Next Article in Journal
Determination of Gluten Contamination in Foods Available on the Turkish Market via Enzyme-Linked Immunosorbent Assay (ELISA)
Previous Article in Journal
GNSS Signal Quality in Forest Stands for Off-Road Vehicle Navigation
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Applied Sciences
Volume 13
Issue 10
10.3390/app13106134
applsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Compound Sodium Nitrophenolate Promotes Denitrification by Nitrifying Bacteria by Upregulating Nitrate Reductase

by
Na Yao
1,2,
Lei Zhang
1,2,*,
Fengrong Tian
3,
Kaichun Wang
3,
Qiang Li
1,2,
Jing Lu
1,2,
Mingsheng Lyu
1,2 and
Shujun Wang
1,2,*
1
Jiangsu Key Laboratory of Marine Bioresources and Environment/Jiangsu Key Laboratory of Marine Biotechnology, Jiangsu Ocean University, Lianyungang 222005, China
2
Co-Innovation Center of Jiangsu Marine Bio-Industry Technology, Jiangsu Ocean University, Lianyungang 222005, China
3
Zhonglan Lianhai Design and Research Institute Co., Ltd., Lianyungang 222004, China
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2023, 13(10), 6134; https://doi.org/10.3390/app13106134
Submission received: 23 April 2023 / Revised: 10 May 2023 / Accepted: 12 May 2023 / Published: 17 May 2023
Browse Figures
Versions Notes

Abstract

:
Biological denitrification is an efficient and low-cost method to treat wastewater, and it has been shown that growth promoters can regulate the metabolism of microorganisms. This study aimed to investigate the effects of gibberellic acid, naphthalene acetic acid, compound sodium nitrophenolate, and diethyl aminoethyl hexanoate on the growth and denitrification process of denitrifying microorganisms and to examine the associated mechanisms. All four tested growth promoters did not affect the growth of the strain Q1; further, compound sodium nitrophenolate could significantly improve the bacterial denitrification efficiency and showed an increase in the removal rate of 13.08% in 72 h. The addition of 15 mg/L compound sodium nitrophenolate increased the removal rate of strain Q1 by 25.88% at 72 h, significantly improving the efficiency of reducing the chemical oxygen demand of the effluent. Transcriptome analysis identified 1664 differentially expressed genes (573 upregulated and 1091 downregulated genes) in the strain Q1 treated with compound sodium nitrophenolate. Nitrate reductase and nitrate transporter, which are two key enzymes related to the nitrate reduction pathway, were found to be upregulated during the denitrification process. Compound sodium nitrophenolate has promising applications in high-salt and high-nitrogen wastewater treatment.

1. Introduction

The release of industrial wastewater has been rising steadily in recent years, causing growing levels of ammonia nitrogen pollution [1,2]. The ecological environment, as well as human life, might be negatively impacted by the high ammonia nitrogen content of wastewater [3]. Excessive nitrogen can lead to the deterioration of air quality, eutrophication of water bodies, and the death of plants and animals in contaminated water. Physical, chemical, and biological procedures are the basic components of treatment technologies for nitrogen-containing wastewater [4]. Among them, biological methods are most often used for wastewater denitrification due to high treatment capacity, low cost, and no secondary pollution [5]. The dissolved solids in high-salinity wastewater are higher than 3.5%, while the salinity of wastewater produced by sectors such as petroleum and seafood processing is high [6,7].
Excessive salinity inhibits the metabolism of microorganisms used in wastewater treatment systems and decreases their ability to denitrify. Presently, high-salinity settings make it difficult for terrestrial denitrifying microorganisms to denitrify successfully [8]. It is possible to increase the effectiveness of nitrogen removal from saline wastewater and the stability of process operation by screening salt-tolerant aerobic denitrifying bacteria from marine samples [9].
Growth promoters have been used extensively in plant development [10,11,12] and can control cell growth and metabolism [13,14]. They are residue-free and favorable to the environment. Moreover, promoters have the power to control an organism’s metabolic pathways [15]. Gibberellin can improve salt tolerance and encourage the growth of seeds and seedlings, according to numerous studies [16,17,18]. Kai Yang et al. showed that indoleacetic acid has a promotion effect on the growth and synthesis of fatty acids in Chlorella dubliniensis, whereas Liu et al. demonstrated that naphthalene acetic acid (NAA), an exogenous growth hormone, imparts a significant promotion effect on the growth and synthesis of lipids in Chlorella vulgaris.
In a study by Geng Yuanyuan et al. [19], it was discovered that the biomass and lipid content of C. vulgaris could be increased by the addition of IAA, NAA, and dichloro phenoxy acetic acid when nitrogen was scarce. Low concentrations of the compound sodium nitrophenol (CSN) were found by Yuling Zou et al. [20] to increase the rate of flower bud differentiation in oil tea by increasing ZR, IAA, and gibberellic acid 3 content in oil tea flower buds during petal formation while decreasing abscisic acid content in the late stages of flower bud morphological differentiation. For the control of wastewater treatment microorganisms, research into growth boosters is crucial.
The total number of transcripts in a tissue or cell at a specific developmental stage or functional state is known as the transcriptome [21]. A novel method for analyzing transcriptomes based on deep sequencing technology is known as transcriptome sequencing [22]. Each fragment is sequenced in high throughput to retrieve the sequence at one or both ends after whole RNAs are transformed into cDNA libraries with ligation sites at one or both ends. After sequencing, reads can be compared with reference genomes and reference transcripts that already exist, or, in the absence of a reference gene sequence, an assembled gene transcript profile that includes transcript structure and levels of gene expression can be generated [23,24]. In this study, we used transcriptomics to analyze differential gene expression and KEGG pathway analysis to investigate the metabolic mechanism of growth promoters. Differential genes were analyzed by DEGs GO enrichment to elucidate the differences in gene function levels between samples, while DEGs KEGG enrichment analysis was used to help us understand the biological functions of genes at the systemic level, such as metabolic pathways, genetic information, and cytological processes.
Growth promoters are widely used to promote the growth of plants and algae, but research into bacterial growth has been little explored. This experiment hypothesized that growth promoters also have a certain promotion effect on bacteria. The development of nitrifying microorganisms, denitrification, and COD of wastewater treatment was investigated in this study using growth stimulants, such as gibberellic acid (GA), NAA, CSN, and diethyl aminoethyl hexanoate (DA-6). The findings of this study can be used to develop microbial strains for the treatment of wastewater containing high levels of salt and nitrogen, as well as serve as an experimental foundation for the use of growth promoters in wastewater treatment.

2. Materials and Methods

2.1. Materials

2.1.1. Strain and Chemical Materials

Bacillus sp. strain Q1 is a heterotrophic nitrifying–aerobic denitrifying strain. The optimum conditions were glucose as the carbon source, a C/N ratio of 14, a pH of 7, a temperature of 30 °C, and a shaker speed of 120 rpm. The China Chemical Company supplied the GA, NAA, CSN, and DA-6.

2.1.2. Mediums

Nitrification media, denitrification media, and Luria-Bertani medium were used in this study. The following nitrification medium (g/L) were prepared: denitrification media (g/L): potassium nitrate 0.36, sodium acetate 0.64, K2HPO4, MgSO4•7H2O 0.3, FeSO4•7H2O 0.03, NaCl 30, pH 7.0. The composition of LB medium (g/L) was: tryptone 10, yeast extract 5, sodium chloride 10, pH 7.4. The solid medium contained 2% agar powder, and the mediums were sterilized at 121 °C for 20 min.

2.2. Methods

2.2.1. Effect of Growth Promoter on the Growth of the Strain

The strains used in this experiment were from the author’s collection of laboratory strains. They were first precultured in LB medium for 24 h to reach the exponential growth phase and then inoculated with 2% of the inoculum into LB medium containing growth promoter (concentration 0.001, 0.01, 0.1, 1 mg/L), without growth promoter as a blank control, and incubated at 30 °C, 160 rpm for 24 h. The medium’s OD600 nm values were determined. The OD600 nm values were assessed following the screened growth promoters under various incubation times (0, 4, 8, 12, 24, 36, 48, 60, and 72 h), and the influence of growth promoters on the strain’s growth was evaluated.

2.2.2. Effect of Growth Promoters on Denitrification by Strains

The seed solution was inoculated at 10% (centrifuged to remove the precipitate) into 100 mL of denitrification medium containing growth promoter (concentration 0, 5, 10, 15, 20, 25 mg/L), with initial NH4+-N concentration 50 mg/L, and without growth promoter as blank control, incubated at 30 °C, 120 r/min for 72 h. Every 24 h, samples were obtained, and the contents of NO3−-N and NO2−-N were analyzed. The contents of NO3−-N and NO2−-N were measured.

2.2.3. Effect of Growth Promoters on Effluent COD

The seed solution was added to 100 mL of wastewater (provided by Chine BlueStar Lehigh Engineering Corp) along with various growth promoters (growth promoter concentration was 1 mg/L) in shaking for 72 h at 10% inoculum (precipitation was taken by centrifugation), and COD values were measured by sampling every 24 h.

2.2.4. Study on the Promotion Mechanism of Growth Promoter

Sample preparation for transcriptomics analysis: The optimum growth promoter, its concentration, and time of treatment were selected using the single-factor experiment. The secondary seed solution was centrifuged at 10% inoculum, and the precipitate was transferred to the nitrification medium with the optimum growth promoter at an optimum concentration, incubated at 30 °C, 160 rpm until the optimum time. Subsequently, the mixture was centrifuged at 8000 rpm and centrifuged at 4 °C for 10 min; the supernatant was discarded, the precipitate was collected, and the sample was considered the treatment group (QF1). The secondary seed solution was centrifuged at 10% inoculum; the precipitate was transferred to the nitrification medium under the same culture conditions, and the sample was considered as the control group (QD1). At least 10 OD·mL of each sample was collected (OD600 = 1; 10 mL of bacterial broth was collected by centrifugation), and the precipitate was transferred to a 1.5 mL sterile lyophilization tube, snap frozen in liquid nitrogen, stored on dry ice, and sent to Shanghai Meiji Biomedical Technology Co., Ltd. (Shanghai, China).

2.2.5. Effects of Promoter on the Transcriptome of the Strain Q1

  • RNA extraction, library construction, and sequencing
Total RNA was extracted using TRIzol RNA Extraction Reagent (Invitrogen, Beijing, China). Genomic DNA was removed using DNase I (Takara, Kusatsu, Japan). RNA quality was subsequently determined using a 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA) and quantified using ND-2000 (NanoDrop Technologies, Wilmington, DE, USA) [25]. OD260/280 = 1.8 to 2.0, OD260/230 ≥ 2.0, RIN ≥ 6.5, 23S:16S ≥ 1.0, concentration ≥100 ng/μL, total ≥2 μg.
RNA library construction was performed using the TruSeqTM RNA sample preparation Kit from Illumina (San Diego, CA, USA). The rRNA was removed using the Ribo-Zero Magnetic kit (epicenter). The mRNA was randomly broken into small fragments of about 200 bp, and the mRNA was used as a template for mRNA synthesis using random primers (Illumina) and the SuperScript double-stranded cDNA synthesis kit. The synthesized double-stranded cDNA was subsequently added to End Repair Mix to make up flat ends, a phosphorylate at the 5′ end, and an A base at the 3′ end to connect the Y-sequencing junction.
The library was enriched, and then PCR amplified with Phusion DNA polymerase (NEB) for 15 cycles. After quantification using TBS380 (Picogreen), RNA-seq double-end sequencing was performed using Illumina HiSeq X Ten (2 × 150 bp).
  • Bioinformatics analysis and gene expression analysis
Bioinformatics analysis was performed using the sequencing data generated from the Illumina platform. All analyses were performed using the cloud platform of Shanghai Majorbio Bio-pharm Technology Co., Ltd. (Shanghai, China) (www.majorbio.com (accessed on 15 March 2023)). Expression of genes or transcripts was calculated by the RSEM tool (http://deweylab.github.io/RSEM/ (accessed on 15 March 2023)). Single- or double-end sequencing data were analyzed using DESeq (http://www.bioconductor.org/packages/release/bioc/html/DESeq.html (accessed on 15 March 2023)) for differential expression analysis.

2.2.6. Data Analysis

Experiments were conducted in three parallel replicates, and the SPSS software was used for data processing. The growth of bacteria was measured by determining the OD600 using a spectrophotometer. The amounts of ammonia, nitrite, and nitrate were measured after centrifugation at 8000 rpm for 5 min. NH4+-N, NO3−-N, NO2−-N, and COD contents were measured using salicylic acid spectrophotometry, UV spectrophotometry, N-(1-naphthyl) ethylenediamine spectrophotometry, and dichromate method, respectively. The nitrogen removal rate was calculated using Equation (1).
R = (C0 − C1)/C0 × 100%,
where R is the nitrogen removal rate, C0 is the initial nitrogen concentration, and C1 is the nitrogen concentration at the end.

3. Results

3.1. Effect of Growth Promoters on Strain Q1

The effect of CSN on the growth of strain Q1 was significantly different from that of the control, whereas the effects of other growth promoters on the growth of strain Q1 were not significantly different (Figure 1a). CSN was found to promote the growth of strain Q1. However, all four tested promoters did not significantly affect the growth of strain Q1 (Figure 1b).
In the nitrification process, ammonia is oxidized to nitrite and nitrate by nitrifying bacteria under aerobic conditions. This process involves the following two steps: Equation (2), the conversion of ammonia to nitrite, and Equation (3), the conversion of nitrite to nitrate [26]. As shown in Figure 2, the ammonia, nitro, and nitroso nitrogen concentrations were used to screen the growth promoter CSN, which can significantly increase the denitrification efficiency of nitrifying bacteria. The initial NH4+-N concentration was 50 mg/L, as shown in Figure 2a, in which the ammonia nitrogen content was significantly lower after 24 h of GA and CSN treatment compared with the control and after 48 and 72 h of the four growth promoters treated in the medium. During 48 and 72 h, the ammonia nitrogen level was much lower in all four cultures that had been treated with growth promoters.
2NH4+ + 3O2 → 2H2O + 4H+ + 2NO2−
2NO2− + O2 → 2NO3−
Figure 2b,c indicates that ammonia nitrogen was first converted to nitrite and subsequently from nitrite to nitrate, which is compatible with the features of nitrifying bacteria. The clearance rate of ammonia nitrogen from strain Q1 rose by 13.08% at 72 h as a result of the CSN treatment. Figure 2b depicts the most striking conversion impact at 48 h, when strain Q1 treated with GA and CSN dramatically enhanced its conversion rate to nitric nitrogen, with GA performing better.
The most pronounced response to the conversion to nitrate nitrogen at 72 h is shown in Figure 2c, and the rate of conversion of strain Q1 treated with GA, CSN, NAA, and DA-6 to nitrite was greatly increased in comparison to the control group, in which the effect of CSN was most noticeable. The impact of CSN was the clearest. Similar to Acinetobacter sp. T1, strain Q1 observed the creation of NO2−-N and NO3−-N during the elimination of NH4+-N [27]. Moreover, strain Q1 was more effective in removing nitrogen from the air than strain L7 of the Bacillus methylotrophicus (48%) [28].

3.2. The Effect of the Concentration of Compound Sodium Nitrophenolate on Strain Q1

The growth stimulation impact of CSN on strain Q1 was at its strongest at 0.01 mg/L, as shown in Figure 3, and it increased with increasing concentration. Instead, as the concentration increased, the growth was suppressed, which is consistent with the property of benzoic acid to encourage P. aeruginosa growth at low concentrations and inhibit it at high concentrations [29].
Figure 4 shows the effect of different concentrations of CSN on bacterial nitrification capacity. We found that 15 mg/L CSN-treated strain Q1 contributed most significantly to the nitrogen removal rate. The ammonia nitrogen removal rate was increased after 24 h of treatment with 5, 10, and 15 mg/L of CSN compared with the control. Further, at concentrations of 5, 10, 15, 20, and 25 mg/L CSN, the ammonia nitrogen removal rate was increased after both 48 h and 72 h (Figure 4a). The removal rate at a concentration of 15 mg/L CSN was more obvious (25.88% increase at 72 h). Furthermore, the conversion rate of nitrite was most efficient after 48 h at 15 mg/L CSN (Figure 4b). The conversion to nitrate nitrogen was most obvious at 72 h, except for the conversion of nitrite after 5 mg/L CSN treatment (Figure 4c). The rate of nitrite conversion was lower than that of the control group after 5 mg/L CSN treatment, and the conversion rate of nitrite by strain Q1 significantly increased after 10, 15, 20, and 25 mg/L CSN treatment, with the most obvious effect after 15 mg/L CSN treatment.

3.3. Effect of Growth Promoter on COD of Wastewater

The COD of the effluent treated with CSN was the only one to decrease compared with the control at 24 h, 48 h, and 72 h, as shown in Figure 5. At 72 h, the promotion effect of CSN was strongest, and the reduction in effluent COD increased by 23.6% compared with the control. The other three promoters had no discernible impact on effluent COD after treatment. Moreover, the effluent COD increased after 48 h and dropped after 72 h of incubation.

3.4. Growth Promoter Promotion Mechanism Study

3.4.1. Transcriptome Changes in Strain Q1 under Compound Sodium Nitrophenolate Treatment

To visualize the library construction quality and sequencing quality of samples from a macroscopic perspective and to analyze the base quality, base error rate, and base distribution of each sample, statistical methods were used to calculate the base distribution and quality fluctuation of each cycle of all sequenced reads. Two libraries were built to compare the strain QF1 following CSN treatment with the control strain QD1. Overall, both samples had good quality, with the proportion of bases for Q20 being above 97% and Q30 being above 93.23% (Table 1).
Six public databases (NR, Swiss-Prot, Pfam, COG, GO, and KEGG) led to the annotation of 5446 predicted genes (Table 2). The highest number of genes was annotated in the NR database (98.95%; 5389). In contrast, the KEGG database annotated the lowest number of genes (3670). COG annotated 4643 genes, divided into four COG primary and 23 secondary categories. The main categories were “amino acid transport and metabolism” (463), “carbohydrate transport and metabolism” (417), “lipid transport and metabolism” (379), “coenzyme transport and metabolism” (294), “energy production and transformation” (259), and “inorganic ion transport and metabolism” (242). A total of 3670 genes were assigned to seven KEGG pathways, including metabolism, genetic information processing, environmental information processing, cellular processes, organismal systems, human diseases, and drug development. “Carbohydrate metabolism” (401), “amino acid metabolism” (329), “energy metabolism” (187), “cofactor and vitamin metabolism” (144), “lipid metabolism” (123), and “xenobiotic biodegradation and metabolism” (52) were the main metabolic pathways identified (Figure 6).

3.4.2. The Effect of the Compound Sodium Nitrophenolate on the Transcriptome of Strain Q1

In the QF1 sample compared with the control QD1, there were 1664 DEGs (573 upregulated and 1091 downregulated genes) (Figure 7). Two important enzyme genes associated with the nitrate reduction pathway during denitrification, nitrate reductase and nitrate transporter, showed upregulated expression (Table 3). Our findings suggest that strain Q1 increased the expression of genes involved in the nitrate reduction pathway to increase the strain’s denitrification efficiency during CSN treatment.
Additionally, it was discovered that several enzymes involved in protein synthesis and translation, including glutamyl-tRNA(Gln) aminotransferase, tRNA lysine synthase, and tRNA-specific adenosine deaminase, displayed various degrees of upregulated expression. This demonstrated that strain Q1 might increase enzyme production by encouraging protein synthesis and translation, which would increase the strain’s capacity for denitrification. This is in line with findings that CSN administration encourages the translation and synthesis of proteins in strain Q1 by the highest number of genes annotated in significant pathways, including amino acid metabolism categorization (Figure 8).
A total of 438 DEGs from the QF1 sample were engaged in 31 pathways (Figure 8). There were 11 categories for metabolic pathways, 6 categories for human disease pathways, 4 categories for processing genetic information, 4 categories for processing information about organismal systems, 2 categories for processing information about the environment, and 4 categories for processing information about cellular processes among the seven major classifications of KEGG. The classification’s most annotated genes were found in significant metabolic pathways, such as glucose and amino acid metabolism. After treating strain Q1 with CSN, the GO genes were primarily enriched in cytoplasmic large ribosomal subunits, large ribosomal subunits, ribosomes, rRNA binding, structural molecular activity, structural components of ribosomes, and ribosomal subunits pathways, indicating that these DEGs are crucial for the nitrifying bacteria’s denitrification process (Figure 9).

4. Discussion

Salt-tolerant nitrifying bacteria are characterized by slow growth, the long time required for the nitrification process, and a weak denitrification effect [30]. Several studies have reported previously on the effect of promoters, such as the application of alginate as a compatible solute in high-salt wastewater treatment to improve nitrate and nitrite nitrogen removal [31]. Guo et al. demonstrated that exogenous alginate could rapidly adapt microbial cells to high-salt environments by regulating osmotic pressure, in turn promoting their growth [32]. The encapsulated denitrification filler was also able to maintain high denitrification performance, according to Zhou Yakun et al. [33]. Zheng et al. reported that a 2.5% NAA microemulsion stimulated spore germination and the development of adherent cells in rubber tree gum cell anthrax RC169 at very low concentrations [34]. Our findings offer an experimental foundation for the use of growth promoters in wastewater treatment of bacterial growth and denitrification capacity. Next, future studies should examine whether or not CSN could act on the other nitrifying bacteria. Moreover, different types of growth promoters could be selected to investigate their effects on microorganisms to improve growth and denitrification efficiency.

5. Conclusions

The results of this study demonstrated that none of the four growth promoters tested had any negative effects on the development of the tested bacterial strains. However, CSN significantly increased the efficiency of the tested bacteria’s denitrification process, increasing the removal rate at 72 h by 13.08%. The clearance rate of strain Q1 was increased by 25.88% at 72 h by the addition of 15 mg/L CSN. The transcriptome of Nitrobacter revealed 1664 DEGs (573 upregulated genes and 1091 downregulated genes) in the strain Q1 treated with CSN. Nitrate reductase and nitrate transporter, two important enzymes related to the nitrate reduction pathway, displayed upregulated expression during the denitrification process. In addition, it was shown that several proteins’ translation and synthesis processes—including those of glutamyl-tRNA(Gln) aminotransferase, tRNA lysine synthase, and tRNA-specific adenosine deaminase—were upregulated. The aforementioned findings imply that strain Q1 increased the strain’s denitrification efficiency under CSN treatment by, on the one hand, increasing the expression of genes involved in the nitrate reduction pathway. On the other side, it might boost protein synthesis and translation to enhance the production of enzymes, improving the strain’s capacity for denitrification. The addition of CSN significantly improved the treatment efficiency of COD of the effluent when compared with the control, with the highest number of genes annotated in significant pathways such as amino acid metabolism, carbohydrate metabolism, and other classifications. GO genes were primarily enriched in cytoplasmic large ribosomal subunit, ribosome, rRNA binding, and other pathways. Our research establishes a foundation for using strain Q1 and the growth stimulant CSN to treat high-salt, nitrogen-containing wastewater.

Author Contributions

Conceptualization, methodology, and writing—original draft preparation, N.Y.; data curation and resources, K.W. and F.T.; visualization and investigation, L.Z.; writing—reviewing and editing, Q.L., J.L. and M.L.; funding acquisition and project administration, S.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Key R&D Program of China (2022YFC2805100), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), and the Nitrobacteria research project (KH21020).

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Piedrahita, R.H. Reducingthe potential environmental impact of tank aquaculture effluents through intensification and recirculation. Aquaculture 2003, 226, 35–44. [Google Scholar] [CrossRef]
  2. Zhou, M.H.; Ye, H.R.; Zhao, X.W. Isolation and characterization of a novel heterotrophic nitrifying and aerobic denitrifying bacterium Pseudomonas stutzeri KTB for bioremediation of wastewater. Biotechnol. Bioprocess Eng. 2014, 19, 231–238. [Google Scholar] [CrossRef]
  3. Shi, Z.; Zhang, Y.; Zhou, J.; Chen, M.X.; Wang, X.J. Biological removal of nitrate and ammonium under aerobic atmosphere by Paracoccus versutus LYM. Bioresour. Technol. 2013, 148, 144–148. [Google Scholar] [CrossRef]
  4. Shi, X.Q.; Lefebvre, O.; Ng, K.K.; Ng, H.Y. Sequential anaerobic–aerobic treatment of pharmaceutical wastewater with high salinity. Bioresour. Technol. 2014, 153, 79–86. [Google Scholar] [CrossRef]
  5. Su, J.F.; Zhang, H.; Huang, T.L.; Hu, X.F.; Chen, C.L.; Liu, J.R. The performance and mechanism of simultaneous removal of fluoride, calcium, and nitrate by calcium precipitating strain Acinetobacter sp. H12. Ecotoxicol. Environ. Saf. 2020, 187, 109855. [Google Scholar] [CrossRef]
  6. Woolard, C.R.; Irvine, R.L. Tretatment of hypersaline wastewater in the sequencing batch reactor. Water Res. 1995, 29, 1159–1168. [Google Scholar] [CrossRef]
  7. Glass, C.; Silverstein, J. Denitrification of high-nitrate, high-salinity wastewater. Water Res. 1999, 33, 223–229. [Google Scholar] [CrossRef]
  8. Ji, L.; Liu, Y.; Zhang, Y.F.; Liu, X.D. Study on the Treatment of High Salinity Oil Waste Water by Reverse Osmosis Technology. Adv. Mater. Res. 2011, 418–420, 90–93. [Google Scholar] [CrossRef]
  9. Wang, X.Y.; Zhu, H.; Shutes, B.; Fu, B.; Yan, B.X.; Yu, X.F.; Wen, H.Y.; Chen, X. Identification and denitrification characteristics of a salt-tolerant denitrifying bacterium Pannonibacter phragmitetus F1. AMB Express 2019, 9, 193. [Google Scholar] [CrossRef]
  10. Ma, C.; Wang, L.; Lee, U.Y.; Tanabe, K.; Kang, S.; Zhang, C.X. Pre-harvest foliar application of ethephon strengthens gibberellins-induced fruit expansion in Pyrus pyrifolia. Genet. Mol. Res. GMR 2016, 15, 4. [Google Scholar] [CrossRef]
  11. Zhou, W.G.; Chen, F.; Zhao, S.H.; Yang, C.Q.; Meng, Y.J.; Shuai, H.W.; Luo, X.F.; Dai, Y.J.; Yin, H.; Du, J.B.; et al. DA-6 promotes germination and seedling establishment from aged soybean seeds by mediating fatty acid metabolism and glycometabolism. J. Exp. Bot. 2019, 70, 101–114. [Google Scholar] [CrossRef] [PubMed]
  12. Voß, U.; Bishopp, A.; Farcot, E.; Bennett, M.J. Modelling hormonal response and development. Trends Plant Sci. 2014, 19, 311–319. [Google Scholar] [CrossRef] [PubMed]
  13. Kulkarni, M.G.; Stirk, W.A.; Southway, C.; Papenfus, H.B.; Swart, P.A.; Lux, A.; Vaculík, M.; Martinka, M.; Van, S.J. Plant growth regulators enhance gold uptake in Brassica juncea. Int. J. Phytoremediat. 2013, 15, 17–26. [Google Scholar] [CrossRef] [PubMed]
  14. Li, Y.Q.; Wang, Y.Y.; Song, G.L. Application of technique of thick-layer base material spraying technology on vegetation restoration of rock slop in semiarid area of north China:a case of Jingcheng Expressway (the third phase). Grassland Turf. 2012, 32, 58–64. [Google Scholar]
  15. Chen, Z.L. Expression profiling of ABA pathway transcripts indicates crosstalk between abiotic and biotic stress responses in Arabidopsis. Genomics 2012, 100, 110–115. [Google Scholar] [CrossRef] [PubMed]
  16. Kumar, P.; Singh, A.; Laishram, N. Effects of plant growth regulators on quality flower and seed production of marigold (Tagetes erecta L.). Bangladesh J. Bot. 2020, 49, 567–577. [Google Scholar] [CrossRef]
  17. Wei, Z.M.; Hu, X.J.; Mo, F. Effect of exogenous gibberellin on seed germination and seedling growth of Marigold under salt stress. North. Hortic. 2022, 16, 69–75. [Google Scholar]
  18. Dai, T.Y.; Wang, Q.C.; Zhang, Y.Y. Effect of exogenous gibberellin on seed germination and seedling growth of tomato under salt stress. Seeds 2022, 3, 74–80. [Google Scholar]
  19. Geng, Y.Y.; Zhang, X.M.; Nie, Y.D. Effects of growth factors on growth and lipid accumulation of Chlorella vulgaris under nitrogen deficiency stress. Chin. Lipids 2022, 47, 95–100. [Google Scholar]
  20. Zou, Y.L.; Zhong, Q.P.; Ge, X.N. Effect of sodium compound nitinol on endogenous hormones and bud differentiation rate of oil tea flower bud. Econ. For. Res. 2020, 2, 69–76. [Google Scholar]
  21. Okoroafor, O.N.; Animoke, P.C.; Mbegbu, E.C. Prevalence of Newcastle disease virus in feces of free-range turkeys in Enugu, Nigeria. Vet World 2020, 13, 1288–1293. [Google Scholar] [CrossRef]
  22. Liu, W.; Qiu, X.; Song, C. Deep sequencing-based transcriptome profiling reveals avian interferon-stimulated genes and provides comprehensive insight into Newcastle disease virus-induced host responses. Viruses 2018, 10, 162. [Google Scholar] [CrossRef]
  23. Zhang, L.H.; Jiang, S.Z.; Guo, X. MiR-146b-5p targets IFI35 to inhibit inflammatory response and apoptosis via JAK1/STAT1 signalling in lipopolysaccharide-induced glomerular cells. Autoimmunity 2021, 54, 430–438. [Google Scholar] [CrossRef]
  24. Molouki, A.; Hsu, Y.T.; Jahanshiri, F. Newcastle disease virus infection promotes Bax redistribution to mitochondria and cell death in HeLa cells. Intervirology 2010, 53, 87–94. [Google Scholar] [CrossRef]
  25. Liu, Y.; Wu, C.; Wang, J.; Mo, W.; Yu, M. Codon optimization, expression, purification, and functional characterization of recombinant human IL-25 in Pichia pastoris. Appl. Microbiol. Biotechnol. 2013, 97, 10349–10358. [Google Scholar] [CrossRef]
  26. Qu, Y.; Zhang, R.; Fang, M. Bioaugmentation with a novel alkali-tolerant Pseudomonas strain for alkaline phenol wastewater treatment in sequencing batch reactor. World J. Microbiol. Biotechnol. 2011, 27, 1919–1926. [Google Scholar] [CrossRef]
  27. Chen, S.H.; He, S.Y.; Wu, C.J. Characteristics of heterotrophic nitrification and aerobic denitrification bacterium Acinetobacter sp. T1 and its application for pig farm wastewater treatment. J. Biosci. Bioeng. 2018, 127, 201–205. [Google Scholar] [CrossRef] [PubMed]
  28. Zhang, Q.L.; Liu, Y.; Ai, G.M. The characteristics of a novel heterotrophic nitrification–aerobic denitrification bacterium, Bacillus methylotrophicus strain L7. Bioresour. Technol. 2012, 108, 35–44. [Google Scholar] [CrossRef]
  29. Li, R.Q.; Zhang, X.X.; Gao, Z.L. Mechanisms of benzoic acid effect on nitrogen transformation by denitrifying bacteria. Environ. Pollut. Prev. 2023, 45, 27–34. [Google Scholar]
  30. Wang, C.; Chen, Y.W.; Zhou, H.Z. Adaptation mechanisms of Rhodococcus sp. CNS16 under different temperature gradients: Physiological and transcriptome. Chemosphere 2020, 238, 124571. [Google Scholar] [CrossRef]
  31. Yang, Z.L.; Yu, D.S.; Li, Z. Nitrogen and carbon removal efficacy of algal sugar-enhanced anaerobic ammonia oxidation coupled with denitrification process for treating high-salt wastewater. Environ. Sci. 2018, 39, 4612–4620. [Google Scholar]
  32. Guo, L.; Xiao, P.Y.; Li, L.S. Metabolic mechanisms of heterotrophic nitrifying- aerobic denitrifying bacterial flora under high salt stress enhanced by algal sugars. J. Biol. Eng. 2022, 12, 4536–4552. [Google Scholar]
  33. Zhou, Y.K. Study on the domestication culture of high efficiency denitrifying bacteria and their application performance under low temperature conditions of encapsulated fillers. Contemp. Chem. Res. 2022, 12, 1–4. [Google Scholar]
  34. Zheng, X.L.; Hu, F.; Liang, Y.Q. Effect of naphthalene acetic acid on the growth rate, spore germination rate and attachment cell formation rate of rubber tree gum cell anthracnose. Trop. Agric. Sci. 2016, 8, 45–48. [Google Scholar]
Applsci 13 06134 g001 550
Figure 1. (a) Effect of growth promoters on the growth of strain Q1; (b) effect of growth promoters on the growth of strain Q1 at different time points. Different letters indicate statistically significant differences (p < 0.05).
Figure 1. (a) Effect of growth promoters on the growth of strain Q1; (b) effect of growth promoters on the growth of strain Q1 at different time points. Different letters indicate statistically significant differences (p < 0.05).
Applsci 13 06134 g001
Applsci 13 06134 g002 550
Figure 2. Effect of growth promoters on the denitrification capacity of strain Q1: (a) NH4+−N; (b) NO2−−N; (c) NO3−−N.
Figure 2. Effect of growth promoters on the denitrification capacity of strain Q1: (a) NH4+−N; (b) NO2−−N; (c) NO3−−N.
Applsci 13 06134 g002
Applsci 13 06134 g003 550
Figure 3. Effect of different CSN concentrations on the growth of strain Q1 (Different lowercase letters indicate statistically significant differences (p < 0.05)).
Figure 3. Effect of different CSN concentrations on the growth of strain Q1 (Different lowercase letters indicate statistically significant differences (p < 0.05)).
Applsci 13 06134 g003
Applsci 13 06134 g004 550
Figure 4. Effect of different CSN concentrations on the denitrification capacity of strain Q1: (a) NH4+−N; (b) NO2−−N; (c) NO3−−N.
Figure 4. Effect of different CSN concentrations on the denitrification capacity of strain Q1: (a) NH4+−N; (b) NO2−−N; (c) NO3−−N.
Applsci 13 06134 g004
Applsci 13 06134 g005 550
Figure 5. Effect of different growth promoters on effluent COD.
Figure 5. Effect of different growth promoters on effluent COD.
Applsci 13 06134 g005
Applsci 13 06134 g006 550
Figure 6. Bar chart of statistics of the pathway classification (vertical coordinate shows the name of KEGG metabolic pathway, and horizontal coordinate is the number of genes annotated).
Figure 6. Bar chart of statistics of the pathway classification (vertical coordinate shows the name of KEGG metabolic pathway, and horizontal coordinate is the number of genes annotated).
Applsci 13 06134 g006
Applsci 13 06134 g007 550
Figure 7. Expression differences between samples: (a) volcano map; (b) scatter plot.
Figure 7. Expression differences between samples: (a) volcano map; (b) scatter plot.
Applsci 13 06134 g007
Applsci 13 06134 g008 550
Figure 8. KEGG classification of genes in QF1 (vertical coordinate is the second classification of the KEGG metabolic pathway, and horizontal coordinate is the number of genes annotated to this pathway).
Figure 8. KEGG classification of genes in QF1 (vertical coordinate is the second classification of the KEGG metabolic pathway, and horizontal coordinate is the number of genes annotated to this pathway).
Applsci 13 06134 g008
Applsci 13 06134 g009 550
Figure 9. GO enrichment analysis classification statistics chart (The color indicates the significance of the enrichment, and the redder the default color indicates the more significant enrichment of the GO term, where FDR & LT; 0.001 is marked with ***, and FDR & Lt) & LT.
Figure 9. GO enrichment analysis classification statistics chart (The color indicates the significance of the enrichment, and the redder the default color indicates the more significant enrichment of the GO term, where FDR & LT; 0.001 is marked with ***, and FDR & Lt) & LT.
Applsci 13 06134 g009
Table
Table 1. Overview of sequencing data.
Table 1. Overview of sequencing data.
Sample NameQD1QF1
Raw Reads23,047,2847,798,766
Raw Bases (bp)3,480,139,8841,177,613,666
Raw Error Rate (%)0.02690.0286
Raw Q20 * (%)97.1696.13
Raw Q30 * (%)92.5491.46
Clean Reads22,858,4847,442,962
Clean Bases (bp)3,304,136,1571,093,331,025
Clean Error Rate (%)0.02590.026
Clean Q20 (%)97.6797.54
Clean Q30 (%)93.2393.23
* Raw Q20, Q30: calculate the percentage of bases with Phred values greater than 20 and 30, respectively, of the overall bases.
Table
Table 2. Distribution of annotation of genes using different databases.
Table 2. Distribution of annotation of genes using different databases.
Annotated in DatabasesNumber of Genes
Genes of NR (Percent (%))5389 (98.95)
Genes of Swiss-Prot (Percent (%))5083 (93.33)
Genes of Pfam (Percent (%))3455 (63.44)
Genes of COG (Percent (%))4643 (85.26)
Genes of GO (Percent (%))3349 (61.49)
Genes of KEGG (Percent (%))3670 (67.39)
Total Genes5446 (100)
Table
Table 3. Selected genes of strain Q1 with increased or decreased relative expression levels after CSN treatment.
Table 3. Selected genes of strain Q1 with increased or decreased relative expression levels after CSN treatment.
Gene NameGene DescriptionLog2FC (QF/QD) *Regulate
miaAtRNA dimethylallyl transferase1.333272633up
gatAGlutamyl-tRNA (Gln) amidotransferase subunit A0.874257195up
trmBtRNA (guanine-N(7)-)-methyltransferase2.181028133up
ybaKCys-tRNA (Pro)/Cys-tRNA (Cys) deacylase YbaK2.662302664up
tsaDtRNA N6-adenosine threonylcarbamoyltransferase1.077234695up
TilStRNA lysidine synthetase TilS, partial1.201721029up
tadA_1tRNA-specific adenosine deaminase1.139064415up
narX_1Nitrate reductase-like protein NarX0.027333981up
narTputative nitrate transporter NarT0.122508372up
* Log2 (expression ratio) of relative transcript levels for CSN-treated cells to transcript levels for untreated cells.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Yao, N.; Zhang, L.; Tian, F.; Wang, K.; Li, Q.; Lu, J.; Lyu, M.; Wang, S. Compound Sodium Nitrophenolate Promotes Denitrification by Nitrifying Bacteria by Upregulating Nitrate Reductase. Appl. Sci. 2023, 13, 6134. https://doi.org/10.3390/app13106134

AMA Style

Yao N, Zhang L, Tian F, Wang K, Li Q, Lu J, Lyu M, Wang S. Compound Sodium Nitrophenolate Promotes Denitrification by Nitrifying Bacteria by Upregulating Nitrate Reductase. Applied Sciences. 2023; 13(10):6134. https://doi.org/10.3390/app13106134

Chicago/Turabian Style

Yao, Na, Lei Zhang, Fengrong Tian, Kaichun Wang, Qiang Li, Jing Lu, Mingsheng Lyu, and Shujun Wang. 2023. "Compound Sodium Nitrophenolate Promotes Denitrification by Nitrifying Bacteria by Upregulating Nitrate Reductase" Applied Sciences 13, no. 10: 6134. https://doi.org/10.3390/app13106134

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop