APPENDIX A
SUPPLEMENTARY INFORMATION
Using rice as a remediating plant to deplete bioavailable arsenic from paddy soils
Sixue He1, Xin Wang1*, Xin Wu2,3, Yulong Yin2,3, Lena Q Ma4
1 Key Laboratory of Environmental Heavy-Metal Contamination and Ecological
Remediation, College of Resources and Environmental Science, Hunan Normal
University, Changsha 410081, China
2 Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of
Subtropical Agriculture, Chinese Academy of Sciences, Changsha, Hunan 410125,
China
3 National Engineering Laboratory for Pollution Control and Waste Utilization in
Livestock and Poultry Production, Changsha, Hunan 410125, China
4 Institute of Soil and Water Resources and Environmental Science, College of
Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058,
China
*Corresponding author: Xin Wang, 86-137-8619-4572, [email protected]
Contents Page
S1
Materials and Methods S4-S6
Table S1. Pearson correlation coefficients of porewater chemical
parameters over the time of rice growing.
S7
Table S2. Averaged biomass production of each rice plant at harvest. S8
Table S3. Effectiveness of phytoremediation of As-contaminated paddy
soils with rice plant.
S9-S10
Figure S1. The time bar shows four successive periods of the entire
experiment.
S11
Figure S2. Pearson correlation coefficients of porewater Fe and soil pH
throughout flooding for both Control and As-soil.
S12
Figure S3. Abundance and diversity of microbial arrA gene in different
growing stages based on phylum. Complete linkage clustering of different
growing stages was calculated by the composition and relative abundance
of arrA genes. Tl: Tillering stage, HF: Heading & flowering stage, Fl:
Grain filling stage.
S13
Figure S4. Neighbor-joining phylogenetic tree of arrA sequences in
heading & flowering stage showing the phylogenic relationship between
respiratory As(V) reducing genes identified from flooded paddy soil in this
study and the known As(V) reducing genes with corresponding accession
numbers from GenBank. The level of support for the phylogenies was
determined from 1000 bootstrap replicates. Bootstrap values are shown for
S14
S2
branches with >30% bootstrap support.
Figure S5. Abundance and diversity of microbial arrA gene in different
growing stages based on OTU. Complete linkage clustering of different
growing stages was calculated by the composition and relative abundance
of arrA genes. The top 20 most abundant OTUs were shown in the heat
map. Species in the parentheses have been identified based on sequence
analysis of each corresponding OTU. Tl: tillering stage, HF: heading &
flowering stage, Fl: grain filling stage.
S15
Figure S6. Changes in dissolved Fe(II) and Fe(III) in floodwater (a) and
porewater (b) throughout the entire flooding period. The maximum
standard deviations of Fe(II) and Fe(III) account for 18% and 14% of each
species measured, which were not shown for concise.
S16
Figure S7. Fe concentrations in different parts of the remediating rice
plants after 93 days of growth under flooded conditions in As-soil+rice.
Error bars represent the standard deviations of three replicates.
S17
References S18
S3
2 Materials and Methods
2.1 Preparation of soil and rhizotron
The tested soil was sampled from the top layer (0-20 cm) of a slightly As-
contaminated paddy field (39.7 mg kg-1) (Lat/Long: 29°39′16″N, 111°3′12″E) at
Shimen Realgar Mine area in Hunan province, China. Shimen Realgar Mine was
Asian largest realgar deposit and has been closed since 1970s due to its heavy As
contamination to surrounding environment. A clean soil with total As below the risk
screening value for soil contamination of agricultural land in China (30 mg kg-1 at pH
≤ 6.5, GB15618-2018) was collected as Control from Wangjiayan village, which is
located at 10.8 km downstream from Shimen Realgar Mine. The soil samples were
naturally air-dried and passed through a sieve of 2 mm. Soil properties, including pH,
total As, total Fe, organic matter (OM), available N, available P and available K, were
determined following standard methods of soil analysis and shown in Table 1.
Besides, changes in poorly-crystalline Fe (hydr)oxides in soils were evaluated by
acid-ammonium-oxalate (AAO) extraction (Sparks et al., 1996).
2.3 Biochemical analysis
2.3.1 Porewater and soil sampling and analysis
Total dissolved Fe and Fe(II) in porewater samples were measured with a UV-
Visible spectrophotometer (EVOLUTION 260 BIO, Thermo Fisher Scientific, USA).
Dissolved organic carbon (DOC) was determined by a total organic carbon analyzer
(vario TOC select, Elementar, Germany).
S4
2.3.2 High-throughput sequencing of arrA genes
After 42 (tillering stage), 66 (heading & flowering stage) and 89 (filling stage)
days of rice growth, total microbial DNA were extracted from the rhizosphere soils in
the As-soil+rice rhizotrons using the EZNA Soil DNA Kit (Omega Bio-tek, Norcross,
GA, USA). The extracted DNA samples were checked by 1% agarose gel
electrophoresis and spectrophotometry (260 nm/280 nm, optical density ratio) for
mass detection. Conventional PCR amplification of arrA genes were then conducted
with degenerate primers arrA-CVF1 (5′-CACAGCGCCATCTGCGCCGA-3′) and
arrA-CVR1 (5′-CCGACGAACTCCYTGYTCCA-3′), respectively (Mirza et al.,
2016). The concentration of each primer in 50 μl PCR system was 0.2 μM. The PCR
thermal cycling parameters were optimized as: 95 °C for 3 min, 35 cycles of 45 s of
denaturation at 94 °C, annealing at 60 °C for 45 s, and extension at 72 °C for 1 min,
and a final extension for 7 min at 72 °C.
The amplified arrA genes were then subject to high-throughput sequencing on
an Illumina Miseq PE300 platform (Illumina, San Diego, USA). The download data
was filtered by QIIME (V1.8.0) with any ambiguous and low-quality reads being
removed. The obtained sequences for each sample were then clustered into OTUs
(Operational Taxonomic Units) using the method described by Mothur based on a
cutoff value of 97% (Schloss et al., 2009). On this basis, the Chao1 estimator for
community richness, the Shannon index for community diversity, the PD whole tree
for phylogenetic diversity and Good's coverage for sequencing depth were calculated
in QIIME for each sample. By blasting the SILVA database, species information of the
S5
representative sequence from each OTU was obtained. The relative abundance of the
OTUs in top 20 were used for generating heatmaps in software R version 3.1.2. The
nucleotide sequences of arrA gene obtained in this study have been deposited in the
NCBI GenBank database under accession numbers MN090027-MN090136,
respectively.
2.5 Rice harvest and post treatment
After rice harvest, soil flooding continued for an additional 27 days to examine
changes in soil bioavailable pool of As in each treatment. During the post-harvest
flooding, porewater chemistry was determined at 5-d intervals as stated above and in
situ imaging of DGT-labile As in soils was performed at the end of this additional
flooding period.
To further evaluate the remediation effect of one crop of rice, at the end of the
whole experiment, the soil in each rhizotron was mixed thoroughly to simulate field
ploughing before subsequent cultivation. A 0.5-kg aliquot of each well-mixed soil was
then put in one pot (90 mm diameter, 125 mm height) with 5 rice seedlings being
transplanted after 7 days of germination. The pots were placed in an incubator
(day/night: 25/16 °C, 3000 lx for 14 h per day). After 30 days of growth, the rice
seedlings were harvested and rinsed with deionized water. As concentration and
speciation in seedlings were then analyzed as described in paper 2.5.
S6
Table S1. Pearson correlation coefficients of porewater chemical parameters over the time of rice growing.
As As(III) As(V) DMA MMA Fe pH Eh Fe(II) Fe(III) DOC
As 1 0.279** 0.156 0.395** 0.238** 0.633** -0.119 0.185* 0.452** 0.578** 0.839*
*
As(III) 1 0.299** -0.318** 0.041 0.072 0.243** 0.404** -0.177* 0.122 -0.07
As(V) 1 0.148 0.379** 0.109 0.057 0.344** -0.035 0.232** 0.227
DMA 1 0.151 0.237** -.194* -0.053 0.321** 0.162 0.486*
*
MMA 1 0.125 -0.13 0.189* 0.105 0.127 0.176
Fe 1 -0.500** 0.251** 0.730** 0.894** 0.774*
*
pH 1 -0.079 -0.557** -
0.329**
-0.129
Eh 1 0.195* 0.263** 0.063
Fe(II) 1 0.573** 0.434*
*
S7
Chemical parameters
Chemical parameters
Fe(III) 1 0.888*
*
DOC 1
Significance level: *p < 0.05, **p < 0.01.
S8
Table S2. Averaged biomass production of each rice plant at harvest.
Root Leaf Stem
(g dwt* plant-1)
Husk Brown rice
Rice 1.7±0.1 2.7±0.3 5.5±0.6 2.1±0.5 4.1±0.8
* Dry weight.
S9
Table S3. Effectiveness of phytoremediation of As-contaminated paddy soils with rice
plant: (a) estimation of As export by harvesting rice plant with root from paddy soils
subject to annual As input mainly through irrigation in South and South-east Asia; (b)
estimation of required crops by harvesting rice plant with root to attenuate
bioavailable As in As-soil to the level of Control. This case is likely to be
representative of most areas subject to past anthropogenic contamination.
(a)
Estimated item Value
Total As extracted by one rice plant
(mg As plant-1)1.76
Plant density A
(number of plants ha-1)756000
Growing seasons
(crops a-1)1-3
Total amount of As removal by harvesting
rice plant with root (mg As m-2 a-1)133-399
Averaged annual As input B
(mg As m-2 a-1)400
S10
(b)
Soil bioavailable
As C
As-soil As-soil-root
(μg l-1)
Control D Net As removal per crop
(mg plant-1)
Required
crops
DGT-As 193.1 E 94.6 79.0 1.76 1-2
A. This density of rice planting is based on rice yield from Chinese National Bureau of statistics
for 2018 (http://www.stats.gov.cn/). According to the data, the rice output of China in 2018
was 7026.59 kg ha-1, and the yield of one rice plant was about 8-15 g.
B. This represents a typical amount of annual As input through irrigation in Bangladesh according
to Roberts et al. (2009).
C. The data on day 27 after rice harvest with root removed (As-soil-root) were used here. Each
rhizotron had a total soil mass of 5.0 kg (dwt), which supported the growth of one rice plant
in the present work.
D. Control was the remediation goal of this work. Total As concentration in the white rice
produced from Control was 0.15 mg kg-1. This is below National Food Safety Standard of
China (0.20 mg kg-1, GB2762-2017), which is probably the strictest in the world for
protecting a nation with high rice consumption.
E. Volume of porewater in each rhizotron of this work was 2.25 L, which was calculated as the
difference between the volume of total water added and floodwater of 5 cm depth after 15 days
of incubation. This was the maximum estimation of porewater volume considering the
inevitable water loss under an open atmosphere.
S11
Figure S1. The time bar shows four successive periods of the entire experiment.
S12
Figure S2. Pearson correlation coefficients of porewater Fe and soil pH throughout
flooding for both Control and As-soil.
S13
Figure S3. Abundance and diversity of microbial arrA gene in different growing
stages based on phylum. Complete linkage clustering of different growing stages was
calculated by the composition and relative abundance of arrA genes. Tl: Tillering
stage, HF: Heading & flowering stage, Fl: Grain filling stage.
S14
Figure S4. Neighbor-joining phylogenetic tree of arrA sequences in heading & flowering stage showing the phylogenic relationship between respiratory As(V) reducing genes identified from flooded paddy soil in this study and the known As(V) reducing genes with corresponding accession numbers from GenBank. The level of support for the phylogenies was determined from 1000 bootstrap replicates. Bootstrap values are shown for branches with >30% bootstrap support.
S15
Figure S5. Abundance and diversity of microbial arrA gene in different growing
stages based on OTU. Complete linkage clustering of different growing stages was
calculated by the composition and relative abundance of arrA genes. The top 20 most
abundant OTUs were shown in the heat map. Species in the parentheses have been
identified based on sequence analysis of each corresponding OTU. Tl: tillering stage,
HF: heading & flowering stage, Fl: grain filling stage.
S16
Figure S6. Changes in dissolved Fe(II) and Fe(III) in floodwater (a) and porewater (b)
throughout the entire flooding period. The maximum standard deviations of Fe(II) and
Fe(III) account for 18% and 14% of each species measured, which were not shown
for concise.
S17
Figure S7. Fe concentrations in different parts of the remediating rice plants after 93
days of growth under flooded conditions in As-soil+rice. Error bars represent the
standard deviations of three replicates.
S18
ReferencesMirza, B.S., Sorensen, D.L., Dupont, R.R., McLeana, J.E., 2016. New arsenate
reductase Gene (arrA) PCR primers for diversity assessment and
quantification in environmental samples. Appl. Environ. Microb. 83 (4),
e02725–16.
Roberts, L.C., Hug, S.J., Dittmar, J., Voegelin, A., Kretzschmar, R., Wehrli, B.,
Cirpka, O.A., Saha, G.C., Ashraf Ali, M., Badruzzaman, A.B.M., 2009.
Arsenic release from paddy soils during monsoon flooding. Nat. Geosci. 3
(1), 53–59.
Schloss, P.D., Westcott, S.L., Ryabin, T., Hall, J.R., Hartmann, M., Hollister, E.B.,
Lesniewski, R.A., Oakley, B.B., Parks, D.H., Robinson, C.J., Sahl, J.W.,
Stres, B., Thallinger, G.G., Van Horn, D.J., Weber, C.F., 2009. Introducing
mothur: opensource, platform-independent, community-supported software
for describing and comparing microbial communities. Appl. Environ.
Microbiol. 75, 7537-7541.
Sparks, D.L., Page, A.L., Helmke, P.A., Loeppert, R.H., Soltanpour, P.N., Tabatabai,
M.A., Johnston, C.T., Sumner, M.E., Bartels, J.M., Bigham, J.M., 1996.
Methods of Soil Analysis. Part 3-Chemical Methods. Soil Sci. Soc. Amer.,
Madison, WI.
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