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Response of microbial community structures and functions of nitrosifying consortia to bio-refractory humic substances Xiaonan Luo, Luwei Shen, and Fangang Meng ACS Sustainable Chem. Eng., Just Accepted Manuscript • Publication Date (Web): 17 Jan 2019 Downloaded from http://pubs.acs.org on January 17, 2019

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ACS Sustainable Chemistry & Engineering

Response of microbial community structures and functions of nitrosifying consortia to bio-refractory humic substances

Xiaonan Luo †,‡ , Luwei Shen†,‡ and Fangang Meng†,‡*

†

School of Environmental Science and Engineering, Sun Yat-sen University,

Guangzhou 510275, PR China ‡

Guangdong Provincial Key Laboratory of Environmental Pollution Control and

Remediation Technology (Sun Yat-sen University), Guangzhou 510275, China

*

Corresponding author

Fangang MENG, Ph.D. Email: [email protected] Tel.: 86-20-39335060 Address: Sun Yat-sen University, NO. 132, Outer Ring East Road, Higher Education Mega Center, Panyu District, Guangzhou, Guangdong province, China.

1

ACS Paragon Plus Environment

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Abstract: Bio-refractory humic substances (HS) that are ubiquitously present in nitrogen-rich wastewater streams, such as landfill leachate and livestock waste after anaerobic digestion, can potentially impact nitritation-anammox processes. In this study, multiple sequencing methods (e.g., 16S rRNA sequencing, clone library analysis and metagenome sequencing) were employed to reveal the response of nitrosifying microbiota to HS at various concentrations (0-50 mg/L). Long-term reactor operation revealed that the nitrite yield was overall stable during all of the experimental days; however, fluctuations were observed as a result of sudden HS loads. The characterization by 16S rRNA sequencing indicated a decreased abundance of the phylum Proteobacteria (from 90.8% in HS0 to 52.1% in HS50) and an increased abundance of the phylum Bacteroidetes (from 4.7% in HS0 to 35.3% in HS50) upon exposure to HS. Both 16S rRNA sequencing and metagenome sequencing revealed that the family Nitrosomonadaceae, which was dominated by the genus Nitrosomonas, dramatically decreased, i.e., from ca. 70% in HS0 to ca. 40% in HS50. Both amoAbased clone libraries and metagenome sequencing suggested a substantial shift of AOB species, e.g., the emergence and enrichment of Nitrosomonas mobilis upon exposure to HS. Interestingly, the amoABC gene was initially inhibited by 5 mg/L HS and then recovered at a higher level of HS (50 mg/L). In comparison, levels of hao gene were reduced with increasing HS (0, 5 and 50 mg/L). In addition, the abundance of genes assigned to membrane transport decreased after the addition of HS, and this reduction 2


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was likely associated with the electron shuttle roles of HS. Overall, the findings of this study provide insights into the response of core species and key genes to HS in nitritation systems. Keywords: Nitritation; Humic substances; Microbial community; Ammoniumoxidizing bacteria; Functional genes

Introduction The nitritation process has been established as a prerequisite for emerging nitrogen removal processes

1-5.

The combined nitritation-anammox processes potentially

achieve energy neutrality and resource positivity as they have minimum aeration and smaller carbon footprints 6. In such integrated processes, the performance of the nitritation system providing nitrite for anammox bacteria is very important 7. Thus, aerobic ammonium-oxidizing bacteria (AOB) play an essential role in the successful application of nitritation-anammox processes 8-11. Given the potential competition between heterotroph and AOB or anammox bacteria, successful operation of nitritation and subsequently anammox processes for treating wastewater both requires a low content of bio-available organic matter in feeding wastewater

12.

As such, the streams of ammonium-rich wastewater, such as

landfill leachate, livestock waste and monosodium glutamate wastewater, are first subjected to anaerobic digestion to remove bio-available organic matter and produce 3



biogas such as CH4

13, 14.

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Upon anaerobic digestion, the organic matter in these

ammonium-rich wastewater streams is mainly composed of recalcitrant organics (e.g., HS) due to the humicfiaction of organic matter15. In addition, the influent also contains a fraction of recalcitrant organics. Humic acids and fulvic acids represent 4%-44% and 7%-72% of the organic matter in landfill leachate, respectively

16, 17.

It was generally

thought that the presence of recalcitrant organics does not impact the performance of nitritation processes, i.e., ammonium removal rates and nitrite accumulation rate. Nevertheless, it should be noted that bio-refractory HS are involved in some microbial oxidation processes as electron acceptors

18

or electron shuttles

19.

For instance, the

activity and abundance of nitrifiers in soils were enhanced by HS due to the improved cell permeability

20.

Similarly, a sudden load of HS was demonstrated to change the

bacterioplankton community composition

21.

Also, the presence of HS promoted

microbial denitrification in engineered ecosystems by shifting the microbial community structure 22. Thus, it can be expected that the occurrence of HS in nitritation reactors can potentially shape the microbial community structure and functional genes of nitrosifying sludge. Unveiling the interactions between bio-refractory HS and AOB consortia would be of high importance for the application of nitritation-based processes. To our knowledge, this is the first work focusing on the roles of bio-refractory HS in nitritation processes. Currently, high-throughput sequencing techniques are being actively used for 4


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characterization of bacterial communities in wastewater treatment facilities

23-27.

In

addition, 16S rRNA gene amplicon sequencing can provide a snapshot of the overall microbial community within a relatively short time and at a low cost; however, the process offers a low taxonomic resolution at the species level 28, 29. Sequences obtained via clone library analysis are long enough to discover microbial diversity and to make predictions at the species level 30. However, the generation of a clone library is quite costly and time consuming. Crucially, both high-throughput sequencing and the generation of clone libraries largely rely on the primer pairs used 31, 32 and are limited in addressing microbial functions and metabolic pathways

33.

Comparatively,

metagenome sequencing bypasses the need for amplification by primers and offers a comprehensive study of functional potentials in complex microbial systems

34.

As

expected, the combined use of these sequencing techniques provides an integrated understanding of microbial community structures and functional potentials 33, 35, 36. Therefore, the overall goal of this study was to investigate changes in the structural and functional diversification of AOB consortia upon exposure to HS-containing wastewater in the nitritation process. The changes in the microbial community structures in response to HS were analyzed by high-throughput 16S rRNA gene sequencing and metagenome sequencing. Meanwhile, the effect of HS on the AOB species and/or functional genes were investigated by a clone library and metagenome sequencing. Overall, this study could provide a comprehensive baseline for the 5



understanding of AOB species and their key genes in response to HS exposure, which would aid in the application of nitritation-based processes.

Materials and methods Setup and operation of the nitritation MBR A nitritation MBR with a working volume of 5.0 L was seeded with activated sludge harvested from a local wastewater treatment plant treating domestic wastewater. A hollow fiber membrane module (0.1 μm, 0.1 m2, PVDF, Litree Corp., Suzhou, China) was submerged in the reactor. The solid retention time (SRT) was set at approximately 30 days by manually discharge the sludge every day. The reactor was operated at a temperature of 30±2°C. The membrane module was sucked by a pump in continuous mode with a fixed membrane flux of 5 L/m2 h (LMH), which achieved a hydraulic retention time (HRT) of 10 h. DO concentrations were maintained in a range of 0.2 to 0.4 mg/L via a DO controller system (6309PDT, JENCO, USA) equipped with an air compressor. The trans-membrane pressure (TMP) was monitored by a pressure gauge. When the TMP reached approximately 0.015 MPa, the fouled membrane model was washed by pressurized water before day 180. From days 180-392, the fouled membrane was washed by pressurized water followed by soaking in a 0.3% NaClO solution for 12 h.

6


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The synthetic wastewater used as the feed solution consisted of 300 mg-N/L (NH4)2SO4, 8000 mg/L NaHCO3, 5 mg/L KH2PO4, and 1 mL/L trace element solution (5.0 mg/L EDTA, 5.0 mg/L FeSO4·7H2O, 1.6 mg/L CoCl2·6H2O, 5.1 mg/L MnCl2·4H2O, 1.6 mg/L CuSO4·5H2O, 5.5 mg/L CaCl2·2H2O, 2.2 mg/L ZnSO4·7H2O and 1.2 mg/L (NH4)6Mo7O24·4H2O). The HS stock solution was prepared by dissolving humic acids (sodium salt, Aladdin Co., Ltd, Shanghai, China) in pure water and applied to the reactor separately at a final concentration of 2, 5, 10, 15, 30 or 50 mg/L in the reactor using a peristaltic pump. The duration of each experimental phase was showed in Figure 1. In addition, the characteristics of HS (i.e., molecular weight distribution, hydrophobicity, FTIR, UV-vis and EEM spectra) were characterized and provided in Supporting Information (Method S1, Table S1-S2, Figure S1-S3). Determination of microbial activity Specific oxygen uptake rates (SOUR) and specific nitritation rates (SNR) were measured using a self-developed device. Details of the device and methods can be found in previous studies 37, 38. Briefly, 250 mL of mixed liquor was collected from the reactor. After filtration with filter paper (ca. 15 μm) and washing with pure water, the mixed liquor was re-suspended to 500 mL with pure water. The DO and temperature were controlled in a range of 1-2 mg/L and at 31±1°C, respectively. The pH of the sludge suspension was controlled at 8.0±0.1 with the addition of NaHCO3 solution. The oxygen uptake rate of heterotrophic bacteria (SOUROHO) was indicated by endogenous 7



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respiration. Subsequently, the oxygen uptake rates of NOB (SOURNOB) was measured with the addition of stock solution of NaNO2 to a final concentration of 10 mg N/L in the reactor, followed by the addition of 30 mg N/L ammonium (NH4Cl, final concentration) for the measurement of the oxygen uptake rate of AOB (SOURAOB). After the addition of ammonium solution described above, samples were collected at 0.5, 5, 10, 15, 20 and 25 min. The SNR was determined by the increase in nitrite concentration with operating time. DNA isolation, PCR amplification, and high-throughput sequencing Two sludge samples were collected for each HS concentration phase (except the phase without HS) and mixed together (fed with 0, 2, 5, 10, 15, 30 and 50 mg/L HS, which were defined as HS0, HS2, HS5, HS10, HS15, HS30 and HS50, respectively). The sampling time was indicated in Figure 1. DNA of each biomass sample was isolated using the Power Soil DNA Kit (MoBio Laboratories, USA) according to the manufacturer’s protocol. Subsequently, the DNA samples were quantified by a Nanodrop 1000 spectrophotometer (Thermo Scientific). The universal primer sets F515 (5’-GTGCCAGCMGCCGCGGTAA-3’)

and

R806

(5’-

GGACTACVSGGGTATCTAAT-3’) were used to amplify the V4 region of the 16S rRNA gene. The PCR mixture, amplification procedure and purification process are presented in the supporting information (Method S2). The purified PCR products were pooled at equimolar amounts prior to sequencing on an Illumina Miseq platform by the 8


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Magigene Institute (Guangzhou, China). The data were processed and analyzed following the pipeline of QIIME

39

and Mothur software

40.

The taxonomic

classifications were determined using the Ribosomal Database Project (RDP) Classifier at an 80% confidence threshold 41. Sequences with a sequence similarity of ≥97% were clustered into operational taxonomic units (OTUs) using UCLUST

42.

Microbial

richness and diversity were estimated by calculating the Chao1 richness estimate and the Shannon diversity index, respectively (Table S6). In total, 786 193 non-chimeric, quality-filtered reads were obtained from all sludge samples by partial gene sequencing of the V4 region of 16S rRNA (Table S6). All reads were clustered into 1363 OTUs. Reads in each sample ranged from 32 675 to 130 789, and OTUs ranged from 600 to 993. Cloning of the amoA gene Three samples (HS0, HS5, and HS50) were subjected to clone library construction of the amoA gene, which belongs to the class Beta-proteobacteria

43, 44,

as most of the

wastewater process relevant AOB belong to this class. DNA samples were amplified using the primer sets amoA-1F (5’-GGGGTTTCTACTGGTGGT-3’) and amoA-2R (5’-CCCCTCKGSAAAGCCTTCTTC-3’) for specific amplification of the amoA gene. PCR products were ligated into the T-vector and transferred to Escherichia coli DH5α cells for clone library construction. Protocol details are provided in the supporting information (Method S3). 9



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Positive clones were sent to The Beijing Genomics Institute (Shenzhen, China) for clone library sequencing. Raw data were assembled and screened using CodonCode Aligner

(CodonCode

Corporation,

Dedham,

MA,

USA)

and

Bioedit

(http://www.mbio.ncsu.edu/BioEdit/bioedit.html). Then, the refined sequences were classified into OTUs (≥ 97% similarity) using Mothur 45 and searched (BLAST) against the NCBI database for species annotation. In total, 219 clones (75, 78 and 66 clones for HS0, HS5, and HS50, respectively) were obtained and grouped into OTUs on the basis of ≥97% similarity (Table S9). Metagenome sequencing and analysis The three samples mentioned above (HS0, HS5, and HS50) were also subject to metagenome sequencing on the Illumina Hiseq4000 platform. Shotgun libraries were constructed with individual DNA from each sample. All raw data (paired-end reads) were filtered to eliminate adapter contamination and low-quality sequences, followed by

another

quality

control

(http://www.bioinformatics.babraham.ac.uk/projects/fastqc/).

using

FastQC

Afterward,

quality-

46.

To obtain

filtered sequences were de novo assembled with k-mers using IDBA

better assembling results, the maximum contig lengths and N50 value were chosen. Information of sequence data, assembling result, N50, L50, and number of contigs were provided in supplementary information. After the filtering and assembling steps, the cleaned sequence reads were aligned 10


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to contigs using Bowtie2 47. Contigs that had at least one read aligned were chosen to predict the open reading frames (ORFs) using MetaGeneMark with default settings 48. The coverage depth of the assembled contigs was calculated using the total number of base pairs of the reads that aligned to a contig divided by the length of the contig. The coverage depth of genes was determined using the same method. Amino acid sequences encoding proteins in ORFs were searched (BLASTP) against the NCBI NR database. After removing ‘redundant’ (or highly similar) sequences, the non-redundant protein sequences were searched (BLASTx) against the Kyoto Encyclopedia of Genes and Genomes (KEGG) database 49 for the annotation of functional genes and metabolic pathways (E-value threshold = 10-5). To ensure the biological meaning, a BLAST coverage ratio of > 40% was required for the results. In total, 30 291 contigs were obtained from all samples, in which 20 757 genes were annotated and 17 199, 19 928 and 18 755 unique genes were annotated from HS0, HS5 and HS50 samples, respectively, using the KEGG database. For species annotation, all the contigs were searched (BLAST, E-value threshold = 10-5) against the NCBI-NT database and then classified into taxonomic groups using MEGAN (version 5.3) 50. The lowest common ancestor (LCA) algorithm in MEGAN was used for the species annotation of the contigs. Analyses of different type of nitrogen concentration The concentrations of ammonium, nitrite, nitrate, and total nitrogen were determined 11



according to the standard methods from APHA 51. Samples were taken and measured twice per week. BOD5 and COD of HS (50 mg/L) was measured with the standard method 51.

Results Reactor performance After a start-up period (day 0-150), the nitritation reactor reached satisfying ammonium transformation, i.e., nitriation, over the complete course of the experimental days (day 151-392) of operation (Figure 1), with an average of 93.8 ± 6.2% for ammonium removal and 90.8 ± 7.7% for nitrite accumulation. The removal of total nitrogen was negligible, indicating that denitrification and anammox did not occur in the reactor. Fluctuations were observed for ammonium conversion during the experimental days, e.g., the ammonium removal efficiency decreased to ca. 80% on days 162 and 230. Meanwhile, FA concentrations were lower than 8 mg/L after day 150 (Figure S9) while FNA concentrations were below 0.013 mg/L over the complete course of the experimental days (Figure S10), which were both under the threshold of the reported inhibition concentration

52.

Therefore, the fluctuations of nitrogen removal could be

attributed to the HS-induced changes in bacterial activity. The SOUR of nitrosifying sludge was dramatically reduced and then recovered in each HS-dosage phase, indicating that the oxygen uptake rates by nitrosifying consortia were impacted by the 12


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sudden load of HS (Figure 2). In comparison, the SNR was reduced from 2.42±0.40 gN/(g-vss•d) in phases I (HS0) and II (HS2) to 1.53±0.21 g-N/(g-vss•d) in the following phases (HS5-HS50). As the ammonia oxidation was initiated by the enzyme AMO and followed by the enzyme HAO

53,

these results imply that the enzymes or genes

responsible for oxygen consumption and nitrite formation exhibited different responses to the HS dosage. In terms of the concentration profile of HS, UV-vis and EEM spectra were used to characterize the differences between the reactor effluents and 50 mg/L HS solution (dissolved in HS-free effluent). As expect, no remarkable differences were observed ((Figure S8, S9 and S12). The BOD essay were also confirmed the recalcitrance of HS to biodegradation with a BOD5 to COD ratio of < 0.02. Humic substances triggered changes in the overall microbial community The 16S rRNA gene is an excellent phylogenetic marker that can provide a snapshot of the dynamics of the overall microbial community in response to HS stress. The analysis of community diversity (Table S6) indicated that the reactor harbored a more diverse microbial community in the absence of HS compared with that under HS stress (i.e., the decreased Chao 1 and OTU numbers), whereas the abundance of rare species (i.e., the increased Shannon index) increased under HS stress. Most of the OTUs (1332, 97.73%) in 16S rRNA gene sequencing were assigned to 31 phyla (Figure S14). The predominant bacterial phyla in the nitrosifying consortia were Proteobacteria and 13



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Bacteroidetes (Figure S14). The relative abundance of the phylum Proteobacteria exhibited a decreasing trend after HS feeding (from 90.84% in HS0 to 52.11% in HS50). Conversely, the abundance of the phylum Bacteroidetes increased remarkably after the exposure to HS, i.e., increased from 4.7% (HS0) to 35.3% (HS50). Some members of the phylum Bacteroidetes exhibited strong ability for degradation of polymeric organic matter 54. The family Cytophagaceae (increased from 3.47% in HS0 to 17.72% in HS50) contains the genus Cytophaga which can digest crystalline cellulose

55.

In addition,

some species of the family Chitinophagaceae have been known to hydrolyze cellulose 56;

the abundance of this family obviously increased under a high HS concentration

(from 0.68% in HS0 to 5.09% in HS50).The microbial community at the family level was characterized by only 354 OTUs (25.97%) that could be assigned exactly to the genus level (Figure 3A and Figure S15). AOB-associated Nitrosomonadaceae was the dominant family in the reactor during the entire experiment period. The abundance of the family Nitrosomonadaceae was dramatically reduced upon exposure to increasing HS concentration (e.g., from 71.25% in HS0 to 40.90% in HS50). Similarly, metagenome sequences also indicated that the relative abundance of the family Nitrosomonadaceae was 73.6%, 53.8% and 40.6% for HS0, HS5 and HS50, respectively. Metagenome sequences also suggested that the genus Nitrosomonas accounted for greater than 90% of all detected contigs belonging to the family Nitrosomonadaceae (98.9%, 98.4% and 90.2% in HS0, HS5 and HS50, respectively). 14


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Other AOB identified by metagenome sequencing were affiliated with the genus Nitrosospira (0.21%, 0.44% and 2.15% in HS0, HS5 and HS50, respectively, and similarly hereinafter) and Nitrosococcus (0.011%, 0.15% and 0.54%). These results imply that the genus Nitrosomonas was suppressed by HS exposure, whereas the genera Nitrosospira and Nitrosococcus likely preferred to live in HS-containing wastewater. In addition, metagenome sequencing also revealed an increased abundance of the genera Pseudomonas (0.93%, 1.11% and 1.67%) and Bacillus (0.006%, 0.027% and 0.031%) upon exposure to HS. Members of genera Pseudomonas and Bacillus are potential degraders of HS 21. The response of AOB species to HS exposure To reveal the shift of AOB species upon exposure to HS, amoA-based clone libraries were constructed for three selected samples (HS0, HS5 and HS50). The clone library results revealed that the majority of sequences were grouped into four OTUs (Figure 4 and Table S9). The AOB in HS0 mainly consisted of uncultured AOB (42.7%) and amoA anoxic biofilm clone S6 (50.7%). The relative abundance of these two AOB species in the total AOB decreased largely after exposure to HS5 (< 15% for each) and HS50 (< 5% for each), suggesting that these two AOB species were extremely susceptible to HS exposure. The main AOB species in the HS5 clone library shifted to Nitrosomonas europaea (55.1%) and a newly emerged species, amoA anoxic biofilm clone S1 (24.4%). After exposure to 50 mg/L HS (HS50), the relative abundance of the 15



species amoA anoxic biofilm clone S1 was up to 70.7%. This finding suggests that the species amoA anoxic biofilm clone S1 preferred to live or grow in HS-rich wastewater. In addition, amoA genes retrieved from metagenome sequences were also analyzed to provide complementary clues for clone library analysis (Figure 4). Four different contigs that contained the amoA gene were retrieved from the three samples. Three of these contigs were affiliated with the genus Nitrosomonas, and one was affiliated with an uncultured strain (Table S10). The AOB species in HS0 were dominated by uncultured bacterium clone pMD19-AOB (75.9%) followed by Nitrosomonas europaea (22.2%) and Nitrosomonas eutropha (1.8%). Similar to clone library analysis (55.1% in HS5), metagenome analysis revealed an increased abundance of Nitrosomonas europaea (56.4%) in HS5 compared with HS0 (22.2%) and HS50 (7.5%). These results indicate that the presence of a relatively low amount of HS in wastewater can enhance the growth or enrichment of the species Nitrosomonas europaea. Metagenome analysis also revealed the emergence and dominance of the species Nitrosomonas mobilis in HS5 (29.0%) and HS50 (91.3%). This phenomenon is quite similar to the newly emerged species amoA anoxic biofilm clone S1 identified via clone library analysis (24.4% and 70.7% in HS5 and HS50, respectively). Thus, we hypothesize that amoA anoxic biofilm clone S1, identified by clone library analysis, represents a strain that belongs to Nitrosomonas mobilis. Functional genes involved in nitrogen metabolism 16


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Metagenome sequencing annotated 17 199, 19 928 and 18 755 genes for HS0, HS5 and HS50, respectively. Moreover, 15 454 genes were shared across the three samples (Figure S16). Metagenome analysis within the KEGG level 2 subsystem indicated that the abundance of genes involved in carbohydrate metabolisms (8.73%, 9.00%, and 8.93%), lipid metabolisms (3.00%, 3.29%, and 3.31%) and amino acid metabolisms (9.89%, 10.24% and 9.89%) exhibited no evident variations (Figure S17). In comparison, the abundance of genes involved in membrane transport was reduced with the HS dose (5.65%, 5.49%, and 4.47%). In addition, the abundance of electron transport complex protein (rnfBC) assigned to the genus Nitrosomonas was considerably reduced in HS-exposed samples (0.038% and 0.047%) compared with the control sample (0.063%). For a better understanding of the functional diversity of the nitrogen metabolism pathways, the abundance of key genes for nitrification, denitrification and anaerobic ammonium oxidation (anammox) was calculated. Genes encoding the enzymes hydrazine synthase subunit (hsz) and hydrazine dehydrogenase (hdh), which are two key enzymes for anammox, were absent in the samples. This finding was consistent with the reactor performance given that no evident nitrogen removal was observed. Most subunits of the genes encoding enzymes belonging to denitrification (nirK, nirS, norB, norC, and nosZ) were annotated, and all of them exhibited relatively low abundance (Figure 5). The nirS gene, a cytochrome cd1-type nitrite reductase for NO 17



formation, only exhibited a relative abundance of approximately 0.0013% (with average depths of approximately 30) in all samples. In addition, the abundance of the copper-containing nitrite reductase nirK was distinctly higher than that of nirS. Most of the sequences containing the nirK gene were affiliated with the genus Nitrosomonas, and only a few sequences containing nirK were affiliated with heterotrophic bacteria. Interestingly, the abundance of the nirK gene was gradually reduced with increasing HS concentration (0.048%, 0.036%, and 0.021%). Nevertheless, the abundance of the nirK gene affiliated with heterotrophic bacteria dramatically increased in the presence of HS (Figure 6). Additionally, the abundance of the narGHI gene was considerably increased in the two HS-exposed samples (0.046% and 0.038%) compared with the control sample (0.010%, Figure 5). The narGHI gene was assigned to several genera, including Caulobacter, Paracoccus, and Geobacter (Figure 6). Compared with nirK, nirS and narGHI, genes affiliated with AOB bacteria exhibited higher abundance and were more susceptible to HS exposure. HS feeding (5 mg/L) decreased the abundance of the amoABC gene (from 0.33% to 0.22%), but the levels were subsequently recovered to the initial level after a further increase in the HS concentration to 50 mg/L (0.35%). As mentioned above, AOB species strongly varied upon exposure to various concentrations of HS. Crucially, amoABC copies differ among each AOB species 57. However, the gene hydroxylamine oxidoreductase (hao) was severely inhibited by HS stress. The abundance of the hao gene was reduced with 18


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increasing HS concentration (0.30%, 0.15% and 0.03%, Figure 5). This finding could be the main reason for the remarkable decrease of the SNR (Figure 2). Of note, amo or hao genes belonging to the genera Nitrosococcus and Nitrosospira were not identified by metagenome sequencing, although these two genera are present in the samples (e.g., 0.54% and 2.15%, respectively, in HS50). Such a phenomenon was attributable to the low abundance of these genera, which limits the efficient identification of functional genes by metagenome sequencing 58. Thus, all genes (i.e., amoABC and hao) identified by metagenome sequencing were affiliated with the genus Nitrosomonas. Similarly, the nxrA gene, which belongs to NOB, was not recovered from metagenome sequences of the three samples.

Discussion Dynamic changes in the abundance and diversity of the AOB population Analysis of metagenome sequences revealed that most AOB in our reactor belonged to the genus Nitrosomonas. In terms of other two genus, the genus Nitrosospira prefers a low ammonia concentration and a low temperature 59 while the genus Nitrosococcus is often found in the marine environment or seawater

60.

Therefore, Nitrosomonas is a

widely distributed AOB genus in engineered systems 61-63 as well as in our reactor. Our current study provided an update given that the presence of HS in wastewater can lead to a reduced abundance of the genus Nitrosomonas and an increased abundance of the 19



genera Nitrosospira and Nitrosococcus. Remmas et al.

64

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recently found that the

addition of landfill leachate and glycerol to feeding wastewater resulted in severe inhibition of Nitrosomonas and increased abundance of Nitrosospira. Noteworthy, previous studies reported that an elevated FA (0 to 200 mg/L)

65

or FNA (0 to 3.64

mg/L) concentration can cause the shift of microbial community structure

65, 66.

However, in our reactor the FA (

Response of microbial community structures and functions of

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