Survey of dissimilatory nitrate reduction to ammonium microbial community at national wetland of Shanghai, China

Journal Pre-proof Survey of dissimilatory nitrate reduction to ammonium microbial community at national wetland of Shanghai, China Yiyi Zhao, Cuina Bu, Houling Yang, Zhuangming Qiao, Shaowu Ding, Shou-Qing Ni PII:

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https://doi.org/10.1016/j.chemosphere.2020.126195

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CHEM 126195

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Received Date: 13 January 2020 Revised Date:

11 February 2020

Accepted Date: 11 February 2020

Please cite this article as: Zhao, Y., Bu, C., Yang, H., Qiao, Z., Ding, S., Ni, S.-Q., Survey of dissimilatory nitrate reduction to ammonium microbial community at national wetland of Shanghai, China, Chemosphere (2020), doi: https://doi.org/10.1016/j.chemosphere.2020.126195. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Ltd.

Credit Author Statement Yiyi Zhao and Cuina Bu performed the research; Shou-Qing Ni designed the research; Yiyi Zhao analyzed the data; Yiyi Zhao and Houling Yang wrote the paper; Shou-Qing Ni, Zhuangming Qiao and Shaowu Ding revised the paper.

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Survey of Dissimilatory Nitrate Reduction to Ammonium Microbial Community

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at National Wetland of Shanghai, China

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Yiyi Zhao a, b, c, Cuina Bu a, Houling Yang d, Zhuangming Qiao e, Shaowu Ding f,

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Shou-Qing Ni a, b, c, *

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a

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Reuse, School of Environmental Science and Engineering, Shandong University,

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Qingdao, Shandong, 266237, China

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b

State Key Laboratory of Estuarine and Coastal Research, Shanghai, 200241, China

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c

State Key Laboratory of Petroleum Pollution Control, Beijing, 102206, China

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d

Jinan Vocational College, Jinan, 250014, China

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e

Shandong Meiquan Environmental Protection Technology Co., Ltd., Jinan, China.

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f

Shandong Wanhao Fertilizer Co., Ltd., Jinan, China.

Shandong Provincial Key Laboratory of Water Pollution Control and Resource

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* Corresponding author ： Shou-Qing Ni, School of Environmental Science and

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Engineering, Shandong University, China. E-mail: [email protected]. Tel. /Fax: +

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86-0532- 58630936

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1

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Abstract

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Dissimilatory nitrate reduction to ammonia (DNRA) process is an important

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nitrate reduction pathway in the environment. Numerous studies focused on the

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DNRA, especially in various natural habitats. However, little is known about the

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envrionmental parameters driving the DNRA process in anthropogenic ecosystem.

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Human activities put forward significant influence on nitrogen cycle and bacterial

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communities of sediment. This study aimed to assess the DNRA potential rates, nrfA

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gene abundance, DNRA bacterial community’s diversity and influencing factors in a

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national wetland park near the Yangtze River estuary, Shanghai. The results of

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isotope tracer experiments showed that DNRA potential rates from 0.13 to 0.44 µmol

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N/kg/h and contribution of nitrate reduction varied from 1.56% to 7.47%. The

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quantitative real-time PCR results showed that DNRA functional gene nrfA

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abundances ranged from 9.87E+10 to 1.98E+11 copies/g dry weight. The results of

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nrfA gene pyrosequencing analysis showed that Lacunisphaera (10.4~13.4%),

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Sorangium (7.1~10.7%), Aeromonas (4.2~6.8%), Corallococcus (1.8~6.9%), and

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Geobacter (3.3~6.6%) showed higher relative abundances in their genus levels.

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Combined with environmental parameters of sediments, redundancy analysis

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indicated that the nrfA functional gene was positively correlated with moisture content,

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the concentration of NO2--N and NO3—N; the DNRA rates was positively correlated

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with sediment organic carbon (SOC), C/NO3- ratio and salinity (ranked by

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explains %). This study is the first simultaneous determination of nitrate reduction

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pathways including denitrification, anammox and DNRA rates to assess the role of 2

15

N

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DNRA in a national wetland park and revealed the community abundance, diversity

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of DNRA bacteria and its relationship with environmental factors.

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Keywords: Dissimilatory Nitrate Reduction to Ammonium; Functional gene nrfA;

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Microorganism diversity; Wetland sediments; Yangtze River estuary

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1. Introduction

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Intensive anthropogenic activities have led to an acute increase in reactive

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nitrogen (Nr) emissions which cause nitrogen deposition in terrestrial and aquatic

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ecosystems all over the world (Gao et al., 2014). Wetlands is one of the most

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important and vulnerable ecosystems on earth (Hu et al., 2017) due to their important

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role in the flood prevention, flow control, nutrient and waste absorption/treatment,

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fishery, and landscaping (Barbier, 1995). Each hectare of wetland can remove more

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than 1,000 kilograms of nitrogen and 130 kilograms of phosphorus per year (Meng et

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al., 2017). However, with increasing human development, the area of natural wetlands

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continues to decline globally, but various constructed wetlands (CWs) have been

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created (Bellio et al., 2009). Wetland sediment is both a source and a sink of nutrients

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(Bu et al., 2017) because sediment acts as a site for adsorption/desorption and

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precipitation/dissolution of various nutrient transformation reactions (Yuan et al.,

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2019). Therefore, the study of the microorganisms in wetland sediment associated

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with nitrogen transformations is important for the environment management of the

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wetland ecosystem.

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Specific pathways of NO3- reduction within estuarine sediments includes

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canonical denitrification, anammox, and DNRA (Domangue and Mortazavi, 2018).

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However, these processes play diverse roles in controlling the fate of nitrate (Deng et

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al., 2015). Both denitrification (reduction of nitrate to nitrite and then N2 via the

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anoxic processes) and anaerobic ammonium oxidation remove nitrite from

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ecosystems (Thamdrup, 2012). Dissimilatory nitrate reduction to ammonium is a 4

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biological process (Jahangir et al., 2017) which cannot remove nitrogen from the soil;

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instead, the final product of DNRA is ammonium nitrogen (Burt et al., 2010). In the

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presence of NO3- or NO2-, all three processes occur under anoxic conditions, but the

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differences in metabolisms among denitrification, anammox, and DNRA bacteria may

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lead to different end products (Hardison et al., 2015). Generally, there are four key

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factors in controlling the balance between nitrate reduction via denitrification and

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DNRA: NO3- availability, organic carbon loading, temperature, and availability of

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reducing agents such as sulfide or iron (II) (Roberts et al., 2014). Denitrification

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dominated at low C/N ratios (limited electron donors growth conditions), while

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respiratory ammonification dominated at high C/N ratios (limited electron acceptor

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growth conditions) (Yoon et al., 2015).

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Numerous studies focused on the DNRA process, especially in various natural

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habitats. Domangue and Mortazavi (2018) found that DNRA exceeded in-situ

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denitrification in nitrate reduction and provided 5% of the nitrogen need for primary

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producers’ N demand in a shallow eutrophic estuary. Cheng et al. (2016) estimated the

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contributions of DNRA, denitrification and anammox to nitrate reduction of urban

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river networks adopting isotope-tracer technology. Riparian zones were confirmed as

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active sites of DNRA (Davis et al., 2008), in contrast, DNRA accounted for only 5-15%

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of nitrate reduction in the CW (Scott et al., 2008). Wetland parks, usually constructed

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and operated by government or public groups, are landscape ecological environment

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systems and (Li et al., 2015). Wetland parks differ from traditional constructed

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wetlands or urban parks. The main part of wetland parks is constructed by reserving, 5

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imitating and restoring wetland habitats (Li, 2013). Environmental protection as well

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as ecotourism and leisure are the two important functions of national wetland parks

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(Pan et al., 2010). The uniqueness of wetland park is the serious control by human

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beings and the decision-making of park management directly effects the development

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and balance of the park ecosystem. Human activities put forward a significant

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influence on nitrogen cycle and bacterial communities of sediment. However, the

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abundance and microbial community study based on nrfA gene analysis in a

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freshwater wetland park near an estuary remains unanswered.

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Wusong Paotaiwan National Wetland Park located in the west coast of Yangtze

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River and it is the largest pristine wetland at Shanghai City. In this study, the rate,

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activity and community structure of DNRA bacteria from the wetland park were

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investigated. The main goal of this study was (1) to examine the rates and abundance

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of DNRA, denitrification and anammox bacteria and their correlation in a national

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wetland park, (2) to explore the composition of DNRA community based on

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pyrosequencing techniques, and (3) to evaluate the relationships among selected

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environmental factors and the distribution of DNRA bacteria.

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2. Material and methods

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2.1 Description of the study area

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Shanghai Wusong Paotaiwan National Wetland Park is the relic of the Yangtze

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River wetland and located in the intersection of Yangtze River and Huangpu River,

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east coast of the Yangtze River. From the 1960s, this area was backfilled with steel

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slag and gradually formed a park. In 2005, to improve the local ecological 6

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environment, the municipal government redesigned the site into the national wetland

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forest park.

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2.2 Sample collection and analysis

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In this study, five representative sampling sites were selected in the wetland park

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(Figure S1). Sediments were collected in September 2017. Surface sediments at each

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site were collected in sterile plastic bags and immediately transported to the

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laboratory and stored at -20℃ for later analysis. Almost all points had a sampling

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depth of 0-10 cm. The five sites were expressed as: SD1 (31°23′44" N, 121°30′26" E),

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SD2 (31°23′47" N, 121°30′31" E), SD3 (31°23′48" N, 121°30′31" E), SD4 (31°23′53"

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N, 121°30′28" E), and SD5 (31°24′12" N, 121°30′15" E). The pH and salinity were

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measured by a pH meter (PhS-3C, Rex Electric Chemical, China) and a conductivity

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meter (STEC-100, SP, USA), respectively. After freeze-drying, the sediment organic

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carbon (SOC) content was measured with the potassium dichromate method (Wang et

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al., 2012). Sediment samples were extracted for NO3--N, NO2--N, and NH4+-N

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analysis using 2M KCl. Then ultraviolet-visible spectrophotometer (TU1810-PC,

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Purkinje General, China) was used to determine with following the standard methods

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(Heaney et al., 2018).

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2.3 15N tracer incubations

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The potential rate of different nitrate reduction pathways (DNRA, denitrification,

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and anammox) was measured by sediment slurry incubation experiments using the

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15

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one gram (wet weight) of sediment samples and 5 mL overlying water were added to

N isotope pairing technique according to previous studies (Pang et al., 2019). First

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12.00 mL glass vials to form slurries. The sediment slurries were purged with argon

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aeration for 15 min after mixing. Then vials were sealed and placed in dark anaerobic

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incubator and preincubated at room temperature (22-25

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residual oxygen and nitrate. After preincubation, the vials were spiked with Na15NO3

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(99%) to a final concentration of 100 µmol 15N L-1. Subsequently, one of the vials was

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preserved with 1 mL 50% w/v ZnCl2 to stop the activities of the microorganisms and

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described as the initial samples. The remaining samples were placed and shaken (200

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rpm) in the dark anaerobic incubator for 8 hours. At the end of the incubations,

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remaining samples replicates were persevered with 1 mL 50% w/v ZnCl2 and

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described as the final samples. The vials were injected with hypobromite iodine

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solution to oxidize the 15NH4+ to 15N gases and then measured by isotope ratio mass

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spectrometer (Isoprime). More details of the assay method of anammox and

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denitrification rates were described by Xiao et al. (2018). The DNRA potential rate

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was quantified by measuring the final and initial

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below equation. [15NH4+]i and [15NH4+]

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concentration of the initial samples and final samples, respectively; V (L) refers to the

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volume of the incubation vial; m (g) refers to the dry weight of sediment, and t (h)

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refers to the incubation time (Porubsky et al., 2008).

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f

15

o

C) for 24h to eliminate

NH4+ concentration according to

(µmol N/L) represented the

15

NH4+

RDNRA=([15NH4+] f -[15NH4+] i) ×V/(m×t) 2.4 DNA extraction and quantitative real-time PCR (q-PCR) analysis

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The DNeasy® Power Soil DNA Kit was used to extract DNA from sediment

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samples, and the quantification of DNA was done by an ultraviolet spectrophotometer. 8

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To quantify the abundance of bacteria, q-PCR assays for the functional gene (nrfA,

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nirS, nirK, and anammox-16S rRNA) were adopted, and the q-PCR reaction mixture

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(20 µL) including 2×SYBR Green PCR master mix (10 µL), forward primer (0.4 µL),

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reverse primer (0.4 µL), template DNA (1 µL), and dd H2O (8.2 µL).. The functional

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gene primers used in this experiment were listed in Supplementary Table 1. The qPCR

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data analysis was performed using the Abs Quant/2nd Derivative Max software

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(Zhang et al., 2016).

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2.5 Amplification PCR, Illumina sequencing and biodiversity analysis

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In this experiment, the primers nrfAF2aw (CARTGYCAYGTBGARTA) and

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nrfAR1 (TWNGGCATRTGRCARTC) were used to amplify the partial sequence of

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nrfA region of bacteria with a length of about 250 bp (Welsh et al., 2014).

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Electrophoresis of the PCR products was identified and then was purified by gel

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extraction kit. The gel recovery kit of AXYGEN was used for recycling.

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Referring to the preliminary quantitative results of electrophoresis, the amplified

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PCR product was subjected to fluorescence quantification. The fluorescent reagent

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was Quant-iT PicoGreen dsDNA Assay, and the quantitative instrument was

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Microplate reader (BioTek, FLx800). Each sample was mixed in the corresponding

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ratio based on the fluorescence quantification results and the amount of sequencing

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required. 2×300bp double-end sequencing was performed on an Illumina MiSeq

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sequencer with the corresponding reagent MiSeq Reagent Kit V3 (600 cycles).

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Using QIIME software and invoking UCLUST sequence comparison tool (Edgar,

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2010), the obtained sequences were merged and OTUs were divided by 97% sequence 9

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similarity, and the most abundant sequence in each OTU was selected as the

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representative sequence. The OTU representative sequences were compared with the

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template sequence of the corresponding database to obtain the taxonomic information

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of each OTU and the four diversity indices (the Chao1 estimator (Chao, 1984), the

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ACE estimator (Chao et al., 1993), Shannon diversity index (Shannon, 1948) and the

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Simpson index (Simpson, 1949)) were calculated. The alpha diversity index of each

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sample and the distribution of DNRA bacteria in five samples were determined using

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QIIME. And heat map was constructed with the 50 most abundant genera using R

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software.

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2.6 Statistical analysis

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The differences of community composition among five sites were evaluated

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through nonmetric multidimensional scaling (NMDS) analysis based on weighted

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uniFrac distance. To examine the relationship between the influences of

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environmental factors and community structures, redundancy analysis (RDA) was

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employed using CANOCO version 4.5 software. Spearman correlational analyses

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were performed using the software package SPSS (Standard version 19.0, SPSS, Inc.).

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Correlation of P values less than 0.05 were relevant.

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3. Results

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3.1 Environmental parameters

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Five environmental parameters of each sediment site are reported in

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Supplementary Table 2. The moisture content of sediments ranged from 24.6% to

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38.4%, and SD1 sediment is the highest. Both sediments’ pH and salinities are similar 10

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to each other without a significant difference for all five sampling locations. Sediment

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organic carbon (SOC) and extractable NH4+-N ranged from 11.6 to 27.0 g-C/kg and

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0.50 to 3.48 µ mol-N/g, respectively. The extractable NH4+-N was as low as 0.50 µ

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mol-N/g at SD5. The SD1 sediment extractable ammonium nitrogen concentration far

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exceeded other sampling points. The concentrations of nitrate and nitrite in sediments

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ranged from 3.87 to 5.05 µ mol-N/g and 2.35 to 10.54 µ mol-N/g, respectively.

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3.2 DNRA potential rates and contributions of NO3- reduction

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Table 1 shows that the potential rates of different nitrate pathways in Shanghai

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Wusong Paotaiwan National Wetland Park. Denitrification was the dominant pathway,

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with potential rates varied from 3.21 to 17.8 µmol N/kg/h. DNRA process had the

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lowest potential, and rates of DNRA ranged from 0.13 to 0.44 µmol N/kg/h,

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accounting for 1.56-7.47 % of the nitrate reduction. The lowest DNRA rate occurred

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at SD5, while the highest DNRA rate was found in SD3.

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3.3 Functional gene abundance

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Figure 1 shows that absolute abundances of related genes involved in

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dissimilatory nitrate reduce process in Shanghai Wusong Paotaiwan National Wetland

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Park. The nitrite reductase nrfA gene abundances suggest the metabolic potential for

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DNRA bacteria (Subedi et al., 2017), nirK and nirS gene abundances represent

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denitrifying bacteria and anammox-16S rRNA stands for anaerobic ammonia

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oxidizing bacteria. The high nrfA gene abundance suggests the metabolic potential of

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DNRA bacteria was favorable in the sediment samples of Wusong Paotaiwan national

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wetland park. The gene abundances of nrfA ranged from 9.87E+10 to 1.98E+11

11

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copies/g dry weight. The lowest gene abundances of nrfA was found at SD3, while

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higher gene abundances were measured in the sediment SD1, SD4, and SD5. For

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denitrifying bacteria, gene abundances ranged 1.36E+09-3.87E+09 copies/g dry

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weight (nirS), and 2.52E+06-2.31E+07 copies/g dry weight (nirK), respectively. The

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anammox-16S rRNA abundances ranged from 6.85E+09 to 1.26E+10 copies/g dry

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weight. NirS, nirK and anammox-16S rRNA gene abundance are basically in the same

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order of magnitude.

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3.4 Diversity of DNRA community

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Via high-throughput sequencing, raw sequences were obtained from the surface

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sediment samples of Wusong Paotaiwan National Wetland in Shanghai. After

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removing low-quality reads, a total of 60699-78463 valid sequences were produced.

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Then, via further filtering, a total of 2663-5198 operational taxonomic units (OTUs)

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was clustered (Supplementary Table 3). The relationships among the OTUs of these

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five samples are illustrated in Figure S2. SD2 has the highest number of OTUs while

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SD5 has the lowest. The bacterial alpha diversity indices concerned both taxon

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richness and evenness (Peng et al., 2018), including Simpson, Chao1, ACE, and

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Shannon. The Chao1 and ACE estimators in SD2 were the highest and these in SD5

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were the lowest, showing that the highest community richness occurred at SD2, while

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the lowest richness occurred at SD5. The Simpson and Shannon indices of SD2

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reached 0.998875 and 11.09, respectively, higher than the other sites, also confirming

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that the highest diversity was found in SD2. Thus, SD2 sediment tended to have

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higher bacterial richness and diversity than the other sites. Similarly, rank abundance 12

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curve (Fig. S3) shows that the line representing SD2 was the longest and smoothest,

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and the line representing SD5 was the shortest and steepest, indicating that SD2 had

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the highest community richness and evenness, and SD5 had the lowest.

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In order to quantify the difference and similarity among the five sites, NMDS

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analysis of genus level community composition was carried out by R software (Fig. 2).

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The higher similarity of microbial community structure between SD1 and SD4, SD3

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and SD2 was observed from Fig. 2. This finding is also demonstrated clearly in the

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cluster analysis in the form of a hierarchical tree in Figure S4.

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Community structures of DNRA bacteria with relative abundances at phylum

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and genus level are given in Fig. 3. Proteobacteria (33.8~35.5%), Chloroflexi

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(10.5~25.2%),

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Planctomycetes (2.1~15.9%), Acidobacteria (1.6~9.5%), Ignavibacteriae (1.4~7.1%)

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and Nitrospirae (2.0~2.8%) were the dominant bacteria among the 10 identified phyla.

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Proteobacteria was the most abundant phylum in all samples. Many sequences based

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on nrfA pyrosequencing were not classified to a certain type, like the results of

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previous research by our group (Bu et al., 2017). Besides, small quantities of

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Actinobacteria and Firmicutes were also present. Interestingly, Planctomycetes and

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Ignavibacteriae relative abundances in the SD5 were more than three times than other

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sites, reaching 15.9% and 7.1%, respectively.

Verrucomicrobia

(10.5~16.3%),

Bacteroidetes

(3.6~11.0%),

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At the genus level, a total of 53-59 genera were identified in five sites, and 15

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of them were predominant (>0.5% abundance in at least one site). As depicted in

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Fig.3(b), Lacunisphaera genus (Verrucomicrobia, Opitutae) was one of the major 13

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DNRA bacterial groups at all sites in this study, accounting for 10.4~13.4%. The

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proportion of Lacunisphaera in SD5 was the highest while in SD3 was lowest.

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Sorangium also occupied a considerable proportion in Wusong Paotaiwan National

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Wetland Park (7.1~10.7%). Aeromonas (Gammaproteobacteria), Corallococcus

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(Deltaproteobacteria) and Geobacter (Deltaproteobacteria) were more abundant than

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other genera, belonging to Proteobacteria. Anaerolinea in SD2 was present at the

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lowest level among five sites. Particularly, the proportion of Planctomyces in SD5

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accounting for 15.2% was about seven to eight times more than it at other sites.

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Ignavibacterium was also present at a very high level, reaching 7.1%. Other abundant

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genera were Draconibacterium (0.8~5.5%), Nitrospira (2.0~2.8%), Caldilinea

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(1.4~2.8%), Bacteroides (0.5~2.1%), Bdellovibrio (0.4~2.6%) and Desulfomicrobium

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(0.3~1.5%).

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Heatmap of the top 50 bacterial genera in sediment samples from Shanghai

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Wusong Paotaiwan National Wetland Park is shown in Fig. 4. Sites were clustered

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using UPGMA dendrogram based on Bray-Curtis similarities. The microbial

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community at genus level was divided into three clusters, in which SD5 alone formed

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one cluster. The community structure in SD1 was similar with SD4, and they were

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clustered into a group. SD2 and SD3 together fell in the other group, indicating their

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similarity in microbial community structure.

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3.5 Relationships of DNRA rate, bacterial abundance, diversity and

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environmental parameters

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Table 2 showed the distribution of DNRA community in Wusong Paotaiwan 14

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national wetland park related to environmental variables (two-tailed, p < 0.05). The

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moisture content of sediments was significantly and positively correlated with nrfA

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gene abundance (P=0.037) while negatively correlated with Shannon index (P=0.037).

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But the correlation between other characteristics and diversity index was not

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significant. Redundancy analysis (RDA) was used for further evaluating the

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relationship among nitrogen functional genes and environmental variables (Figure 5).

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The angle < 90 ° indicates a positive correlation, and a smaller angle represents a

294

stronger positive correlation. Conversely, the angle > 90° indicates a negative

295

relationship, and larger angle also implies a stronger negative relationship. Besides,

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the arrow length reflects the importance of the parameter, and the orientation

297

represents the association between the parameter and the axis (Zhang et al., 2018a).

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As Fig.5 shows, nrfA gene abundance were positively correlated with moisture

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content, the concentration of NO3- and NO2-. The DNRA rates was positively

300

correlated with SOC, C/NO3- ratio and salinity.

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4. Discussion

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4.1 High nrfA gene abundance does not represent high DNRA rate

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Although the conditions for promoting DNRA and denitrification are similar

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(hypoxia, available nitrate, and organic substrates), denitrification is a permanent

305

nitrogen removal pathway (Sgouridis et al., 2011), while the presence of DNRA

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transforms nitrate to ammonium nitrogen which is more bioavailable (Deng et al.,

307

2015). The aquatic plant is an essential and special component in the wetland system

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(Pang et al., 2016). In such a system, ammonium nitrogen is easy to be assimilation 15

309

and absorption, and nitrate is also removed. Thus the plants grow fast, and the water

310

quality of wetland is purified. The co-existed anammox bacteria also contributed to

311

the consumption of ammonium nitrogen. DNRA process is a vital contributor for

312

renewable nitrogen in the ecosystem of the study area. They can effectively conserve

313

and recycle nitrogen and reduce the nutrient loss caused by denitrification (Cao et al.,

314

2016). In addition, temperature is also important for the nitrogen cycle (Gardner and

315

McCarthy, 2009). High temperatures were conducive to the occurrence of DNRA

316

process in temperate estuarine sediments (King and Nedwell, 1984). In this study,

317

sediments were collected in September 2017 with the monthly average temperature of

318

23-28 oC. Dunn et al. (2013) pointed out that highest total DNRA rates occurred in

319

summer when the temperature was maximal and the sediment was in a strong

320

reductive state. Thus, DNAR potential rates may become even lower in sediments in

321

winter. However, the current qPCR method has its limitation, thus, result in many of

322

the nrfA genes detected may be dormant and not expressed. This is one reason why

323

nrfA gene abundance far exceeded nirS, nirK and anammox-16S rRNA but the DNRA

324

process only accounted for 1.56-7.47 % of the nitrate reduction. The only way to

325

prove nrfA relevance is to follow transcripts of the genes and proteins.

326

Compared to nirS, nirK is preponderating in the abundances of wetland. The

327

findings of this study in agreement with the results of Garcia-Lledo et al. (2011), who

328

found that in sediment samples of CW the proportions of nirK-type denitrifiers in the

329

bacterial community exceeded nirS-type ones. Li et al. (2018) also found that nirK

330

outnumbered nirS in all seasons in sediments of surface flow CW during swine 16

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wastewater treatment. On the other hand, Ligi et al. (2014) reported that nirS-type

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denitrifiers dominated in a created riverine wetland complex soil. The abundances of a

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functional gene in 3 different nitrate reduction pathways was found higher at SD1,

334

SD4, and SD5. This phenomenon suggests that the three places have a special

335

environment which is suitable for the growth of this microorganisms.

336

4.2 The DNRA bacterial community diversity and environmental implications

337

In terms of geography, SD1 sediment came from an internal lake of Wusong

338

Paotaiwan national wetland park, while SD2, SD3, and SD5 sediments were from the

339

Yangtze river estuary tidal flats. SD4’s environment is rather special since it is the

340

junction of the internal lake and the Yangtze river. However, it was unexpected that

341

bacterial composition in SD5 was much more distinct, confirmed by NMDS analysis

342

(Fig.2) and hierarchical tree (Fig. S4). Ten dominant phyla could perform DNRA

343

among which Proteobacteria had the highest relative abundance (33.8~35.5%),

344

followed by Chloroflexi (10.5~25.2%), Verrucomicrobia (10.5~16.3%), Bacteroidetes

345

(3.6~11.0%),

346

Proteobacteria is the most abundant phylum of the known DNRA bacteria identified

347

by the presence of the nrfA gene, and its phenotype was predominantly found in

348

Delta- (17.2~27.0%) and Gammaproteobacteria (6.32~17.59%), the same as those in

349

some shallow estuarine sediments (Decleyre et al., 2015; Song et al., 2014; Wang et

350

al., 2018). Notably, at the phylum level, the relative abundance of Planctomycetes and

351

Ignavibacteriae in the SD5 was more than three times than others, reaching 15.9%

352

and 7.1%, respectively. The proportion of Planctomyces in SD5 was about seven or

Planctomycetes

(2.1~15.9%)

17

and

Acidobacteria

(1.6~9.5%).

353

eight times higher than that of other sites, accounting for 15.2% while

354

Ignavibacterium reached 7.1% at the genus level. Planctomycetes was a typical

355

anammox bacteria (Xu et al., 2018) and were discovered in many marines and

356

freshwater aquatic habitats and soils, as well as in extreme habitats (Schlesner, 1994).

357

Planctomycetes had a strong ability to remove carbon and ammonium nitrogen,

358

resulting in the lower SOC and NH4+-N concentrations at SD5 (Liu et al., 2018).

359

DNRA bacteria

included

obligate

anaerobic,

facultatively

anaerobic,

360

microaerobic and aerobic bacteria, these bacteria have different electron transport

361

chains (Kraft et al., 2014; Li et al., 2018a; Sgouridis et al., 2011). The facultatively

362

anaerobic bacteria were more common among DNRA bacteria (Zhang et al., 2018b).

363

In the study, Lacunisphaera genus (Verrucomicrobia, Opitutae) was one of the major

364

DNRA bacterial groups at all sites, accounting for 10.4~13.4%. Sorangium

365

(7.1~10.7%) also occupied a considerable proportion. Lancunisphaera was a spherical

366

microorganism from the freshwater lake and considered to be aerobic (Rast et al.,

367

2017; Tegtmeier et al., 2018). This also explained the predominance of

368

Lancunisphaera at various sampling sites in the wetland park. However, there is also

369

no clear whether Lancunisphaera has the DNRA function. Sorangium was a

370

cellulose-decomposing bacterium and derived from the surfaces or close to the

371

surface of the soil, manure and decaying plant debris (Shimkets et al., 2006). Its

372

agricultural or ecological significance was unclear (Lupwayi et al., 2017). Nitric oxide

373

synthase (NOS) is a ubiquitous enzyme responsible for the synthesis of NO in the

374

cells of bacteria and higher organisms (Medinets et al., 2015). Studies have shown 18

375

that NOS-like enzymes in Firmicutes, Actinobacteria, Deinococcus-thermus and one

376

representative of the Proteobacteria phylum (Sorangium) have highly homologous

377

with the eukaryotic domain NOS oxygenase (Crane et al., 2010; Gusarov et al., 2008;

378

Sudhamsu and Crane, 2009). There are some indications that enzyme bound NO and

379

NH2OH are probable intermediates of DNRA process (Kraft et al., 2011). Therefore,

380

we speculate that the detail effect of Sorangium in the DNRA process is to synthesize

381

NO by using NO3--N or NO2--N. In Wusong Paotaiwan national wetland park,

382

Aeromonas (4.2~6.8%), Corallococcus (1.8~6.9%), and Geobacter (3.3~6.6%) were

383

more abundant than other genera. Unlike denitrification, which is mediated by

384

respiratory organisms, DNRA is performed by fermentative organisms (e.g.,

385

Aeromonas) shunting excess electrons to NO3- (Caskey and Tiedje, 1980; Santoro,

386

2009). Geobacter is the only isolate demonstrated to carry out DNRA coupled to Fe2+

387

oxidation so far (Finneran et al., 2002; Lovley et al., 1993). They are abundant species

388

in iron-rich freshwater sediments and implicated as conveyors of DNRA process in

389

enrichment cultures (Weber et al., 2006).

390

4.3 Environmental factors that determine nrfA gene abundance and DNRA

391

potential rates

392

Through the relative abundance map and heat map, the community structure of

393

DNRA bacteria at each sample is different. Different environmental factors led to

394

different DNRA bacterial composition and structure (van den Berg et al., 2015).

395

Previous studies indicated that the contribution rate of DNRA in soils or sediments of

396

different ecosystems correlated closely to moisture content, pH, carbon-nitrogen ratio, 19

397

the concentration of NO3--N and NO2--N (Dong et al., 2011; Friedl et al., 2018;

398

Schmidt et al., 2011). In this study, combining Spearman correlation with RDA

399

analysis, the moisture content of sediments was significantly and positively correlated

400

with nrfA gene abundance (P=0.037). Besides, the nrfA functional gene abundance

401

was positively correlated with the concentration of NO3--N, NO2--N. The DNRA rates

402

was positively correlated with SOC and C/NO3- ratio. The high soil moisture content

403

increased the labile C in the soil, enhanced heterotrophic soil respiration, and reduced

404

soil redox potential. Thus, denitrification was inhibited, and ultimately transferred

405

NO3- consumption shifted from denitrification to DNRA (Friedl et al., 2018). The

406

high SOC and C/NO3- may be responsible for the higher DNRA rates because organic

407

carbon can be used as an electron donor in the fermentative DNRA process, and the

408

reduction of 1 mol nitrate fermentative DNRA needs 3 mol more C than

409

denitrification, which means that a high C/N favors the fermentative DNRA process

410

(Laverman et al., 2006; Wang et al., 2020). Since the SOC and C/NO3- were the major

411

influence factors of DNRA potential rates, it can be inferred that DNRA process in

412

Wusong Paotaiwan wetland park sediments was mainly conducted by heterotrophic

413

bacteria. Similar results have been found in natural ecosystems such as shallow lake

414

sediments and Yangtze estuarine sediments (Pang et al., 2019; Deng et al., 2015).

415

5. Conclusion

416

The present study reports an investigation of DNRA potential rates, nrfA gene

417

abundance, DNRA bacterial community’s diversity and its interaction with

418

environmental factors in Wusong Paotaiwan national wetland park near the Yangtze 20

15

419

River estuary, Shanghai. The results of

N isotope tracer experiments indicated that

420

DNRA potential rates varied from 0.13 to 0.44 µmol N/kg/h, corresponding to the

421

contribution from 1.56% to 7.47%. While the qPCR assays results showed that nrfA

422

gene abundance far exceeded nirS, nirK and anammox-16S rRNA. The gene

423

abundances of nrfA ranged from 9.87E+10 to 1.98E+11 copies/g dry weight.

424

Pyrosequencing technology of nrfA gene results indicated ten phyla and 53-59 genera

425

were identified in the sediments of five sites, and 15 of them were predominant (>0.5%

426

abundance in at least one site). This study also proved that microorganisms were

427

affected by different environmental factors and presented differently in distribution

428

patterns.

429

6. Acknowledgment

430

The authors gratefully acknowledge the support from the Open Research Fund of

431

State Key Laboratory of Estuarine and Coastal Research (SKLEC-KF201909),

432

National

433

Taishan Scholar Youth Expert Program of Shandong Province (tsqn201909005), Key

434

Research & Developmental Program of Shandong Province (2019JZZY020308),

435

Natural Science Foundation for Distinguished Young Scholars of Shandong Province

436

(JQ201809), Young Scholars Program of Shandong University (2016WLJH16,

437

2020QNQT012), Shandong Provincial Water Conservancy Research and Technology

438

Promotion Project (SDSLKY201802), the Open Project Program of State Key

439

Laboratory of Petroleum Pollution Control (PPC2018007), and CNPC Research

440

Institute of Safety and Environmental Technology, and China Association of Marine

Natural

Science

Foundation

21

of

China

(21777086),

441

Affairs (CAMA) and Association of Ocean of China (AOC) (CAMAJJ201808).

442

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31

Table 1 Potential rates of different nitrate reduction pathways in Wusong Paotaiwan National Wetland. Sampling

DNRA rate (µmol N

Denitrification rate

Anammox rate

DNRA

sites

/kg/h)

(µmol N /kg/h)

(µmol N /kg/h)

contribution (%)

SD1

0.32

17.8

2.41

1.56

SD2

0.24

5.44

1.04

3.57

SD3

0.44

4.29

1.16

7.47

SD4

0.15

3.26

1.63

2.98

SD5

0.13

3.21

1.14

2.90

Table 2 Spearman’s correlation coefficients of nrfA gene abundance, diversity index and environmental parameters in Wusong Paotaiwan National Wetland (N=5). Moisture content (%)

pH

Salinity (‰)

SOC (g/kg)

NH4+-N (µ mol N /g)

NO3(µ mol N /g)

NO2(µ mol N /g)

0.900*

0.103

-0.224

0.200

0.500

0.500

0.300

-0.200 -0.800 -0.900*

-0.872 0.154 -0.205

0.224 0.224 0.447

0.600 0.000 0.200

-0.300 0.300 -0.100

-0.300 0.300 -0.100

-0.400 -0.400 -0.300

0.037

0.870

0.718

0.747

0.391

0.391

0.624

0.747 0.104 0.037

0.054 0.805 0.741

0.718 0.718 0.450

0.285 1.000 0.747

0.624 0.624 0.873

0.624 0.624 0.873

0.505 0.505 0.624

Coefficients nrfA gene abundance DNRA rate Chao1 Shannon P values nrfA gene abundance DNRA rate Chao1 Shannon

* means significant correlation when P<0.05.

Figure 1. Absolute abundances of related genes involved in dissimilatory nitrate reduction process in Shanghai Wusong Paotaiwan National Wetland Park

Figure 2. Nonmetric multidimensional scaling (NMDS) analysis of nrfA communities in Shanghai Wusong Paotaiwan National Wetland Park.

Figure 3. Distributions of DNRA bacteria in Shanghai Wusong Paotaiwan National Wetland Park at the phylum(a)and genus (b) level.

Figure 4. Richness heatmap of the 50 most abundant genera in Shanghai Wusong Paotaiwan National Wetland Park.

Figure 5. Redundancy analysis plot of the relationship among the nitrogen functional genes and dominant environmental parameters. Red-solid lines indicate environmental variables. Blue-solid lines show microbial genes. Numbers represent the sampling location.

Highlights

Denitrification was the dominant nitrate reduction pathway in the wetland park. The contribution of DNRA to nitrate reduction varied from 1.56% to 7.47%. SOC and C/NO3- were the key factors driving the distinction of DNRA potentials rates. Lacunisphaera, Sorangium, Aeromonas, Corallococcus and Geobacter were dominant DNRA.

Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: