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Sep 27, 2016 - Structure, Variation, and Co-occurrence of Soil Microbial. Communities in Abandoned Sites of a Rare Earth Elements Mine. Yuanqing Chao,...
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Structure, Variation, and Co-occurrence of Soil Microbial Communities in Abandoned Sites of a Rare Earth Elements Mine Yuanqing Chao, Wenshen Liu, Yanmei Chen, Wenhui Chen, Lihua Zhao, Qiaobei Ding, Shizhong Wang, Ye-Tao TANG, Tong Zhang, and Rong-Liang Qiu Environ. Sci. Technol., Just Accepted Manuscript • Publication Date (Web): 27 Sep 2016 Downloaded from http://pubs.acs.org on September 27, 2016

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Variation,

and

Co-occurrence

of

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Structure,

Soil

Microbial

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Communities in Abandoned Sites of a Rare Earth Elements Mine

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Yuanqing Chao,1,2 Wenshen Liu,1 Yanmei Chen,1 Wenhui Chen,1 Lihua Zhao,1

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Qiaobei Ding,1 Shizhong Wang,1,2 Ye-Tao Tang,1,2,* Tong Zhang,3 and Rong-Liang

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Qiu1,2,*

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1

9

Guangzhou, 510275, China.

School of Environmental Science and Engineering, Sun Yat-sen University,

10

2

11

Remediation Technology, Guangzhou, 510275, China.

12

3

13

University of Hong Kong, Hong Kong SAR, China.

Guangdong Provincial Key Laboratory of Environmental Pollution Control and

Environmental Biotechnology Laboratory, Department of Civil Engineering, The

14 15

*

Corresponding authors

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Address: School of Environmental Science and Engineering, Sun Yat-sen

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University, Guangzhou, 510275, China.

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Telephone: +86 020-84111215 (Y.T.) and +86 020-84113454 (R.Q.).

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Fax: +86 020-84110508 (Y.T.) and +86 020-84110267 (R.Q.).

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E-mail: [email protected] (Y.T.) and [email protected] (R.Q.).

1

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Abstract: Mining activity for rare earth elements (REEs) has caused serious

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environmental pollution, particularly for soil ecosystems. However, the effects of

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REEs on soil microbiota are still poorly understood. In this study, soils were collected

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from abandoned sites of a REEs mine, and the structure, diversity, and co-occurrence

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patterns of soil microbiota were evaluated by Illumina high-throughput sequencing

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targeting 16S rRNA genes. Although microbiota developed significantly along with

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the natural restoration, the microbial structure on the site abandoned for 10 years still

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significantly differed from that on the unmined site. Potential plant growth promoting

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bacteria (PGPB) were identified by comparing 16S sequences against a

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self-constructed

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siderophore-producing and phosphorus-solubilizing bacteria were more abundant in

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the studied soils than in reference soils. Canonical correspondence analysis indicated

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that species richness of plant community was the prime factor affecting microbial

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structure, followed by limiting nutrients (total carbon and total nitrogen) and REEs

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content. Further co-occurring network analysis revealed nonrandom assembly patterns

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of microbiota in the studied soils. These results increase our understanding of

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microbial variation and assembly pattern during natural restoration in REE

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contaminated soils.

PGPB

database

via

BLAST,

and

it

was

found

that

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Introduction

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It is estimated that China holds about 50% of the world's rare earth elements (REEs)

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resource and provides over 90% of the worldwide REEs supply.1 As a result of

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massive and intensive mining activities, increased REEs contamination of soil, water,

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and sediment has occurred in mining areas in China.1-3 Additionally, large-scale

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application of REEs-containing fertilizers in agricultural activities4,5 and global usage

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of technological devices such as rechargeable batteries, cell phones, and fluorescent

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monitors6 has resulted in a substantial increase of anthropogenic REEs discharges to

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various ecosystems, including farmlands,7 rivers,8 the marine environments,6 and

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wastewater and solid waste treatment systems.9,10 Recently, anthropogenic REEs

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pollution has attracted much attention because of the environmental persistence,

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bioaccumulation, and toxicity of these elements.7

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Microbes in soil are considered to be sensitive to environmental changes.11 Numerous

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studies have demonstrated that heavy metals can cause adverse effects (e.g., decline

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of microbial biomass and diversity, and inhibition of microbial activity) on soil

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microbiota and their ecological functions.12-14 With short-term exposure to heavy

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metals, tolerant species may be enriched while maintaining metabolic activity for the

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selective effect of heavy metals.15 With long-term exposure, the processes including

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heavy metal solubilization, transportation, and deposition may alter the structure of

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soil microbiota and eventually affect their overall ecological functions.16 3

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Compared with studies on the more common heavy metals (e.g., copper, cadmium,

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arsenic, lead, and zinc), only a few studies have investigated the effects of REEs on

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microbiota. One study showed that REEs could significantly inhibit the activity of

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ammonia and nitrite oxidizers, and thereby possibly decrease the efficiency of

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nitrification in biological wastewater treatment.17 Another study on rumen microbial

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fermentation found that REEs did not affect microbial denitrification and fermentation

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efficiency.18 Additionally, several studies have shown that REEs are essential for

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methanotrophic bacteria in extreme acidic environments and can significantly

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enhance the catalytic efficiency of methanol dehydrogenase.19,20 These previous

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studies have provided clues to the relationships between specific microbes and REEs

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in various environments. Nevertheless, to our knowledge there has been little research

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on the effects of REEs on the microbiome of soils, which suffer more serious REEs

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pollution than any other ecosystem. Without such data, it is difficult to

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comprehensively understand the effects of anthropogenic REEs on soil microbial

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communities and their ecological functions.

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In order to fill the research gap described above, we studied the microbial

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communities in REE contaminated soils collected from abandoned sites of a REEs

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mine in China. Illumina Miseq sequencing data targeting 16S rRNA genes were

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generated and analyzed in-depth in order to (1) characterize the diversity and 4

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taxonomic profile of microbial communities, (2) investigate the occurrence and

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abundance of potential plant growth promoting bacteria (PGPB), (3) determine the

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influence of various environmental factors on microbial structure, and (4) explore

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co-occurring patterns among microbial communities in REE contaminated soils.

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Materials and Methods

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Field Sites and Soils

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Soils were collected from abandoned REEs mining sites in Jiangxi, China. This mine

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applied heap leaching for REEs extraction, including 7 light REEs (La, Ce, Pr, Nd,

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Pm, Sm, and Eu) and 10 heavy REEs (Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Sc, and Y).

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Three sites with different times since abandonment, i.e., three (3Y), six (6Y), and ten

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(10Y) years ago, were selected to evaluate the influence of natural recovery on the

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microbial community (Figure S1 and Table S1). All sites were confirmed to have

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received no amendment or remediation. An unexploited site at the REEs mine, at

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which the soil contained relatively high REEs concentrations, was selected as a

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control (HREE_CK). For each site, soils from three depths (0-5, 5-15, and 15-30 cm)

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were collected in triplicate using a hollow-stem soil sampler. For comparison, another

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control site (LREE_CK) in the region with lower REEs concentrations but with

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similar climate and soil type (Table S1) was selected. Surface soil (0-5 cm) at this site

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was collected in triplicate. All collected soils were divided into two parts. One part,

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used for physicochemical analyses, was sealed in zip bags, stored at ambient 5

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temperature, and processed immediately after being transported to the laboratory. The

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remaining soil, which was used for microbial analyses, was packed in sterilized

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centrifuge tubes (50 mL), stored in a portable freezer (-18 ºC) at the site, and then

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stored at -40 ºC in the laboratory until use.

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Plant Communities and Soil Physicochemical Properties

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Species richness (SR) and plant coverage (PC) of the plant communities were

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measured by quadrat method. Soil physicochemical properties, including pH,

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electrical conductivity (EC), water content (WC), gravel content (GC), total carbon

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(TC), total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP),

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lithophile elements (LE), siderophile elements (SE), light REEs (LR), and heavy

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REEs (HR), were also measured. Detailed analytical methods are provided in the SI

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(supplementary text T1).

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DNA Extraction, PCR Amplification and Illumina Miseq Sequencing

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DNA of soils was extracted using the FastDNATM SPIN Kit for Soil (MP Biomedicals,

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France). PCR amplification and Illumina Miseq sequencing for 16S rRNA genes were

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conducted according to standard protocols recommended by the Earth Microbiome

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Project

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(supplementary text T2).

(http://www.earthmicrobiome.org/).

For

details,

please

see

the

SI

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Sequence Preprocessing

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The obtained 16S rRNA sequences were preprocessed in Mothur (v 1.36.1).21

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Paired-end sequences were overlapped to form contigs by command “make.contigs”.

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The contigs were screened for high quality by command “trim.seqs” as follows: (1) an

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exact match to barcodes and primers; (2) a quality cutoff of Q30; (3) zero ambiguous

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base calls. Screened contigs, which were assigned to chloroplasts, mitochondria, or

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Eukaryota

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“remove.lineage”. The chimeras were detected in de novo mode22 and discarded by

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commands “chimera.uchime” and “remove.seqs”, respectively. Finally, 1,349,224

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high-quality sequences were obtained, with an average of 34,595 sequences per

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sample (Table S2). Datasets of the 16S rRNA sequences were deposited in

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MG-RAST under accession ID 4689540.3-4689578.3.

by

command

“classify.seqs”,

were

removed

by

command

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Bioinformatic Analyses

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High-quality sequences that passed preprocessing were taxonomically assigned by the

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RDP classifier (v 2.10)23 with 50% confidence threshold based on a trade-off between

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maintaining classification accuracy and maximizing the classifiable sequences.24 The

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sequences were also clustered into operational taxonomic units (OTUs) by UCLUST

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at 97% identity using the script “pick_open_reference_otus.py” in QIIME (v 1.91),25

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which used the Greengene database (13_8 release)26 as a reference. Based on the

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reproducibility of technical duplicates (Figure S2 and supplementary text T3 in SI), 7

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low-abundance OTUs (0.6 and the Benjamini-Hochberg adjusted p-value

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was