Metabolomics Uncovers the Regulatory Pathway of Acyl-homoserine

Jan 29, 2018 - For phenotypic data, analysis of variance (ANOVA) with a post hoc test by Dunnett's multiple comparison was conducted using the statist...
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Metabolomics uncovers the regulatory pathway of acylhomoserine lactones-based quorum sensing in anammox consortia Xi Tang, Yongzhao Guo, Shanshan Wu, Liming Chen, Huchun Tao, and Sitong Liu Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b05699 • Publication Date (Web): 29 Jan 2018 Downloaded from http://pubs.acs.org on January 30, 2018

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Metabolomics uncovers the regulatory pathway of acyl-homoserine

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lactones-based quorum sensing in anammox consortia

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Xi Tang1,2, Yongzhao Guo1,3, Shanshan Wu1,2, Liming Chen1,2, Huchun Tao3, Sitong Liu*1,2,3

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China

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College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China

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School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055,

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China

Key Laboratory of Water and Sediment Sciences, Ministry of Education of China, Beijing 100871,

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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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Tel/Fax: 0086-10-62754290.

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E-mail: [email protected]

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Abstract

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Acyl-Homoserine Lactones (AHLs)-mediated quorum sensing in bacterial communities have been

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extensively observed. However, the metabolic pathways regulated by AHLs in bacteria remain elusive.

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Here, we combined long-term reactor operation with microbiological and metabolomics analyses to

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explore the regulatory pathways for different AHLs in anammox consortia, which perform promising

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nitrogen removal for wastewater treatment. The results showed that no obvious shifts induced by

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exogenous AHLs occurred in the microbial community and, mainly, dosing AHLs induced changes in

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the metabolites. 3OC6-HSL, C6-HSL and C8-HSL controlled the electron transport carriers that

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influence the bacterial activity. In contrast, only 3OC6-HSL regulated LysoPC(20:0) metabolism,

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which affected bacterial growth. AHLs mainly regulated the synthesis of the amino acids Ala, Val, and

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Glu, as well as selectively regulated Asp and Leu to affect extracellular proteins. Simultaneously, all

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the AHLs regulated the ManNAc biosynthetic pathways, while OC6-HSL, OC8-HSL and C6-HSL

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particularly enriched the UDP-GlcNAc pathway to promote exopolysaccharides, resulting in different

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aggregation levels of the anammox consortia. Our results not only provide the first metabolic insights

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into the means by which AHLs affect anammox consortia but also hint at potential strategies for

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overcoming the limitations of the long start-up period required for wastewater treatment by anammox

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processing.

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Key words: anammox; nitrogen removal; quorum sensing; metabolomics; acyl homoserine lactone

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Introduction Quorum sensing (QS) communication among bacteria is one of the most important discoveries in

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the field of microbial research in the past 20 years. Acyl-homoserine lactones (AHLs) have been

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found to be used by gram-negative bacteria as common signaling molecules and are involved in the

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regulation of biofilm formation and other properties1,2. So far, more than 37 genera of gram-negative

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bacteria have been identified that are regulated by AHLs signaling molecules3. In recent years,

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researchers have utilized AHLs-based quorum sensing in wastewater treatment to enhance sludge

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aggregation and the environmental stress resistance of microorganisms4,5. Undoubtedly, AHLs offer

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new approaches to solving problems related to biological wastewater treatment.

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Anammox has attracted much attention recently as a high-efficiency, energy-saving approach for

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nitrogen removal from wastewater6,7. It can achieve autotrophic ammonium conversion into nitrogen

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gas with nitrite as the electron acceptor via the bio-catalysis of anammox bacteria8. Although many

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anammox reactors have been built on a pilot scale, an additional bottleneck still remains6. The slow

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growth rate and strict metabolic conditions of anammox bacteria make start-up of the reactor difficult9.

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Researchers have attempted to enhance the bacterial activity and viability to achieve faster a more

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rapid start-up using various methods, such as applying bacterial carriers, choosing a suitable

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bioreactor type and seeding sludge10–12. These methods do not essentially regulate the metabolism of

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anammox bacteria, and the problem of the required long start-up time for anammox process still

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persists13–16.

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AHLs can regulate the expression of key genes in bacteria, thereby enhancing their activity,

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proliferation, viability and aggregation17. Different AHLs have disparate regulatory pathways18. For

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example, a combination of three AHLs (3OC6-, C6- and C8-HSL) controls the maltose fermentation

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pathway and the glyoxylate bypass to regulate bacterial growth with specific substrates in Yersinia

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pestis19. C8-HSL has been shown to regulate glucose uptake, pentose phosphate pathway and de novo

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nucleotide biosynthesis via the activation of QsmR in Burkholderia glumae to enable survival20. 3

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However, the identification of AHL-regulated metabolism is still limited and almost all the related

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studies focus on single bacterial strains. In complex bacterial communities, it is more difficult to

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uncover the regulatory mechanism of AHLs. Very recently, metabolomic analysis has been applied in

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many phylogenetically highly diverse and complex communities to reveal their metabolic activity and

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changes in the metabolic pathways20–22. Although the phenomenon of AHL-mediated QS regulation

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has been reported23, the AHL-regulated metabolic pathways in anammox consortia remain unexplored.

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Thus, it would be significant to employ recently developed metabolomics to reveal the regulatory

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pathway of AHLs-based QS in anammox consortia.

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In this study, we used six Sequencing Batch Reactors (SBRs), one as a control and others that were

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treated with five different AHLs, respectively. The AHLs-regulated metabolic pathways in the

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anammox consortia were explored by metabolomics and relevant phenotype monitoring. The first

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metabolically regulated pathways for enhancing bacterial aggregation, activity and growth rate

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modulated by different AHLs, were identified in the anammox consortia. These results suggest the

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potential for developing strategies based on AHLs to overcome the required long start-up periods of

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anammox process in wastewater treatment.

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Material and methods

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Bioreactor operation

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Six identical SBRs with working volumes of 1.0 L were operated at 37°C for 90 days. The influent

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of these SBRs was synthetic wastewater, described previously24. One reactor (R1) was incubated

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without AHLs as a control, while the remaining five reactors (R2-R6) were regarded as treatment

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groups, dosing with 2 µM 3OC6-HSL (N-(3-oxohexanoyl)-DL-homoserine lactone), 3OC8-HSL

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(N-(3-oxooctanoyl)-DL-homoserine lactone), C6-HSL (N-hexanoyl-DL-homoserine lactone), C8-HSL

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(N-octanoyl-DL-homoserine lactone), and C12-HSL (N-dodecanoyl-DL-homoserine lactone), which

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were obtained from Sigma (St. Louis, MO, USA) (Figure S1a). The dosing concentration was

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determined as described previously 20. The anammox consortia, mainly composed of Candidatus 4

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Jettenia23, were seeded into the reactors with an initial biomass concentration of 0.18 gVSS L-1

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(Figure S2). Detailed information operation are described in the supplemental material.

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The concentrations of NH4+-N and NO2--N in the influent were maintained at 240 mg L-1 and 200

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mg L-1, respectively, with the highest concentration in the reactor was basically less than 100 mg L-1.

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It is a common operation strategy of SBR for anammox consortia with high concentrations of

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NO2--N25–27 and was not toxic to the anammox bacteria. Hydraulic Retention Time (HRT) was set to

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12 h on the initial day. When NO2--N concentration in the effluent dropped below 10 mg L-1, HRT was

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shortened to increase the nitrogen loading rate. It was decreased to 8 h, and then to 6 h. The reactor

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loading rate was not increased in the later period of reactor operation (day 67 to 90), in order to study

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the potential effects of AHLs on nutrient-deficient anammox consortia (Figure S1b). Nitrite was the

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limiting substrate mainly responsible for nutrient-deficiency in the anammox consortia. The influent

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and effluent were collected every 2 days for NH4+-N, NO2--N, and NO3--N analysis. Biomass samples

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were harvested from the six reactors every 15 days for analysis of the particle size, Volatile Suspended

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Solids (VSS), and Extracellular Polymeric Substances (EPS). The Specific Anammox Activities

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(SAAs), biomass yield rate, and microbiome and metabolome profiles were analyzed using the

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biomass in the six reactors on day 30 and 90 of the reactor operation. To address the reproducibility of

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the experiment, six identical reactors (same as the reactors described above) were operated and the

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details are presented in the supplemental material.

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Chemical Analysis and EPS determination

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The concentrations of NH4+-N, NO2--N, and NO3--N, as well as VSS, were measured using the

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standard methods of the American Public Health Association (APHA, 1998). The total nitrogen (TN)

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was measured using a TN analyzer (IL500, HACH, USA). The pH was obtained using a pH meter

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(Mettler Toledo, Columbus, OH, USA). The biomass yield rates of the anammox consortia during the

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reactor operation were calculated following the methods of previous studies28,29. Briefly, they were

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calculated from the biomass yield, taking the VSS increase as the main characterization parameter.

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The experiments were performed in triplicate to obtain average values. The SAAs were determined by 5

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a batch test according to methods described previously30 and the experimental details are described in

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the supplemental material. Floc sizes were measured in triplicate using a laser particle size analyzer (Mastersizer MS2000,

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Malvern Instruments, Malvern, UK) with a detection range of 0.02–2000 µm. The median diameter of

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floc was chosen to represent the floc size in the reactor. Additionally, the EPS extractions were

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performed using Cation Exchange Resin (CER), as proposed by Hou et al.31, such that the release of

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intracellular substances could be neglected32. Extracellular Polysaccharide (PS) and protein (PN)

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concentrations were quantified using the anthrone method with glucose as a standard and the Lowry

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method with bovine serum albumin as a standard, respectively33. Both the PS and PN results were the

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average value of three parallel samples. To monitor the microbial community shifts during the 90 days

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of operation, DNA extraction and 16S rRNA gene sequencing analysis were performed. The detailed

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methods are presented in the supplemental materials.

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Extraction and identification of AHLs The identification of AHLs released by the anammox consortia was performed before the

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inoculation. AHLs were extracted from the supernatant of the anammox consortia23. Briefly, 200 ml of

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the supernatants were extracted twice with an equal volume of ethyl acetate and 0.1% (v/v) formic

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acid. The ethyl acetate extracts were concentrated and re-suspended in 200 µL of acetonitrile before

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analysis. All the samples were analyzed by LC-MS (Q Exactive orbitrap Thermo, CA) and the details

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are described in the supplemental material.

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Metabolite extraction and profiling

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The biomass samples for metabolite analysis were collected in triplicate to investigate variations in

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the bacterial metabolic profiles. These samples were quenched and extracted, as described previously

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methanol at –40°C. The biomass was separated from the quenching solution by immediate

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centrifugation at 9,000 g for 10 min at –20°C. The pellet was re-suspended in 5 mL of 80% cold

. The biomass samples were quickly harvested, washed, and quenched using 60% (v/v) cold

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methanol and sonicated at 200 W for 30 min in an ice bath. Afterwards, the supernatants were

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harvested after centrifugation of the lysates at 10,000 g for 20 min. To purify the metabolites, the

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samples were dried under a nitrogen flow at room temperature (25°C) for metabolomic analysis. The

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mass spectrometry data were collected using a Q Exactive mass spectrometer (Thermo Fisher,

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Waltham, MA, USA). The details are presented in the Supplemental materials.

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In addition, to investigate the potential relationship between the intracellular amino acids and the

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extracellular PN, fifteen biomass samples taken from the control reactor on different operation days

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(the sampling days are described in Table S1) were collected to measure their intracellular amino acids

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and PN. Separation of cells from the EPS was conducted by stripping the EPS from the biomass using

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CER. The extraction method and the quantification of intracellular amino acids were the same as that

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for the metabolites. The determination of the extracellular PN of these samples was also performed as

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described above.

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Statistical analysis

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For phenotypic data, Analysis of Variance (ANOVA) with a post hoc test by Dunnett’s multiple

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comparison was conducted using the Statistical Product and Service Solutions (SPSS) software to

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determine the differences between the biomass dosed with AHLs and the control without any AHL

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treatment. SPSS was also used to build a multiple regression model for investigating the relationship

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between the intracellular amino acids and extracellular PN.

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For the microbial community data, Non-metric Multidimensional Scaling (NMDS) was used to

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reduce the community data complexity and assess the community similarity among all the samples

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using the R statistical environment (version 3.2.2) based on Bray–Curtis similarities35. The abundance

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of selected genera was visualized as a 100% stacked column.

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For metabolomic data, log-transformation followed by individual scaling (mean-centered and

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divided by the standard deviation of each variable) was applied initially. Next, multivariate statistical

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analysis and pathway analysis were performed with Mev 4.9.0 (MultiExperiment Viewer) and 7

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MetaboAnalyst 3.036, and hierarchical clustering was performed using Pearson distance as the distance

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measure. The metabolites were then filtered to identify significantly different metabolites using

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ANOVA with a Dunnett’s multiple-comparison test between the biomass dosed with AHLs and the

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control. Metabolic features with p1.5 were considered to be significantly

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different37. Thus, significant metabolites from each comparison were identified and analyzed in detail.

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Results

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AHLs increased reactor performance

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First we identified the release of 3OC6-HSL, 3OC8-HSL, C6-HSL, C8-HSL, and C12-HSL by

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anammox consortia (Figure S3). To investigate whether reactor performance could be improved by

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these exogenous AHLs, 2 µM of 3OC6-HSL, 3OC8-HSL, C6-HSL, C8-HSL, and C12-HSL were

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added to the influent of treatment reactors R2, R3, R4, R5 and R6, respectively. The nitrogen removal

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rates (NRRs) of the six reactors over 90 days of operation are recorded in Figure 1 and S4. Based on

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the fold-changes in the NRRs of all the treatment reactors compared to the control without addition of

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AHLs, the reactor operation was divided into three phases.

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During phase I (the first 16 days), the NRR of the control reactor increased from 0.6 to 0.8 gN L-1

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day-1. The fold-changes of the NRRs of all the treatment reactors (except for the reactor treated with

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C12-HSL) were close to 1, indicating that the addition of AHLs (with the exception of C12-HSL) did

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not significantly affect the NRRs. Phase II (days 17–66) was characterized by a dramatic increase in

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the fold-changes of the NRRs. The NRR of the control reactor increased from 0.8 to 1.4 gN L-1 day-1.

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Following the addition of 3OC6-HSL, C6-HSL, and C8-HSL, the average value of the fold-changes in

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the NRR of reactors with additional AHLs compared to that of the control reactor during phase II was

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1.14, 1.10, and 1.10, respectively. That is, 3OC6-HSL, C6-HSL, and C8-HSL significantly increased

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the NRRs by 14%, 10%, and 10%, respectively, compared to that in the control (p