Insight into the Aggregation Capacity of Anammox Consortia during

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Insight into aggregation capacity of anammox consortia during reactor start-up Yunpeng Zhao, Ying Feng, Jianqi Li, Yongzhao Guo, Liming Chen, and Sitong Liu Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b06553 • Publication Date (Web): 05 Mar 2018 Downloaded from http://pubs.acs.org on March 8, 2018

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Environmental Science & Technology

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Insight into aggregation capacity of anammox consortia

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during reactor start-up

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Yunpeng Zhao 1, 2, Ying Feng 1, 2, Jianqi Li 2, 3, Yongzhao Guo 2, 3, Liming Chen 1, 2,

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Sitong Liu 1, 2 *

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1

Department of Environmental Engineering, Peking University, Beijing 100871, China

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2

Key Laboratory of Water and Sediment Sciences, Ministry of Education of China, Beijing

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100871, China

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3

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518055, China

School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen

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*Corresponding author: Sitong Liu

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Address: College of Environmental Science and Engineering, Peking University, Yiheyuan Road,

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No.5, Haidian District, Beijing 100871, China.

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E-mail: [email protected]

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Tel/Fax: 0086-10-62754290.

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1

ACS Paragon Plus Environment


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Abstract

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Anammox aggregates have been extensively observed in high-efficiency

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nitrogen-removal reactors, yet the variation and inherent cause of its aggregation

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capacity related to reactor operation are still unknown. Here, we used microbial

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detection, metabolomics, extended DLVO theory and multivariate statistical analysis

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to address this issue. The aggregation capacity of anammox consortia varied

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periodically during reactor operation, which was determined by the hydrophobic force

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and the ratio of extracellular protein (PN) to extracellular polysaccharides (PS).

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Fundamentally, it related to the variation of polysaccharides degradation bacteria

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abundance and the discrepancy of consortia metabolism. Specifically, the

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distinguishable up-regulation of the amino acids Phe, Leu, Ala, Thr, Gly, Glu, and Val

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potentially contributed to the high biosynthesis of extracellular PN. Together with the

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reduced extracellular PS production that was regulated via the

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UDP-N-acetyl-D-glucosamine and UDP-N-acetyl-D-galactosamine pathways, the

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elevated extracellular PN/PS resulted in the obviously increased extracellular

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hydrophobicity and aggregation capacity. Additionally, the overtly enriched

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phosphatidylethanolamine biosynthesis pathway was also vital to increasing

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extracellular hydrophobicity to accelerate aggregation. Understanding aggregation

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capacity variation is useful for advancing anammox aggregation for its application in

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wastewater treatment.

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2


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Introduction

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The anaerobic ammonium-oxidizing (anammox) process, which converts ammonium

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and nitrite to dinitrogen gas,1 has been applied as a promising technology to treat

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ammonium wastewater with its inherent advantages of high nitrogen removal, no

41

requirement for oxygen, an additional carbon source and low sludge yield.2 The slow

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growth rate of functional bacteria with two weeks of doubling time3 makes the high

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sludge retention a primary requirement for anammox reactor operation. Researchers

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have applied lots of different strategies to improve sludge retention, such as adding

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functional carriers, using membrane filters in MBR4 and rapid granulation by

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signaling molecules, among others. Actually, no matter the consortia granulation or

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biofilm formation, the intrinsic aggregation capacity of anammox consortia is very

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important, which varies in different conditions. To investigate this issue, it is

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important not only to advance biofilm or aggregation formation but also to clarify the

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potential metabolism conversion in the bacteria along with the different phases of

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reactor operation.

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The extracellular polymeric substance (EPS) matrix plays a core role in

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determining the bacterial aggregation capacity. There were three different concepts

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existing in the EPS compositions determining the microbial aggregation: (i) The “PS”

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mechanism: the gel-forming alginate-like PS could form a cross-network that favors

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sludge aggregation or is a trigger for sludge granulation;5–7 (ii) The “PN” mechanism:

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the electronegativity and hydrophobicity of PN could promote and stabilize the

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aggregate structure;8,9 and (iii) The “PN/PS” mechanism: increasing the PN/PS ratio 3



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could induce an increase in sludge hydrophobicity and bioflocculation ability.10,11

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Previous reports have demonstrated that the EPS of anammox sludge has a strong

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tendency to form biofilm or adhere to inert surfaces,12,13 as it has a larger amount of

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hydrophobic proteins and more loose secondary structure compared to activated

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sludge, nitrifying sludge and denitrifying sludge.8,14 The EPS is closely related to the

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microbial survival ability and aggregation morphology. There are some factors that

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influence EPS production, such as growth phase, substrate type, and external

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conditions.15 In fact, the EPS levels and chemical composition vitally depend on the

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bacteria metabolism. Therefore, the metabolism profile of the bacteria significantly

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determines its aggregation capacity.

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EPS consists of different types of biopolymers, such as PN, PS, and phospholipids.

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They are all organic macromolecules that are biosynthesized by polymerization of the

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specific building blocks.5 For example, 20 amino acids, such as Ala, Arg, Asn, and

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others, are reported for bacterial protein synthesis.16 Bacterial polysaccharides are

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found to be converted from monosaccharides that could be biosynthesized from the

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Embden–Meyerhoff–Parnas gluconeogenesis (EMP) pathway or amino sugars as

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precursors.17 The major composition of extracellular phospholipids includes

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phosphatidylethanolamine (PtE) and phosphatidylcholine (PtC).16,17 Recently,

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researchers found many generation genes and pathways for bacterial EPS. For

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example, the biosynthesis of tetratricopeptide repeat (TPR) protein is coded by the

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asnB gene for activated sludge bacteria.18 Polysaccharide biosynthesis is encoded by

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the cps3E-F region in some types of lactic acid bacteria.19 Phosphoethanolamine (PE) 4


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and phosphocholine (PC) can be formed by a bifunctional

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cardiolipin/phosphoethanolamine synthase and glycerolphosphocholine (GPC)

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pathway, respectively.20 Although the hydrophobicity of anammox consortia EPS for

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its aggregation has been described previously, how bacterial metabolism regulates

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EPS production and further influences the bacterial aggregation capacity remain to be

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clarified.

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Therefore, this study focused on understanding the variation in bacterial

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aggregation capacity during anammox reactor operation and interpreting the inherent

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cause using recently developed metabolome biotechnology. Bacterial aggregation

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capacity, EPS components, and community composition combined with the extended

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DLVO theory for the bacteria samples harvested across 210 days of reactor operation

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were used to go insight into consortia aggregation capacity variation during anammox

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reactor start-up.

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Materials and methods

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Reactor start-up and operation. A membrane bioreactor (MBR) with a 5.0-L

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working volume was operated for 210 d. The polyvinylidene fluoride (PVDF)

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membrane was placed in the center of the reactor. Then, anammox consortia that had

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been stored at 4 °C for 60 days was inoculated with the initial VSS concentration of

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about 0.06 g /L.21 The influent ammonium and nitrite concentration was gradually

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increased from 20 mg–N/L that was favorable for inoculum adaption to 300 mg–N/L.

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The details of the medium composition are presented in Supporting Information (SI)

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Text S1.

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The reactor was operated in continuous mode at a constant flow rate (2.3 mL/min,

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HRT=36 h) and was maintained in an anaerobic condition during the reactor operation.

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According to the microbial community structure, the start-up period could be divided

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into two stages: phase I (days 1–90) and phase II (days 91–210). The reactor pH was

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kept in the range of 7.5 to 8.0, and the temperature was maintained at 37 ± 1 °C.

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The influent and effluent concentrations of ammonium, nitrite and nitrate were

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determined every two days using an APHA standard engineering method. 22

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Suspended granular samples were obtained from the reactor every 30 days in two

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phases (on day 30 60, 90, 120, 150, 180 and 210) and samples on day 165 and 195

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were also harvested to get more information about the variation of aggregation

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capacity in the late stage of the reactor operation. Inoculum and these samples were

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labeled in order as S1–S10, respectively. These samples were used to determine

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biomass concentration, aggregation capacity, diameter, EPS composition and structure,

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contact angle, zeta potential and bacterial community structure. Meanwhile, the

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representative samples were also applied to detect metabolites: (i) the samples

118

obtained every 60 days [on day 60 (S3), 120 (S5) and 180 (S8), respectively]; (ii) the

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samples obtained on the final day of the reactor operation [on day 210 (S10)].

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Aggregation capacity and diameter size assay. Aggregation capacity was

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determined using attachment-crystal violet staining.23 The consortia samples with

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synthetic medium were added to a 12-well plate and then incubated on a shaker. After

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that, the microbial suspension that could not be immobilized onto the plate wall was

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removed. Anammox consortia that were immobilized onto the plate wall were stained

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with crystal violet before elution by ethanol. Finally, the aggregation capacity was

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expressed in terms of the absorbance of ethanol solution. Higher absorbance indicated

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higher aggregation capacity.23 Additionally, the turbidity assays were used to support

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the results. Detailed methods are presented in SI Texts S2 and S3. The diameter of

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samples was determined using the Nano ZS instrument (Malvern. Inc., USA), based

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on the assumption that the aggregates were spherical.24 Five parallel samples were

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determined for each test.

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EPS Extraction and Determination. EPS was extracted using the cation exchange

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resin (CER) method proposed by Hou et al.8 The extracellular polysaccharides and

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proteins were determined using the Anthrone method25 and the BCA assay26

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respectively, and was normalized by the biomass concentration. The biomass

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concentrations were determined in terms of volatile suspended solids (VSS)

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concentration22 using the vigorously mixed consortia by magnetic stirring and N2

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gas.27 The PN or PS percentage was defined as the ratio of PN or PS to the sum of PN

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and PS concentrations. The extraction EPS solution was also lyophilized for the FTIR

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and XPS analyses.8 Pearson correlation analysis and Kruskal–Wallis tests were carried

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out using SPSS v20.0.

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Extended DLVO theory. To determine the interaction energy between sludge cells

143

influencing anammox aggregation, the extended DLVO analysis was performed.28-30

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The total interaction energy (WT) is the summation of the Van der Waal energies (WA), 7



145

electric double layer (WR), and acid–base interaction (WAB), or WT = WA + WR +

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WAB. Calculation of the functional forces of WR, WA, and WAB was performed

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according to the surface thermodynamic calculation approach based on the contact

148

angle and zeta potential of samples.29,30 The contact angle and zeta potential were

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measured as described previously.29,30 Detailed methodology and calculations can be

150

found in SI Texts S4 and S5, respectively.

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Microbial community analysis. Microbial DNA from consortia samples was

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extracted using the FastDNA @ SPIN Kit for Soil (MP Biomedicals, USA), as per the

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manufacturer’s instructions. Next, the V4 regions of bacterial 16S rRNA gene were

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amplified with the primer pair 5158F/806R.31 Finally, the extracted and purified PCR

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products were sequenced using the Illumina MiSeq platform at Majorbio Co., Ltd.

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(Shanghai, China). Thereafter, raw sequences (NCBI SRA: SRP126708) were quality

157

filtered using the following criteria: sequence length shorter than 200 bp, average

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sequence quality score less than 25, or sequences containing any primer mismatches,

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barcode mismatches, ambiguous bases, or homopolymer runs exceeding two bases

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were excluded from further sequence analysis.31 Furthermore, the biomarkers among

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different phases were identified using the filtered data with linear discriminant

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analysis (LDA) effect size (LEfSe) as describe.32 The Fluorescence in situ

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hybridization (FISH) was used to validate the abundance of anammox species. Details

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were presented in SI Text S6.

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Metabolomic Profiling and Quantitation Analysis. The sample was harvested

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after centrifugation at 4°C at 6000×g for 3 min and washing with 1× PBS buffer three 8


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times. The sample was resuspended in 1.5 mL of cold ultrapure water (stored at 4 °C),

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and the mixture was sonicated with a probe tip sonicator on ice (3–s intervals between

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3-s pulses; 30 min, 30% of maximum intensity; Scientz, JY–92–IIN, 650W).33 Then,

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6 mL of pre-chilled methanol/water (4:1, v/v) was subsequently added to the

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samples.34 The samples were incubated at -80 °C for 2 h to precipitate the cellular

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proteins. After centrifugation (20 min at 10,000× g at 4°C), the supernatants were

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collected and dried under a gentle steam of nitrogen gas at room temperature.

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Afterwards, the samples were stored in a -80 °C freezer and prepared for metabolites

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that including intracellular and extracellular compounds determination using

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high-performance liquid chromatography with tandem mass spectrometry

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(HPLC–MS/MS). Furthermore, untargeted metabolomic analysis is used for global

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metabolome analysis, while targeted analysis is more accurate for quantitation.35

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Detailed metabolomics analysis methods are presented in SI Text S7. All tests were

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repeated three times. Additionally, the detailed methods to determine the hydrolysates

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of extracellular proteins and polysaccharides were presented in SI Text S8.

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The metabolites that were identified in all four samples were used for statistical,

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principal components analysis (PCA), and pathway analyses. Two–tail paired t-tests

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were conducted in Excel. All the heatmaps and the PCA analysis in this study were

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completed in R using the ggbiplot packages respectively. Prior to analysis, the

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metabolic data were pretreated using the autoscaling method.36 Pathway analysis was

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finished using Metaboanalyst (www.metaboanalyst.ca).

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Results 9



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Bacterial aggregation capacity and diameter size variations response to

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operational phases. During reactor start-up, there were discrepant nitrogen

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conversion ratios and nitrogen removal rates (NRRs) between two phases (Figure 1

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and SI Figure S1). During phase I, both the nitrite to ammonium consumption ratio

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(△NO2-–N/△NH4+–N) and the nitrate to ammonium conversion ratio

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(△NO3-–N/△NH4+–N) varied considerably. And the reactor performance gradually

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increased corresponding to the highest NRR of 124.52 g–N/(m3 d) in the end. In phase

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II, the average △NO2-–N/△NH4+–N and △NO3-–N/△NH4+–N was 1.07±0.03 and

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0.22±0.04, respectively. The total NRR increased sharply from 131.46 to 356.73

198

g–N/(m3 d) with the increased influent nitrogen concentrations from 120 mg/L to 300

199

mg/L.

200

To determine whether the aggregation behavior of anammox consortia varied with

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the reactor operation, a comparison of aggregation capacity was conducted.

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Interestingly, the aggregation capacity exhibited the periodic law of first increase, and

203

subsequently decreased during the reactor start-up. For example, it decreased to the

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minimum in the beginning of phase II (S5) and then increased. It decreased again for

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S8 and increased until the end of phase II (S10). The diameters of anammox

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aggregates that were the intuitive reflection of aggregate capacity were shown in SI

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Figure S2. Importantly, its variation tendency was all agreed with the variations of

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aggregation capacity (r = 0.947, P = 0.000). Turbidity assay was also conducted to

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support these results (SI Figure S3) (details were presented in SI Text S9).

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Variation in EPS chemical structure and composition. To uncover the variation 10


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in the EPS composition of anammox consortia, the concentrations of PN and PS were

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determined. Changes in the concentration of PN, PS, and the ratio of PN/PS showed

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different trends as follows [Figure 2(b)]: (i) PN concentration was relatively lower for

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inoculum and the samples in the end of phase I (S4) and in the initial period of phase

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II (S5 and S6). The average concentration of PN in phase II was significantly higher

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than that in phase I (Kruskal–Wallis test, P < 0.03). (ii) Intriguingly, PS concentration

217

exhibited the periodic variation law of first increase, and subsequently decreased

218

during the reactor start-up. (iii) Integrating the change rules of these two indices, the

219

ratio of PN/PS changed periodically in two phases. It was relatively lower for the

220

inoculum (S1), at the end of phase I (S4), the initial period of phase II (S5) and S8.

221

Furthermore, the correlation between the aggregation ability and the concentration

222

of PN was significantly positive (r = 0.547, P < 0.003) [Figure 2(c)]. Importantly,

223

though there was no significant relationship with the concentration of PS [Figure 2(d)],

224

a relatively stronger and significantly more positive correlation was observed between

225

the aggregation capacity and ratio of PN/PS (r = 0.670, P = 0.000) than that observed

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between the aggregation capacity and PN concentration [Figure 2(e)]. Consequently,

227

the PN/PS ratio, and not the individual concentration of PN or PS, showed a stronger

228

positive correlation with the aggregation capacity.

229

To unravel the functional groups of the anammox consortia surface, the EPS was

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further analyzed by FTIR spectroscopy and XPS analysis. The FTIR results showed

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that the variation in the chemical structure of EPS was in line with the composition

232

change (SI Figure S4). In addition, the absorption bands of lipids reached a maximum 11



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in the end of phase I (S4) and afterwards became invisible in phase II (S5-S10). Most

234

importantly, the XPS analysis showed that the ratio of hydrophobic functional groups

235

also changed periodically along with the variation of aggregation capacity during the

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reactor operation (SI Figure S5). Details are presented in SI Text S10.

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Various bacterial interaction energies. To determine the key interaction energy

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influencing the anammox aggregation, the contact angles and zeta potential combined

239

with an extended DLVO theory analysis were performed. The results of the contact

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angles against the three types of liquids (water, ethanediol and propanetriol) and the

241

zeta potential in 0.1 M NaCl solution are shown in SI Tables S1 and S2, respectively.

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Combining these experimental results, the interaction energies can be calculated using

243

the formula presented in SI Text S5. Figure 3 shows the curves for total energy (WT)

244

as a function of separation distance among bacteria of different samples. Interestingly,

245

the energy barriers that would prevent the bacteria from aggregating also varied

246

periodically. This finding was in line with the aggregation capacity results [Figure

247

2(a)].

248

In fact, the contributions of WA, WR and WAB in extend DLVO were significantly

249

dependent and discrepant. Here, though the WA and WR curves were nearly similar for

250

different consortia samples (SI Figure S6), the WAB curves that depended on the

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hydrophobic interaction followed the periodical rule during the reactor start-up.

252

Importantly, there were obvious energy barriers while the WAB values of consortia

253

samples were higher, such as S1, S4 and S5. Thus, the WAB that on behalf on the

254

hydrophobic force played a decisive role in determining the aggregation process, 12


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which agreed with the EPS content results. Therefore, it is important to elaborate on

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the biosynthesis and degradation of anammox EPS that led to the variation in bacterial

257

hydrophobicity and aggregation ability.

258

Bacterial community shift. To identify the microbiological community shift

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during the reactor operation, 16S rRNA gene sequencing and FISH combined with

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PCA analysis were conducted. Though the abundance of 47 community members

261

(species with more than 1% relative abundance) changed markedly between phase I

262

and phase II [Figures 4(a) and 4(b)] (details were presented in SI Text S11 and

263

Figures S7 and S8), the PCA analysis showed the colonization-specific clustering of

264

phase I and phase II, respectively. Therefore, the bacterial community structures were

265

relatively stable in phase I and phase II, respectively.

266

Importantly, the variation in the Phycisphaerae classes and the Anaerolineaceae

267

families followed a periodic law [Figure 4(a)], which was the same as the variation in

268

PS [Figure 2(b)]. To explore whether there was a correlation between these species

269

and the PS in anammox consortia, a Pearson correlation analysis was carried out.

270

Surprisingly, the relationship between the ratio of PS and the sum of the relative

271

abundance of these two species was significantly negative (P < 0.03) [Figure 4(c)].

272

Metabolite profile related to anammox consortia EPS shift. To provide insight

273

into the possible metabolic pathways of EPS, the metabolites of one sample in phase I

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(S3) and three samples in phase II (S5, S8 and S10) were examined. In all, the 383

275

metabolites that were detected in all four samples belonged to the following Kyoto

13



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Encyclopedia of Genes and Genomes metabolic pathways: amino acids,

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carbohydrates, lipids, peptides, nucleotides, cofactors and vitamins.

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Figure 5(a) depicts the intensities of the detected metabolites in each sample. As

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whole, dramatic changes of amino acids, sugar and glycerophospholipid were

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observed in the metabolic activities of anammox consortia. PCA of the metabolic

281

profiles brought insight into the colonization-specific clustering of the four samples

282

[Figure 5(b)]. The detail differentiation among colonization states has been shown in

283

Figures 5(c)-(e). From these figures, we could distinguish specific biosynthetic

284

pathways for the predominant EPS components.

285

Figure 5(c) shows the biosynthetic pathway of amino acids. These amino acid

286

intensities of four samples were all significantly distinct, especially for phenylalanine

287

(Phe), leucine (Leu), alanine (Ala), threonine (Thr), glycine (Gly), glutamate (Glu),

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valine (Val), and others. However, not every amino acid can be the predominant

289

component of extracellular proteins. The relationships of 20 amino acids and PN were

290

established using Pearson correlation analysis. The results showed that only seven

291

amino acids exhibited strongly positive correlations (P < 0.003), including Phe, Leu,

292

Ala, Thr, Gly, Glu and Val (SI Figure S9). Importantly, these seven amino acids were

293

indeed involved in the hydrolysates of extracellular PN (SI Figure S10). Therefore,

294

these seven amino acids might be the main synthetic monomers of extracellular

295

proteins.

296

Unlike the complex biosynthesis pathway of PN, the sugar metabolism of

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anammox consortia is relatively straightforward. PS was biosynthesized mainly via

298

the uridine diphosphate-N-acetylglucosamine (UDP-GlcNAc) and uridine

299

diphosphate-N-acetylgalactosamine (UDP-GalNAc) biosynthetic pathways, since

300

these metabolites and their biosynthetic precursors (Fru-6P and Glu-6P) were all

301

detected in the hydrolysates of extracellular polysaccharides (SI Figure S10).

302

Additionally, it also can be supposed by the varied regulation of sugar metabolites

303

intensities and PS concentrations in different samples (Details were presented in Text

304

S12). Furthermore, the catabolism of UDP-hexosamine was more active for S10 than

305

that for S8 and the lower concentration of PS might be degraded for S10 (details were

306

presented in Text S12).

307

Except for PN and PS, phospholipids are the other important components of

308

microorganism EPS and have an important role in determining the hydrophobicity.5

309

Although there were many types of lipids detected, only phosphatidylcholine (PtC)

310

and phosphatidylethanolamine (PtE) biosynthesis pathways were relatively intact. The

311

intensities of phosphocholine (PC) and phosphoethanolamine (PE), which are the

312

precursors of PtC and PtE, respectively, varied unceasingly with the reactor start-up.

313

Integrating the results of FTIR analysis, the PtE that was formed by the reaction of PE

314

decarboxylation was supposed to be the dominant content of extracellular

315

phospholipids instead of PtC (details were presented in SI Text S13).

316

Discussion

317

Increased extracellular PN/PS improves anammox sludge aggregation capacity.

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To our best knowledge, this is the first to present the aggregation capacity of

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anammox consortia through the microbial and metabolome analysis during reactor

320

start-up, as aggregation capacity is important for anammox sludge retention and

321

accelerating anammox reactor start-up. The anammox process can be proved through

322

the bacterial community structure and nitrogen conversion ratios. Although both of

323

△NO2-–N/△NH4+–N and△NO3-–N/△NH4+–N did not completely conform with the

324

theoretical value of anammox process, they both agreed well with the anammox

325

process during bioreactor start–up.37 This was because an almost pure free-cells

326

suspension of highly active anammox was used to calculate the stoichiometry of

327

anammox process as described previously, but several other species of bacteria were

328

present in the anammox consortia community in the bioreactor.38 EPS, a complex

329

organic macromolecule mixture of polymers, is accountable for organism cohesion.5,15

330

Since PN and PS were predominantly present in EPS and the summation of these two

331

components concentration was regarded as the EPS concentration, the PN and PS

332

concentrations of EPS could focally affect the surface characteristics of anammox

333

consortia.14

334

Here, we first presented that the ratio of extracellular PN/PS showed a stronger

335

positive correlation with aggregation capacity of anammox consortia, which indicated

336

that it played more potentially important role in affecting the aggregation capacity.

337

Though it has been reported that PN, PS and PN/PS ratio all could determine the

338

microorganism aggregation,5-11 here, the aggregation capacity had a more strongly

339

and significantly positive relationship with the PN/PS ratio. Furthermore, the 16


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aggregation capacity increased while the extracellular hydrophobic compositions and

341

interaction increased. Therefore, we supposed that the anammox aggregation was

342

determined by the hydrophobic components and force, which agreed with the results

343

of previous studies.8,39 As the aggregate caused by hydrophobic force that is a

344

hydrogen band in the micro-scale28 had more tight structure that could prevent oxygen

345

pervasion into the interior of aggregates1 than that caused by the alginate PS that

346

contains the diamond-shaped holes.6 The abundance of PN, as well as PS, affected the

347

hydrophobicity. Hence, the higher PN/PS ratio resulted from the metabolism of EPS

348

(detailed discussion in 4.2, 4.3 and 4.4), and not the individual PN or PS

349

concentration, contributed more to the anammox aggregates.

350

Active PN metabolism increases the bacterial aggregation capacity.

351

Considering that the bacterial community structure was relatively stable in different

352

phases and the aggregation capacity and EPS components varied constantly, the shift

353

in microbial community was not the only cause for the variations observed in the

354

aggregation capacity and EPS composition. Variations in the EPS composition also

355

corresponded with the metabolites. Additionally, all metabolites from the entire

356

biomass were extracted. Some identified metabolites from the inner of the aggregates

357

that contain the inert biomass may not contribute towards surface aggregation.

358

However, it has been reported that in microorganisms, the cell-free channel structures

359

were a strategy to transport metabolites from inner aggregation to the surface.40

360

Therefore, all identified metabolites from different layers of aggregates were assumed

361

to have the same contribution for surface aggregation. 17



362

Page 18 of 43

In this study, the concentration of PN changed greatly, and those of S1 (inoculum),

363

S4 (end of Phase I), S5and S6 (initial of phase II) consortia were relatively lower than

364

those of other samples. The low protein concentration of S1 may have been caused by

365

enzyme hydrolysis when stored at 4 °C.41 The lower content of the other samples may

366

be attributed to the operational stage. Previous studies have shown that the EPS

367

composition of the same sludge is dynamic in different operational phases.42

368

Interestingly, the PN concentration of anammox consortia was relative lower for S4,

369

S5 and S6. Since there was a marked increase in the biomass concentration from S4 to

370

S6, this period was considered as the propagation phase (SI Figure S11). There are

371

different theories about the variation in bacterial extracellular PN in this phase. It has

372

been found that the PN concentration increased for hydrogenotrophic methanogens,43

373

while it was decreased for Rhodopseudomonas acidophila.44 In this study, the

374

reduction in the PN composition of anammox consortia was caused by the amino

375

acids for PN biosynthesis being used for cell growth and reproduction. Here, we

376

proposed that the main amino acids to synthesize protein included Phe, Leu, Ala, Thr,

377

Gly, Glu, and Val based on the Pearson correlation analysis. In addition, the

378

abundance of Gly, Glu, and Thr, which were selected on the basis of the correlation

379

analysis, was relatively lower in the hydrolysates of extracellular proteins. This may

380

be because amino acids were used as carbon and energy sources by heterotrophic

381

bacteria.1 Firstly, the intensities of these seven amino acids were significantly lower

382

for S5 compared to the other three samples (S3, S8 and S10) and led to a decrease in

383

PN production at this stage. Secondly, the possible participant in other roles of these 18


Page 19 of 43


384

amino acids in metabolism including the biosynthesis of nucleotide sugar45-47 and

385

phospholipids48,49 could also cause a further decrease in excretion in propagation

386

phase (detailed discussion in 4.3, 4.4 and SI Text S14). Therefore, Phe, Leu, Ala, Thr,

387

Gly, Glu and Val were supposed to be the dominant residues of extracellular PN, and

388

their low concentrations for the synthesis of extracellular PN contributed to the low

389

aggregation capacity.

390

Furthermore, the average PN concentration of phase I was significantly lower than

391

that of phase II, especially than that of the end of phase II. These results might be

392

caused by the energy metabolism of anammox consortia to adapt to the environment

393

changes. Analysis of the purine metabolic pathway revealed that the intensities of

394

metabolites required for ATP synthesis, such as guanosine and AMP, were all higher

395

in S3 (phase I) than those in S8 and S10 (phase II) (SI Table S5), which indicated that

396

the energy metabolism during phase I was more active than that during phase II.

397

Importantly, it has been shown that the microorganism have a distinct upregulation of

398

energy metabolism to adapt to the new environment, and maintain steady-state

399

metabolism during the stationary phase.50 Hence, compared to phase II, the anammox

400

consortia need more energy in phase I. Additionally, it has been reported that EPS

401

synthesis costs energy, and decreased EPS secretion potentially conserves energy for

402

bacterial growth.51 Consequently, the energy that is produced might be preferentially

403

used for microbial growth, rather than for PN production in phase I, which may result

404

in lower PN concentration in phase I.

405

Polysaccharides degradation and inactive UDP-hexosamine biosynthesis 19



Page 20 of 43

406

metabolism increases the bacterial aggregation capacity. Though the carbohydrate

407

structure in EPS was relatively stable, their content changed greatly and influenced

408

the characteristics of EPS.52 The results of this study agree with this finding.

409

Interestingly, the variation in PS concentration followed a periodic law, and we

410

proposed that one of the crucial reasons was the shift of PS degradation bacteria. It

411

has been shown that the Phycisphaerae classes can grow on cellobiose and

412

monosaccharides.53 Additionally, the Anaerolineaceae families have the ability to

413

degrade polysaccharides.54,55 Here, the variation in the sum of the abundance of these

414

two species also followed a periodic law and lagged behind the variation in PS. Most

415

importantly, there was a significantly negative relationship between the sum

416

abundance of these two species and the PS ratio. Just as the sugar metabolism for S10

417

was more active compared to S8, the sum of the relative abundance of these two

418

species was also higher for S10 than that for S8, which caused the PS concentration of

419

S10 to be lower than that of S8 and aggregation capacity of S10 to be higher than that

420

of S8. Therefore, these kinds of species could potentially increase the aggregation

421

capacity of anammox consortia through degrading PS. It’s also the possible reason

422

that the polysaccharides concentration and aggregation capacity changed periodically.

423

Furthermore, the biosynthesis of PS can be divided into two classes based on the

424

synthesis pathway.5,56 The first class comprises the production of

425

monopolysaccharides that are biosynthesized by the polymerization reaction of

426

monosaccharides including glucose and fructose. However, most PS is

427

heteropolysaccharides with irregular repeating units that are synthesized from a 20


Page 21 of 43


428

variety of intracellular sugar nucleotides including glucose, GlcNAc and GalNAc,

429

among others.5,56 Here, we proposed that the PS of anammox consortia was mainly

430

biosynthesized through the UDP-GlcNAc and UDP-GalNAc synthesis pathways from

431

GlcNAc and GalNAc as precursors, which is the same as the lactic acid bacteria.56 At

432

the same time, the higher PS concentration of S5 was causd by the active metabolism

433

of sugar to biosynthesize cell tissues for anammox growth and reproduction (detailed

434

discussion in SI Text S15).5,57 Additionally, some types of amino acids might also be

435

translated into glucose and hexosamine via the EMP pathway for synthesis of

436

cell-building organisms for supplementation as described previously (detailed

437

discussion in SI Text S15).17,45,46,58 Taken together, the active biosynthesis of

438

UDP-GlcNAc and UDP-GalNAc was the fundamental cause of the high content of PS

439

and also led to the low aggregation capacity.

440

Active phosphatidylethanolamine (PtE) biosynthesis metabolism benefits the

441

bacterial aggregation capacity. It is known that hydrophobic phospholipids also

442

have effects on the bacterial aggregation ability.5 As the dominant compositions of

443

phospholipids, phosphatidylcholine (PtC) and phosphatidylethanolamine (PtE) can be

444

synthesized through three routes: CDP-choline and CDP-ethanolamine (Kennedy)

445

pathways and the CDP-diacylglycerol pathway. Therein, the Kennedy pathways

446

biosynthesized PtC and PtE from phosphocholine (PC) and phosphoethanolamine (PE)

447

as precursors, respectively, while the CDP-diacylglycerol pathway synthesized

448

phosphatidylserine from CDP-diacylglycerol as a precursor.59,60 Considering the

449

variation in phospholipids metabolites and extracellular phospholipids, we proposed 21



450

that PtE might be the predominant component of extracellular phospholipids for

451

anammox consortia.

Page 22 of 43

452

Furthermore, the decreased intensities of phospholipids for consortia in phase II

453

were caused by the role and metabolism of PE and PC. Previous studies have shown

454

that PE and PC are the major components of phospholipids in most bacterial

455

membranes.20 It has been found that either PE or PC is the head-group of ladderane

456

lipids that play an important role in translocation of hydrazine in the anammoxosome

457

membrane to complete the anammox process.58,61 Hence, the metabolism of this type

458

of lipid should be active to transport the increasing hydrazine while the NRR

459

increased. Here, compared to PE, the metabolism and catabolism pathway of PC

460

became more active while the influent nitrogen concentration increased. Hence, we

461

supposed that PC instead of PE was the dominant head-group of the anammoxosome

462

membrane for anammox consortia and that the active metabolism of PC contributed to

463

the increased NRR for phase II, which was also one of the reasons for the lower PN

464

concentration.

465

Most importantly, the active metabolism of PtE could increase the aggregation

466

capacity of anammox consortia. Taking the case of S4 and S5, S4 consortia had a

467

lower PN concentration and a similar PN/PS ratio to S5. However, the aggregation

468

capacity of S4 was significantly higher than that of S5. This result was likely because

469

the active PtE metabolism in S4 contributed to the higher concentration of

470

hydrophobic lipids in EPS. Then, it contributed stronger hydrophobic interactions and

471

higher aggregation capacity for S4, which also agreed with results of the extended 22


Page 23 of 43


472

DLVO theory. Therefore, the metabolism of phospholipids was also critical to

473

bacterial aggregation capacity.

474

Significance of this study. The determination of the aggregation capacity of

475

anammox consortia during reactor start-up has an important role in achieving rapid

476

biofilm formation, reactor start-up and advancing the anammox technology

477

applications for wastewater treatment. This study, for the first time, showed that the

478

anammox aggregation capacity changed periodically and was strongly correlated to

479

the extracellular PN/PS ratio and hydrophobic functional groups that are related to the

480

periodical variation of microbial community structure and discrepant metabolism. As

481

there was a great difference in bacterial aggregation capacity among the different

482

operational phases, optimal bio-carriers with special surface characteristics such as

483

hydrophobicity and zeta potential could be designed for different phases.

484

Importantly, active metabolism of the seven amino acids and PtE biosynthesis and

485

the inactive metabolism of the two UDP-hexosamine biosynthetic pathways have the

486

potential to improve the aggregation capacity. Therefore, the accommodation capacity

487

of anammox biomass can be improved through stimulating some metabolism

488

pathways. This study is first to elucidate the variation in aggregation capacity and

489

EPS composition of anammox consortia across the operational phases of the reactor

490

based on the metabolism profile, and it provides a methodology reference for similar

491

studies.

492

23



493

Acknowledgments

494

The authors are grateful to the Foundations (NSFC No.51478006 and

495

No.JSGG20160429162015597) for financial support.

496

Supporting Information

497

Tables showing contact angle and zeta potential assay results, main bacterial taxa of

498

anammox consortia, metabolites intensities of purine pathway and pyruvate and

499

abbreviations of partial metabolites. Details of two aggregation capacity assays,

500

contact angle and zeta potential analysis, extended DLVO theory, FISH method,

501

untargeted and targeted metabolomic method, hydrolysates of extracellular proteins

502

and polysaccharides measurement methods, FTIR and XPS results, microbial

503

community shifts, sugar and glycerophospholipid vary, and discussions of amino

504

acids and nucleotide sugars. Figures illustrating the nitrogen conversion ratio,

505

aggregation capacity, aggregate diameter, FTIR and XPS analysis, extended DLVO

506

theory, FISH analysis, correlation between the amino acids and extracellular PN,

507

hydrolysates of extracellular PN and PS and biomass concentration.

Page 24 of 43

508

24


Page 25 of 43


509

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predominating in a full-scale oxidation ditch wastewater treatment plant. Microbes Environ 2016,

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31 (4), 449–455.

666

(56) Boels, I. C.; van Kranenburg, R.; Hugenholtz, J.; Kleerebezem, M.; de Vos, W. M. Sugar

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catabolism and its impact on the biosynthesis and engeneering of exopolysaccahrides production

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in lactic acid bacteria. Int. Diary J. 2001, 11, 723–732.

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(57) van Teeseling, M. C. F.; Maresch, D.; Rath, C. B.; Figl, R.; Altmann, F.; Jetten, M. S. M.;

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Messner, P.; Schäffer, C.; van Niftrik, L. The S-layer protein of the anammox bacterium Kuenenia

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stuttgartiensis is heavily O-Glycosylated. Front. Microbiol. 2016, 7, 1–10.

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(58) Strous, M.; Pelletier, E.; Mangenot, S.; Rattei, T.; Lehner, A.; Taylor, M. W.; Horn, M.;

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Daims, H.; Bartol-Mavel, D.; Wincker, P. Barbe, V.; Fonknechten, N.; Vallenet, D.; Segurens, B.;

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Schenowitz-Truong, C.; Medigue, C.; Collingro, A.; Snel, B.; Dutilh, B. E.; Op den Camp, H. J.

675

M.; van der Drift, C.; Cirpus, I.; van de Pas-Schoonen, K. T.; Harhangi, H. R.; van Niftrik, L.;

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Schmid, M.; Keltjens, J.; van de Vossenberg, J.; Kartal, B.; Meier, H.; Frishman, D.; Huynen, M.

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A.; Mewes, H. W.; Weissenbach, J.; Jetten, M. S. M.; Wagner, M.; Le Paslier, D. Deciphering the

678

evolution and metabolism of an anammox bacterium from a community genome. Nature 2006,

679

440 (7085), 790–794.

680

(59) Gibellini, F.; Smith, T. K. The Kennedy pathway-de novo synthesis of

681

phosphatidylethanolamine and phosphatidylcholine. IUBMB Life 2010, 62 (6), 414–428.

682

(60) P Pessi, G.; Kociubinski, G.; Mamoun, C. B. A pathway for phosphatidylcholine biosynthesis

683

in Plasmodium falciparum involving phosphoethanolamine methylation. Proc. Natl. Acad. Sci. U.

684

S. A. 2004, 101 (16), 6206–6211.

685

(61) Chaban, V. V.; Nielsen, M. B.; Kopec, W.; Khandelia, H. Insights into the role of cyclic

686

ladderane lipids in bacteria from computer simulations. Chem. Phys. Lipids 2014, 181, 76–82.

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688

Figure captions

689

Figure 1. Nitrogen concentration profile and removal rate during anammox reactor

690

start-up: (a) NH4+-N, NO2--N and NO3--N concentrations in the influent and effluent

691

in phase I (days 1-90) and phase II (days 91-210). (b) NH4+-N and NO2--N removal

692

efficiency, as well as nitrogen removal rate in two phases.

693

Figure 2. (a) The aggregation capacity for ten anammox consortia samples during the

694

reactor start-up. S1-S10 represent that the inoculum samples and the samples obtained

695

on day 30, 60, 90, 120, 150, 165, 180, 195, and 210, respectively. Red, green and blue

696

columns indicate the samples in inoculum, phase I and phase II, respectively. (b) The

697

extracellular proteins (red columns) and polysaccharides (grey columns) contents and

698

the ratio of protein to polysaccharides (blue columns) of anammox consortia in

699

inoculum, phase I and phase II. Error bars represent standard deviations of triplicate.

700

(c), (d) and (e) show the correlation relationships between the sludge aggregation

701

capacity and the concentration of extracellular PN, PS and PN/PS ratio, respectively.

702

The red open circles depict the value of these three indexes. The dark grey lines

703

indicate fitted linear models with confidence intervals of 0.95 (light grey lines), which

704

were established by the Pearson correlation analysis. P < 0.05 was considered

705

statistically significant in all statistical analysis.

706

Figure 3. Total energy of the interaction (WT) vs. separation distance curves of

707

anammox consortia samples of (a) inoculum (S1), (b) phase I (S2-S4), (c) phase II

708

(S5-S10) calculated by extended DLVO theory. The electric double layer (WR), the 34


Page 35 of 43


709

van der Waals energies (WA) and the acidbase interaction (WAB) vs. separation

710

distance curves were presented in SI Figure S4.

711

Figure 4. (a)Heatmap showing relative abundance of 47 kinds of predominant

712

bacterial community types (phyla with more than 1% relative abundance) detected in

713

samples from inoculum and two phases. The detailed taxonomy was presented in SI

714

Table S3. (b) Principal component analysis (PCA) plot of bacterial taxa of anammox

715

consortia among different phases. Red, green and blue colonization-specific clustering

716

indicates the samples of inoculum, phase I and phase II, respectively. (c) The

717

correlation relationship between the sum relative abundance of the Phycisphaerae

718

classes and the Anaerolineaceae families and the ratio of extracellular

719

polysaccharides in the sum of extracellular proteins and polysaccharides. Correlation

720

relationship was assessed by the Pearson analysis. The dark grey lines indicate fitted

721

linear models with confidence intervals of 0.95 (light grey lines). P < 0.05 was

722

considered statistically significant.

723

Figure 5. (a) The heatmap showing relative abundance of metabolites in four samples

724

(S3, S5, S8 and S10) determined by the untargeted and targeted metabolomic analysis.

725

S3, S5, S8 and S10 represented the samples obtained on day 60, 120, 180 and 210,

726

respectively. Each column represents one biological replicate and every sample was

727

conducted in triplicate. (b) PCA analysis plot of anammox consortia metabolites in

728

four samples. (c) (d) and (e) represent metabolic pathway of amino acids,

729

polysaccharides and glycerophospholipid. Red, green, blue and purple circle represent

730

the metabolite intensity of the samples obtained on day 60 (S3), 150 (S5), 180 (S8) 35



Page 36 of 43

731

and 210 (S10), respectively. The different circle’s diameter represents the different

732

metabolite intensity. And the metabolite intensity of S3 was used as a control with the

733

fixed diameter. The circle’s diameters of other three samples were same as that of S3

734

when the metabolites intensities changed no significance, and were bigger or smaller

735

than that of S3 when the metabolites intensities were significantly increased or

736

decreased, respectively (P < 0.05). The solid lines represent the intracellular

737

metabolic pathways, and the dotted lines represent the supposed extracellular

738

metabolic pathways.

739

36


Page 37 of 43


740 741

Figure 1. Nitrogen concentration profile and removal rate during anammox reactor

742

start-up: (a) NH4+-N, NO2--N and NO3--N concentrations in the influent and effluent

743

in phase I (days 1-90) and phase II (days 91-210). (b) NH4+-N and NO2--N removal

744

efficiency, as well as nitrogen removal rate in two phases.

37



Page 38 of 43

745 746

Figure 2. (a) The aggregation capacity for ten anammox consortia samples during the

747

reactor start-up. S1-S10 represent that the inoculum samples and the samples obtained

748

on day 30, 60, 90, 120, 150, 165, 180, 195, and 210, respectively. Red, green and blue

749

columns indicate the samples in inoculum, phase I and phase II, respectively. (b) The

750

extracellular proteins (red columns) and polysaccharides (grey columns) contents and

751

the ratio of protein to polysaccharides (blue columns) of anammox consortia in

752

inoculum, phase I and phase II. Error bars represent standard deviations of triplicate.

753

(c), (d) and (e) show the correlation relationships between the sludge aggregation

754

capacity and the concentration of extracellular PN, PS and PN/PS ratio, respectively.

755

The red open circles depict the value of these three indexes. The dark grey lines

756

indicate fitted linear models with confidence intervals of 0.95 (light grey lines), which

757

were established by the Pearson correlation analysis. P < 0.05 was considered

758

statistically significant in all statistical analysis.

759 38


Page 39 of 43


760

761

Figure 3. Total energy of the interaction (WT) vs. separation distance curves of

762

anammox consortia samples of (a) inoculum (S1), (b) phase I (S2-S4), (c) phase II

763

(S5-S10) calculated by extended DLVO theory. The electric double layer (WR), the

764

van der Waals energies (WA) and the acidbase interaction (WAB) vs. separation

765

distance curves were presented in SI Figure S4.

766

39



Page 40 of 43

767 768

Figure 4. (a)Heatmap showing relative abundance of 47 kinds of predominant

769

bacterial community types (phyla with more than 1% relative abundance) detected in

770

samples from inoculum and two phases. The detailed taxonomy was presented in SI

771

Table S3. (b) Principal component analysis (PCA) plot of bacterial taxa of anammox

772

consortia among different phases. Red, green and blue colonization-specific clustering

773

indicates the samples of inoculum, phase I and phase II, respectively. (c) The

774

correlation relationship between the sum relative abundance of the Phycisphaerae

775

classes and the Anaerolineaceae families and the ratio of extracellular

776

polysaccharides in the sum of extracellular proteins and polysaccharides. Correlation

777

relationship was assessed by the Pearson analysis. The dark grey lines indicate fitted

778

linear models with confidence intervals of 0.95 (light grey lines). P < 0.05 was

779

considered statistically significant.

780 40


Page 41 of 43


781 782

Figure 5. (a) The heatmap showing relative abundance of metabolites in four samples

783

(S3, S5, S8 and S10) determined by the untargeted and targeted metabolomic analysis.

784

S3, S5, S8 and S10 represented the samples obtained on day 60, 120, 180 and 210,

785

respectively. Each column represents one biological replicate and every sample was

786

conducted in triplicate. (b) PCA analysis plot of anammox consortia metabolites in

787

four samples. (c) (d) and (e) represent metabolic pathway of amino acids,

788

polysaccharides and glycerophospholipid. Red, green, blue and purple circle represent

789

the metabolite intensity of the samples obtained on day 60 (S3), 150 (S5), 180 (S8) 41



Page 42 of 43

790

and 210 (S10), respectively. The different circle’s diameter represents the different

791

metabolite intensity. And the metabolite intensity of S3 was used as a control with the

792

fixed diameter. The circle’s diameters of other three samples were same as that of S3

793

when the metabolites intensities changed no significance, and were bigger or smaller

794

than that of S3 when the metabolites intensities were significantly increased or

795

decreased, respectively (P < 0.05). The solid lines represent the intracellular

796

metabolic pathways, and the dotted lines represent the supposed extracellular

797

metabolic pathways.

798

42


Page 43 of 43


799

TOC/Abstract graphic

800 801

For Table of Contents Only

802

43


Insight into the Aggregation Capacity of Anammox Consortia during

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