Microbial communities in biological denitri ﬁ cation system using methanol as carbon source for treatment of reverse osmosis concentrate from coking wastewater

A biological denitrifying process using methanol as a carbon source was employed for the treatment of reverse osmosis concentrate (ROC) from coking wastewater in a sequencing batch reactor (SBR). The results showed that the average removal ef ﬁ ciencies of chemical oxygen demand (COD), total organic carbon, total nitrogen and nitrate were 81.4%, 83.7%, 90.6% and 92.9%, respectively. Different microbial communities were identi ﬁ ed on the MiSeq platform, showing that the most abundant bacterial phyla were Proteobacteria and Bacteroidetes , the sum of which, in this study, accounted for almost over 92%. The key genera responsible for denitri ﬁ cation were Hyphomicrobium, Thauera and Methyloversatilis . Quantitative real-time polymerase chain reaction was used to quantify the absolute abundances of microbial genera by using 16S rRNAs and denitrifying genes, such as narG, nirS and nirK , during both start-up and stable operations in the SBR. nirS was much more abundant than nirK , thus became the main functional gene to execute nitrite reduction. The high removal ef ﬁ ciency of COD and nitrate suggests that a biological denitrifying process using SBR is an effective technique for treating ROC from coking wastewater.

deterioration in the quality of water resources and eutrophication of rivers and lakes. Thus, the discharge of ROC must meet the requirements of the National Discharge Standard (GB16171-2012) in China, in which TN should be below 20 mg/L. Therefore, the removal of nitrate from ROC is important.
In comparison to physicochemical treatment methods, biological denitrification, in which the nitrate is reduced to harmless N 2 gas under anoxic conditions, is a potential approach to treating nitrate-contaminated ROC from coking wastewater (Nancharaiah & Venugopalan ). Biological denitrification is conducted by denitrifying microbes that use nitrate as a terminal electron acceptor, and organic and inorganic substances as electron donors, as well as energy sources for sustaining microbial growth.
In addition, the extent and overall rate of the denitrification process largely depend on the biodegradability of the influent wastewater or external carbon sources. In some industrial wastewater treatment plants where wastewater is treated with limited degradable organic matter, external carbon sources, such as glucose and acetate, are added into an anoxic reactor to facilitate denitrification. Methanol is the most commonly employed external carbon source and has the advantages of: (1) being easily assimilated by denitrifying bacteria, (2) having the potential for complete denitrification without nitrite accumulation, (3) having high nitrate removal efficiency, (4) possessing low operational costs and (5) being broadly available in various industrial wastewaters. A previous study has also reported a methanol-feeding denitrification system of coking wastewater, in which nitrate removal efficiency achieved 99% (Vazquez et al. ).
High-throughput sequencing technology has been successfully used to investigate the dynamics of microbial communities in both domestic and industrial wastewater treatment processes (Fernandes et al. ). Since these populations are associated with efficient pollutant removal, understanding community structures in coking wastewater is important. Some studies (Ma et al. ) have focused on revealing the abundance, diversity and distribution in full-scale coking wastewater treatment systems corresponding to the degradation of phenols, COD, TN, PAH and CN À . Additionally, applications of quantitative real-time polymerase chain reaction (qPCR) have given further insight into features of denitrifying communities, such as nitrate reductase (Nar) and nitrite reductase (Nir) used for wastewater treatment in biological denitrification systems (Heylen et al. ). However, few studies have investigated further correlation between denitrification process and the microbial communities in ROC from coking wastewater, which is always regarded as a 'black box' model.
In this study, a laboratory-scale SBR was used to investigate the denitrification with methanol as an external carbon source of ROC for 90 days. The removal of COD, total organic carbon (TOC), TN and nitrate was evaluated for each stage. Concomitantly, microbial community compositions and abundances in sludge samples were analyzed using high-throughput sequencing. The study also quantified the absolute abundance of functional genes involved in nitrate removal and investigated the ecological associations among these functional genes in SBR. This study highlights the feasibility of the denitrifying process by SBR and provides insights into the diverse microbial groups that have the potential to degrade nitrate in ROC from coking wastewater.

Status of coking wastewater treatment procedures
The rate of coking wastewater production in a steel plant (Baosteel Company, Shanghai, China) was 150 m 3 /h. The first phase used the two-step biological denitrification procedure, namely A 1 -A 2 -O 1 -A 3 -O 2 (anaerobic 1, anoxic 2, aerobic 1, anoxic 3, aerobic 2), and in the second stage, the advanced treatment procedure, namely membrane technology (ultrafiltration þ nanofiltration þ RO), was used. During the entire procedure, 20 m 3 of ROC was produced per hour with a water production rate of 65%. The RO membranes used in the procedure were TML20-400, supplied by Toray Group (Japan). The characteristics of ROC are shown in Table 1.

SBR and operational conditions
The experiments were performed using a laboratory scale cylinder SBR with a working volume of 5.0 L. The 24-h operational cycle of the SBR system included the following five phases: filling (5 min), anoxic reaction (6 h The solution pH and conductivity were measured using a DR1900 portable spectrophotometer (HACH, USA).

Sequence pre-processing
FastQC was used to assess the quality of raw reads with adapter sequences and low quality (<Q20) bases trimmed using Cutadapt and trimmed paired reads merged into single contigs using FLASH software. According to the designed barcode information, the reads were assigned to samples by using this system. QIIME analysis QIIME version 1.7 was used to perform operational taxonomic unit (OTU) clustering and alpha and beta diversity

RESULTS AND DISCUSSION
Changes in COD and TOC during denitrification of ROC using methanol as a carbon source In the advanced treatment process of coking wastewater, the conductivity of the RO feed was 58-361 μs/cm, which completely achieved the water quality standards for recycled cooling water. As the desalinization ratio of the RO membrane was maintained at 99.3%, the conductivity of ROC reached 17,539 ± 885 μs/cm. ROC from coking wastewater is a typical industrial wastewater with high conductivity, TN and nitrate (Table 1). Thus, it is essential to employ a biological means to remove nitrogen by a denitrification process.
The BOD 5 /COD in raw ROC from coking wastewater was 0.06-0.15, with poor biodegradability, thus, it cannot be used as the internal carbon source of denitrification. Consequently, methanol is added before the SBR anoxic stirring reaction process, playing the role of a carbon source for microbes during denitrification. In the environment of ROC with high conductivity, enough methanol is added to achieve C:N (carbon:nitrogen) value of 8:1, hence ensuring  The biological denitrification experiment in the SBR with methanol as the carbon source continued for 90 days.
The first 30 days were the acclimatization stage, and for the next 60 days, the reactor operated stably, whilst the sludge was discharged on time. Figure 7,590, 6,702, 7,532, 7,355 and 5,593 OTUs, respectively, were identified. Moreover, the number of sequences and These results confirm that the activated sludge samples from SBR contained an abundant diversity of bacterial genera.

Diversity and compositional variation in the SBR bacterial community
The phylogenetic spectrum was used to characterize the microbial community structure and composition during the SBR operation. On the level of the phylum, 34 main phyla, as listed in Figure 4, were selected.    were found to be dominant in the SBR system and contributed significantly to both denitrification and COD removal.

Quantitative abundances of denitrifying genes in SBR
It is well known that nitrate reductase (Nar) and nitrite reductase (Nir) are responsible for converting nitrate to nitrite and nitrite to nitrous oxide, respectively. In this study, the 16S rRNA, narG, nirS and nirK gene copy numbers were detected during the entire SBR operation period; these denitrifying bacteria were generally spread across a number of genera of Proteobacteria.
As shown in Figure 6, the quantity of 16S rRNA detected showed a trend of an initial increase, followed by a more constant quantity overall with the copy numbers of 16S rRNA being 8.15 × 10 4 copies/ng on ROC-1d, 3.53 × 10 5 copies/ng on ROC-31d, 4.62 × 10 5 copies/ng on ROC-51d, 4.97 × 10 5 copies/ng on ROC-71d and 3.56 × 10 5 copies/ng on ROC-91d. The change in copy numbers indicated that the hyper-saline ROC promoted steady concentrations of the dominant bacterial communities after acclimatization.
NarG, a membrane bound nitrate reductase enzyme, was the key gene for converting nitrate to nitrite, which consumed nitrate and provided substrate nitrite for converting NO 2 À to NO (Lu et al. ). The narG concentration on ROC-1d was 6.85 × 10 3 copies/ng, then gradually increased to 1.31 × 10 5 copies/ng on ROC-31d and became stable during the later period of stable operation with quantities of 4.54 × 10 3 , 5.47 × 10 3 and 4.21 × 10 3 copies/ng at ROC-51d, ROC-71d and ROC-91d, respectively. These results illustrate that the high abundance of narG had promoted the reduction of nitrate to nitrite, ensuring the performance of denitrifying nitrogen removal.
The nirS and nirK genes express cytochrome cd1containing and copper-containing nitrite reductase, respectively, which catalyze the reduction of nitrite to nitric-oxide.
NirS and nirK were found to be prevalent in Betaproteobacteria and Alphaproteobacteria, respectively; nirS and nirK were found at equal frequency in the Gammaproteobacteria   During the whole operational process, the quantity of nirS showed a trend of an initial increase, followed by generally stable abundances with 9.52 × 10 4 copies/ ng (ROC-1d), 3.99 × 10 5 copies/ng (ROC-31d), 3.35 × 10 4 copies/ng (ROC-51d), 3.19 × 10 4 copies/ng (ROC-71d) and 2.45 × 10 4 copies/ng (ROC-91d). The abundance of nirK showed a similarly changing pattern with the quantity on ROC-31d being the highest at 7.52 × 10 3 copies/ng, and declining to overall similar magnitudes of 3.03 × 10 3 copies/ ng (ROC-51d), 3.21 × 10 3 copies/ng (ROC-71d) and 2.01 × 10 3 copies/ng (ROC-91d). As expected, nirS and nirK genes are often used as nitrite reduction markers to study the deni- indicates that nirS not only played a dominant role in nitrite reduction, but also was a primary contributor to NO greenhouse gas production in SBR. The abundances of narG, nirS and nirK involved in the denitrification process were enriched in the stable operation, suggesting that under complex environmental conditions, the denitrifying community may adapt to the hyper-saline ROC after acclimatization.
Overall, this suggests that gene analysis may be relied upon to assess the relative dominance of the denitrifying microbial populations in ROC treatment from coking wastewater.

CONCLUSIONS
In this study, stable and efficient denitrification was achieved by using an SBR process to treat ROC discharged from a coking wastewater treatment plant.