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Stratification of extracellular polymeric substances (EPS) for aggregated anammox microorganisms Fangxu Jia, Qing Yang, Xiuhong Liu, Xiyao Li, Baikun Li, Liang Zhang, and Yongzhen Peng Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b05761 • Publication Date (Web): 27 Feb 2017 Downloaded from http://pubs.acs.org on February 27, 2017
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Stratification of extracellular polymeric substances (EPS) for
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aggregated anammox microorganisms
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Fangxu Jia 1, Qing Yang 1,*, Xiuhong Liu 2, Xiyao Li 1, Baikun Li 1, Liang Zhang 1, Yongzhen Peng
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1,*
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1
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Technology, Engineering Research Center of Beijing ,Key Laboratory of Beijing for Water Quality
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Science and Water Environment Recovery Engineering, Beijing University of Technology, Beijing
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100124, PR China
National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse
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2
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China
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*Corresponding Author.
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School of Environment & Natural Resources, Renmin University of China, Beijing 100872, PR
E-mail:
[email protected] Tel: 86-10-67392627 Fax: 86-10-67392627
E-mail:
[email protected] Tel: 86-10-67392627 Fax: 86-10-67392627
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ABSTRACT: Sludge aggregation and biofilm formation are the most effective approaches to
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solve the washout of anammox microorganisms. In this study, the structure and composition of
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EPS (extracellular polymeric substances) were investigated to elucidate the factors for the
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anammox aggregation property. Anammox sludge taken from 18 lab-scale and pilot-scale
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reactors treating different types of wastewater was analyzed using EEM-PARAFAC (excitation-
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emission matrix and parallel factor analysis), FTIR (fourier transform infrared spectroscopy)
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and real-time PCR combined with multivariate statistical analysis. The results showed that
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slime and TB-EPS (tightly bound EPS) were closely related with water quality and sludge
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morphology, and could be used as the indicators for anammox microbial survival ability and
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microbial aggregate morphology. Furthermore, slime secreted from anammox bacterial cells
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may be exhibited higher viscosity to the sludge surface and easily formed the gel network to
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aggregate. Large amounts of hydrophobic groups of protein in TB-EPS promoted the microbial
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aggregation. The mechanisms of anammox aggregation explored in this study enhanced the
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understanding of anammox stability in wastewater treatment processes.
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Keywords: Anammox, Extracellular polymeric substances (EPS), Aggregation behavior, Uronic
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acids, β-sheet.
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Table of Contents
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Introduction
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Application of anammox in wastewater treatment plants has been extensively studied, due to
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its high efficiency, no need of oxygen and additional carbon source and low sludge output 1.
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However, the anammox bacteria have slow growth rate with doubling time of two weeks 2, which
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hinders the adoption of this technology. Maintaining high biomass concentrations and preventing
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the loss of anammox biomass is critical for this process. To date, the most feasible and effective
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method to improve the bacterial accommodation capacity are granulation, biofilm formation and
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immobilized biomass 3.
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EPS (extracellular polymeric substances) plays a crucial role in sludge granulation and biofilm
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formation as well as the maintenance of the structural integrity 4. Their physicochemical properties
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and spatial distribution structure can dramatically affect the structure and function of microbial
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aggregate. For example, proteins, humic acids and uronic acids in EPS contributed to the
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hydrophobicity of activated sludge while carbohydrates contributed to the hydrophilic nature 5. The
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β-polysaccharides forms the outer layer to support the mechanical stability of aerobic granules 6.
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Certain protein secondary structures promoted bioflocculation aggregation, adsorption and biofilm
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formation 7, 8. Although EPS in activated sludge and biofilms have been extensively studied, the key
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mechanism of aggregation ability of anammox microorganisms remains unknown. Since the unique
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properties of anammox sludge including density dependent 9, high aggregation ability
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aggregation morphology of broccoli shape 10, strong tendency to form granules 11, 12 and the ability
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to secrete large amounts of EPS 13, the EPS of anammox sludge is different from that in conventional
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activated sludge. Therefore, a new approach to elucidate EPS production in anammox sludge should
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be explored. 4
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To date, only a few studies have focused on EPS in anammox-dominated mixed culture, and 13, 14.
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mainly limited to the content of protein and polysaccharides using colorimetric method
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Meanwhile, many factors including different treatment processes, operational conditions and water
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quality
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previous studies only compared one anammox sludge sample with that of nitrifying sludge or
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denitrifying sludge sample
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anammox cannot suitable for other anammox processes. In addition, EPS had different stratified
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structure in sludge and each fraction possesses different physicochemical characteristics of organic
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matters16, such as slime layers markedly impeded the sludge dewaterability16, LB-EPS (loosely
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bound EPS) might inhibit bioflocculation, sedimentation and sludge dewatering17, and cause the
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irreversible fouling in membrane bioreactors18. On the other hand, TB-EPS (tightly bound EPS) had
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the gel-like characteristics and strong elasticity and might benefit flocculation16, 19, 20. Furthermore,
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since anammox bacteria have not been cultivated as a pure culture 9, it is so significant to determine
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the origin of EPS from different microbes in anammox-dominated mixed culture. Therefore, to
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elucidate the effect of EPS on anammox microbial aggregation, the structure and composition of
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stratified EPS should be investigated at the microscopic level.
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influenced the properties of EPS (fractions, structure, composition, etc.), whereas the
7, 10.
Therefore, these obtained results related to the aggregation of
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The objective of the study was to elucidate the relationship between the properties of stratified
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EPS (fractions, structure, composition, etc.) and the properties of anammox biomass (macro-
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structure, activity, microbial composition, etc.) by studying a variety of anammox-dominated
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biomass samples collected from lab-scale and pilot-scale systems using multivariate statistical
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analysis (principal component analysis and Pearson correlation analysis). This study devote to
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explore the critical factors for anammox microbes aggregation, which provide a reference to 5
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enhance the understanding of anammox stability in wastewater treatment processes.
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Materials and methods
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Sludge samples
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Anammox sludge samples were collected from 18 different lab-scale and pilot-scale reactors,
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which treated wastewater from synthetic wastewater, domestic sewage, landfill leachate and reject
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water and possess different sludge morphology (flocs, biofilm and granules). The characteristics of
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these sludge samples were shown in Supplementary Table S1. The collected samples were stored at
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4℃ immediately after sampling for further analysis.
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Bacterial activity test
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To elucidate the activities of ammonium oxidizing bacteria (AOB), nitrite oxidizing bacteria
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(NOB) and anammox bacteria, a series of batch experiments were carried out. The sludge samples
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were washed three times by oxygen-free water to avoid the oxygen inhibition, and then injected into
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a 500 ml flask to measure AOB, NOB and anammox activity. The initial pH was 7.5 and temperature
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was maintained at 35 ±1 ℃. Initial concentration of ammonia and nitrite was 30 mg/L for anammox
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bacteria. As for AOB and NOB, ammonia and nitrite was respectively added to 30 mg/L and the
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average DO was maintained at 3.0 ±0.5 mg/L.
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EPS extraction protocol
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The slime and LB-EPS extraction protocol was modified according to the research of Yu et
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al.16. In brief, 40 ml of sludge sample was placed in a 50 ml centrifuge tube and centrifuged at 2000 6
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g for 15 min, then the bulk solution was collected as slime. The bottom sediments were collected
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and resuspended to their original volumes with PBS. After that, the suspensions were centrifuged at
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5000 g for 15 min and the bulk solution was collected as LB-EPS. The TB-EPS extraction protocol
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was according to our previous work
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resuspended to original volumes with PBS. The ultrasonic method was employed to extract the TB-
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EPS from resuspended sediments at 20 kHz and 5.59 W/ml for 1 min. The extracted solutions were
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centrifuged at 20,000g for 20 min. Organic matter in the bulk solution was comprised of the TB-
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EPS. Polytetrafluoroethylene membranes with a pore size of 0.45 μm were used to remove the
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particulates present in the slime, LB-EPS and TB-EPS solutions.
21.
Briefly, the bottom sediments were collected and
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EEM fluorescence spectroscopy and PARAFAC analysis
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To avoid any inner-filtering effects, the EPS sample was diluted with deionized water to ensure
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that their absorbance at 200 nm was lower than 0.05 22. EEM fluorescence spectroscopy measure
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method was according to our previous work 21. The fluorescence spectral parameters of fluorescence
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index (FI) and humification index (HIX) value were calculated as the report of Gabor et al.23.
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The PARAFAC is a three-way method that was used to model the EEM fluorescence data. The
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principle of the PARAFAC could be found elsewhere 24, so there is no need to provide a detailed
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description on it. The PARAFAC process was carried out in MATLAB 8.3 (MathWorks, Natick,
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MA) with the DOMFluor Toolbox (http://www.models.life.ku.dk). To avoid the impact on the
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component score caused by varying EPS concentrations in different samples, the EEMs were
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normalized by dividing the spectra by the corresponding DOC concentrations
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the Rayleigh and Raman scatters by Delaunay triangulation method and subtract the control Milli7
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after removal of
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Q water, respectively. The outliers were examined by comparing the leverage. The number of
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fluorescence components was determined by a validation method, including split half analysis,
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residual analysis and visual inspection.
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Quantitative real-time PCR Assay
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Genomic DNA was extracted from about 0.2 g of freeze-dried sludge using the FastDNA SPIN
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Kit for Soil (QBIOgene Inc.,Carlsbad, CA, USA), with a beating time of 30 s and a speed setting of
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5.0. The concentration of the extracted DNA was determined with Nanodrop ND-1000 ultraviolet-
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visible spectrophotometry (Thermo, USA). Quantitative real-time PCR were performed in
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MX3000P Real-Time PCR system (Stratagene, La Jolla, CA) with SYBR Premix Ex TaqTM
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(TAKARA, Dalian, China) and the assays were carried out in a volume of 20 μL reaction mixtures,
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including 10 μL of SYBR Premix Ex Taq, 0.4 μL of ROX Reference Dye, 0.3 μL of each primer
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(10 μM), and 2μL of tenfold-diluted DNA template (1–10 ng). The program of protocol of each
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consisted of the following steps: 3 min at 95 ℃, followed by 40 cycles of 30 s at 95 ℃, 30 s at
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corresponding annealing temperature, and 45 s at 72 ℃. The standard curves for each bacteria gene
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copies were constructed from a series of 10-fold dilutions of the plasmid DNAs. The results with
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amplification efficiency in a range from 90%-110% and correlation coefficient above 0.9 were
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employed. Primers and corresponding annealing temperature are listed in Supplementary Table S2.
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Fourier transform infrared spectroscopy
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The EPS samples were lyophilized and ground with the infrared grade KBr and molded into a
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disc to characterize the major functional groups in the EPS using a FTIR spectrometer (IRPrestige8
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21, Shimadzu, Tokyo, Japan). IRsolution (v1.10) operating software was used to generate and
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process the FTIR Spectra. The amide I region (1700-1600 cm-1) in the EPS was further analyzed to
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extract information regarding protein secondary structures. Furthermore, the second-derivative
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spectra and deconvolution spectra of amide I region were carried out to resolve the overlapped peaks
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with the minimum residual using Peakfit software (version 4.12, Seasolve Software Inc.). Moreover,
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a ratio of α-helix/(β-sheet + random coil) was used to describe the tightness degree of protein
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structure (Supporting Information (SI) Table S5) 10.
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Chemical analysis
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Proteins (PN), humic acid (HA), polysaccharides (PS) and uronic acids (UA) were measured
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according to the research of Badireddy et al.8. The DNA content was measured by the diphenylamine
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colorimetric method
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Vario TOC analyzer (Elementar Analysensysteme Hanau, Germany). The UV254 was measured with
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a spectrophotometer UV-4802 (UNICO, Shanghai, China). Specific ultraviolet light absorbance
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(SUVA) was calculated as UV254/DOC to characterize aromaticity 27. SCOD, TSS and VSS contents
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of sludge were analyzed according to the Standard Methods 28. Ammonium, nitrite, nitrate were
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analyzed using Lachat QuikChem8000 Flow Injection Analyzer (Lachat Instrument, Milwaukee,
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USA). DO, pH and temperature were measured by oxygen, pH and temperature probes (WTW 340i,
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WTW Company). All standards were purchased from Sigma-Aldrich (St. Louis, USA), and the
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chemical analyses were carried out in duplicate using chemicals of analytical grade.
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The dissolve organic carbon (DOC) in the filtrate was analyzed using a
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Data Analyses and Statistical Methods 9
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To display variation in samples of a statistical population, the boxplot was used for data
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visualization (Fig 1a and e). The relationships between anammox sludge samples and EPS
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components characteristics were analyzed using the principal component analysis (PCA) method in
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CANOCO 5.0 software. Pearson correlation analysis was showed in heatmaps using the Euclidean
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distances and hierarchical cluster analysis in the “pheatmap” package of R 3.1.0 software.
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Results and discussion
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Chemical characterization of EPS components
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Variations on the contents of the three spatial scales EPS components were examined in 18
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samples taken from different reactors (Fig 1a), with significant difference in water quality and
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sludge morphology (the detailed data are presented in Fig.S1). Compare to slime (15.61±9.92%)
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and LB-EPS (6.46±3.02%), TB-EP (77.93±10.3%) was the major component of total EPS, which
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was similar to previous findings.
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distributed substance in slime. The predominant substance in LB-EPS and TB-EPS was humic acid
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and protein, respectively. The ratios of protein to polysaccharides, protein to DNA and protein to
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humic acid were 2.10±1.07, 6.38±7.88 and 1.48±0.57, respectively. The SUVA of EPS was: TB-
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EPS (0.62±0.12) > slime (0.55±0.41) > LB-EPS (0.39±0.31). Higher SUVA values indicate a higher
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concentration of organic matters with carbon-carbon double bonds, such as lignin, humic acid, PAHs
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(polycyclic aromatic hydrocarbon), PCBs (polychlorinated biphenyls), aromatic protein, etc 30. TB-
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EPS should contain large amounts of aromatic protein and other two scales contained a lot of humic
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acid in DOC.
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Polysaccharides and humic acid were the most widely
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Fig.1 here
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EEM fluorescence spectra of three EPS fractions in different anammox samples was
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investigated using PARAFAC model (Fig.1 b-d). The decomposed three components were identified
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as the characteristic peaks at Ex/Em of (215, 275)/342 nm, (205, 240, 305)/398.5 nm and (225, 240,
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335)/434.5 nm, which represented the protein-like substance (C1), heme-like substance (C2) and
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humic-like substance (C3) fluorophores, respectively (peak recognition of EEM fluorescence
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spectra are presented in Supporting Information (SI) Text 1). C1 was the most widely distributed
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substance in all three spatial scales EPS (45.19±16.29%, 46.88±18.42%, 74.26±18.40%) (Fig. 1e
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and the detailed data are presented in Fig.S1). Unlike the TB-EPS, there was approximately the
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same magnitude of C1 to C3 in slime and LB-EPS. The fluorescence intensity scores showed the
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relative abundance of EPS components in three spatial scales was inconsistent with the results of
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colorimetric method, which was caused by extremely high sensitivity of fluorescence spectroscopy
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than chromatic spectrum 31. In addition, FI values in the three spatial scales EPS varied in a range
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of 1.59±0.11~1.72±0.13, with relatively moderate values (1.4~1.7), indicating that the DOC in the
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EPS was originated from both microbial metabolism and waste water 32. Except for sample F6/L
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with a strong humic content of landfill leachate (HIX>6), the HIX values in slime and LB-EPS
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ranged from 1.37±0.59 to 1.57±0.73, representing the character of weak humic content and high
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microbial metabolic activity 33 that was consistent with the high SUVA values in slime and LB-EPS.
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Low levels of TB-EPS (HIX=0.49±0.16) illustrated the TB-EPS components were originated from
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from bacterial secretion rather than exogenous source.
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Quantification of EPS components using PCA method
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The compositional characteristics of EPS based on the chemical and spectral analysis was
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correlated with the activities of AOB, NOB and anammox bacteria using PCA method. By
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projecting the sample points onto the arrows of component concentration, samples were centered
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satisfactorily on the basis of water quality (Fig.2 a-3). Synthetic wastewater samples (bottom-left)
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were separated from domestic sewage (upper-right). The C1, C2 and PN had a relatively high
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abundance in the domestic sewage, while PS, FI, DOC, UA and HIX were more abundant in
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synthetic wastewater (Fig.2 a-1). In addition, landfill leachate and reject water samples were located
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in the upper-left side (Fig.2 a-3), showing a strong humification depended upon high content of
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SUVA, DNA, HA, UV254 and C3 (Fig.2 a-1). However, LB-EPS samples were scattered in PCA
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scatterplot of both water quality and sludge morphology (Fig.2 b-2 and b-3), whereas there was a
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clear clustering of the TB-EPS samples based on sludge morphology (Fig.2 c-2). Biofilm samples
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clustered on the upper-middle side of the plot (Fig.2 c-2), which had high levels of UA, C1 and PS
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(Fig.2 c-1), while granule samples located in the bottom-left (Fig.2 c-2) that were characterized by
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high SUVA and UV254 richness (Fig.2 c-1). Furthermore, flocs samples were apart from other two
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types of sludge and occupied a large area in the middle of the scatterplot (Fig.2 c-2), so that the
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distribution of each component in flocs was comparatively uniform.
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Fig.2 here
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PCA results indicated that different clusters represented different types of water quality and
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sludge morphology. The slime layer was correlated with water quality type due to its outermost
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spatial scales location. This might be helpful for identifying microbial survival environment. The 12
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TB-EPS layer was associated with microbial aggregates morphology, since the gel-like property of
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TB-EPS was tightly bounded to the cell surface and played an important role for flocculation
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Bacterial activity (the Supporting Information Table S1) showed that nitrification activity of AOB
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and NOB were higher in the flocs, whereas the anammox activity was higher in the granules (Fig.2
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c-1), which was consistent with previous findings that nitrification mostly occurred in small flocs
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while anammox was found in large aggregates 35. Since loose structure of the flocs have lower mass
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transfer resistance, ammonium and oxygen was easily penetrated in to the flocs, which benefited
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the growth of nitrifying bacteria (AOB and NOB). While large aggregates had high retention
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capability to accommodate microorganisms with slow growth rates (e.g. anammox bacteria) and
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provided anoxic micro-environment.
34.
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Pearson correlation analysis of anammox sludge aggregation
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Relationships of functional microorganisms and EPS parameters were established to explore
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the aggregation behavior of anammox sludge using Pearson correlation analysis (Fig.3). The real-
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time PCR and FTIR results showed many positive and negative correlations (Supporting
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Information Text 2, Table S4 and S5). In this study, we only focused on the relationships associated
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with anammox microorganisms. For slime layer, the abundance of anammox were positively
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correlated with the level of UA and DOC but was negatively correlated with SUVA, indicating that
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the more abundance of anammox in sludge, the more slime was secreted that was characterized by
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high UA content and low carbon-carbon double bonds (Fig.3(a)). For TB-EPS layer, anammox
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abundance was positively correlated with the protein secondary structures of β-sheet in TB-EPS
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layer (Fig.3(c)). Based on these results, two relationships: anammox and UA in slime; anammox 13
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and β-sheet in TB-EPS were elaborated.
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Fig.3 here
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Table 1 here
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For the first positive correlation between anammox and UA in slime (Fig.4 a-1), anammox
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bacteria were able to synthesize UA. Given the metagenome of Candidatus Kuenenia stuttgartiensis,
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one gene named kustb0219 was found to encoded GDP-mannose dehydrogenase synthesis (algD)
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36,
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the ability to synthesize UA. In addition, the FTIR spectra of slime demonstrated typical bands of
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UA (Fig.4 a-2 and Table 1): the bands at 1655 cm-1 and 1402 cm-1 were corresponded to the
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asymmetric and symmetric stretching vibration of COO- attributed to the presence of UA. The band
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at 1540 cm-1 was assigned to the C=C in pyranose ring, which might be caused by the β-elimination
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effect of alginate lyases. The band at 1240 cm-1 was assigned to the presence of O-acetyl ester for
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bacterial alginates 38. The bands at 952 cm-1 showed a weak absorbance that might be caused by the
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existence of nucleic acids 8. From a structural point of view, UA is the unique component in alginate,
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which is an unbranched exopolysaccharide composed of random arranged 1, 4-linked uronic
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residues of β-d-mannuronate (M) and α-l-guluronate (G) 39, and typically occurred as (–G–)n, (–
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M–)n and (–MG–)n blocks (Fig.4c) 40. The (–G–)n blocks are a rod-like polymer yielding an array
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of coordination sites that benefit divalent cations in their cavities and provide gel-forming capacity
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(Fig.4c). In contrast, (–M–)n and (–MG–)n blocks are fiber-like chain necessary for the flexibility of
which was known as crucial enzymes for alginate biosynthesis 37. Hence, anammox bacteria have
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the chains, the connection of (–G–)n blocks and the network structure during gelation 38. Alginate
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was involved in the development of microcolonies and responsible for the mechanical stability of
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biofilms
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affected by UA 5, 8. Since the viscosity of slime was increased with alginate concentration, UA in
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the slime of anammox bacteria may be showed stronger viscosity, and plays a key role for the
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adhesive ability and architecture structures of anammox sludge 38, 39, 41.
39.
In addition, bioflocculation, settling and dewatering properties were substantially
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For the second positive correlation between anammox and β-sheet in TB-EPS (Fig.4 b-1),
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secondary structure of protein in EPS played important roles in aggregation, adhesion,
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bioflocculation and biofilm formation
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bioflocculation 8, and β-sheet contributed to high aggregation ability of anammox sludge 10. Due to
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the twisted and pleated sheet structure of β-sheet (Fig. 4c), large amounts of inner hydrophobic
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groups of amino acids were more easily to be exposed and express the hydrophobic property of
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anammox sludge 10. Increasing the hydrophobicity of cell surfaces promoted cell-to-cell aggregation
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42,
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spectra showed more hydrophobic functional groups in TB-EPS (Fig. 4 b-2 and Table 1): the peak
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at approximately 1668 cm-1 and 1623 cm-1 were mainly assigned to C=C and C=O in proteins. The
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band at 1384 cm-1 was attributed to the bending vibration of C-H in -CH3. There were fewer
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hydrophilic functional groups (especially for high polarity of N-H, -OH and COO-) in TB-EPS.
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Relative content of β-sheet in TB-EPS proteins increased with the abundance of anammox bacteria
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(Fig. 4 b-1), implying that TB-EPS secreted from anammox bacteria had a strong hydrophobicity to
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promote microbial aggregation.
7, 8.
Previous studies showed that β-sheets promoted
and the cell surface hydrophobicity was the triggering force for bio-granulation
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The FTIR
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Fig.4 here
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Overall, the mechanisms of anammox aggregation might be contain three stages. (1) Initial
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attachment of anammox cells to the surface: Free anammox bacteria swimming in close proximity
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to abiotic solid surface until find an nutritious habitat for initial contact by secrete small amounts of
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sticky UA in bulk water; (2) Production of UA resulting in more firmly irreversible adherence: Then
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they come to rest on the surface and contact with other cells. In this moment, many anammox
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bacteria began to secrete a lot of UA. The gelation properties of UA can play a role in net capturing
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to prevent cells detachment due to its three dimensional network structure. (3) Development of
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microcolony architecture: After that, during the growth and reproduction of anammox bacteria,
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more EPS is produced and tightly-wrapped on cell surface. Due to the β-sheet secondary structure
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in extracellular protein, inner hydrophobic groups were more easily to be exposed, which makes the
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surface of anammox community showed higher hydrophobic property. It can promote cell-to-cell
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aggregation and form strong microcolony architecture, which make them undergo further adaptation
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to life in large aggregates.
312 313
Significance of this study
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The identification of the key role of stratified EPS is of importance to understand the
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mechanisms of anammox microbial aggregation and enhance anammox efficiency through biofilms
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and granules formation. By examining anammox-dominated mixed culture samples from 18
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anammox systems, this study for the first time elucidated the characteristics of slime and TB-EPS
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composition and their correlation with water quality and sludge morphology. UA (in slime) and β16
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Sheet (in TB-EPS) level were positively correlated with anammox abundance (Fig. 4a). To improve
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the accommodation capacity of anammox biomass, mature anammox sludge should be added in
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order to promote the release of UA or directly added alginate to make the flocs quickly form granules
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or biofilm. Another option will be adding accelerants (e.g. quorum sensing molecules
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pretreatment (e.g. ultrasound
324
activity that may promote anammox bacterial secrete more UA. In addition, Verrier et al. found that
325
hydrophobic surfaces are favor adhesion of hydrophobic bacteria 49, Based on the above result, the
326
high hydrophobic characteristic of anammox can be utilized to develop the special carriers or small
327
particles (acting as crystal nucleus) with high hydrophobicity (eg. polytetrafluorethylene,
328
polypropylene or polyethylene 49) that can priority selection bond anammaox bacterial cells to form
329
biofilms or granules 50. Future studies should be extracted alginate-like exopolysaccharides from
330
anammox sludge and verified its gel networks by gel formation experiments and further elucidated
331
the role of stratified EPS on the anammox aggregation behavior by proteomics and glycomics.
47
and magnetic field
48)
45, 46)
or
to enhance anammox bacterial metabolic
332 333
ASSOCIATED CONTENT
334
Supporting Information
335
The Supporting Information is available free of charge on the ACS Publications website at DOI:
336
Additional discussion details Text1-Text2 and Table S1-S5 and Figures S1−S5. (PDF)
337 338
AUTHOR INFORMATION
339
Corresponding Author
340
*Tel: 86-10-67392627; E-mail:
[email protected] (Yongzhen Peng) 17
ACS Paragon Plus Environment
Environmental Science & Technology
341
*Tel: 86-10-67392627; E-mail:
[email protected] (Qing yang)
342
Notes
343
The authors declare no competing financial interest.
344 345
ACKNOWLEDGEMENTS
346
We greatly thank Dr. Shanyun Wang, Dr. Lei Miao, Dr. Xiaoxia Wang, Dr. Rui Du, Dr.Yandong
347
Yang, Mr. Pengchao Gu and Miss. Han Xiao for their kind help in sampling on this work. This
348
research was financially supported by Nature Science Foundation of China (21677005) and the
349
Funding Projects of Beijing Municipal Commission of Education.
350 351
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475 476 477
TABLE AND FIGURE CAPTIONS
478
Table 1 Band assignments for FTIR spectral features (cm-1) of slime and TB-EPS. The
479
band assignments are based on previous reports 7, 8, 10, 38.
480
Fig. 1 Characterization of EPS fractions (a) colorimetric components. EEM contours
481
of three components (b) Component 1, (c) Component 2 and (d) Component 3
482
decomposed using the PARAFAC approach. (e) fluorescence components in the
483
different anammox sludges. The line in the middle of the box marks the median and the
484
star point marks the mean. The boundary of the box indicates the 25th percentile and
485
the 75th percentile. Whiskers that protrude out of the box indicate the 10th and 90th
486
percentiles. The hollow and solid circle point represent the minimums and maximums.
487
The value above solid circle is the mean and the standard deviation (in parentheses).
488
Fig. 2 PCA ordination diagram based on compositional characteristics of three spatial
489
scales of EPS. (a) slime; (b) LB-EPS; (c) TB-EPS. Different groupings is enclosed in
490
polygon based on sludge morphology (a-2, b-2, c-2) and water quality (a-3, b-3, c-3).
491
Fig. 3 Pearson correlation analysis between major genera and EPS parameters.
492
Heatmap analysis of (a) slime, (b) LB-EPS and (c) TB-EPS. The strength of correlation
493
is defined by a color code with red indicating positive correlations, white a neutral
494
context, and blue a negative correlation. (Ratio=α-helix/(β-sheet + random coil), white
495
stars, p < 0.05; black stars, p < 0.01). 24
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496
Fig. 4 Pearson correlation analysis of anammox abundance with UA in slime (a-1) and β-sheet in
497
TB-EPS (b-1). FTIR spectra of slime (a-2) and TB-EPS (b-2). (c) The primary mechanisms of
498
anammox aggregation behavior (the pictures of protein secondary structures was cited from
499
Molecular Biology of the Cell,5th 44 )
25
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Table 1 Band assignments for FTIR spectral features (cm-1) of slime and TB-EPS. The band assignments are based on previous reports 7, 8, 10, 38. Wavenumber (cm-1) slime
TB-EPS
3323 2927 1655 1540 1402 1240
3393 2937 1668 1623 1384 -
1158
-
1075 952 859
1112 1046, 995 -
Band assignments O-H stretching (hydrogen-bonded) ν C-H stretching (-CH2 and -CH3 groups) νas COO- stretches possibly associated with uronic acid ν C=C stretch associated with proteins νs C=O stretch (amide I) associated with proteins ν C=C stretches possibly associated with pyranose ring νs COO- stretches possibly associated with uronic acid δ C-H stretches in -CH3 associated with amines and lipids νs C-N stretch possibly associated with O-acetyl ester δ C-OH, δ C-O and ν C-O possibly associated with polysaccharide Ring vibrations ν P=O, ν C-O-C, ν C-O-P as in polysaccharides δ C-H stretching (-CH groups) νas O-P-O stretches associated with nucleic acids Ring “breathing” associated with ν C-C and ν C-OH
500
26
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Environmental Science & Technology
0.12 (0.15)
0.8
350
0.08 (0.31)
2.35 (4.21)
14.20 (5.91)
0.48 (0.77)
2.25 (2.03)
0.4
8.60 (4.40)
8.55 2.82 (1.51) (2.00) 1.21 (1.23)
0.03 (0.02)
0.2
0.3
DNA
300
HA
UA
DOC
UV 254
0.02
250
LB
0.005 200
(b) (c)
0.0 300
350
400 450 Em (nm)
500
550
200
0.045
Component 2
0.03 300
0.025
8
0.005 200
16.51
2.0
(29.08)
100
1.5
19.86
11.10 10.39
(21.78)
(16.04) (15.88)
(c) (d)
300
350
0.49 (0.16)
1.0
400 450 Em (nm)
500
0.2
0.0
550
200 x 10 18
400 Component 3
250
300
350
400
Wavelength (
-3
0.3 Component 3
16 14
350
0.2
12 Ex (nm)
(0.13) 1.59 1.59 (0.12) (0.11)
FI & HIX
6 1.72
0.3
0.1
0.01
(1.41)
27.40
0.4
0.015
23.89
(43.20)
400
Component 2
0.5
0.035
250
(42.14)
350
Wavelength (
(1.72) 1.88
(62.96)
300
0.04
SUVA
1.77
250
400
350
TB
53.09
250
0.2
0.1
0.01
0.02
Slime
163.48
150
300
0.015
0.0
PS
0.03 0.025
Ex (nm)
2.17
20 (5.33)
0.69 (1.96) 2.99 (2.33)
Component 1
0.4
0.035
10
300
8
Loadings
40
200
Component 1
Loadings
1.0
400
Loadings
0.62 (0.12)
0.6
(55.25)
0.1 6
50
250
5.98
2
0
0.0
C1
C2
C3
4
0.5
(1.60)
501
1.4
(a) (b)
Ex (nm)
0.64 (0.16)
22.92 (19.10)
8.02 (12.88)
30.40 (9.98)
1.6
1.2
80 60
0.39 0.55 (0.31) (0.41)
-1
Concentration (mg/g VSS)
45.09 (21.63)
56.32 (15.42)
PN
Fluorescence intensity scores
103.62 (14.52)
TB
100
0
(e)
LB
-1
Slime
120
-1
(a)
m mg ) UV254(m ) & SUVA(L·
Page 27 of 30
FI
HIX
200
0.0 300
350
400 450 Em (nm)
500
550
502
Fig. 1 Characterization of EPS fractions (a) colorimetric components. EEM contours of three
503
components (b) Component 1, (c) Component 2 and (d) Component 3 decomposed using the
504
PARAFAC approach. (e) fluorescence components in the different anammox sludges. The line
505
in the middle of the box marks the median and the star point marks the mean. The boundary
506
of the box indicates the 25th percentile and the 75th percentile. Whiskers that protrude out of
507
the box indicate the 10th and 90th percentiles. The hollow and solid circle point represent the
508
minimums and maximums. The value above solid circle is the mean and the standard
509
deviation (in parentheses).
27
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200
250
300
350
400
Wavelength (
Environmental Science & Technology
(a-1)
Page 28 of 30
(c-1)
(b-1)
UV254
μanammox μNOB
UV254
μanammox
UV254
Slime
LB-EPS
(a-2)
(b-2)
Slime
LB-EPS
(a-3)
(b-3)
Slime
μAOB μNOB
μNOB μAOB
μAOB
μanammox
TB-EPS
(c-2)
TB-EPS
(c-3)
TB-EPS
LB-EPS
510 511
Fig. 2 PCA ordination diagram based on compositional characteristics of three spatial scales
512
of EPS. (a) slime; (b) LB-EPS; (c) TB-EPS. Different groupings is enclosed in polygon based
513
on sludge morphology (a-2, b-2, c-2) and water quality (a-3, b-3, c-3).
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(a) 0.8 Nitrospira AOB Anammox Nitrobacter DNB (nirK) Total bacterial DNB (nirS)
0.6 0.4 0.2 0 -0.2
C2 C1 β-sheet FI α-Helix HIX PS DOC UA Random coil C3 Ratio β-turn HA DNA UV254 PN SUVA
-0.4
(b) 0.4 Nitrospira AOB Total bacterial DNB(nirS) DNB(nirK) Nitrobacter Anammox
0.2 0 -0.2 -0.4
Ratio α-Helix β-turn FI C2 C3 C1 UV254 DNA SUVA HA PS β-sheet DOC HIX PN Random coil UA
-0.6
(c) 0.8 Anammox Total bacterial DNB (nirS) Nitrospira AOB Nitrobacter DNB (nirK)
PN UA PS DNA DOC HA SUVA UV254 C2 HIX β-sheet Ratio α-Helix FI C3 Random coil C1 β-turn
514
0.6 0.4 0.2 0 -0.2 -0.4
515
Fig.3 Pearson correlation analysis between major genera and EPS parameters. Heatmap
516
analysis of (a) slime, (b) LB-EPS and (c) TB-EPS. The strength of correlation is defined by a
517
color code with red indicating positive correlations, white a neutral context, and blue a
518
negative correlation. (Ratio=α-helix/(β-sheet + random coil), white stars, p < 0.05; black stars,
519
p < 0.01).
29
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(a-1) 7 6
(a-2) 100
Anammox ∝ UA (slime) -10
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Slime (sample G4/S for exemple)
90
2
y=1.7233×10 x+2.1312 (R =0.7259) Transmittance (q.u.)
1240
UA (mg/L)
5 4 3
80
70
60
Linear fit 95% Confidence bands
1 0.00E+000
5.00E+009
1.00E+010
1.50E+010
2.00E+010
40
2.50E+010
3500
1158 C-O 1075 C-O-C
1655 COO
3323 O-H
4000
3000
952 O-P-O
1540 C=C
2927 C-H
50
2
859 C-C C-OH
1402 COO
2500
2000
1500
1000
500
-1
Wavenumber (cm )
Anammox abundance (copies/mg-dry sludge)
β-sheet (%)
35
(b-2) 100
Anammox ∝ β-sheet (TB-EPS) -10
2
TB-EPS (sample G4/S for exemple)
90
y=7.3389×10 x+17.7060 (R =0.6436) Transmittance (q.u.)
(b-1) 40
30
25
20
80 2937 C-H
70
60
2555 S-H
Linear fit 95% Confidence bands
100
995 1046 C-H C-H
3393 O-H
90
1668 C=C 1623 C=O
50
15
1112 C-O-C
80
1384 CH3
40
70
0.00E+000
5.00E+009
1.00E+010
1.50E+010
2.00E+010
2.50E+010
4000
3500
3000
2500
2000
1500
1000
500
-1
Wavenumber (cm )
Anammox abundance (copies/mg-dry sludge)
60
50
(c)
β-Sheet
α-Helix 40
4
hydrophobic grouping
(–G–)n
(–MG–)n
(–M–)n
(–G–)n
520 521
Fig. 4 Pearson correlation analysis of anammox abundance with UA in slime (a-1) and β-sheet
522
in TB-EPS (b-1). FTIR spectra of slime (a-2) and TB-EPS (b-2). (c) The primary mechanisms
523
of anammox aggregation behavior (the pictures of protein secondary structures was cited from
524
Molecular Biology of the Cell,5th 44 ).
30
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