A single strain capable of efficient S2−-oxidizing was isolated from a black-odor river in Beijing. The single strain was identified as Stenotrophomonas through the physiology and biochemical characteristics as well as the 16S rRNA sequencing experiment. This strain was named as Stenotrophomonas sp.sp3 (strain sp3). The experimental results showed that for the strain sp3 growth and S2− oxidization, the optimal conditions were as follows: 25 °C of temperature, initial pH 7, 2.5 g/L of initial glucose concentration and 1.00 g/L of initial cell concentration. It was found that there were 31 kinds of sulfur oxidation-related genes in the strain sp3 through the whole genomic analysis. The results of the transcriptome analysis suggested that the main metabolic pathway of S2− to SO42− was the paracoccus sulfur oxidation process. The bioconversion processes of S2− to S0, S2− to SO32−, S2O32− to S0 and SO32−, and SO32− to SO42− were controlled by hdrA, cysIJ, tst and sox gene, respectively.

  • This study found a novel SOB, i.e. Stenotrophomonas sp. sp3, that was capable of sulfur oxidation.

  • It was proved that S2− could be converted into SO42− via the paracoccus sulfur oxidation process.

Graphical Abstract

Graphical Abstract
Graphical Abstract

Recently, the black-odor water problem has become a very urgent issue in China (Song et al. 2017). Black-odor water is defined as a heavily polluted river or lake that presents with black or green colors and simultaneously gives off an unpleasant smell (Cao et al. 2020). Black-odor pollution not only led to a serious imbalance of the water eco-environment but also has a negative impact on the surrounding residential environment (Zhang et al. 2019). Previous research indicated that sulfide (S2−) is the key blacking pollutant because S2− can react with some metal ions (such as Fe2+, Mn2+, Cu2+) and generate metal sulfides. Metal sulfides are suspended in overlaying water and cause rivers to become black (Song et al. 2017). Oxidizing S2− into SO42− was proved as effective processes to alleviate, even eliminate water blacking (Gągol et al. 2019). This process is mainly performed by sulfur-oxidizing bacteria (SOB) in water and sediment. However, the rate of S2−-oxidizing is very slow under the action of native SOB in the water body, especially in black-odor water (Cai et al. 2019). To improve S2−-oxidizing efficiency, one of the most promising and feasible approaches is to add the SOB into the water body, which can obviously accelerate the bioconversion of S2− to SO42−.

SOB has been discovered worldwide. Many strains have been isolated and characterized, and their application in water pollution treatment have been reported. A bioreactor based on SOB application was used to detect the heavy metals of wastewater (Eom et al. 2019). Several technologies using SOB as the biofilm in a moving bed reactor have been reported. For example, SOB biofilm could remove S2O32− and NO3 in the wastewater (Khanongnuch et al. 2019). SOB biofilm is also used to remove hydrogen sulfide which is the by-product of the anaerobic digestion process of organic wastewater (Lestari et al. 2016). However, there are few studies applying and evaluating SOB in the black-odor water treatment. It was found that the optimum temperature and pH of each kind of SOB are of great difference (Pokorna & Zabranska 2015). These differences indicated that there might be different metabolic pathways among different SOB (Ghosh & Dam 2009).

This study aimed to find a SOB that has the ability of oxidizing S2− into SO42−, and attempt to explore its S2−-oxidizing pathway. Firstly, a single strain with S2−-oxidizing ability was isolated from a black-odor river located in Beijing of China, and this strain was identified by the physiology and biochemical characteristics as well as the 16S rRNA sequence. Secondly, the optimal temperature, pH, nutrient condition and initial cell concentration for the growth and S2−-oxidizing of the isolated strain were investigated, respectively. Subsequently, the growth curve and S2−-oxidizing curve of this isolated strain were then analyzed, and S2−-oxidizing process was also investigated by detecting each inorganic sulfur compound in the whole process. Finally, S2−-oxidizing metabolic pathway of this strain was explored using both of genome and transcriptome analysis.

Source of the isolated strain

A single strain was isolated from the mixture of sludge and water that were obtained from the Dongsha river (a heavily polluted black-odor river) located in Beijing, China. The water was collected from surface layer water of the Dongsha river. The sludge was collected from a depth of 0.5–1.0 m underwater using a sediment sampler. All samples were collected from the Dongsha river at a temperature of 25 °C in September. There were some cyanobacteria floating on the surface of the black-odor water body, no fish, and the water body was stagnant. The mean values of S2−, TP, NH3-N, COD and DO in the water samples were 11.7, 1.3, 3.6, 47 and 2.0 mg/L.

Culture medium

In order to enrich the initial culture, the composition of enrichment medium was as follows: 0.162 g/L Na2S·9H2O, 0.1 g/L KNO3, 0.05 g/L K2HPO4, 0.05 g/L NaCl, 0.05 g/L MgSO4·7H2O, 0.001 g/L FeSO4, 2 g/L soluble starch and 20 g/L agar. In order to screen the strain, the isolation medium was prepared, and the following composition was used: 0.162 g/L Na2S·9H2O, 0.05 g/L NaCl, 0.1 g/L KNO3, 0.05 g/L MgSO4·7H2O, 0.002 g/L FeSO4·7H2O, 0.05 g/L K2HPO4, 20 g/L glucose, 10 g/L peptone, 5 g/L yeast extract and 20 g/L agar. The liquid growth medium was prepared to incubate the isolated strain, and its composition was as follows: 20 g/L glucose, 10 g/L peptone and 10 g/L yeast extract. The pH values of culture mediums including the enrichment, isolation and liquid growth medium were all adjusted to 7.0 by 1 M HCl or 1 M NaOH. Sterilization was subsequently performed by autoclaving at 121 °C for 20 min.

Artificial S2−-containing wastewater

The composition of artificial S2−-containing wastewater was as follows: 2.50 g/L glucose, 0.40 g/L K2HPO4, 1.00 g/L NH4Cl and 0.162 g/L Na2S·9H2O (Zhuang et al. 2017). The pH value was adjusted to 7.0 by 1 M HCl or 1 M NaOH. Sterilization of the artificial wastewater was then carried out at 121 °C for 20 min.

Enrichment and isolation of single strain

The suspension of the mixture sample of sludge and water was performed by adding 5 mL of the sample into 500 mL asepsis NaCl solution with mass concentration of 5%. A small drop of the suspension was spread on the enrichment medium and incubated at 25 °C for 2–3 days. Then the colonies on the enrichment medium were inoculated on the isolation medium and incubated at 25 °C for 2–3 days. The strain was purified by repeating single colony re-isolation on the isolation medium.

Preparation of microbial inoculum

The isolated strain was incubated at 25 °C for 48 hr to obtain the microbial inoculum. After 48 hr of cultivation, the cell concentration of the microbial inoculum reached 2.5 × 108 cfu/mL. More microbial inoculum was obtained by transferring the original microbial inoculum to other 250 mL Erlenmeyer flask with fresh 100 mL liquid growth medium at a volume percent of 5%, and was incubated at 25 °C on a rotary shaker at 120 rpm for 48 hr.

Experiment of different S2−-oxidizing conditions

Effects of temperature, initial pH, glucose concentration and initial cell concentration on the growth and S2−-oxidizing of the strain were investigated using the artificial S2−-containing wastewater. For the temperature experiment, the microbial inoculum was transferred to a 500 mL Erlenmeyer flask with 200 mL artificial wastewater at a volume percent of 5% and was incubated at different temperatures (5, 15, 20, 25, 30 and 35 °C) on a rotary shaker at 120 rpm for 48 hr. For the initial pH experiment, the same experimental conditions were adopted except that the initial pHs of the artificial wastewater were respectively adjusted to 4, 5, 6, 7 and 8, and the temperature was kept at 25 °C. The glucose at different concentrations (0.5, 1.0, 2.5, 5.0 and 10 g/L) and initial cell of microbial inoculum at different concentrations (0.01, 0.10, 1.00, 2.00 and 5.00 g/L) were designed, and the experiment was conducted, respectively. Both the strain growth and the S2− oxidation rate were measured after bio-reaction.

Experiment of S2−-oxidizing process

The experiment of the strain growth curve and S2−-oxidizing curve was performed by transferring the microbial inoculum to a 500 mL erlenmeyer flask with 200 mL artificial wastewater at a volume percent of 5%, and was incubated at 25 °C and 120 rpm for 72 hr. The strain growth and the concentration of S2− were measured regularly.

The experiment of S2−-oxidizing process was carried out in a biochemical reactor with 5 L artificial wastewater at the cell concentration of 1 g/L, and a biochemical reactor without the microbial inoculum was set as a blank control. The incubation was performed at 25 °C and 120 rpm for 60 hr and the concentrations of S2−, S0, S2O32−, S4O62−, SO32− and SO42− were measured regularly.

Identification of strain

DNA extraction and 16S rRNA sequencing

The total DNA of the strain was extracted using an ezup column type bacterial genomic DNA extraction kit SK8255 (Sangon Biotech, Shanghai, China). The extraction processes and steps were followed the manufacturer's instructions of this kit. The concentration of total DNA was measured using a microfluorometer (TBS-380, Turner BioSystems, USA); while the purity of total DNA was analyzed by a UV microspectrophotometer (NanoDrop2000, Thermo Fisher, USA). The experiment of 16S rRNA sequencing was performed by Sangon Biotech (Shanghai, China). For PCR, primers specific for 16S rRNA 27F (AGTTTGATCMTGGCTCAG) and 1492R (GGTTACCTTGTTACGACTT) were used. The 16S rRNA of the strain was compared with other sequences in GenBank using the blast program of national center for biotechnology information (NCBI). Alignment with a representative set of related 16S rRNA gene sequences was carried out with the clustal-w program implemented in the phylogenetic analysis package mega (version 7.0).

Morphological, physiology and biochemical tests

For morphological characteristics (colony characteristics, shape, motility and gram's reaction), the pure strain was cultured in the same media used for isolation at 25 °C for 2 d. The physiology and biochemical tests for strain identification were carried out following the standard method described by Dong & Cai (2002).

Genome sequencing and analysis

DNA extraction and sequencing

Genomic DNA was isolated using E.Z.N.A.® DNA kit (Omega Bio-Tek, USA). The isolated DNA was fragmented using a high performance sample processing system (Covaris M220, Thermo Fisher Scientific, USA). The PE library was constructed using a TruSeq™ DNA sample prep kit (Illumina, USA). For bridge PCR, the hiseq PE cluster kit v4-cbot (Illumina, USA) was used. The genome was sequenced using the Illumina hiseq program.

Assembly and annotation of genomic sequence

The assembly of quality filtered reads was performed using IDBA-UD program. Automated annotation was performed using Glimmer 3.02 program. The annotated genes were compared with database Nr, Genes, String and Go.

RNA extraction and sequencing

The samples for RNA extraction were respectively collected in the experiment of S2−-oxidizing process at 1, 18, 30 and 60 hr. Total RNA from the collected samples was extracted using a trizol reagent (Invitrogen) kit (Thermo Fisher Scientific, USA). RNA purification was performed with deoxyribonuclease I (Thermo Fisher Scientific, USA) and ribo-zeroTM rRNA removal kit (Thermo Fisher Scientific, USA). The mRNA was extracted using oligo (dT) 18 magnetic substance (Thermo Fisher Scientific, USA). The cDNA library was prepared using reverse transcription PCR method and the first-strand cDNA was synthesized using random hexamers and fragmented mRNA. For successful sequencing, the quality and size of the cDNA libraries were checked by an Agilent 2100 system. The cDNA library was sequenced using Illumina hiseq program.

Analytical method

The cell concentration during the growth of the strain was evaluated at 600 nm (OD600). According to the methylene blue spectrophotometric method, S2− was measured at 665 nm by a spectrophotometer (Chinese National Environmental Protection Agency 1996); while S0 was examined spectrophotometrically at 350 nm using the previous method (Miura et al. 1995). The concentrations of S2O32−, SO32− and SO42− were measured using an ion chromatograph (CIC-D120, Qingdao Shenghan Chromatography Technology, China). The concentration of S4O62− was determined using a high performance liquid chromatograph (LC-10AD, Shimadzu, Shanghai, China).

Identification of the isolated strain

The physiology and biochemical characteristics of the isolated strain are shown in Table 1. The isolated strain formed round-shaped opaque yellow colony (0.5–1 mm in diameter) with ammonia smell; the edge of the colony was smooth and partial irregular. The center of the colony was bulge; the cell was motile rods and gram-stain negative. The phylogenetic tree of the isolated strain is shown in Figure 1. The results of 16S rRNA gene identification revealed that the strain was 99% homologous with genus Stenotrophomonas. According to the results of morphological observation, physiology and biochemical characteristics and 16S rRNA analysis, the isolated strain was identified as Stenotrophomonas sp. and named as Stenotrophomonas sp.sp3 (strain sp3). The sequence of the strain sp3 was uploaded to NCBI and the GenBank accession number was MH181796.

Table 1

Physiology and biochemical characteristics of the isolated strain

ItemsResult
Gram stain − 
Lysine decarboxylase test 
Maltase test 
Nitrate reductase enzymes test 
Esculin hydrolysis test 
Gelatin liquefaction test 
ItemsResult
Gram stain − 
Lysine decarboxylase test 
Maltase test 
Nitrate reductase enzymes test 
Esculin hydrolysis test 
Gelatin liquefaction test 
Figure 1

Phylogenetic tree of the isolated strain.

Figure 1

Phylogenetic tree of the isolated strain.

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S2−-oxidizing characteristics of the isolated strain

The effects of temperature, initial pH, initial glucose concentration and initial cell concentration on the growth of the strain sp3 and the S2−-oxidizing rate were analyzed, as shown in Figure 2.

Figure 2

Effects of (a) temperature, (b) initial pH, (c) initial glucose concentration and (d) initial cell concentration broth on the growth of the isolated strain and S2−-oxidizing rate.

Figure 2

Effects of (a) temperature, (b) initial pH, (c) initial glucose concentration and (d) initial cell concentration broth on the growth of the isolated strain and S2−-oxidizing rate.

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As shown in Figure 2(a), S2−-oxidizing rate increased with the increase of incubation temperature from 5 °C to 25 °C. The S2−-oxidizing rate by the strain sp3 under 5 °C was only 21% and the strain sp3 showed the maximum S2—oxidizing rate under 25 °C. The maximum S2—oxidizing rate was 85.2%. However, the S2—oxidizing rate decreased with the increase of incubation temperature from 25 °C to 35 °C, indicated that 25 °C was the most optimum incubation temperature of S2− oxidation. The growth curve of the strain sp3 at various temperatures showed the same tendency: increased with the increase of temperature from 5 °C to 25 °C and decreased with the increase of temperature from 5 °C to 25 °C. Thus, 25 °C was the optimal temperature for strain growth and S2−-oxidizing.

The strain growth and S2−-oxidizing varied significantly with the change of initial pH, as shown in Figure 2(b). It was found that the S2−-oxidizing rate increased with the increase of pH from 4 to 7, and then decreased with the increase of pH from 7 to 8. The maximum S2−-oxidizing rate was achieved at the initial pH of 7, and it reached 85% after 48 hr of bio-reaction. Variation of the growth of the strain sp3 at various initial pH was similar to S2−-oxidizing, indicated the initial pH 7 was the optimal for strain growth and S2−-oxidizing.

The effect of initial glucose concentration on the strain growth and S2−-oxidizing was shown in Figure 2(c). It was found that the S2−-oxidizing rate increased with the increase of initial glucose concentration from 0.5 to 2.5 g/L and decreased with the increase of initial glucose concentration from 2.5 to 10.0 g/L. The strain sp3 showed the maximum S2−-oxidizing activity at initial glucose concentration of 2.5 g/L and the maximum S2−-oxidizing rate was 83%. The strain growth curve showed that the growth of the strain sp3 increased with the increase of initial glucose concentration from 0.5 to 2.5 g/L, and then increased slowly when initial glucose concentration increased from 2.5 to 10.0 g/L. The above results indicated that glucose was a kind of efficient carbon resource for the strain sp3 and was able to accelerate strain growth and S2−-oxidizing, when the initial glucose concentration increased from 0.5 to 2.5 g/L. It was showed that 2.5 g/L was the optimal initial glucose concentration for strain growth and S2−-oxidizing.

As shown in Figure 2(d), variation of strain growth and S2−-oxidizing were different with the increase of initial cell concentration of the microbial inoculum. It was found that the S2−-oxidizing rate increased with the increase of initial cell concentration from 0.01 to 1.00 g/L, and then maintained stability. The strain sp3 showed the maximum S2−-oxidizing when the initial cell concentration was 1.00 g/L, and it reached 81.3%. The strain growth curve showed that the growth of the strain sp3 kept increasing with the increase of initial cell concentration of the microbial inoculum from 0.01 to 5.00 g/L. This result indicated that increasing the initial cell concentration of the microbial inoculum was efficient for S2− oxidization. Thus, 1.00 g/L was the optimal initial cell concentration of the microbial inoculum for S2−-oxidizing efficiency.

Based on the above results, the optimal conditions including temperature, initial pH, initial glucose concentration and initial cell concentration were 25 °C, 7, 2.5 g/L and 1.00 g/L, respectively.

Growth curve and S2−-oxidizing curve of strain sp3

Growth curve and S2−-oxidizing curve of the strain sp3 were shown in Figure 3. In the first of 16 hr, the OD600 value of the strain sp3 increased slowly, indicated the first 16 hr was the lag phase of the strain growth. During the lad phase of the strain growth, the concentration of S2− decreased significantly, showing that the lad phase was the main phase for S2− oxidation. After 16 hr, the OD600 value of the strain increased significantly until the 35 hr, indicating that the logarithmic phase of the strain growth was appeared in the range of 16 to 35 hr. During the logarithmic phase, the concentration of S2− kept decreasing and reached the minimum value at 35 hr. The minimum value of S2− concentration was 2.9 mg/L and the S2− oxidation rate reached 86.6%. The OD600 value of the strain maintained stability from 35 to 60 hr indicated that the stationary phase of the strain growth was in the range of 35 to 60 hr. In the last 12 hr, the OD600 value of the strain sp3 decreased rapidly, indicated this period was the decline phase of the strain growth. During the stationary phase and the decline phase of the strain growth, the concentration of S2− maintained stability.

Figure 3

Growth curve and S2−-oxidizing curve of the isolated strain.

Figure 3

Growth curve and S2−-oxidizing curve of the isolated strain.

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S2−-oxidizing process of strain sp3

Each inorganic sulfur compound including S2−, S0, S2O32−, S4O62−, SO32− and SO42− in the whole process of S2− oxidization were detected, and the results are shown in Figure 4. Four inorganic sulfur compounds (S0, S2O32−, SO32− and SO42−) were formed in the S2−-oxidizing process and their concentrations varied significantly at different phase of the S2−-oxidizing process. As shown in Figure 4(a), as the main electron donor in the S2−-oxidizing process, the concentration of S2− decreased significantly in the first 10 hr. Then the decreasing rate of S2− concentration slowed in the range of 10 to 30 hr. At 30 hr, the concentration of S2− reached the minimum value and maintained stability. The minimum value of S2− concentration was 3.0 mg/L and the S2− oxidation rate reached 86.1%. Variation of the concentrations of S0 and SO32− showed a wave-type tendency during the whole S2−-oxidizing process, indicated the dynamic synthesis and decomposition of the two compounds in the S2−-oxidizing process. The maximum value of S0 concentration was 1.75 mg/L at 18 hr, and the maximum value of SO32− concentration was 1.78 mg/L at 35 hr. The concentration of S2O32− increased in the first 8 hr and then turned to decrease, indicating that the synthesis rate of S2O32− was higher than the decomposition rate in the first 8 hr and became lower than the decomposition rate in the period of 8 to 60 hr. The maximum value of S2O32− concentration was 11.23 mg/L. The concentration of SO42− kept increasing in the S2−-oxidizing process and reached the maximum value at 60 hr, and its maximum value was 9.2 mg/L. The concentration of S4O62− was not detected in the whole process, indicating that this compound was not produced during S2− oxidization. As shown in Figure 4(b), the concentration curves of the inorganic sulfur compounds were of great difference in the blank control. The concentration of S2− decreased at a slow rate, and the concentrations of S0, SO32− and S4O62− were not detected and the concentrations of S2O32− and SO42− were low. These results indicated that the oxygen in the air has little effect on the S2−-oxidizing process in the artificial water.

Figure 4

Variation of each inorganic sulfur compound concentration: (a) experiment, (b) control.

Figure 4

Variation of each inorganic sulfur compound concentration: (a) experiment, (b) control.

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The above results show that the addition of the strain sp3 accelerated the S2−-oxidizing process. S2− oxidation was a complex process involving the production and bioconversion of S0, S2O32−, and SO32−, and finally the unstable S2− was oxidized to stable SO42−. Previous research also indicated that the addition of SOB can accelerate the oxidization process of S2− to SO42− (Zhuang et al. 2017).

Analysis on S2−-oxidizing metabolic pathway of strain sp3

Some previous research on the metabolic pathway of SOB show that there are two major pathways for oxidation of sulfur compounds including paracoccus sulfur oxidation (PSO) pathway and S4 intermediate (S4I) pathway (Kelly et al. 1997). Part of the oxidation of sulfur compounds exists in both the PSO pathway and S4I pathway, including these bioconversion processes of S2− to S0, S2− to SO32−, S0 to SO32−, S2O32− to S0 and SO32− along with SO32− to SO42−. The process of S2− converted to S0 was controlled by enzyme sulfide quinone oxidoreductase (SQR) or flavocytochrome c (FCC). The enzyme SQR was encoded by the sqr gene and the enzyme FCC was encoded by the fcc gene (Kelly et al. 1997). The process of S2− conversion to SO32− was controlled by enzyme sulfite reductase (SRN, the reduced form of nicotinamide adenine dinucleotide) that was encoded by the cysIJ gene (Tan et al. 2013). The process of S0 converted to SO32− was controlled by the grx gene and the enzyme hetero disulfide reductases (HDR) that was encoded by the hdrBC gene (Quatrini et al. 2009). The process of S2O32− converted to S0 and SO32− was controlled by the enzyme thiosulfate sulfurtransferase (TST), which was encoded by the tst gene (Rohwerder & Sand 2007). The process of SO32− converted to SO42− could occur in two different ways: direct and indirect oxidation. The direct oxidation process of SO32− converted to SO42− was controlled by the enzyme sulfite oxidase (SO) that was encoded by the sox gene (Toghrol & Southerland 1983; Bruser et al. 2000). The indirect oxidation process was controlled through the enzyme phosphoadenosine phosphosulfate reductase (PAPS), which was encoded by the paps gene (Bruser et al. 2000). Apart from the common part of the two pathways, some oxidation of the sulfur compounds including the process of S2O32− converted to S4O62− and the process of S4O62− converted to SO42−, which doesn't exist in the PSO pathway but in the S4I pathway (Rohwerder & Sand 2007; Quatrini et al. 2009; Sakurai et al. 2010). The process of S2O32− converted to S4O62− was controlled by the enzyme thiosulfate quinone oxidoreductase (TQO) that was encoded by the soxVW gene (Holden et al. 2004; Moller & Hederstedt 2008). The process of S4O62− conversion to SO42− was controlled by the enzyme tetrathionate hydrolase (TTH), which was encoded by the tetH gene (Rohwerder & Sand 2007; Sakurai et al. 2010). Thus, it could be inferred that there was no existence of the tetH gene in the PSO pathway. Moreover, S4O62− would not be detected in the whole of the S2−-oxidizing process for the PSO pathway.

The whole genome sequence of strain sp3 was aligned to the public database Kyoto encyclopedia of genes and genomes (KEGG) and NCBI. The results indicated that 31 kinds of sulfur oxidation-related genes were detected in the strain sp3 (Table 2). Some key genes belonging to the major pathways for oxidation of sulfur compounds were detected in the strain sp3, including the cysIJ, grx, tst and sox genes. However, some key genes including the sqr, fcc, hdrBC, paps and tetH genes were not detected in strain sp3. Although the sqr gene was not detected in strain sp3, the hdrA gene was found in strain sp3, which was proved to be able to encode the enzyme SQR (Imhoff & Thiel 2010). The results that both the tetH gene and S4O62− were not detected in strain sp3 suggested that the S4I pathway was not the metabolic pathway of strain sp3 and the PSO pathway might be the only S2−-oxidizing metabolic pathway.

Table 2

Sulfur oxidation related genes of Stenotrophomonas sp.sp3 genome

GeneGene annotationReference
sufES Cysteine desulfurase Albrecht et al. (2011)  
cybCytochrome b561 Chen et al. (2012)  
coxA/B/C/D Cytochrome c oxidase Marks et al. (2010)  
nqor NAD(P)H-quinone oxidoreductase Eickelmann et al. (1994)  
nuo NADH-ubiquinone oxidoreductase Yang & Hekimi (2010)  
ato Cytochrome c oxidase subunit III Methé et al. (2003)  
his Phosphoribosyl-AMP cyclohydrolase Methé et al. (2003)  
stp Sulfate ABC transporter permease Rohwerder & Sand (2007)  
hdrPyridine nucleotide-disulfide oxidoreductase Hedderich et al. (1994)  
psr4Fe-4S cluster-binding Cai et al. (2012)  
fisTranscriptional regulator Hadizadeh et al. (2016)  
cysIJ Sulfite reductase (NADPH) Shigenobu et al. (2000)  
thiSulfur carrier protein ThiS adenylyltransferase Wang et al. (2001)  
St S-transferase Carkaci et al. (2016)  
sbp Sulfate transporter Sirko et al. (1995)  
Dsb/soxThiol:disulfide interchange protein Holden et al. (2004)  
trxThioredoxin reductase Negri et al. (2010)  
trxAC/soxThioredoxin Moller & Hederstedt (2008)  
tst Thiosulfate sulfurtransferase Rohwerder & Sand (2007)  
grx Glutaredoxin Belda et al. (2016)  
gst Glutathione S-transferase Romine (2011)  
gsr Glutathione reductase Bowler et al. (2008)  
gshp Glutathione peroxidase Romine (2011)  
gsh-dtr Glutathione-dependent thiol reductase Romine (2011)  
cydAB Cytochrome d ubiquinol oxidase Holden et al. (2004)  
cyoABCD Cytochrome o ubiquinol oxidase Frericks et al. (2006)  
soxBI Cytochrome b6 Eisen et al. (2002)  
soxBII Thioesterase Eisen et al. (2002)  
soxMolybdenum cofactor Eisen et al. (2002)  
soxFAD Deckert et al. (1998)  
soxCytochrome c Eisen et al. (2002)  
GeneGene annotationReference
sufES Cysteine desulfurase Albrecht et al. (2011)  
cybCytochrome b561 Chen et al. (2012)  
coxA/B/C/D Cytochrome c oxidase Marks et al. (2010)  
nqor NAD(P)H-quinone oxidoreductase Eickelmann et al. (1994)  
nuo NADH-ubiquinone oxidoreductase Yang & Hekimi (2010)  
ato Cytochrome c oxidase subunit III Methé et al. (2003)  
his Phosphoribosyl-AMP cyclohydrolase Methé et al. (2003)  
stp Sulfate ABC transporter permease Rohwerder & Sand (2007)  
hdrPyridine nucleotide-disulfide oxidoreductase Hedderich et al. (1994)  
psr4Fe-4S cluster-binding Cai et al. (2012)  
fisTranscriptional regulator Hadizadeh et al. (2016)  
cysIJ Sulfite reductase (NADPH) Shigenobu et al. (2000)  
thiSulfur carrier protein ThiS adenylyltransferase Wang et al. (2001)  
St S-transferase Carkaci et al. (2016)  
sbp Sulfate transporter Sirko et al. (1995)  
Dsb/soxThiol:disulfide interchange protein Holden et al. (2004)  
trxThioredoxin reductase Negri et al. (2010)  
trxAC/soxThioredoxin Moller & Hederstedt (2008)  
tst Thiosulfate sulfurtransferase Rohwerder & Sand (2007)  
grx Glutaredoxin Belda et al. (2016)  
gst Glutathione S-transferase Romine (2011)  
gsr Glutathione reductase Bowler et al. (2008)  
gshp Glutathione peroxidase Romine (2011)  
gsh-dtr Glutathione-dependent thiol reductase Romine (2011)  
cydAB Cytochrome d ubiquinol oxidase Holden et al. (2004)  
cyoABCD Cytochrome o ubiquinol oxidase Frericks et al. (2006)  
soxBI Cytochrome b6 Eisen et al. (2002)  
soxBII Thioesterase Eisen et al. (2002)  
soxMolybdenum cofactor Eisen et al. (2002)  
soxFAD Deckert et al. (1998)  
soxCytochrome c Eisen et al. (2002)  

Transcriptome analysis of Stenotrophomonas sp. sp3 was then conducted, and the result indicated that 4,733 protein-encoding genes were detected. Visualization of differences and similarities among these detected protein-encoding genes was performed by cluster analysis. The cluster heatmap of differential expression of the 4,733 protein-encoding genes is shown in Figure 5. The gene expression level was of great difference at the S2−-oxidizing process of 1, 18 and 30 hours and subsequently the similarities existed in the samples collected at 30 and 60 hours. This indicated that the microbial metabolisms of strain sp3 appeared with significant difference before the bio-reaction of 30 hours, and then maintained stability in the rest of the bio-reaction. This resulted in the obvious variation of the concentration of each inorganic sulfur compound during the first 30 hours of the bio-reaction (Figure 4).

Figure 5

Cluster heatmap of differential expression genes (red line represents high expression level genes; blue line represents low expression level genes; each column represents the sample collected at 1 hr, 18 hr, 30 hr and 60 hr of the bio-reaction respectively). Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/ws.2022.011.

Figure 5

Cluster heatmap of differential expression genes (red line represents high expression level genes; blue line represents low expression level genes; each column represents the sample collected at 1 hr, 18 hr, 30 hr and 60 hr of the bio-reaction respectively). Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/ws.2022.011.

Close modal

The results of differential gene expression analysis are shown in Figure 6. As shown in Figure 6(a), the number of up genes in the range of 1–18 hr was 751, and the number of down genes was 745. With the further bio-reaction up to 30 hours, the number of up genes arrived at 820, while down genes reached 784 (Figure 6(b)). As for the S2−-oxidization process in the range of 30 to 60 hours, the number of up genes decreased to 44, while down genes also reduced to 188 (Figure 6(c)). Moreover, the differential expression of sulfur oxidation-related genes was significant from 1 to 30 hours, and the rate of S2− oxidation was rapid; but there was no significant differential expression of sulfur oxidation-related genes from 30 to 60 hours, and the concentration of S2− decreased to the lowest value and kept relatively stable (Figure 4). These results suggested that most of the microbial metabolism of strain sp3 happened in the first 30 hours of the bio-reaction. This time range was the main phase for S2−-oxidizing, too (Figure 3).

Figure 6

Analysis of differential gene expression: (a) Volcano plot of 1 ∼ 18 hr, (b) Volcano plot of 18 ∼ 30 hr, (c) Volcano plot of 30 ∼ 60 hr. Red dot represents up genes; blue dot represents down genes; gray dot represents none-differentially expressed genes. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/ws.2022.011.

Figure 6

Analysis of differential gene expression: (a) Volcano plot of 1 ∼ 18 hr, (b) Volcano plot of 18 ∼ 30 hr, (c) Volcano plot of 30 ∼ 60 hr. Red dot represents up genes; blue dot represents down genes; gray dot represents none-differentially expressed genes. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/ws.2022.011.

Close modal

The expression level of sulfur oxidation-related genes detected in strain sp3 was chosen from the cluster heatmap of differential expression genes. The heatmap of sulfur oxidation genes expression level is shown in Figure 7. The expression level of eleven kinds of genes, especially hdrA, cysIJ and cybB genes, increased significantly during the bio-reaction of 1 to 18 hours. The process of S2− converted to S0 was controlled by the hdrA gene through encoding the enzyme SQR and the process of S2− converted to SO32− was controlled by the cysIJ gene through encoding the enzyme SRN (Tan et al. 2013). Figure 4 shows that the concentrations of S0 and SO32− increased in the first 18 hours of the bio-reaction, indicating that the processes of S2− converted to S0 and SO32− were performed in this period. The formation progress of other sulfur compounds could be found and concluded in this way. The electron transportation was controlled by the cybB gene (Chen et al. 2012) and the concentration of the electron donor S2− decreased in the first 18 hours of the bio-reaction. The expression level of nine kinds of genes, especially the tst, sox and sbp genes, increased in the range of 18 to 30 hours. The process of S2O32− conversion to S0 and SO32− was controlled by the tst gene through encoding the enzyme TST (Rohwerder & Sand 2007) and was performed during the process of 18 to 30 hours. The process of SO32− conversion to SO42− was controlled by the sox gene through encoding the enzyme SO (Toghrol & Southerland 1983) and the sbp gene controlled the transportation of SO42− (Sirko et al. 1995). After the bio-reaction of 30 hours, the expression level of most genes maintained stability except that the expression level of some genes like the hdrA and sbp genes decreased significantly, and some genes such as soxX, soxW and soxV became higher.

Figure 7

Heatmap of sulfur oxidation genes expression level.

Figure 7

Heatmap of sulfur oxidation genes expression level.

Close modal

According to the above experimental results, the major metabolic pathway of strain sp3 was the PSO pathway, as shown in Figure 8. Four inorganic sulfur compounds including S0, S2O32−, SO32− and SO42− were formed in the process of S2− oxidization. In the PSO pathway, some S2− were converted to S0 under the action of the enzyme SQR that was encoded by the hdrA gene; while the other part of S2− was converted to SO32−, which was controlled by the cysIJ gene through encoding the enzyme SRN. The process of S0 converted to SO32− was controlled by the grx and hdrBC genes. However, although the grx gene was detected in strain sp3, the hdrBC gene was not detected in strain sp3, suggesting that the process of S0 conversion to SO32− was not available in strain sp3. Meanwhile, some SO32− reacted with S0 spontaneously to form S2O32−, and an other part of SO32− was converted to SO42− in the control of the sox gene through encoding the enzyme SO. S2O32− released S0 and SO32− at the same time through the action of the enzyme TST encoded by the tst gene. The sox gene was detected in strain sp3 while the paps gene was not detected, indicating that the direct oxidation process was the only metabolic pathway of SO32− conversion to SO42−.

Figure 8

Major metabolic pathway of S2−-oxidizing in Stenotrophomonas sp.sp3.

Figure 8

Major metabolic pathway of S2−-oxidizing in Stenotrophomonas sp.sp3.

Close modal

The strain sp3 isolated in our study was biologically classified as genus Stenotrophomonas. Stenotrophomonas has various metabolic functions. In the previous studies, Stenotrophomonas was mainly found to have the abilities of antibiotic resistance, organophosphorus degradation, and dichlorodiphenyltrichloroethane degradation (Shen et al. 2010; Dubey & Fulekar 2012; Fang et al. 2018). In our study, strain sp3 was isolated from a typical black-odor water body. The experimental results confirmed that this strain was capable of sulfur oxidation, and S2− could be converted into SO42− via the PSO pathway. Therefore, a novel SOB (i.e. Stenotrophomonas sp.sp3) was found in our study. In the subsequent treatment of black-odor water bodies, three aspects might be selected to proceed: 1) compounding with other organisms that have other sulfur-oxidizing metabolic pathways to improve the treatment efficiency for black-odor water bodies; 2) investigating the removal efficiency of other items (such as TP, NH3-N, COD, etc.) in black-odor water bodies under the action of this compounded microorganism; 3) A solid bacterial agent that consisted of this compounded microorganism would attempt to prepare for treating the black-odor water by direct dosing on the water surface, and there have been similar cases in previous studies (Cao et al. 2020).

For the strain sp3 growth and S2− oxidization, the optimal conditions were as follows: 25 °C of temperature, initial pH 7, 2.5 g/L of initial glucose concentration, and 1.00 g/L of initial cell concentration. After a bio-reaction of 60 hr, S2−-oxidization ratio by strain sp3 arrived at 86.6%. Four kinds of inorganic sulfur compounds including S0, S2O32−, SO32− and SO42− were produced during the S2− oxidization. Combining high-throughput sequencing with transcriptomics analysis, the PSO pathway was the main metabolic process of S2− to SO42−, and the microbial metabolism of S2− oxidization mainly happened in the first 30 hours of the bio-reaction. S2− was efficiently oxidized by the strain sp3, which possessed significant potential for the black-odor water treatment.

This work was supported by the Natural Science Foundation of Beijing, China [Grant No. 8182058] and the Central Level, Scientific Research Institutes for Basic R&D Special Fund Business [2019YSKY003].

All relevant data are included in the paper or its Supplementary Information.

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