Co-Variation between Distribution of Microbial Communities and

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Co-variation between Distribution of Microbial Communities and Biological Metabolization of Organics in Urban Sewer Systems Pengkang Jin, Xuan Shi, Guangxi Sun, Lei Yang, Yixiao Cai, and Xiaochang C. Wang Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b05121 • Publication Date (Web): 04 Jan 2018 Downloaded from http://pubs.acs.org on January 4, 2018

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Co-variation between Distribution of Microbial Communities and Biological Metabolization of Organics in Urban Sewer Systems

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Pengkang Jin 1,*, Xuan Shi 1, Guangxi Sun 2, Lei Yang 1, Yixiao Cai 3, Xiaochang C. Wang 1

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1. School of Environmental and Municipal Engineering, Xi’an University of Architecture

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and Technology, Xi’an, Shaanxi Province, 710055, China 2. Sino-Danish Center for Education and Research (SDC), ,University of Chinese Academy of Sciences, Beijing, 100190, China 3. NUS Environmental Research Institute, National University of Singapore, 1 Create Way, Singapore 138602, Singapore

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ABSTRACT: Distribution characteristics and biodiversity of microbial communities were

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studied in a 1200-m pilot sewer system. Results showed that the dominant microorganisms,

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fermentation bacteria (FB), hydrogen-producing acetogen (HPA), sulphate-reducing bacteria

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(SRB) and methanogenic archaea (MA) changed significantly along the sewer systems, from

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start to the end. The distribution of the functional microorganisms could induce substrate

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transformation and lead to the accumulation of micromolecular organics (i.e., acetic acid,

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propionic acid and amino acid). However, substrate transformation induced by these microbes

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was affected by environmental factors such as oxidation-reduction potential, pH and dissolved

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oxygen. Changes in environmental conditions along the sewer resulted in the variation of

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dominant bioreactions. FB were enriched at the beginning of the sewer, while SRB and MA

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were found toward the end. Furthermore, based on Spearman rank correlation analysis of

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microbial communities, environmental factors and substrates, co-variation between microbial

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community distribution and organics metabolization along the sewer was identified. This

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study could provide a theoretical foundation for understanding wastewater quality variation

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during transportation from sewers to treatment plants, therefore, promoting optimization of

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design and operation of wastewater treatment.

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INTRODUCTION

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The urban sewer system is an important component of urban water infrastructure for sewage

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collection and transportation. 1 As the starting point part of the entire urban sewage disposal

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system, urban sewer systems have been studied for decades.

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sessions of sewage quality variation were convened in Denmark, opening a new chapter in the

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research on bioreactions in sewer system,

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different oxygen environment effects on microbial communities, Chen et al 6 studied biofilms

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from sediments and the inner surface of sewers by cross-cutting biofilm samples and

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analyzing the bio-activity of microbial communities. In addition, Tanji et al

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self-biopurification capacity of sewage by installing concrete blocks as carriers in sewer

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systems, and after 79 days, biofilms were found on the surface of the carriers, indicating that

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the inner environment of the sewer was suitable for biofilm growth.

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In general, pollutants in urban sewage are easily degraded by the microbial community in the

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sewers, and with abundant carbon, nitrogen and other nutrients, urban sewage could provide

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substantial substrates for the growth and reproduction of microbes. Relevant study has

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indicated that hydrolysis and acidification were the dominant bioreactions for the

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decomposition of substrates in sewers. 8 Our previous study 9 demonstrated that larger organic

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molecules were transformed into products with smaller molecular weights and that

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unsaturated organics were converted into saturated organics, leading to the improvement in

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biodegradability of the sewage. Furthermore, the transformation of VFA into acetic acid with

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the production of CH4 and CO2 contributed to an obvious reduction in chemical oxygen

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demand (COD) along the sewer. However, due to a lack of understanding of the

3, 4, 5

2

In 1994, the IAWQ thematic

For example, in order to understand the

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studied the

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environmental factors in sewer systems, the correlation between substrate transformation and

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microbial community distribution is unknown.

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The urban sewer is generally an anaerobic environment. Low dissolved oxygen (DO) could

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affect the distribution of microbial communities and then induce homologous substrate

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transformation. Liu et al 10 investigated differences in microbial community distribution under

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anaerobic conditions, between manholes and sewage pipes. Results showed that the dominant

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microbial communities were significantly correlated to certain crucial anaerobic

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environmental factors (i.e., CH4, sulfide). In addition, it is likely that changes in the content

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and composition of organics along the sewer would lead to changes in microbial communities,

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especially for fermentation bacteria (FB), hydrogen-producing acetogen (HPA) and

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methanogenic Archaea (MA). Therefore, in addition to the environmental effect on sewage

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quality, it is of particular significance to investigate the mechanism of how a variable

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environment influences microbial communities and what the correlation is between organics

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transformation and microbial community distribution. However, due to lack of relevant study,

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understanding remains poor regarding the distribution characteristics and diversity of

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microbial communities along the sewer system.

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To investigate these mechanisms, a pilot experimental system consisting of a 1200-m-long

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sewer was built. The variation of substrates and environment in the sewer was monitored and

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the variation of microbial communities along the sewer was analyzed by high-throughput

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sequencing and quantitative polymerase chain reaction (qPCR) technologies. Furthermore,

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based on the Spearman analysis, the co-variation between microbial community distribution

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and organic metabolization along the sewer was determined. In general, the sewage quality

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variation in sewer system resulted in the obvious differences between the design values of

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water quality and the actual influent quality in wastewater treatment plants. Therefore, this

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study provides a theoretical foundation for the understanding of wastewater quality variation

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during the transportation from sewer to treatment plant, and promotes information to optimize

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the operation of urban wastewater treatment plants.

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MATERIALS AND METHODS

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Experimental setup and raw water quality

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The pilot urban sewer system was constructed from 1200 m of 40-mm-diameter PVC pipe and

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consisted of a total of 35 layers from the bottom to the top. Each layer was approximately 35 m

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in length. The sewage in the pilot sewer system was gravity fed. The experiment was

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conducted at room temperature (25 ± 2 °C) in a controlled environment where dissolved oxygen

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(DO) was maintained at 0.3 ± 0.05 mg/L (under anaerobic conditions), which was similar to

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that of actual sewer networks in China. During system operation, the flow rate was controlled

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at 0.6 m/s. To avoid sedimentation in the pipe, the pipe slope and depth ratio of sewage was

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adjusted to 5‰ and 0.6, respectively. Detailed information was provided by Jin et al. 9 Every

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2-3 days during the pilot test, raw water was taken from a real sewer system in Xi’an, and the

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raw water quality (COD: 358±17 mg/L; BOD5: 260±10 mg/L; TN: 45±3 mg/L; NH3-N: 38±7

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mg/L; TP: 7.9±0.6 mg/L; pH: 7.3±0.2) was analysed. The data obtained from approximate

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120 samples were averaged.

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Sampling method

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For wastewater quality sampling and analysis, nine selected sampling points were located at 0,

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30, 100, 200, 400, 600, 800, 1000 and 1200 m from the inlet in the sewer system. Five

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replicates at each location were taken. For each sampling point, water quality analysis

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included COD (chemical oxygen demand), BOD5 (biochemical oxygen demand), NH3-N

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(ammonia nitrogen), TN (total nitrogen), and TP (total phosphorous) among others.

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For biofilm sampling, two slipknots, one at each end of the organic glass pipe in the sewer

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system were untied. Then, adhered biofilm was peeled off with sterile cotton swabs and

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carefully placed on disposable culture dishes. The samples were fully covered by dry ice

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during rapid transport to laboratory, and then stored at -40 °C. Due to the destructive nature of

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the sampling, the biofilm was only sampled for once.

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Analysis of methanol and ethanol

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The concentration of methanol and ethanol were measured by a gas chromatograph (GC-2014

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Shimadzu, Japan) equipped with a flame ionization detector (FID), CB-5 capillary column

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and AOC-5000 automatic headspace sampler. The oven was maintained at 50 °C for 5 min;

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heated to 100 °C at a rate of 5 °C/min and held for 2 min; and then heated to 200 °C at a rate

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of 5 °C/min. Sample injection occurred at 200 °C, and the detector was operated at 280 °C.

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Nitrogen was used as the carrier gas at a flow rate of 5.0 mL/min. The split ratio was 2:1. The

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headspace operating conditions were: 30 min with strong shaking for sample equilibration at

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80 °C with sampling probe held at 90 °C. The injection volume was 1.0 mL.

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Fluorescence excitation-emission matrix analysis

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A spectrofluorometer (FP-6500, Jasco, Japan) was used to analyze protein concentration in

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the treated samples. During measurements, the slit widths for excitation and emission were 5

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nm with a scanning speed of 2000 nm/min. The excitation wavelength ranged from 220 to

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480 nm with 2 nm intervals, and the emission wavelength ranged from 280 to 570 nm with 5

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nm intervals. The scanning of distilled water was used to eliminate water Raman scattering.

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Molecular weight distribution analysis of organic matter

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LC-2010AHF high-performance liquid chromatography (Shimadzu, Japan) with a Zenix

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SEC-100 7.8×300 mm gel column was used to determine the molecular weight. The

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wavelength of the ultraviolet detector was 254 nm. The mobile phase was a phosphate buffer

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solution with a pH of 7.0. The injection volume was 20 µL. The rate was set at 0.8 mL/min.

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Polystyrene sulfonic acid sodium salt was used as a standard.

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Analysis of pH, DO and ORP

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The pH, DO and ORP of the sewage were measured by a HQ30d meter (HACH. USA).

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The pH, DO and ORP of the biofilm were analyzed by microelectrodes (Unisense Denmark).

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The tip diameters of the DO, pH and ORP microelectrodes were 10 µm. During measurement,

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the ultrapure water, bubbled by N2, was used as the base fluid. Nylon nets immobilized the

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biofilm. The microelectrodes were controlled to penetrate the biofilm to analyze the

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micro-environment inside.

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Analysis of VFAs, CH4, formic acid and other wastewater parameters

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VFAs and CH4 were measured by gas chromatography and formic acid was measured by

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high-performance liquid chromatography. 9 The measurements of COD, NH3-N, NO3-TN and

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TP were processed according to the standard methods (State Environmental Protection

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Administration of China, 2002). Carbohydrates were measured by the anthrone method. 12

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Protein was measured by Lowry method. 11 All measurements were performed for 3 times for

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each sample.

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High-throughput sequencing

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Illumina Miseq sequencing and 454 pyrosequencing were performed to analyze the

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distribution of bacteria and Archaea in this study.

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by Shanghai Majorbio Bio-pharm Biotechnology Co. Ltd., Shanghai, China. The PCR

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reactions were performed three times for each sample and three parallel samples were

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sequenced in this study. In addition, the Spearman analysis was used in this study and the

13, 14, 15

Those sequencing were conducted

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correlation of microbes and environment (p-value) are represented by gradient colours from

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dark blue to dark red, and the significant positive or negative correlation in this analysis are

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represented by stars (inside the gridding). The NCBI accession number is SRP118971

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Quantitative polymerase chain reaction

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Quantitative polymerase chain reaction (qPCR) was performed using an Applied Biosystems

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7500 qPCR system (Applied Biosystems, Forster City, USA). To target the fermentation

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bacteria (FB), hydA-1290F (GGTGGAGTTATGGAAGCWGCHHT) and hydA-1538R

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(CATCCACCWGGRCAHGCCAT) were used as the forward and reverse primer respectively.

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16

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(ACGCAGACTCATCCCCGTG),

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(ACTGGTNTTCCTCCTGATTTGTA),

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(ACGCAGGCCCATCCCCGAA) were used. 17 To target the sulfate reducing bacteria (SRB),

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dsrA-290F

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(GTGGMGCCGTGCATGTT) were used as the forward and reverse primer respectively. 16 To

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target the denitrifying bacteria (DNB), nirK 876 (ATYGGCGGVCAYGGCGA) and nirK

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1040 (GCCTCGATCAGRTTRTGGTT) were used as the forward and reverse primer

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respectively.

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(TTCTATGGTTACGACTTVCAGGACCARTGYGG)

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(TTCATTGCRTAGTTWGGRTAGTT) were used as the forward and reverse primer

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respectively. 16 The analysis of blind samples was repeated 3 times. The 20 µL qPCR reaction

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mixture was prepared in triplicate using 6.8 µL of PCR-grade water, 10 µL TaKaRa SYBR®

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Premix Ex TaqTM (TaKaRa BIO INC. Japan), 0.4 µL of each primer, 0.4 µL of 50 × ROX

To target hydrogen-producing acetogen (HPA), probes of S-S-S.wol-0223-a-R-19 S-F-Synm-0700-a-R-23 S-S-MPOB-0222-a-R-19

(CGGCGTTGCGCATTTYCAYACVVT)

18

To

target

the

methanogenic

and

archaea

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(MA),

RH3-dsr-R'

mcrA-1430F mcrA-1530R

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reference dye, 20 ng of template DNA. The thermal cycler protocol was as follows: initial

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step for 10 s at 95°C followed by 40 cycles of 95 °C for 5 s, then maintained 56 °C for 10 s,

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finally maintained 72 °C for 27 s. The qPCR was tested for three times. The qPCR was

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conducted by the fluorochrome detection in PCR amplification production which differed

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with different sequencing methods (high throughput and high sequence depth), therefore,

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some results might not be identical.

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Functional microbial community classification standard

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To investigate bioreactions occurring in sewer system, the microbial communities (determined

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by sequencing results) were classified as fermentation bacteria (FB), hydrogen-producing

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acetogen (HPA), sulfate reducing bacteria (SRB), denitrifying bacteria (DNB), and other

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bacteria (OB). According to the three steps theory of anaerobic fermentation, 19 the microbial

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communities participating in the first step were represented by hydrolytic and fermentative

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communities. In this step, the microbial communities decomposed the macromolecular

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organic matters into micromolecular compounds (such as volatile fatty acids, alcohol among

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others), therefore these kinds of microbial communities were classified as fermentation

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bacteria (FB). 20, 21 In the second step, hydrogen-producing and acetate-producing bacteria

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would consume the substrates produced in the first step and produce hydrogen and acetate,

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which could be available to methanogens for methane formation. Therefore, this type of

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bacteria was classified as hydrogen-producing acetogen (HPA). 22, 23 Sulfate-reducing bacteria

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(SRB) obtain energy by oxidizing macromolecular organic compounds or molecular hydrogen

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(H2) while reducing sulfate (SO42−) to hydrogen sulfide (H2S). 24 Denitrifying bacteria (DNB)

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are capable of performing denitrification as part of the nitrogen cycle. This kind of bacteria

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metabolizes nitrogenous compounds using the enzyme nitrate reductase, turning nitrogen

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oxides back to nitrogen gas or nitrous oxide.

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bacteria were classified as OB.

25, 26

Except for FB, HPA, DNB and SRB, other

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RESULTS AND DISCUSSION

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Analysis of the biodiversity and wastewater quality in the sewer system

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The Shannon index decreased from the start to the rear along the sewer system. The Shannon

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index was 4.53-4.79 from 30 to 600 m along the sewer system; however, it decreased to 4

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toward the end of the sewer from 800-1200 m. The reduction of the Shannon index showed

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that the biodiversity changed along the sewer. 30m

Firmicutes 15.61%

Bacteroidetes 28.91%

Proteobacteria 50.94%

200m Bacteroidetes 25.54%

Firmicutes .17.56%

Proteobacteria 45.37%

600m

Firmicutes 18.95%

Bacteroidetes 27.71% Proteobacteria 33.09%

Bacteroidetes 10.06%

1000m

Proteobacteria 71.74%

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Firmicutes 1.15%

100m

Proteobacteria Bacteroidetes Bacteroidetes 25.38% Firmicutes Chlorobi Chloroflexi Spirochaetae Candidate_division_TM7 Acidobacteria Bacteria_unclassified Proteobacteria Fusobacteria 44.11% Verrucomicrobia Cyanobacteria Synergistetes Actinobacteria Candidate_division_WS6 Others Proteobacteria Bacteroidetes Firmicutes Chlorobi Chloroflexi Spirochaetae Candidate_division_TM7 Acidobacteria Bacteria_unclassified Fusobacteria Verrucomicrobia Cyanobacteria Synergistetes Actinobacteria Candidate_division_WS6 Others Proteobacteria Bacteroidetes Firmicutes Chlorobi Chloroflexi Spirochaetae Candidate_division_TM7 Acidobacteria Bacteria_unclassified Fusobacteria Verrucomicrobia Cyanobacteria Synergistetes Actinobacteria Candidate_division_WS6 Others Proteobacteria Bacteroidetes Firmicutes Chlorobi Chloroflexi Spirochaetae Candidate_division_TM7 Acidobacteria Bacteria_unclassified Fusobacteria Verrucomicrobia Cyanobacteria Synergistetes Actinobacteria Candidate_division_WS6 Others

400m

Firmicutes 17.40%

Firmicutes 12.18%

Bacteroidetes 25.16%

Proteobacteria 44.82%

Bacteroidetes 9.89%

800m

Firmicutes 2.44%

Proteobacteria 83.20%

Bacteroidetes 9.94%

1200m

Proteobacteria 72.01%

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Firmicutes 0.35%

Proteobacteria Bacteroidetes Firmicutes Chlorobi Chloroflexi Spirochaetae Candidate_division_TM7 Acidobacteria Bacteria_unclassified Fusobacteria Verrucomicrobia Cyanobacteria Synergistetes Actinobacteria Candidate_division_WS6 Others Proteobacteria Bacteroidetes Firmicutes Chlorobi Chloroflexi Spirochaetae Candidate_division_TM7 Acidobacteria Bacteria_unclassified Fusobacteria Verrucomicrobia Cyanobacteria Synergistetes Actinobacteria Candidate_division_WS6 Others Proteobacteria Bacteroidetes Firmicutes Chlorobi Chloroflexi Spirochaetae Candidate_division_TM7 Acidobacteria Bacteria_unclassified Fusobacteria Verrucomicrobia Cyanobacteria Synergistetes Actinobacteria Candidate_division_WS6 Others Proteobacteria Bacteroidetes Firmicutes Chlorobi Chloroflexi Spirochaetae Candidate_division_TM7 Acidobacteria Bacteria_unclassified Fusobacteria Verrucomicrobia Cyanobacteria Synergistetes Actinobacteria Candidate_division_WS6 Others

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Fig. 1 Relative abundance of microbial communities at the phylum level along the sewer

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(Others in each plot represented the unidentified bacteria)

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As shown in Fig. 1, the relative abundance of Proteobacteria was 30.08-50.94% within the

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beginning 30-600 m of the sewer, however, from 600 to 800 m, Proteobacteria became

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dominant with a relative abundance of 71.7-83.2%. In contrast, in the first 600 m of the sewer,

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the relative abundance of Bacteroidetes was 25.2-28.9%, and, rapidly decreased to

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approximately 10% at 800-1200 m. Moreover, within 30-600 m, the relative abundance of

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Fimicutes was 12.2-18.9%, however, it dramatically decreased to less than 2.5% at 800-1200

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m.

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In fact, Firmicutes, Bacteroidetes and Proteobacteria contain the fermentative genera which

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contribute to the fermentation processes in the anaerobic digestion system. 27 Moreover, the

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environmental conditions of the sewer system are dark and anaerobic, similar to anaerobic

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digestion systems, indicating that fermentation might occur in a sewer system. In general,

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hydrolysis and acidification are components of fermentation process. During hydrolysis,

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refractory organic matter is decomposed into degradable compounds, and macromolecular

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organic matter is decomposed into small molecules. On the other hand, acidification produces

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acid and gases. Kang et al

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and acidification during sludge fermentation, suggesting that the competitive capacity of

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Proteobacteria could be stronger at the end of the sewer, where acidification might be the

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primary process (accumulation of small-molecule organic matters as shown in supporting Fig.

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3). It has been reported that Bacteroidetes and Firmicutes could hydrolyze protein and

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carbohydrates.

29, 30

28

found that Proteobacteria was the major phylum in hydrolysis

As the content of macromolecular organic compounds (molecular

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weight > 10000 Dalton and within 650-10000 Dalton) decreased along the sewer (Supporting

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Fig. 3), and the relative abundance of Bacteroidetes and Firmicutes similarly decreased, it can

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be inferred that the local environment became disadvantageous for Bacteroidetes and

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Firmicutes due to lack of metabolizable substrates.

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To study the effect of sewer length on the microbial community (bacteria and Archaea)

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distribution, the beta-diversity as principal component analysis (PCA) plots were produced

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(Supporting Fig. 1), and the microbial communities in each biofilm sample were represented

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as colored points. The results showed that significant separation of bacteria occurred in the

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samples from 0-200 m, 400-600 m and 800-1200 m (Supporting Fig. 1(a)). It indicated that

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due to the variation of environmental factors along the sewer, the diversity (Beta) of bacteria

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was affected along the range of 400-600 m (diversity changed significantly in the beginning

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of the sewer). The separation groups of Archaea were found in the samples from 0-400 m,

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600-800 m and 1000-1200 m (Supporting Fig. 1(b)). The results indicated that the diversity

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(Beta) of Archaea could be affected in the range of 600-800 m of sewer. The PCA analysis

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was in accordance with the results shown in Fig. 1. The analysis of microbial community

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diversity and structures at the phylum level along the length of sewer could provide a

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profound understanding on microenvironments and the investigation of the diverse

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metabolism occurring in sewer system.

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Distribution characteristics of functional microbial communities in the sewer system

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Concentration of 16S rRNA gene copy (copied/ml)

1.00E+13

1.00E+11

1.00E+09

30m

100m

200m

400m

600m

800m

1000m

1200m

1.00E+07

1.00E+05

1.00E+03 FB

HPA

SRB

DNB

Funtional microbial communities

291

(a)

292 6.00E+03

1.60E+04

DNB DNB SRB

1.20E+04 OHB OB

DNB DNB SRB HPA

32.5% 31.6% 31.6%

Reads

Relative Abundance

4.00E+03

Reads

38.3%

5.00E+03

OHB OB

DNB DNB

OHB OB

OHB OB

OB OHB

OHB OB

OHB OB

DNB 4.00E+03

SRB

SRB

HPA

HPA

0.00E+00 30

3.00E+03

DNB DNB

29.7%

21.1% 2.00E+03 17.4%

OB OHB

8.00E+03

400

600

DNB DNB HPA

FB FB

200

800

1000

1200

Length of the sewer system (m)

SRB SRB

HPA

FB

100

DNB DNB

SRB

FB

HPA FB

FB

1.00E+03

DNB

5.8%

SRB FB

HPA FB

0.00E+00 30

OB OHB OHB

293 294

` Desulfonema Enterobacter Lactococcus

100

200

Thauera Desulfovibrio Paludibacter Tolumonas

400

600

800

1000

Length of the sewer system (m) Alicycliphilus Dechloromonas Anaerolinea Veillonella Flavobacterium Aeromonas Lactobacillus Cloacibacterium

1200

Desulfobulbus Anaeroarcus Raoultella Trichococcus

(b)

295

Fig. 2 Variation of fermentation bacteria (FB), hydrogen-producing acetogen (HPA), sulfate

296

reducing bacteria (SRB), denitrifying bacteria (DNB), and other bacteria (OB) along the

297

sewer (a) 16S rRNA gene copy concentration of functional microbial communities (detected

298

by qPCR); (b) relative abundance of functional microbial communities (detected by

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sequencing ). (The data and detailed classification of each functional microbial community

300

was shown in Supporting Table 1 and Table 2)

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Because pyrosequencing only provided information on the relative abundance of microbial

302

communities rather than the absolute quantity variation, quantitative polymerase chain

303

reaction (qPCR) and pyrosequencing were used together to investigate the distribution

304

characteristics of functional microbial communities along the sewer. The variation of the 16S

305

rRNA gene copy concentration and the relative abundance at the genus level are shown in Fig.

306

2. It was observed that the functional microbes in the sewer were mainly comprised of

307

fermentation bacteria (FB), hydrogen-producing acetogen (HPA), sulfate reducing bacteria

308

(SRB) and denitrifying bacteria (DNB).

309

As shown in Fig. 2 (a), the 16S rRNA gene copy concentration of FB continuously increased

310

along the 0-600 m range of the sewer and reached the maximum at 600 m (2.39E+12

311

copied/ml). It then began to decrease significantly from 600 m to 1200 m. These results

312

indicated that: within 600-1200 m of the sewer, some communities of FB declined in

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population, and the microbial community structures and biometabolism processes might be

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altered in this region. To understand this phenomenon, pyrosequencing was utilized to reveal

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the variation of microbial community structures and then infer the bioreactions that occurred

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in the sewer system. In the first 30 m of the sewer system, Trichococcus and Cloacibacterium

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were the dominant genera. As the distance increased, Cloacibacterium was gradually

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eliminated. Previous studies indicated that Trichococcus could adapt to the environment

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where hydrolysis substrates, (especially macromolecular organic compounds) were rich. 31

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Therefore, along the sewer from 0 to 400 m, due to the high content and complicated

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composition of macromolecular organic compounds (Supporting Fig. 3), the environment

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might be more suitable for the growth of Trichococcus (which displayed high relative

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abundance in this region). From 600 to 800 m, the relative abundance of Trichococcus

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decreased dramatically, indicating that Trichococcus might no longer adapt to the changing

325

environment. This result was highly consistent with the qPCR data which indicated that the

326

16S rRNA gene copy concentration of FB decreased significantly after 600 m. Moreover, it

327

also indicated that the change of FB concentration was mainly due to the elimination of

328

Trichococcus. However, the relative abundance of Flavobacterium significantly increased,

329

making it the dominant genus in this region. This might be resulted from the accumulation of

330

micromolecule compounds as substrates for its reproduction (Supporting Fig. 3). After 800 m,

331

as the substrates were gradually consumed, the relative abundance of Flavobacterium and the

332

16S rRNA gene copy concentration of FB continuously decreased along the sewer, indicating

333

that the substrates were more readily utilized by other genera at the end of the sewer. Hence,

334

these results indicated that the distribution characteristics of FB featured the dominant genus

335

changing from Trichococcus to Flavobacterium within 600-800 m of the sewer system.

336

HPA mainly consumed hydrolysate for final acidification. The 16S rRNA gene copy

337

concentration of HPA remained low in the beginning of sewer, with no accumulation of

338

(hydrolytic products), and then it increased dramatically after 100 m as hydrolysis improved

339

along the sewer (Fig. 2 (a)). Moreover, the distribution characteristics of HPA changed in the

340

sewer, i.e., the dominant HPA genus changed from Veillonella to Anaerolinea within the

341

600-800 m region. Therefore, the variation of the HPA structure also caused the decline of

342

HPA concentration after 600 m (Fig. 2 (a)). Previous studies have showed that Veillonella and

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32, 33

343

Anaerolinea prefer to utilize lactic acid and small-molecule fatty acids respectively.

344

Therefore, the accumulation of lactic acid at the beginning of the sewer (supporting Fig. 5)

345

might be the reason for the high relative abundance of Veillonella. When the content of lactic

346

acid decreased near the end of the sewer, the reproduction of Veillonella was limited while

347

Anaerolinea became dominant perhaps due to the stable concentration of small-molecule fatty

348

acids (VFA).

349

As shown in Fig. 2(b), the relative abundance of Desulfovibrio was higher than that of other

350

SRB genera at 30 m. Previous reports indicated that Desulfovibrio preferred to utilize

351

methanol and lactic acid as carbon source. 34 From 100 to 400 m, the relative abundance of

352

Desulfovibrio decreased gradually, while Desulfonema became the dominant genus, which

353

might be due to the accumulation of isobutyric acid, the preferable carbon source for

354

Desulfonema, in this region (supporting Fig. 5). 35 However, due to the low content of SO42-,

355

the relative abundance of all SRB genera decreased beyond 600 m in the sewer, suggesting

356

that the sulfate reduction process had gradually declined. This was also verified by the qPCR

357

data that showed that the 16S rRNA gene copy concentration of SRB decreased after 600 m.

358

These results suggest that the distribution characteristics of SRB changed along the sewer

359

with the dominant genus changing from Desulfovibrio to Desulfonema.

360

Due to the anaerobic environment in sewer systems, nitrification was inhibited. Therefore, the

361

content of NO3- was extremely low (Supporting Fig. 4). Previous study has shown that

362

Dechloromonas and Alicycliphilus can reduce NO3-, 36 however, due to the low content of

363

NO3- in the sewer, the metabolism of these two dominant DNB genera might be weakened.

364

Moreover, the total concentration of DNB was also low in the sewer.

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365

Except for microbial genera discussed above, all other genera could be regarded as a whole

366

microbial community, namely, other bacteria (OB). The relative abundance of OB varied from

367

60% to 95% along the sewer system, suggesting that the competition capacity of functional

368

bacteria mentioned above were gradually weaker than OB, and the OB were the most

369

dominant microbial communities at the end of sewer. Concentration of 16S rRNA gene copy (copied/ml)

1.00E+11

1.00E+09

1.00E+07

1.00E+05

1.00E+03

100m

200m

400m

600m

800m

1000m

1200m

1000

1200

Lenth of the sewer system (m)

370 1.20E+04

100 %

Reads Relative Abundance

1.00E+04

75 %

8.00E+03

6.00E+03 50 % 4.00E+03

25 % 2.00E+03

0.00E+00 0% 100

371 372

200

400 600 800 Length of the sewer system (m)

Others

Methanosaeta

Archaea

Methanobacterium

Methanospirillum

Methanosarcinaceae

Methanobacteriaceae

Euryarchaeota

Methanosarcina

Fig. 3 Variation of methanogenic Archaea (MA) along the sewer (a) 16S rRNA gene copy

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373

concentration of MA (detected by qPCR); (b) relative abundance of MA ((detected by

374

sequencing)

375

The production of methane in the sewer system indicated the existence of methanogenic

376

Archaea (MA). Most likely due to lack of metabolizable substrates available to MA at the

377

beginning of the sewer, MA was not found at the 30 m location (verified by both qPCR and

378

pyrosequencing detection as shown in Fig. 3). The 16S rRNA gene copy concentration of MA

379

increased from 100 m to 1000 m of the sewer, which indicated that methanogenesis could be

380

gradually enhanced along the sewer. To acquire the specific information on methanogenesis,

381

the MA taxa were identified. The dominant MA genera were Methanosarcina, Euryarchaeota

382

and Methanobacteriaceae, among which a transition from Methanosarcina to Euryarchaeota

383

was clearly observed. It was reported that Methanosarcina was able to use aceticlastic and

384

hydrogenotrophic pathways, as they are more adaptable to changes in nutritional conditions. 37

385

The relative abundance of Methanosarcina continuously increased from 100 to 800 m, and

386

exceeded that of Euryarchaeota at 200 m while the relative abundance of Euryarchaeota

387

decreased continously along the sewer. This indicates that Methanosarcina adapted to grow in

388

the environment where the substrates were rich in complex substrate conditions from 100 to

389

600 m. However, after 800 m, the relative abundance of Methanosarcina decreased while that

390

of Euryarchaeota increased along 800-1200 m. This suggested that the substrate conditions

391

from 800 to 1200 m were more suitable for the growth of Euryarchaeota. Based on the

392

analysis of the functional microbial communities distribution along the sewer discussed above,

393

the metabolism can be inferred. The metabolism occurring in sewer would be affected by

394

environmental factors, and therefore cause the substrate transformation. Therefore, the

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395

variation of nutrient substrate and environmental conditions along the sewer were further

396

studied

397

The variation of nutrient substrate and environmental conditions along the sewer protein

tryptophan-like 类色氨酸

类腐殖质 humic-like 类腐殖质

>10000Da

800

200

600

150

400

100

200

50

0 0

200

400 600 800 Lenth of the sewer system (m)

1000

650 Dalton) continuously declined while the small-molecule

416

organics (< 650 Dalton) rose constantly. This indicated that the macromolecular organic

417

compounds were continuously decomposed to small-molecule organics in the 800-1200 m

418

region, which might retard hydrolysis and facilitate acidification. Thus, the environment

419

might be more suitable for the growth of Flavobacterium (FB), Anaerolinea (HPA),

420

Desulfonema (SRB), and Euryarchaeota (MA) near the end of sewer due to the enhancement

421

of acidification. pH of sewage

pH of biofilm

DO of sewage

DO of biofilm

200 15

400 30

600 45

800 60

1000 75

1

7

0.8

6

0.6

pH

8

5

0.4

4

0.2

3

0 0

200

400

600

800

1000

422

Length of the sewer system (m)

423

(a)

1200

ORP of biofilm

Passing time (min)

0 1200 90

00

200 15

400 30

600 45

800 60

1000 75

1200 90

0

200

400

600

800

1000

1200

300 200 100

ORP (mV)

0

Concentration of DO (O2mg/L)

Passing time (min)

3.2

ORP of sewage

0 -100 -200 -300 -400 0

-500 Length of the sewer system (m)

(b)

424

Fig. 5 Variation of pH, DO and ORP along the sewer system (measured five times)

425

To further study the influence of environmental condition on microbial communities in the

426

sewer, pH, DO, and ORP of the sewage and biofilm were measured. As shown in Fig. 5 (a),

427

the concentration of DO in the sewage and biofilm decreased gradually along the sewer from

428

0.5 mgO2/L to 0.19 mgO2/L, and from 0.38 mgO2/L to 0.16 mgO2/L, respectively, while the

429

pH values of the sewage and biofilm both remained stable (6.0-7.0). Therefore, the sewer was

430

anaerobic. Moreover, the anaerobic conditions in both sewage and biofilm became more

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431

pronounced along the sewer. Fig. 5 (b) presents the change of ORP in sewage and biofilm.

432

The ORP of sewage decreased from 175 mV to -70 mV along the sewer. In the first 600 m,

433

the ORP of the biofilm decreased steadily along the sewer, however, it decreased rapidly from

434

-200 to -306 mV between 600 and 800 m. The rate of decrease slowed at the end of the sewer.

435

The ORP variation in the biofilm affected biochemical reactions and therefore could influence

436

the change of substrates in the sewer. As shown in Fig. 5 (b), the ORP of biofilm ranged from

437

-100 to -200 mV between 30 and 600 m in the sewer. As reported previously, the optimal ORP

438

ranges for acidogenic fermentation and sulfate reduction are from -100 to -225 mV and from

439

-50 to -250 mV, respectively 38. Therefore, it can be inferred that acidogenic fermentation and

440

sulfate reduction mainly occurred along the 30-600 m segment the sewer system. This result

441

was verified by the distribution of acidogenic fermentation microflora (i.e., high relative

442

abundance of FB and HPA) in the beginning of sewer (Fig. 2). In contrast, despite of the

443

favorable ORP condition for SRB reproduction, the relative abundance of SRB remained low

444

probably due to the low content of SO42- (less than 50 mg/L along the sewer, Supporting Fig.

445

4). From 800 to 1000 m, the ORP of biofilm ranged from -300 to -350 mV, therefore,

446

acidogenic fermentation and sulfate reduction was reduced and the relative abundance of the

447

corresponding functional microbes was lower than that in the 0-600 m segment. Moreover,

448

the suitable ORP for denitrification ranged from 50 to -50 mV 38, therefore, along the entire

449

sewer the relative abundance of DNB genera was lower than that of other functional microbes.

450

In addition, the optimal range of ORP for the methane production is between -175 to -400 mV,

451

38

452

production. As shown in Fig. 4, from 100 to 800 m, the relative abundance of Methanosarcina

thus the ORP condition along the majority part of the sewer was beneficial to methane

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453

was the highest among MA with ORP between -147 and -306 mV, suggesting that the ORP

454

condition was highly suitable for Methanosarcina growth. When ORP decreased to -356 mV,

455

the relative abundance of Euryarchaeota was the highest among the MA, indicating that the

456

ORP condition was more beneficial for the growth of Euryarchaeota.

457

Within 0-200 m of the sewer, fermentation products continuously increased, including lactic

458

acid, acetic acid, propionic acid and isobutyric acid, of which lactic acid and acetic acid are

459

the dominant products and contribute to the highest ratio (Supporting Fig. 5). The content of

460

lactic acid reached its maximum value of 7.89 mg/L at 200 m. In the 200-600 m segment of

461

the sewer, lactic acid and ethanol concentration was reduced while the content of propionic

462

acid and isobutyric acid increased continuously. At the 600 m location, the content of acetic

463

acid, propionic acid and isobutyric acid increased to 8.67 mg/L, 3.5 mg/L and 2.5 mg/L,

464

respectively, and it was corresponded with the analysis of molecular weight that demonstrated

465

that the macromolecular organic compounds were gradually decomposed to small-molecule

466

organic compounds along the sewer systems.

467

The

468

communities

co-variation

DO

between

pH

environmental

Ethanol

condition,

Lactic acid Formic acid Acetic acid Propionic acid

FB

SRB HPA DNB 469

substrate

Archaea

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470

Fig. 6 Correlations between microbiota abundances and environment conditions (based on

471

Spearman' s correlation between the relative abundance of significantly functional microbes

472

and the environment condition in the sewer. The color and the stars of each stripe indicate

473

magnitude of correlation, with p-values superimposed on stripe (One star represents p<0.05,

474

and two stars represent p<0.01); Subject groups were divided in FB, SRB, HPA, DNB and

475

Archaea; the alpha values and water quality along the sewer are shown in supporting Table 5,

476

Table 6)

477

To assess the correlation between sewage quality variables and microbial communities on

478

bioflims in the sewer, the Spearman analysis was conducted to visualize the correlation

479

between functional microorganism and environmental factors. As shown in Fig. 6, FB

480

exhibited a significantly positive correlation (red cell with stars) with macromolecular

481

organics, especially ethanol and lactic acid, therefore the levels of DO and pH in sewer could

482

remarkably affect the metabolism of FB. These results were highly consistent with the

483

previous discussion that FB became the dominant microflora as a result of the abundant

484

macromolecular organics available as substrate in the beginning of sewer system while the

485

relative abundance of FB gradually decreased along the sewer. Nevertheless, it should be

486

noted that Flavobacterium (FB) showed positive correlation with small-molecule organics

487

(acetic acid and propionic acid), and the bacteria could survived in the sewer despite

488

variations in DO and pH. Therefore, FB could still be detected at the end of sewer even

489

though their relative abundance was quite low. HPA and SRB exhibited a positive correlation

490

with lactic acid (red cell), therefore, abundant lactic acid at the beginning of the sewer enabled

491

HPA and SRB to be more competitive and display greater relative abundance. The utilization

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492

of lactic acid as a carbon source by Veillonella (the dominant genus of HPA) and

493

Desulfovibrio (the dominant genus of SRB) led to the continuous decrease of lactic acid. Thus,

494

beyond 600 m, due to the lower content of lactic acid, the distribution characteristics of HPA

495

changed. Meanwhile, due to lack of SO42-, the relative abundance of SRB decreased within

496

800-1200 m. DNB (Alicycliphilus and Thauera) exhibited significantly negative correlation

497

with carbon availability (blue cell with stars) although Dechloromonas could use carbon for

498

denitrification. This is due to the extremely low content of NO3- was in sewer. A complex

499

substrate composition for MA was observed, which included methanol, lactic acid, formic

500

acid and propionic acid. The relative abundance of Methanosarcina was higher before 800 m.

501

However, beyond 800 m, acetic acid contributed nearly all of the substrate for MA and the

502

relative abundance of Euryarchaeota became the highest among the MA. Thus, it can be

503

inferred that Methanosarcina could adapt to the complex substrate conditions while

504

Euryarchaeota tended to prefer acetic acid as a substrate.

505

In conclusion, this study revealed the distribution characteristics of different functional

506

microbial communities (FB, HPA, SRB, DNB, MA). Due to the variation of ORP, DO and pH,

507

the dominant bioreaction changed from fermentation to methane production along the sewer.

508

These results indicated that different environmental factors could affect the distribution of

509

functional microbial community, and the change of dominant FB, HPA, SRB, DNB and MA

510

genera along the sewer could induce homologous transformation of organics. The distribution

511

of microbial communities and organic metabolism are inseparably connected along sewer

512

systems. This study could provide a theoretical foundation for an understanding of wastewater

513

quality variation along sewer transport systems. Thus, these results could help to predict the

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514

actual influent quality of wastewater treatment plants, and promote optimization of wastewater

515

treatment.

516

AUTHOR INFORMATION

517

Corresponding Author

518

Pengkang Jin, Phone: +86 13379217572; E-mail: [email protected]

519

Author Contributions

520

The manuscript was written by contributions of all authors. All authors have approved the

521

final version of the manuscript.

522

Notes

523

The authors declare no competing financial interest.

524

ACKNOWLEDGEMENTS

525

This study was supported by the National Key Project of Water Pollution Control and

526

Management (No. 2012ZX07313001), Shaanxi Science & Technology Co-ordination &

527

Innovation Project (2016TZC-S-19-3), and the Program for Innovative Research Team in

528

Shaanxi Province (PIRT) (No. 2013KCT-13).

529

SUPPORTING INFORMATION AVAILABLE

530

Including the relative abundance of functional microbial community; the variation of substrate

531

concentrations; the variation of environmental factors along the sewer. This information is

532

available free of charge via the Internet at http://pubs.acs.org.

533

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(38) Gerardi, M, H. ORP management in wastewater as an indicator of process efficiency. YSI, Yellow Springs, OH. 2007.

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Graphical abstract Relative abundance of bacteria Biofilms on the inner pipe surface

100m

Firmicutes 17.40%

600m

Bacteroidetes 25.38%

Firmicutes 18.95%

Bacteroidetes 27.71% Proteobacteria 33.09%

Proteobacteria 44.11% Bacteroidetes 9.94%

1200m

Firm icutes 0.35%

Proteobacteria 72.01%

Variation of sewage quality along the sewer system

Proteobacteria Bacteroidetes Firmicutes Chlorobi Chloroflexi Spirochaetae Candidate_division_TM7 Others

Variation of biodegradable intermediates along the sewer system

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