PCs were taken from paddy fields in Huang-Gu (HG; N27°34′28″, E113°12′58″), Zhao-Ling (ZL; N27°33′25″, E113°09′55″), Da-Xing (DX; N26°49′40″, E113°32′06″), and Xin-Ma (XM; N27°28′57″, E113°08′37″) in Hunan Province, China, in October 2017. These PCs form HG, ZL, DX and XM were named as HG-PC, ZL-PC, DX-PC and XM-PC, respectively. The four sites where the PCs were collected from had the same climatic conditions, soil types, and land use types, but they differed in their Cd concentrations in soil and irrigation water. The 5 random PCs was sampled and mixed at every site. The PCs were carefully removed from 2

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2.3. Bacterial richness and diversity The PC samples from three locations at every contamination level were mixed together and thoroughly homogenized. For each, its total microbial DNA was extracted using a Soil Master DNA Extraction kit (Epicentre Biotechnologies, Madison, WI, USA), according to the manufacturer's instructions. The universal primers 515F (GTGCCAGC MGCCGCGG) and 907R (CCGTCAATTCMTTTRAGTTT) were used to amplify the V4–V5 region of the 16 S ribosomal RNA (rRNA) gene (i.e., 515–907). The oligonucleotide sequence barcode was fused to the forward primer. The PCR reaction mixture (20 μL) contained 4 μL of 5 × FastPfu reaction buffer (TransGen Biotech, Beijing, China); 2 μL of a dNTP mixture (2.5 mM); 0.4 μL of each primer (5 μmol/L); 0.4 μL of FastPfu polymerase; 10 ng of the template DNA, with H2O added to make up the volume. For the PCR thermal cycling, an applied microbiology biotechnology scheme was set as follows: initial denaturation at 95 °C for 5 min, 25 cycles of denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, and an extension at 72 °C for 30 s, followed by a final extension period of 5 min at 72 °C. This PCR amplification was performed on an ABI GeneAmp PCR System 9700 (Applied Biosystems, Foster City, CA, USA) and its ensuing products examined on 2% (w/v) agarose gel and further purified with an Maxiprep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA). Purified amplicons were quantified using QuantiFluor™-ST (Promega, Fitchburg, WI, USA) with their paired-end sequencing carried out on an Illumina MiSeq platform at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China), according to standard protocols. These tags were clustered to operational taxonomic units (OTUs) using a threshold of 97% sequence similarity. Taxonomic ranks were assigned to OTU representative sequences by using the naïve Bayesian Classifier (v.2.2) of the Ribosomal Database Project (RDP). Finally, the diversity was determined, and the different bacterial species were screened based on their OTUs and taxonomic rankings.

Fig. 1. Cd concentration in irrigation water, soil and PC (a). Biological concentration factor (BCF) for PC/irrigation water and PC/soil (b).

The total Cd concentration in the PCs from HG, ZL, DX, and XM was 2.29, 2.53, 18.01, and 94.21 mg/kg, respectively (Fig. 1a). Higher Cd concentrations were present in the PCs, irrigation water, and soil sampled from XM and DX than those from ZL and HG. The BCFs of PC/ irrigation water decreased as follows: XM > DX > HG ≈ ZL, i.e., XM had greater Cd accumulation in its PCs (i.e., XM-PC) than the other three sites (Fig. 1b). The respective accumulation and distribution of Cd, Mn, Fe, and Zn within the different fractions for the PCs were quantified to determine the relationships between Cd and other metallic elements. The total Cd concentration in HG-PC (1.79 mg/kg) was similar to that in ZL-PC (2.53 mg/kg), whereas in DX-PC it was much higher (18.00 mg/kg) (Fig. 2a). The dominating Cd species of HG-PC and ZL-PC were EPSbinding fraction and sorbed faction, only a small amount non-EDTAexchangeable fraction (< 10%). For XM-PC, most of the accumulated Cd occurred in the sorbed fraction (82%). The total Cd concentration of XM-PC (94.21 mg/kg) exceeded that of all other samples. The Cd in non-EDTA-exchangeable and sorbed fraction was the prominent fraction, however, the EPS-binding Cd fraction was very low (< 5%) (the results were shown in the graph abstract). The Cd/C (this C is based on the TC) intracellular ratios were similar in HG-PC and ZL-PC (2.38 and 4.11 μmol/mol, respectively), whereas in DX-PC and XM-PC they were more than 10 times higher (30.16 and 65.12 μmol/mol, respectively) (Table 1). Mn concentrations in the PCs were ranked as XM (4.68 × 103 mg/ kg) > HG (1.46 × 103 mg/kg) > ZL (7.58 × 102 mg/kg) ≈ DX (6.60 × 102 mg/kg) (Fig. 2b). However, the majority of accumulated Mn was present in the sorbed fraction for HG-PC (57.88%) and ZL-PC (83.51%), while for DX-PC (32.72%) and XM-PC (34.04%), it mainly occurred in the non-EDTA-exchangeable fraction (57–67%). The Mn/C ratio was similar in all four PC site samples (~5.00 × 103), with the exception of DX-PC (2.42 × 103), which had a lower ratio than did HGPC, ZL-PC, or XM-PC (Table 1). The Fe concentrations in the four site

2.4. Bioinformatics and statistical analysis Raw pyrosequencing data were de-multiplexed and quality-filtered, by using Trimmomatic tool in the way Lohse et al. (2012) described. Overlapping reads were then merged into single long reads with the FLASH software tool (Mago and Salzberg, 2011). Qualified sequences were then clustered into OTUs at a 97% similarity cutoff using Usearch v7.1 (http://qiime.org/). The phylogenetic affiliation of each 16 S rDNA sequence was analyzed with the RDP Classifier v2.2 (http:// sourceforge.net/projects/rdp-classifier/), using a confidence threshold of 0.7 and the reference database Silva (Release 115, http://www.arbsilva.de). Venn diagrams and heatmap figures were produced using package 'gplots' in the R (v3.1.1) software (http://www.Rproject.org/). A Canonical correspondence analysis (CCA) was performed using Canoco v.5.0 software (Microcomputer Power, Ithaca, NY, USA). 3. Results 3.1. Metals’ accumulation and distribution The Cd, Fe, Mn, and Zn concentrations in soil, irrigation water, and the PCs were measured and summarized in Table S1. Heavy metal concentrations were higher in the PCs than in either the soil or irrigation water samples, and decreased in the order of PCs > Soil > irrigation water for the four sites. The Bioconcentration Factor (BCF) is the concentration of a metal in a PC per concentration of that metal in surrounding water/soil. That is, a dimensionless number representing how much of a metal is in a PC relative to how much of that metal exists in the environment. The BCF of PC to irrigation water were 3.80 × 103–6.50 × 103 for Cd, 2.30 × 103–4.09 × 104 for Fe, 1.50 × 103–1.20 × 104 for Mn, and 1.10 × 103–7.90 × 103for Zn. 3

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Fig. 2. Distribution of metal in PCs fractions (extracellular polymeric substances (EPS), sorbed, and non-EDTA-exchangeable) upon collection. Metal distributions of Cd (a), Mn (b), Fe (c) and Zn (d) were measured in PCs.

indicating the sample is most abundant in organisms. The XPS results from the carbon analysis are shown in Fig. S2, in which the peaks at 284.48, 286.35, 287.97, and 289.28 eV correspond to the binding energies of C in the CC, C–O/C–N, C]O, and O–C]O bonds, respectively (Lee et al., 2009; Liu et al., 2014). Among these four types, the peak area for C–C was much larger than others, while that of O–C]O was the smallest. These results implied that most of the carbon was associated with organisms rather than inorganic compounds such as carbonate, an interpretation further supported by the low C/N values of 17–35 in the PCs.

Table 1 Total carbon (TC), carbon-to-nitrogen, and metal-to-carbon ratios of PCs in four locations.

TC (mol/kg) C:N (mol/mol) Cd:C (μmol/mol) Fe:C (μmol/mol) Mn:C (μmol/mol) Zn:C (μmol/mol)

HG

ZL

DX

XM

4.95 17.6 2.38 9.37 × 104 5.38 × 103 5.21 × 102

3.41 25.1 4.12 1.35 × 105 4.05 × 103 8.60 × 102

4.96 20.9 30.16 8.33 × 104 2.42 × 103 2.43 × 103

12.64 35.13 65.12 1.74 × 104 6.12 × 103 1.74 × 103

samples differed considerably from those of Cd and Zn (Fig. 2c). The Fe/C ratios were similar in HG-PC, ZL-PC, and DX-PC (~9.00 × 104), all of which had much higher ratios than XM-PC (1.74 × 104). The accumulation of Zn followed the same pattern found for Cd (Fig. 2d). It was apparent that the ability of PCs to accumulate Cd increased with more Cd contamination at a site. Nevertheless, the metal distributions of Zn and Cd were not identical. While most of the accumulated Zn was present in the non-EDTA-exchangeable fraction, that of Cd occurred primarily in the sorbed and non-EDTA-exchangeable fractions. Notably, the Zn/C ratio did not match the Zn concentration pattern, being higher in DX-PC (2.44 × 103 μmol/mol) than HG-PC (5.21 × 102 μmol/mol), ZL-PC (8.60 × 102 μmol/mol), or XM-PC (1.74 × 103 μmol/mol).

3.3. Bacterial richness and diversity The number of OTUs of a sample primarily represents its degree of bacterial diversity. The total number of OTUs per sample for HG-PC, ZLPC, DX-PC, and XM-PC were respectively 4566, 4617, 2850, and 1050. Similar patterns for bacterial diversity were obtained for the Chao and Shannon indices. A Venn diagram revealed that the number of OTUs shared by all PCs was 360, or 4.60% of all OTUs identified (Fig. S11). These results showed that 43.28% of OTUs were shared between HG-PC and ZL-PC, and likewise 23.54% between HG-PC and DX-PC, 21.63% between DX-PC and ZL-PC, 18.58% between DX-PC and XM-PC, 12.82% between HG-PC and XM-PC, and 10.60% between ZL-PC and XM-PC. The OTUs found unique to HG-PC, ZL-PC, DX-PC, and XM-PC amounted to 1390, 1567, 1075, and 221, respectively. Valid sequences obtained from all the PCs were assigned to 7824 OTUs, which were assigned to 61 phyla. The main phyla were Proteobacteria, Bacteroidetes, and Gemmatimonadetes, and Acidobacteria. Members of the Actinobacteria, Chlamydiae, Chlorobi, and Fusobacteria phyla were also present in most samples, but at very low abundances. The main species in class level of HG-PC are Betaproteobacteria, Deltaproteobacteria and Anaerolineae. The ZL-PC is of Deltaproteobacteria, Betaproteobacteria and Anaerolineae. The

3.2. Organic matter The major elements in the PCs were carbon, nitrogen and oxygen, which together accounted for 80–95% of a paddy crust's matter. The vast majority of these elements (> 80%) were attributable to the biological components of PCs. The TC in the PCs from HG, ZL, DX, and XM was 4.95, 3.41, 4.96, and 12.64 mol/kg, respectively. The highest organic matter content and C/N ratio values were found in XM-PC, 4

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Fig. 3. Log-scaled percentage heat map of the class-level among the four PCs.

DX-PC mainly includes Betaproteobacteria, Saprospirae and Cytophagia. Lastly, the XM-PC owns predominant species: Betaproteobacteria, Chloroplast and Alphaproteobacteria. A class-level heatmap split the four site samples of PCs into two groups at the first level (Fig. 3). One was composed of XM-PC, while the other was jointly composed of DX-PC, HG-PC, and ZL-PC. The bacterial community of HG-PC showed high similarity to that of ZL-PC, and then both grouped into a branch distinct from the DX-PC and XM-PC communities. The physio-chemical features of PCs, including pH, concentrations of Cd, Mn, Fe, Zn, and TC and TN, were all taken into consideration to evaluate their relative contributions to the bacterial community at the class level based on a canonical correspondence analysis (CCA) (Fig. 4). Among them, the heavy metals Cd, Mn, and Zn, as well as both TC and TN were positively related with XM-PC, suggesting they were strongly associated with its biological community. The Pearson correlations between environmental indicators and bacterial phyla showed that heavy metals were positively associated with the Deinococci, Gemmatimonadetes, VadinHA49, Alphaproteobacteria, Chloroplast, and Betaproteobacteria classes. Both pH and Fe were positively related to some classes, including Oscillatoriophycideae, BPC102, Venuco-5, Pedosphaerae, Bacteroidia, Gammaproteobacteria, and Clostridia, among others. For the biological community structure, the Cd, Fe, and Mn were the dominant contributors to it. Fig. 4. Canonical correspondence analysis (CCA) of the microbial community in class level (relative abundance > 1.0%), environmental parameters and samples.

4. Discussion 4.1. Cd accumulation and fraction distribution characteristics

independently from water and sediments into biofilms in stream ecosystems (Farag et al., 2007). In PCs, however, their total metal accumulation is related not only to the metals present in irrigation water but

The high Cd accumulation effect of PCs has been demonstrated by our results. An earlier study reported that Cd, Cu, and Zn may move 5

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The non-EDTA-exchangeable fraction increased as the Cd concentration increased. Hence, the Cd of the non-EDTA-exchangeable fraction in XM-PC was the greatest found among our four sites. In this fraction, its Cd and Mn concentrations were positively correlated (Fig. 6a), while its Cd/Mn ratio i was ~0.011 for XM-PC and DX-PC each. A higher Cd adsorption capacity for manganese oxides could be attributed to the higher Cd concentration in irrigation water. The nonEDTA-exchangeable Cd fraction is the result of entrapment by Mn oxidation has been identified by our other experiment (Peng et al., 2019). Based on our results, we attribute the Mn oxidization process to Mnoxidizing bacteria (MOB) because Mn and Cd in pure water could not be oxidized under the same experimental conditions. Some MOB were successfully isolated from paddy soils, including Bacillus safensis, Brevibacillus reuszeri, Bacillus altitudinis, Arthrobacter stackebrandtii, Frondihabitans australicus, Bacillus subtilis, and Sphingomonas mucosissima (Mayanna et al., 2015; Peng et al., 2019). These MOB normally belong to Gemmatimonadetes, Alphproteobacteria, Betaproteobacteria, Actinobacteria, and Bacteroidia (Cho et al., 2018). However, in our study, the Cd/Mn ratio was only 0.0006 in the paddy soil samples, so considerably lower than that of 0.011–0.015 in our samples of PCs. This indicated that some MOB in PCs possessed a high accumulation capacity for Cd. The non-EDTA-exchangeable Mn was positively related with the bacteria of Alphaproteobacteria, Chloroplast, and Gemmatimonadetes classes. MOB are rarely found in the Chloroplast class; however, the Mn biomineral is reportedly common on the surface of organisms in that class, such as Spirogyra (Peng et al., 2019). Consequently, we infer that a symbiotic relationship may well exist between the Chloroplast member organisms and MOB. Our results demonstrated biomineralization as the dominating mechanism on accumulation of Cd in PCs in a high-Cd environment. The accumulation of Cd was positively related to the Mn concentration in the non-EDTA-exchangeable fraction, but not the Fe concentration. Nelson et al. (2002) had reported that Fe–Mn dioxides were responsible for binding the majority of Pb in soils; in some cases, Fe and Mn oxides were responsible for more than 90% of the sorbed Pb. It is known, however, that the binding capacity of Mn oxides is more than an order of magnitude greater than that of Fe oxides (Dong et al., 2000; Nelson et al., 2002). From our metal distribution results it was apparent that the Cd (Zn) and Fe concentrations were negatively correlated with each other (Fig. 6b), as were the Fe and Mn concentrations in the non-EDTA-exchangeable fraction. Both results suggest to us that Fe and Mn oxides existed in separate mineral forms, rather than as a Fe–Mn oxide complex. Specifically, in the PCs, we predict the dominant (inorganic) speciation of Cd and Zn to be Cd2+(aq) and Zn2+(aq), while the point of zero charge is at ~ pH 2 for poorly crystalline birnessite and at ~ pH 8 for ferrihydrite (Moon and Peacock, 2013). In this way Cd and Zn would be captured by Mn oxides, thus underpinning the positive relationship found between the Cd (Zn) and Mn concentrations. The total accumulated Fe was negatively related to the Cd concentration. This could be explained by a toxic effect of Cd on microorganisms in the PCs that leads to different species compositions within the PCs, namely as the Cd concentration increases, the relative abundance of Fe-oxidizing bacteria declines due to Cd-induced toxicity. Hence, total Fe concentration in the non-EDTA-exchangeable fraction of DX-PC was lower than that of HG-PC and ZL-PC, with the concentration of DX-PC being twice that of XM-PC.

also to those in soil. An analysis of porewater geochemistry found a strong correlation between metal concentrations in porewater and biological soil crust (Alexander et al., 2010). Nevertheless, the BCFs and Cd concentration curves in our study indicated irrigation water and soil to be the main source of Cd in the PCs. The proportion corresponding to the soluble EPS-binding fraction decreased as the level of Cd site contamination increased. However, sorbed fraction proportion first increased and then declined, while the proportion of non-EDTA-exchangeable fraction increased, with more Cd. Taken together, these results suggest the Cd detoxification process in PCs should consist of different levels associated with the Cd concentration. The first barrier presumed is the weak interaction effect of the outer EPS; if the Cd content is sufficiently large enough to penetrate that barrier, the Cd reaches a second barrier: the strong sorbed effect of the internal EPS or cell surface. The third and final barrier would be biomineralization and biological uptake, which become relevant once both prior barriers reach saturation levels in a high-Cd environment. In paddy fields polluted with low-level Cd, the bulk of Cd was captured by the soluble EPS of a site's PCs. Thus, in HG-PC and ZL-PC, the proportion of the Cd associated with the EPS fraction was much higher than that found in DX-PC and XM-PC. EPS are thought to exercise a protective function, by slowing the spread of metals to cell surfaces, and increased EPS production in phytoplankton due to metal exposure has been reported (Pistocchi et al., 2000). The EPS mitigate the metal toxicity to microbial cells through an associative weak interaction has been reported by Shou et al. (2017). Therefore, the weak EPS-binding effect was considered as the dominating detoxification method for PC in the environment with low concentration Cd. The dominating Cd was distributed among sorbed fractions under medium-Cd environment in PCs, the result in line with that reported by Ledin et al. (1996). Such accumulation by microorganisms is present widely in nature. More than 60% of added metals were captured by the microorganism in soil. We found a positive association between the Cd concentration in the sorbed fraction and TC (Fig. 5). A higher TC concentration corresponds to more organisms in the PCs, with the sorbed Cd fraction representing a complex outcome between microorganism cell and Cd, through a deprotonated carboxyl integrate with the occupied d, s orbitals of Cd2+. Consequently, biological sorption (complexion) takes on a critical function in Cd accumulation in sites with medium levels of Cd, such as DX-PC. The sorbed Cd concentration was positively related with Alphaproteobacteria, Gemmatimonadetes, Chloroplast, and Sphingobacteria microorganisms; however, the first two of these bacterial classes were also positively associated with TN, TC, and sorbed Cd. Therefore, we propose that Cd accumulation may be attributable to these particular species in the PCs.

4.2. Bacterial diversity and community structure The proposed Cd tolerance level for microbial activity in soil is 44 mg Cd/kg on a dry weight basis (Zheng and Zheng, 2012) yet its concentration in XM-PC, at 94 mg/kg, greatly exceeded this. Therefore, the bacterial richness and diversity in XM-PC was likely to be severely affected by Cd contamination. According to our sequencing results, the Proteobacteria (30–37%),

Fig. 5. Relation between Cd in sorbed fractions and TC in PCs. 6

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Fig. 6. Relation between different metals in the non-EDTA-exchangeable fraction of PCs. Cd(Zn) vs Mn (a); and Cd(Zn) vs Fe (b).

contaminants, which in theory could extend to the immobilization of metals. Our present findings are important since future studies could isolate and investigate the potential of these bacteria for EPS production and for bioremediation of Cd-polluted soils. We noted that the Deinococci, VadinHA49, and Gemmatimonadetes all occurred in very low abundances in all PCs, despite having the ability to persist under conditions of high Cd stress. Organisms in the Alphaproteobacteria and Chloroplast classes were highly abundant and also had excellent tolerance of Cd. In less diverse communities, the Alphaproteobacteria and Chloroplast might thus take on key roles in the accumulation of Cd in PCs, as suggested by their high abundance. The Cd contamination apparently drove the abundance of specific genera, namely Alternaria, Davidiella, Hannaella, and Cladosporium. In particular, Alternaria abundance rose with more Cd in the PCs and this compositional shift may help protect co-occurring organisms against Cd toxicity, given that some species are reportedly endophytic microorganisms with highly bioactive metabolites. The Spirogyra and bluegreen microalage in the Chloroplast class can uptake Cd might under the protected effect of Alternaria (Khan et al., 2017).

Bacteroidetes (16–27%), Cyanobacteria (4–14%), Verrucomicrobia (3–8%), and Planctomycetes (3–5%) were the dominant phyla in all four samples of PCs. These results agree with previous study (e.g., Miranda et al., 2018). Proteobacteria and Bacteroidetes can produce exopolysaccharides, so they could also participate in soil stabilization and PC formation (Liu et al., 2017). In our study, the relative abundance of Proteobacteria was only slightly influenced by the different levels of Cd contamination among sites, for which the main OTUs shared by all PCs sampled belonged to the Proteobacteria. Other research has suggested the Proteobacteria possess a degree of resistance to pollution from various heavy metals, including Cd (Zhu et al., 2013), and this could explain the prime position of this phylum in all our PCs. Several important MOB are Proteobacteria, including Roseobacter sp. AzwK-3b (Hansel and Francis, 2006), Albidiferax isolate TB-2 (Akob et al., 2014), Leptothrix sp. (Boogerd and de Vrind, 1987), Pseudomonas putida GB-1 (Francis and Tebo, 2001), and Aurantimonas manganoxydans (Anderson et al., 2009). Moreover, the abundance of Proteobacteria shows a correspondence with the Mn concentration in some environments. However, the Proteobacteria's abundance in DX-PC was lower than in other samples, while the Mn concentrations in the soil and PC samples from ZL were also lower than those at the other three sites. This indicates that the Mn concentration could not be the sole factor influencing the abundance of this group of bacteria. Bacteroidetes are commonly found as members of cropland microbial communities (Loria et al., 2008) while the Cyanobacteria are deemed to be an important biological component of biological soil crust (Belnap and Eldridge, 2001). Previous studies have shown that both Bacteroidetes and Cyanobacteria are capable of resisting and accumulating heavy metals (Luo et al., 2011b; Philippis et al., 2007; Silver and Le, 1996). The relative abundances of these two phyla in DX-PC and XM-PC were significantly higher than their corresponding values in HGPC and ZL-PC. Hence, it is plausible high levels of Cd contamination had eliminated sensitive bacteria and thereby promoted the abundance of Cd-resistant bacteria. Providing further support for this shift were Cd concentrations at their highest in DX-PC and XM-PC. With more Cd, the abundances of Deinococci, Gemmatimonadetes, VadinHA49, Alphaproteobacteria, and Chloroplast microorganisms also rose, suggesting that these classes possess adaptive traits to persist in harsh environments such as Cd-rich waters and soils. The high tolerance of Cd by this group of bacteria may depend on their particular detoxification mechanism; that is, production of bacterial biofilms that consist of EPS, or biomineralization. In this context, it is worth noting that Gemmatimonadetes and Alphaproteobacteria can induce Mn-biomineralization to immobilize Cd, while other bacteria—namely Deinococci and VadinHA49—could produce a large amount of EPS composed of carbohydrates, protein, DNA, and sorbed abiotic constituents, with both types of response characteristics protecting individual cells from chemical damage (Miranda et al., 2018). In particular, Sheng et al. (2010) have posited a mechanism of EPS for binding

5. Conclusions The distribution of four metals and the biological diversity of PCs in paddy fields from four sites in south China under different levels of Cd contamination were investigated. The PCs accumulated heavy metals from irrigation water and soil, with BCFs (PC/water) in the range of 3800–6700. The weak EPS-binding Cd fraction decreased, whereas the non-EDTA-exchangeable Cd fraction increased, with greater Cd concentrations in paddy fields. The sorbed Cd fraction was initially enhanced by low-to mid-level Cd concentrations but then it gradually declined. The Cd accumulation in the non-EDTA-exchangeable fraction was mainly associated with biogenic birnessite. The Proteobacteria, Bacteroidetes, and Cyanobacteria were dominant phyla in all four sites’ PCs. However, as the Cd-contaminated level increased, the abundances of Deinococci, Gemmatimonadetes, VadinHA49, Alphaproteobacteria, and Chloroplast all increased as well. Our work strongly suggests that special bacteria are associated with the Cd biomineralization and biosorption effect. And these organisms in PC could include potential functional species for the Cd bio-stabilization in paddy fields.

Acknowledgments For financial support, we are grateful to The National Key Research and Development Program of China (No. SQ2017YFNC060064), Natural Science Foundation of Hunan Province (No.2017JJ2112), Key Projects of the Hunan Education Department (No.18A095), Changsha Plan Project of Science and Technology (kq1801025). 7

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Appendix A. Supplementary data

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